2023/08/09 15:35:58 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.8.10 (default, Jun 4 2021, 15:09:15) [GCC 7.5.0] CUDA available: True numpy_random_seed: 1595333044 GPU 0,1: Tesla V100-SXM2-32GB CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0 PyTorch: 1.11.0+cu113 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e) - OpenMP 201511 (a.k.a. OpenMP 4.5) - LAPACK is enabled (usually provided by MKL) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.3 - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86 - CuDNN 8.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, TorchVision: 0.12.0+cu113 OpenCV: 4.8.0 MMEngine: 0.8.4 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: 1595333044 Distributed launcher: pytorch Distributed training: True GPU number: 2 ------------------------------------------------------------ 2023/08/09 15:35:59 - mmengine - INFO - Config: auto_scale_lr = dict(base_batch_size=256) backend_args = dict(backend='local') codec = dict( heatmap_size=( 48, 64, ), input_size=( 192, 256, ), sigma=2, type='UDPHeatmap') custom_hooks = [ dict(type='SyncBuffersHook'), ] data_mode = 'topdown' data_root = '/root/autodl-tmp/data/fld/' dataset_type = 'DeepFashionDataset' default_hooks = dict( checkpoint=dict( interval=10, rule='greater', save_best='AUC', type='CheckpointHook'), logger=dict(interval=10, type='LoggerHook'), param_scheduler=dict(type='ParamSchedulerHook'), sampler_seed=dict(type='DistSamplerSeedHook'), timer=dict(type='IterTimerHook'), visualization=dict(enable=False, type='PoseVisualizationHook')) default_scope = 'mmpose' env_cfg = dict( cudnn_benchmark=False, dist_cfg=dict(backend='nccl'), mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0)) launcher = 'pytorch' load_from = None log_level = 'INFO' log_processor = dict( by_epoch=True, num_digits=6, type='LogProcessor', window_size=50) model = dict( backbone=dict( extra=dict( stage1=dict( block='BOTTLENECK', num_blocks=(4, ), num_branches=1, num_channels=(64, ), num_modules=1), stage2=dict( block='BASIC', num_blocks=( 4, 4, ), num_branches=2, num_channels=( 48, 96, ), num_modules=1), stage3=dict( block='BASIC', num_blocks=( 4, 4, 4, ), num_branches=3, num_channels=( 48, 96, 192, ), num_modules=4), stage4=dict( block='BASIC', num_blocks=( 4, 4, 4, 4, ), num_branches=4, num_channels=( 48, 96, 192, 384, ), num_modules=3)), in_channels=3, init_cfg=dict( checkpoint= 'https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth', type='Pretrained'), type='HRNet'), data_preprocessor=dict( bgr_to_rgb=True, mean=[ 123.675, 116.28, 103.53, ], std=[ 58.395, 57.12, 57.375, ], type='PoseDataPreprocessor'), head=dict( decoder=dict( heatmap_size=( 48, 64, ), input_size=( 192, 256, ), sigma=2, type='MSRAHeatmap'), deconv_out_channels=None, in_channels=48, loss=dict(type='KeypointMSELoss', use_target_weight=True), out_channels=6, type='HeatmapHead'), test_cfg=dict(flip_mode='heatmap', flip_test=True, shift_heatmap=False), type='TopdownPoseEstimator') optim_wrapper = dict( loss_scale='dynamic', optimizer=dict(lr=0.0005, type='Adam'), type='AmpOptimWrapper') param_scheduler = [ dict( begin=0, by_epoch=False, end=500, start_factor=0.001, type='LinearLR'), dict( begin=0, by_epoch=True, end=210, gamma=0.1, milestones=[ 170, 200, ], type='MultiStepLR'), ] resume = True test_cfg = dict() test_dataloader = dict( batch_size=32, dataset=dict( ann_file='annotations/fld_upper_test.json', data_mode='topdown', data_prefix=dict(img='img/'), data_root='/root/autodl-tmp/data/fld/', pipeline=[ dict(type='LoadImage'), dict(type='GetBBoxCenterScale'), dict(input_size=( 192, 256, ), type='TopdownAffine'), dict(type='PackPoseInputs'), ], subset='upper', test_mode=True, type='DeepFashionDataset'), drop_last=False, num_workers=2, persistent_workers=True, sampler=dict(round_up=False, shuffle=False, type='DefaultSampler')) test_evaluator = [ dict(thr=0.2, type='PCKAccuracy'), dict(type='AUC'), dict(type='EPE'), ] test_pipeline = [ dict(type='LoadImage'), dict(type='GetBBoxCenterScale'), dict(input_size=( 192, 256, ), type='TopdownAffine'), dict(type='PackPoseInputs'), ] train_cfg = dict(by_epoch=True, max_epochs=210, val_interval=10) train_dataloader = dict( batch_size=32, dataset=dict( ann_file='annotations/fld_upper_train.json', data_mode='topdown', data_prefix=dict(img='img/'), data_root='/root/autodl-tmp/data/fld/', pipeline=[ dict(type='LoadImage'), dict(type='GetBBoxCenterScale'), dict(direction='horizontal', type='RandomFlip'), dict(type='RandomBBoxTransform'), dict(input_size=( 192, 256, ), type='TopdownAffine'), dict( encoder=dict( heatmap_size=( 48, 64, ), input_size=( 192, 256, ), sigma=2, type='MSRAHeatmap'), type='GenerateTarget'), dict(type='PackPoseInputs'), ], subset='upper', type='DeepFashionDataset'), num_workers=2, persistent_workers=True, sampler=dict(shuffle=True, type='DefaultSampler')) train_pipeline = [ dict(type='LoadImage'), dict(type='GetBBoxCenterScale'), dict(direction='horizontal', type='RandomFlip'), dict(type='RandomHalfBody'), dict(type='RandomBBoxTransform'), dict(input_size=( 192, 256, ), type='TopdownAffine', use_udp=True), dict( encoder=dict( heatmap_size=( 48, 64, ), input_size=( 192, 256, ), sigma=2, type='UDPHeatmap'), type='GenerateTarget'), dict(type='PackPoseInputs'), ] val_cfg = dict() val_dataloader = dict( batch_size=32, dataset=dict( ann_file='annotations/fld_upper_val.json', data_mode='topdown', data_prefix=dict(img='img/'), data_root='/root/autodl-tmp/data/fld/', pipeline=[ dict(type='LoadImage'), dict(type='GetBBoxCenterScale'), dict(input_size=( 192, 256, ), type='TopdownAffine'), dict(type='PackPoseInputs'), ], subset='upper', test_mode=True, type='DeepFashionDataset'), drop_last=False, num_workers=2, persistent_workers=True, sampler=dict(round_up=False, shuffle=False, type='DefaultSampler')) val_evaluator = [ dict(thr=0.2, type='PCKAccuracy'), dict(type='AUC'), dict(type='EPE'), ] val_pipeline = [ dict(type='LoadImage'), dict(type='GetBBoxCenterScale'), dict(input_size=( 192, 256, ), type='TopdownAffine', use_udp=True), dict(type='PackPoseInputs'), ] vis_backends = [ dict(type='LocalVisBackend'), ] visualizer = dict( name='visualizer', type='PoseLocalVisualizer', vis_backends=[ dict(save_dir='/root/tf-logs', type='TensorboardVisBackend'), dict( init_kwargs=dict( name='td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192', project='mmpose-deepfashion'), type='WandbVisBackend'), ]) work_dir = './work_dirs/td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192' 2023/08/09 15:36:10 - mmengine - INFO - Hooks will be executed in the following order: before_run: (VERY_HIGH ) RuntimeInfoHook (BELOW_NORMAL) LoggerHook -------------------- before_train: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (VERY_LOW ) CheckpointHook -------------------- before_train_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (NORMAL ) DistSamplerSeedHook -------------------- before_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook -------------------- after_train_iter: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_train_epoch: (NORMAL ) IterTimerHook (NORMAL ) SyncBuffersHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- before_val: (VERY_HIGH ) RuntimeInfoHook -------------------- before_val_epoch: (NORMAL ) IterTimerHook (NORMAL ) SyncBuffersHook -------------------- before_val_iter: (NORMAL ) IterTimerHook -------------------- after_val_iter: (NORMAL ) IterTimerHook (NORMAL ) PoseVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_val_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook (LOW ) ParamSchedulerHook (VERY_LOW ) CheckpointHook -------------------- after_val: (VERY_HIGH ) RuntimeInfoHook -------------------- after_train: (VERY_HIGH ) RuntimeInfoHook (VERY_LOW ) CheckpointHook -------------------- before_test: (VERY_HIGH ) RuntimeInfoHook -------------------- before_test_epoch: (NORMAL ) IterTimerHook -------------------- before_test_iter: (NORMAL ) IterTimerHook -------------------- after_test_iter: (NORMAL ) IterTimerHook (NORMAL ) PoseVisualizationHook (BELOW_NORMAL) LoggerHook -------------------- after_test_epoch: (VERY_HIGH ) RuntimeInfoHook (NORMAL ) IterTimerHook (BELOW_NORMAL) LoggerHook -------------------- after_test: (VERY_HIGH ) RuntimeInfoHook -------------------- after_run: (BELOW_NORMAL) LoggerHook -------------------- 2023/08/09 15:36:18 - mmengine - WARNING - The prefix is not set in metric class PCKAccuracy. 2023/08/09 15:36:18 - mmengine - WARNING - The prefix is not set in metric class AUC. 2023/08/09 15:36:18 - mmengine - WARNING - The prefix is not set in metric class EPE. 2023/08/09 15:36:19 - mmengine - INFO - load model from: https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth 2023/08/09 15:36:19 - mmengine - INFO - Loads checkpoint by http backend from path: https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth 2023/08/09 15:36:20 - mmengine - WARNING - The model and loaded state dict do not match exactly unexpected key in source state_dict: head.0.0.0.conv1.weight, head.0.0.0.bn1.weight, head.0.0.0.bn1.bias, head.0.0.0.bn1.running_mean, head.0.0.0.bn1.running_var, head.0.0.0.conv2.weight, head.0.0.0.bn2.weight, head.0.0.0.bn2.bias, head.0.0.0.bn2.running_mean, head.0.0.0.bn2.running_var, head.0.0.0.conv3.weight, head.0.0.0.bn3.weight, head.0.0.0.bn3.bias, head.0.0.0.bn3.running_mean, head.0.0.0.bn3.running_var, head.0.0.0.downsample.0.weight, head.0.0.0.downsample.1.weight, head.0.0.0.downsample.1.bias, head.0.0.0.downsample.1.running_mean, head.0.0.0.downsample.1.running_var, head.0.1.0.conv1.weight, head.0.1.0.bn1.weight, head.0.1.0.bn1.bias, head.0.1.0.bn1.running_mean, head.0.1.0.bn1.running_var, head.0.1.0.conv2.weight, head.0.1.0.bn2.weight, head.0.1.0.bn2.bias, head.0.1.0.bn2.running_mean, head.0.1.0.bn2.running_var, head.0.1.0.conv3.weight, head.0.1.0.bn3.weight, head.0.1.0.bn3.bias, head.0.1.0.bn3.running_mean, head.0.1.0.bn3.running_var, head.0.1.0.downsample.0.weight, head.0.1.0.downsample.1.weight, head.0.1.0.downsample.1.bias, head.0.1.0.downsample.1.running_mean, head.0.1.0.downsample.1.running_var, head.0.2.0.conv1.weight, head.0.2.0.bn1.weight, head.0.2.0.bn1.bias, head.0.2.0.bn1.running_mean, head.0.2.0.bn1.running_var, head.0.2.0.conv2.weight, head.0.2.0.bn2.weight, head.0.2.0.bn2.bias, head.0.2.0.bn2.running_mean, head.0.2.0.bn2.running_var, head.0.2.0.conv3.weight, head.0.2.0.bn3.weight, head.0.2.0.bn3.bias, head.0.2.0.bn3.running_mean, head.0.2.0.bn3.running_var, head.0.2.0.downsample.0.weight, head.0.2.0.downsample.1.weight, head.0.2.0.downsample.1.bias, head.0.2.0.downsample.1.running_mean, head.0.2.0.downsample.1.running_var, head.1.0.0.conv1.weight, head.1.0.0.bn1.weight, head.1.0.0.bn1.bias, head.1.0.0.bn1.running_mean, head.1.0.0.bn1.running_var, head.1.0.0.conv2.weight, head.1.0.0.bn2.weight, head.1.0.0.bn2.bias, head.1.0.0.bn2.running_mean, head.1.0.0.bn2.running_var, head.1.0.0.conv3.weight, head.1.0.0.bn3.weight, head.1.0.0.bn3.bias, head.1.0.0.bn3.running_mean, head.1.0.0.bn3.running_var, head.1.0.0.downsample.0.weight, head.1.0.0.downsample.1.weight, head.1.0.0.downsample.1.bias, head.1.0.0.downsample.1.running_mean, head.1.0.0.downsample.1.running_var, head.1.1.0.conv1.weight, head.1.1.0.bn1.weight, head.1.1.0.bn1.bias, head.1.1.0.bn1.running_mean, head.1.1.0.bn1.running_var, head.1.1.0.conv2.weight, head.1.1.0.bn2.weight, head.1.1.0.bn2.bias, head.1.1.0.bn2.running_mean, head.1.1.0.bn2.running_var, head.1.1.0.conv3.weight, head.1.1.0.bn3.weight, head.1.1.0.bn3.bias, head.1.1.0.bn3.running_mean, head.1.1.0.bn3.running_var, head.1.1.0.downsample.0.weight, head.1.1.0.downsample.1.weight, head.1.1.0.downsample.1.bias, head.1.1.0.downsample.1.running_mean, head.1.1.0.downsample.1.running_var, head.2.0.0.conv1.weight, head.2.0.0.bn1.weight, head.2.0.0.bn1.bias, head.2.0.0.bn1.running_mean, head.2.0.0.bn1.running_var, head.2.0.0.conv2.weight, head.2.0.0.bn2.weight, head.2.0.0.bn2.bias, head.2.0.0.bn2.running_mean, head.2.0.0.bn2.running_var, head.2.0.0.conv3.weight, head.2.0.0.bn3.weight, head.2.0.0.bn3.bias, head.2.0.0.bn3.running_mean, head.2.0.0.bn3.running_var, head.2.0.0.downsample.0.weight, head.2.0.0.downsample.1.weight, head.2.0.0.downsample.1.bias, head.2.0.0.downsample.1.running_mean, head.2.0.0.downsample.1.running_var, head.3.0.0.conv1.weight, head.3.0.0.bn1.weight, head.3.0.0.bn1.bias, head.3.0.0.bn1.running_mean, head.3.0.0.bn1.running_var, head.3.0.0.conv2.weight, head.3.0.0.bn2.weight, head.3.0.0.bn2.bias, head.3.0.0.bn2.running_mean, head.3.0.0.bn2.running_var, head.3.0.0.conv3.weight, head.3.0.0.bn3.weight, head.3.0.0.bn3.bias, head.3.0.0.bn3.running_mean, head.3.0.0.bn3.running_var, head.3.0.0.downsample.0.weight, head.3.0.0.downsample.1.weight, head.3.0.0.downsample.1.bias, head.3.0.0.downsample.1.running_mean, head.3.0.0.downsample.1.running_var, fc.weight, fc.bias, stage4.2.fuse_layers.1.0.0.0.weight, stage4.2.fuse_layers.1.0.0.1.weight, stage4.2.fuse_layers.1.0.0.1.bias, stage4.2.fuse_layers.1.0.0.1.running_mean, stage4.2.fuse_layers.1.0.0.1.running_var, stage4.2.fuse_layers.1.2.0.weight, stage4.2.fuse_layers.1.2.1.weight, stage4.2.fuse_layers.1.2.1.bias, stage4.2.fuse_layers.1.2.1.running_mean, stage4.2.fuse_layers.1.2.1.running_var, stage4.2.fuse_layers.1.3.0.weight, stage4.2.fuse_layers.1.3.1.weight, stage4.2.fuse_layers.1.3.1.bias, stage4.2.fuse_layers.1.3.1.running_mean, stage4.2.fuse_layers.1.3.1.running_var, stage4.2.fuse_layers.2.0.0.0.weight, stage4.2.fuse_layers.2.0.0.1.weight, stage4.2.fuse_layers.2.0.0.1.bias, stage4.2.fuse_layers.2.0.0.1.running_mean, stage4.2.fuse_layers.2.0.0.1.running_var, stage4.2.fuse_layers.2.0.1.0.weight, stage4.2.fuse_layers.2.0.1.1.weight, stage4.2.fuse_layers.2.0.1.1.bias, stage4.2.fuse_layers.2.0.1.1.running_mean, stage4.2.fuse_layers.2.0.1.1.running_var, stage4.2.fuse_layers.2.1.0.0.weight, stage4.2.fuse_layers.2.1.0.1.weight, stage4.2.fuse_layers.2.1.0.1.bias, stage4.2.fuse_layers.2.1.0.1.running_mean, stage4.2.fuse_layers.2.1.0.1.running_var, stage4.2.fuse_layers.2.3.0.weight, stage4.2.fuse_layers.2.3.1.weight, stage4.2.fuse_layers.2.3.1.bias, stage4.2.fuse_layers.2.3.1.running_mean, stage4.2.fuse_layers.2.3.1.running_var, stage4.2.fuse_layers.3.0.0.0.weight, stage4.2.fuse_layers.3.0.0.1.weight, stage4.2.fuse_layers.3.0.0.1.bias, stage4.2.fuse_layers.3.0.0.1.running_mean, stage4.2.fuse_layers.3.0.0.1.running_var, stage4.2.fuse_layers.3.0.1.0.weight, stage4.2.fuse_layers.3.0.1.1.weight, stage4.2.fuse_layers.3.0.1.1.bias, stage4.2.fuse_layers.3.0.1.1.running_mean, stage4.2.fuse_layers.3.0.1.1.running_var, stage4.2.fuse_layers.3.0.2.0.weight, stage4.2.fuse_layers.3.0.2.1.weight, stage4.2.fuse_layers.3.0.2.1.bias, stage4.2.fuse_layers.3.0.2.1.running_mean, stage4.2.fuse_layers.3.0.2.1.running_var, stage4.2.fuse_layers.3.1.0.0.weight, stage4.2.fuse_layers.3.1.0.1.weight, stage4.2.fuse_layers.3.1.0.1.bias, stage4.2.fuse_layers.3.1.0.1.running_mean, stage4.2.fuse_layers.3.1.0.1.running_var, stage4.2.fuse_layers.3.1.1.0.weight, stage4.2.fuse_layers.3.1.1.1.weight, stage4.2.fuse_layers.3.1.1.1.bias, stage4.2.fuse_layers.3.1.1.1.running_mean, stage4.2.fuse_layers.3.1.1.1.running_var, stage4.2.fuse_layers.3.2.0.0.weight, stage4.2.fuse_layers.3.2.0.1.weight, stage4.2.fuse_layers.3.2.0.1.bias, stage4.2.fuse_layers.3.2.0.1.running_mean, stage4.2.fuse_layers.3.2.0.1.running_var Name of parameter - Initialization information backbone.conv1.weight - torch.Size([64, 3, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.bn1.weight - torch.Size([64]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.bn1.bias - torch.Size([64]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.bn2.weight - torch.Size([64]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.bn2.bias - torch.Size([64]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.layer1.0.conv1.weight - torch.Size([64, 64, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.layer1.0.bn1.weight - torch.Size([64]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.layer1.0.bn1.bias - torch.Size([64]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.layer1.0.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.layer1.0.bn2.weight - torch.Size([64]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.layer1.0.bn2.bias - torch.Size([64]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.layer1.0.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.layer1.0.bn3.weight - torch.Size([256]): PretrainedInit: 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from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.0.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.1.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.1.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.1.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.1.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.1.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.1.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.2.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.2.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.2.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.2.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.2.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.2.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.3.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.3.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.3.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.3.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.3.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.0.3.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.0.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.0.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.0.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.0.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.0.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.0.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.1.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.1.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.1.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.1.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.1.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.1.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.2.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.2.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.2.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.2.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.2.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.2.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.3.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.3.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.3.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.3.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.3.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.branches.1.3.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.fuse_layers.0.1.0.weight - torch.Size([48, 96, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.fuse_layers.0.1.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.fuse_layers.0.1.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.fuse_layers.1.0.0.0.weight - torch.Size([96, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.fuse_layers.1.0.0.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage2.0.fuse_layers.1.0.0.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.transition2.2.0.0.weight - torch.Size([192, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.transition2.2.0.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.transition2.2.0.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.0.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.0.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.0.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.0.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.0.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.0.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.1.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.1.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.1.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.1.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.1.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.1.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.2.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.2.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.2.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.2.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.2.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.0.2.bn2.bias - torch.Size([48]): PretrainedInit: 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PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.0.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.0.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.0.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.0.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.0.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.0.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.1.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.1.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.1.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.1.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.1.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.1.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.2.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.2.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.2.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.2.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.2.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.2.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.3.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.3.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.3.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.3.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.1.3.bn2.weight - torch.Size([96]): PretrainedInit: 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PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.0.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.1.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.1.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.1.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.1.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.1.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.1.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.2.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.2.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.2.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.2.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.2.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.2.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.3.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.3.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.3.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.3.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.3.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.branches.2.3.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.0.1.0.weight - torch.Size([48, 96, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.0.1.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.0.1.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.0.2.0.weight - torch.Size([48, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.0.2.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.0.2.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.1.0.0.0.weight - torch.Size([96, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.1.0.0.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.1.0.0.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.1.2.0.weight - torch.Size([96, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.1.2.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.1.2.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.2.0.0.0.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.2.0.0.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.2.0.0.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.2.0.1.0.weight - torch.Size([192, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.2.0.1.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.2.0.1.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.2.1.0.0.weight - torch.Size([192, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.2.1.0.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.0.fuse_layers.2.1.0.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.0.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.0.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.0.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.0.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.0.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.0.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.1.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.1.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.1.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.1.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.1.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.1.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.2.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.2.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.2.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.2.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.2.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.2.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.3.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.3.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.3.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.3.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.3.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.0.3.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.0.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.0.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.0.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.0.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.0.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.0.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.1.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.1.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.1.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.1.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.1.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.1.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.2.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.2.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.2.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.2.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.2.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.2.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.3.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.3.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.3.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.3.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.3.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.1.3.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.0.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.0.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.0.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.0.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.0.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.0.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.1.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.1.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.1.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.1.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.1.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.1.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.2.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.2.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.2.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.2.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.2.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.2.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.3.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.3.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.3.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.3.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.3.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.branches.2.3.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.0.1.0.weight - torch.Size([48, 96, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.0.1.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.0.1.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.0.2.0.weight - torch.Size([48, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.0.2.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.0.2.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.1.0.0.0.weight - torch.Size([96, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.1.0.0.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.1.0.0.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.1.2.0.weight - torch.Size([96, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.1.2.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.1.2.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.2.0.0.0.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.2.0.0.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.2.0.0.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.2.0.1.0.weight - torch.Size([192, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.2.0.1.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.2.0.1.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.2.1.0.0.weight - torch.Size([192, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.2.1.0.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.1.fuse_layers.2.1.0.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.0.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.0.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.0.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.0.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.0.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.0.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.1.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.1.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.1.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.1.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.1.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.1.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.2.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.2.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.2.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.2.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.2.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.2.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.3.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.3.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.3.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.3.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.3.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.0.3.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.0.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.0.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.0.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.0.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.0.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.0.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.1.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.1.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.1.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.1.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.1.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.1.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.2.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.2.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.2.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.2.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.2.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.2.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.3.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.3.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.3.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.3.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.3.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.1.3.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.0.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.0.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.0.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.0.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.0.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.0.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.1.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.1.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.1.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.1.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.1.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.1.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.2.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.2.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.2.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.2.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.2.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.2.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.3.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.3.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.3.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.3.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.3.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.branches.2.3.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.0.1.0.weight - torch.Size([48, 96, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.0.1.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.0.1.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.0.2.0.weight - torch.Size([48, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.0.2.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.0.2.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.1.0.0.0.weight - torch.Size([96, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.1.0.0.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.1.0.0.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.1.2.0.weight - torch.Size([96, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.1.2.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.1.2.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.2.0.0.0.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.2.0.0.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.2.0.0.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.2.0.1.0.weight - torch.Size([192, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.2.0.1.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.2.0.1.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.2.1.0.0.weight - torch.Size([192, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.2.1.0.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.2.fuse_layers.2.1.0.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.0.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.0.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.0.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.0.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.0.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.0.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.1.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.1.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.1.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.1.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.1.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.1.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.2.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.2.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.2.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.2.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.2.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.2.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.3.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.3.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.3.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.3.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.3.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.0.3.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.0.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.0.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.0.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.0.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.0.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.0.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.1.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.1.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.1.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.1.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.1.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.1.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.2.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.2.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.2.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.2.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.2.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.2.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.3.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.3.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.3.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.3.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.3.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.1.3.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.0.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.0.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.0.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.0.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.0.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.0.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.1.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.1.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.1.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.1.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.1.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.1.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.2.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.2.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.2.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.2.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.2.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.2.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.3.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.3.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.3.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.3.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.3.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.branches.2.3.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.0.1.0.weight - torch.Size([48, 96, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.0.1.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.0.1.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.0.2.0.weight - torch.Size([48, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.0.2.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.0.2.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.1.0.0.0.weight - torch.Size([96, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.1.0.0.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.1.0.0.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.1.2.0.weight - torch.Size([96, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.1.2.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.1.2.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.2.0.0.0.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.2.0.0.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.2.0.0.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.2.0.1.0.weight - torch.Size([192, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.2.0.1.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.2.0.1.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.2.1.0.0.weight - torch.Size([192, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.2.1.0.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage3.3.fuse_layers.2.1.0.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.transition3.3.0.0.weight - torch.Size([384, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.transition3.3.0.1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.transition3.3.0.1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.0.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.0.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.0.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.0.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.0.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.0.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.1.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.1.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.1.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.1.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.1.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.1.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.2.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.2.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.2.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.2.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.2.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.2.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.3.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.3.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.3.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.3.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.3.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.0.3.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.0.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.0.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.0.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.0.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.0.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.0.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.1.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.1.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.1.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.1.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.1.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.1.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.2.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.2.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.2.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.2.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.2.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.2.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.3.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.3.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.3.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.3.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.3.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.1.3.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.0.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.0.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.0.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.0.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.0.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.0.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.1.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.1.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.1.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.1.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.1.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.1.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.2.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.2.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.2.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.2.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.2.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.2.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.3.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.3.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.3.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.3.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.3.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.2.3.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.0.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.0.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.0.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.0.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.0.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.0.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.1.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.1.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.1.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.1.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.1.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.1.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.2.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.2.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.2.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.2.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.2.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.2.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.3.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.3.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.3.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.3.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.3.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.branches.3.3.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.0.1.0.weight - torch.Size([48, 96, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.0.1.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.0.1.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.0.2.0.weight - torch.Size([48, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.0.2.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.0.2.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.0.3.0.weight - torch.Size([48, 384, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.0.3.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.0.3.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.1.0.0.0.weight - torch.Size([96, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.1.0.0.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.1.0.0.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.1.2.0.weight - torch.Size([96, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.1.2.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.1.2.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.1.3.0.weight - torch.Size([96, 384, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.1.3.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.1.3.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.0.0.0.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.0.0.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.0.0.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.0.1.0.weight - torch.Size([192, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.0.1.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.0.1.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.1.0.0.weight - torch.Size([192, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.1.0.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.1.0.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.3.0.weight - torch.Size([192, 384, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.3.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.2.3.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.0.0.0.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.0.0.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.0.0.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.0.1.0.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.0.1.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.0.1.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.0.2.0.weight - torch.Size([384, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.0.2.1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.0.2.1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.1.0.0.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.1.0.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.1.0.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.1.1.0.weight - torch.Size([384, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.1.1.1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.1.1.1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.2.0.0.weight - torch.Size([384, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.2.0.1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.0.fuse_layers.3.2.0.1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.0.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.0.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.0.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.0.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.0.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.0.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.1.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.1.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.1.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.1.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.1.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.1.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.2.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.2.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.2.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.2.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.2.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.2.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.3.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.3.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.3.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.3.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.3.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.0.3.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.0.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.0.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.0.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.0.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.0.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.0.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.1.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.1.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.1.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.1.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.1.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.1.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.2.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.2.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.2.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.2.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.2.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.2.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.3.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.3.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.3.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.3.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.3.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.1.3.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.0.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.0.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.0.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.0.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.0.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.0.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.1.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.1.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.1.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.1.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.1.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.1.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.2.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.2.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.2.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.2.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.2.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.2.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.3.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.3.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.3.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.3.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.3.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.2.3.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.0.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.0.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.0.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.0.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.0.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.0.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.1.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.1.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.1.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.1.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.1.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.1.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.2.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.2.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.2.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.2.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.2.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.2.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.3.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.3.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.3.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.3.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.3.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.branches.3.3.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.0.1.0.weight - torch.Size([48, 96, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.0.1.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.0.1.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.0.2.0.weight - torch.Size([48, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.0.2.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.0.2.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.0.3.0.weight - torch.Size([48, 384, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.0.3.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.0.3.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.1.0.0.0.weight - torch.Size([96, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.1.0.0.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.1.0.0.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.1.2.0.weight - torch.Size([96, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.1.2.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.1.2.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.1.3.0.weight - torch.Size([96, 384, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.1.3.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.1.3.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.0.0.0.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.0.0.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.0.0.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.0.1.0.weight - torch.Size([192, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.0.1.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.0.1.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.1.0.0.weight - torch.Size([192, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.1.0.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.1.0.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.3.0.weight - torch.Size([192, 384, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.3.1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.2.3.1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.0.0.0.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.0.0.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.0.0.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.0.1.0.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.0.1.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.0.1.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.0.2.0.weight - torch.Size([384, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.0.2.1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.0.2.1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.1.0.0.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.1.0.1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.1.0.1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.1.1.0.weight - torch.Size([384, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.1.1.1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.1.1.1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.2.0.0.weight - torch.Size([384, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.2.0.1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.1.fuse_layers.3.2.0.1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.0.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.0.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.0.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.0.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.0.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.0.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.1.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.1.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.1.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.1.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.1.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.1.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.2.conv1.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: 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PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.3.bn1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.3.bn1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.3.conv2.weight - torch.Size([48, 48, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.3.bn2.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.0.3.bn2.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.0.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.0.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.0.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.0.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.0.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.0.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.1.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.1.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.1.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.1.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.1.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.1.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.2.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.2.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.2.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.2.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.2.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.2.bn2.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.3.conv1.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.3.bn1.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.3.bn1.bias - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.3.conv2.weight - torch.Size([96, 96, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.3.bn2.weight - torch.Size([96]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.1.3.bn2.bias - torch.Size([96]): PretrainedInit: 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torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.1.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.1.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.1.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.1.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.1.bn2.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.1.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.2.conv1.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.2.bn1.weight - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.2.bn1.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.2.conv2.weight - torch.Size([192, 192, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.2.bn2.weight - torch.Size([192]): PretrainedInit: load from 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PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.2.3.bn2.bias - torch.Size([192]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.0.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.0.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.0.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.0.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.0.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.0.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.1.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.1.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.1.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.1.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.1.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.1.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.2.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.2.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.2.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.2.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.2.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.2.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.3.conv1.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.3.bn1.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.3.bn1.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.3.conv2.weight - torch.Size([384, 384, 3, 3]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.3.bn2.weight - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.branches.3.3.bn2.bias - torch.Size([384]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.fuse_layers.0.1.0.weight - torch.Size([48, 96, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.fuse_layers.0.1.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.fuse_layers.0.1.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.fuse_layers.0.2.0.weight - torch.Size([48, 192, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.fuse_layers.0.2.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.fuse_layers.0.2.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.fuse_layers.0.3.0.weight - torch.Size([48, 384, 1, 1]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.fuse_layers.0.3.1.weight - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth backbone.stage4.2.fuse_layers.0.3.1.bias - torch.Size([48]): PretrainedInit: load from https://download.openmmlab.com/mmpose/pretrain_models/hrnet_w48-8ef0771d.pth head.final_layer.weight - torch.Size([6, 48, 1, 1]): NormalInit: mean=0, std=0.001, bias=0 head.final_layer.bias - torch.Size([6]): NormalInit: mean=0, std=0.001, bias=0 2023/08/09 15:36:20 - mmengine - INFO - Auto resumed from the latest checkpoint /root/mmpose/work_dirs/td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192/epoch_110.pth. 2023/08/09 15:36:21 - mmengine - INFO - Load checkpoint from /root/mmpose/work_dirs/td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192/epoch_110.pth 2023/08/09 15:36:22 - mmengine - INFO - resumed epoch: 110, iter: 48620 2023/08/09 15:36:22 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io 2023/08/09 15:36:22 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. 2023/08/09 15:36:22 - mmengine - INFO - Checkpoints will be saved to /root/mmpose/work_dirs/td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192. 2023/08/09 15:36:26 - mmengine - INFO - Epoch(train) [111][ 10/442] lr: 5.000000e-04 eta: 5:31:44 time: 0.370879 data_time: 0.042178 memory: 4565 loss: 0.001023 loss_kpt: 0.001023 acc_pose: 0.779910 2023/08/09 15:36:30 - mmengine - INFO - Epoch(train) [111][ 20/442] lr: 5.000000e-04 eta: 4:54:50 time: 0.371530 data_time: 0.042502 memory: 4565 loss: 0.001006 loss_kpt: 0.001006 acc_pose: 0.838487 2023/08/09 15:36:33 - mmengine - INFO - Epoch(train) [111][ 30/442] lr: 5.000000e-04 eta: 4:41:02 time: 0.371542 data_time: 0.042770 memory: 4565 loss: 0.001003 loss_kpt: 0.001003 acc_pose: 0.802951 2023/08/09 15:36:37 - mmengine - INFO - Epoch(train) [111][ 40/442] lr: 5.000000e-04 eta: 4:34:10 time: 0.367406 data_time: 0.042249 memory: 4565 loss: 0.001006 loss_kpt: 0.001006 acc_pose: 0.822780 2023/08/09 15:36:40 - mmengine - INFO - Epoch(train) [111][ 50/442] lr: 5.000000e-04 eta: 4:29:51 time: 0.366737 data_time: 0.042262 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.802104 2023/08/09 15:36:43 - mmengine - INFO - Epoch(train) [111][ 60/442] lr: 5.000000e-04 eta: 4:26:19 time: 0.344345 data_time: 0.031060 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.748167 2023/08/09 15:36:47 - mmengine - INFO - Epoch(train) [111][ 70/442] lr: 5.000000e-04 eta: 4:24:02 time: 0.342442 data_time: 0.031004 memory: 4565 loss: 0.001005 loss_kpt: 0.001005 acc_pose: 0.880885 2023/08/09 15:36:50 - mmengine - INFO - Epoch(train) [111][ 80/442] lr: 5.000000e-04 eta: 4:22:33 time: 0.342238 data_time: 0.030961 memory: 4565 loss: 0.001009 loss_kpt: 0.001009 acc_pose: 0.798868 2023/08/09 15:36:54 - mmengine - INFO - Epoch(train) [111][ 90/442] lr: 5.000000e-04 eta: 4:23:30 time: 0.347151 data_time: 0.031065 memory: 4565 loss: 0.001001 loss_kpt: 0.001001 acc_pose: 0.806676 2023/08/09 15:36:57 - mmengine - INFO - Epoch(train) [111][100/442] lr: 5.000000e-04 eta: 4:22:35 time: 0.347814 data_time: 0.031342 memory: 4565 loss: 0.001011 loss_kpt: 0.001011 acc_pose: 0.834681 2023/08/09 15:37:01 - mmengine - INFO - Epoch(train) [111][110/442] lr: 5.000000e-04 eta: 4:21:49 time: 0.349457 data_time: 0.031336 memory: 4565 loss: 0.001006 loss_kpt: 0.001006 acc_pose: 0.741583 2023/08/09 15:37:04 - mmengine - INFO - Epoch(train) [111][120/442] lr: 5.000000e-04 eta: 4:21:01 time: 0.350086 data_time: 0.031087 memory: 4565 loss: 0.000998 loss_kpt: 0.000998 acc_pose: 0.800992 2023/08/09 15:37:08 - mmengine - INFO - Epoch(train) [111][130/442] lr: 5.000000e-04 eta: 4:20:27 time: 0.350692 data_time: 0.031017 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.831712 2023/08/09 15:37:11 - mmengine - INFO - Epoch(train) [111][140/442] lr: 5.000000e-04 eta: 4:19:41 time: 0.345032 data_time: 0.030875 memory: 4565 loss: 0.001004 loss_kpt: 0.001004 acc_pose: 0.756507 2023/08/09 15:37:15 - mmengine - INFO - Epoch(train) [111][150/442] lr: 5.000000e-04 eta: 4:19:18 time: 0.345079 data_time: 0.030966 memory: 4565 loss: 0.001005 loss_kpt: 0.001005 acc_pose: 0.825439 2023/08/09 15:37:18 - mmengine - INFO - Epoch(train) [111][160/442] lr: 5.000000e-04 eta: 4:19:58 time: 0.349543 data_time: 0.031274 memory: 4565 loss: 0.000990 loss_kpt: 0.000990 acc_pose: 0.868930 2023/08/09 15:37:22 - mmengine - INFO - Epoch(train) [111][170/442] lr: 5.000000e-04 eta: 4:19:41 time: 0.350523 data_time: 0.031526 memory: 4565 loss: 0.000998 loss_kpt: 0.000998 acc_pose: 0.660742 2023/08/09 15:37:25 - mmengine - INFO - Epoch(train) [111][180/442] lr: 5.000000e-04 eta: 4:19:14 time: 0.350067 data_time: 0.031492 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.840748 2023/08/09 15:37:29 - mmengine - INFO - Epoch(train) [111][190/442] lr: 5.000000e-04 eta: 4:18:43 time: 0.350169 data_time: 0.031340 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.783940 2023/08/09 15:37:32 - mmengine - INFO - Epoch(train) [111][200/442] lr: 5.000000e-04 eta: 4:18:09 time: 0.348495 data_time: 0.030988 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.747580 2023/08/09 15:37:36 - mmengine - INFO - Epoch(train) [111][210/442] lr: 5.000000e-04 eta: 4:17:48 time: 0.343401 data_time: 0.030613 memory: 4565 loss: 0.001007 loss_kpt: 0.001007 acc_pose: 0.872042 2023/08/09 15:37:39 - mmengine - INFO - Epoch(train) [111][220/442] lr: 5.000000e-04 eta: 4:17:19 time: 0.341428 data_time: 0.030311 memory: 4565 loss: 0.001014 loss_kpt: 0.001014 acc_pose: 0.908182 2023/08/09 15:37:42 - mmengine - INFO - Epoch(train) [111][230/442] lr: 5.000000e-04 eta: 4:17:03 time: 0.341508 data_time: 0.030442 memory: 4565 loss: 0.001021 loss_kpt: 0.001021 acc_pose: 0.731903 2023/08/09 15:37:46 - mmengine - INFO - Epoch(train) [111][240/442] lr: 5.000000e-04 eta: 4:16:50 time: 0.342252 data_time: 0.030604 memory: 4565 loss: 0.001030 loss_kpt: 0.001030 acc_pose: 0.827526 2023/08/09 15:37:49 - mmengine - INFO - Epoch(train) [111][250/442] lr: 5.000000e-04 eta: 4:16:31 time: 0.342921 data_time: 0.030675 memory: 4565 loss: 0.001038 loss_kpt: 0.001038 acc_pose: 0.805834 2023/08/09 15:37:53 - mmengine - INFO - Epoch(train) [111][260/442] lr: 5.000000e-04 eta: 4:16:09 time: 0.342068 data_time: 0.030638 memory: 4565 loss: 0.001027 loss_kpt: 0.001027 acc_pose: 0.829352 2023/08/09 15:37:56 - mmengine - INFO - Epoch(train) [111][270/442] lr: 5.000000e-04 eta: 4:15:45 time: 0.341624 data_time: 0.030624 memory: 4565 loss: 0.001040 loss_kpt: 0.001040 acc_pose: 0.775044 2023/08/09 15:37:59 - mmengine - INFO - Epoch(train) [111][280/442] lr: 5.000000e-04 eta: 4:15:24 time: 0.340386 data_time: 0.030354 memory: 4565 loss: 0.001068 loss_kpt: 0.001068 acc_pose: 0.708482 2023/08/09 15:38:03 - mmengine - INFO - Epoch(train) [111][290/442] lr: 5.000000e-04 eta: 4:15:06 time: 0.339179 data_time: 0.030219 memory: 4565 loss: 0.001068 loss_kpt: 0.001068 acc_pose: 0.795597 2023/08/09 15:38:06 - mmengine - INFO - Epoch(train) [111][300/442] lr: 5.000000e-04 eta: 4:15:20 time: 0.342901 data_time: 0.030204 memory: 4565 loss: 0.001070 loss_kpt: 0.001070 acc_pose: 0.835131 2023/08/09 15:38:10 - mmengine - INFO - Epoch(train) [111][310/442] lr: 5.000000e-04 eta: 4:15:10 time: 0.343869 data_time: 0.030767 memory: 4565 loss: 0.001067 loss_kpt: 0.001067 acc_pose: 0.782469 2023/08/09 15:38:13 - mmengine - INFO - Epoch(train) [111][320/442] lr: 5.000000e-04 eta: 4:14:55 time: 0.344637 data_time: 0.030895 memory: 4565 loss: 0.001041 loss_kpt: 0.001041 acc_pose: 0.823286 2023/08/09 15:38:17 - mmengine - INFO - Epoch(train) [111][330/442] lr: 5.000000e-04 eta: 4:14:37 time: 0.344404 data_time: 0.030896 memory: 4565 loss: 0.001017 loss_kpt: 0.001017 acc_pose: 0.839241 2023/08/09 15:38:20 - mmengine - INFO - Epoch(train) [111][340/442] lr: 5.000000e-04 eta: 4:14:21 time: 0.344347 data_time: 0.030870 memory: 4565 loss: 0.001018 loss_kpt: 0.001018 acc_pose: 0.763687 2023/08/09 15:38:23 - mmengine - INFO - Epoch(train) [111][350/442] lr: 5.000000e-04 eta: 4:14:09 time: 0.340434 data_time: 0.030795 memory: 4565 loss: 0.001009 loss_kpt: 0.001009 acc_pose: 0.825269 2023/08/09 15:38:27 - mmengine - INFO - Epoch(train) [111][360/442] lr: 5.000000e-04 eta: 4:13:57 time: 0.339790 data_time: 0.030300 memory: 4565 loss: 0.001009 loss_kpt: 0.001009 acc_pose: 0.854469 2023/08/09 15:38:30 - mmengine - INFO - Epoch(train) [111][370/442] lr: 5.000000e-04 eta: 4:13:48 time: 0.340153 data_time: 0.030336 memory: 4565 loss: 0.001007 loss_kpt: 0.001007 acc_pose: 0.865539 2023/08/09 15:38:34 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:38:34 - mmengine - INFO - Epoch(train) [111][380/442] lr: 5.000000e-04 eta: 4:13:48 time: 0.342781 data_time: 0.030698 memory: 4565 loss: 0.001018 loss_kpt: 0.001018 acc_pose: 0.852701 2023/08/09 15:38:37 - mmengine - INFO - Epoch(train) [111][390/442] lr: 5.000000e-04 eta: 4:13:52 time: 0.345789 data_time: 0.030809 memory: 4565 loss: 0.001001 loss_kpt: 0.001001 acc_pose: 0.806017 2023/08/09 15:38:41 - mmengine - INFO - Epoch(train) [111][400/442] lr: 5.000000e-04 eta: 4:13:54 time: 0.348173 data_time: 0.033878 memory: 4565 loss: 0.000990 loss_kpt: 0.000990 acc_pose: 0.885449 2023/08/09 15:38:44 - mmengine - INFO - Epoch(train) [111][410/442] lr: 5.000000e-04 eta: 4:13:39 time: 0.347417 data_time: 0.033785 memory: 4565 loss: 0.001010 loss_kpt: 0.001010 acc_pose: 0.816577 2023/08/09 15:38:48 - mmengine - INFO - Epoch(train) [111][420/442] lr: 5.000000e-04 eta: 4:13:36 time: 0.348519 data_time: 0.033711 memory: 4565 loss: 0.001024 loss_kpt: 0.001024 acc_pose: 0.772205 2023/08/09 15:38:51 - mmengine - INFO - Epoch(train) [111][430/442] lr: 5.000000e-04 eta: 4:13:32 time: 0.347754 data_time: 0.033437 memory: 4565 loss: 0.001005 loss_kpt: 0.001005 acc_pose: 0.815014 2023/08/09 15:38:55 - mmengine - INFO - Epoch(train) [111][440/442] lr: 5.000000e-04 eta: 4:13:57 time: 0.352197 data_time: 0.034016 memory: 4565 loss: 0.001007 loss_kpt: 0.001007 acc_pose: 0.831530 2023/08/09 15:38:56 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:39:00 - mmengine - INFO - Epoch(train) [112][ 10/442] lr: 5.000000e-04 eta: 4:14:32 time: 0.359894 data_time: 0.036694 memory: 4565 loss: 0.001030 loss_kpt: 0.001030 acc_pose: 0.703369 2023/08/09 15:39:03 - mmengine - INFO - Epoch(train) [112][ 20/442] lr: 5.000000e-04 eta: 4:14:26 time: 0.361193 data_time: 0.036684 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.865504 2023/08/09 15:39:07 - mmengine - INFO - Epoch(train) [112][ 30/442] lr: 5.000000e-04 eta: 4:14:21 time: 0.361483 data_time: 0.036524 memory: 4565 loss: 0.000989 loss_kpt: 0.000989 acc_pose: 0.814482 2023/08/09 15:39:10 - mmengine - INFO - Epoch(train) [112][ 40/442] lr: 5.000000e-04 eta: 4:14:15 time: 0.359338 data_time: 0.036424 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.827911 2023/08/09 15:39:14 - mmengine - INFO - Epoch(train) [112][ 50/442] lr: 5.000000e-04 eta: 4:14:28 time: 0.358965 data_time: 0.036331 memory: 4565 loss: 0.001008 loss_kpt: 0.001008 acc_pose: 0.859200 2023/08/09 15:39:17 - mmengine - INFO - Epoch(train) [112][ 60/442] lr: 5.000000e-04 eta: 4:14:38 time: 0.354326 data_time: 0.031240 memory: 4565 loss: 0.000998 loss_kpt: 0.000998 acc_pose: 0.831802 2023/08/09 15:39:21 - mmengine - INFO - Epoch(train) [112][ 70/442] lr: 5.000000e-04 eta: 4:14:44 time: 0.357261 data_time: 0.032153 memory: 4565 loss: 0.001025 loss_kpt: 0.001025 acc_pose: 0.821107 2023/08/09 15:39:24 - mmengine - INFO - Epoch(train) [112][ 80/442] lr: 5.000000e-04 eta: 4:14:40 time: 0.357618 data_time: 0.032213 memory: 4565 loss: 0.001029 loss_kpt: 0.001029 acc_pose: 0.818853 2023/08/09 15:39:28 - mmengine - INFO - Epoch(train) [112][ 90/442] lr: 5.000000e-04 eta: 4:14:34 time: 0.357771 data_time: 0.032252 memory: 4565 loss: 0.001036 loss_kpt: 0.001036 acc_pose: 0.781864 2023/08/09 15:39:32 - mmengine - INFO - Epoch(train) [112][100/442] lr: 5.000000e-04 eta: 4:14:42 time: 0.357179 data_time: 0.031930 memory: 4565 loss: 0.001039 loss_kpt: 0.001039 acc_pose: 0.876262 2023/08/09 15:39:35 - mmengine - INFO - Epoch(train) [112][110/442] lr: 5.000000e-04 eta: 4:14:44 time: 0.355550 data_time: 0.030940 memory: 4565 loss: 0.001046 loss_kpt: 0.001046 acc_pose: 0.775124 2023/08/09 15:39:39 - mmengine - INFO - Epoch(train) [112][120/442] lr: 5.000000e-04 eta: 4:14:50 time: 0.355883 data_time: 0.030076 memory: 4565 loss: 0.001048 loss_kpt: 0.001048 acc_pose: 0.756756 2023/08/09 15:39:42 - mmengine - INFO - Epoch(train) [112][130/442] lr: 5.000000e-04 eta: 4:15:02 time: 0.360111 data_time: 0.030555 memory: 4565 loss: 0.001034 loss_kpt: 0.001034 acc_pose: 0.796742 2023/08/09 15:39:46 - mmengine - INFO - Epoch(train) [112][140/442] lr: 5.000000e-04 eta: 4:15:14 time: 0.365093 data_time: 0.031684 memory: 4565 loss: 0.001038 loss_kpt: 0.001038 acc_pose: 0.883507 2023/08/09 15:39:50 - mmengine - INFO - Epoch(train) [112][150/442] lr: 5.000000e-04 eta: 4:15:10 time: 0.362440 data_time: 0.032568 memory: 4565 loss: 0.001030 loss_kpt: 0.001030 acc_pose: 0.861489 2023/08/09 15:39:53 - mmengine - INFO - Epoch(train) [112][160/442] lr: 5.000000e-04 eta: 4:15:00 time: 0.359409 data_time: 0.032976 memory: 4565 loss: 0.001006 loss_kpt: 0.001006 acc_pose: 0.796528 2023/08/09 15:39:56 - mmengine - INFO - Epoch(train) [112][170/442] lr: 5.000000e-04 eta: 4:14:48 time: 0.354826 data_time: 0.033231 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.820194 2023/08/09 15:40:00 - mmengine - INFO - Epoch(train) [112][180/442] lr: 5.000000e-04 eta: 4:14:45 time: 0.351005 data_time: 0.033177 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.853712 2023/08/09 15:40:03 - mmengine - INFO - Epoch(train) [112][190/442] lr: 5.000000e-04 eta: 4:14:36 time: 0.345213 data_time: 0.032324 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.866928 2023/08/09 15:40:07 - mmengine - INFO - Epoch(train) [112][200/442] lr: 5.000000e-04 eta: 4:14:30 time: 0.344535 data_time: 0.031979 memory: 4565 loss: 0.000980 loss_kpt: 0.000980 acc_pose: 0.828937 2023/08/09 15:40:10 - mmengine - INFO - Epoch(train) [112][210/442] lr: 5.000000e-04 eta: 4:14:28 time: 0.346650 data_time: 0.031908 memory: 4565 loss: 0.000989 loss_kpt: 0.000989 acc_pose: 0.812506 2023/08/09 15:40:14 - mmengine - INFO - Epoch(train) [112][220/442] lr: 5.000000e-04 eta: 4:14:22 time: 0.348013 data_time: 0.031691 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.817991 2023/08/09 15:40:17 - mmengine - INFO - Epoch(train) [112][230/442] lr: 5.000000e-04 eta: 4:14:14 time: 0.346623 data_time: 0.031634 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.889015 2023/08/09 15:40:21 - mmengine - INFO - Epoch(train) [112][240/442] lr: 5.000000e-04 eta: 4:14:06 time: 0.346834 data_time: 0.031770 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.841680 2023/08/09 15:40:24 - mmengine - INFO - Epoch(train) [112][250/442] lr: 5.000000e-04 eta: 4:13:59 time: 0.346216 data_time: 0.031445 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.851908 2023/08/09 15:40:28 - mmengine - INFO - Epoch(train) [112][260/442] lr: 5.000000e-04 eta: 4:14:06 time: 0.349288 data_time: 0.031406 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.759521 2023/08/09 15:40:31 - mmengine - INFO - Epoch(train) [112][270/442] lr: 5.000000e-04 eta: 4:14:00 time: 0.349045 data_time: 0.031785 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.892375 2023/08/09 15:40:35 - mmengine - INFO - Epoch(train) [112][280/442] lr: 5.000000e-04 eta: 4:14:05 time: 0.353143 data_time: 0.035153 memory: 4565 loss: 0.001001 loss_kpt: 0.001001 acc_pose: 0.840651 2023/08/09 15:40:38 - mmengine - INFO - Epoch(train) [112][290/442] lr: 5.000000e-04 eta: 4:13:55 time: 0.352284 data_time: 0.034899 memory: 4565 loss: 0.001011 loss_kpt: 0.001011 acc_pose: 0.778244 2023/08/09 15:40:42 - mmengine - INFO - Epoch(train) [112][300/442] lr: 5.000000e-04 eta: 4:13:43 time: 0.350670 data_time: 0.034801 memory: 4565 loss: 0.001002 loss_kpt: 0.001002 acc_pose: 0.891935 2023/08/09 15:40:45 - mmengine - INFO - Epoch(train) [112][310/442] lr: 5.000000e-04 eta: 4:13:32 time: 0.344842 data_time: 0.034547 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.830600 2023/08/09 15:40:49 - mmengine - INFO - Epoch(train) [112][320/442] lr: 5.000000e-04 eta: 4:13:29 time: 0.345708 data_time: 0.034376 memory: 4565 loss: 0.001011 loss_kpt: 0.001011 acc_pose: 0.803515 2023/08/09 15:40:52 - mmengine - INFO - Epoch(train) [112][330/442] lr: 5.000000e-04 eta: 4:13:29 time: 0.344075 data_time: 0.031552 memory: 4565 loss: 0.001005 loss_kpt: 0.001005 acc_pose: 0.815192 2023/08/09 15:40:56 - mmengine - INFO - Epoch(train) [112][340/442] lr: 5.000000e-04 eta: 4:13:26 time: 0.346577 data_time: 0.031905 memory: 4565 loss: 0.001000 loss_kpt: 0.001000 acc_pose: 0.826169 2023/08/09 15:40:59 - mmengine - INFO - Epoch(train) [112][350/442] lr: 5.000000e-04 eta: 4:13:22 time: 0.349227 data_time: 0.032092 memory: 4565 loss: 0.001004 loss_kpt: 0.001004 acc_pose: 0.796712 2023/08/09 15:41:03 - mmengine - INFO - Epoch(train) [112][360/442] lr: 5.000000e-04 eta: 4:13:15 time: 0.350374 data_time: 0.032084 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.786907 2023/08/09 15:41:06 - mmengine - INFO - Epoch(train) [112][370/442] lr: 5.000000e-04 eta: 4:13:05 time: 0.347808 data_time: 0.031779 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.762735 2023/08/09 15:41:09 - mmengine - INFO - Epoch(train) [112][380/442] lr: 5.000000e-04 eta: 4:12:55 time: 0.344007 data_time: 0.030766 memory: 4565 loss: 0.001001 loss_kpt: 0.001001 acc_pose: 0.833098 2023/08/09 15:41:13 - mmengine - INFO - Epoch(train) [112][390/442] lr: 5.000000e-04 eta: 4:12:45 time: 0.341246 data_time: 0.030227 memory: 4565 loss: 0.001009 loss_kpt: 0.001009 acc_pose: 0.825397 2023/08/09 15:41:16 - mmengine - INFO - Epoch(train) [112][400/442] lr: 5.000000e-04 eta: 4:12:40 time: 0.340694 data_time: 0.030057 memory: 4565 loss: 0.001002 loss_kpt: 0.001002 acc_pose: 0.833543 2023/08/09 15:41:20 - mmengine - INFO - Epoch(train) [112][410/442] lr: 5.000000e-04 eta: 4:12:43 time: 0.344383 data_time: 0.030197 memory: 4565 loss: 0.001019 loss_kpt: 0.001019 acc_pose: 0.727495 2023/08/09 15:41:24 - mmengine - INFO - Epoch(train) [112][420/442] lr: 5.000000e-04 eta: 4:12:58 time: 0.354429 data_time: 0.030769 memory: 4565 loss: 0.001000 loss_kpt: 0.001000 acc_pose: 0.860814 2023/08/09 15:41:27 - mmengine - INFO - Epoch(train) [112][430/442] lr: 5.000000e-04 eta: 4:13:01 time: 0.359404 data_time: 0.031011 memory: 4565 loss: 0.000998 loss_kpt: 0.000998 acc_pose: 0.867801 2023/08/09 15:41:31 - mmengine - INFO - Epoch(train) [112][440/442] lr: 5.000000e-04 eta: 4:12:51 time: 0.359182 data_time: 0.031064 memory: 4565 loss: 0.000989 loss_kpt: 0.000989 acc_pose: 0.874255 2023/08/09 15:41:31 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:41:35 - mmengine - INFO - Epoch(train) [113][ 10/442] lr: 5.000000e-04 eta: 4:13:00 time: 0.365858 data_time: 0.034268 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.754936 2023/08/09 15:41:39 - mmengine - INFO - Epoch(train) [113][ 20/442] lr: 5.000000e-04 eta: 4:13:04 time: 0.364573 data_time: 0.037269 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.814681 2023/08/09 15:41:42 - mmengine - INFO - Epoch(train) [113][ 30/442] lr: 5.000000e-04 eta: 4:13:02 time: 0.357888 data_time: 0.036871 memory: 4565 loss: 0.000980 loss_kpt: 0.000980 acc_pose: 0.827147 2023/08/09 15:41:46 - mmengine - INFO - Epoch(train) [113][ 40/442] lr: 5.000000e-04 eta: 4:13:03 time: 0.359790 data_time: 0.037246 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.823483 2023/08/09 15:41:50 - mmengine - INFO - Epoch(train) [113][ 50/442] lr: 5.000000e-04 eta: 4:12:59 time: 0.363192 data_time: 0.037565 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.798606 2023/08/09 15:41:53 - mmengine - INFO - Epoch(train) [113][ 60/442] lr: 5.000000e-04 eta: 4:12:55 time: 0.355899 data_time: 0.034030 memory: 4565 loss: 0.000993 loss_kpt: 0.000993 acc_pose: 0.823305 2023/08/09 15:41:57 - mmengine - INFO - Epoch(train) [113][ 70/442] lr: 5.000000e-04 eta: 4:12:50 time: 0.352507 data_time: 0.030994 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.847146 2023/08/09 15:42:00 - mmengine - INFO - Epoch(train) [113][ 80/442] lr: 5.000000e-04 eta: 4:12:46 time: 0.351649 data_time: 0.031026 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.820579 2023/08/09 15:42:04 - mmengine - INFO - Epoch(train) [113][ 90/442] lr: 5.000000e-04 eta: 4:12:45 time: 0.350247 data_time: 0.030827 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.816740 2023/08/09 15:42:07 - mmengine - INFO - Epoch(train) [113][100/442] lr: 5.000000e-04 eta: 4:12:42 time: 0.350796 data_time: 0.031097 memory: 4565 loss: 0.000980 loss_kpt: 0.000980 acc_pose: 0.801772 2023/08/09 15:42:11 - mmengine - INFO - Epoch(train) [113][110/442] lr: 5.000000e-04 eta: 4:12:41 time: 0.352337 data_time: 0.031284 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.808555 2023/08/09 15:42:14 - mmengine - INFO - Epoch(train) [113][120/442] lr: 5.000000e-04 eta: 4:12:38 time: 0.352981 data_time: 0.031188 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.813409 2023/08/09 15:42:18 - mmengine - INFO - Epoch(train) [113][130/442] lr: 5.000000e-04 eta: 4:12:33 time: 0.352627 data_time: 0.031116 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.833147 2023/08/09 15:42:21 - mmengine - INFO - Epoch(train) [113][140/442] lr: 5.000000e-04 eta: 4:12:28 time: 0.351435 data_time: 0.030807 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.816326 2023/08/09 15:42:25 - mmengine - INFO - Epoch(train) [113][150/442] lr: 5.000000e-04 eta: 4:12:30 time: 0.353612 data_time: 0.030433 memory: 4565 loss: 0.000993 loss_kpt: 0.000993 acc_pose: 0.793226 2023/08/09 15:42:28 - mmengine - INFO - Epoch(train) [113][160/442] lr: 5.000000e-04 eta: 4:12:29 time: 0.353614 data_time: 0.030543 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.792213 2023/08/09 15:42:32 - mmengine - INFO - Epoch(train) [113][170/442] lr: 5.000000e-04 eta: 4:12:29 time: 0.355446 data_time: 0.030383 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.814603 2023/08/09 15:42:35 - mmengine - INFO - Epoch(train) [113][180/442] lr: 5.000000e-04 eta: 4:12:25 time: 0.355856 data_time: 0.030214 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.858778 2023/08/09 15:42:39 - mmengine - INFO - Epoch(train) [113][190/442] lr: 5.000000e-04 eta: 4:12:22 time: 0.356695 data_time: 0.030976 memory: 4565 loss: 0.000995 loss_kpt: 0.000995 acc_pose: 0.840922 2023/08/09 15:42:43 - mmengine - INFO - Epoch(train) [113][200/442] lr: 5.000000e-04 eta: 4:12:18 time: 0.353824 data_time: 0.031143 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.822622 2023/08/09 15:42:46 - mmengine - INFO - Epoch(train) [113][210/442] lr: 5.000000e-04 eta: 4:12:14 time: 0.352521 data_time: 0.030772 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.823874 2023/08/09 15:42:50 - mmengine - INFO - Epoch(train) [113][220/442] lr: 5.000000e-04 eta: 4:12:12 time: 0.351135 data_time: 0.030842 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.860449 2023/08/09 15:42:53 - mmengine - INFO - Epoch(train) [113][230/442] lr: 5.000000e-04 eta: 4:12:11 time: 0.352570 data_time: 0.031162 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.866990 2023/08/09 15:42:57 - mmengine - INFO - Epoch(train) [113][240/442] lr: 5.000000e-04 eta: 4:12:10 time: 0.353802 data_time: 0.030978 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.839912 2023/08/09 15:43:00 - mmengine - INFO - Epoch(train) [113][250/442] lr: 5.000000e-04 eta: 4:12:05 time: 0.353510 data_time: 0.030978 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.880846 2023/08/09 15:43:04 - mmengine - INFO - Epoch(train) [113][260/442] lr: 5.000000e-04 eta: 4:12:05 time: 0.355687 data_time: 0.034081 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.774385 2023/08/09 15:43:07 - mmengine - INFO - Epoch(train) [113][270/442] lr: 5.000000e-04 eta: 4:12:00 time: 0.354042 data_time: 0.034032 memory: 4565 loss: 0.000993 loss_kpt: 0.000993 acc_pose: 0.806432 2023/08/09 15:43:11 - mmengine - INFO - Epoch(train) [113][280/442] lr: 5.000000e-04 eta: 4:11:56 time: 0.352828 data_time: 0.033805 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.811787 2023/08/09 15:43:14 - mmengine - INFO - Epoch(train) [113][290/442] lr: 5.000000e-04 eta: 4:11:52 time: 0.351096 data_time: 0.033233 memory: 4565 loss: 0.000980 loss_kpt: 0.000980 acc_pose: 0.850783 2023/08/09 15:43:18 - mmengine - INFO - Epoch(train) [113][300/442] lr: 5.000000e-04 eta: 4:11:54 time: 0.354641 data_time: 0.033248 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.788903 2023/08/09 15:43:21 - mmengine - INFO - Epoch(train) [113][310/442] lr: 5.000000e-04 eta: 4:11:52 time: 0.353633 data_time: 0.030450 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.856198 2023/08/09 15:43:25 - mmengine - INFO - Epoch(train) [113][320/442] lr: 5.000000e-04 eta: 4:11:48 time: 0.354411 data_time: 0.030877 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.809094 2023/08/09 15:43:29 - mmengine - INFO - Epoch(train) [113][330/442] lr: 5.000000e-04 eta: 4:11:44 time: 0.354478 data_time: 0.030958 memory: 4565 loss: 0.001003 loss_kpt: 0.001003 acc_pose: 0.776550 2023/08/09 15:43:32 - mmengine - INFO - Epoch(train) [113][340/442] lr: 5.000000e-04 eta: 4:11:40 time: 0.354474 data_time: 0.031141 memory: 4565 loss: 0.001015 loss_kpt: 0.001015 acc_pose: 0.805226 2023/08/09 15:43:36 - mmengine - INFO - Epoch(train) [113][350/442] lr: 5.000000e-04 eta: 4:11:36 time: 0.351614 data_time: 0.031137 memory: 4565 loss: 0.001022 loss_kpt: 0.001022 acc_pose: 0.830871 2023/08/09 15:43:39 - mmengine - INFO - Epoch(train) [113][360/442] lr: 5.000000e-04 eta: 4:11:33 time: 0.350665 data_time: 0.030949 memory: 4565 loss: 0.001037 loss_kpt: 0.001037 acc_pose: 0.786662 2023/08/09 15:43:43 - mmengine - INFO - Epoch(train) [113][370/442] lr: 5.000000e-04 eta: 4:11:30 time: 0.351562 data_time: 0.030832 memory: 4565 loss: 0.001032 loss_kpt: 0.001032 acc_pose: 0.802306 2023/08/09 15:43:46 - mmengine - INFO - Epoch(train) [113][380/442] lr: 5.000000e-04 eta: 4:11:31 time: 0.353818 data_time: 0.031119 memory: 4565 loss: 0.001041 loss_kpt: 0.001041 acc_pose: 0.829602 2023/08/09 15:43:50 - mmengine - INFO - Epoch(train) [113][390/442] lr: 5.000000e-04 eta: 4:11:28 time: 0.354763 data_time: 0.031144 memory: 4565 loss: 0.001032 loss_kpt: 0.001032 acc_pose: 0.801942 2023/08/09 15:43:53 - mmengine - INFO - Epoch(train) [113][400/442] lr: 5.000000e-04 eta: 4:11:23 time: 0.353852 data_time: 0.031085 memory: 4565 loss: 0.001026 loss_kpt: 0.001026 acc_pose: 0.806628 2023/08/09 15:43:57 - mmengine - INFO - Epoch(train) [113][410/442] lr: 5.000000e-04 eta: 4:11:17 time: 0.352306 data_time: 0.030931 memory: 4565 loss: 0.001026 loss_kpt: 0.001026 acc_pose: 0.824717 2023/08/09 15:44:00 - mmengine - INFO - Epoch(train) [113][420/442] lr: 5.000000e-04 eta: 4:11:12 time: 0.350968 data_time: 0.030579 memory: 4565 loss: 0.001001 loss_kpt: 0.001001 acc_pose: 0.882201 2023/08/09 15:44:04 - mmengine - INFO - Epoch(train) [113][430/442] lr: 5.000000e-04 eta: 4:11:10 time: 0.349487 data_time: 0.030585 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.860534 2023/08/09 15:44:07 - mmengine - INFO - Epoch(train) [113][440/442] lr: 5.000000e-04 eta: 4:11:08 time: 0.349719 data_time: 0.030779 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.863842 2023/08/09 15:44:08 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:44:12 - mmengine - INFO - Epoch(train) [114][ 10/442] lr: 5.000000e-04 eta: 4:11:09 time: 0.354367 data_time: 0.035022 memory: 4565 loss: 0.000974 loss_kpt: 0.000974 acc_pose: 0.720713 2023/08/09 15:44:15 - mmengine - INFO - Epoch(train) [114][ 20/442] lr: 5.000000e-04 eta: 4:11:10 time: 0.358840 data_time: 0.035094 memory: 4565 loss: 0.000974 loss_kpt: 0.000974 acc_pose: 0.754177 2023/08/09 15:44:19 - mmengine - INFO - Epoch(train) [114][ 30/442] lr: 5.000000e-04 eta: 4:11:06 time: 0.359216 data_time: 0.035141 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.827956 2023/08/09 15:44:22 - mmengine - INFO - Epoch(train) [114][ 40/442] lr: 5.000000e-04 eta: 4:11:02 time: 0.357710 data_time: 0.034878 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.757794 2023/08/09 15:44:26 - mmengine - INFO - Epoch(train) [114][ 50/442] lr: 5.000000e-04 eta: 4:11:00 time: 0.358879 data_time: 0.034777 memory: 4565 loss: 0.001013 loss_kpt: 0.001013 acc_pose: 0.852790 2023/08/09 15:44:27 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:44:30 - mmengine - INFO - Epoch(train) [114][ 60/442] lr: 5.000000e-04 eta: 4:11:01 time: 0.358173 data_time: 0.033751 memory: 4565 loss: 0.000998 loss_kpt: 0.000998 acc_pose: 0.792933 2023/08/09 15:44:33 - mmengine - INFO - Epoch(train) [114][ 70/442] lr: 5.000000e-04 eta: 4:10:59 time: 0.356073 data_time: 0.033887 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.904254 2023/08/09 15:44:37 - mmengine - INFO - Epoch(train) [114][ 80/442] lr: 5.000000e-04 eta: 4:10:56 time: 0.356650 data_time: 0.033941 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.815463 2023/08/09 15:44:40 - mmengine - INFO - Epoch(train) [114][ 90/442] lr: 5.000000e-04 eta: 4:10:52 time: 0.356453 data_time: 0.034080 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.721801 2023/08/09 15:44:44 - mmengine - INFO - Epoch(train) [114][100/442] lr: 5.000000e-04 eta: 4:10:47 time: 0.355277 data_time: 0.034232 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.817658 2023/08/09 15:44:47 - mmengine - INFO - Epoch(train) [114][110/442] lr: 5.000000e-04 eta: 4:10:44 time: 0.351585 data_time: 0.030840 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.777688 2023/08/09 15:44:51 - mmengine - INFO - Epoch(train) [114][120/442] lr: 5.000000e-04 eta: 4:10:41 time: 0.351272 data_time: 0.030995 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.721058 2023/08/09 15:44:54 - mmengine - INFO - Epoch(train) [114][130/442] lr: 5.000000e-04 eta: 4:10:40 time: 0.353010 data_time: 0.031234 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.826815 2023/08/09 15:44:58 - mmengine - INFO - Epoch(train) [114][140/442] lr: 5.000000e-04 eta: 4:10:40 time: 0.355733 data_time: 0.031622 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.837686 2023/08/09 15:45:02 - mmengine - INFO - Epoch(train) [114][150/442] lr: 5.000000e-04 eta: 4:10:42 time: 0.360372 data_time: 0.032164 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.768541 2023/08/09 15:45:06 - mmengine - INFO - Epoch(train) [114][160/442] lr: 5.000000e-04 eta: 4:10:53 time: 0.370437 data_time: 0.032920 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.717578 2023/08/09 15:45:09 - mmengine - INFO - Epoch(train) [114][170/442] lr: 5.000000e-04 eta: 4:10:51 time: 0.371339 data_time: 0.032657 memory: 4565 loss: 0.000980 loss_kpt: 0.000980 acc_pose: 0.816319 2023/08/09 15:45:13 - mmengine - INFO - Epoch(train) [114][180/442] lr: 5.000000e-04 eta: 4:10:48 time: 0.370154 data_time: 0.032494 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.793189 2023/08/09 15:45:17 - mmengine - INFO - Epoch(train) [114][190/442] lr: 5.000000e-04 eta: 4:10:50 time: 0.371345 data_time: 0.032016 memory: 4565 loss: 0.000993 loss_kpt: 0.000993 acc_pose: 0.792433 2023/08/09 15:45:20 - mmengine - INFO - Epoch(train) [114][200/442] lr: 5.000000e-04 eta: 4:10:48 time: 0.368527 data_time: 0.031595 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.837427 2023/08/09 15:45:24 - mmengine - INFO - Epoch(train) [114][210/442] lr: 5.000000e-04 eta: 4:10:43 time: 0.357903 data_time: 0.030651 memory: 4565 loss: 0.001002 loss_kpt: 0.001002 acc_pose: 0.804701 2023/08/09 15:45:27 - mmengine - INFO - Epoch(train) [114][220/442] lr: 5.000000e-04 eta: 4:10:39 time: 0.356064 data_time: 0.030736 memory: 4565 loss: 0.000993 loss_kpt: 0.000993 acc_pose: 0.861285 2023/08/09 15:45:31 - mmengine - INFO - Epoch(train) [114][230/442] lr: 5.000000e-04 eta: 4:10:34 time: 0.354666 data_time: 0.030548 memory: 4565 loss: 0.001003 loss_kpt: 0.001003 acc_pose: 0.788302 2023/08/09 15:45:34 - mmengine - INFO - Epoch(train) [114][240/442] lr: 5.000000e-04 eta: 4:10:30 time: 0.351121 data_time: 0.030489 memory: 4565 loss: 0.001004 loss_kpt: 0.001004 acc_pose: 0.822910 2023/08/09 15:45:38 - mmengine - INFO - Epoch(train) [114][250/442] lr: 5.000000e-04 eta: 4:10:26 time: 0.349639 data_time: 0.030420 memory: 4565 loss: 0.001007 loss_kpt: 0.001007 acc_pose: 0.734668 2023/08/09 15:45:41 - mmengine - INFO - Epoch(train) [114][260/442] lr: 5.000000e-04 eta: 4:10:23 time: 0.350940 data_time: 0.030552 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.870208 2023/08/09 15:45:45 - mmengine - INFO - Epoch(train) [114][270/442] lr: 5.000000e-04 eta: 4:10:24 time: 0.354707 data_time: 0.031285 memory: 4565 loss: 0.001027 loss_kpt: 0.001027 acc_pose: 0.752324 2023/08/09 15:45:48 - mmengine - INFO - Epoch(train) [114][280/442] lr: 5.000000e-04 eta: 4:10:19 time: 0.354370 data_time: 0.031262 memory: 4565 loss: 0.001005 loss_kpt: 0.001005 acc_pose: 0.809087 2023/08/09 15:45:52 - mmengine - INFO - Epoch(train) [114][290/442] lr: 5.000000e-04 eta: 4:10:14 time: 0.353718 data_time: 0.031252 memory: 4565 loss: 0.001022 loss_kpt: 0.001022 acc_pose: 0.774014 2023/08/09 15:45:55 - mmengine - INFO - Epoch(train) [114][300/442] lr: 5.000000e-04 eta: 4:10:09 time: 0.353027 data_time: 0.031018 memory: 4565 loss: 0.001022 loss_kpt: 0.001022 acc_pose: 0.828122 2023/08/09 15:45:59 - mmengine - INFO - Epoch(train) [114][310/442] lr: 5.000000e-04 eta: 4:10:05 time: 0.352097 data_time: 0.031074 memory: 4565 loss: 0.001019 loss_kpt: 0.001019 acc_pose: 0.745443 2023/08/09 15:46:02 - mmengine - INFO - Epoch(train) [114][320/442] lr: 5.000000e-04 eta: 4:10:02 time: 0.349639 data_time: 0.030510 memory: 4565 loss: 0.001014 loss_kpt: 0.001014 acc_pose: 0.794205 2023/08/09 15:46:06 - mmengine - INFO - Epoch(train) [114][330/442] lr: 5.000000e-04 eta: 4:09:59 time: 0.351013 data_time: 0.030890 memory: 4565 loss: 0.001030 loss_kpt: 0.001030 acc_pose: 0.789160 2023/08/09 15:46:10 - mmengine - INFO - Epoch(train) [114][340/442] lr: 5.000000e-04 eta: 4:10:01 time: 0.356650 data_time: 0.031123 memory: 4565 loss: 0.001018 loss_kpt: 0.001018 acc_pose: 0.781651 2023/08/09 15:46:13 - mmengine - INFO - Epoch(train) [114][350/442] lr: 5.000000e-04 eta: 4:09:58 time: 0.357440 data_time: 0.031243 memory: 4565 loss: 0.001008 loss_kpt: 0.001008 acc_pose: 0.773908 2023/08/09 15:46:17 - mmengine - INFO - Epoch(train) [114][360/442] lr: 5.000000e-04 eta: 4:09:54 time: 0.358034 data_time: 0.031287 memory: 4565 loss: 0.001013 loss_kpt: 0.001013 acc_pose: 0.824497 2023/08/09 15:46:20 - mmengine - INFO - Epoch(train) [114][370/442] lr: 5.000000e-04 eta: 4:09:51 time: 0.357362 data_time: 0.031167 memory: 4565 loss: 0.001021 loss_kpt: 0.001021 acc_pose: 0.842903 2023/08/09 15:46:24 - mmengine - INFO - Epoch(train) [114][380/442] lr: 5.000000e-04 eta: 4:09:49 time: 0.359012 data_time: 0.030847 memory: 4565 loss: 0.001010 loss_kpt: 0.001010 acc_pose: 0.836336 2023/08/09 15:46:27 - mmengine - INFO - Epoch(train) [114][390/442] lr: 5.000000e-04 eta: 4:09:47 time: 0.355640 data_time: 0.030905 memory: 4565 loss: 0.001035 loss_kpt: 0.001035 acc_pose: 0.739155 2023/08/09 15:46:31 - mmengine - INFO - Epoch(train) [114][400/442] lr: 5.000000e-04 eta: 4:09:47 time: 0.358222 data_time: 0.031092 memory: 4565 loss: 0.001046 loss_kpt: 0.001046 acc_pose: 0.775430 2023/08/09 15:46:35 - mmengine - INFO - Epoch(train) [114][410/442] lr: 5.000000e-04 eta: 4:09:43 time: 0.358365 data_time: 0.030858 memory: 4565 loss: 0.001047 loss_kpt: 0.001047 acc_pose: 0.794595 2023/08/09 15:46:38 - mmengine - INFO - Epoch(train) [114][420/442] lr: 5.000000e-04 eta: 4:09:39 time: 0.357989 data_time: 0.030667 memory: 4565 loss: 0.001046 loss_kpt: 0.001046 acc_pose: 0.832333 2023/08/09 15:46:42 - mmengine - INFO - Epoch(train) [114][430/442] lr: 5.000000e-04 eta: 4:09:39 time: 0.358631 data_time: 0.030606 memory: 4565 loss: 0.001047 loss_kpt: 0.001047 acc_pose: 0.790476 2023/08/09 15:46:45 - mmengine - INFO - Epoch(train) [114][440/442] lr: 5.000000e-04 eta: 4:09:35 time: 0.357529 data_time: 0.030327 memory: 4565 loss: 0.001035 loss_kpt: 0.001035 acc_pose: 0.777874 2023/08/09 15:46:46 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:46:50 - mmengine - INFO - Epoch(train) [115][ 10/442] lr: 5.000000e-04 eta: 4:09:36 time: 0.359043 data_time: 0.033883 memory: 4565 loss: 0.001013 loss_kpt: 0.001013 acc_pose: 0.911445 2023/08/09 15:46:53 - mmengine - INFO - Epoch(train) [115][ 20/442] lr: 5.000000e-04 eta: 4:09:34 time: 0.360667 data_time: 0.034013 memory: 4565 loss: 0.001000 loss_kpt: 0.001000 acc_pose: 0.828968 2023/08/09 15:46:57 - mmengine - INFO - Epoch(train) [115][ 30/442] lr: 5.000000e-04 eta: 4:09:32 time: 0.359525 data_time: 0.034195 memory: 4565 loss: 0.000995 loss_kpt: 0.000995 acc_pose: 0.796083 2023/08/09 15:47:01 - mmengine - INFO - Epoch(train) [115][ 40/442] lr: 5.000000e-04 eta: 4:09:31 time: 0.361846 data_time: 0.037402 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.858096 2023/08/09 15:47:04 - mmengine - INFO - Epoch(train) [115][ 50/442] lr: 5.000000e-04 eta: 4:09:26 time: 0.362132 data_time: 0.037648 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.836129 2023/08/09 15:47:08 - mmengine - INFO - Epoch(train) [115][ 60/442] lr: 5.000000e-04 eta: 4:09:22 time: 0.355935 data_time: 0.033652 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.778528 2023/08/09 15:47:11 - mmengine - INFO - Epoch(train) [115][ 70/442] lr: 5.000000e-04 eta: 4:09:18 time: 0.353916 data_time: 0.033536 memory: 4565 loss: 0.001004 loss_kpt: 0.001004 acc_pose: 0.802346 2023/08/09 15:47:15 - mmengine - INFO - Epoch(train) [115][ 80/442] lr: 5.000000e-04 eta: 4:09:15 time: 0.353574 data_time: 0.033500 memory: 4565 loss: 0.001005 loss_kpt: 0.001005 acc_pose: 0.829028 2023/08/09 15:47:18 - mmengine - INFO - Epoch(train) [115][ 90/442] lr: 5.000000e-04 eta: 4:09:12 time: 0.352242 data_time: 0.030426 memory: 4565 loss: 0.001002 loss_kpt: 0.001002 acc_pose: 0.859184 2023/08/09 15:47:22 - mmengine - INFO - Epoch(train) [115][100/442] lr: 5.000000e-04 eta: 4:09:07 time: 0.351888 data_time: 0.030600 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.807592 2023/08/09 15:47:25 - mmengine - INFO - Epoch(train) [115][110/442] lr: 5.000000e-04 eta: 4:09:02 time: 0.351202 data_time: 0.030359 memory: 4565 loss: 0.001001 loss_kpt: 0.001001 acc_pose: 0.781009 2023/08/09 15:47:29 - mmengine - INFO - Epoch(train) [115][120/442] lr: 5.000000e-04 eta: 4:08:57 time: 0.350382 data_time: 0.030448 memory: 4565 loss: 0.001004 loss_kpt: 0.001004 acc_pose: 0.802490 2023/08/09 15:47:32 - mmengine - INFO - Epoch(train) [115][130/442] lr: 5.000000e-04 eta: 4:08:52 time: 0.348227 data_time: 0.030119 memory: 4565 loss: 0.001004 loss_kpt: 0.001004 acc_pose: 0.840327 2023/08/09 15:47:36 - mmengine - INFO - Epoch(train) [115][140/442] lr: 5.000000e-04 eta: 4:08:47 time: 0.346731 data_time: 0.030209 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.811992 2023/08/09 15:47:39 - mmengine - INFO - Epoch(train) [115][150/442] lr: 5.000000e-04 eta: 4:08:47 time: 0.350782 data_time: 0.030560 memory: 4565 loss: 0.001017 loss_kpt: 0.001017 acc_pose: 0.821493 2023/08/09 15:47:43 - mmengine - INFO - Epoch(train) [115][160/442] lr: 5.000000e-04 eta: 4:08:45 time: 0.353835 data_time: 0.031051 memory: 4565 loss: 0.001022 loss_kpt: 0.001022 acc_pose: 0.795472 2023/08/09 15:47:46 - mmengine - INFO - Epoch(train) [115][170/442] lr: 5.000000e-04 eta: 4:08:41 time: 0.354223 data_time: 0.031141 memory: 4565 loss: 0.001019 loss_kpt: 0.001019 acc_pose: 0.816750 2023/08/09 15:47:50 - mmengine - INFO - Epoch(train) [115][180/442] lr: 5.000000e-04 eta: 4:08:36 time: 0.354872 data_time: 0.031374 memory: 4565 loss: 0.001010 loss_kpt: 0.001010 acc_pose: 0.828414 2023/08/09 15:47:53 - mmengine - INFO - Epoch(train) [115][190/442] lr: 5.000000e-04 eta: 4:08:32 time: 0.355158 data_time: 0.031541 memory: 4565 loss: 0.001012 loss_kpt: 0.001012 acc_pose: 0.845189 2023/08/09 15:47:57 - mmengine - INFO - Epoch(train) [115][200/442] lr: 5.000000e-04 eta: 4:08:28 time: 0.351382 data_time: 0.031097 memory: 4565 loss: 0.001005 loss_kpt: 0.001005 acc_pose: 0.773836 2023/08/09 15:48:00 - mmengine - INFO - Epoch(train) [115][210/442] lr: 5.000000e-04 eta: 4:08:28 time: 0.353452 data_time: 0.034169 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.755562 2023/08/09 15:48:04 - mmengine - INFO - Epoch(train) [115][220/442] lr: 5.000000e-04 eta: 4:08:25 time: 0.355203 data_time: 0.034141 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.831663 2023/08/09 15:48:08 - mmengine - INFO - Epoch(train) [115][230/442] lr: 5.000000e-04 eta: 4:08:21 time: 0.355968 data_time: 0.034230 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.839468 2023/08/09 15:48:11 - mmengine - INFO - Epoch(train) [115][240/442] lr: 5.000000e-04 eta: 4:08:16 time: 0.354972 data_time: 0.033823 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.813108 2023/08/09 15:48:15 - mmengine - INFO - Epoch(train) [115][250/442] lr: 5.000000e-04 eta: 4:08:12 time: 0.354825 data_time: 0.033697 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.810650 2023/08/09 15:48:18 - mmengine - INFO - Epoch(train) [115][260/442] lr: 5.000000e-04 eta: 4:08:07 time: 0.349707 data_time: 0.030111 memory: 4565 loss: 0.000993 loss_kpt: 0.000993 acc_pose: 0.886074 2023/08/09 15:48:21 - mmengine - INFO - Epoch(train) [115][270/442] lr: 5.000000e-04 eta: 4:08:02 time: 0.347494 data_time: 0.029768 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.847802 2023/08/09 15:48:25 - mmengine - INFO - Epoch(train) [115][280/442] lr: 5.000000e-04 eta: 4:07:58 time: 0.347367 data_time: 0.029760 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.897486 2023/08/09 15:48:28 - mmengine - INFO - Epoch(train) [115][290/442] lr: 5.000000e-04 eta: 4:07:54 time: 0.348251 data_time: 0.029831 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.810445 2023/08/09 15:48:32 - mmengine - INFO - Epoch(train) [115][300/442] lr: 5.000000e-04 eta: 4:07:51 time: 0.349901 data_time: 0.030245 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.814946 2023/08/09 15:48:35 - mmengine - INFO - Epoch(train) [115][310/442] lr: 5.000000e-04 eta: 4:07:46 time: 0.350019 data_time: 0.030147 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.786770 2023/08/09 15:48:39 - mmengine - INFO - Epoch(train) [115][320/442] lr: 5.000000e-04 eta: 4:07:41 time: 0.350108 data_time: 0.030422 memory: 4565 loss: 0.000983 loss_kpt: 0.000983 acc_pose: 0.822950 2023/08/09 15:48:42 - mmengine - INFO - Epoch(train) [115][330/442] lr: 5.000000e-04 eta: 4:07:36 time: 0.348980 data_time: 0.030092 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.796321 2023/08/09 15:48:46 - mmengine - INFO - Epoch(train) [115][340/442] lr: 5.000000e-04 eta: 4:07:33 time: 0.349869 data_time: 0.030086 memory: 4565 loss: 0.000983 loss_kpt: 0.000983 acc_pose: 0.846892 2023/08/09 15:48:50 - mmengine - INFO - Epoch(train) [115][350/442] lr: 5.000000e-04 eta: 4:07:32 time: 0.351594 data_time: 0.029818 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.843466 2023/08/09 15:48:53 - mmengine - INFO - Epoch(train) [115][360/442] lr: 5.000000e-04 eta: 4:07:29 time: 0.353436 data_time: 0.030227 memory: 4565 loss: 0.000995 loss_kpt: 0.000995 acc_pose: 0.822843 2023/08/09 15:48:57 - mmengine - INFO - Epoch(train) [115][370/442] lr: 5.000000e-04 eta: 4:07:28 time: 0.357649 data_time: 0.033321 memory: 4565 loss: 0.001002 loss_kpt: 0.001002 acc_pose: 0.834010 2023/08/09 15:49:00 - mmengine - INFO - Epoch(train) [115][380/442] lr: 5.000000e-04 eta: 4:07:24 time: 0.357973 data_time: 0.033579 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.842207 2023/08/09 15:49:04 - mmengine - INFO - Epoch(train) [115][390/442] lr: 5.000000e-04 eta: 4:07:19 time: 0.356946 data_time: 0.033571 memory: 4565 loss: 0.001006 loss_kpt: 0.001006 acc_pose: 0.771389 2023/08/09 15:49:07 - mmengine - INFO - Epoch(train) [115][400/442] lr: 5.000000e-04 eta: 4:07:15 time: 0.353314 data_time: 0.033733 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.852572 2023/08/09 15:49:11 - mmengine - INFO - Epoch(train) [115][410/442] lr: 5.000000e-04 eta: 4:07:10 time: 0.351689 data_time: 0.033429 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.819161 2023/08/09 15:49:14 - mmengine - INFO - Epoch(train) [115][420/442] lr: 5.000000e-04 eta: 4:07:07 time: 0.348892 data_time: 0.030567 memory: 4565 loss: 0.000993 loss_kpt: 0.000993 acc_pose: 0.804772 2023/08/09 15:49:18 - mmengine - INFO - Epoch(train) [115][430/442] lr: 5.000000e-04 eta: 4:07:04 time: 0.350913 data_time: 0.030460 memory: 4565 loss: 0.001000 loss_kpt: 0.001000 acc_pose: 0.865489 2023/08/09 15:49:21 - mmengine - INFO - Epoch(train) [115][440/442] lr: 5.000000e-04 eta: 4:07:00 time: 0.350881 data_time: 0.030458 memory: 4565 loss: 0.000989 loss_kpt: 0.000989 acc_pose: 0.828262 2023/08/09 15:49:22 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:49:26 - mmengine - INFO - Epoch(train) [116][ 10/442] lr: 5.000000e-04 eta: 4:06:55 time: 0.351567 data_time: 0.033916 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.855612 2023/08/09 15:49:29 - mmengine - INFO - Epoch(train) [116][ 20/442] lr: 5.000000e-04 eta: 4:06:48 time: 0.349418 data_time: 0.033799 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.768769 2023/08/09 15:49:32 - mmengine - INFO - Epoch(train) [116][ 30/442] lr: 5.000000e-04 eta: 4:06:43 time: 0.347332 data_time: 0.033866 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.895593 2023/08/09 15:49:36 - mmengine - INFO - Epoch(train) [116][ 40/442] lr: 5.000000e-04 eta: 4:06:38 time: 0.345051 data_time: 0.033828 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.847176 2023/08/09 15:49:39 - mmengine - INFO - Epoch(train) [116][ 50/442] lr: 5.000000e-04 eta: 4:06:34 time: 0.346284 data_time: 0.035009 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.708317 2023/08/09 15:49:43 - mmengine - INFO - Epoch(train) [116][ 60/442] lr: 5.000000e-04 eta: 4:06:28 time: 0.343201 data_time: 0.031237 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.857029 2023/08/09 15:49:46 - mmengine - INFO - Epoch(train) [116][ 70/442] lr: 5.000000e-04 eta: 4:06:22 time: 0.343679 data_time: 0.031234 memory: 4565 loss: 0.000971 loss_kpt: 0.000971 acc_pose: 0.879491 2023/08/09 15:49:50 - mmengine - INFO - Epoch(train) [116][ 80/442] lr: 5.000000e-04 eta: 4:06:17 time: 0.343900 data_time: 0.031057 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.799172 2023/08/09 15:49:53 - mmengine - INFO - Epoch(train) [116][ 90/442] lr: 5.000000e-04 eta: 4:06:12 time: 0.343354 data_time: 0.031043 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.847462 2023/08/09 15:49:57 - mmengine - INFO - Epoch(train) [116][100/442] lr: 5.000000e-04 eta: 4:06:08 time: 0.344177 data_time: 0.030445 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.846691 2023/08/09 15:50:00 - mmengine - INFO - Epoch(train) [116][110/442] lr: 5.000000e-04 eta: 4:06:03 time: 0.343934 data_time: 0.030316 memory: 4565 loss: 0.000953 loss_kpt: 0.000953 acc_pose: 0.842198 2023/08/09 15:50:03 - mmengine - INFO - Epoch(train) [116][120/442] lr: 5.000000e-04 eta: 4:05:58 time: 0.344831 data_time: 0.030858 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.776523 2023/08/09 15:50:07 - mmengine - INFO - Epoch(train) [116][130/442] lr: 5.000000e-04 eta: 4:05:54 time: 0.346109 data_time: 0.031395 memory: 4565 loss: 0.000971 loss_kpt: 0.000971 acc_pose: 0.857670 2023/08/09 15:50:10 - mmengine - INFO - Epoch(train) [116][140/442] lr: 5.000000e-04 eta: 4:05:50 time: 0.347625 data_time: 0.034368 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.742263 2023/08/09 15:50:14 - mmengine - INFO - Epoch(train) [116][150/442] lr: 5.000000e-04 eta: 4:05:44 time: 0.345218 data_time: 0.034347 memory: 4565 loss: 0.000995 loss_kpt: 0.000995 acc_pose: 0.844161 2023/08/09 15:50:17 - mmengine - INFO - Epoch(train) [116][160/442] lr: 5.000000e-04 eta: 4:05:38 time: 0.344300 data_time: 0.034337 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.817170 2023/08/09 15:50:21 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:50:21 - mmengine - INFO - Epoch(train) [116][170/442] lr: 5.000000e-04 eta: 4:05:32 time: 0.343465 data_time: 0.033951 memory: 4565 loss: 0.001000 loss_kpt: 0.001000 acc_pose: 0.858535 2023/08/09 15:50:24 - mmengine - INFO - Epoch(train) [116][180/442] lr: 5.000000e-04 eta: 4:05:27 time: 0.342148 data_time: 0.033617 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.854732 2023/08/09 15:50:28 - mmengine - INFO - Epoch(train) [116][190/442] lr: 5.000000e-04 eta: 4:05:24 time: 0.342488 data_time: 0.030889 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.823562 2023/08/09 15:50:31 - mmengine - INFO - Epoch(train) [116][200/442] lr: 5.000000e-04 eta: 4:05:19 time: 0.343611 data_time: 0.030896 memory: 4565 loss: 0.000972 loss_kpt: 0.000972 acc_pose: 0.840856 2023/08/09 15:50:34 - mmengine - INFO - Epoch(train) [116][210/442] lr: 5.000000e-04 eta: 4:05:14 time: 0.344649 data_time: 0.031291 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.702887 2023/08/09 15:50:38 - mmengine - INFO - Epoch(train) [116][220/442] lr: 5.000000e-04 eta: 4:05:07 time: 0.343907 data_time: 0.031375 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.821575 2023/08/09 15:50:41 - mmengine - INFO - Epoch(train) [116][230/442] lr: 5.000000e-04 eta: 4:05:02 time: 0.343428 data_time: 0.031226 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.904933 2023/08/09 15:50:45 - mmengine - INFO - Epoch(train) [116][240/442] lr: 5.000000e-04 eta: 4:04:56 time: 0.340004 data_time: 0.030889 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.760645 2023/08/09 15:50:48 - mmengine - INFO - Epoch(train) [116][250/442] lr: 5.000000e-04 eta: 4:04:51 time: 0.340114 data_time: 0.030967 memory: 4565 loss: 0.000974 loss_kpt: 0.000974 acc_pose: 0.888078 2023/08/09 15:50:52 - mmengine - INFO - Epoch(train) [116][260/442] lr: 5.000000e-04 eta: 4:04:49 time: 0.343572 data_time: 0.030552 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.832994 2023/08/09 15:50:55 - mmengine - INFO - Epoch(train) [116][270/442] lr: 5.000000e-04 eta: 4:04:45 time: 0.346985 data_time: 0.030526 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.839128 2023/08/09 15:50:59 - mmengine - INFO - Epoch(train) [116][280/442] lr: 5.000000e-04 eta: 4:04:40 time: 0.346575 data_time: 0.030519 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.825021 2023/08/09 15:51:02 - mmengine - INFO - Epoch(train) [116][290/442] lr: 5.000000e-04 eta: 4:04:33 time: 0.346126 data_time: 0.030473 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.825618 2023/08/09 15:51:05 - mmengine - INFO - Epoch(train) [116][300/442] lr: 5.000000e-04 eta: 4:04:27 time: 0.344441 data_time: 0.030315 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.791006 2023/08/09 15:51:09 - mmengine - INFO - Epoch(train) [116][310/442] lr: 5.000000e-04 eta: 4:04:21 time: 0.339546 data_time: 0.030303 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.776504 2023/08/09 15:51:12 - mmengine - INFO - Epoch(train) [116][320/442] lr: 5.000000e-04 eta: 4:04:17 time: 0.338308 data_time: 0.030279 memory: 4565 loss: 0.000974 loss_kpt: 0.000974 acc_pose: 0.883234 2023/08/09 15:51:16 - mmengine - INFO - Epoch(train) [116][330/442] lr: 5.000000e-04 eta: 4:04:14 time: 0.341565 data_time: 0.033418 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.837722 2023/08/09 15:51:19 - mmengine - INFO - Epoch(train) [116][340/442] lr: 5.000000e-04 eta: 4:04:10 time: 0.344462 data_time: 0.034049 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.864201 2023/08/09 15:51:22 - mmengine - INFO - Epoch(train) [116][350/442] lr: 5.000000e-04 eta: 4:04:04 time: 0.344869 data_time: 0.034694 memory: 4565 loss: 0.001010 loss_kpt: 0.001010 acc_pose: 0.766956 2023/08/09 15:51:26 - mmengine - INFO - Epoch(train) [116][360/442] lr: 5.000000e-04 eta: 4:03:58 time: 0.345394 data_time: 0.035352 memory: 4565 loss: 0.001031 loss_kpt: 0.001031 acc_pose: 0.802322 2023/08/09 15:51:29 - mmengine - INFO - Epoch(train) [116][370/442] lr: 5.000000e-04 eta: 4:03:52 time: 0.343657 data_time: 0.035205 memory: 4565 loss: 0.001026 loss_kpt: 0.001026 acc_pose: 0.832695 2023/08/09 15:51:33 - mmengine - INFO - Epoch(train) [116][380/442] lr: 5.000000e-04 eta: 4:03:47 time: 0.340248 data_time: 0.032110 memory: 4565 loss: 0.001022 loss_kpt: 0.001022 acc_pose: 0.825353 2023/08/09 15:51:36 - mmengine - INFO - Epoch(train) [116][390/442] lr: 5.000000e-04 eta: 4:03:42 time: 0.338799 data_time: 0.031661 memory: 4565 loss: 0.001021 loss_kpt: 0.001021 acc_pose: 0.772381 2023/08/09 15:51:39 - mmengine - INFO - Epoch(train) [116][400/442] lr: 5.000000e-04 eta: 4:03:37 time: 0.340111 data_time: 0.030965 memory: 4565 loss: 0.001013 loss_kpt: 0.001013 acc_pose: 0.779983 2023/08/09 15:51:43 - mmengine - INFO - Epoch(train) [116][410/442] lr: 5.000000e-04 eta: 4:03:33 time: 0.341763 data_time: 0.030439 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.832302 2023/08/09 15:51:46 - mmengine - INFO - Epoch(train) [116][420/442] lr: 5.000000e-04 eta: 4:03:29 time: 0.344576 data_time: 0.030457 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.823220 2023/08/09 15:51:50 - mmengine - INFO - Epoch(train) [116][430/442] lr: 5.000000e-04 eta: 4:03:25 time: 0.345679 data_time: 0.030417 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.845638 2023/08/09 15:51:53 - mmengine - INFO - Epoch(train) [116][440/442] lr: 5.000000e-04 eta: 4:03:19 time: 0.345179 data_time: 0.030195 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.809379 2023/08/09 15:51:54 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:51:58 - mmengine - INFO - Epoch(train) [117][ 10/442] lr: 5.000000e-04 eta: 4:03:17 time: 0.348449 data_time: 0.033861 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.887618 2023/08/09 15:52:01 - mmengine - INFO - Epoch(train) [117][ 20/442] lr: 5.000000e-04 eta: 4:03:13 time: 0.350629 data_time: 0.033828 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.813078 2023/08/09 15:52:05 - mmengine - INFO - Epoch(train) [117][ 30/442] lr: 5.000000e-04 eta: 4:03:11 time: 0.351319 data_time: 0.033999 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.802258 2023/08/09 15:52:08 - mmengine - INFO - Epoch(train) [117][ 40/442] lr: 5.000000e-04 eta: 4:03:06 time: 0.352121 data_time: 0.033989 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.801342 2023/08/09 15:52:12 - mmengine - INFO - Epoch(train) [117][ 50/442] lr: 5.000000e-04 eta: 4:03:02 time: 0.354470 data_time: 0.034406 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.842568 2023/08/09 15:52:15 - mmengine - INFO - Epoch(train) [117][ 60/442] lr: 5.000000e-04 eta: 4:02:58 time: 0.349682 data_time: 0.030326 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.801962 2023/08/09 15:52:19 - mmengine - INFO - Epoch(train) [117][ 70/442] lr: 5.000000e-04 eta: 4:02:57 time: 0.352327 data_time: 0.030164 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.805385 2023/08/09 15:52:22 - mmengine - INFO - Epoch(train) [117][ 80/442] lr: 5.000000e-04 eta: 4:02:53 time: 0.351284 data_time: 0.030250 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.800629 2023/08/09 15:52:26 - mmengine - INFO - Epoch(train) [117][ 90/442] lr: 5.000000e-04 eta: 4:02:51 time: 0.353854 data_time: 0.031193 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.797389 2023/08/09 15:52:30 - mmengine - INFO - Epoch(train) [117][100/442] lr: 5.000000e-04 eta: 4:02:49 time: 0.356713 data_time: 0.031745 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.855776 2023/08/09 15:52:33 - mmengine - INFO - Epoch(train) [117][110/442] lr: 5.000000e-04 eta: 4:02:44 time: 0.356883 data_time: 0.031599 memory: 4565 loss: 0.001004 loss_kpt: 0.001004 acc_pose: 0.759204 2023/08/09 15:52:36 - mmengine - INFO - Epoch(train) [117][120/442] lr: 5.000000e-04 eta: 4:02:40 time: 0.352292 data_time: 0.031581 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.761424 2023/08/09 15:52:40 - mmengine - INFO - Epoch(train) [117][130/442] lr: 5.000000e-04 eta: 4:02:36 time: 0.352366 data_time: 0.031222 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.854807 2023/08/09 15:52:43 - mmengine - INFO - Epoch(train) [117][140/442] lr: 5.000000e-04 eta: 4:02:32 time: 0.349968 data_time: 0.030487 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.796692 2023/08/09 15:52:47 - mmengine - INFO - Epoch(train) [117][150/442] lr: 5.000000e-04 eta: 4:02:30 time: 0.349579 data_time: 0.030642 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.828412 2023/08/09 15:52:51 - mmengine - INFO - Epoch(train) [117][160/442] lr: 5.000000e-04 eta: 4:02:26 time: 0.350899 data_time: 0.031087 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.842786 2023/08/09 15:52:54 - mmengine - INFO - Epoch(train) [117][170/442] lr: 5.000000e-04 eta: 4:02:25 time: 0.356008 data_time: 0.031566 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.846595 2023/08/09 15:52:58 - mmengine - INFO - Epoch(train) [117][180/442] lr: 5.000000e-04 eta: 4:02:21 time: 0.355403 data_time: 0.031728 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.798939 2023/08/09 15:53:01 - mmengine - INFO - Epoch(train) [117][190/442] lr: 5.000000e-04 eta: 4:02:17 time: 0.355257 data_time: 0.031391 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.727049 2023/08/09 15:53:05 - mmengine - INFO - Epoch(train) [117][200/442] lr: 5.000000e-04 eta: 4:02:13 time: 0.352827 data_time: 0.030650 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.867935 2023/08/09 15:53:08 - mmengine - INFO - Epoch(train) [117][210/442] lr: 5.000000e-04 eta: 4:02:09 time: 0.351839 data_time: 0.030299 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.816410 2023/08/09 15:53:12 - mmengine - INFO - Epoch(train) [117][220/442] lr: 5.000000e-04 eta: 4:02:07 time: 0.350180 data_time: 0.030268 memory: 4565 loss: 0.000995 loss_kpt: 0.000995 acc_pose: 0.840391 2023/08/09 15:53:15 - mmengine - INFO - Epoch(train) [117][230/442] lr: 5.000000e-04 eta: 4:02:04 time: 0.351335 data_time: 0.030190 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.772001 2023/08/09 15:53:19 - mmengine - INFO - Epoch(train) [117][240/442] lr: 5.000000e-04 eta: 4:02:07 time: 0.361393 data_time: 0.033894 memory: 4565 loss: 0.000995 loss_kpt: 0.000995 acc_pose: 0.895458 2023/08/09 15:53:23 - mmengine - INFO - Epoch(train) [117][250/442] lr: 5.000000e-04 eta: 4:02:08 time: 0.368823 data_time: 0.034025 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.830540 2023/08/09 15:53:27 - mmengine - INFO - Epoch(train) [117][260/442] lr: 5.000000e-04 eta: 4:02:08 time: 0.375406 data_time: 0.034449 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.838280 2023/08/09 15:53:30 - mmengine - INFO - Epoch(train) [117][270/442] lr: 5.000000e-04 eta: 4:02:05 time: 0.373855 data_time: 0.034089 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.804290 2023/08/09 15:53:34 - mmengine - INFO - Epoch(train) [117][280/442] lr: 5.000000e-04 eta: 4:02:02 time: 0.373860 data_time: 0.034183 memory: 4565 loss: 0.000970 loss_kpt: 0.000970 acc_pose: 0.862396 2023/08/09 15:53:38 - mmengine - INFO - Epoch(train) [117][290/442] lr: 5.000000e-04 eta: 4:01:58 time: 0.365182 data_time: 0.030921 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.808620 2023/08/09 15:53:41 - mmengine - INFO - Epoch(train) [117][300/442] lr: 5.000000e-04 eta: 4:01:56 time: 0.359756 data_time: 0.031037 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.828999 2023/08/09 15:53:45 - mmengine - INFO - Epoch(train) [117][310/442] lr: 5.000000e-04 eta: 4:01:52 time: 0.354257 data_time: 0.031044 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.786482 2023/08/09 15:53:48 - mmengine - INFO - Epoch(train) [117][320/442] lr: 5.000000e-04 eta: 4:01:48 time: 0.353101 data_time: 0.031412 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.786921 2023/08/09 15:53:52 - mmengine - INFO - Epoch(train) [117][330/442] lr: 5.000000e-04 eta: 4:01:46 time: 0.354919 data_time: 0.031836 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.803678 2023/08/09 15:53:55 - mmengine - INFO - Epoch(train) [117][340/442] lr: 5.000000e-04 eta: 4:01:43 time: 0.354740 data_time: 0.032035 memory: 4565 loss: 0.001004 loss_kpt: 0.001004 acc_pose: 0.838815 2023/08/09 15:53:59 - mmengine - INFO - Epoch(train) [117][350/442] lr: 5.000000e-04 eta: 4:01:40 time: 0.354934 data_time: 0.032486 memory: 4565 loss: 0.001002 loss_kpt: 0.001002 acc_pose: 0.895790 2023/08/09 15:54:02 - mmengine - INFO - Epoch(train) [117][360/442] lr: 5.000000e-04 eta: 4:01:37 time: 0.354902 data_time: 0.032604 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.844359 2023/08/09 15:54:06 - mmengine - INFO - Epoch(train) [117][370/442] lr: 5.000000e-04 eta: 4:01:35 time: 0.357563 data_time: 0.032760 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.766767 2023/08/09 15:54:10 - mmengine - INFO - Epoch(train) [117][380/442] lr: 5.000000e-04 eta: 4:01:31 time: 0.355283 data_time: 0.032542 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.859496 2023/08/09 15:54:13 - mmengine - INFO - Epoch(train) [117][390/442] lr: 5.000000e-04 eta: 4:01:29 time: 0.357668 data_time: 0.035633 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.766574 2023/08/09 15:54:17 - mmengine - INFO - Epoch(train) [117][400/442] lr: 5.000000e-04 eta: 4:01:27 time: 0.358874 data_time: 0.038101 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.802303 2023/08/09 15:54:20 - mmengine - INFO - Epoch(train) [117][410/442] lr: 5.000000e-04 eta: 4:01:24 time: 0.359066 data_time: 0.037695 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.839378 2023/08/09 15:54:24 - mmengine - INFO - Epoch(train) [117][420/442] lr: 5.000000e-04 eta: 4:01:21 time: 0.358303 data_time: 0.037271 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.814517 2023/08/09 15:54:27 - mmengine - INFO - Epoch(train) [117][430/442] lr: 5.000000e-04 eta: 4:01:18 time: 0.358918 data_time: 0.036945 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.788852 2023/08/09 15:54:31 - mmengine - INFO - Epoch(train) [117][440/442] lr: 5.000000e-04 eta: 4:01:14 time: 0.355809 data_time: 0.033462 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.758679 2023/08/09 15:54:32 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:54:35 - mmengine - INFO - Epoch(train) [118][ 10/442] lr: 5.000000e-04 eta: 4:01:10 time: 0.354417 data_time: 0.033665 memory: 4565 loss: 0.000990 loss_kpt: 0.000990 acc_pose: 0.870379 2023/08/09 15:54:39 - mmengine - INFO - Epoch(train) [118][ 20/442] lr: 5.000000e-04 eta: 4:01:05 time: 0.351287 data_time: 0.033377 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.778190 2023/08/09 15:54:42 - mmengine - INFO - Epoch(train) [118][ 30/442] lr: 5.000000e-04 eta: 4:01:00 time: 0.348083 data_time: 0.033497 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.847469 2023/08/09 15:54:45 - mmengine - INFO - Epoch(train) [118][ 40/442] lr: 5.000000e-04 eta: 4:00:55 time: 0.345371 data_time: 0.033941 memory: 4565 loss: 0.000970 loss_kpt: 0.000970 acc_pose: 0.795001 2023/08/09 15:54:49 - mmengine - INFO - Epoch(train) [118][ 50/442] lr: 5.000000e-04 eta: 4:00:53 time: 0.350320 data_time: 0.034766 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.875314 2023/08/09 15:54:53 - mmengine - INFO - Epoch(train) [118][ 60/442] lr: 5.000000e-04 eta: 4:00:51 time: 0.350070 data_time: 0.031494 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.780355 2023/08/09 15:54:56 - mmengine - INFO - Epoch(train) [118][ 70/442] lr: 5.000000e-04 eta: 4:00:46 time: 0.349285 data_time: 0.031582 memory: 4565 loss: 0.000970 loss_kpt: 0.000970 acc_pose: 0.812451 2023/08/09 15:55:00 - mmengine - INFO - Epoch(train) [118][ 80/442] lr: 5.000000e-04 eta: 4:00:41 time: 0.349829 data_time: 0.031556 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.760625 2023/08/09 15:55:03 - mmengine - INFO - Epoch(train) [118][ 90/442] lr: 5.000000e-04 eta: 4:00:36 time: 0.349054 data_time: 0.030913 memory: 4565 loss: 0.001005 loss_kpt: 0.001005 acc_pose: 0.731116 2023/08/09 15:55:06 - mmengine - INFO - Epoch(train) [118][100/442] lr: 5.000000e-04 eta: 4:00:31 time: 0.344242 data_time: 0.030560 memory: 4565 loss: 0.001002 loss_kpt: 0.001002 acc_pose: 0.826070 2023/08/09 15:55:10 - mmengine - INFO - Epoch(train) [118][110/442] lr: 5.000000e-04 eta: 4:00:26 time: 0.339310 data_time: 0.030077 memory: 4565 loss: 0.001012 loss_kpt: 0.001012 acc_pose: 0.848847 2023/08/09 15:55:13 - mmengine - INFO - Epoch(train) [118][120/442] lr: 5.000000e-04 eta: 4:00:21 time: 0.340271 data_time: 0.030678 memory: 4565 loss: 0.001014 loss_kpt: 0.001014 acc_pose: 0.812565 2023/08/09 15:55:17 - mmengine - INFO - Epoch(train) [118][130/442] lr: 5.000000e-04 eta: 4:00:19 time: 0.344858 data_time: 0.034791 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.823320 2023/08/09 15:55:20 - mmengine - INFO - Epoch(train) [118][140/442] lr: 5.000000e-04 eta: 4:00:14 time: 0.344951 data_time: 0.035708 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.804733 2023/08/09 15:55:24 - mmengine - INFO - Epoch(train) [118][150/442] lr: 5.000000e-04 eta: 4:00:09 time: 0.344908 data_time: 0.036358 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.880506 2023/08/09 15:55:27 - mmengine - INFO - Epoch(train) [118][160/442] lr: 5.000000e-04 eta: 4:00:03 time: 0.344574 data_time: 0.036378 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.727700 2023/08/09 15:55:30 - mmengine - INFO - Epoch(train) [118][170/442] lr: 5.000000e-04 eta: 3:59:58 time: 0.343996 data_time: 0.035718 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.793995 2023/08/09 15:55:34 - mmengine - INFO - Epoch(train) [118][180/442] lr: 5.000000e-04 eta: 3:59:54 time: 0.339636 data_time: 0.031943 memory: 4565 loss: 0.000970 loss_kpt: 0.000970 acc_pose: 0.835475 2023/08/09 15:55:37 - mmengine - INFO - Epoch(train) [118][190/442] lr: 5.000000e-04 eta: 3:59:49 time: 0.340117 data_time: 0.031307 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.860531 2023/08/09 15:55:41 - mmengine - INFO - Epoch(train) [118][200/442] lr: 5.000000e-04 eta: 3:59:45 time: 0.341261 data_time: 0.030679 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.755757 2023/08/09 15:55:44 - mmengine - INFO - Epoch(train) [118][210/442] lr: 5.000000e-04 eta: 3:59:41 time: 0.343667 data_time: 0.030773 memory: 4565 loss: 0.001001 loss_kpt: 0.001001 acc_pose: 0.803952 2023/08/09 15:55:48 - mmengine - INFO - Epoch(train) [118][220/442] lr: 5.000000e-04 eta: 3:59:36 time: 0.343503 data_time: 0.030807 memory: 4565 loss: 0.001017 loss_kpt: 0.001017 acc_pose: 0.848927 2023/08/09 15:55:51 - mmengine - INFO - Epoch(train) [118][230/442] lr: 5.000000e-04 eta: 3:59:30 time: 0.342295 data_time: 0.030358 memory: 4565 loss: 0.001026 loss_kpt: 0.001026 acc_pose: 0.812681 2023/08/09 15:55:54 - mmengine - INFO - Epoch(train) [118][240/442] lr: 5.000000e-04 eta: 3:59:26 time: 0.342436 data_time: 0.030138 memory: 4565 loss: 0.001025 loss_kpt: 0.001025 acc_pose: 0.798245 2023/08/09 15:55:58 - mmengine - INFO - Epoch(train) [118][250/442] lr: 5.000000e-04 eta: 3:59:21 time: 0.342132 data_time: 0.030089 memory: 4565 loss: 0.001008 loss_kpt: 0.001008 acc_pose: 0.755957 2023/08/09 15:56:01 - mmengine - INFO - Epoch(train) [118][260/442] lr: 5.000000e-04 eta: 3:59:17 time: 0.340635 data_time: 0.030095 memory: 4565 loss: 0.001000 loss_kpt: 0.001000 acc_pose: 0.775332 2023/08/09 15:56:05 - mmengine - INFO - Epoch(train) [118][270/442] lr: 5.000000e-04 eta: 3:59:13 time: 0.342989 data_time: 0.030395 memory: 4565 loss: 0.000974 loss_kpt: 0.000974 acc_pose: 0.799631 2023/08/09 15:56:08 - mmengine - INFO - Epoch(train) [118][280/442] lr: 5.000000e-04 eta: 3:59:08 time: 0.344133 data_time: 0.030506 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.746893 2023/08/09 15:56:10 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:56:12 - mmengine - INFO - Epoch(train) [118][290/442] lr: 5.000000e-04 eta: 3:59:05 time: 0.347066 data_time: 0.030398 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.821243 2023/08/09 15:56:15 - mmengine - INFO - Epoch(train) [118][300/442] lr: 5.000000e-04 eta: 3:59:01 time: 0.346816 data_time: 0.030332 memory: 4565 loss: 0.000989 loss_kpt: 0.000989 acc_pose: 0.844815 2023/08/09 15:56:19 - mmengine - INFO - Epoch(train) [118][310/442] lr: 5.000000e-04 eta: 3:58:56 time: 0.346845 data_time: 0.030287 memory: 4565 loss: 0.000993 loss_kpt: 0.000993 acc_pose: 0.892833 2023/08/09 15:56:22 - mmengine - INFO - Epoch(train) [118][320/442] lr: 5.000000e-04 eta: 3:58:53 time: 0.348669 data_time: 0.030355 memory: 4565 loss: 0.001005 loss_kpt: 0.001005 acc_pose: 0.876117 2023/08/09 15:56:26 - mmengine - INFO - Epoch(train) [118][330/442] lr: 5.000000e-04 eta: 3:58:49 time: 0.348860 data_time: 0.030619 memory: 4565 loss: 0.000990 loss_kpt: 0.000990 acc_pose: 0.873462 2023/08/09 15:56:29 - mmengine - INFO - Epoch(train) [118][340/442] lr: 5.000000e-04 eta: 3:58:45 time: 0.347301 data_time: 0.030906 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.817331 2023/08/09 15:56:33 - mmengine - INFO - Epoch(train) [118][350/442] lr: 5.000000e-04 eta: 3:58:43 time: 0.350752 data_time: 0.031038 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.744889 2023/08/09 15:56:36 - mmengine - INFO - Epoch(train) [118][360/442] lr: 5.000000e-04 eta: 3:58:38 time: 0.350909 data_time: 0.031066 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.815917 2023/08/09 15:56:40 - mmengine - INFO - Epoch(train) [118][370/442] lr: 5.000000e-04 eta: 3:58:35 time: 0.350593 data_time: 0.030836 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.867216 2023/08/09 15:56:43 - mmengine - INFO - Epoch(train) [118][380/442] lr: 5.000000e-04 eta: 3:58:31 time: 0.350323 data_time: 0.030743 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.745428 2023/08/09 15:56:47 - mmengine - INFO - Epoch(train) [118][390/442] lr: 5.000000e-04 eta: 3:58:27 time: 0.349496 data_time: 0.030888 memory: 4565 loss: 0.000970 loss_kpt: 0.000970 acc_pose: 0.733862 2023/08/09 15:56:50 - mmengine - INFO - Epoch(train) [118][400/442] lr: 5.000000e-04 eta: 3:58:24 time: 0.349598 data_time: 0.030964 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.736343 2023/08/09 15:56:54 - mmengine - INFO - Epoch(train) [118][410/442] lr: 5.000000e-04 eta: 3:58:20 time: 0.350474 data_time: 0.031084 memory: 4565 loss: 0.001006 loss_kpt: 0.001006 acc_pose: 0.904052 2023/08/09 15:56:57 - mmengine - INFO - Epoch(train) [118][420/442] lr: 5.000000e-04 eta: 3:58:15 time: 0.346793 data_time: 0.031050 memory: 4565 loss: 0.001012 loss_kpt: 0.001012 acc_pose: 0.876011 2023/08/09 15:57:00 - mmengine - INFO - Epoch(train) [118][430/442] lr: 5.000000e-04 eta: 3:58:10 time: 0.346273 data_time: 0.031033 memory: 4565 loss: 0.001000 loss_kpt: 0.001000 acc_pose: 0.828564 2023/08/09 15:57:04 - mmengine - INFO - Epoch(train) [118][440/442] lr: 5.000000e-04 eta: 3:58:05 time: 0.344545 data_time: 0.030821 memory: 4565 loss: 0.000989 loss_kpt: 0.000989 acc_pose: 0.848556 2023/08/09 15:57:04 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:57:08 - mmengine - INFO - Epoch(train) [119][ 10/442] lr: 5.000000e-04 eta: 3:58:03 time: 0.346332 data_time: 0.034707 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.737103 2023/08/09 15:57:12 - mmengine - INFO - Epoch(train) [119][ 20/442] lr: 5.000000e-04 eta: 3:57:59 time: 0.347290 data_time: 0.035725 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.864950 2023/08/09 15:57:15 - mmengine - INFO - Epoch(train) [119][ 30/442] lr: 5.000000e-04 eta: 3:57:56 time: 0.349821 data_time: 0.035705 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.734701 2023/08/09 15:57:19 - mmengine - INFO - Epoch(train) [119][ 40/442] lr: 5.000000e-04 eta: 3:57:51 time: 0.350006 data_time: 0.035566 memory: 4565 loss: 0.000999 loss_kpt: 0.000999 acc_pose: 0.772062 2023/08/09 15:57:22 - mmengine - INFO - Epoch(train) [119][ 50/442] lr: 5.000000e-04 eta: 3:57:46 time: 0.350296 data_time: 0.035841 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.843778 2023/08/09 15:57:25 - mmengine - INFO - Epoch(train) [119][ 60/442] lr: 5.000000e-04 eta: 3:57:41 time: 0.341738 data_time: 0.031327 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.807645 2023/08/09 15:57:29 - mmengine - INFO - Epoch(train) [119][ 70/442] lr: 5.000000e-04 eta: 3:57:35 time: 0.340273 data_time: 0.030311 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.788174 2023/08/09 15:57:32 - mmengine - INFO - Epoch(train) [119][ 80/442] lr: 5.000000e-04 eta: 3:57:31 time: 0.338720 data_time: 0.030231 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.864224 2023/08/09 15:57:36 - mmengine - INFO - Epoch(train) [119][ 90/442] lr: 5.000000e-04 eta: 3:57:27 time: 0.339979 data_time: 0.030566 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.823581 2023/08/09 15:57:39 - mmengine - INFO - Epoch(train) [119][100/442] lr: 5.000000e-04 eta: 3:57:25 time: 0.345178 data_time: 0.031153 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.829021 2023/08/09 15:57:43 - mmengine - INFO - Epoch(train) [119][110/442] lr: 5.000000e-04 eta: 3:57:20 time: 0.345412 data_time: 0.031296 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.817395 2023/08/09 15:57:46 - mmengine - INFO - Epoch(train) [119][120/442] lr: 5.000000e-04 eta: 3:57:15 time: 0.346292 data_time: 0.031200 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.883918 2023/08/09 15:57:49 - mmengine - INFO - Epoch(train) [119][130/442] lr: 5.000000e-04 eta: 3:57:10 time: 0.345600 data_time: 0.031418 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.763440 2023/08/09 15:57:53 - mmengine - INFO - Epoch(train) [119][140/442] lr: 5.000000e-04 eta: 3:57:06 time: 0.344414 data_time: 0.031035 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.859176 2023/08/09 15:57:57 - mmengine - INFO - Epoch(train) [119][150/442] lr: 5.000000e-04 eta: 3:57:04 time: 0.344995 data_time: 0.030665 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.767723 2023/08/09 15:58:00 - mmengine - INFO - Epoch(train) [119][160/442] lr: 5.000000e-04 eta: 3:57:04 time: 0.355090 data_time: 0.031030 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.748011 2023/08/09 15:58:04 - mmengine - INFO - Epoch(train) [119][170/442] lr: 5.000000e-04 eta: 3:57:01 time: 0.357873 data_time: 0.031444 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.885578 2023/08/09 15:58:07 - mmengine - INFO - Epoch(train) [119][180/442] lr: 5.000000e-04 eta: 3:56:57 time: 0.357794 data_time: 0.031174 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.705824 2023/08/09 15:58:11 - mmengine - INFO - Epoch(train) [119][190/442] lr: 5.000000e-04 eta: 3:56:52 time: 0.358051 data_time: 0.031187 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.882423 2023/08/09 15:58:14 - mmengine - INFO - Epoch(train) [119][200/442] lr: 5.000000e-04 eta: 3:56:47 time: 0.353069 data_time: 0.030925 memory: 4565 loss: 0.001013 loss_kpt: 0.001013 acc_pose: 0.804278 2023/08/09 15:58:18 - mmengine - INFO - Epoch(train) [119][210/442] lr: 5.000000e-04 eta: 3:56:43 time: 0.343620 data_time: 0.030593 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.847524 2023/08/09 15:58:21 - mmengine - INFO - Epoch(train) [119][220/442] lr: 5.000000e-04 eta: 3:56:41 time: 0.346004 data_time: 0.030617 memory: 4565 loss: 0.001007 loss_kpt: 0.001007 acc_pose: 0.754076 2023/08/09 15:58:25 - mmengine - INFO - Epoch(train) [119][230/442] lr: 5.000000e-04 eta: 3:56:37 time: 0.347920 data_time: 0.030809 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.839707 2023/08/09 15:58:28 - mmengine - INFO - Epoch(train) [119][240/442] lr: 5.000000e-04 eta: 3:56:35 time: 0.352561 data_time: 0.034276 memory: 4565 loss: 0.001015 loss_kpt: 0.001015 acc_pose: 0.831614 2023/08/09 15:58:32 - mmengine - INFO - Epoch(train) [119][250/442] lr: 5.000000e-04 eta: 3:56:30 time: 0.352502 data_time: 0.034342 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.807370 2023/08/09 15:58:35 - mmengine - INFO - Epoch(train) [119][260/442] lr: 5.000000e-04 eta: 3:56:25 time: 0.351779 data_time: 0.034296 memory: 4565 loss: 0.001001 loss_kpt: 0.001001 acc_pose: 0.813396 2023/08/09 15:58:39 - mmengine - INFO - Epoch(train) [119][270/442] lr: 5.000000e-04 eta: 3:56:21 time: 0.345693 data_time: 0.033915 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.776833 2023/08/09 15:58:42 - mmengine - INFO - Epoch(train) [119][280/442] lr: 5.000000e-04 eta: 3:56:16 time: 0.343770 data_time: 0.034095 memory: 4565 loss: 0.000983 loss_kpt: 0.000983 acc_pose: 0.824297 2023/08/09 15:58:45 - mmengine - INFO - Epoch(train) [119][290/442] lr: 5.000000e-04 eta: 3:56:11 time: 0.339272 data_time: 0.030689 memory: 4565 loss: 0.000972 loss_kpt: 0.000972 acc_pose: 0.752033 2023/08/09 15:58:49 - mmengine - INFO - Epoch(train) [119][300/442] lr: 5.000000e-04 eta: 3:56:07 time: 0.340131 data_time: 0.031213 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.798126 2023/08/09 15:58:52 - mmengine - INFO - Epoch(train) [119][310/442] lr: 5.000000e-04 eta: 3:56:03 time: 0.341978 data_time: 0.031341 memory: 4565 loss: 0.000998 loss_kpt: 0.000998 acc_pose: 0.845081 2023/08/09 15:58:56 - mmengine - INFO - Epoch(train) [119][320/442] lr: 5.000000e-04 eta: 3:55:58 time: 0.342043 data_time: 0.031299 memory: 4565 loss: 0.001005 loss_kpt: 0.001005 acc_pose: 0.735866 2023/08/09 15:58:59 - mmengine - INFO - Epoch(train) [119][330/442] lr: 5.000000e-04 eta: 3:55:53 time: 0.341453 data_time: 0.030945 memory: 4565 loss: 0.001009 loss_kpt: 0.001009 acc_pose: 0.740864 2023/08/09 15:59:03 - mmengine - INFO - Epoch(train) [119][340/442] lr: 5.000000e-04 eta: 3:55:50 time: 0.343873 data_time: 0.030842 memory: 4565 loss: 0.001012 loss_kpt: 0.001012 acc_pose: 0.774552 2023/08/09 15:59:06 - mmengine - INFO - Epoch(train) [119][350/442] lr: 5.000000e-04 eta: 3:55:46 time: 0.343703 data_time: 0.030360 memory: 4565 loss: 0.001022 loss_kpt: 0.001022 acc_pose: 0.852844 2023/08/09 15:59:09 - mmengine - INFO - Epoch(train) [119][360/442] lr: 5.000000e-04 eta: 3:55:42 time: 0.343600 data_time: 0.030328 memory: 4565 loss: 0.000998 loss_kpt: 0.000998 acc_pose: 0.808880 2023/08/09 15:59:13 - mmengine - INFO - Epoch(train) [119][370/442] lr: 5.000000e-04 eta: 3:55:38 time: 0.344887 data_time: 0.030688 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.870722 2023/08/09 15:59:16 - mmengine - INFO - Epoch(train) [119][380/442] lr: 5.000000e-04 eta: 3:55:35 time: 0.349110 data_time: 0.030869 memory: 4565 loss: 0.000995 loss_kpt: 0.000995 acc_pose: 0.906168 2023/08/09 15:59:20 - mmengine - INFO - Epoch(train) [119][390/442] lr: 5.000000e-04 eta: 3:55:30 time: 0.346787 data_time: 0.030907 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.744724 2023/08/09 15:59:23 - mmengine - INFO - Epoch(train) [119][400/442] lr: 5.000000e-04 eta: 3:55:26 time: 0.346042 data_time: 0.030890 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.840278 2023/08/09 15:59:27 - mmengine - INFO - Epoch(train) [119][410/442] lr: 5.000000e-04 eta: 3:55:21 time: 0.345452 data_time: 0.030767 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.846933 2023/08/09 15:59:30 - mmengine - INFO - Epoch(train) [119][420/442] lr: 5.000000e-04 eta: 3:55:18 time: 0.346500 data_time: 0.030717 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.794726 2023/08/09 15:59:34 - mmengine - INFO - Epoch(train) [119][430/442] lr: 5.000000e-04 eta: 3:55:14 time: 0.344610 data_time: 0.030745 memory: 4565 loss: 0.001008 loss_kpt: 0.001008 acc_pose: 0.796083 2023/08/09 15:59:37 - mmengine - INFO - Epoch(train) [119][440/442] lr: 5.000000e-04 eta: 3:55:10 time: 0.345599 data_time: 0.031480 memory: 4565 loss: 0.001025 loss_kpt: 0.001025 acc_pose: 0.834050 2023/08/09 15:59:38 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 15:59:42 - mmengine - INFO - Epoch(train) [120][ 10/442] lr: 5.000000e-04 eta: 3:55:07 time: 0.350553 data_time: 0.035518 memory: 4565 loss: 0.001024 loss_kpt: 0.001024 acc_pose: 0.725667 2023/08/09 15:59:45 - mmengine - INFO - Epoch(train) [120][ 20/442] lr: 5.000000e-04 eta: 3:55:02 time: 0.349201 data_time: 0.035853 memory: 4565 loss: 0.001008 loss_kpt: 0.001008 acc_pose: 0.837995 2023/08/09 15:59:48 - mmengine - INFO - Epoch(train) [120][ 30/442] lr: 5.000000e-04 eta: 3:54:59 time: 0.350215 data_time: 0.036046 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.886662 2023/08/09 15:59:52 - mmengine - INFO - Epoch(train) [120][ 40/442] lr: 5.000000e-04 eta: 3:54:55 time: 0.349789 data_time: 0.036340 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.830104 2023/08/09 15:59:55 - mmengine - INFO - Epoch(train) [120][ 50/442] lr: 5.000000e-04 eta: 3:54:51 time: 0.348932 data_time: 0.036320 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.870681 2023/08/09 15:59:59 - mmengine - INFO - Epoch(train) [120][ 60/442] lr: 5.000000e-04 eta: 3:54:47 time: 0.345567 data_time: 0.032482 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.769473 2023/08/09 16:00:02 - mmengine - INFO - Epoch(train) [120][ 70/442] lr: 5.000000e-04 eta: 3:54:44 time: 0.348123 data_time: 0.032351 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.833169 2023/08/09 16:00:06 - mmengine - INFO - Epoch(train) [120][ 80/442] lr: 5.000000e-04 eta: 3:54:39 time: 0.345762 data_time: 0.031744 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.810727 2023/08/09 16:00:09 - mmengine - INFO - Epoch(train) [120][ 90/442] lr: 5.000000e-04 eta: 3:54:35 time: 0.344924 data_time: 0.031295 memory: 4565 loss: 0.000974 loss_kpt: 0.000974 acc_pose: 0.828470 2023/08/09 16:00:13 - mmengine - INFO - Epoch(train) [120][100/442] lr: 5.000000e-04 eta: 3:54:30 time: 0.344691 data_time: 0.030902 memory: 4565 loss: 0.000980 loss_kpt: 0.000980 acc_pose: 0.692965 2023/08/09 16:00:16 - mmengine - INFO - Epoch(train) [120][110/442] lr: 5.000000e-04 eta: 3:54:27 time: 0.346780 data_time: 0.030591 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.784451 2023/08/09 16:00:20 - mmengine - INFO - Epoch(train) [120][120/442] lr: 5.000000e-04 eta: 3:54:24 time: 0.346018 data_time: 0.030447 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.824519 2023/08/09 16:00:23 - mmengine - INFO - Epoch(train) [120][130/442] lr: 5.000000e-04 eta: 3:54:20 time: 0.347203 data_time: 0.030955 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.841883 2023/08/09 16:00:27 - mmengine - INFO - Epoch(train) [120][140/442] lr: 5.000000e-04 eta: 3:54:16 time: 0.349178 data_time: 0.031226 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.890789 2023/08/09 16:00:30 - mmengine - INFO - Epoch(train) [120][150/442] lr: 5.000000e-04 eta: 3:54:12 time: 0.349136 data_time: 0.031358 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.906663 2023/08/09 16:00:33 - mmengine - INFO - Epoch(train) [120][160/442] lr: 5.000000e-04 eta: 3:54:07 time: 0.344641 data_time: 0.031244 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.867523 2023/08/09 16:00:37 - mmengine - INFO - Epoch(train) [120][170/442] lr: 5.000000e-04 eta: 3:54:02 time: 0.342586 data_time: 0.031061 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.849386 2023/08/09 16:00:40 - mmengine - INFO - Epoch(train) [120][180/442] lr: 5.000000e-04 eta: 3:53:58 time: 0.341281 data_time: 0.030642 memory: 4565 loss: 0.000972 loss_kpt: 0.000972 acc_pose: 0.814740 2023/08/09 16:00:44 - mmengine - INFO - Epoch(train) [120][190/442] lr: 5.000000e-04 eta: 3:53:56 time: 0.345175 data_time: 0.030797 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.815802 2023/08/09 16:00:47 - mmengine - INFO - Epoch(train) [120][200/442] lr: 5.000000e-04 eta: 3:53:52 time: 0.346183 data_time: 0.030639 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.792391 2023/08/09 16:00:51 - mmengine - INFO - Epoch(train) [120][210/442] lr: 5.000000e-04 eta: 3:53:48 time: 0.348405 data_time: 0.030821 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.881315 2023/08/09 16:00:54 - mmengine - INFO - Epoch(train) [120][220/442] lr: 5.000000e-04 eta: 3:53:44 time: 0.348918 data_time: 0.030871 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.855137 2023/08/09 16:00:58 - mmengine - INFO - Epoch(train) [120][230/442] lr: 5.000000e-04 eta: 3:53:39 time: 0.348145 data_time: 0.030737 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.821603 2023/08/09 16:01:01 - mmengine - INFO - Epoch(train) [120][240/442] lr: 5.000000e-04 eta: 3:53:34 time: 0.341479 data_time: 0.030406 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.842454 2023/08/09 16:01:04 - mmengine - INFO - Epoch(train) [120][250/442] lr: 5.000000e-04 eta: 3:53:30 time: 0.341031 data_time: 0.030542 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.878198 2023/08/09 16:01:08 - mmengine - INFO - Epoch(train) [120][260/442] lr: 5.000000e-04 eta: 3:53:26 time: 0.340235 data_time: 0.030386 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.845145 2023/08/09 16:01:11 - mmengine - INFO - Epoch(train) [120][270/442] lr: 5.000000e-04 eta: 3:53:22 time: 0.342178 data_time: 0.030948 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.827514 2023/08/09 16:01:15 - mmengine - INFO - Epoch(train) [120][280/442] lr: 5.000000e-04 eta: 3:53:19 time: 0.344177 data_time: 0.031415 memory: 4565 loss: 0.000970 loss_kpt: 0.000970 acc_pose: 0.795664 2023/08/09 16:01:18 - mmengine - INFO - Epoch(train) [120][290/442] lr: 5.000000e-04 eta: 3:53:14 time: 0.344399 data_time: 0.031288 memory: 4565 loss: 0.000980 loss_kpt: 0.000980 acc_pose: 0.732832 2023/08/09 16:01:22 - mmengine - INFO - Epoch(train) [120][300/442] lr: 5.000000e-04 eta: 3:53:10 time: 0.346368 data_time: 0.034257 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.765225 2023/08/09 16:01:25 - mmengine - INFO - Epoch(train) [120][310/442] lr: 5.000000e-04 eta: 3:53:06 time: 0.344718 data_time: 0.034077 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.822011 2023/08/09 16:01:29 - mmengine - INFO - Epoch(train) [120][320/442] lr: 5.000000e-04 eta: 3:53:01 time: 0.342464 data_time: 0.033561 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.763961 2023/08/09 16:01:32 - mmengine - INFO - Epoch(train) [120][330/442] lr: 5.000000e-04 eta: 3:52:57 time: 0.342151 data_time: 0.033252 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.792992 2023/08/09 16:01:35 - mmengine - INFO - Epoch(train) [120][340/442] lr: 5.000000e-04 eta: 3:52:53 time: 0.342616 data_time: 0.033314 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.832902 2023/08/09 16:01:39 - mmengine - INFO - Epoch(train) [120][350/442] lr: 5.000000e-04 eta: 3:52:51 time: 0.345598 data_time: 0.030507 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.816010 2023/08/09 16:01:42 - mmengine - INFO - Epoch(train) [120][360/442] lr: 5.000000e-04 eta: 3:52:46 time: 0.346391 data_time: 0.030584 memory: 4565 loss: 0.000990 loss_kpt: 0.000990 acc_pose: 0.819751 2023/08/09 16:01:46 - mmengine - INFO - Epoch(train) [120][370/442] lr: 5.000000e-04 eta: 3:52:42 time: 0.345817 data_time: 0.030566 memory: 4565 loss: 0.001013 loss_kpt: 0.001013 acc_pose: 0.854241 2023/08/09 16:01:49 - mmengine - INFO - Epoch(train) [120][380/442] lr: 5.000000e-04 eta: 3:52:37 time: 0.344240 data_time: 0.030511 memory: 4565 loss: 0.001018 loss_kpt: 0.001018 acc_pose: 0.792431 2023/08/09 16:01:53 - mmengine - INFO - Epoch(train) [120][390/442] lr: 5.000000e-04 eta: 3:52:33 time: 0.344576 data_time: 0.030652 memory: 4565 loss: 0.001009 loss_kpt: 0.001009 acc_pose: 0.804558 2023/08/09 16:01:56 - mmengine - INFO - Epoch(train) [120][400/442] lr: 5.000000e-04 eta: 3:52:29 time: 0.340345 data_time: 0.030749 memory: 4565 loss: 0.001000 loss_kpt: 0.001000 acc_pose: 0.815204 2023/08/09 16:01:57 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:01:59 - mmengine - INFO - Epoch(train) [120][410/442] lr: 5.000000e-04 eta: 3:52:24 time: 0.340705 data_time: 0.030655 memory: 4565 loss: 0.000990 loss_kpt: 0.000990 acc_pose: 0.789432 2023/08/09 16:02:03 - mmengine - INFO - Epoch(train) [120][420/442] lr: 5.000000e-04 eta: 3:52:21 time: 0.342523 data_time: 0.030849 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.847569 2023/08/09 16:02:06 - mmengine - INFO - Epoch(train) [120][430/442] lr: 5.000000e-04 eta: 3:52:16 time: 0.342658 data_time: 0.030809 memory: 4565 loss: 0.000970 loss_kpt: 0.000970 acc_pose: 0.780829 2023/08/09 16:02:10 - mmengine - INFO - Epoch(train) [120][440/442] lr: 5.000000e-04 eta: 3:52:11 time: 0.342255 data_time: 0.030520 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.796012 2023/08/09 16:02:10 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:02:10 - mmengine - INFO - Saving checkpoint at 120 epochs 2023/08/09 16:02:16 - mmengine - INFO - Epoch(val) [120][ 10/108] eta: 0:00:22 time: 0.203277 data_time: 0.019394 memory: 4565 2023/08/09 16:02:18 - mmengine - INFO - Epoch(val) [120][ 20/108] eta: 0:00:19 time: 0.206621 data_time: 0.018916 memory: 1624 2023/08/09 16:02:20 - mmengine - INFO - Epoch(val) [120][ 30/108] eta: 0:00:16 time: 0.206400 data_time: 0.018473 memory: 1624 2023/08/09 16:02:22 - mmengine - INFO - Epoch(val) [120][ 40/108] eta: 0:00:14 time: 0.205819 data_time: 0.017943 memory: 1624 2023/08/09 16:02:24 - mmengine - INFO - Epoch(val) [120][ 50/108] eta: 0:00:12 time: 0.207839 data_time: 0.017880 memory: 1624 2023/08/09 16:02:26 - mmengine - INFO - Epoch(val) [120][ 60/108] eta: 0:00:09 time: 0.200853 data_time: 0.011423 memory: 1624 2023/08/09 16:02:28 - mmengine - INFO - Epoch(val) [120][ 70/108] eta: 0:00:07 time: 0.197274 data_time: 0.011830 memory: 1624 2023/08/09 16:02:30 - mmengine - INFO - Epoch(val) [120][ 80/108] eta: 0:00:05 time: 0.197335 data_time: 0.012170 memory: 1624 2023/08/09 16:02:32 - mmengine - INFO - Epoch(val) [120][ 90/108] eta: 0:00:03 time: 0.197652 data_time: 0.012572 memory: 1624 2023/08/09 16:02:34 - mmengine - INFO - Epoch(val) [120][100/108] eta: 0:00:01 time: 0.197646 data_time: 0.012807 memory: 1624 2023/08/09 16:02:36 - mmengine - INFO - Evaluating PCKAccuracy (normalized by ``"bbox_size"``)... 2023/08/09 16:02:36 - mmengine - INFO - Evaluating AUC... 2023/08/09 16:02:36 - mmengine - INFO - Evaluating EPE... 2023/08/09 16:02:36 - mmengine - INFO - Epoch(val) [120][108/108] PCK: 0.962826 AUC: 0.612325 EPE: 14.582473 data_time: 0.014813 time: 0.200243 2023/08/09 16:02:40 - mmengine - INFO - Epoch(train) [121][ 10/442] lr: 5.000000e-04 eta: 3:52:07 time: 0.343883 data_time: 0.033428 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.757440 2023/08/09 16:02:43 - mmengine - INFO - Epoch(train) [121][ 20/442] lr: 5.000000e-04 eta: 3:52:03 time: 0.343188 data_time: 0.033570 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.827273 2023/08/09 16:02:47 - mmengine - INFO - Epoch(train) [121][ 30/442] lr: 5.000000e-04 eta: 3:52:00 time: 0.346308 data_time: 0.033572 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.828701 2023/08/09 16:02:50 - mmengine - INFO - Epoch(train) [121][ 40/442] lr: 5.000000e-04 eta: 3:51:56 time: 0.347662 data_time: 0.033848 memory: 4565 loss: 0.001005 loss_kpt: 0.001005 acc_pose: 0.816490 2023/08/09 16:02:54 - mmengine - INFO - Epoch(train) [121][ 50/442] lr: 5.000000e-04 eta: 3:51:52 time: 0.349234 data_time: 0.034525 memory: 4565 loss: 0.000998 loss_kpt: 0.000998 acc_pose: 0.791935 2023/08/09 16:02:57 - mmengine - INFO - Epoch(train) [121][ 60/442] lr: 5.000000e-04 eta: 3:51:48 time: 0.345556 data_time: 0.030906 memory: 4565 loss: 0.000989 loss_kpt: 0.000989 acc_pose: 0.786164 2023/08/09 16:03:01 - mmengine - INFO - Epoch(train) [121][ 70/442] lr: 5.000000e-04 eta: 3:51:43 time: 0.344969 data_time: 0.031138 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.797400 2023/08/09 16:03:04 - mmengine - INFO - Epoch(train) [121][ 80/442] lr: 5.000000e-04 eta: 3:51:39 time: 0.341080 data_time: 0.031641 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.880159 2023/08/09 16:03:07 - mmengine - INFO - Epoch(train) [121][ 90/442] lr: 5.000000e-04 eta: 3:51:35 time: 0.340429 data_time: 0.032169 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.810974 2023/08/09 16:03:11 - mmengine - INFO - Epoch(train) [121][100/442] lr: 5.000000e-04 eta: 3:51:30 time: 0.339672 data_time: 0.031999 memory: 4565 loss: 0.000955 loss_kpt: 0.000955 acc_pose: 0.811457 2023/08/09 16:03:14 - mmengine - INFO - Epoch(train) [121][110/442] lr: 5.000000e-04 eta: 3:51:26 time: 0.340226 data_time: 0.032211 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.810640 2023/08/09 16:03:18 - mmengine - INFO - Epoch(train) [121][120/442] lr: 5.000000e-04 eta: 3:51:21 time: 0.339672 data_time: 0.031803 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.807841 2023/08/09 16:03:21 - mmengine - INFO - Epoch(train) [121][130/442] lr: 5.000000e-04 eta: 3:51:17 time: 0.340546 data_time: 0.031378 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.864455 2023/08/09 16:03:24 - mmengine - INFO - Epoch(train) [121][140/442] lr: 5.000000e-04 eta: 3:51:13 time: 0.340747 data_time: 0.030756 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.785329 2023/08/09 16:03:28 - mmengine - INFO - Epoch(train) [121][150/442] lr: 5.000000e-04 eta: 3:51:11 time: 0.347088 data_time: 0.033788 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.746882 2023/08/09 16:03:32 - mmengine - INFO - Epoch(train) [121][160/442] lr: 5.000000e-04 eta: 3:51:08 time: 0.348597 data_time: 0.033796 memory: 4565 loss: 0.000955 loss_kpt: 0.000955 acc_pose: 0.728671 2023/08/09 16:03:35 - mmengine - INFO - Epoch(train) [121][170/442] lr: 5.000000e-04 eta: 3:51:04 time: 0.350510 data_time: 0.034408 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.805158 2023/08/09 16:03:39 - mmengine - INFO - Epoch(train) [121][180/442] lr: 5.000000e-04 eta: 3:51:01 time: 0.352262 data_time: 0.034230 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.844462 2023/08/09 16:03:42 - mmengine - INFO - Epoch(train) [121][190/442] lr: 5.000000e-04 eta: 3:50:56 time: 0.351715 data_time: 0.034077 memory: 4565 loss: 0.000990 loss_kpt: 0.000990 acc_pose: 0.791073 2023/08/09 16:03:45 - mmengine - INFO - Epoch(train) [121][200/442] lr: 5.000000e-04 eta: 3:50:52 time: 0.346199 data_time: 0.030882 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.871861 2023/08/09 16:03:49 - mmengine - INFO - Epoch(train) [121][210/442] lr: 5.000000e-04 eta: 3:50:48 time: 0.344057 data_time: 0.030622 memory: 4565 loss: 0.000989 loss_kpt: 0.000989 acc_pose: 0.859387 2023/08/09 16:03:52 - mmengine - INFO - Epoch(train) [121][220/442] lr: 5.000000e-04 eta: 3:50:43 time: 0.342910 data_time: 0.030195 memory: 4565 loss: 0.000983 loss_kpt: 0.000983 acc_pose: 0.845335 2023/08/09 16:03:56 - mmengine - INFO - Epoch(train) [121][230/442] lr: 5.000000e-04 eta: 3:50:40 time: 0.341685 data_time: 0.030421 memory: 4565 loss: 0.000972 loss_kpt: 0.000972 acc_pose: 0.884750 2023/08/09 16:03:59 - mmengine - INFO - Epoch(train) [121][240/442] lr: 5.000000e-04 eta: 3:50:36 time: 0.343375 data_time: 0.030496 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.811923 2023/08/09 16:04:03 - mmengine - INFO - Epoch(train) [121][250/442] lr: 5.000000e-04 eta: 3:50:32 time: 0.345076 data_time: 0.031037 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.811643 2023/08/09 16:04:06 - mmengine - INFO - Epoch(train) [121][260/442] lr: 5.000000e-04 eta: 3:50:30 time: 0.349824 data_time: 0.031265 memory: 4565 loss: 0.000990 loss_kpt: 0.000990 acc_pose: 0.771178 2023/08/09 16:04:10 - mmengine - INFO - Epoch(train) [121][270/442] lr: 5.000000e-04 eta: 3:50:29 time: 0.357205 data_time: 0.032070 memory: 4565 loss: 0.001012 loss_kpt: 0.001012 acc_pose: 0.806142 2023/08/09 16:04:14 - mmengine - INFO - Epoch(train) [121][280/442] lr: 5.000000e-04 eta: 3:50:25 time: 0.356553 data_time: 0.031840 memory: 4565 loss: 0.001012 loss_kpt: 0.001012 acc_pose: 0.858705 2023/08/09 16:04:17 - mmengine - INFO - Epoch(train) [121][290/442] lr: 5.000000e-04 eta: 3:50:21 time: 0.356596 data_time: 0.031952 memory: 4565 loss: 0.001036 loss_kpt: 0.001036 acc_pose: 0.733400 2023/08/09 16:04:21 - mmengine - INFO - Epoch(train) [121][300/442] lr: 5.000000e-04 eta: 3:50:19 time: 0.359636 data_time: 0.032867 memory: 4565 loss: 0.001031 loss_kpt: 0.001031 acc_pose: 0.817247 2023/08/09 16:04:24 - mmengine - INFO - Epoch(train) [121][310/442] lr: 5.000000e-04 eta: 3:50:16 time: 0.357826 data_time: 0.033140 memory: 4565 loss: 0.001017 loss_kpt: 0.001017 acc_pose: 0.792572 2023/08/09 16:04:28 - mmengine - INFO - Epoch(train) [121][320/442] lr: 5.000000e-04 eta: 3:50:12 time: 0.351836 data_time: 0.032117 memory: 4565 loss: 0.001012 loss_kpt: 0.001012 acc_pose: 0.782625 2023/08/09 16:04:31 - mmengine - INFO - Epoch(train) [121][330/442] lr: 5.000000e-04 eta: 3:50:09 time: 0.353751 data_time: 0.032065 memory: 4565 loss: 0.001004 loss_kpt: 0.001004 acc_pose: 0.803113 2023/08/09 16:04:35 - mmengine - INFO - Epoch(train) [121][340/442] lr: 5.000000e-04 eta: 3:50:05 time: 0.353069 data_time: 0.031840 memory: 4565 loss: 0.001004 loss_kpt: 0.001004 acc_pose: 0.850047 2023/08/09 16:04:38 - mmengine - INFO - Epoch(train) [121][350/442] lr: 5.000000e-04 eta: 3:50:02 time: 0.351467 data_time: 0.033513 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.759464 2023/08/09 16:04:42 - mmengine - INFO - Epoch(train) [121][360/442] lr: 5.000000e-04 eta: 3:49:58 time: 0.349629 data_time: 0.033096 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.801948 2023/08/09 16:04:45 - mmengine - INFO - Epoch(train) [121][370/442] lr: 5.000000e-04 eta: 3:49:55 time: 0.351592 data_time: 0.033313 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.875673 2023/08/09 16:04:49 - mmengine - INFO - Epoch(train) [121][380/442] lr: 5.000000e-04 eta: 3:49:53 time: 0.354181 data_time: 0.033413 memory: 4565 loss: 0.000990 loss_kpt: 0.000990 acc_pose: 0.706052 2023/08/09 16:04:53 - mmengine - INFO - Epoch(train) [121][390/442] lr: 5.000000e-04 eta: 3:49:51 time: 0.357399 data_time: 0.033589 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.791756 2023/08/09 16:04:56 - mmengine - INFO - Epoch(train) [121][400/442] lr: 5.000000e-04 eta: 3:49:47 time: 0.355519 data_time: 0.030491 memory: 4565 loss: 0.001001 loss_kpt: 0.001001 acc_pose: 0.858324 2023/08/09 16:05:00 - mmengine - INFO - Epoch(train) [121][410/442] lr: 5.000000e-04 eta: 3:49:43 time: 0.356486 data_time: 0.031625 memory: 4565 loss: 0.001010 loss_kpt: 0.001010 acc_pose: 0.825226 2023/08/09 16:05:03 - mmengine - INFO - Epoch(train) [121][420/442] lr: 5.000000e-04 eta: 3:49:40 time: 0.355406 data_time: 0.032407 memory: 4565 loss: 0.001028 loss_kpt: 0.001028 acc_pose: 0.813385 2023/08/09 16:05:07 - mmengine - INFO - Epoch(train) [121][430/442] lr: 5.000000e-04 eta: 3:49:38 time: 0.355578 data_time: 0.033321 memory: 4565 loss: 0.001034 loss_kpt: 0.001034 acc_pose: 0.790490 2023/08/09 16:05:10 - mmengine - INFO - Epoch(train) [121][440/442] lr: 5.000000e-04 eta: 3:49:34 time: 0.353307 data_time: 0.033387 memory: 4565 loss: 0.001027 loss_kpt: 0.001027 acc_pose: 0.813620 2023/08/09 16:05:11 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:05:15 - mmengine - INFO - Epoch(train) [122][ 10/442] lr: 5.000000e-04 eta: 3:49:31 time: 0.357228 data_time: 0.037850 memory: 4565 loss: 0.001019 loss_kpt: 0.001019 acc_pose: 0.859075 2023/08/09 16:05:18 - mmengine - INFO - Epoch(train) [122][ 20/442] lr: 5.000000e-04 eta: 3:49:27 time: 0.355774 data_time: 0.036242 memory: 4565 loss: 0.001001 loss_kpt: 0.001001 acc_pose: 0.722992 2023/08/09 16:05:22 - mmengine - INFO - Epoch(train) [122][ 30/442] lr: 5.000000e-04 eta: 3:49:23 time: 0.354023 data_time: 0.035566 memory: 4565 loss: 0.001002 loss_kpt: 0.001002 acc_pose: 0.795218 2023/08/09 16:05:25 - mmengine - INFO - Epoch(train) [122][ 40/442] lr: 5.000000e-04 eta: 3:49:19 time: 0.349073 data_time: 0.034518 memory: 4565 loss: 0.000983 loss_kpt: 0.000983 acc_pose: 0.751282 2023/08/09 16:05:28 - mmengine - INFO - Epoch(train) [122][ 50/442] lr: 5.000000e-04 eta: 3:49:15 time: 0.347714 data_time: 0.034624 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.746137 2023/08/09 16:05:32 - mmengine - INFO - Epoch(train) [122][ 60/442] lr: 5.000000e-04 eta: 3:49:11 time: 0.343977 data_time: 0.030200 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.814061 2023/08/09 16:05:35 - mmengine - INFO - Epoch(train) [122][ 70/442] lr: 5.000000e-04 eta: 3:49:08 time: 0.345496 data_time: 0.030471 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.804796 2023/08/09 16:05:39 - mmengine - INFO - Epoch(train) [122][ 80/442] lr: 5.000000e-04 eta: 3:49:05 time: 0.346748 data_time: 0.030480 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.838675 2023/08/09 16:05:42 - mmengine - INFO - Epoch(train) [122][ 90/442] lr: 5.000000e-04 eta: 3:49:00 time: 0.347111 data_time: 0.030620 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.816641 2023/08/09 16:05:46 - mmengine - INFO - Epoch(train) [122][100/442] lr: 5.000000e-04 eta: 3:48:57 time: 0.349051 data_time: 0.030637 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.786839 2023/08/09 16:05:49 - mmengine - INFO - Epoch(train) [122][110/442] lr: 5.000000e-04 eta: 3:48:53 time: 0.347252 data_time: 0.030347 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.822206 2023/08/09 16:05:53 - mmengine - INFO - Epoch(train) [122][120/442] lr: 5.000000e-04 eta: 3:48:50 time: 0.347382 data_time: 0.030173 memory: 4565 loss: 0.000995 loss_kpt: 0.000995 acc_pose: 0.862212 2023/08/09 16:05:56 - mmengine - INFO - Epoch(train) [122][130/442] lr: 5.000000e-04 eta: 3:48:47 time: 0.350931 data_time: 0.033589 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.785569 2023/08/09 16:06:00 - mmengine - INFO - Epoch(train) [122][140/442] lr: 5.000000e-04 eta: 3:48:44 time: 0.352619 data_time: 0.033702 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.800527 2023/08/09 16:06:03 - mmengine - INFO - Epoch(train) [122][150/442] lr: 5.000000e-04 eta: 3:48:39 time: 0.349199 data_time: 0.033808 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.824086 2023/08/09 16:06:07 - mmengine - INFO - Epoch(train) [122][160/442] lr: 5.000000e-04 eta: 3:48:35 time: 0.348960 data_time: 0.033854 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.876641 2023/08/09 16:06:10 - mmengine - INFO - Epoch(train) [122][170/442] lr: 5.000000e-04 eta: 3:48:31 time: 0.346507 data_time: 0.033865 memory: 4565 loss: 0.000983 loss_kpt: 0.000983 acc_pose: 0.820986 2023/08/09 16:06:14 - mmengine - INFO - Epoch(train) [122][180/442] lr: 5.000000e-04 eta: 3:48:27 time: 0.341629 data_time: 0.030540 memory: 4565 loss: 0.000989 loss_kpt: 0.000989 acc_pose: 0.823237 2023/08/09 16:06:17 - mmengine - INFO - Epoch(train) [122][190/442] lr: 5.000000e-04 eta: 3:48:23 time: 0.340541 data_time: 0.030770 memory: 4565 loss: 0.000972 loss_kpt: 0.000972 acc_pose: 0.836628 2023/08/09 16:06:20 - mmengine - INFO - Epoch(train) [122][200/442] lr: 5.000000e-04 eta: 3:48:19 time: 0.342415 data_time: 0.030708 memory: 4565 loss: 0.000980 loss_kpt: 0.000980 acc_pose: 0.782232 2023/08/09 16:06:24 - mmengine - INFO - Epoch(train) [122][210/442] lr: 5.000000e-04 eta: 3:48:16 time: 0.345864 data_time: 0.030868 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.786951 2023/08/09 16:06:27 - mmengine - INFO - Epoch(train) [122][220/442] lr: 5.000000e-04 eta: 3:48:11 time: 0.345736 data_time: 0.030748 memory: 4565 loss: 0.000983 loss_kpt: 0.000983 acc_pose: 0.819151 2023/08/09 16:06:31 - mmengine - INFO - Epoch(train) [122][230/442] lr: 5.000000e-04 eta: 3:48:07 time: 0.344970 data_time: 0.030534 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.816492 2023/08/09 16:06:34 - mmengine - INFO - Epoch(train) [122][240/442] lr: 5.000000e-04 eta: 3:48:03 time: 0.343843 data_time: 0.030087 memory: 4565 loss: 0.000998 loss_kpt: 0.000998 acc_pose: 0.775986 2023/08/09 16:06:38 - mmengine - INFO - Epoch(train) [122][250/442] lr: 5.000000e-04 eta: 3:47:59 time: 0.343504 data_time: 0.029910 memory: 4565 loss: 0.001002 loss_kpt: 0.001002 acc_pose: 0.856055 2023/08/09 16:06:41 - mmengine - INFO - Epoch(train) [122][260/442] lr: 5.000000e-04 eta: 3:47:56 time: 0.345267 data_time: 0.029746 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.831423 2023/08/09 16:06:45 - mmengine - INFO - Epoch(train) [122][270/442] lr: 5.000000e-04 eta: 3:47:53 time: 0.347715 data_time: 0.029866 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.856991 2023/08/09 16:06:48 - mmengine - INFO - Epoch(train) [122][280/442] lr: 5.000000e-04 eta: 3:47:50 time: 0.351422 data_time: 0.030580 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.816823 2023/08/09 16:06:52 - mmengine - INFO - Epoch(train) [122][290/442] lr: 5.000000e-04 eta: 3:47:46 time: 0.352047 data_time: 0.030809 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.790170 2023/08/09 16:06:55 - mmengine - INFO - Epoch(train) [122][300/442] lr: 5.000000e-04 eta: 3:47:42 time: 0.351334 data_time: 0.031023 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.815147 2023/08/09 16:06:59 - mmengine - INFO - Epoch(train) [122][310/442] lr: 5.000000e-04 eta: 3:47:38 time: 0.346305 data_time: 0.031124 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.803448 2023/08/09 16:07:02 - mmengine - INFO - Epoch(train) [122][320/442] lr: 5.000000e-04 eta: 3:47:33 time: 0.344335 data_time: 0.032068 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.780670 2023/08/09 16:07:06 - mmengine - INFO - Epoch(train) [122][330/442] lr: 5.000000e-04 eta: 3:47:30 time: 0.343131 data_time: 0.032518 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.912570 2023/08/09 16:07:09 - mmengine - INFO - Epoch(train) [122][340/442] lr: 5.000000e-04 eta: 3:47:26 time: 0.344578 data_time: 0.033316 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.753195 2023/08/09 16:07:13 - mmengine - INFO - Epoch(train) [122][350/442] lr: 5.000000e-04 eta: 3:47:23 time: 0.346349 data_time: 0.033698 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.831307 2023/08/09 16:07:16 - mmengine - INFO - Epoch(train) [122][360/442] lr: 5.000000e-04 eta: 3:47:19 time: 0.347042 data_time: 0.033588 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.784390 2023/08/09 16:07:20 - mmengine - INFO - Epoch(train) [122][370/442] lr: 5.000000e-04 eta: 3:47:19 time: 0.359004 data_time: 0.036130 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.801397 2023/08/09 16:07:24 - mmengine - INFO - Epoch(train) [122][380/442] lr: 5.000000e-04 eta: 3:47:18 time: 0.365655 data_time: 0.035353 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.758410 2023/08/09 16:07:28 - mmengine - INFO - Epoch(train) [122][390/442] lr: 5.000000e-04 eta: 3:47:17 time: 0.372471 data_time: 0.034977 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.905386 2023/08/09 16:07:31 - mmengine - INFO - Epoch(train) [122][400/442] lr: 5.000000e-04 eta: 3:47:14 time: 0.372556 data_time: 0.034479 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.863405 2023/08/09 16:07:35 - mmengine - INFO - Epoch(train) [122][410/442] lr: 5.000000e-04 eta: 3:47:10 time: 0.373098 data_time: 0.034571 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.799876 2023/08/09 16:07:38 - mmengine - INFO - Epoch(train) [122][420/442] lr: 5.000000e-04 eta: 3:47:07 time: 0.363182 data_time: 0.031096 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.815585 2023/08/09 16:07:42 - mmengine - INFO - Epoch(train) [122][430/442] lr: 5.000000e-04 eta: 3:47:02 time: 0.353680 data_time: 0.030829 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.843632 2023/08/09 16:07:45 - mmengine - INFO - Epoch(train) [122][440/442] lr: 5.000000e-04 eta: 3:46:58 time: 0.344658 data_time: 0.030184 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.802709 2023/08/09 16:07:46 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:07:49 - mmengine - INFO - Epoch(train) [123][ 10/442] lr: 5.000000e-04 eta: 3:46:54 time: 0.346928 data_time: 0.033623 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.807369 2023/08/09 16:07:53 - mmengine - INFO - Epoch(train) [123][ 20/442] lr: 5.000000e-04 eta: 3:46:52 time: 0.350171 data_time: 0.033677 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.817150 2023/08/09 16:07:56 - mmengine - INFO - Epoch(train) [123][ 30/442] lr: 5.000000e-04 eta: 3:46:48 time: 0.350797 data_time: 0.033895 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.820644 2023/08/09 16:08:00 - mmengine - INFO - Epoch(train) [123][ 40/442] lr: 5.000000e-04 eta: 3:46:45 time: 0.354486 data_time: 0.034140 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.851596 2023/08/09 16:08:03 - mmengine - INFO - Epoch(train) [123][ 50/442] lr: 5.000000e-04 eta: 3:46:42 time: 0.358460 data_time: 0.034627 memory: 4565 loss: 0.000972 loss_kpt: 0.000972 acc_pose: 0.804720 2023/08/09 16:08:07 - mmengine - INFO - Epoch(train) [123][ 60/442] lr: 5.000000e-04 eta: 3:46:39 time: 0.355452 data_time: 0.030807 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.825224 2023/08/09 16:08:11 - mmengine - INFO - Epoch(train) [123][ 70/442] lr: 5.000000e-04 eta: 3:46:35 time: 0.353547 data_time: 0.030723 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.815782 2023/08/09 16:08:13 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:08:14 - mmengine - INFO - Epoch(train) [123][ 80/442] lr: 5.000000e-04 eta: 3:46:32 time: 0.353704 data_time: 0.030667 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.841002 2023/08/09 16:08:18 - mmengine - INFO - Epoch(train) [123][ 90/442] lr: 5.000000e-04 eta: 3:46:30 time: 0.356737 data_time: 0.030569 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.872460 2023/08/09 16:08:21 - mmengine - INFO - Epoch(train) [123][100/442] lr: 5.000000e-04 eta: 3:46:27 time: 0.357529 data_time: 0.030664 memory: 4565 loss: 0.000953 loss_kpt: 0.000953 acc_pose: 0.856182 2023/08/09 16:08:25 - mmengine - INFO - Epoch(train) [123][110/442] lr: 5.000000e-04 eta: 3:46:24 time: 0.357898 data_time: 0.031267 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.876456 2023/08/09 16:08:28 - mmengine - INFO - Epoch(train) [123][120/442] lr: 5.000000e-04 eta: 3:46:21 time: 0.358200 data_time: 0.031663 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.788314 2023/08/09 16:08:32 - mmengine - INFO - Epoch(train) [123][130/442] lr: 5.000000e-04 eta: 3:46:19 time: 0.362260 data_time: 0.032696 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.793732 2023/08/09 16:08:36 - mmengine - INFO - Epoch(train) [123][140/442] lr: 5.000000e-04 eta: 3:46:16 time: 0.359030 data_time: 0.033421 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.839101 2023/08/09 16:08:39 - mmengine - INFO - Epoch(train) [123][150/442] lr: 5.000000e-04 eta: 3:46:13 time: 0.358746 data_time: 0.033519 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.762467 2023/08/09 16:08:43 - mmengine - INFO - Epoch(train) [123][160/442] lr: 5.000000e-04 eta: 3:46:10 time: 0.358790 data_time: 0.033587 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.753068 2023/08/09 16:08:46 - mmengine - INFO - Epoch(train) [123][170/442] lr: 5.000000e-04 eta: 3:46:07 time: 0.359889 data_time: 0.033673 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.749186 2023/08/09 16:08:50 - mmengine - INFO - Epoch(train) [123][180/442] lr: 5.000000e-04 eta: 3:46:03 time: 0.355017 data_time: 0.032558 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.810331 2023/08/09 16:08:53 - mmengine - INFO - Epoch(train) [123][190/442] lr: 5.000000e-04 eta: 3:46:00 time: 0.353900 data_time: 0.031716 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.830058 2023/08/09 16:08:57 - mmengine - INFO - Epoch(train) [123][200/442] lr: 5.000000e-04 eta: 3:45:56 time: 0.353160 data_time: 0.031418 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.853539 2023/08/09 16:09:00 - mmengine - INFO - Epoch(train) [123][210/442] lr: 5.000000e-04 eta: 3:45:53 time: 0.352196 data_time: 0.030901 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.723402 2023/08/09 16:09:04 - mmengine - INFO - Epoch(train) [123][220/442] lr: 5.000000e-04 eta: 3:45:50 time: 0.351306 data_time: 0.031360 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.782790 2023/08/09 16:09:08 - mmengine - INFO - Epoch(train) [123][230/442] lr: 5.000000e-04 eta: 3:45:47 time: 0.352738 data_time: 0.031449 memory: 4565 loss: 0.000980 loss_kpt: 0.000980 acc_pose: 0.775879 2023/08/09 16:09:11 - mmengine - INFO - Epoch(train) [123][240/442] lr: 5.000000e-04 eta: 3:45:45 time: 0.357784 data_time: 0.032027 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.821546 2023/08/09 16:09:15 - mmengine - INFO - Epoch(train) [123][250/442] lr: 5.000000e-04 eta: 3:45:41 time: 0.357736 data_time: 0.032871 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.833875 2023/08/09 16:09:18 - mmengine - INFO - Epoch(train) [123][260/442] lr: 5.000000e-04 eta: 3:45:38 time: 0.357670 data_time: 0.033532 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.793373 2023/08/09 16:09:22 - mmengine - INFO - Epoch(train) [123][270/442] lr: 5.000000e-04 eta: 3:45:35 time: 0.359373 data_time: 0.033406 memory: 4565 loss: 0.000974 loss_kpt: 0.000974 acc_pose: 0.851037 2023/08/09 16:09:26 - mmengine - INFO - Epoch(train) [123][280/442] lr: 5.000000e-04 eta: 3:45:32 time: 0.358436 data_time: 0.034276 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.744497 2023/08/09 16:09:29 - mmengine - INFO - Epoch(train) [123][290/442] lr: 5.000000e-04 eta: 3:45:29 time: 0.354356 data_time: 0.033800 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.737536 2023/08/09 16:09:33 - mmengine - INFO - Epoch(train) [123][300/442] lr: 5.000000e-04 eta: 3:45:25 time: 0.355181 data_time: 0.032948 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.855507 2023/08/09 16:09:36 - mmengine - INFO - Epoch(train) [123][310/442] lr: 5.000000e-04 eta: 3:45:22 time: 0.356807 data_time: 0.032362 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.730729 2023/08/09 16:09:40 - mmengine - INFO - Epoch(train) [123][320/442] lr: 5.000000e-04 eta: 3:45:19 time: 0.353911 data_time: 0.031519 memory: 4565 loss: 0.000989 loss_kpt: 0.000989 acc_pose: 0.831468 2023/08/09 16:09:43 - mmengine - INFO - Epoch(train) [123][330/442] lr: 5.000000e-04 eta: 3:45:15 time: 0.353214 data_time: 0.030577 memory: 4565 loss: 0.000971 loss_kpt: 0.000971 acc_pose: 0.874064 2023/08/09 16:09:47 - mmengine - INFO - Epoch(train) [123][340/442] lr: 5.000000e-04 eta: 3:45:12 time: 0.352653 data_time: 0.030491 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.815232 2023/08/09 16:09:50 - mmengine - INFO - Epoch(train) [123][350/442] lr: 5.000000e-04 eta: 3:45:08 time: 0.351967 data_time: 0.030587 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.771641 2023/08/09 16:09:54 - mmengine - INFO - Epoch(train) [123][360/442] lr: 5.000000e-04 eta: 3:45:05 time: 0.351006 data_time: 0.030323 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.757665 2023/08/09 16:09:57 - mmengine - INFO - Epoch(train) [123][370/442] lr: 5.000000e-04 eta: 3:45:02 time: 0.353509 data_time: 0.030605 memory: 4565 loss: 0.000972 loss_kpt: 0.000972 acc_pose: 0.815619 2023/08/09 16:10:01 - mmengine - INFO - Epoch(train) [123][380/442] lr: 5.000000e-04 eta: 3:45:00 time: 0.357710 data_time: 0.030633 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.866806 2023/08/09 16:10:05 - mmengine - INFO - Epoch(train) [123][390/442] lr: 5.000000e-04 eta: 3:44:57 time: 0.357183 data_time: 0.030670 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.772960 2023/08/09 16:10:08 - mmengine - INFO - Epoch(train) [123][400/442] lr: 5.000000e-04 eta: 3:44:54 time: 0.358585 data_time: 0.030572 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.844857 2023/08/09 16:10:12 - mmengine - INFO - Epoch(train) [123][410/442] lr: 5.000000e-04 eta: 3:44:50 time: 0.358371 data_time: 0.030661 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.906315 2023/08/09 16:10:15 - mmengine - INFO - Epoch(train) [123][420/442] lr: 5.000000e-04 eta: 3:44:47 time: 0.356646 data_time: 0.030504 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.810324 2023/08/09 16:10:19 - mmengine - INFO - Epoch(train) [123][430/442] lr: 5.000000e-04 eta: 3:44:44 time: 0.353908 data_time: 0.031040 memory: 4565 loss: 0.000991 loss_kpt: 0.000991 acc_pose: 0.787776 2023/08/09 16:10:22 - mmengine - INFO - Epoch(train) [123][440/442] lr: 5.000000e-04 eta: 3:44:41 time: 0.356596 data_time: 0.031584 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.858805 2023/08/09 16:10:23 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:10:27 - mmengine - INFO - Epoch(train) [124][ 10/442] lr: 5.000000e-04 eta: 3:44:37 time: 0.354634 data_time: 0.035256 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.774275 2023/08/09 16:10:30 - mmengine - INFO - Epoch(train) [124][ 20/442] lr: 5.000000e-04 eta: 3:44:33 time: 0.351934 data_time: 0.035006 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.790627 2023/08/09 16:10:34 - mmengine - INFO - Epoch(train) [124][ 30/442] lr: 5.000000e-04 eta: 3:44:29 time: 0.350339 data_time: 0.034839 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.834003 2023/08/09 16:10:37 - mmengine - INFO - Epoch(train) [124][ 40/442] lr: 5.000000e-04 eta: 3:44:24 time: 0.346308 data_time: 0.034137 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.790945 2023/08/09 16:10:40 - mmengine - INFO - Epoch(train) [124][ 50/442] lr: 5.000000e-04 eta: 3:44:20 time: 0.344946 data_time: 0.034117 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.829834 2023/08/09 16:10:44 - mmengine - INFO - Epoch(train) [124][ 60/442] lr: 5.000000e-04 eta: 3:44:16 time: 0.341298 data_time: 0.030136 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.873358 2023/08/09 16:10:47 - mmengine - INFO - Epoch(train) [124][ 70/442] lr: 5.000000e-04 eta: 3:44:12 time: 0.342194 data_time: 0.030582 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.839239 2023/08/09 16:10:51 - mmengine - INFO - Epoch(train) [124][ 80/442] lr: 5.000000e-04 eta: 3:44:10 time: 0.346907 data_time: 0.031367 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.896701 2023/08/09 16:10:54 - mmengine - INFO - Epoch(train) [124][ 90/442] lr: 5.000000e-04 eta: 3:44:07 time: 0.350784 data_time: 0.034615 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.847595 2023/08/09 16:10:58 - mmengine - INFO - Epoch(train) [124][100/442] lr: 5.000000e-04 eta: 3:44:03 time: 0.351922 data_time: 0.034566 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.822572 2023/08/09 16:11:01 - mmengine - INFO - Epoch(train) [124][110/442] lr: 5.000000e-04 eta: 3:43:59 time: 0.351579 data_time: 0.034663 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.736424 2023/08/09 16:11:05 - mmengine - INFO - Epoch(train) [124][120/442] lr: 5.000000e-04 eta: 3:43:55 time: 0.352045 data_time: 0.034499 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.867052 2023/08/09 16:11:08 - mmengine - INFO - Epoch(train) [124][130/442] lr: 5.000000e-04 eta: 3:43:52 time: 0.347962 data_time: 0.033818 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.840856 2023/08/09 16:11:12 - mmengine - INFO - Epoch(train) [124][140/442] lr: 5.000000e-04 eta: 3:43:48 time: 0.346570 data_time: 0.030821 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.801684 2023/08/09 16:11:15 - mmengine - INFO - Epoch(train) [124][150/442] lr: 5.000000e-04 eta: 3:43:44 time: 0.344365 data_time: 0.030677 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.809932 2023/08/09 16:11:19 - mmengine - INFO - Epoch(train) [124][160/442] lr: 5.000000e-04 eta: 3:43:40 time: 0.344232 data_time: 0.030525 memory: 4565 loss: 0.000941 loss_kpt: 0.000941 acc_pose: 0.824911 2023/08/09 16:11:22 - mmengine - INFO - Epoch(train) [124][170/442] lr: 5.000000e-04 eta: 3:43:35 time: 0.342955 data_time: 0.030532 memory: 4565 loss: 0.000955 loss_kpt: 0.000955 acc_pose: 0.777338 2023/08/09 16:11:25 - mmengine - INFO - Epoch(train) [124][180/442] lr: 5.000000e-04 eta: 3:43:32 time: 0.342008 data_time: 0.030434 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.839298 2023/08/09 16:11:29 - mmengine - INFO - Epoch(train) [124][190/442] lr: 5.000000e-04 eta: 3:43:28 time: 0.341334 data_time: 0.030497 memory: 4565 loss: 0.000963 loss_kpt: 0.000963 acc_pose: 0.738590 2023/08/09 16:11:32 - mmengine - INFO - Epoch(train) [124][200/442] lr: 5.000000e-04 eta: 3:43:24 time: 0.344414 data_time: 0.030923 memory: 4565 loss: 0.000971 loss_kpt: 0.000971 acc_pose: 0.826577 2023/08/09 16:11:36 - mmengine - INFO - Epoch(train) [124][210/442] lr: 5.000000e-04 eta: 3:43:21 time: 0.346361 data_time: 0.031424 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.831409 2023/08/09 16:11:39 - mmengine - INFO - Epoch(train) [124][220/442] lr: 5.000000e-04 eta: 3:43:16 time: 0.346000 data_time: 0.031228 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.802201 2023/08/09 16:11:43 - mmengine - INFO - Epoch(train) [124][230/442] lr: 5.000000e-04 eta: 3:43:12 time: 0.344813 data_time: 0.031297 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.795484 2023/08/09 16:11:46 - mmengine - INFO - Epoch(train) [124][240/442] lr: 5.000000e-04 eta: 3:43:09 time: 0.347619 data_time: 0.031353 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.806387 2023/08/09 16:11:50 - mmengine - INFO - Epoch(train) [124][250/442] lr: 5.000000e-04 eta: 3:43:05 time: 0.344504 data_time: 0.031096 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.823573 2023/08/09 16:11:53 - mmengine - INFO - Epoch(train) [124][260/442] lr: 5.000000e-04 eta: 3:43:01 time: 0.344319 data_time: 0.030604 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.858814 2023/08/09 16:11:57 - mmengine - INFO - Epoch(train) [124][270/442] lr: 5.000000e-04 eta: 3:42:59 time: 0.350747 data_time: 0.034014 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.865684 2023/08/09 16:12:00 - mmengine - INFO - Epoch(train) [124][280/442] lr: 5.000000e-04 eta: 3:42:55 time: 0.351578 data_time: 0.033896 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.813303 2023/08/09 16:12:04 - mmengine - INFO - Epoch(train) [124][290/442] lr: 5.000000e-04 eta: 3:42:51 time: 0.347958 data_time: 0.033666 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.841141 2023/08/09 16:12:07 - mmengine - INFO - Epoch(train) [124][300/442] lr: 5.000000e-04 eta: 3:42:47 time: 0.347967 data_time: 0.033534 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.834123 2023/08/09 16:12:10 - mmengine - INFO - Epoch(train) [124][310/442] lr: 5.000000e-04 eta: 3:42:43 time: 0.347116 data_time: 0.033432 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.768005 2023/08/09 16:12:14 - mmengine - INFO - Epoch(train) [124][320/442] lr: 5.000000e-04 eta: 3:42:39 time: 0.341728 data_time: 0.030259 memory: 4565 loss: 0.000995 loss_kpt: 0.000995 acc_pose: 0.810968 2023/08/09 16:12:17 - mmengine - INFO - Epoch(train) [124][330/442] lr: 5.000000e-04 eta: 3:42:36 time: 0.344031 data_time: 0.030505 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.817540 2023/08/09 16:12:21 - mmengine - INFO - Epoch(train) [124][340/442] lr: 5.000000e-04 eta: 3:42:33 time: 0.348069 data_time: 0.031231 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.875396 2023/08/09 16:12:24 - mmengine - INFO - Epoch(train) [124][350/442] lr: 5.000000e-04 eta: 3:42:28 time: 0.348077 data_time: 0.031708 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.839754 2023/08/09 16:12:28 - mmengine - INFO - Epoch(train) [124][360/442] lr: 5.000000e-04 eta: 3:42:24 time: 0.347013 data_time: 0.031733 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.807112 2023/08/09 16:12:31 - mmengine - INFO - Epoch(train) [124][370/442] lr: 5.000000e-04 eta: 3:42:20 time: 0.347204 data_time: 0.031544 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.835775 2023/08/09 16:12:35 - mmengine - INFO - Epoch(train) [124][380/442] lr: 5.000000e-04 eta: 3:42:17 time: 0.347102 data_time: 0.031157 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.848489 2023/08/09 16:12:38 - mmengine - INFO - Epoch(train) [124][390/442] lr: 5.000000e-04 eta: 3:42:13 time: 0.343481 data_time: 0.030508 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.882838 2023/08/09 16:12:42 - mmengine - INFO - Epoch(train) [124][400/442] lr: 5.000000e-04 eta: 3:42:09 time: 0.345157 data_time: 0.030368 memory: 4565 loss: 0.000955 loss_kpt: 0.000955 acc_pose: 0.766367 2023/08/09 16:12:45 - mmengine - INFO - Epoch(train) [124][410/442] lr: 5.000000e-04 eta: 3:42:06 time: 0.348718 data_time: 0.031090 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.817913 2023/08/09 16:12:49 - mmengine - INFO - Epoch(train) [124][420/442] lr: 5.000000e-04 eta: 3:42:03 time: 0.352795 data_time: 0.031121 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.806431 2023/08/09 16:12:52 - mmengine - INFO - Epoch(train) [124][430/442] lr: 5.000000e-04 eta: 3:42:00 time: 0.350672 data_time: 0.031264 memory: 4565 loss: 0.000941 loss_kpt: 0.000941 acc_pose: 0.845111 2023/08/09 16:12:56 - mmengine - INFO - Epoch(train) [124][440/442] lr: 5.000000e-04 eta: 3:41:56 time: 0.350904 data_time: 0.031248 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.884000 2023/08/09 16:12:56 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:13:00 - mmengine - INFO - Epoch(train) [125][ 10/442] lr: 5.000000e-04 eta: 3:41:52 time: 0.352534 data_time: 0.034192 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.791811 2023/08/09 16:13:03 - mmengine - INFO - Epoch(train) [125][ 20/442] lr: 5.000000e-04 eta: 3:41:48 time: 0.350453 data_time: 0.034149 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.756263 2023/08/09 16:13:07 - mmengine - INFO - Epoch(train) [125][ 30/442] lr: 5.000000e-04 eta: 3:41:44 time: 0.345908 data_time: 0.034351 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.808791 2023/08/09 16:13:10 - mmengine - INFO - Epoch(train) [125][ 40/442] lr: 5.000000e-04 eta: 3:41:40 time: 0.346625 data_time: 0.034884 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.861729 2023/08/09 16:13:14 - mmengine - INFO - Epoch(train) [125][ 50/442] lr: 5.000000e-04 eta: 3:41:36 time: 0.347984 data_time: 0.035377 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.873919 2023/08/09 16:13:17 - mmengine - INFO - Epoch(train) [125][ 60/442] lr: 5.000000e-04 eta: 3:41:33 time: 0.344588 data_time: 0.032475 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.828044 2023/08/09 16:13:21 - mmengine - INFO - Epoch(train) [125][ 70/442] lr: 5.000000e-04 eta: 3:41:29 time: 0.344470 data_time: 0.032182 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.834677 2023/08/09 16:13:24 - mmengine - INFO - Epoch(train) [125][ 80/442] lr: 5.000000e-04 eta: 3:41:25 time: 0.344451 data_time: 0.032378 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.804119 2023/08/09 16:13:28 - mmengine - INFO - Epoch(train) [125][ 90/442] lr: 5.000000e-04 eta: 3:41:21 time: 0.343709 data_time: 0.031993 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.894535 2023/08/09 16:13:31 - mmengine - INFO - Epoch(train) [125][100/442] lr: 5.000000e-04 eta: 3:41:18 time: 0.347906 data_time: 0.031918 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.885313 2023/08/09 16:13:35 - mmengine - INFO - Epoch(train) [125][110/442] lr: 5.000000e-04 eta: 3:41:14 time: 0.347940 data_time: 0.031288 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.847548 2023/08/09 16:13:38 - mmengine - INFO - Epoch(train) [125][120/442] lr: 5.000000e-04 eta: 3:41:11 time: 0.348205 data_time: 0.032021 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.889395 2023/08/09 16:13:42 - mmengine - INFO - Epoch(train) [125][130/442] lr: 5.000000e-04 eta: 3:41:08 time: 0.352514 data_time: 0.031740 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.851129 2023/08/09 16:13:45 - mmengine - INFO - Epoch(train) [125][140/442] lr: 5.000000e-04 eta: 3:41:04 time: 0.351694 data_time: 0.031617 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.769321 2023/08/09 16:13:49 - mmengine - INFO - Epoch(train) [125][150/442] lr: 5.000000e-04 eta: 3:41:00 time: 0.347478 data_time: 0.032373 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.767044 2023/08/09 16:13:52 - mmengine - INFO - Epoch(train) [125][160/442] lr: 5.000000e-04 eta: 3:40:56 time: 0.346922 data_time: 0.032349 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.765563 2023/08/09 16:13:55 - mmengine - INFO - Epoch(train) [125][170/442] lr: 5.000000e-04 eta: 3:40:52 time: 0.346985 data_time: 0.031824 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.775476 2023/08/09 16:13:59 - mmengine - INFO - Epoch(train) [125][180/442] lr: 5.000000e-04 eta: 3:40:49 time: 0.344436 data_time: 0.031860 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.830780 2023/08/09 16:14:02 - mmengine - INFO - Epoch(train) [125][190/442] lr: 5.000000e-04 eta: 3:40:45 time: 0.345063 data_time: 0.032107 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.871967 2023/08/09 16:14:03 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:14:06 - mmengine - INFO - Epoch(train) [125][200/442] lr: 5.000000e-04 eta: 3:40:41 time: 0.347688 data_time: 0.032348 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.862385 2023/08/09 16:14:10 - mmengine - INFO - Epoch(train) [125][210/442] lr: 5.000000e-04 eta: 3:40:40 time: 0.357427 data_time: 0.033496 memory: 4565 loss: 0.000940 loss_kpt: 0.000940 acc_pose: 0.824881 2023/08/09 16:14:14 - mmengine - INFO - Epoch(train) [125][220/442] lr: 5.000000e-04 eta: 3:40:39 time: 0.364648 data_time: 0.033995 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.837247 2023/08/09 16:14:17 - mmengine - INFO - Epoch(train) [125][230/442] lr: 5.000000e-04 eta: 3:40:36 time: 0.365588 data_time: 0.034355 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.767968 2023/08/09 16:14:21 - mmengine - INFO - Epoch(train) [125][240/442] lr: 5.000000e-04 eta: 3:40:32 time: 0.366732 data_time: 0.034309 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.830016 2023/08/09 16:14:24 - mmengine - INFO - Epoch(train) [125][250/442] lr: 5.000000e-04 eta: 3:40:28 time: 0.364622 data_time: 0.033151 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.829312 2023/08/09 16:14:28 - mmengine - INFO - Epoch(train) [125][260/442] lr: 5.000000e-04 eta: 3:40:26 time: 0.360513 data_time: 0.031696 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.819355 2023/08/09 16:14:31 - mmengine - INFO - Epoch(train) [125][270/442] lr: 5.000000e-04 eta: 3:40:22 time: 0.351709 data_time: 0.031076 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.769489 2023/08/09 16:14:35 - mmengine - INFO - Epoch(train) [125][280/442] lr: 5.000000e-04 eta: 3:40:18 time: 0.348633 data_time: 0.030617 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.794987 2023/08/09 16:14:38 - mmengine - INFO - Epoch(train) [125][290/442] lr: 5.000000e-04 eta: 3:40:13 time: 0.347201 data_time: 0.030494 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.863432 2023/08/09 16:14:42 - mmengine - INFO - Epoch(train) [125][300/442] lr: 5.000000e-04 eta: 3:40:10 time: 0.348813 data_time: 0.030660 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.843016 2023/08/09 16:14:45 - mmengine - INFO - Epoch(train) [125][310/442] lr: 5.000000e-04 eta: 3:40:07 time: 0.344110 data_time: 0.031004 memory: 4565 loss: 0.000953 loss_kpt: 0.000953 acc_pose: 0.782586 2023/08/09 16:14:49 - mmengine - INFO - Epoch(train) [125][320/442] lr: 5.000000e-04 eta: 3:40:03 time: 0.344848 data_time: 0.031226 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.803979 2023/08/09 16:14:52 - mmengine - INFO - Epoch(train) [125][330/442] lr: 5.000000e-04 eta: 3:39:59 time: 0.345448 data_time: 0.031096 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.822787 2023/08/09 16:14:55 - mmengine - INFO - Epoch(train) [125][340/442] lr: 5.000000e-04 eta: 3:39:54 time: 0.344953 data_time: 0.030973 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.909309 2023/08/09 16:14:59 - mmengine - INFO - Epoch(train) [125][350/442] lr: 5.000000e-04 eta: 3:39:50 time: 0.342298 data_time: 0.030735 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.845023 2023/08/09 16:15:02 - mmengine - INFO - Epoch(train) [125][360/442] lr: 5.000000e-04 eta: 3:39:47 time: 0.342667 data_time: 0.030749 memory: 4565 loss: 0.000983 loss_kpt: 0.000983 acc_pose: 0.711849 2023/08/09 16:15:06 - mmengine - INFO - Epoch(train) [125][370/442] lr: 5.000000e-04 eta: 3:39:44 time: 0.348102 data_time: 0.030730 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.844425 2023/08/09 16:15:09 - mmengine - INFO - Epoch(train) [125][380/442] lr: 5.000000e-04 eta: 3:39:41 time: 0.348958 data_time: 0.030925 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.794683 2023/08/09 16:15:13 - mmengine - INFO - Epoch(train) [125][390/442] lr: 5.000000e-04 eta: 3:39:37 time: 0.348907 data_time: 0.030796 memory: 4565 loss: 0.001002 loss_kpt: 0.001002 acc_pose: 0.814422 2023/08/09 16:15:16 - mmengine - INFO - Epoch(train) [125][400/442] lr: 5.000000e-04 eta: 3:39:32 time: 0.348873 data_time: 0.030768 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.778991 2023/08/09 16:15:20 - mmengine - INFO - Epoch(train) [125][410/442] lr: 5.000000e-04 eta: 3:39:29 time: 0.349525 data_time: 0.030312 memory: 4565 loss: 0.000963 loss_kpt: 0.000963 acc_pose: 0.821597 2023/08/09 16:15:23 - mmengine - INFO - Epoch(train) [125][420/442] lr: 5.000000e-04 eta: 3:39:26 time: 0.347107 data_time: 0.030169 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.812589 2023/08/09 16:15:27 - mmengine - INFO - Epoch(train) [125][430/442] lr: 5.000000e-04 eta: 3:39:23 time: 0.350796 data_time: 0.030301 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.874151 2023/08/09 16:15:30 - mmengine - INFO - Epoch(train) [125][440/442] lr: 5.000000e-04 eta: 3:39:20 time: 0.352802 data_time: 0.030567 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.804815 2023/08/09 16:15:31 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:15:35 - mmengine - INFO - Epoch(train) [126][ 10/442] lr: 5.000000e-04 eta: 3:39:16 time: 0.357425 data_time: 0.034093 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.787263 2023/08/09 16:15:38 - mmengine - INFO - Epoch(train) [126][ 20/442] lr: 5.000000e-04 eta: 3:39:13 time: 0.356802 data_time: 0.034102 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.844899 2023/08/09 16:15:42 - mmengine - INFO - Epoch(train) [126][ 30/442] lr: 5.000000e-04 eta: 3:39:09 time: 0.355621 data_time: 0.033957 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.828474 2023/08/09 16:15:45 - mmengine - INFO - Epoch(train) [126][ 40/442] lr: 5.000000e-04 eta: 3:39:06 time: 0.351897 data_time: 0.033654 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.846112 2023/08/09 16:15:49 - mmengine - INFO - Epoch(train) [126][ 50/442] lr: 5.000000e-04 eta: 3:39:02 time: 0.352827 data_time: 0.033921 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.818571 2023/08/09 16:15:52 - mmengine - INFO - Epoch(train) [126][ 60/442] lr: 5.000000e-04 eta: 3:38:58 time: 0.349105 data_time: 0.030504 memory: 4565 loss: 0.000971 loss_kpt: 0.000971 acc_pose: 0.854686 2023/08/09 16:15:56 - mmengine - INFO - Epoch(train) [126][ 70/442] lr: 5.000000e-04 eta: 3:38:55 time: 0.348585 data_time: 0.031127 memory: 4565 loss: 0.000970 loss_kpt: 0.000970 acc_pose: 0.745319 2023/08/09 16:15:59 - mmengine - INFO - Epoch(train) [126][ 80/442] lr: 5.000000e-04 eta: 3:38:51 time: 0.346118 data_time: 0.031088 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.852578 2023/08/09 16:16:03 - mmengine - INFO - Epoch(train) [126][ 90/442] lr: 5.000000e-04 eta: 3:38:47 time: 0.345062 data_time: 0.030977 memory: 4565 loss: 0.000963 loss_kpt: 0.000963 acc_pose: 0.830874 2023/08/09 16:16:06 - mmengine - INFO - Epoch(train) [126][100/442] lr: 5.000000e-04 eta: 3:38:43 time: 0.346040 data_time: 0.030985 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.757827 2023/08/09 16:16:10 - mmengine - INFO - Epoch(train) [126][110/442] lr: 5.000000e-04 eta: 3:38:40 time: 0.347460 data_time: 0.030757 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.898228 2023/08/09 16:16:13 - mmengine - INFO - Epoch(train) [126][120/442] lr: 5.000000e-04 eta: 3:38:36 time: 0.346697 data_time: 0.030895 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.806093 2023/08/09 16:16:17 - mmengine - INFO - Epoch(train) [126][130/442] lr: 5.000000e-04 eta: 3:38:33 time: 0.348678 data_time: 0.031223 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.696256 2023/08/09 16:16:20 - mmengine - INFO - Epoch(train) [126][140/442] lr: 5.000000e-04 eta: 3:38:29 time: 0.350649 data_time: 0.032233 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.776806 2023/08/09 16:16:24 - mmengine - INFO - Epoch(train) [126][150/442] lr: 5.000000e-04 eta: 3:38:25 time: 0.348394 data_time: 0.032177 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.885699 2023/08/09 16:16:27 - mmengine - INFO - Epoch(train) [126][160/442] lr: 5.000000e-04 eta: 3:38:21 time: 0.346452 data_time: 0.032222 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.818135 2023/08/09 16:16:30 - mmengine - INFO - Epoch(train) [126][170/442] lr: 5.000000e-04 eta: 3:38:17 time: 0.345206 data_time: 0.031520 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.857241 2023/08/09 16:16:34 - mmengine - INFO - Epoch(train) [126][180/442] lr: 5.000000e-04 eta: 3:38:14 time: 0.346510 data_time: 0.031175 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.855047 2023/08/09 16:16:37 - mmengine - INFO - Epoch(train) [126][190/442] lr: 5.000000e-04 eta: 3:38:10 time: 0.345139 data_time: 0.030285 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.886064 2023/08/09 16:16:41 - mmengine - INFO - Epoch(train) [126][200/442] lr: 5.000000e-04 eta: 3:38:07 time: 0.346198 data_time: 0.030882 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.805498 2023/08/09 16:16:44 - mmengine - INFO - Epoch(train) [126][210/442] lr: 5.000000e-04 eta: 3:38:03 time: 0.348107 data_time: 0.031282 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.820894 2023/08/09 16:16:48 - mmengine - INFO - Epoch(train) [126][220/442] lr: 5.000000e-04 eta: 3:38:01 time: 0.353904 data_time: 0.032045 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.782104 2023/08/09 16:16:52 - mmengine - INFO - Epoch(train) [126][230/442] lr: 5.000000e-04 eta: 3:37:58 time: 0.356163 data_time: 0.032761 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.830133 2023/08/09 16:16:56 - mmengine - INFO - Epoch(train) [126][240/442] lr: 5.000000e-04 eta: 3:37:56 time: 0.363397 data_time: 0.033361 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.825332 2023/08/09 16:16:59 - mmengine - INFO - Epoch(train) [126][250/442] lr: 5.000000e-04 eta: 3:37:55 time: 0.371954 data_time: 0.032977 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.849216 2023/08/09 16:17:03 - mmengine - INFO - Epoch(train) [126][260/442] lr: 5.000000e-04 eta: 3:37:54 time: 0.380120 data_time: 0.033007 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.822009 2023/08/09 16:17:07 - mmengine - INFO - Epoch(train) [126][270/442] lr: 5.000000e-04 eta: 3:37:51 time: 0.377598 data_time: 0.032567 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.837018 2023/08/09 16:17:10 - mmengine - INFO - Epoch(train) [126][280/442] lr: 5.000000e-04 eta: 3:37:47 time: 0.373309 data_time: 0.032909 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.809921 2023/08/09 16:17:14 - mmengine - INFO - Epoch(train) [126][290/442] lr: 5.000000e-04 eta: 3:37:43 time: 0.367029 data_time: 0.032699 memory: 4565 loss: 0.000970 loss_kpt: 0.000970 acc_pose: 0.787220 2023/08/09 16:17:17 - mmengine - INFO - Epoch(train) [126][300/442] lr: 5.000000e-04 eta: 3:37:40 time: 0.358606 data_time: 0.032569 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.819916 2023/08/09 16:17:21 - mmengine - INFO - Epoch(train) [126][310/442] lr: 5.000000e-04 eta: 3:37:36 time: 0.348094 data_time: 0.032146 memory: 4565 loss: 0.000998 loss_kpt: 0.000998 acc_pose: 0.799072 2023/08/09 16:17:24 - mmengine - INFO - Epoch(train) [126][320/442] lr: 5.000000e-04 eta: 3:37:32 time: 0.345934 data_time: 0.032357 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.814895 2023/08/09 16:17:28 - mmengine - INFO - Epoch(train) [126][330/442] lr: 5.000000e-04 eta: 3:37:28 time: 0.345795 data_time: 0.032193 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.839711 2023/08/09 16:17:31 - mmengine - INFO - Epoch(train) [126][340/442] lr: 5.000000e-04 eta: 3:37:25 time: 0.347288 data_time: 0.032352 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.784991 2023/08/09 16:17:35 - mmengine - INFO - Epoch(train) [126][350/442] lr: 5.000000e-04 eta: 3:37:24 time: 0.356930 data_time: 0.033177 memory: 4565 loss: 0.000998 loss_kpt: 0.000998 acc_pose: 0.773518 2023/08/09 16:17:39 - mmengine - INFO - Epoch(train) [126][360/442] lr: 5.000000e-04 eta: 3:37:21 time: 0.361369 data_time: 0.033669 memory: 4565 loss: 0.000990 loss_kpt: 0.000990 acc_pose: 0.843988 2023/08/09 16:17:42 - mmengine - INFO - Epoch(train) [126][370/442] lr: 5.000000e-04 eta: 3:37:17 time: 0.361651 data_time: 0.033422 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.839392 2023/08/09 16:17:46 - mmengine - INFO - Epoch(train) [126][380/442] lr: 5.000000e-04 eta: 3:37:14 time: 0.361816 data_time: 0.032944 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.782734 2023/08/09 16:17:50 - mmengine - INFO - Epoch(train) [126][390/442] lr: 5.000000e-04 eta: 3:37:11 time: 0.365163 data_time: 0.032613 memory: 4565 loss: 0.001004 loss_kpt: 0.001004 acc_pose: 0.778027 2023/08/09 16:17:53 - mmengine - INFO - Epoch(train) [126][400/442] lr: 5.000000e-04 eta: 3:37:07 time: 0.354690 data_time: 0.031922 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.807518 2023/08/09 16:17:57 - mmengine - INFO - Epoch(train) [126][410/442] lr: 5.000000e-04 eta: 3:37:04 time: 0.352317 data_time: 0.031543 memory: 4565 loss: 0.000992 loss_kpt: 0.000992 acc_pose: 0.760895 2023/08/09 16:18:00 - mmengine - INFO - Epoch(train) [126][420/442] lr: 5.000000e-04 eta: 3:37:00 time: 0.351043 data_time: 0.031589 memory: 4565 loss: 0.000986 loss_kpt: 0.000986 acc_pose: 0.808740 2023/08/09 16:18:03 - mmengine - INFO - Epoch(train) [126][430/442] lr: 5.000000e-04 eta: 3:36:56 time: 0.350037 data_time: 0.031466 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.841402 2023/08/09 16:18:07 - mmengine - INFO - Epoch(train) [126][440/442] lr: 5.000000e-04 eta: 3:36:52 time: 0.343402 data_time: 0.031322 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.868752 2023/08/09 16:18:07 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:18:11 - mmengine - INFO - Epoch(train) [127][ 10/442] lr: 5.000000e-04 eta: 3:36:48 time: 0.346729 data_time: 0.034666 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.799931 2023/08/09 16:18:14 - mmengine - INFO - Epoch(train) [127][ 20/442] lr: 5.000000e-04 eta: 3:36:44 time: 0.345049 data_time: 0.034696 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.860246 2023/08/09 16:18:18 - mmengine - INFO - Epoch(train) [127][ 30/442] lr: 5.000000e-04 eta: 3:36:41 time: 0.346799 data_time: 0.034652 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.940141 2023/08/09 16:18:21 - mmengine - INFO - Epoch(train) [127][ 40/442] lr: 5.000000e-04 eta: 3:36:37 time: 0.347384 data_time: 0.034573 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.855551 2023/08/09 16:18:25 - mmengine - INFO - Epoch(train) [127][ 50/442] lr: 5.000000e-04 eta: 3:36:33 time: 0.347810 data_time: 0.034812 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.809354 2023/08/09 16:18:28 - mmengine - INFO - Epoch(train) [127][ 60/442] lr: 5.000000e-04 eta: 3:36:29 time: 0.342253 data_time: 0.030887 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.842384 2023/08/09 16:18:32 - mmengine - INFO - Epoch(train) [127][ 70/442] lr: 5.000000e-04 eta: 3:36:26 time: 0.346342 data_time: 0.030885 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.767477 2023/08/09 16:18:35 - mmengine - INFO - Epoch(train) [127][ 80/442] lr: 5.000000e-04 eta: 3:36:22 time: 0.345443 data_time: 0.030822 memory: 4565 loss: 0.000971 loss_kpt: 0.000971 acc_pose: 0.784076 2023/08/09 16:18:39 - mmengine - INFO - Epoch(train) [127][ 90/442] lr: 5.000000e-04 eta: 3:36:19 time: 0.349884 data_time: 0.031148 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.876772 2023/08/09 16:18:42 - mmengine - INFO - Epoch(train) [127][100/442] lr: 5.000000e-04 eta: 3:36:16 time: 0.352488 data_time: 0.032010 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.849658 2023/08/09 16:18:46 - mmengine - INFO - Epoch(train) [127][110/442] lr: 5.000000e-04 eta: 3:36:12 time: 0.354160 data_time: 0.032892 memory: 4565 loss: 0.000970 loss_kpt: 0.000970 acc_pose: 0.796369 2023/08/09 16:18:49 - mmengine - INFO - Epoch(train) [127][120/442] lr: 5.000000e-04 eta: 3:36:08 time: 0.349733 data_time: 0.033350 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.751418 2023/08/09 16:18:53 - mmengine - INFO - Epoch(train) [127][130/442] lr: 5.000000e-04 eta: 3:36:05 time: 0.352256 data_time: 0.036590 memory: 4565 loss: 0.000963 loss_kpt: 0.000963 acc_pose: 0.834925 2023/08/09 16:18:56 - mmengine - INFO - Epoch(train) [127][140/442] lr: 5.000000e-04 eta: 3:36:01 time: 0.347370 data_time: 0.036371 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.856861 2023/08/09 16:19:00 - mmengine - INFO - Epoch(train) [127][150/442] lr: 5.000000e-04 eta: 3:35:57 time: 0.346581 data_time: 0.035532 memory: 4565 loss: 0.000963 loss_kpt: 0.000963 acc_pose: 0.889420 2023/08/09 16:19:03 - mmengine - INFO - Epoch(train) [127][160/442] lr: 5.000000e-04 eta: 3:35:54 time: 0.346909 data_time: 0.035062 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.843611 2023/08/09 16:19:07 - mmengine - INFO - Epoch(train) [127][170/442] lr: 5.000000e-04 eta: 3:35:50 time: 0.349520 data_time: 0.034792 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.860848 2023/08/09 16:19:10 - mmengine - INFO - Epoch(train) [127][180/442] lr: 5.000000e-04 eta: 3:35:47 time: 0.348192 data_time: 0.031958 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.877056 2023/08/09 16:19:14 - mmengine - INFO - Epoch(train) [127][190/442] lr: 5.000000e-04 eta: 3:35:43 time: 0.347929 data_time: 0.032582 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.895079 2023/08/09 16:19:17 - mmengine - INFO - Epoch(train) [127][200/442] lr: 5.000000e-04 eta: 3:35:39 time: 0.346625 data_time: 0.032591 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.809362 2023/08/09 16:19:21 - mmengine - INFO - Epoch(train) [127][210/442] lr: 5.000000e-04 eta: 3:35:35 time: 0.347955 data_time: 0.032319 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.912467 2023/08/09 16:19:24 - mmengine - INFO - Epoch(train) [127][220/442] lr: 5.000000e-04 eta: 3:35:31 time: 0.345023 data_time: 0.032118 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.814888 2023/08/09 16:19:28 - mmengine - INFO - Epoch(train) [127][230/442] lr: 5.000000e-04 eta: 3:35:28 time: 0.345099 data_time: 0.032235 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.882604 2023/08/09 16:19:31 - mmengine - INFO - Epoch(train) [127][240/442] lr: 5.000000e-04 eta: 3:35:24 time: 0.347466 data_time: 0.031586 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.866524 2023/08/09 16:19:34 - mmengine - INFO - Epoch(train) [127][250/442] lr: 5.000000e-04 eta: 3:35:21 time: 0.347888 data_time: 0.032134 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.812296 2023/08/09 16:19:38 - mmengine - INFO - Epoch(train) [127][260/442] lr: 5.000000e-04 eta: 3:35:17 time: 0.344664 data_time: 0.032196 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.911770 2023/08/09 16:19:41 - mmengine - INFO - Epoch(train) [127][270/442] lr: 5.000000e-04 eta: 3:35:13 time: 0.345054 data_time: 0.032000 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.888407 2023/08/09 16:19:45 - mmengine - INFO - Epoch(train) [127][280/442] lr: 5.000000e-04 eta: 3:35:09 time: 0.343383 data_time: 0.031427 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.803744 2023/08/09 16:19:48 - mmengine - INFO - Epoch(train) [127][290/442] lr: 5.000000e-04 eta: 3:35:05 time: 0.341871 data_time: 0.031500 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.900896 2023/08/09 16:19:52 - mmengine - INFO - Epoch(train) [127][300/442] lr: 5.000000e-04 eta: 3:35:01 time: 0.343648 data_time: 0.031009 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.768601 2023/08/09 16:19:54 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:19:55 - mmengine - INFO - Epoch(train) [127][310/442] lr: 5.000000e-04 eta: 3:34:58 time: 0.347435 data_time: 0.031208 memory: 4565 loss: 0.000941 loss_kpt: 0.000941 acc_pose: 0.806019 2023/08/09 16:19:59 - mmengine - INFO - Epoch(train) [127][320/442] lr: 5.000000e-04 eta: 3:34:56 time: 0.355011 data_time: 0.032042 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.875699 2023/08/09 16:20:03 - mmengine - INFO - Epoch(train) [127][330/442] lr: 5.000000e-04 eta: 3:34:53 time: 0.355864 data_time: 0.033209 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.828179 2023/08/09 16:20:06 - mmengine - INFO - Epoch(train) [127][340/442] lr: 5.000000e-04 eta: 3:34:49 time: 0.355600 data_time: 0.033310 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.836215 2023/08/09 16:20:10 - mmengine - INFO - Epoch(train) [127][350/442] lr: 5.000000e-04 eta: 3:34:46 time: 0.357256 data_time: 0.033952 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.806600 2023/08/09 16:20:13 - mmengine - INFO - Epoch(train) [127][360/442] lr: 5.000000e-04 eta: 3:34:42 time: 0.355844 data_time: 0.034162 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.833935 2023/08/09 16:20:17 - mmengine - INFO - Epoch(train) [127][370/442] lr: 5.000000e-04 eta: 3:34:39 time: 0.351584 data_time: 0.034075 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.812516 2023/08/09 16:20:20 - mmengine - INFO - Epoch(train) [127][380/442] lr: 5.000000e-04 eta: 3:34:36 time: 0.353676 data_time: 0.033867 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.847693 2023/08/09 16:20:24 - mmengine - INFO - Epoch(train) [127][390/442] lr: 5.000000e-04 eta: 3:34:32 time: 0.354046 data_time: 0.034507 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.863600 2023/08/09 16:20:27 - mmengine - INFO - Epoch(train) [127][400/442] lr: 5.000000e-04 eta: 3:34:29 time: 0.354410 data_time: 0.035666 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.846947 2023/08/09 16:20:31 - mmengine - INFO - Epoch(train) [127][410/442] lr: 5.000000e-04 eta: 3:34:26 time: 0.354212 data_time: 0.035554 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.825862 2023/08/09 16:20:34 - mmengine - INFO - Epoch(train) [127][420/442] lr: 5.000000e-04 eta: 3:34:22 time: 0.352839 data_time: 0.035346 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.910133 2023/08/09 16:20:38 - mmengine - INFO - Epoch(train) [127][430/442] lr: 5.000000e-04 eta: 3:34:19 time: 0.352529 data_time: 0.035379 memory: 4565 loss: 0.000983 loss_kpt: 0.000983 acc_pose: 0.825384 2023/08/09 16:20:41 - mmengine - INFO - Epoch(train) [127][440/442] lr: 5.000000e-04 eta: 3:34:16 time: 0.355376 data_time: 0.035520 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.840956 2023/08/09 16:20:42 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:20:46 - mmengine - INFO - Epoch(train) [128][ 10/442] lr: 5.000000e-04 eta: 3:34:14 time: 0.365178 data_time: 0.038651 memory: 4565 loss: 0.000980 loss_kpt: 0.000980 acc_pose: 0.838326 2023/08/09 16:20:50 - mmengine - INFO - Epoch(train) [128][ 20/442] lr: 5.000000e-04 eta: 3:34:12 time: 0.370918 data_time: 0.038600 memory: 4565 loss: 0.000974 loss_kpt: 0.000974 acc_pose: 0.844585 2023/08/09 16:20:54 - mmengine - INFO - Epoch(train) [128][ 30/442] lr: 5.000000e-04 eta: 3:34:09 time: 0.369627 data_time: 0.038530 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.801120 2023/08/09 16:20:57 - mmengine - INFO - Epoch(train) [128][ 40/442] lr: 5.000000e-04 eta: 3:34:06 time: 0.371336 data_time: 0.038961 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.841008 2023/08/09 16:21:01 - mmengine - INFO - Epoch(train) [128][ 50/442] lr: 5.000000e-04 eta: 3:34:02 time: 0.371378 data_time: 0.038535 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.797583 2023/08/09 16:21:04 - mmengine - INFO - Epoch(train) [128][ 60/442] lr: 5.000000e-04 eta: 3:33:59 time: 0.358492 data_time: 0.034252 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.859106 2023/08/09 16:21:08 - mmengine - INFO - Epoch(train) [128][ 70/442] lr: 5.000000e-04 eta: 3:33:56 time: 0.354497 data_time: 0.034530 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.842812 2023/08/09 16:21:12 - mmengine - INFO - Epoch(train) [128][ 80/442] lr: 5.000000e-04 eta: 3:33:54 time: 0.360690 data_time: 0.034573 memory: 4565 loss: 0.000940 loss_kpt: 0.000940 acc_pose: 0.913404 2023/08/09 16:21:15 - mmengine - INFO - Epoch(train) [128][ 90/442] lr: 5.000000e-04 eta: 3:33:50 time: 0.358694 data_time: 0.033787 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.837300 2023/08/09 16:21:19 - mmengine - INFO - Epoch(train) [128][100/442] lr: 5.000000e-04 eta: 3:33:46 time: 0.356566 data_time: 0.033791 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.817916 2023/08/09 16:21:22 - mmengine - INFO - Epoch(train) [128][110/442] lr: 5.000000e-04 eta: 3:33:43 time: 0.359441 data_time: 0.033759 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.769550 2023/08/09 16:21:26 - mmengine - INFO - Epoch(train) [128][120/442] lr: 5.000000e-04 eta: 3:33:41 time: 0.362476 data_time: 0.033825 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.816825 2023/08/09 16:21:29 - mmengine - INFO - Epoch(train) [128][130/442] lr: 5.000000e-04 eta: 3:33:38 time: 0.357405 data_time: 0.033795 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.837095 2023/08/09 16:21:33 - mmengine - INFO - Epoch(train) [128][140/442] lr: 5.000000e-04 eta: 3:33:35 time: 0.360233 data_time: 0.033836 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.838295 2023/08/09 16:21:37 - mmengine - INFO - Epoch(train) [128][150/442] lr: 5.000000e-04 eta: 3:33:33 time: 0.369623 data_time: 0.033980 memory: 4565 loss: 0.000981 loss_kpt: 0.000981 acc_pose: 0.840565 2023/08/09 16:21:41 - mmengine - INFO - Epoch(train) [128][160/442] lr: 5.000000e-04 eta: 3:33:32 time: 0.375026 data_time: 0.034740 memory: 4565 loss: 0.000987 loss_kpt: 0.000987 acc_pose: 0.838851 2023/08/09 16:21:45 - mmengine - INFO - Epoch(train) [128][170/442] lr: 5.000000e-04 eta: 3:33:29 time: 0.372356 data_time: 0.034422 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.873729 2023/08/09 16:21:48 - mmengine - INFO - Epoch(train) [128][180/442] lr: 5.000000e-04 eta: 3:33:26 time: 0.377141 data_time: 0.034327 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.830278 2023/08/09 16:21:52 - mmengine - INFO - Epoch(train) [128][190/442] lr: 5.000000e-04 eta: 3:33:23 time: 0.375340 data_time: 0.034312 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.844052 2023/08/09 16:21:55 - mmengine - INFO - Epoch(train) [128][200/442] lr: 5.000000e-04 eta: 3:33:20 time: 0.367856 data_time: 0.034414 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.888004 2023/08/09 16:21:59 - mmengine - INFO - Epoch(train) [128][210/442] lr: 5.000000e-04 eta: 3:33:17 time: 0.360806 data_time: 0.033696 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.720666 2023/08/09 16:22:03 - mmengine - INFO - Epoch(train) [128][220/442] lr: 5.000000e-04 eta: 3:33:15 time: 0.365258 data_time: 0.033831 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.846934 2023/08/09 16:22:07 - mmengine - INFO - Epoch(train) [128][230/442] lr: 5.000000e-04 eta: 3:33:13 time: 0.367733 data_time: 0.033856 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.746498 2023/08/09 16:22:10 - mmengine - INFO - Epoch(train) [128][240/442] lr: 5.000000e-04 eta: 3:33:10 time: 0.370402 data_time: 0.033891 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.879168 2023/08/09 16:22:15 - mmengine - INFO - Epoch(train) [128][250/442] lr: 5.000000e-04 eta: 3:33:10 time: 0.382775 data_time: 0.038105 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.835567 2023/08/09 16:22:18 - mmengine - INFO - Epoch(train) [128][260/442] lr: 5.000000e-04 eta: 3:33:06 time: 0.381997 data_time: 0.037750 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.791688 2023/08/09 16:22:22 - mmengine - INFO - Epoch(train) [128][270/442] lr: 5.000000e-04 eta: 3:33:02 time: 0.373895 data_time: 0.037367 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.859254 2023/08/09 16:22:25 - mmengine - INFO - Epoch(train) [128][280/442] lr: 5.000000e-04 eta: 3:32:59 time: 0.367654 data_time: 0.036762 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.845678 2023/08/09 16:22:29 - mmengine - INFO - Epoch(train) [128][290/442] lr: 5.000000e-04 eta: 3:32:56 time: 0.364604 data_time: 0.036678 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.868280 2023/08/09 16:22:32 - mmengine - INFO - Epoch(train) [128][300/442] lr: 5.000000e-04 eta: 3:32:52 time: 0.351423 data_time: 0.031751 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.777674 2023/08/09 16:22:36 - mmengine - INFO - Epoch(train) [128][310/442] lr: 5.000000e-04 eta: 3:32:49 time: 0.350928 data_time: 0.031163 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.890426 2023/08/09 16:22:39 - mmengine - INFO - Epoch(train) [128][320/442] lr: 5.000000e-04 eta: 3:32:45 time: 0.352821 data_time: 0.030963 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.849032 2023/08/09 16:22:43 - mmengine - INFO - Epoch(train) [128][330/442] lr: 5.000000e-04 eta: 3:32:42 time: 0.352774 data_time: 0.031538 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.787055 2023/08/09 16:22:46 - mmengine - INFO - Epoch(train) [128][340/442] lr: 5.000000e-04 eta: 3:32:39 time: 0.352548 data_time: 0.031103 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.814814 2023/08/09 16:22:50 - mmengine - INFO - Epoch(train) [128][350/442] lr: 5.000000e-04 eta: 3:32:35 time: 0.353133 data_time: 0.031289 memory: 4565 loss: 0.000953 loss_kpt: 0.000953 acc_pose: 0.776947 2023/08/09 16:22:53 - mmengine - INFO - Epoch(train) [128][360/442] lr: 5.000000e-04 eta: 3:32:32 time: 0.354094 data_time: 0.031131 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.865473 2023/08/09 16:22:57 - mmengine - INFO - Epoch(train) [128][370/442] lr: 5.000000e-04 eta: 3:32:28 time: 0.353597 data_time: 0.030984 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.889737 2023/08/09 16:23:00 - mmengine - INFO - Epoch(train) [128][380/442] lr: 5.000000e-04 eta: 3:32:25 time: 0.352994 data_time: 0.030505 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.861851 2023/08/09 16:23:04 - mmengine - INFO - Epoch(train) [128][390/442] lr: 5.000000e-04 eta: 3:32:22 time: 0.353191 data_time: 0.030435 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.841714 2023/08/09 16:23:08 - mmengine - INFO - Epoch(train) [128][400/442] lr: 5.000000e-04 eta: 3:32:18 time: 0.353446 data_time: 0.030418 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.776698 2023/08/09 16:23:11 - mmengine - INFO - Epoch(train) [128][410/442] lr: 5.000000e-04 eta: 3:32:15 time: 0.355060 data_time: 0.030468 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.836746 2023/08/09 16:23:15 - mmengine - INFO - Epoch(train) [128][420/442] lr: 5.000000e-04 eta: 3:32:11 time: 0.354381 data_time: 0.030381 memory: 4565 loss: 0.000972 loss_kpt: 0.000972 acc_pose: 0.834786 2023/08/09 16:23:18 - mmengine - INFO - Epoch(train) [128][430/442] lr: 5.000000e-04 eta: 3:32:09 time: 0.356908 data_time: 0.030261 memory: 4565 loss: 0.000970 loss_kpt: 0.000970 acc_pose: 0.789929 2023/08/09 16:23:22 - mmengine - INFO - Epoch(train) [128][440/442] lr: 5.000000e-04 eta: 3:32:05 time: 0.355998 data_time: 0.030176 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.857644 2023/08/09 16:23:22 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:23:26 - mmengine - INFO - Epoch(train) [129][ 10/442] lr: 5.000000e-04 eta: 3:32:02 time: 0.358833 data_time: 0.034011 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.868537 2023/08/09 16:23:30 - mmengine - INFO - Epoch(train) [129][ 20/442] lr: 5.000000e-04 eta: 3:31:59 time: 0.360573 data_time: 0.034757 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.861290 2023/08/09 16:23:33 - mmengine - INFO - Epoch(train) [129][ 30/442] lr: 5.000000e-04 eta: 3:31:55 time: 0.361233 data_time: 0.034843 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.830629 2023/08/09 16:23:37 - mmengine - INFO - Epoch(train) [129][ 40/442] lr: 5.000000e-04 eta: 3:31:52 time: 0.357205 data_time: 0.034891 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.777941 2023/08/09 16:23:40 - mmengine - INFO - Epoch(train) [129][ 50/442] lr: 5.000000e-04 eta: 3:31:48 time: 0.359250 data_time: 0.035228 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.871203 2023/08/09 16:23:44 - mmengine - INFO - Epoch(train) [129][ 60/442] lr: 5.000000e-04 eta: 3:31:45 time: 0.354329 data_time: 0.031108 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.892637 2023/08/09 16:23:47 - mmengine - INFO - Epoch(train) [129][ 70/442] lr: 5.000000e-04 eta: 3:31:42 time: 0.351520 data_time: 0.030392 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.827054 2023/08/09 16:23:51 - mmengine - INFO - Epoch(train) [129][ 80/442] lr: 5.000000e-04 eta: 3:31:39 time: 0.354229 data_time: 0.031121 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.756421 2023/08/09 16:23:55 - mmengine - INFO - Epoch(train) [129][ 90/442] lr: 5.000000e-04 eta: 3:31:35 time: 0.355832 data_time: 0.031474 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.832510 2023/08/09 16:23:58 - mmengine - INFO - Epoch(train) [129][100/442] lr: 5.000000e-04 eta: 3:31:32 time: 0.355308 data_time: 0.031466 memory: 4565 loss: 0.000955 loss_kpt: 0.000955 acc_pose: 0.845734 2023/08/09 16:24:02 - mmengine - INFO - Epoch(train) [129][110/442] lr: 5.000000e-04 eta: 3:31:29 time: 0.357367 data_time: 0.031442 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.831019 2023/08/09 16:24:05 - mmengine - INFO - Epoch(train) [129][120/442] lr: 5.000000e-04 eta: 3:31:25 time: 0.355682 data_time: 0.031455 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.807088 2023/08/09 16:24:09 - mmengine - INFO - Epoch(train) [129][130/442] lr: 5.000000e-04 eta: 3:31:22 time: 0.353636 data_time: 0.030693 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.812917 2023/08/09 16:24:12 - mmengine - INFO - Epoch(train) [129][140/442] lr: 5.000000e-04 eta: 3:31:18 time: 0.354039 data_time: 0.030541 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.871635 2023/08/09 16:24:16 - mmengine - INFO - Epoch(train) [129][150/442] lr: 5.000000e-04 eta: 3:31:15 time: 0.356930 data_time: 0.030747 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.867428 2023/08/09 16:24:20 - mmengine - INFO - Epoch(train) [129][160/442] lr: 5.000000e-04 eta: 3:31:12 time: 0.356082 data_time: 0.030722 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.827040 2023/08/09 16:24:23 - mmengine - INFO - Epoch(train) [129][170/442] lr: 5.000000e-04 eta: 3:31:09 time: 0.356061 data_time: 0.030719 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.844787 2023/08/09 16:24:27 - mmengine - INFO - Epoch(train) [129][180/442] lr: 5.000000e-04 eta: 3:31:05 time: 0.355998 data_time: 0.030711 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.822638 2023/08/09 16:24:30 - mmengine - INFO - Epoch(train) [129][190/442] lr: 5.000000e-04 eta: 3:31:02 time: 0.354228 data_time: 0.030446 memory: 4565 loss: 0.000974 loss_kpt: 0.000974 acc_pose: 0.900430 2023/08/09 16:24:34 - mmengine - INFO - Epoch(train) [129][200/442] lr: 5.000000e-04 eta: 3:30:58 time: 0.352142 data_time: 0.030217 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.793220 2023/08/09 16:24:37 - mmengine - INFO - Epoch(train) [129][210/442] lr: 5.000000e-04 eta: 3:30:55 time: 0.351836 data_time: 0.030236 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.864989 2023/08/09 16:24:41 - mmengine - INFO - Epoch(train) [129][220/442] lr: 5.000000e-04 eta: 3:30:52 time: 0.353806 data_time: 0.030316 memory: 4565 loss: 0.000971 loss_kpt: 0.000971 acc_pose: 0.897216 2023/08/09 16:24:44 - mmengine - INFO - Epoch(train) [129][230/442] lr: 5.000000e-04 eta: 3:30:49 time: 0.357520 data_time: 0.033784 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.848520 2023/08/09 16:24:48 - mmengine - INFO - Epoch(train) [129][240/442] lr: 5.000000e-04 eta: 3:30:45 time: 0.357491 data_time: 0.034039 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.862064 2023/08/09 16:24:52 - mmengine - INFO - Epoch(train) [129][250/442] lr: 5.000000e-04 eta: 3:30:42 time: 0.359238 data_time: 0.034080 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.840167 2023/08/09 16:24:55 - mmengine - INFO - Epoch(train) [129][260/442] lr: 5.000000e-04 eta: 3:30:39 time: 0.357706 data_time: 0.034021 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.790020 2023/08/09 16:24:59 - mmengine - INFO - Epoch(train) [129][270/442] lr: 5.000000e-04 eta: 3:30:36 time: 0.358357 data_time: 0.033962 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.822264 2023/08/09 16:25:02 - mmengine - INFO - Epoch(train) [129][280/442] lr: 5.000000e-04 eta: 3:30:33 time: 0.357792 data_time: 0.031186 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.838690 2023/08/09 16:25:06 - mmengine - INFO - Epoch(train) [129][290/442] lr: 5.000000e-04 eta: 3:30:31 time: 0.365054 data_time: 0.032044 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.873694 2023/08/09 16:25:10 - mmengine - INFO - Epoch(train) [129][300/442] lr: 5.000000e-04 eta: 3:30:27 time: 0.362248 data_time: 0.032166 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.833973 2023/08/09 16:25:13 - mmengine - INFO - Epoch(train) [129][310/442] lr: 5.000000e-04 eta: 3:30:24 time: 0.362579 data_time: 0.032181 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.770069 2023/08/09 16:25:17 - mmengine - INFO - Epoch(train) [129][320/442] lr: 5.000000e-04 eta: 3:30:20 time: 0.359961 data_time: 0.032339 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.805108 2023/08/09 16:25:20 - mmengine - INFO - Epoch(train) [129][330/442] lr: 5.000000e-04 eta: 3:30:16 time: 0.356347 data_time: 0.031768 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.924902 2023/08/09 16:25:24 - mmengine - INFO - Epoch(train) [129][340/442] lr: 5.000000e-04 eta: 3:30:13 time: 0.349381 data_time: 0.030755 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.831353 2023/08/09 16:25:27 - mmengine - INFO - Epoch(train) [129][350/442] lr: 5.000000e-04 eta: 3:30:09 time: 0.350395 data_time: 0.030800 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.836286 2023/08/09 16:25:31 - mmengine - INFO - Epoch(train) [129][360/442] lr: 5.000000e-04 eta: 3:30:06 time: 0.352073 data_time: 0.030912 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.836753 2023/08/09 16:25:34 - mmengine - INFO - Epoch(train) [129][370/442] lr: 5.000000e-04 eta: 3:30:03 time: 0.353215 data_time: 0.031247 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.864320 2023/08/09 16:25:38 - mmengine - INFO - Epoch(train) [129][380/442] lr: 5.000000e-04 eta: 3:30:00 time: 0.356767 data_time: 0.031345 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.886145 2023/08/09 16:25:42 - mmengine - INFO - Epoch(train) [129][390/442] lr: 5.000000e-04 eta: 3:29:56 time: 0.356601 data_time: 0.031873 memory: 4565 loss: 0.000955 loss_kpt: 0.000955 acc_pose: 0.851940 2023/08/09 16:25:45 - mmengine - INFO - Epoch(train) [129][400/442] lr: 5.000000e-04 eta: 3:29:53 time: 0.356388 data_time: 0.031739 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.845729 2023/08/09 16:25:49 - mmengine - INFO - Epoch(train) [129][410/442] lr: 5.000000e-04 eta: 3:29:50 time: 0.356399 data_time: 0.031826 memory: 4565 loss: 0.000974 loss_kpt: 0.000974 acc_pose: 0.849375 2023/08/09 16:25:52 - mmengine - INFO - Epoch(train) [129][420/442] lr: 5.000000e-04 eta: 3:29:47 time: 0.360121 data_time: 0.031559 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.791157 2023/08/09 16:25:54 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:25:56 - mmengine - INFO - Epoch(train) [129][430/442] lr: 5.000000e-04 eta: 3:29:44 time: 0.357051 data_time: 0.032194 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.868982 2023/08/09 16:25:59 - mmengine - INFO - Epoch(train) [129][440/442] lr: 5.000000e-04 eta: 3:29:40 time: 0.356407 data_time: 0.031838 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.781364 2023/08/09 16:26:00 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:26:04 - mmengine - INFO - Epoch(train) [130][ 10/442] lr: 5.000000e-04 eta: 3:29:36 time: 0.358167 data_time: 0.034913 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.900774 2023/08/09 16:26:07 - mmengine - INFO - Epoch(train) [130][ 20/442] lr: 5.000000e-04 eta: 3:29:32 time: 0.353014 data_time: 0.034637 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.862999 2023/08/09 16:26:11 - mmengine - INFO - Epoch(train) [130][ 30/442] lr: 5.000000e-04 eta: 3:29:29 time: 0.351096 data_time: 0.034278 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.845344 2023/08/09 16:26:14 - mmengine - INFO - Epoch(train) [130][ 40/442] lr: 5.000000e-04 eta: 3:29:25 time: 0.352039 data_time: 0.033693 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.755339 2023/08/09 16:26:18 - mmengine - INFO - Epoch(train) [130][ 50/442] lr: 5.000000e-04 eta: 3:29:22 time: 0.356632 data_time: 0.034361 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.800311 2023/08/09 16:26:21 - mmengine - INFO - Epoch(train) [130][ 60/442] lr: 5.000000e-04 eta: 3:29:19 time: 0.353479 data_time: 0.030734 memory: 4565 loss: 0.000953 loss_kpt: 0.000953 acc_pose: 0.879676 2023/08/09 16:26:25 - mmengine - INFO - Epoch(train) [130][ 70/442] lr: 5.000000e-04 eta: 3:29:16 time: 0.354550 data_time: 0.030898 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.792737 2023/08/09 16:26:28 - mmengine - INFO - Epoch(train) [130][ 80/442] lr: 5.000000e-04 eta: 3:29:12 time: 0.354852 data_time: 0.030846 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.828123 2023/08/09 16:26:32 - mmengine - INFO - Epoch(train) [130][ 90/442] lr: 5.000000e-04 eta: 3:29:09 time: 0.357252 data_time: 0.030533 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.883741 2023/08/09 16:26:36 - mmengine - INFO - Epoch(train) [130][100/442] lr: 5.000000e-04 eta: 3:29:06 time: 0.355593 data_time: 0.030528 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.874424 2023/08/09 16:26:39 - mmengine - INFO - Epoch(train) [130][110/442] lr: 5.000000e-04 eta: 3:29:02 time: 0.355548 data_time: 0.030651 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.796220 2023/08/09 16:26:43 - mmengine - INFO - Epoch(train) [130][120/442] lr: 5.000000e-04 eta: 3:28:59 time: 0.357573 data_time: 0.030708 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.857746 2023/08/09 16:26:46 - mmengine - INFO - Epoch(train) [130][130/442] lr: 5.000000e-04 eta: 3:28:56 time: 0.360239 data_time: 0.031261 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.777347 2023/08/09 16:26:50 - mmengine - INFO - Epoch(train) [130][140/442] lr: 5.000000e-04 eta: 3:28:53 time: 0.356835 data_time: 0.031312 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.871912 2023/08/09 16:26:53 - mmengine - INFO - Epoch(train) [130][150/442] lr: 5.000000e-04 eta: 3:28:49 time: 0.356163 data_time: 0.031088 memory: 4565 loss: 0.000989 loss_kpt: 0.000989 acc_pose: 0.829982 2023/08/09 16:26:57 - mmengine - INFO - Epoch(train) [130][160/442] lr: 5.000000e-04 eta: 3:28:46 time: 0.356078 data_time: 0.031156 memory: 4565 loss: 0.000988 loss_kpt: 0.000988 acc_pose: 0.842062 2023/08/09 16:27:01 - mmengine - INFO - Epoch(train) [130][170/442] lr: 5.000000e-04 eta: 3:28:42 time: 0.354468 data_time: 0.031363 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.820330 2023/08/09 16:27:04 - mmengine - INFO - Epoch(train) [130][180/442] lr: 5.000000e-04 eta: 3:28:39 time: 0.352753 data_time: 0.031154 memory: 4565 loss: 0.000972 loss_kpt: 0.000972 acc_pose: 0.803797 2023/08/09 16:27:08 - mmengine - INFO - Epoch(train) [130][190/442] lr: 5.000000e-04 eta: 3:28:36 time: 0.353612 data_time: 0.031380 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.849147 2023/08/09 16:27:11 - mmengine - INFO - Epoch(train) [130][200/442] lr: 5.000000e-04 eta: 3:28:32 time: 0.353859 data_time: 0.031782 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.830464 2023/08/09 16:27:15 - mmengine - INFO - Epoch(train) [130][210/442] lr: 5.000000e-04 eta: 3:28:29 time: 0.353410 data_time: 0.032167 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.812161 2023/08/09 16:27:18 - mmengine - INFO - Epoch(train) [130][220/442] lr: 5.000000e-04 eta: 3:28:25 time: 0.352327 data_time: 0.032068 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.756000 2023/08/09 16:27:22 - mmengine - INFO - Epoch(train) [130][230/442] lr: 5.000000e-04 eta: 3:28:22 time: 0.354521 data_time: 0.032121 memory: 4565 loss: 0.000974 loss_kpt: 0.000974 acc_pose: 0.785714 2023/08/09 16:27:25 - mmengine - INFO - Epoch(train) [130][240/442] lr: 5.000000e-04 eta: 3:28:19 time: 0.356034 data_time: 0.032426 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.892765 2023/08/09 16:27:29 - mmengine - INFO - Epoch(train) [130][250/442] lr: 5.000000e-04 eta: 3:28:16 time: 0.359492 data_time: 0.032913 memory: 4565 loss: 0.000953 loss_kpt: 0.000953 acc_pose: 0.895344 2023/08/09 16:27:33 - mmengine - INFO - Epoch(train) [130][260/442] lr: 5.000000e-04 eta: 3:28:13 time: 0.363710 data_time: 0.032532 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.793567 2023/08/09 16:27:36 - mmengine - INFO - Epoch(train) [130][270/442] lr: 5.000000e-04 eta: 3:28:10 time: 0.363754 data_time: 0.032770 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.844154 2023/08/09 16:27:40 - mmengine - INFO - Epoch(train) [130][280/442] lr: 5.000000e-04 eta: 3:28:06 time: 0.360804 data_time: 0.032439 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.810176 2023/08/09 16:27:43 - mmengine - INFO - Epoch(train) [130][290/442] lr: 5.000000e-04 eta: 3:28:03 time: 0.359537 data_time: 0.031975 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.794020 2023/08/09 16:27:47 - mmengine - INFO - Epoch(train) [130][300/442] lr: 5.000000e-04 eta: 3:28:01 time: 0.361080 data_time: 0.031478 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.815248 2023/08/09 16:27:51 - mmengine - INFO - Epoch(train) [130][310/442] lr: 5.000000e-04 eta: 3:27:58 time: 0.360444 data_time: 0.032014 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.741505 2023/08/09 16:27:55 - mmengine - INFO - Epoch(train) [130][320/442] lr: 5.000000e-04 eta: 3:27:55 time: 0.364368 data_time: 0.032597 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.756271 2023/08/09 16:27:58 - mmengine - INFO - Epoch(train) [130][330/442] lr: 5.000000e-04 eta: 3:27:52 time: 0.364642 data_time: 0.032834 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.834801 2023/08/09 16:28:02 - mmengine - INFO - Epoch(train) [130][340/442] lr: 5.000000e-04 eta: 3:27:48 time: 0.363866 data_time: 0.032866 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.869985 2023/08/09 16:28:05 - mmengine - INFO - Epoch(train) [130][350/442] lr: 5.000000e-04 eta: 3:27:44 time: 0.358234 data_time: 0.032661 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.789225 2023/08/09 16:28:09 - mmengine - INFO - Epoch(train) [130][360/442] lr: 5.000000e-04 eta: 3:27:41 time: 0.355859 data_time: 0.032373 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.893150 2023/08/09 16:28:12 - mmengine - INFO - Epoch(train) [130][370/442] lr: 5.000000e-04 eta: 3:27:38 time: 0.356340 data_time: 0.031732 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.827503 2023/08/09 16:28:16 - mmengine - INFO - Epoch(train) [130][380/442] lr: 5.000000e-04 eta: 3:27:35 time: 0.356753 data_time: 0.031721 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.793460 2023/08/09 16:28:20 - mmengine - INFO - Epoch(train) [130][390/442] lr: 5.000000e-04 eta: 3:27:32 time: 0.359229 data_time: 0.031765 memory: 4565 loss: 0.000953 loss_kpt: 0.000953 acc_pose: 0.806165 2023/08/09 16:28:23 - mmengine - INFO - Epoch(train) [130][400/442] lr: 5.000000e-04 eta: 3:27:28 time: 0.359390 data_time: 0.031788 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.761247 2023/08/09 16:28:27 - mmengine - INFO - Epoch(train) [130][410/442] lr: 5.000000e-04 eta: 3:27:25 time: 0.360568 data_time: 0.031490 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.845084 2023/08/09 16:28:30 - mmengine - INFO - Epoch(train) [130][420/442] lr: 5.000000e-04 eta: 3:27:22 time: 0.356021 data_time: 0.031043 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.904280 2023/08/09 16:28:34 - mmengine - INFO - Epoch(train) [130][430/442] lr: 5.000000e-04 eta: 3:27:18 time: 0.355241 data_time: 0.031004 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.810665 2023/08/09 16:28:37 - mmengine - INFO - Epoch(train) [130][440/442] lr: 5.000000e-04 eta: 3:27:15 time: 0.353931 data_time: 0.031322 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.738761 2023/08/09 16:28:38 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:28:38 - mmengine - INFO - Saving checkpoint at 130 epochs 2023/08/09 16:28:44 - mmengine - INFO - Epoch(val) [130][ 10/108] eta: 0:00:20 time: 0.197321 data_time: 0.014006 memory: 4565 2023/08/09 16:28:46 - mmengine - INFO - Epoch(val) [130][ 20/108] eta: 0:00:17 time: 0.196979 data_time: 0.013691 memory: 1624 2023/08/09 16:28:48 - mmengine - INFO - Epoch(val) [130][ 30/108] eta: 0:00:15 time: 0.199305 data_time: 0.016012 memory: 1624 2023/08/09 16:28:50 - mmengine - INFO - Epoch(val) [130][ 40/108] eta: 0:00:13 time: 0.198824 data_time: 0.015569 memory: 1624 2023/08/09 16:28:52 - mmengine - INFO - Epoch(val) [130][ 50/108] eta: 0:00:11 time: 0.200775 data_time: 0.015661 memory: 1624 2023/08/09 16:28:54 - mmengine - INFO - Epoch(val) [130][ 60/108] eta: 0:00:09 time: 0.198218 data_time: 0.013584 memory: 1624 2023/08/09 16:28:56 - mmengine - INFO - Epoch(val) [130][ 70/108] eta: 0:00:07 time: 0.198207 data_time: 0.013511 memory: 1624 2023/08/09 16:28:58 - mmengine - INFO - Epoch(val) [130][ 80/108] eta: 0:00:05 time: 0.195469 data_time: 0.010834 memory: 1624 2023/08/09 16:29:00 - mmengine - INFO - Epoch(val) [130][ 90/108] eta: 0:00:03 time: 0.195718 data_time: 0.011010 memory: 1624 2023/08/09 16:29:01 - mmengine - INFO - Epoch(val) [130][100/108] eta: 0:00:01 time: 0.195709 data_time: 0.010982 memory: 1624 2023/08/09 16:29:03 - mmengine - INFO - Evaluating PCKAccuracy (normalized by ``"bbox_size"``)... 2023/08/09 16:29:03 - mmengine - INFO - Evaluating AUC... 2023/08/09 16:29:04 - mmengine - INFO - Evaluating EPE... 2023/08/09 16:29:04 - mmengine - INFO - Epoch(val) [130][108/108] PCK: 0.962184 AUC: 0.608664 EPE: 14.779995 data_time: 0.013009 time: 0.196421 2023/08/09 16:29:07 - mmengine - INFO - Epoch(train) [131][ 10/442] lr: 5.000000e-04 eta: 3:27:11 time: 0.357753 data_time: 0.035475 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.842329 2023/08/09 16:29:11 - mmengine - INFO - Epoch(train) [131][ 20/442] lr: 5.000000e-04 eta: 3:27:08 time: 0.356448 data_time: 0.035678 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.818343 2023/08/09 16:29:14 - mmengine - INFO - Epoch(train) [131][ 30/442] lr: 5.000000e-04 eta: 3:27:04 time: 0.355590 data_time: 0.035650 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.896897 2023/08/09 16:29:18 - mmengine - INFO - Epoch(train) [131][ 40/442] lr: 5.000000e-04 eta: 3:27:00 time: 0.353093 data_time: 0.035663 memory: 4565 loss: 0.000996 loss_kpt: 0.000996 acc_pose: 0.780121 2023/08/09 16:29:21 - mmengine - INFO - Epoch(train) [131][ 50/442] lr: 5.000000e-04 eta: 3:26:56 time: 0.352822 data_time: 0.035667 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.877815 2023/08/09 16:29:25 - mmengine - INFO - Epoch(train) [131][ 60/442] lr: 5.000000e-04 eta: 3:26:53 time: 0.350129 data_time: 0.034967 memory: 4565 loss: 0.000994 loss_kpt: 0.000994 acc_pose: 0.825065 2023/08/09 16:29:28 - mmengine - INFO - Epoch(train) [131][ 70/442] lr: 5.000000e-04 eta: 3:26:50 time: 0.348637 data_time: 0.034861 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.820449 2023/08/09 16:29:32 - mmengine - INFO - Epoch(train) [131][ 80/442] lr: 5.000000e-04 eta: 3:26:46 time: 0.348076 data_time: 0.035168 memory: 4565 loss: 0.000975 loss_kpt: 0.000975 acc_pose: 0.847291 2023/08/09 16:29:35 - mmengine - INFO - Epoch(train) [131][ 90/442] lr: 5.000000e-04 eta: 3:26:42 time: 0.348315 data_time: 0.035283 memory: 4565 loss: 0.000971 loss_kpt: 0.000971 acc_pose: 0.784988 2023/08/09 16:29:39 - mmengine - INFO - Epoch(train) [131][100/442] lr: 5.000000e-04 eta: 3:26:38 time: 0.347528 data_time: 0.035153 memory: 4565 loss: 0.000997 loss_kpt: 0.000997 acc_pose: 0.830548 2023/08/09 16:29:42 - mmengine - INFO - Epoch(train) [131][110/442] lr: 5.000000e-04 eta: 3:26:34 time: 0.344393 data_time: 0.031652 memory: 4565 loss: 0.000985 loss_kpt: 0.000985 acc_pose: 0.766015 2023/08/09 16:29:46 - mmengine - INFO - Epoch(train) [131][120/442] lr: 5.000000e-04 eta: 3:26:30 time: 0.343347 data_time: 0.031574 memory: 4565 loss: 0.000976 loss_kpt: 0.000976 acc_pose: 0.855496 2023/08/09 16:29:49 - mmengine - INFO - Epoch(train) [131][130/442] lr: 5.000000e-04 eta: 3:26:28 time: 0.348104 data_time: 0.032044 memory: 4565 loss: 0.000982 loss_kpt: 0.000982 acc_pose: 0.810587 2023/08/09 16:29:53 - mmengine - INFO - Epoch(train) [131][140/442] lr: 5.000000e-04 eta: 3:26:24 time: 0.349541 data_time: 0.031801 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.842025 2023/08/09 16:29:56 - mmengine - INFO - Epoch(train) [131][150/442] lr: 5.000000e-04 eta: 3:26:20 time: 0.349232 data_time: 0.031753 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.791552 2023/08/09 16:30:00 - mmengine - INFO - Epoch(train) [131][160/442] lr: 5.000000e-04 eta: 3:26:17 time: 0.351098 data_time: 0.031331 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.871868 2023/08/09 16:30:03 - mmengine - INFO - Epoch(train) [131][170/442] lr: 5.000000e-04 eta: 3:26:13 time: 0.350347 data_time: 0.031364 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.833602 2023/08/09 16:30:07 - mmengine - INFO - Epoch(train) [131][180/442] lr: 5.000000e-04 eta: 3:26:09 time: 0.348684 data_time: 0.030860 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.817580 2023/08/09 16:30:11 - mmengine - INFO - Epoch(train) [131][190/442] lr: 5.000000e-04 eta: 3:26:07 time: 0.356879 data_time: 0.031131 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.849728 2023/08/09 16:30:14 - mmengine - INFO - Epoch(train) [131][200/442] lr: 5.000000e-04 eta: 3:26:04 time: 0.357782 data_time: 0.031414 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.863980 2023/08/09 16:30:18 - mmengine - INFO - Epoch(train) [131][210/442] lr: 5.000000e-04 eta: 3:26:02 time: 0.364280 data_time: 0.031904 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.836544 2023/08/09 16:30:22 - mmengine - INFO - Epoch(train) [131][220/442] lr: 5.000000e-04 eta: 3:25:59 time: 0.373705 data_time: 0.032015 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.877903 2023/08/09 16:30:26 - mmengine - INFO - Epoch(train) [131][230/442] lr: 5.000000e-04 eta: 3:25:57 time: 0.379582 data_time: 0.032047 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.825643 2023/08/09 16:30:29 - mmengine - INFO - Epoch(train) [131][240/442] lr: 5.000000e-04 eta: 3:25:54 time: 0.371811 data_time: 0.034920 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.853708 2023/08/09 16:30:33 - mmengine - INFO - Epoch(train) [131][250/442] lr: 5.000000e-04 eta: 3:25:50 time: 0.371930 data_time: 0.034506 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.784693 2023/08/09 16:30:36 - mmengine - INFO - Epoch(train) [131][260/442] lr: 5.000000e-04 eta: 3:25:46 time: 0.363159 data_time: 0.034129 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.953417 2023/08/09 16:30:40 - mmengine - INFO - Epoch(train) [131][270/442] lr: 5.000000e-04 eta: 3:25:42 time: 0.354980 data_time: 0.034095 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.830251 2023/08/09 16:30:43 - mmengine - INFO - Epoch(train) [131][280/442] lr: 5.000000e-04 eta: 3:25:38 time: 0.345848 data_time: 0.033780 memory: 4565 loss: 0.000963 loss_kpt: 0.000963 acc_pose: 0.850694 2023/08/09 16:30:46 - mmengine - INFO - Epoch(train) [131][290/442] lr: 5.000000e-04 eta: 3:25:35 time: 0.343704 data_time: 0.030515 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.801894 2023/08/09 16:30:50 - mmengine - INFO - Epoch(train) [131][300/442] lr: 5.000000e-04 eta: 3:25:31 time: 0.344651 data_time: 0.030447 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.891352 2023/08/09 16:30:53 - mmengine - INFO - Epoch(train) [131][310/442] lr: 5.000000e-04 eta: 3:25:27 time: 0.343435 data_time: 0.030303 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.806911 2023/08/09 16:30:57 - mmengine - INFO - Epoch(train) [131][320/442] lr: 5.000000e-04 eta: 3:25:23 time: 0.343074 data_time: 0.030107 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.850355 2023/08/09 16:31:00 - mmengine - INFO - Epoch(train) [131][330/442] lr: 5.000000e-04 eta: 3:25:19 time: 0.343361 data_time: 0.030364 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.753856 2023/08/09 16:31:04 - mmengine - INFO - Epoch(train) [131][340/442] lr: 5.000000e-04 eta: 3:25:16 time: 0.344259 data_time: 0.030763 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.825460 2023/08/09 16:31:07 - mmengine - INFO - Epoch(train) [131][350/442] lr: 5.000000e-04 eta: 3:25:12 time: 0.342239 data_time: 0.031067 memory: 4565 loss: 0.000971 loss_kpt: 0.000971 acc_pose: 0.928124 2023/08/09 16:31:10 - mmengine - INFO - Epoch(train) [131][360/442] lr: 5.000000e-04 eta: 3:25:08 time: 0.342699 data_time: 0.031178 memory: 4565 loss: 0.000971 loss_kpt: 0.000971 acc_pose: 0.778284 2023/08/09 16:31:14 - mmengine - INFO - Epoch(train) [131][370/442] lr: 5.000000e-04 eta: 3:25:04 time: 0.341441 data_time: 0.031140 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.763752 2023/08/09 16:31:17 - mmengine - INFO - Epoch(train) [131][380/442] lr: 5.000000e-04 eta: 3:25:00 time: 0.340342 data_time: 0.030764 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.809389 2023/08/09 16:31:21 - mmengine - INFO - Epoch(train) [131][390/442] lr: 5.000000e-04 eta: 3:24:56 time: 0.342891 data_time: 0.033433 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.827332 2023/08/09 16:31:24 - mmengine - INFO - Epoch(train) [131][400/442] lr: 5.000000e-04 eta: 3:24:53 time: 0.346865 data_time: 0.033314 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.848598 2023/08/09 16:31:28 - mmengine - INFO - Epoch(train) [131][410/442] lr: 5.000000e-04 eta: 3:24:49 time: 0.348383 data_time: 0.033478 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.814191 2023/08/09 16:31:31 - mmengine - INFO - Epoch(train) [131][420/442] lr: 5.000000e-04 eta: 3:24:46 time: 0.349309 data_time: 0.033772 memory: 4565 loss: 0.000941 loss_kpt: 0.000941 acc_pose: 0.850970 2023/08/09 16:31:35 - mmengine - INFO - Epoch(train) [131][430/442] lr: 5.000000e-04 eta: 3:24:42 time: 0.349389 data_time: 0.033827 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.816188 2023/08/09 16:31:38 - mmengine - INFO - Epoch(train) [131][440/442] lr: 5.000000e-04 eta: 3:24:38 time: 0.347873 data_time: 0.030816 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.910979 2023/08/09 16:31:39 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:31:42 - mmengine - INFO - Epoch(train) [132][ 10/442] lr: 5.000000e-04 eta: 3:24:34 time: 0.348702 data_time: 0.034165 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.779386 2023/08/09 16:31:46 - mmengine - INFO - Epoch(train) [132][ 20/442] lr: 5.000000e-04 eta: 3:24:30 time: 0.347755 data_time: 0.033958 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.877524 2023/08/09 16:31:49 - mmengine - INFO - Epoch(train) [132][ 30/442] lr: 5.000000e-04 eta: 3:24:27 time: 0.348473 data_time: 0.034760 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.887559 2023/08/09 16:31:53 - mmengine - INFO - Epoch(train) [132][ 40/442] lr: 5.000000e-04 eta: 3:24:23 time: 0.350372 data_time: 0.034770 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.824867 2023/08/09 16:31:56 - mmengine - INFO - Epoch(train) [132][ 50/442] lr: 5.000000e-04 eta: 3:24:19 time: 0.348804 data_time: 0.035177 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.842513 2023/08/09 16:32:00 - mmengine - INFO - Epoch(train) [132][ 60/442] lr: 5.000000e-04 eta: 3:24:15 time: 0.341683 data_time: 0.031324 memory: 4565 loss: 0.000897 loss_kpt: 0.000897 acc_pose: 0.886261 2023/08/09 16:32:03 - mmengine - INFO - Epoch(train) [132][ 70/442] lr: 5.000000e-04 eta: 3:24:11 time: 0.340987 data_time: 0.031251 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.759089 2023/08/09 16:32:06 - mmengine - INFO - Epoch(train) [132][ 80/442] lr: 5.000000e-04 eta: 3:24:07 time: 0.339974 data_time: 0.030356 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.851973 2023/08/09 16:32:10 - mmengine - INFO - Epoch(train) [132][ 90/442] lr: 5.000000e-04 eta: 3:24:03 time: 0.339774 data_time: 0.030547 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.816681 2023/08/09 16:32:13 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:32:13 - mmengine - INFO - Epoch(train) [132][100/442] lr: 5.000000e-04 eta: 3:24:00 time: 0.342565 data_time: 0.030742 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.761783 2023/08/09 16:32:17 - mmengine - INFO - Epoch(train) [132][110/442] lr: 5.000000e-04 eta: 3:23:56 time: 0.345583 data_time: 0.031022 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.818961 2023/08/09 16:32:20 - mmengine - INFO - Epoch(train) [132][120/442] lr: 5.000000e-04 eta: 3:23:52 time: 0.345750 data_time: 0.031026 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.852705 2023/08/09 16:32:24 - mmengine - INFO - Epoch(train) [132][130/442] lr: 5.000000e-04 eta: 3:23:49 time: 0.351470 data_time: 0.034335 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.818306 2023/08/09 16:32:27 - mmengine - INFO - Epoch(train) [132][140/442] lr: 5.000000e-04 eta: 3:23:45 time: 0.350567 data_time: 0.034124 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.829179 2023/08/09 16:32:31 - mmengine - INFO - Epoch(train) [132][150/442] lr: 5.000000e-04 eta: 3:23:41 time: 0.348350 data_time: 0.034186 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.848484 2023/08/09 16:32:34 - mmengine - INFO - Epoch(train) [132][160/442] lr: 5.000000e-04 eta: 3:23:38 time: 0.348180 data_time: 0.034153 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.824422 2023/08/09 16:32:38 - mmengine - INFO - Epoch(train) [132][170/442] lr: 5.000000e-04 eta: 3:23:34 time: 0.348594 data_time: 0.034200 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.788497 2023/08/09 16:32:41 - mmengine - INFO - Epoch(train) [132][180/442] lr: 5.000000e-04 eta: 3:23:31 time: 0.345187 data_time: 0.031257 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.926808 2023/08/09 16:32:45 - mmengine - INFO - Epoch(train) [132][190/442] lr: 5.000000e-04 eta: 3:23:27 time: 0.345701 data_time: 0.031271 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.825585 2023/08/09 16:32:48 - mmengine - INFO - Epoch(train) [132][200/442] lr: 5.000000e-04 eta: 3:23:23 time: 0.345273 data_time: 0.031187 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.823585 2023/08/09 16:32:51 - mmengine - INFO - Epoch(train) [132][210/442] lr: 5.000000e-04 eta: 3:23:19 time: 0.342261 data_time: 0.030809 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.779137 2023/08/09 16:32:55 - mmengine - INFO - Epoch(train) [132][220/442] lr: 5.000000e-04 eta: 3:23:15 time: 0.341261 data_time: 0.030848 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.856537 2023/08/09 16:32:58 - mmengine - INFO - Epoch(train) [132][230/442] lr: 5.000000e-04 eta: 3:23:11 time: 0.340601 data_time: 0.030622 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.762193 2023/08/09 16:33:02 - mmengine - INFO - Epoch(train) [132][240/442] lr: 5.000000e-04 eta: 3:23:07 time: 0.341249 data_time: 0.030824 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.842166 2023/08/09 16:33:05 - mmengine - INFO - Epoch(train) [132][250/442] lr: 5.000000e-04 eta: 3:23:04 time: 0.342723 data_time: 0.030921 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.865370 2023/08/09 16:33:09 - mmengine - INFO - Epoch(train) [132][260/442] lr: 5.000000e-04 eta: 3:23:00 time: 0.343242 data_time: 0.031221 memory: 4565 loss: 0.000941 loss_kpt: 0.000941 acc_pose: 0.845277 2023/08/09 16:33:12 - mmengine - INFO - Epoch(train) [132][270/442] lr: 5.000000e-04 eta: 3:22:56 time: 0.346567 data_time: 0.031079 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.772266 2023/08/09 16:33:15 - mmengine - INFO - Epoch(train) [132][280/442] lr: 5.000000e-04 eta: 3:22:52 time: 0.344555 data_time: 0.031022 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.840985 2023/08/09 16:33:19 - mmengine - INFO - Epoch(train) [132][290/442] lr: 5.000000e-04 eta: 3:22:49 time: 0.346342 data_time: 0.030864 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.819480 2023/08/09 16:33:23 - mmengine - INFO - Epoch(train) [132][300/442] lr: 5.000000e-04 eta: 3:22:45 time: 0.346785 data_time: 0.030727 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.847583 2023/08/09 16:33:26 - mmengine - INFO - Epoch(train) [132][310/442] lr: 5.000000e-04 eta: 3:22:42 time: 0.351092 data_time: 0.030648 memory: 4565 loss: 0.000979 loss_kpt: 0.000979 acc_pose: 0.904598 2023/08/09 16:33:30 - mmengine - INFO - Epoch(train) [132][320/442] lr: 5.000000e-04 eta: 3:22:38 time: 0.348654 data_time: 0.030705 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.766547 2023/08/09 16:33:33 - mmengine - INFO - Epoch(train) [132][330/442] lr: 5.000000e-04 eta: 3:22:34 time: 0.349029 data_time: 0.030602 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.861382 2023/08/09 16:33:36 - mmengine - INFO - Epoch(train) [132][340/442] lr: 5.000000e-04 eta: 3:22:30 time: 0.345239 data_time: 0.030476 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.837546 2023/08/09 16:33:40 - mmengine - INFO - Epoch(train) [132][350/442] lr: 5.000000e-04 eta: 3:22:26 time: 0.343376 data_time: 0.030326 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.754163 2023/08/09 16:33:43 - mmengine - INFO - Epoch(train) [132][360/442] lr: 5.000000e-04 eta: 3:22:22 time: 0.339329 data_time: 0.030458 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.823071 2023/08/09 16:33:47 - mmengine - INFO - Epoch(train) [132][370/442] lr: 5.000000e-04 eta: 3:22:18 time: 0.339764 data_time: 0.030687 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.814879 2023/08/09 16:33:50 - mmengine - INFO - Epoch(train) [132][380/442] lr: 5.000000e-04 eta: 3:22:15 time: 0.340268 data_time: 0.030831 memory: 4565 loss: 0.000940 loss_kpt: 0.000940 acc_pose: 0.798334 2023/08/09 16:33:53 - mmengine - INFO - Epoch(train) [132][390/442] lr: 5.000000e-04 eta: 3:22:11 time: 0.342786 data_time: 0.031096 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.756305 2023/08/09 16:33:57 - mmengine - INFO - Epoch(train) [132][400/442] lr: 5.000000e-04 eta: 3:22:07 time: 0.344609 data_time: 0.031097 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.808246 2023/08/09 16:34:01 - mmengine - INFO - Epoch(train) [132][410/442] lr: 5.000000e-04 eta: 3:22:04 time: 0.347824 data_time: 0.030987 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.809399 2023/08/09 16:34:04 - mmengine - INFO - Epoch(train) [132][420/442] lr: 5.000000e-04 eta: 3:22:00 time: 0.347852 data_time: 0.030729 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.867145 2023/08/09 16:34:07 - mmengine - INFO - Epoch(train) [132][430/442] lr: 5.000000e-04 eta: 3:21:57 time: 0.349167 data_time: 0.030690 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.848216 2023/08/09 16:34:11 - mmengine - INFO - Epoch(train) [132][440/442] lr: 5.000000e-04 eta: 3:21:53 time: 0.350493 data_time: 0.030809 memory: 4565 loss: 0.000953 loss_kpt: 0.000953 acc_pose: 0.811871 2023/08/09 16:34:12 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:34:16 - mmengine - INFO - Epoch(train) [133][ 10/442] lr: 5.000000e-04 eta: 3:21:50 time: 0.359608 data_time: 0.038305 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.827790 2023/08/09 16:34:19 - mmengine - INFO - Epoch(train) [133][ 20/442] lr: 5.000000e-04 eta: 3:21:47 time: 0.358407 data_time: 0.038486 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.821135 2023/08/09 16:34:23 - mmengine - INFO - Epoch(train) [133][ 30/442] lr: 5.000000e-04 eta: 3:21:43 time: 0.359025 data_time: 0.038611 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.777709 2023/08/09 16:34:26 - mmengine - INFO - Epoch(train) [133][ 40/442] lr: 5.000000e-04 eta: 3:21:40 time: 0.358647 data_time: 0.038195 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.829914 2023/08/09 16:34:30 - mmengine - INFO - Epoch(train) [133][ 50/442] lr: 5.000000e-04 eta: 3:21:36 time: 0.358607 data_time: 0.038570 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.844511 2023/08/09 16:34:33 - mmengine - INFO - Epoch(train) [133][ 60/442] lr: 5.000000e-04 eta: 3:21:33 time: 0.350343 data_time: 0.030725 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.784020 2023/08/09 16:34:37 - mmengine - INFO - Epoch(train) [133][ 70/442] lr: 5.000000e-04 eta: 3:21:29 time: 0.350676 data_time: 0.030599 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.872470 2023/08/09 16:34:40 - mmengine - INFO - Epoch(train) [133][ 80/442] lr: 5.000000e-04 eta: 3:21:26 time: 0.352755 data_time: 0.030753 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.761754 2023/08/09 16:34:44 - mmengine - INFO - Epoch(train) [133][ 90/442] lr: 5.000000e-04 eta: 3:21:22 time: 0.353582 data_time: 0.031080 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.814839 2023/08/09 16:34:47 - mmengine - INFO - Epoch(train) [133][100/442] lr: 5.000000e-04 eta: 3:21:19 time: 0.354134 data_time: 0.030886 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.860997 2023/08/09 16:34:51 - mmengine - INFO - Epoch(train) [133][110/442] lr: 5.000000e-04 eta: 3:21:16 time: 0.353391 data_time: 0.031275 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.853725 2023/08/09 16:34:54 - mmengine - INFO - Epoch(train) [133][120/442] lr: 5.000000e-04 eta: 3:21:12 time: 0.354786 data_time: 0.031189 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.864558 2023/08/09 16:34:58 - mmengine - INFO - Epoch(train) [133][130/442] lr: 5.000000e-04 eta: 3:21:10 time: 0.357756 data_time: 0.031408 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.861282 2023/08/09 16:35:02 - mmengine - INFO - Epoch(train) [133][140/442] lr: 5.000000e-04 eta: 3:21:06 time: 0.359533 data_time: 0.031461 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.749310 2023/08/09 16:35:05 - mmengine - INFO - Epoch(train) [133][150/442] lr: 5.000000e-04 eta: 3:21:03 time: 0.359237 data_time: 0.031646 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.864546 2023/08/09 16:35:09 - mmengine - INFO - Epoch(train) [133][160/442] lr: 5.000000e-04 eta: 3:20:59 time: 0.359106 data_time: 0.031378 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.825530 2023/08/09 16:35:12 - mmengine - INFO - Epoch(train) [133][170/442] lr: 5.000000e-04 eta: 3:20:56 time: 0.357280 data_time: 0.031160 memory: 4565 loss: 0.000940 loss_kpt: 0.000940 acc_pose: 0.872073 2023/08/09 16:35:16 - mmengine - INFO - Epoch(train) [133][180/442] lr: 5.000000e-04 eta: 3:20:53 time: 0.355562 data_time: 0.034014 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.830746 2023/08/09 16:35:19 - mmengine - INFO - Epoch(train) [133][190/442] lr: 5.000000e-04 eta: 3:20:49 time: 0.353946 data_time: 0.033812 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.758680 2023/08/09 16:35:23 - mmengine - INFO - Epoch(train) [133][200/442] lr: 5.000000e-04 eta: 3:20:46 time: 0.354330 data_time: 0.033773 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.861776 2023/08/09 16:35:27 - mmengine - INFO - Epoch(train) [133][210/442] lr: 5.000000e-04 eta: 3:20:43 time: 0.357186 data_time: 0.033738 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.828184 2023/08/09 16:35:30 - mmengine - INFO - Epoch(train) [133][220/442] lr: 5.000000e-04 eta: 3:20:39 time: 0.357802 data_time: 0.033919 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.813506 2023/08/09 16:35:34 - mmengine - INFO - Epoch(train) [133][230/442] lr: 5.000000e-04 eta: 3:20:36 time: 0.355854 data_time: 0.030484 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.823410 2023/08/09 16:35:37 - mmengine - INFO - Epoch(train) [133][240/442] lr: 5.000000e-04 eta: 3:20:32 time: 0.355031 data_time: 0.030384 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.905229 2023/08/09 16:35:41 - mmengine - INFO - Epoch(train) [133][250/442] lr: 5.000000e-04 eta: 3:20:29 time: 0.353797 data_time: 0.029922 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.841152 2023/08/09 16:35:44 - mmengine - INFO - Epoch(train) [133][260/442] lr: 5.000000e-04 eta: 3:20:25 time: 0.351288 data_time: 0.030010 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.875966 2023/08/09 16:35:48 - mmengine - INFO - Epoch(train) [133][270/442] lr: 5.000000e-04 eta: 3:20:22 time: 0.352665 data_time: 0.030020 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.890242 2023/08/09 16:35:52 - mmengine - INFO - Epoch(train) [133][280/442] lr: 5.000000e-04 eta: 3:20:19 time: 0.354778 data_time: 0.030922 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.776787 2023/08/09 16:35:55 - mmengine - INFO - Epoch(train) [133][290/442] lr: 5.000000e-04 eta: 3:20:16 time: 0.357940 data_time: 0.031569 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.884592 2023/08/09 16:35:59 - mmengine - INFO - Epoch(train) [133][300/442] lr: 5.000000e-04 eta: 3:20:12 time: 0.358737 data_time: 0.031861 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.821698 2023/08/09 16:36:02 - mmengine - INFO - Epoch(train) [133][310/442] lr: 5.000000e-04 eta: 3:20:09 time: 0.358716 data_time: 0.031900 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.721461 2023/08/09 16:36:06 - mmengine - INFO - Epoch(train) [133][320/442] lr: 5.000000e-04 eta: 3:20:05 time: 0.357097 data_time: 0.032114 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.738620 2023/08/09 16:36:09 - mmengine - INFO - Epoch(train) [133][330/442] lr: 5.000000e-04 eta: 3:20:02 time: 0.354659 data_time: 0.031411 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.766583 2023/08/09 16:36:13 - mmengine - INFO - Epoch(train) [133][340/442] lr: 5.000000e-04 eta: 3:19:59 time: 0.356582 data_time: 0.034751 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.809674 2023/08/09 16:36:17 - mmengine - INFO - Epoch(train) [133][350/442] lr: 5.000000e-04 eta: 3:19:56 time: 0.357534 data_time: 0.034819 memory: 4565 loss: 0.000964 loss_kpt: 0.000964 acc_pose: 0.890517 2023/08/09 16:36:20 - mmengine - INFO - Epoch(train) [133][360/442] lr: 5.000000e-04 eta: 3:19:52 time: 0.357528 data_time: 0.034733 memory: 4565 loss: 0.000984 loss_kpt: 0.000984 acc_pose: 0.872352 2023/08/09 16:36:24 - mmengine - INFO - Epoch(train) [133][370/442] lr: 5.000000e-04 eta: 3:19:49 time: 0.357888 data_time: 0.034377 memory: 4565 loss: 0.000977 loss_kpt: 0.000977 acc_pose: 0.825919 2023/08/09 16:36:27 - mmengine - INFO - Epoch(train) [133][380/442] lr: 5.000000e-04 eta: 3:19:45 time: 0.357539 data_time: 0.034290 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.912498 2023/08/09 16:36:31 - mmengine - INFO - Epoch(train) [133][390/442] lr: 5.000000e-04 eta: 3:19:42 time: 0.353839 data_time: 0.030227 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.828224 2023/08/09 16:36:34 - mmengine - INFO - Epoch(train) [133][400/442] lr: 5.000000e-04 eta: 3:19:39 time: 0.353858 data_time: 0.030331 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.816906 2023/08/09 16:36:38 - mmengine - INFO - Epoch(train) [133][410/442] lr: 5.000000e-04 eta: 3:19:35 time: 0.355041 data_time: 0.030424 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.856887 2023/08/09 16:36:41 - mmengine - INFO - Epoch(train) [133][420/442] lr: 5.000000e-04 eta: 3:19:32 time: 0.354323 data_time: 0.030798 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.859991 2023/08/09 16:36:45 - mmengine - INFO - Epoch(train) [133][430/442] lr: 5.000000e-04 eta: 3:19:28 time: 0.354346 data_time: 0.030747 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.850958 2023/08/09 16:36:48 - mmengine - INFO - Epoch(train) [133][440/442] lr: 5.000000e-04 eta: 3:19:25 time: 0.353830 data_time: 0.030958 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.826994 2023/08/09 16:36:49 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:36:53 - mmengine - INFO - Epoch(train) [134][ 10/442] lr: 5.000000e-04 eta: 3:19:21 time: 0.355029 data_time: 0.034504 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.873631 2023/08/09 16:36:57 - mmengine - INFO - Epoch(train) [134][ 20/442] lr: 5.000000e-04 eta: 3:19:18 time: 0.358673 data_time: 0.034457 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.767006 2023/08/09 16:37:00 - mmengine - INFO - Epoch(train) [134][ 30/442] lr: 5.000000e-04 eta: 3:19:15 time: 0.360240 data_time: 0.035531 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.852966 2023/08/09 16:37:04 - mmengine - INFO - Epoch(train) [134][ 40/442] lr: 5.000000e-04 eta: 3:19:12 time: 0.364752 data_time: 0.036538 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.834669 2023/08/09 16:37:07 - mmengine - INFO - Epoch(train) [134][ 50/442] lr: 5.000000e-04 eta: 3:19:09 time: 0.366001 data_time: 0.036923 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.715147 2023/08/09 16:37:11 - mmengine - INFO - Epoch(train) [134][ 60/442] lr: 5.000000e-04 eta: 3:19:05 time: 0.364430 data_time: 0.032821 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.924443 2023/08/09 16:37:14 - mmengine - INFO - Epoch(train) [134][ 70/442] lr: 5.000000e-04 eta: 3:19:02 time: 0.358842 data_time: 0.032357 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.765504 2023/08/09 16:37:18 - mmengine - INFO - Epoch(train) [134][ 80/442] lr: 5.000000e-04 eta: 3:18:58 time: 0.358528 data_time: 0.031648 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.821419 2023/08/09 16:37:22 - mmengine - INFO - Epoch(train) [134][ 90/442] lr: 5.000000e-04 eta: 3:18:55 time: 0.354282 data_time: 0.031025 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.820072 2023/08/09 16:37:25 - mmengine - INFO - Epoch(train) [134][100/442] lr: 5.000000e-04 eta: 3:18:52 time: 0.357527 data_time: 0.032002 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.770093 2023/08/09 16:37:29 - mmengine - INFO - Epoch(train) [134][110/442] lr: 5.000000e-04 eta: 3:18:48 time: 0.354914 data_time: 0.031925 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.823492 2023/08/09 16:37:32 - mmengine - INFO - Epoch(train) [134][120/442] lr: 5.000000e-04 eta: 3:18:45 time: 0.354912 data_time: 0.031972 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.764830 2023/08/09 16:37:36 - mmengine - INFO - Epoch(train) [134][130/442] lr: 5.000000e-04 eta: 3:18:41 time: 0.353831 data_time: 0.031512 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.880284 2023/08/09 16:37:39 - mmengine - INFO - Epoch(train) [134][140/442] lr: 5.000000e-04 eta: 3:18:38 time: 0.352935 data_time: 0.031437 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.792284 2023/08/09 16:37:43 - mmengine - INFO - Epoch(train) [134][150/442] lr: 5.000000e-04 eta: 3:18:34 time: 0.350252 data_time: 0.030513 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.845641 2023/08/09 16:37:46 - mmengine - INFO - Epoch(train) [134][160/442] lr: 5.000000e-04 eta: 3:18:31 time: 0.352303 data_time: 0.030875 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.895525 2023/08/09 16:37:50 - mmengine - INFO - Epoch(train) [134][170/442] lr: 5.000000e-04 eta: 3:18:28 time: 0.355793 data_time: 0.031029 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.857248 2023/08/09 16:37:54 - mmengine - INFO - Epoch(train) [134][180/442] lr: 5.000000e-04 eta: 3:18:25 time: 0.358768 data_time: 0.031601 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.863080 2023/08/09 16:37:57 - mmengine - INFO - Epoch(train) [134][190/442] lr: 5.000000e-04 eta: 3:18:21 time: 0.358643 data_time: 0.031084 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.846790 2023/08/09 16:38:01 - mmengine - INFO - Epoch(train) [134][200/442] lr: 5.000000e-04 eta: 3:18:17 time: 0.357379 data_time: 0.030798 memory: 4565 loss: 0.000915 loss_kpt: 0.000915 acc_pose: 0.915431 2023/08/09 16:38:04 - mmengine - INFO - Epoch(train) [134][210/442] lr: 5.000000e-04 eta: 3:18:14 time: 0.355308 data_time: 0.030816 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.706746 2023/08/09 16:38:06 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:38:08 - mmengine - INFO - Epoch(train) [134][220/442] lr: 5.000000e-04 eta: 3:18:10 time: 0.352921 data_time: 0.030817 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.859952 2023/08/09 16:38:11 - mmengine - INFO - Epoch(train) [134][230/442] lr: 5.000000e-04 eta: 3:18:08 time: 0.355641 data_time: 0.034299 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.814205 2023/08/09 16:38:15 - mmengine - INFO - Epoch(train) [134][240/442] lr: 5.000000e-04 eta: 3:18:04 time: 0.356180 data_time: 0.034655 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.758636 2023/08/09 16:38:18 - mmengine - INFO - Epoch(train) [134][250/442] lr: 5.000000e-04 eta: 3:18:01 time: 0.356866 data_time: 0.035010 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.798277 2023/08/09 16:38:22 - mmengine - INFO - Epoch(train) [134][260/442] lr: 5.000000e-04 eta: 3:17:57 time: 0.356341 data_time: 0.034530 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.918714 2023/08/09 16:38:25 - mmengine - INFO - Epoch(train) [134][270/442] lr: 5.000000e-04 eta: 3:17:53 time: 0.355241 data_time: 0.034557 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.848128 2023/08/09 16:38:29 - mmengine - INFO - Epoch(train) [134][280/442] lr: 5.000000e-04 eta: 3:17:50 time: 0.349853 data_time: 0.030564 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.875261 2023/08/09 16:38:33 - mmengine - INFO - Epoch(train) [134][290/442] lr: 5.000000e-04 eta: 3:17:47 time: 0.350344 data_time: 0.030642 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.868589 2023/08/09 16:38:36 - mmengine - INFO - Epoch(train) [134][300/442] lr: 5.000000e-04 eta: 3:17:43 time: 0.351046 data_time: 0.030584 memory: 4565 loss: 0.000915 loss_kpt: 0.000915 acc_pose: 0.749138 2023/08/09 16:38:40 - mmengine - INFO - Epoch(train) [134][310/442] lr: 5.000000e-04 eta: 3:17:40 time: 0.351932 data_time: 0.030972 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.839965 2023/08/09 16:38:43 - mmengine - INFO - Epoch(train) [134][320/442] lr: 5.000000e-04 eta: 3:17:36 time: 0.351944 data_time: 0.030648 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.834772 2023/08/09 16:38:47 - mmengine - INFO - Epoch(train) [134][330/442] lr: 5.000000e-04 eta: 3:17:32 time: 0.351396 data_time: 0.030816 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.838479 2023/08/09 16:38:50 - mmengine - INFO - Epoch(train) [134][340/442] lr: 5.000000e-04 eta: 3:17:29 time: 0.349885 data_time: 0.030374 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.849904 2023/08/09 16:38:54 - mmengine - INFO - Epoch(train) [134][350/442] lr: 5.000000e-04 eta: 3:17:26 time: 0.353616 data_time: 0.030366 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.858628 2023/08/09 16:38:57 - mmengine - INFO - Epoch(train) [134][360/442] lr: 5.000000e-04 eta: 3:17:22 time: 0.355058 data_time: 0.030297 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.854886 2023/08/09 16:39:01 - mmengine - INFO - Epoch(train) [134][370/442] lr: 5.000000e-04 eta: 3:17:19 time: 0.357245 data_time: 0.030798 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.773063 2023/08/09 16:39:04 - mmengine - INFO - Epoch(train) [134][380/442] lr: 5.000000e-04 eta: 3:17:16 time: 0.358554 data_time: 0.030705 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.859293 2023/08/09 16:39:08 - mmengine - INFO - Epoch(train) [134][390/442] lr: 5.000000e-04 eta: 3:17:12 time: 0.359200 data_time: 0.030972 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.854085 2023/08/09 16:39:12 - mmengine - INFO - Epoch(train) [134][400/442] lr: 5.000000e-04 eta: 3:17:09 time: 0.358695 data_time: 0.034075 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.859812 2023/08/09 16:39:15 - mmengine - INFO - Epoch(train) [134][410/442] lr: 5.000000e-04 eta: 3:17:06 time: 0.360348 data_time: 0.037166 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.771720 2023/08/09 16:39:19 - mmengine - INFO - Epoch(train) [134][420/442] lr: 5.000000e-04 eta: 3:17:03 time: 0.358482 data_time: 0.036779 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.764281 2023/08/09 16:39:22 - mmengine - INFO - Epoch(train) [134][430/442] lr: 5.000000e-04 eta: 3:17:00 time: 0.359699 data_time: 0.037582 memory: 4565 loss: 0.000961 loss_kpt: 0.000961 acc_pose: 0.890402 2023/08/09 16:39:26 - mmengine - INFO - Epoch(train) [134][440/442] lr: 5.000000e-04 eta: 3:16:56 time: 0.360499 data_time: 0.037488 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.817494 2023/08/09 16:39:27 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:39:30 - mmengine - INFO - Epoch(train) [135][ 10/442] lr: 5.000000e-04 eta: 3:16:52 time: 0.357185 data_time: 0.037902 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.871142 2023/08/09 16:39:34 - mmengine - INFO - Epoch(train) [135][ 20/442] lr: 5.000000e-04 eta: 3:16:48 time: 0.351542 data_time: 0.034770 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.828491 2023/08/09 16:39:37 - mmengine - INFO - Epoch(train) [135][ 30/442] lr: 5.000000e-04 eta: 3:16:44 time: 0.348320 data_time: 0.034342 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.903994 2023/08/09 16:39:40 - mmengine - INFO - Epoch(train) [135][ 40/442] lr: 5.000000e-04 eta: 3:16:40 time: 0.345174 data_time: 0.033904 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.779801 2023/08/09 16:39:44 - mmengine - INFO - Epoch(train) [135][ 50/442] lr: 5.000000e-04 eta: 3:16:37 time: 0.346147 data_time: 0.034375 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.855873 2023/08/09 16:39:47 - mmengine - INFO - Epoch(train) [135][ 60/442] lr: 5.000000e-04 eta: 3:16:33 time: 0.343430 data_time: 0.030804 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.859643 2023/08/09 16:39:51 - mmengine - INFO - Epoch(train) [135][ 70/442] lr: 5.000000e-04 eta: 3:16:29 time: 0.344389 data_time: 0.031591 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.906921 2023/08/09 16:39:54 - mmengine - INFO - Epoch(train) [135][ 80/442] lr: 5.000000e-04 eta: 3:16:25 time: 0.344753 data_time: 0.032183 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.806340 2023/08/09 16:39:58 - mmengine - INFO - Epoch(train) [135][ 90/442] lr: 5.000000e-04 eta: 3:16:21 time: 0.344412 data_time: 0.032199 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.840741 2023/08/09 16:40:01 - mmengine - INFO - Epoch(train) [135][100/442] lr: 5.000000e-04 eta: 3:16:18 time: 0.344199 data_time: 0.031947 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.888470 2023/08/09 16:40:05 - mmengine - INFO - Epoch(train) [135][110/442] lr: 5.000000e-04 eta: 3:16:14 time: 0.344145 data_time: 0.031756 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.847039 2023/08/09 16:40:08 - mmengine - INFO - Epoch(train) [135][120/442] lr: 5.000000e-04 eta: 3:16:11 time: 0.344947 data_time: 0.031145 memory: 4565 loss: 0.000953 loss_kpt: 0.000953 acc_pose: 0.773973 2023/08/09 16:40:12 - mmengine - INFO - Epoch(train) [135][130/442] lr: 5.000000e-04 eta: 3:16:07 time: 0.345798 data_time: 0.030587 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.866608 2023/08/09 16:40:15 - mmengine - INFO - Epoch(train) [135][140/442] lr: 5.000000e-04 eta: 3:16:03 time: 0.348543 data_time: 0.030697 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.854511 2023/08/09 16:40:19 - mmengine - INFO - Epoch(train) [135][150/442] lr: 5.000000e-04 eta: 3:16:00 time: 0.346413 data_time: 0.031331 memory: 4565 loss: 0.000967 loss_kpt: 0.000967 acc_pose: 0.778978 2023/08/09 16:40:22 - mmengine - INFO - Epoch(train) [135][160/442] lr: 5.000000e-04 eta: 3:15:56 time: 0.345223 data_time: 0.031253 memory: 4565 loss: 0.000973 loss_kpt: 0.000973 acc_pose: 0.770122 2023/08/09 16:40:25 - mmengine - INFO - Epoch(train) [135][170/442] lr: 5.000000e-04 eta: 3:15:52 time: 0.346527 data_time: 0.031069 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.873946 2023/08/09 16:40:29 - mmengine - INFO - Epoch(train) [135][180/442] lr: 5.000000e-04 eta: 3:15:48 time: 0.346272 data_time: 0.031105 memory: 4565 loss: 0.000963 loss_kpt: 0.000963 acc_pose: 0.834867 2023/08/09 16:40:32 - mmengine - INFO - Epoch(train) [135][190/442] lr: 5.000000e-04 eta: 3:15:45 time: 0.345097 data_time: 0.031145 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.749770 2023/08/09 16:40:36 - mmengine - INFO - Epoch(train) [135][200/442] lr: 5.000000e-04 eta: 3:15:41 time: 0.347610 data_time: 0.030876 memory: 4565 loss: 0.000941 loss_kpt: 0.000941 acc_pose: 0.860865 2023/08/09 16:40:39 - mmengine - INFO - Epoch(train) [135][210/442] lr: 5.000000e-04 eta: 3:15:38 time: 0.349013 data_time: 0.031568 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.890731 2023/08/09 16:40:43 - mmengine - INFO - Epoch(train) [135][220/442] lr: 5.000000e-04 eta: 3:15:34 time: 0.346262 data_time: 0.031833 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.901842 2023/08/09 16:40:46 - mmengine - INFO - Epoch(train) [135][230/442] lr: 5.000000e-04 eta: 3:15:30 time: 0.345446 data_time: 0.031826 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.805701 2023/08/09 16:40:50 - mmengine - INFO - Epoch(train) [135][240/442] lr: 5.000000e-04 eta: 3:15:26 time: 0.343514 data_time: 0.031684 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.819915 2023/08/09 16:40:53 - mmengine - INFO - Epoch(train) [135][250/442] lr: 5.000000e-04 eta: 3:15:22 time: 0.340761 data_time: 0.031452 memory: 4565 loss: 0.000941 loss_kpt: 0.000941 acc_pose: 0.821984 2023/08/09 16:40:56 - mmengine - INFO - Epoch(train) [135][260/442] lr: 5.000000e-04 eta: 3:15:18 time: 0.340705 data_time: 0.030850 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.860617 2023/08/09 16:41:00 - mmengine - INFO - Epoch(train) [135][270/442] lr: 5.000000e-04 eta: 3:15:15 time: 0.341405 data_time: 0.030788 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.886176 2023/08/09 16:41:03 - mmengine - INFO - Epoch(train) [135][280/442] lr: 5.000000e-04 eta: 3:15:11 time: 0.343023 data_time: 0.031416 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.835046 2023/08/09 16:41:07 - mmengine - INFO - Epoch(train) [135][290/442] lr: 5.000000e-04 eta: 3:15:07 time: 0.343838 data_time: 0.032049 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.868477 2023/08/09 16:41:10 - mmengine - INFO - Epoch(train) [135][300/442] lr: 5.000000e-04 eta: 3:15:04 time: 0.346205 data_time: 0.032403 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.794943 2023/08/09 16:41:14 - mmengine - INFO - Epoch(train) [135][310/442] lr: 5.000000e-04 eta: 3:15:00 time: 0.344815 data_time: 0.032171 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.802248 2023/08/09 16:41:17 - mmengine - INFO - Epoch(train) [135][320/442] lr: 5.000000e-04 eta: 3:14:56 time: 0.345462 data_time: 0.032720 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.860030 2023/08/09 16:41:21 - mmengine - INFO - Epoch(train) [135][330/442] lr: 5.000000e-04 eta: 3:14:53 time: 0.346695 data_time: 0.032506 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.858302 2023/08/09 16:41:24 - mmengine - INFO - Epoch(train) [135][340/442] lr: 5.000000e-04 eta: 3:14:49 time: 0.348252 data_time: 0.032298 memory: 4565 loss: 0.000941 loss_kpt: 0.000941 acc_pose: 0.785822 2023/08/09 16:41:28 - mmengine - INFO - Epoch(train) [135][350/442] lr: 5.000000e-04 eta: 3:14:45 time: 0.346999 data_time: 0.031901 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.856018 2023/08/09 16:41:31 - mmengine - INFO - Epoch(train) [135][360/442] lr: 5.000000e-04 eta: 3:14:42 time: 0.349617 data_time: 0.031905 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.791254 2023/08/09 16:41:35 - mmengine - INFO - Epoch(train) [135][370/442] lr: 5.000000e-04 eta: 3:14:38 time: 0.347633 data_time: 0.031203 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.797150 2023/08/09 16:41:38 - mmengine - INFO - Epoch(train) [135][380/442] lr: 5.000000e-04 eta: 3:14:34 time: 0.345692 data_time: 0.030901 memory: 4565 loss: 0.000953 loss_kpt: 0.000953 acc_pose: 0.868648 2023/08/09 16:41:41 - mmengine - INFO - Epoch(train) [135][390/442] lr: 5.000000e-04 eta: 3:14:30 time: 0.343424 data_time: 0.030436 memory: 4565 loss: 0.000968 loss_kpt: 0.000968 acc_pose: 0.807705 2023/08/09 16:41:45 - mmengine - INFO - Epoch(train) [135][400/442] lr: 5.000000e-04 eta: 3:14:26 time: 0.342605 data_time: 0.030942 memory: 4565 loss: 0.000971 loss_kpt: 0.000971 acc_pose: 0.785063 2023/08/09 16:41:48 - mmengine - INFO - Epoch(train) [135][410/442] lr: 5.000000e-04 eta: 3:14:23 time: 0.342889 data_time: 0.031576 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.855487 2023/08/09 16:41:52 - mmengine - INFO - Epoch(train) [135][420/442] lr: 5.000000e-04 eta: 3:14:19 time: 0.343934 data_time: 0.031560 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.842291 2023/08/09 16:41:55 - mmengine - INFO - Epoch(train) [135][430/442] lr: 5.000000e-04 eta: 3:14:15 time: 0.343108 data_time: 0.031557 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.813953 2023/08/09 16:41:58 - mmengine - INFO - Epoch(train) [135][440/442] lr: 5.000000e-04 eta: 3:14:11 time: 0.341742 data_time: 0.031630 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.796279 2023/08/09 16:41:59 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:42:03 - mmengine - INFO - Epoch(train) [136][ 10/442] lr: 5.000000e-04 eta: 3:14:07 time: 0.345120 data_time: 0.034453 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.854148 2023/08/09 16:42:06 - mmengine - INFO - Epoch(train) [136][ 20/442] lr: 5.000000e-04 eta: 3:14:04 time: 0.345927 data_time: 0.034355 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.796774 2023/08/09 16:42:10 - mmengine - INFO - Epoch(train) [136][ 30/442] lr: 5.000000e-04 eta: 3:14:00 time: 0.348325 data_time: 0.034477 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.808727 2023/08/09 16:42:13 - mmengine - INFO - Epoch(train) [136][ 40/442] lr: 5.000000e-04 eta: 3:13:57 time: 0.352836 data_time: 0.035052 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.827944 2023/08/09 16:42:17 - mmengine - INFO - Epoch(train) [136][ 50/442] lr: 5.000000e-04 eta: 3:13:54 time: 0.360301 data_time: 0.035496 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.880435 2023/08/09 16:42:21 - mmengine - INFO - Epoch(train) [136][ 60/442] lr: 5.000000e-04 eta: 3:13:50 time: 0.356044 data_time: 0.031544 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.803630 2023/08/09 16:42:24 - mmengine - INFO - Epoch(train) [136][ 70/442] lr: 5.000000e-04 eta: 3:13:47 time: 0.355116 data_time: 0.031100 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.886293 2023/08/09 16:42:28 - mmengine - INFO - Epoch(train) [136][ 80/442] lr: 5.000000e-04 eta: 3:13:43 time: 0.354663 data_time: 0.030840 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.739685 2023/08/09 16:42:31 - mmengine - INFO - Epoch(train) [136][ 90/442] lr: 5.000000e-04 eta: 3:13:40 time: 0.353438 data_time: 0.030362 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.806212 2023/08/09 16:42:35 - mmengine - INFO - Epoch(train) [136][100/442] lr: 5.000000e-04 eta: 3:13:36 time: 0.351027 data_time: 0.030141 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.806251 2023/08/09 16:42:38 - mmengine - INFO - Epoch(train) [136][110/442] lr: 5.000000e-04 eta: 3:13:34 time: 0.355760 data_time: 0.033329 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.754558 2023/08/09 16:42:42 - mmengine - INFO - Epoch(train) [136][120/442] lr: 5.000000e-04 eta: 3:13:30 time: 0.355893 data_time: 0.033240 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.836926 2023/08/09 16:42:45 - mmengine - INFO - Epoch(train) [136][130/442] lr: 5.000000e-04 eta: 3:13:26 time: 0.355002 data_time: 0.033193 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.840904 2023/08/09 16:42:49 - mmengine - INFO - Epoch(train) [136][140/442] lr: 5.000000e-04 eta: 3:13:23 time: 0.354007 data_time: 0.033030 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.862124 2023/08/09 16:42:52 - mmengine - INFO - Epoch(train) [136][150/442] lr: 5.000000e-04 eta: 3:13:19 time: 0.354325 data_time: 0.033160 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.845100 2023/08/09 16:42:56 - mmengine - INFO - Epoch(train) [136][160/442] lr: 5.000000e-04 eta: 3:13:16 time: 0.354730 data_time: 0.030147 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.843366 2023/08/09 16:43:00 - mmengine - INFO - Epoch(train) [136][170/442] lr: 5.000000e-04 eta: 3:13:13 time: 0.356657 data_time: 0.030938 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.873835 2023/08/09 16:43:03 - mmengine - INFO - Epoch(train) [136][180/442] lr: 5.000000e-04 eta: 3:13:10 time: 0.359025 data_time: 0.031212 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.862206 2023/08/09 16:43:07 - mmengine - INFO - Epoch(train) [136][190/442] lr: 5.000000e-04 eta: 3:13:06 time: 0.360105 data_time: 0.031357 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.877217 2023/08/09 16:43:10 - mmengine - INFO - Epoch(train) [136][200/442] lr: 5.000000e-04 eta: 3:13:03 time: 0.361055 data_time: 0.031316 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.787715 2023/08/09 16:43:14 - mmengine - INFO - Epoch(train) [136][210/442] lr: 5.000000e-04 eta: 3:13:00 time: 0.357203 data_time: 0.031230 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.854056 2023/08/09 16:43:18 - mmengine - INFO - Epoch(train) [136][220/442] lr: 5.000000e-04 eta: 3:12:56 time: 0.356397 data_time: 0.030478 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.759102 2023/08/09 16:43:21 - mmengine - INFO - Epoch(train) [136][230/442] lr: 5.000000e-04 eta: 3:12:53 time: 0.357465 data_time: 0.030817 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.874195 2023/08/09 16:43:25 - mmengine - INFO - Epoch(train) [136][240/442] lr: 5.000000e-04 eta: 3:12:50 time: 0.359102 data_time: 0.031103 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.845552 2023/08/09 16:43:28 - mmengine - INFO - Epoch(train) [136][250/442] lr: 5.000000e-04 eta: 3:12:46 time: 0.358087 data_time: 0.031106 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.867105 2023/08/09 16:43:32 - mmengine - INFO - Epoch(train) [136][260/442] lr: 5.000000e-04 eta: 3:12:43 time: 0.357852 data_time: 0.031871 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.847531 2023/08/09 16:43:36 - mmengine - INFO - Epoch(train) [136][270/442] lr: 5.000000e-04 eta: 3:12:40 time: 0.359898 data_time: 0.032618 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.875564 2023/08/09 16:43:39 - mmengine - INFO - Epoch(train) [136][280/442] lr: 5.000000e-04 eta: 3:12:37 time: 0.359644 data_time: 0.032483 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.844497 2023/08/09 16:43:43 - mmengine - INFO - Epoch(train) [136][290/442] lr: 5.000000e-04 eta: 3:12:33 time: 0.358223 data_time: 0.032718 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.701686 2023/08/09 16:43:46 - mmengine - INFO - Epoch(train) [136][300/442] lr: 5.000000e-04 eta: 3:12:30 time: 0.358479 data_time: 0.032804 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.834360 2023/08/09 16:43:50 - mmengine - INFO - Epoch(train) [136][310/442] lr: 5.000000e-04 eta: 3:12:26 time: 0.358500 data_time: 0.032273 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.863930 2023/08/09 16:43:53 - mmengine - INFO - Epoch(train) [136][320/442] lr: 5.000000e-04 eta: 3:12:23 time: 0.355599 data_time: 0.031627 memory: 4565 loss: 0.000978 loss_kpt: 0.000978 acc_pose: 0.805494 2023/08/09 16:43:57 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:43:57 - mmengine - INFO - Epoch(train) [136][330/442] lr: 5.000000e-04 eta: 3:12:20 time: 0.354561 data_time: 0.031704 memory: 4565 loss: 0.000966 loss_kpt: 0.000966 acc_pose: 0.735879 2023/08/09 16:44:00 - mmengine - INFO - Epoch(train) [136][340/442] lr: 5.000000e-04 eta: 3:12:16 time: 0.353241 data_time: 0.031158 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.832688 2023/08/09 16:44:04 - mmengine - INFO - Epoch(train) [136][350/442] lr: 5.000000e-04 eta: 3:12:12 time: 0.352731 data_time: 0.031043 memory: 4565 loss: 0.000963 loss_kpt: 0.000963 acc_pose: 0.882086 2023/08/09 16:44:08 - mmengine - INFO - Epoch(train) [136][360/442] lr: 5.000000e-04 eta: 3:12:09 time: 0.353209 data_time: 0.031257 memory: 4565 loss: 0.000962 loss_kpt: 0.000962 acc_pose: 0.803674 2023/08/09 16:44:11 - mmengine - INFO - Epoch(train) [136][370/442] lr: 5.000000e-04 eta: 3:12:06 time: 0.353812 data_time: 0.031337 memory: 4565 loss: 0.000956 loss_kpt: 0.000956 acc_pose: 0.823797 2023/08/09 16:44:15 - mmengine - INFO - Epoch(train) [136][380/442] lr: 5.000000e-04 eta: 3:12:02 time: 0.353351 data_time: 0.030967 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.837942 2023/08/09 16:44:18 - mmengine - INFO - Epoch(train) [136][390/442] lr: 5.000000e-04 eta: 3:11:59 time: 0.353659 data_time: 0.030907 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.808630 2023/08/09 16:44:22 - mmengine - INFO - Epoch(train) [136][400/442] lr: 5.000000e-04 eta: 3:11:55 time: 0.355462 data_time: 0.030854 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.817177 2023/08/09 16:44:25 - mmengine - INFO - Epoch(train) [136][410/442] lr: 5.000000e-04 eta: 3:11:52 time: 0.356916 data_time: 0.033484 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.750979 2023/08/09 16:44:29 - mmengine - INFO - Epoch(train) [136][420/442] lr: 5.000000e-04 eta: 3:11:49 time: 0.355792 data_time: 0.033370 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.784192 2023/08/09 16:44:32 - mmengine - INFO - Epoch(train) [136][430/442] lr: 5.000000e-04 eta: 3:11:45 time: 0.356287 data_time: 0.033207 memory: 4565 loss: 0.000960 loss_kpt: 0.000960 acc_pose: 0.887030 2023/08/09 16:44:36 - mmengine - INFO - Epoch(train) [136][440/442] lr: 5.000000e-04 eta: 3:11:42 time: 0.357801 data_time: 0.033411 memory: 4565 loss: 0.000969 loss_kpt: 0.000969 acc_pose: 0.851793 2023/08/09 16:44:37 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:44:40 - mmengine - INFO - Epoch(train) [137][ 10/442] lr: 5.000000e-04 eta: 3:11:38 time: 0.357616 data_time: 0.036989 memory: 4565 loss: 0.000965 loss_kpt: 0.000965 acc_pose: 0.785423 2023/08/09 16:44:44 - mmengine - INFO - Epoch(train) [137][ 20/442] lr: 5.000000e-04 eta: 3:11:34 time: 0.354513 data_time: 0.034254 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.841106 2023/08/09 16:44:47 - mmengine - INFO - Epoch(train) [137][ 30/442] lr: 5.000000e-04 eta: 3:11:31 time: 0.353401 data_time: 0.034591 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.776786 2023/08/09 16:44:51 - mmengine - INFO - Epoch(train) [137][ 40/442] lr: 5.000000e-04 eta: 3:11:27 time: 0.351481 data_time: 0.034640 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.889619 2023/08/09 16:44:54 - mmengine - INFO - Epoch(train) [137][ 50/442] lr: 5.000000e-04 eta: 3:11:24 time: 0.352749 data_time: 0.035085 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.858484 2023/08/09 16:44:58 - mmengine - INFO - Epoch(train) [137][ 60/442] lr: 5.000000e-04 eta: 3:11:20 time: 0.349949 data_time: 0.031390 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.862764 2023/08/09 16:45:01 - mmengine - INFO - Epoch(train) [137][ 70/442] lr: 5.000000e-04 eta: 3:11:17 time: 0.350874 data_time: 0.031133 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.844565 2023/08/09 16:45:05 - mmengine - INFO - Epoch(train) [137][ 80/442] lr: 5.000000e-04 eta: 3:11:13 time: 0.350934 data_time: 0.030826 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.781276 2023/08/09 16:45:08 - mmengine - INFO - Epoch(train) [137][ 90/442] lr: 5.000000e-04 eta: 3:11:10 time: 0.354389 data_time: 0.030975 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.829370 2023/08/09 16:45:12 - mmengine - INFO - Epoch(train) [137][100/442] lr: 5.000000e-04 eta: 3:11:06 time: 0.353276 data_time: 0.030670 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.861577 2023/08/09 16:45:15 - mmengine - INFO - Epoch(train) [137][110/442] lr: 5.000000e-04 eta: 3:11:03 time: 0.352767 data_time: 0.030527 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.812443 2023/08/09 16:45:19 - mmengine - INFO - Epoch(train) [137][120/442] lr: 5.000000e-04 eta: 3:10:59 time: 0.353641 data_time: 0.030631 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.835857 2023/08/09 16:45:23 - mmengine - INFO - Epoch(train) [137][130/442] lr: 5.000000e-04 eta: 3:10:56 time: 0.355141 data_time: 0.030825 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.826558 2023/08/09 16:45:26 - mmengine - INFO - Epoch(train) [137][140/442] lr: 5.000000e-04 eta: 3:10:52 time: 0.352384 data_time: 0.030601 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.840409 2023/08/09 16:45:30 - mmengine - INFO - Epoch(train) [137][150/442] lr: 5.000000e-04 eta: 3:10:49 time: 0.351994 data_time: 0.030558 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.821897 2023/08/09 16:45:33 - mmengine - INFO - Epoch(train) [137][160/442] lr: 5.000000e-04 eta: 3:10:45 time: 0.351090 data_time: 0.030428 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.864424 2023/08/09 16:45:37 - mmengine - INFO - Epoch(train) [137][170/442] lr: 5.000000e-04 eta: 3:10:42 time: 0.349796 data_time: 0.030130 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.928335 2023/08/09 16:45:40 - mmengine - INFO - Epoch(train) [137][180/442] lr: 5.000000e-04 eta: 3:10:38 time: 0.352446 data_time: 0.033419 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.773615 2023/08/09 16:45:44 - mmengine - INFO - Epoch(train) [137][190/442] lr: 5.000000e-04 eta: 3:10:35 time: 0.353120 data_time: 0.033654 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.861408 2023/08/09 16:45:47 - mmengine - INFO - Epoch(train) [137][200/442] lr: 5.000000e-04 eta: 3:10:32 time: 0.354968 data_time: 0.033899 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.896017 2023/08/09 16:45:51 - mmengine - INFO - Epoch(train) [137][210/442] lr: 5.000000e-04 eta: 3:10:28 time: 0.358132 data_time: 0.033986 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.845520 2023/08/09 16:45:54 - mmengine - INFO - Epoch(train) [137][220/442] lr: 5.000000e-04 eta: 3:10:25 time: 0.357823 data_time: 0.033998 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.745412 2023/08/09 16:45:58 - mmengine - INFO - Epoch(train) [137][230/442] lr: 5.000000e-04 eta: 3:10:22 time: 0.356203 data_time: 0.030468 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.815814 2023/08/09 16:46:02 - mmengine - INFO - Epoch(train) [137][240/442] lr: 5.000000e-04 eta: 3:10:18 time: 0.356442 data_time: 0.030912 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.847139 2023/08/09 16:46:05 - mmengine - INFO - Epoch(train) [137][250/442] lr: 5.000000e-04 eta: 3:10:15 time: 0.356570 data_time: 0.031409 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.739942 2023/08/09 16:46:09 - mmengine - INFO - Epoch(train) [137][260/442] lr: 5.000000e-04 eta: 3:10:12 time: 0.357491 data_time: 0.032223 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.801064 2023/08/09 16:46:12 - mmengine - INFO - Epoch(train) [137][270/442] lr: 5.000000e-04 eta: 3:10:08 time: 0.357286 data_time: 0.032227 memory: 4565 loss: 0.000915 loss_kpt: 0.000915 acc_pose: 0.786501 2023/08/09 16:46:16 - mmengine - INFO - Epoch(train) [137][280/442] lr: 5.000000e-04 eta: 3:10:04 time: 0.354962 data_time: 0.032173 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.877183 2023/08/09 16:46:19 - mmengine - INFO - Epoch(train) [137][290/442] lr: 5.000000e-04 eta: 3:10:01 time: 0.353788 data_time: 0.031455 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.778882 2023/08/09 16:46:23 - mmengine - INFO - Epoch(train) [137][300/442] lr: 5.000000e-04 eta: 3:09:57 time: 0.353506 data_time: 0.030859 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.867910 2023/08/09 16:46:26 - mmengine - INFO - Epoch(train) [137][310/442] lr: 5.000000e-04 eta: 3:09:54 time: 0.352158 data_time: 0.030185 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.855422 2023/08/09 16:46:30 - mmengine - INFO - Epoch(train) [137][320/442] lr: 5.000000e-04 eta: 3:09:51 time: 0.352699 data_time: 0.030271 memory: 4565 loss: 0.000953 loss_kpt: 0.000953 acc_pose: 0.814025 2023/08/09 16:46:34 - mmengine - INFO - Epoch(train) [137][330/442] lr: 5.000000e-04 eta: 3:09:47 time: 0.353672 data_time: 0.030442 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.809087 2023/08/09 16:46:37 - mmengine - INFO - Epoch(train) [137][340/442] lr: 5.000000e-04 eta: 3:09:43 time: 0.353246 data_time: 0.030503 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.799668 2023/08/09 16:46:40 - mmengine - INFO - Epoch(train) [137][350/442] lr: 5.000000e-04 eta: 3:09:40 time: 0.351813 data_time: 0.030516 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.805440 2023/08/09 16:46:44 - mmengine - INFO - Epoch(train) [137][360/442] lr: 5.000000e-04 eta: 3:09:36 time: 0.349091 data_time: 0.030322 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.818053 2023/08/09 16:46:48 - mmengine - INFO - Epoch(train) [137][370/442] lr: 5.000000e-04 eta: 3:09:33 time: 0.351898 data_time: 0.030510 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.845772 2023/08/09 16:46:51 - mmengine - INFO - Epoch(train) [137][380/442] lr: 5.000000e-04 eta: 3:09:29 time: 0.351455 data_time: 0.030551 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.846267 2023/08/09 16:46:55 - mmengine - INFO - Epoch(train) [137][390/442] lr: 5.000000e-04 eta: 3:09:26 time: 0.354824 data_time: 0.031030 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.862313 2023/08/09 16:46:58 - mmengine - INFO - Epoch(train) [137][400/442] lr: 5.000000e-04 eta: 3:09:23 time: 0.354659 data_time: 0.031021 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.834050 2023/08/09 16:47:02 - mmengine - INFO - Epoch(train) [137][410/442] lr: 5.000000e-04 eta: 3:09:19 time: 0.358633 data_time: 0.034509 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.789208 2023/08/09 16:47:05 - mmengine - INFO - Epoch(train) [137][420/442] lr: 5.000000e-04 eta: 3:09:16 time: 0.355545 data_time: 0.034384 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.855306 2023/08/09 16:47:09 - mmengine - INFO - Epoch(train) [137][430/442] lr: 5.000000e-04 eta: 3:09:12 time: 0.355929 data_time: 0.034688 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.868768 2023/08/09 16:47:12 - mmengine - INFO - Epoch(train) [137][440/442] lr: 5.000000e-04 eta: 3:09:09 time: 0.353593 data_time: 0.034443 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.826190 2023/08/09 16:47:13 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:47:17 - mmengine - INFO - Epoch(train) [138][ 10/442] lr: 5.000000e-04 eta: 3:09:05 time: 0.357763 data_time: 0.037625 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.886752 2023/08/09 16:47:20 - mmengine - INFO - Epoch(train) [138][ 20/442] lr: 5.000000e-04 eta: 3:09:02 time: 0.354620 data_time: 0.034321 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.888783 2023/08/09 16:47:24 - mmengine - INFO - Epoch(train) [138][ 30/442] lr: 5.000000e-04 eta: 3:08:58 time: 0.354102 data_time: 0.034276 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.792630 2023/08/09 16:47:27 - mmengine - INFO - Epoch(train) [138][ 40/442] lr: 5.000000e-04 eta: 3:08:54 time: 0.352707 data_time: 0.033739 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.794752 2023/08/09 16:47:31 - mmengine - INFO - Epoch(train) [138][ 50/442] lr: 5.000000e-04 eta: 3:08:51 time: 0.354611 data_time: 0.034000 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.882820 2023/08/09 16:47:34 - mmengine - INFO - Epoch(train) [138][ 60/442] lr: 5.000000e-04 eta: 3:08:47 time: 0.349904 data_time: 0.030391 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.814392 2023/08/09 16:47:38 - mmengine - INFO - Epoch(train) [138][ 70/442] lr: 5.000000e-04 eta: 3:08:44 time: 0.354570 data_time: 0.030624 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.794705 2023/08/09 16:47:42 - mmengine - INFO - Epoch(train) [138][ 80/442] lr: 5.000000e-04 eta: 3:08:41 time: 0.355560 data_time: 0.030640 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.783910 2023/08/09 16:47:45 - mmengine - INFO - Epoch(train) [138][ 90/442] lr: 5.000000e-04 eta: 3:08:37 time: 0.355907 data_time: 0.030549 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.850178 2023/08/09 16:47:49 - mmengine - INFO - Epoch(train) [138][100/442] lr: 5.000000e-04 eta: 3:08:34 time: 0.354278 data_time: 0.030415 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.836602 2023/08/09 16:47:52 - mmengine - INFO - Epoch(train) [138][110/442] lr: 5.000000e-04 eta: 3:08:30 time: 0.353778 data_time: 0.030324 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.869136 2023/08/09 16:47:56 - mmengine - INFO - Epoch(train) [138][120/442] lr: 5.000000e-04 eta: 3:08:26 time: 0.349351 data_time: 0.030211 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.820242 2023/08/09 16:47:59 - mmengine - INFO - Epoch(train) [138][130/442] lr: 5.000000e-04 eta: 3:08:23 time: 0.350435 data_time: 0.030294 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.837275 2023/08/09 16:48:03 - mmengine - INFO - Epoch(train) [138][140/442] lr: 5.000000e-04 eta: 3:08:20 time: 0.351376 data_time: 0.030324 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.856540 2023/08/09 16:48:06 - mmengine - INFO - Epoch(train) [138][150/442] lr: 5.000000e-04 eta: 3:08:16 time: 0.352700 data_time: 0.030417 memory: 4565 loss: 0.000941 loss_kpt: 0.000941 acc_pose: 0.815910 2023/08/09 16:48:10 - mmengine - INFO - Epoch(train) [138][160/442] lr: 5.000000e-04 eta: 3:08:13 time: 0.354146 data_time: 0.030479 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.791164 2023/08/09 16:48:13 - mmengine - INFO - Epoch(train) [138][170/442] lr: 5.000000e-04 eta: 3:08:09 time: 0.355753 data_time: 0.030204 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.803871 2023/08/09 16:48:17 - mmengine - INFO - Epoch(train) [138][180/442] lr: 5.000000e-04 eta: 3:08:06 time: 0.354455 data_time: 0.030044 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.778055 2023/08/09 16:48:20 - mmengine - INFO - Epoch(train) [138][190/442] lr: 5.000000e-04 eta: 3:08:03 time: 0.355749 data_time: 0.030350 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.904922 2023/08/09 16:48:24 - mmengine - INFO - Epoch(train) [138][200/442] lr: 5.000000e-04 eta: 3:07:59 time: 0.356101 data_time: 0.030569 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.777396 2023/08/09 16:48:28 - mmengine - INFO - Epoch(train) [138][210/442] lr: 5.000000e-04 eta: 3:07:56 time: 0.358507 data_time: 0.030734 memory: 4565 loss: 0.000915 loss_kpt: 0.000915 acc_pose: 0.850400 2023/08/09 16:48:31 - mmengine - INFO - Epoch(train) [138][220/442] lr: 5.000000e-04 eta: 3:07:52 time: 0.356227 data_time: 0.030760 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.829221 2023/08/09 16:48:35 - mmengine - INFO - Epoch(train) [138][230/442] lr: 5.000000e-04 eta: 3:07:49 time: 0.355811 data_time: 0.030821 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.777253 2023/08/09 16:48:38 - mmengine - INFO - Epoch(train) [138][240/442] lr: 5.000000e-04 eta: 3:07:45 time: 0.354740 data_time: 0.030644 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.813069 2023/08/09 16:48:42 - mmengine - INFO - Epoch(train) [138][250/442] lr: 5.000000e-04 eta: 3:07:42 time: 0.353806 data_time: 0.030421 memory: 4565 loss: 0.000959 loss_kpt: 0.000959 acc_pose: 0.852236 2023/08/09 16:48:45 - mmengine - INFO - Epoch(train) [138][260/442] lr: 5.000000e-04 eta: 3:07:38 time: 0.350973 data_time: 0.030400 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.856220 2023/08/09 16:48:49 - mmengine - INFO - Epoch(train) [138][270/442] lr: 5.000000e-04 eta: 3:07:35 time: 0.352843 data_time: 0.030686 memory: 4565 loss: 0.000940 loss_kpt: 0.000940 acc_pose: 0.910982 2023/08/09 16:48:52 - mmengine - INFO - Epoch(train) [138][280/442] lr: 5.000000e-04 eta: 3:07:31 time: 0.352823 data_time: 0.030755 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.855893 2023/08/09 16:48:56 - mmengine - INFO - Epoch(train) [138][290/442] lr: 5.000000e-04 eta: 3:07:28 time: 0.353212 data_time: 0.030872 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.814579 2023/08/09 16:48:59 - mmengine - INFO - Epoch(train) [138][300/442] lr: 5.000000e-04 eta: 3:07:24 time: 0.353746 data_time: 0.031100 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.861202 2023/08/09 16:49:03 - mmengine - INFO - Epoch(train) [138][310/442] lr: 5.000000e-04 eta: 3:07:21 time: 0.352835 data_time: 0.031158 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.809981 2023/08/09 16:49:07 - mmengine - INFO - Epoch(train) [138][320/442] lr: 5.000000e-04 eta: 3:07:18 time: 0.356039 data_time: 0.031299 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.864843 2023/08/09 16:49:10 - mmengine - INFO - Epoch(train) [138][330/442] lr: 5.000000e-04 eta: 3:07:15 time: 0.357503 data_time: 0.031241 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.842194 2023/08/09 16:49:14 - mmengine - INFO - Epoch(train) [138][340/442] lr: 5.000000e-04 eta: 3:07:11 time: 0.356772 data_time: 0.031134 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.904503 2023/08/09 16:49:17 - mmengine - INFO - Epoch(train) [138][350/442] lr: 5.000000e-04 eta: 3:07:08 time: 0.358258 data_time: 0.030776 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.892740 2023/08/09 16:49:21 - mmengine - INFO - Epoch(train) [138][360/442] lr: 5.000000e-04 eta: 3:07:04 time: 0.358360 data_time: 0.030639 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.806591 2023/08/09 16:49:24 - mmengine - INFO - Epoch(train) [138][370/442] lr: 5.000000e-04 eta: 3:07:01 time: 0.353739 data_time: 0.030282 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.778290 2023/08/09 16:49:28 - mmengine - INFO - Epoch(train) [138][380/442] lr: 5.000000e-04 eta: 3:06:57 time: 0.354280 data_time: 0.030361 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.826288 2023/08/09 16:49:31 - mmengine - INFO - Epoch(train) [138][390/442] lr: 5.000000e-04 eta: 3:06:54 time: 0.354772 data_time: 0.030559 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.866935 2023/08/09 16:49:35 - mmengine - INFO - Epoch(train) [138][400/442] lr: 5.000000e-04 eta: 3:06:50 time: 0.354349 data_time: 0.031006 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.839405 2023/08/09 16:49:39 - mmengine - INFO - Epoch(train) [138][410/442] lr: 5.000000e-04 eta: 3:06:47 time: 0.354633 data_time: 0.030869 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.774871 2023/08/09 16:49:42 - mmengine - INFO - Epoch(train) [138][420/442] lr: 5.000000e-04 eta: 3:06:44 time: 0.357738 data_time: 0.034041 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.823974 2023/08/09 16:49:46 - mmengine - INFO - Epoch(train) [138][430/442] lr: 5.000000e-04 eta: 3:06:40 time: 0.355666 data_time: 0.033931 memory: 4565 loss: 0.000955 loss_kpt: 0.000955 acc_pose: 0.859231 2023/08/09 16:49:49 - mmengine - INFO - Epoch(train) [138][440/442] lr: 5.000000e-04 eta: 3:06:37 time: 0.354320 data_time: 0.033773 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.735923 2023/08/09 16:49:50 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:49:51 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:49:54 - mmengine - INFO - Epoch(train) [139][ 10/442] lr: 5.000000e-04 eta: 3:06:33 time: 0.356020 data_time: 0.037210 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.843403 2023/08/09 16:49:57 - mmengine - INFO - Epoch(train) [139][ 20/442] lr: 5.000000e-04 eta: 3:06:29 time: 0.354571 data_time: 0.034246 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.858707 2023/08/09 16:50:01 - mmengine - INFO - Epoch(train) [139][ 30/442] lr: 5.000000e-04 eta: 3:06:26 time: 0.355678 data_time: 0.034382 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.871803 2023/08/09 16:50:04 - mmengine - INFO - Epoch(train) [139][ 40/442] lr: 5.000000e-04 eta: 3:06:23 time: 0.358815 data_time: 0.034037 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.839218 2023/08/09 16:50:08 - mmengine - INFO - Epoch(train) [139][ 50/442] lr: 5.000000e-04 eta: 3:06:19 time: 0.360149 data_time: 0.034612 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.805840 2023/08/09 16:50:11 - mmengine - INFO - Epoch(train) [139][ 60/442] lr: 5.000000e-04 eta: 3:06:16 time: 0.356143 data_time: 0.030785 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.781080 2023/08/09 16:50:15 - mmengine - INFO - Epoch(train) [139][ 70/442] lr: 5.000000e-04 eta: 3:06:12 time: 0.354870 data_time: 0.030930 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.849818 2023/08/09 16:50:18 - mmengine - INFO - Epoch(train) [139][ 80/442] lr: 5.000000e-04 eta: 3:06:09 time: 0.353985 data_time: 0.030839 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.834101 2023/08/09 16:50:22 - mmengine - INFO - Epoch(train) [139][ 90/442] lr: 5.000000e-04 eta: 3:06:06 time: 0.359342 data_time: 0.031013 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.863679 2023/08/09 16:50:26 - mmengine - INFO - Epoch(train) [139][100/442] lr: 5.000000e-04 eta: 3:06:03 time: 0.362927 data_time: 0.030767 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.757889 2023/08/09 16:50:29 - mmengine - INFO - Epoch(train) [139][110/442] lr: 5.000000e-04 eta: 3:05:59 time: 0.361939 data_time: 0.030473 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.896002 2023/08/09 16:50:33 - mmengine - INFO - Epoch(train) [139][120/442] lr: 5.000000e-04 eta: 3:05:56 time: 0.360710 data_time: 0.030030 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.837621 2023/08/09 16:50:36 - mmengine - INFO - Epoch(train) [139][130/442] lr: 5.000000e-04 eta: 3:05:52 time: 0.361448 data_time: 0.030395 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.867773 2023/08/09 16:50:40 - mmengine - INFO - Epoch(train) [139][140/442] lr: 5.000000e-04 eta: 3:05:49 time: 0.355364 data_time: 0.030385 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.857644 2023/08/09 16:50:44 - mmengine - INFO - Epoch(train) [139][150/442] lr: 5.000000e-04 eta: 3:05:46 time: 0.355453 data_time: 0.031118 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.874839 2023/08/09 16:50:47 - mmengine - INFO - Epoch(train) [139][160/442] lr: 5.000000e-04 eta: 3:05:42 time: 0.356456 data_time: 0.031220 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.827746 2023/08/09 16:50:51 - mmengine - INFO - Epoch(train) [139][170/442] lr: 5.000000e-04 eta: 3:05:39 time: 0.356322 data_time: 0.031410 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.812815 2023/08/09 16:50:54 - mmengine - INFO - Epoch(train) [139][180/442] lr: 5.000000e-04 eta: 3:05:35 time: 0.355416 data_time: 0.031038 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.909017 2023/08/09 16:50:58 - mmengine - INFO - Epoch(train) [139][190/442] lr: 5.000000e-04 eta: 3:05:32 time: 0.353542 data_time: 0.030980 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.788728 2023/08/09 16:51:01 - mmengine - INFO - Epoch(train) [139][200/442] lr: 5.000000e-04 eta: 3:05:28 time: 0.353716 data_time: 0.030757 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.870926 2023/08/09 16:51:05 - mmengine - INFO - Epoch(train) [139][210/442] lr: 5.000000e-04 eta: 3:05:26 time: 0.358682 data_time: 0.031318 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.837637 2023/08/09 16:51:09 - mmengine - INFO - Epoch(train) [139][220/442] lr: 5.000000e-04 eta: 3:05:22 time: 0.359538 data_time: 0.031304 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.741746 2023/08/09 16:51:12 - mmengine - INFO - Epoch(train) [139][230/442] lr: 5.000000e-04 eta: 3:05:18 time: 0.359471 data_time: 0.031367 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.852928 2023/08/09 16:51:16 - mmengine - INFO - Epoch(train) [139][240/442] lr: 5.000000e-04 eta: 3:05:15 time: 0.359965 data_time: 0.031277 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.819163 2023/08/09 16:51:19 - mmengine - INFO - Epoch(train) [139][250/442] lr: 5.000000e-04 eta: 3:05:11 time: 0.356704 data_time: 0.030954 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.824328 2023/08/09 16:51:23 - mmengine - INFO - Epoch(train) [139][260/442] lr: 5.000000e-04 eta: 3:05:08 time: 0.351858 data_time: 0.030412 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.781746 2023/08/09 16:51:26 - mmengine - INFO - Epoch(train) [139][270/442] lr: 5.000000e-04 eta: 3:05:04 time: 0.352099 data_time: 0.030392 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.830259 2023/08/09 16:51:30 - mmengine - INFO - Epoch(train) [139][280/442] lr: 5.000000e-04 eta: 3:05:01 time: 0.353675 data_time: 0.030567 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.810203 2023/08/09 16:51:33 - mmengine - INFO - Epoch(train) [139][290/442] lr: 5.000000e-04 eta: 3:04:57 time: 0.352394 data_time: 0.030604 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.840186 2023/08/09 16:51:37 - mmengine - INFO - Epoch(train) [139][300/442] lr: 5.000000e-04 eta: 3:04:54 time: 0.351511 data_time: 0.030350 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.866216 2023/08/09 16:51:40 - mmengine - INFO - Epoch(train) [139][310/442] lr: 5.000000e-04 eta: 3:04:50 time: 0.350292 data_time: 0.030227 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.791165 2023/08/09 16:51:44 - mmengine - INFO - Epoch(train) [139][320/442] lr: 5.000000e-04 eta: 3:04:47 time: 0.351271 data_time: 0.030219 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.814854 2023/08/09 16:51:48 - mmengine - INFO - Epoch(train) [139][330/442] lr: 5.000000e-04 eta: 3:04:44 time: 0.352178 data_time: 0.029976 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.899161 2023/08/09 16:51:51 - mmengine - INFO - Epoch(train) [139][340/442] lr: 5.000000e-04 eta: 3:04:40 time: 0.355558 data_time: 0.030179 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.828316 2023/08/09 16:51:55 - mmengine - INFO - Epoch(train) [139][350/442] lr: 5.000000e-04 eta: 3:04:37 time: 0.356814 data_time: 0.030387 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.871773 2023/08/09 16:51:58 - mmengine - INFO - Epoch(train) [139][360/442] lr: 5.000000e-04 eta: 3:04:34 time: 0.361098 data_time: 0.030394 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.757916 2023/08/09 16:52:02 - mmengine - INFO - Epoch(train) [139][370/442] lr: 5.000000e-04 eta: 3:04:30 time: 0.360338 data_time: 0.030320 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.830420 2023/08/09 16:52:06 - mmengine - INFO - Epoch(train) [139][380/442] lr: 5.000000e-04 eta: 3:04:27 time: 0.360228 data_time: 0.030399 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.885076 2023/08/09 16:52:09 - mmengine - INFO - Epoch(train) [139][390/442] lr: 5.000000e-04 eta: 3:04:23 time: 0.358607 data_time: 0.030175 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.833605 2023/08/09 16:52:13 - mmengine - INFO - Epoch(train) [139][400/442] lr: 5.000000e-04 eta: 3:04:20 time: 0.362346 data_time: 0.030855 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.859804 2023/08/09 16:52:16 - mmengine - INFO - Epoch(train) [139][410/442] lr: 5.000000e-04 eta: 3:04:17 time: 0.360114 data_time: 0.030997 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.914513 2023/08/09 16:52:20 - mmengine - INFO - Epoch(train) [139][420/442] lr: 5.000000e-04 eta: 3:04:13 time: 0.358799 data_time: 0.030955 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.792546 2023/08/09 16:52:23 - mmengine - INFO - Epoch(train) [139][430/442] lr: 5.000000e-04 eta: 3:04:10 time: 0.358001 data_time: 0.030884 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.868347 2023/08/09 16:52:27 - mmengine - INFO - Epoch(train) [139][440/442] lr: 5.000000e-04 eta: 3:04:06 time: 0.356557 data_time: 0.030870 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.800475 2023/08/09 16:52:28 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:52:31 - mmengine - INFO - Epoch(train) [140][ 10/442] lr: 5.000000e-04 eta: 3:04:03 time: 0.354434 data_time: 0.033585 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.792513 2023/08/09 16:52:35 - mmengine - INFO - Epoch(train) [140][ 20/442] lr: 5.000000e-04 eta: 3:03:59 time: 0.353347 data_time: 0.033643 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.864495 2023/08/09 16:52:38 - mmengine - INFO - Epoch(train) [140][ 30/442] lr: 5.000000e-04 eta: 3:03:56 time: 0.355155 data_time: 0.034136 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.807298 2023/08/09 16:52:42 - mmengine - INFO - Epoch(train) [140][ 40/442] lr: 5.000000e-04 eta: 3:03:52 time: 0.353953 data_time: 0.034179 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.872619 2023/08/09 16:52:45 - mmengine - INFO - Epoch(train) [140][ 50/442] lr: 5.000000e-04 eta: 3:03:48 time: 0.355133 data_time: 0.034440 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.870569 2023/08/09 16:52:49 - mmengine - INFO - Epoch(train) [140][ 60/442] lr: 5.000000e-04 eta: 3:03:45 time: 0.350851 data_time: 0.030614 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.815826 2023/08/09 16:52:53 - mmengine - INFO - Epoch(train) [140][ 70/442] lr: 5.000000e-04 eta: 3:03:42 time: 0.354372 data_time: 0.030366 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.807165 2023/08/09 16:52:56 - mmengine - INFO - Epoch(train) [140][ 80/442] lr: 5.000000e-04 eta: 3:03:38 time: 0.353985 data_time: 0.029999 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.834716 2023/08/09 16:53:00 - mmengine - INFO - Epoch(train) [140][ 90/442] lr: 5.000000e-04 eta: 3:03:35 time: 0.355469 data_time: 0.030173 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.769363 2023/08/09 16:53:03 - mmengine - INFO - Epoch(train) [140][100/442] lr: 5.000000e-04 eta: 3:03:31 time: 0.355398 data_time: 0.030104 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.876462 2023/08/09 16:53:07 - mmengine - INFO - Epoch(train) [140][110/442] lr: 5.000000e-04 eta: 3:03:28 time: 0.355334 data_time: 0.030126 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.812137 2023/08/09 16:53:10 - mmengine - INFO - Epoch(train) [140][120/442] lr: 5.000000e-04 eta: 3:03:24 time: 0.351322 data_time: 0.030511 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.848536 2023/08/09 16:53:14 - mmengine - INFO - Epoch(train) [140][130/442] lr: 5.000000e-04 eta: 3:03:20 time: 0.350422 data_time: 0.030412 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.763714 2023/08/09 16:53:17 - mmengine - INFO - Epoch(train) [140][140/442] lr: 5.000000e-04 eta: 3:03:17 time: 0.350490 data_time: 0.030825 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.877800 2023/08/09 16:53:21 - mmengine - INFO - Epoch(train) [140][150/442] lr: 5.000000e-04 eta: 3:03:14 time: 0.354090 data_time: 0.034076 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.864138 2023/08/09 16:53:24 - mmengine - INFO - Epoch(train) [140][160/442] lr: 5.000000e-04 eta: 3:03:10 time: 0.355790 data_time: 0.034157 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.892066 2023/08/09 16:53:28 - mmengine - INFO - Epoch(train) [140][170/442] lr: 5.000000e-04 eta: 3:03:08 time: 0.361945 data_time: 0.034290 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.830067 2023/08/09 16:53:32 - mmengine - INFO - Epoch(train) [140][180/442] lr: 5.000000e-04 eta: 3:03:05 time: 0.369723 data_time: 0.034791 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.884306 2023/08/09 16:53:36 - mmengine - INFO - Epoch(train) [140][190/442] lr: 5.000000e-04 eta: 3:03:02 time: 0.376285 data_time: 0.034823 memory: 4565 loss: 0.000915 loss_kpt: 0.000915 acc_pose: 0.807978 2023/08/09 16:53:40 - mmengine - INFO - Epoch(train) [140][200/442] lr: 5.000000e-04 eta: 3:02:59 time: 0.377159 data_time: 0.031962 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.879436 2023/08/09 16:53:44 - mmengine - INFO - Epoch(train) [140][210/442] lr: 5.000000e-04 eta: 3:02:56 time: 0.380960 data_time: 0.032840 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.762209 2023/08/09 16:53:47 - mmengine - INFO - Epoch(train) [140][220/442] lr: 5.000000e-04 eta: 3:02:53 time: 0.376290 data_time: 0.032746 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.794873 2023/08/09 16:53:51 - mmengine - INFO - Epoch(train) [140][230/442] lr: 5.000000e-04 eta: 3:02:49 time: 0.369096 data_time: 0.032319 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.852645 2023/08/09 16:53:54 - mmengine - INFO - Epoch(train) [140][240/442] lr: 5.000000e-04 eta: 3:02:46 time: 0.360638 data_time: 0.031838 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.852083 2023/08/09 16:53:58 - mmengine - INFO - Epoch(train) [140][250/442] lr: 5.000000e-04 eta: 3:02:42 time: 0.354770 data_time: 0.031549 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.809240 2023/08/09 16:54:01 - mmengine - INFO - Epoch(train) [140][260/442] lr: 5.000000e-04 eta: 3:02:38 time: 0.349578 data_time: 0.030790 memory: 4565 loss: 0.000941 loss_kpt: 0.000941 acc_pose: 0.861989 2023/08/09 16:54:05 - mmengine - INFO - Epoch(train) [140][270/442] lr: 5.000000e-04 eta: 3:02:35 time: 0.350183 data_time: 0.030649 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.796645 2023/08/09 16:54:08 - mmengine - INFO - Epoch(train) [140][280/442] lr: 5.000000e-04 eta: 3:02:32 time: 0.352306 data_time: 0.030733 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.821466 2023/08/09 16:54:12 - mmengine - INFO - Epoch(train) [140][290/442] lr: 5.000000e-04 eta: 3:02:28 time: 0.352296 data_time: 0.030918 memory: 4565 loss: 0.000949 loss_kpt: 0.000949 acc_pose: 0.839162 2023/08/09 16:54:15 - mmengine - INFO - Epoch(train) [140][300/442] lr: 5.000000e-04 eta: 3:02:25 time: 0.354444 data_time: 0.030886 memory: 4565 loss: 0.000955 loss_kpt: 0.000955 acc_pose: 0.772385 2023/08/09 16:54:19 - mmengine - INFO - Epoch(train) [140][310/442] lr: 5.000000e-04 eta: 3:02:21 time: 0.353976 data_time: 0.030567 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.816081 2023/08/09 16:54:22 - mmengine - INFO - Epoch(train) [140][320/442] lr: 5.000000e-04 eta: 3:02:18 time: 0.353961 data_time: 0.030378 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.773087 2023/08/09 16:54:26 - mmengine - INFO - Epoch(train) [140][330/442] lr: 5.000000e-04 eta: 3:02:14 time: 0.351712 data_time: 0.030502 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.799499 2023/08/09 16:54:30 - mmengine - INFO - Epoch(train) [140][340/442] lr: 5.000000e-04 eta: 3:02:11 time: 0.359030 data_time: 0.030688 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.879569 2023/08/09 16:54:33 - mmengine - INFO - Epoch(train) [140][350/442] lr: 5.000000e-04 eta: 3:02:08 time: 0.361984 data_time: 0.031500 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.810552 2023/08/09 16:54:37 - mmengine - INFO - Epoch(train) [140][360/442] lr: 5.000000e-04 eta: 3:02:05 time: 0.363060 data_time: 0.031624 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.823753 2023/08/09 16:54:40 - mmengine - INFO - Epoch(train) [140][370/442] lr: 5.000000e-04 eta: 3:02:01 time: 0.360780 data_time: 0.031509 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.825941 2023/08/09 16:54:44 - mmengine - INFO - Epoch(train) [140][380/442] lr: 5.000000e-04 eta: 3:01:57 time: 0.359977 data_time: 0.031303 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.892150 2023/08/09 16:54:47 - mmengine - INFO - Epoch(train) [140][390/442] lr: 5.000000e-04 eta: 3:01:54 time: 0.353152 data_time: 0.030831 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.809431 2023/08/09 16:54:51 - mmengine - INFO - Epoch(train) [140][400/442] lr: 5.000000e-04 eta: 3:01:51 time: 0.351662 data_time: 0.030287 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.866700 2023/08/09 16:54:55 - mmengine - INFO - Epoch(train) [140][410/442] lr: 5.000000e-04 eta: 3:01:47 time: 0.354842 data_time: 0.030766 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.852979 2023/08/09 16:54:58 - mmengine - INFO - Epoch(train) [140][420/442] lr: 5.000000e-04 eta: 3:01:44 time: 0.357111 data_time: 0.031065 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.841050 2023/08/09 16:55:02 - mmengine - INFO - Epoch(train) [140][430/442] lr: 5.000000e-04 eta: 3:01:41 time: 0.358300 data_time: 0.031164 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.801633 2023/08/09 16:55:05 - mmengine - INFO - Epoch(train) [140][440/442] lr: 5.000000e-04 eta: 3:01:37 time: 0.361225 data_time: 0.031291 memory: 4565 loss: 0.000940 loss_kpt: 0.000940 acc_pose: 0.894188 2023/08/09 16:55:06 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:55:06 - mmengine - INFO - Saving checkpoint at 140 epochs 2023/08/09 16:55:12 - mmengine - INFO - Epoch(val) [140][ 10/108] eta: 0:00:20 time: 0.196846 data_time: 0.012887 memory: 4565 2023/08/09 16:55:14 - mmengine - INFO - Epoch(val) [140][ 20/108] eta: 0:00:17 time: 0.197044 data_time: 0.012948 memory: 1624 2023/08/09 16:55:16 - mmengine - INFO - Epoch(val) [140][ 30/108] eta: 0:00:15 time: 0.197337 data_time: 0.012925 memory: 1624 2023/08/09 16:55:18 - mmengine - INFO - Epoch(val) [140][ 40/108] eta: 0:00:13 time: 0.197577 data_time: 0.013108 memory: 1624 2023/08/09 16:55:20 - mmengine - INFO - Epoch(val) [140][ 50/108] eta: 0:00:11 time: 0.199175 data_time: 0.013162 memory: 1624 2023/08/09 16:55:22 - mmengine - INFO - Epoch(val) [140][ 60/108] eta: 0:00:09 time: 0.196446 data_time: 0.011070 memory: 1624 2023/08/09 16:55:23 - mmengine - INFO - Epoch(val) [140][ 70/108] eta: 0:00:07 time: 0.196294 data_time: 0.010980 memory: 1624 2023/08/09 16:55:25 - mmengine - INFO - Epoch(val) [140][ 80/108] eta: 0:00:05 time: 0.195846 data_time: 0.010827 memory: 1624 2023/08/09 16:55:27 - mmengine - INFO - Epoch(val) [140][ 90/108] eta: 0:00:03 time: 0.195577 data_time: 0.010614 memory: 1624 2023/08/09 16:55:29 - mmengine - INFO - Epoch(val) [140][100/108] eta: 0:00:01 time: 0.195481 data_time: 0.010648 memory: 1624 2023/08/09 16:55:31 - mmengine - INFO - Evaluating PCKAccuracy (normalized by ``"bbox_size"``)... 2023/08/09 16:55:31 - mmengine - INFO - Evaluating AUC... 2023/08/09 16:55:31 - mmengine - INFO - Evaluating EPE... 2023/08/09 16:55:31 - mmengine - INFO - Epoch(val) [140][108/108] PCK: 0.961622 AUC: 0.607768 EPE: 14.861745 data_time: 0.011718 time: 0.195629 2023/08/09 16:55:35 - mmengine - INFO - Epoch(train) [141][ 10/442] lr: 5.000000e-04 eta: 3:01:34 time: 0.364421 data_time: 0.035027 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.804025 2023/08/09 16:55:39 - mmengine - INFO - Epoch(train) [141][ 20/442] lr: 5.000000e-04 eta: 3:01:30 time: 0.363083 data_time: 0.034987 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.886260 2023/08/09 16:55:42 - mmengine - INFO - Epoch(train) [141][ 30/442] lr: 5.000000e-04 eta: 3:01:27 time: 0.361826 data_time: 0.036078 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.820525 2023/08/09 16:55:46 - mmengine - INFO - Epoch(train) [141][ 40/442] lr: 5.000000e-04 eta: 3:01:23 time: 0.360927 data_time: 0.036861 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.814628 2023/08/09 16:55:50 - mmengine - INFO - Epoch(train) [141][ 50/442] lr: 5.000000e-04 eta: 3:01:20 time: 0.362906 data_time: 0.041336 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.880129 2023/08/09 16:55:53 - mmengine - INFO - Epoch(train) [141][ 60/442] lr: 5.000000e-04 eta: 3:01:16 time: 0.355154 data_time: 0.038107 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.931540 2023/08/09 16:55:57 - mmengine - INFO - Epoch(train) [141][ 70/442] lr: 5.000000e-04 eta: 3:01:13 time: 0.353674 data_time: 0.038699 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.884025 2023/08/09 16:56:00 - mmengine - INFO - Epoch(train) [141][ 80/442] lr: 5.000000e-04 eta: 3:01:09 time: 0.353709 data_time: 0.038610 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.848148 2023/08/09 16:56:04 - mmengine - INFO - Epoch(train) [141][ 90/442] lr: 5.000000e-04 eta: 3:01:06 time: 0.358521 data_time: 0.038325 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.789359 2023/08/09 16:56:07 - mmengine - INFO - Epoch(train) [141][100/442] lr: 5.000000e-04 eta: 3:01:03 time: 0.354274 data_time: 0.033943 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.843249 2023/08/09 16:56:11 - mmengine - INFO - Epoch(train) [141][110/442] lr: 5.000000e-04 eta: 3:00:59 time: 0.355880 data_time: 0.033463 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.837993 2023/08/09 16:56:14 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:56:14 - mmengine - INFO - Epoch(train) [141][120/442] lr: 5.000000e-04 eta: 3:00:56 time: 0.356428 data_time: 0.032501 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.822982 2023/08/09 16:56:18 - mmengine - INFO - Epoch(train) [141][130/442] lr: 5.000000e-04 eta: 3:00:52 time: 0.357230 data_time: 0.031714 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.871751 2023/08/09 16:56:22 - mmengine - INFO - Epoch(train) [141][140/442] lr: 5.000000e-04 eta: 3:00:49 time: 0.353819 data_time: 0.031169 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.800693 2023/08/09 16:56:25 - mmengine - INFO - Epoch(train) [141][150/442] lr: 5.000000e-04 eta: 3:00:45 time: 0.355537 data_time: 0.031026 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.902697 2023/08/09 16:56:29 - mmengine - INFO - Epoch(train) [141][160/442] lr: 5.000000e-04 eta: 3:00:42 time: 0.355012 data_time: 0.031185 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.832173 2023/08/09 16:56:32 - mmengine - INFO - Epoch(train) [141][170/442] lr: 5.000000e-04 eta: 3:00:38 time: 0.354217 data_time: 0.031156 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.881810 2023/08/09 16:56:36 - mmengine - INFO - Epoch(train) [141][180/442] lr: 5.000000e-04 eta: 3:00:35 time: 0.352850 data_time: 0.030949 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.839699 2023/08/09 16:56:39 - mmengine - INFO - Epoch(train) [141][190/442] lr: 5.000000e-04 eta: 3:00:32 time: 0.355374 data_time: 0.031195 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.843079 2023/08/09 16:56:43 - mmengine - INFO - Epoch(train) [141][200/442] lr: 5.000000e-04 eta: 3:00:28 time: 0.354990 data_time: 0.031251 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.820005 2023/08/09 16:56:46 - mmengine - INFO - Epoch(train) [141][210/442] lr: 5.000000e-04 eta: 3:00:25 time: 0.355269 data_time: 0.030936 memory: 4565 loss: 0.000915 loss_kpt: 0.000915 acc_pose: 0.891044 2023/08/09 16:56:50 - mmengine - INFO - Epoch(train) [141][220/442] lr: 5.000000e-04 eta: 3:00:21 time: 0.355891 data_time: 0.031011 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.832171 2023/08/09 16:56:53 - mmengine - INFO - Epoch(train) [141][230/442] lr: 5.000000e-04 eta: 3:00:18 time: 0.355367 data_time: 0.030895 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.803278 2023/08/09 16:56:57 - mmengine - INFO - Epoch(train) [141][240/442] lr: 5.000000e-04 eta: 3:00:14 time: 0.351579 data_time: 0.030598 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.791288 2023/08/09 16:57:00 - mmengine - INFO - Epoch(train) [141][250/442] lr: 5.000000e-04 eta: 3:00:10 time: 0.350807 data_time: 0.031103 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.727381 2023/08/09 16:57:04 - mmengine - INFO - Epoch(train) [141][260/442] lr: 5.000000e-04 eta: 3:00:08 time: 0.356473 data_time: 0.031189 memory: 4565 loss: 0.000951 loss_kpt: 0.000951 acc_pose: 0.897512 2023/08/09 16:57:08 - mmengine - INFO - Epoch(train) [141][270/442] lr: 5.000000e-04 eta: 3:00:05 time: 0.361195 data_time: 0.031801 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.850330 2023/08/09 16:57:12 - mmengine - INFO - Epoch(train) [141][280/442] lr: 5.000000e-04 eta: 3:00:02 time: 0.369415 data_time: 0.036462 memory: 4565 loss: 0.000958 loss_kpt: 0.000958 acc_pose: 0.867800 2023/08/09 16:57:15 - mmengine - INFO - Epoch(train) [141][290/442] lr: 5.000000e-04 eta: 2:59:58 time: 0.370442 data_time: 0.037292 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.831850 2023/08/09 16:57:19 - mmengine - INFO - Epoch(train) [141][300/442] lr: 5.000000e-04 eta: 2:59:55 time: 0.370870 data_time: 0.037395 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.803064 2023/08/09 16:57:23 - mmengine - INFO - Epoch(train) [141][310/442] lr: 5.000000e-04 eta: 2:59:51 time: 0.365317 data_time: 0.038025 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.832067 2023/08/09 16:57:26 - mmengine - INFO - Epoch(train) [141][320/442] lr: 5.000000e-04 eta: 2:59:48 time: 0.359996 data_time: 0.037572 memory: 4565 loss: 0.000940 loss_kpt: 0.000940 acc_pose: 0.811183 2023/08/09 16:57:30 - mmengine - INFO - Epoch(train) [141][330/442] lr: 5.000000e-04 eta: 2:59:45 time: 0.354280 data_time: 0.033004 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.799644 2023/08/09 16:57:33 - mmengine - INFO - Epoch(train) [141][340/442] lr: 5.000000e-04 eta: 2:59:41 time: 0.356771 data_time: 0.032737 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.802974 2023/08/09 16:57:37 - mmengine - INFO - Epoch(train) [141][350/442] lr: 5.000000e-04 eta: 2:59:38 time: 0.359271 data_time: 0.032366 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.820410 2023/08/09 16:57:40 - mmengine - INFO - Epoch(train) [141][360/442] lr: 5.000000e-04 eta: 2:59:35 time: 0.358947 data_time: 0.031386 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.811116 2023/08/09 16:57:44 - mmengine - INFO - Epoch(train) [141][370/442] lr: 5.000000e-04 eta: 2:59:31 time: 0.359224 data_time: 0.031061 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.810413 2023/08/09 16:57:48 - mmengine - INFO - Epoch(train) [141][380/442] lr: 5.000000e-04 eta: 2:59:28 time: 0.358008 data_time: 0.030967 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.808910 2023/08/09 16:57:51 - mmengine - INFO - Epoch(train) [141][390/442] lr: 5.000000e-04 eta: 2:59:25 time: 0.362620 data_time: 0.031051 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.818298 2023/08/09 16:57:55 - mmengine - INFO - Epoch(train) [141][400/442] lr: 5.000000e-04 eta: 2:59:21 time: 0.360592 data_time: 0.030895 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.846254 2023/08/09 16:57:59 - mmengine - INFO - Epoch(train) [141][410/442] lr: 5.000000e-04 eta: 2:59:18 time: 0.361774 data_time: 0.031432 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.837891 2023/08/09 16:58:02 - mmengine - INFO - Epoch(train) [141][420/442] lr: 5.000000e-04 eta: 2:59:14 time: 0.361250 data_time: 0.031403 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.807863 2023/08/09 16:58:06 - mmengine - INFO - Epoch(train) [141][430/442] lr: 5.000000e-04 eta: 2:59:11 time: 0.360127 data_time: 0.031354 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.818817 2023/08/09 16:58:09 - mmengine - INFO - Epoch(train) [141][440/442] lr: 5.000000e-04 eta: 2:59:07 time: 0.352712 data_time: 0.030704 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.847407 2023/08/09 16:58:10 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 16:58:13 - mmengine - INFO - Epoch(train) [142][ 10/442] lr: 5.000000e-04 eta: 2:59:03 time: 0.352160 data_time: 0.034278 memory: 4565 loss: 0.000944 loss_kpt: 0.000944 acc_pose: 0.864616 2023/08/09 16:58:17 - mmengine - INFO - Epoch(train) [142][ 20/442] lr: 5.000000e-04 eta: 2:58:59 time: 0.350948 data_time: 0.034253 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.882026 2023/08/09 16:58:20 - mmengine - INFO - Epoch(train) [142][ 30/442] lr: 5.000000e-04 eta: 2:58:56 time: 0.350731 data_time: 0.035128 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.870208 2023/08/09 16:58:24 - mmengine - INFO - Epoch(train) [142][ 40/442] lr: 5.000000e-04 eta: 2:58:52 time: 0.348955 data_time: 0.036130 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.810016 2023/08/09 16:58:27 - mmengine - INFO - Epoch(train) [142][ 50/442] lr: 5.000000e-04 eta: 2:58:49 time: 0.351955 data_time: 0.037130 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.833536 2023/08/09 16:58:31 - mmengine - INFO - Epoch(train) [142][ 60/442] lr: 5.000000e-04 eta: 2:58:45 time: 0.351285 data_time: 0.033583 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.847276 2023/08/09 16:58:34 - mmengine - INFO - Epoch(train) [142][ 70/442] lr: 5.000000e-04 eta: 2:58:42 time: 0.351376 data_time: 0.033446 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.819280 2023/08/09 16:58:38 - mmengine - INFO - Epoch(train) [142][ 80/442] lr: 5.000000e-04 eta: 2:58:38 time: 0.351097 data_time: 0.032848 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.871807 2023/08/09 16:58:41 - mmengine - INFO - Epoch(train) [142][ 90/442] lr: 5.000000e-04 eta: 2:58:34 time: 0.352480 data_time: 0.031989 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.862450 2023/08/09 16:58:45 - mmengine - INFO - Epoch(train) [142][100/442] lr: 5.000000e-04 eta: 2:58:31 time: 0.349404 data_time: 0.031265 memory: 4565 loss: 0.000915 loss_kpt: 0.000915 acc_pose: 0.810006 2023/08/09 16:58:48 - mmengine - INFO - Epoch(train) [142][110/442] lr: 5.000000e-04 eta: 2:58:27 time: 0.344545 data_time: 0.030780 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.746721 2023/08/09 16:58:52 - mmengine - INFO - Epoch(train) [142][120/442] lr: 5.000000e-04 eta: 2:58:23 time: 0.342525 data_time: 0.030478 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.852569 2023/08/09 16:58:55 - mmengine - INFO - Epoch(train) [142][130/442] lr: 5.000000e-04 eta: 2:58:19 time: 0.342578 data_time: 0.030677 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.827194 2023/08/09 16:58:58 - mmengine - INFO - Epoch(train) [142][140/442] lr: 5.000000e-04 eta: 2:58:16 time: 0.342237 data_time: 0.030935 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.864449 2023/08/09 16:59:02 - mmengine - INFO - Epoch(train) [142][150/442] lr: 5.000000e-04 eta: 2:58:12 time: 0.342372 data_time: 0.031153 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.854424 2023/08/09 16:59:06 - mmengine - INFO - Epoch(train) [142][160/442] lr: 5.000000e-04 eta: 2:58:09 time: 0.349008 data_time: 0.031555 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.899194 2023/08/09 16:59:09 - mmengine - INFO - Epoch(train) [142][170/442] lr: 5.000000e-04 eta: 2:58:06 time: 0.358460 data_time: 0.032129 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.826319 2023/08/09 16:59:13 - mmengine - INFO - Epoch(train) [142][180/442] lr: 5.000000e-04 eta: 2:58:03 time: 0.366144 data_time: 0.032028 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.803082 2023/08/09 16:59:17 - mmengine - INFO - Epoch(train) [142][190/442] lr: 5.000000e-04 eta: 2:58:00 time: 0.368725 data_time: 0.031916 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.901835 2023/08/09 16:59:20 - mmengine - INFO - Epoch(train) [142][200/442] lr: 5.000000e-04 eta: 2:57:56 time: 0.370257 data_time: 0.031666 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.799786 2023/08/09 16:59:24 - mmengine - INFO - Epoch(train) [142][210/442] lr: 5.000000e-04 eta: 2:57:53 time: 0.368393 data_time: 0.031527 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.855980 2023/08/09 16:59:28 - mmengine - INFO - Epoch(train) [142][220/442] lr: 5.000000e-04 eta: 2:57:49 time: 0.361120 data_time: 0.031198 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.813461 2023/08/09 16:59:31 - mmengine - INFO - Epoch(train) [142][230/442] lr: 5.000000e-04 eta: 2:57:46 time: 0.352008 data_time: 0.030950 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.816986 2023/08/09 16:59:34 - mmengine - INFO - Epoch(train) [142][240/442] lr: 5.000000e-04 eta: 2:57:42 time: 0.349875 data_time: 0.030688 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.798182 2023/08/09 16:59:38 - mmengine - INFO - Epoch(train) [142][250/442] lr: 5.000000e-04 eta: 2:57:38 time: 0.347054 data_time: 0.030687 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.860163 2023/08/09 16:59:41 - mmengine - INFO - Epoch(train) [142][260/442] lr: 5.000000e-04 eta: 2:57:34 time: 0.342438 data_time: 0.030295 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.848905 2023/08/09 16:59:45 - mmengine - INFO - Epoch(train) [142][270/442] lr: 5.000000e-04 eta: 2:57:31 time: 0.340964 data_time: 0.030125 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.890021 2023/08/09 16:59:48 - mmengine - INFO - Epoch(train) [142][280/442] lr: 5.000000e-04 eta: 2:57:27 time: 0.342671 data_time: 0.030555 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.870161 2023/08/09 16:59:52 - mmengine - INFO - Epoch(train) [142][290/442] lr: 5.000000e-04 eta: 2:57:23 time: 0.343555 data_time: 0.031028 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.919343 2023/08/09 16:59:55 - mmengine - INFO - Epoch(train) [142][300/442] lr: 5.000000e-04 eta: 2:57:20 time: 0.343827 data_time: 0.030973 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.862606 2023/08/09 16:59:58 - mmengine - INFO - Epoch(train) [142][310/442] lr: 5.000000e-04 eta: 2:57:16 time: 0.343619 data_time: 0.030977 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.830707 2023/08/09 17:00:02 - mmengine - INFO - Epoch(train) [142][320/442] lr: 5.000000e-04 eta: 2:57:12 time: 0.343473 data_time: 0.031785 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.834103 2023/08/09 17:00:05 - mmengine - INFO - Epoch(train) [142][330/442] lr: 5.000000e-04 eta: 2:57:08 time: 0.341710 data_time: 0.031730 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.847537 2023/08/09 17:00:09 - mmengine - INFO - Epoch(train) [142][340/442] lr: 5.000000e-04 eta: 2:57:05 time: 0.340780 data_time: 0.031579 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.774094 2023/08/09 17:00:12 - mmengine - INFO - Epoch(train) [142][350/442] lr: 5.000000e-04 eta: 2:57:02 time: 0.348458 data_time: 0.032114 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.815444 2023/08/09 17:00:16 - mmengine - INFO - Epoch(train) [142][360/442] lr: 5.000000e-04 eta: 2:56:58 time: 0.349665 data_time: 0.032235 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.911581 2023/08/09 17:00:19 - mmengine - INFO - Epoch(train) [142][370/442] lr: 5.000000e-04 eta: 2:56:54 time: 0.351814 data_time: 0.034566 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.844703 2023/08/09 17:00:23 - mmengine - INFO - Epoch(train) [142][380/442] lr: 5.000000e-04 eta: 2:56:51 time: 0.353148 data_time: 0.034119 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.831276 2023/08/09 17:00:27 - mmengine - INFO - Epoch(train) [142][390/442] lr: 5.000000e-04 eta: 2:56:48 time: 0.361058 data_time: 0.034140 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.771512 2023/08/09 17:00:31 - mmengine - INFO - Epoch(train) [142][400/442] lr: 5.000000e-04 eta: 2:56:45 time: 0.365453 data_time: 0.037335 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.823517 2023/08/09 17:00:34 - mmengine - INFO - Epoch(train) [142][410/442] lr: 5.000000e-04 eta: 2:56:42 time: 0.367494 data_time: 0.037349 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.850055 2023/08/09 17:00:38 - mmengine - INFO - Epoch(train) [142][420/442] lr: 5.000000e-04 eta: 2:56:38 time: 0.367438 data_time: 0.034498 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.790225 2023/08/09 17:00:41 - mmengine - INFO - Epoch(train) [142][430/442] lr: 5.000000e-04 eta: 2:56:35 time: 0.366302 data_time: 0.034486 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.814386 2023/08/09 17:00:45 - mmengine - INFO - Epoch(train) [142][440/442] lr: 5.000000e-04 eta: 2:56:31 time: 0.356881 data_time: 0.034141 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.757879 2023/08/09 17:00:45 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:00:49 - mmengine - INFO - Epoch(train) [143][ 10/442] lr: 5.000000e-04 eta: 2:56:26 time: 0.346856 data_time: 0.033818 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.791111 2023/08/09 17:00:52 - mmengine - INFO - Epoch(train) [143][ 20/442] lr: 5.000000e-04 eta: 2:56:23 time: 0.343976 data_time: 0.033817 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.812081 2023/08/09 17:00:56 - mmengine - INFO - Epoch(train) [143][ 30/442] lr: 5.000000e-04 eta: 2:56:19 time: 0.342295 data_time: 0.034195 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.831777 2023/08/09 17:00:59 - mmengine - INFO - Epoch(train) [143][ 40/442] lr: 5.000000e-04 eta: 2:56:15 time: 0.344283 data_time: 0.034839 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.753152 2023/08/09 17:01:03 - mmengine - INFO - Epoch(train) [143][ 50/442] lr: 5.000000e-04 eta: 2:56:12 time: 0.352213 data_time: 0.035732 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.837204 2023/08/09 17:01:06 - mmengine - INFO - Epoch(train) [143][ 60/442] lr: 5.000000e-04 eta: 2:56:09 time: 0.350443 data_time: 0.032429 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.887962 2023/08/09 17:01:10 - mmengine - INFO - Epoch(train) [143][ 70/442] lr: 5.000000e-04 eta: 2:56:05 time: 0.351157 data_time: 0.032828 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.865556 2023/08/09 17:01:13 - mmengine - INFO - Epoch(train) [143][ 80/442] lr: 5.000000e-04 eta: 2:56:01 time: 0.350842 data_time: 0.032652 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.881463 2023/08/09 17:01:17 - mmengine - INFO - Epoch(train) [143][ 90/442] lr: 5.000000e-04 eta: 2:55:58 time: 0.355225 data_time: 0.032971 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.765755 2023/08/09 17:01:20 - mmengine - INFO - Epoch(train) [143][100/442] lr: 5.000000e-04 eta: 2:55:55 time: 0.352348 data_time: 0.032798 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.861376 2023/08/09 17:01:24 - mmengine - INFO - Epoch(train) [143][110/442] lr: 5.000000e-04 eta: 2:55:51 time: 0.354728 data_time: 0.033172 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.818526 2023/08/09 17:01:28 - mmengine - INFO - Epoch(train) [143][120/442] lr: 5.000000e-04 eta: 2:55:48 time: 0.355888 data_time: 0.032785 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.871336 2023/08/09 17:01:31 - mmengine - INFO - Epoch(train) [143][130/442] lr: 5.000000e-04 eta: 2:55:44 time: 0.357309 data_time: 0.032480 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.841752 2023/08/09 17:01:35 - mmengine - INFO - Epoch(train) [143][140/442] lr: 5.000000e-04 eta: 2:55:41 time: 0.353994 data_time: 0.031730 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.883912 2023/08/09 17:01:38 - mmengine - INFO - Epoch(train) [143][150/442] lr: 5.000000e-04 eta: 2:55:37 time: 0.353436 data_time: 0.031707 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.778351 2023/08/09 17:01:42 - mmengine - INFO - Epoch(train) [143][160/442] lr: 5.000000e-04 eta: 2:55:34 time: 0.353182 data_time: 0.031183 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.780716 2023/08/09 17:01:45 - mmengine - INFO - Epoch(train) [143][170/442] lr: 5.000000e-04 eta: 2:55:31 time: 0.357306 data_time: 0.031442 memory: 4565 loss: 0.000915 loss_kpt: 0.000915 acc_pose: 0.827358 2023/08/09 17:01:49 - mmengine - INFO - Epoch(train) [143][180/442] lr: 5.000000e-04 eta: 2:55:27 time: 0.357830 data_time: 0.031606 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.856739 2023/08/09 17:01:52 - mmengine - INFO - Epoch(train) [143][190/442] lr: 5.000000e-04 eta: 2:55:23 time: 0.357590 data_time: 0.031623 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.835069 2023/08/09 17:01:56 - mmengine - INFO - Epoch(train) [143][200/442] lr: 5.000000e-04 eta: 2:55:20 time: 0.356954 data_time: 0.031263 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.814943 2023/08/09 17:02:00 - mmengine - INFO - Epoch(train) [143][210/442] lr: 5.000000e-04 eta: 2:55:17 time: 0.357963 data_time: 0.031187 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.777032 2023/08/09 17:02:03 - mmengine - INFO - Epoch(train) [143][220/442] lr: 5.000000e-04 eta: 2:55:13 time: 0.356477 data_time: 0.031359 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.878999 2023/08/09 17:02:07 - mmengine - INFO - Epoch(train) [143][230/442] lr: 5.000000e-04 eta: 2:55:10 time: 0.359172 data_time: 0.031091 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.857517 2023/08/09 17:02:09 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:02:11 - mmengine - INFO - Epoch(train) [143][240/442] lr: 5.000000e-04 eta: 2:55:07 time: 0.360831 data_time: 0.031130 memory: 4565 loss: 0.000940 loss_kpt: 0.000940 acc_pose: 0.751127 2023/08/09 17:02:14 - mmengine - INFO - Epoch(train) [143][250/442] lr: 5.000000e-04 eta: 2:55:03 time: 0.360838 data_time: 0.031188 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.862809 2023/08/09 17:02:18 - mmengine - INFO - Epoch(train) [143][260/442] lr: 5.000000e-04 eta: 2:55:00 time: 0.357582 data_time: 0.030842 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.885289 2023/08/09 17:02:21 - mmengine - INFO - Epoch(train) [143][270/442] lr: 5.000000e-04 eta: 2:54:56 time: 0.354722 data_time: 0.030394 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.852368 2023/08/09 17:02:25 - mmengine - INFO - Epoch(train) [143][280/442] lr: 5.000000e-04 eta: 2:54:53 time: 0.354850 data_time: 0.033844 memory: 4565 loss: 0.000915 loss_kpt: 0.000915 acc_pose: 0.827977 2023/08/09 17:02:28 - mmengine - INFO - Epoch(train) [143][290/442] lr: 5.000000e-04 eta: 2:54:49 time: 0.353412 data_time: 0.033622 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.857808 2023/08/09 17:02:32 - mmengine - INFO - Epoch(train) [143][300/442] lr: 5.000000e-04 eta: 2:54:46 time: 0.355849 data_time: 0.034253 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.866214 2023/08/09 17:02:35 - mmengine - INFO - Epoch(train) [143][310/442] lr: 5.000000e-04 eta: 2:54:42 time: 0.355809 data_time: 0.034246 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.846346 2023/08/09 17:02:39 - mmengine - INFO - Epoch(train) [143][320/442] lr: 5.000000e-04 eta: 2:54:39 time: 0.355957 data_time: 0.034206 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.808854 2023/08/09 17:02:42 - mmengine - INFO - Epoch(train) [143][330/442] lr: 5.000000e-04 eta: 2:54:35 time: 0.352779 data_time: 0.030736 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.854938 2023/08/09 17:02:46 - mmengine - INFO - Epoch(train) [143][340/442] lr: 5.000000e-04 eta: 2:54:32 time: 0.352426 data_time: 0.030763 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.832574 2023/08/09 17:02:49 - mmengine - INFO - Epoch(train) [143][350/442] lr: 5.000000e-04 eta: 2:54:28 time: 0.351352 data_time: 0.030312 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.808654 2023/08/09 17:02:53 - mmengine - INFO - Epoch(train) [143][360/442] lr: 5.000000e-04 eta: 2:54:25 time: 0.352629 data_time: 0.030538 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.863884 2023/08/09 17:02:57 - mmengine - INFO - Epoch(train) [143][370/442] lr: 5.000000e-04 eta: 2:54:22 time: 0.357860 data_time: 0.030986 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.855239 2023/08/09 17:03:00 - mmengine - INFO - Epoch(train) [143][380/442] lr: 5.000000e-04 eta: 2:54:18 time: 0.357368 data_time: 0.030927 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.825788 2023/08/09 17:03:04 - mmengine - INFO - Epoch(train) [143][390/442] lr: 5.000000e-04 eta: 2:54:15 time: 0.357616 data_time: 0.030962 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.850788 2023/08/09 17:03:07 - mmengine - INFO - Epoch(train) [143][400/442] lr: 5.000000e-04 eta: 2:54:11 time: 0.355864 data_time: 0.030789 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.821454 2023/08/09 17:03:11 - mmengine - INFO - Epoch(train) [143][410/442] lr: 5.000000e-04 eta: 2:54:07 time: 0.355693 data_time: 0.030759 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.822221 2023/08/09 17:03:14 - mmengine - INFO - Epoch(train) [143][420/442] lr: 5.000000e-04 eta: 2:54:04 time: 0.353298 data_time: 0.031052 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.800441 2023/08/09 17:03:18 - mmengine - INFO - Epoch(train) [143][430/442] lr: 5.000000e-04 eta: 2:54:01 time: 0.354933 data_time: 0.031246 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.752099 2023/08/09 17:03:21 - mmengine - INFO - Epoch(train) [143][440/442] lr: 5.000000e-04 eta: 2:53:57 time: 0.354578 data_time: 0.031148 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.920819 2023/08/09 17:03:22 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:03:26 - mmengine - INFO - Epoch(train) [144][ 10/442] lr: 5.000000e-04 eta: 2:53:53 time: 0.356575 data_time: 0.035439 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.791803 2023/08/09 17:03:29 - mmengine - INFO - Epoch(train) [144][ 20/442] lr: 5.000000e-04 eta: 2:53:50 time: 0.355050 data_time: 0.035060 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.810767 2023/08/09 17:03:33 - mmengine - INFO - Epoch(train) [144][ 30/442] lr: 5.000000e-04 eta: 2:53:46 time: 0.357765 data_time: 0.034994 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.796038 2023/08/09 17:03:37 - mmengine - INFO - Epoch(train) [144][ 40/442] lr: 5.000000e-04 eta: 2:53:43 time: 0.359272 data_time: 0.035240 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.768875 2023/08/09 17:03:40 - mmengine - INFO - Epoch(train) [144][ 50/442] lr: 5.000000e-04 eta: 2:53:40 time: 0.364361 data_time: 0.036273 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.889509 2023/08/09 17:03:44 - mmengine - INFO - Epoch(train) [144][ 60/442] lr: 5.000000e-04 eta: 2:53:36 time: 0.361869 data_time: 0.031925 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.862496 2023/08/09 17:03:47 - mmengine - INFO - Epoch(train) [144][ 70/442] lr: 5.000000e-04 eta: 2:53:33 time: 0.361871 data_time: 0.031977 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.774928 2023/08/09 17:03:51 - mmengine - INFO - Epoch(train) [144][ 80/442] lr: 5.000000e-04 eta: 2:53:30 time: 0.361063 data_time: 0.032158 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.942087 2023/08/09 17:03:55 - mmengine - INFO - Epoch(train) [144][ 90/442] lr: 5.000000e-04 eta: 2:53:26 time: 0.360074 data_time: 0.032208 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.804128 2023/08/09 17:03:58 - mmengine - INFO - Epoch(train) [144][100/442] lr: 5.000000e-04 eta: 2:53:23 time: 0.359514 data_time: 0.032284 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.874060 2023/08/09 17:04:02 - mmengine - INFO - Epoch(train) [144][110/442] lr: 5.000000e-04 eta: 2:53:20 time: 0.360192 data_time: 0.031981 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.789715 2023/08/09 17:04:06 - mmengine - INFO - Epoch(train) [144][120/442] lr: 5.000000e-04 eta: 2:53:16 time: 0.362424 data_time: 0.032315 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.824752 2023/08/09 17:04:09 - mmengine - INFO - Epoch(train) [144][130/442] lr: 5.000000e-04 eta: 2:53:13 time: 0.358981 data_time: 0.032182 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.850772 2023/08/09 17:04:12 - mmengine - INFO - Epoch(train) [144][140/442] lr: 5.000000e-04 eta: 2:53:09 time: 0.356676 data_time: 0.031674 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.835828 2023/08/09 17:04:16 - mmengine - INFO - Epoch(train) [144][150/442] lr: 5.000000e-04 eta: 2:53:05 time: 0.353997 data_time: 0.030934 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.846779 2023/08/09 17:04:20 - mmengine - INFO - Epoch(train) [144][160/442] lr: 5.000000e-04 eta: 2:53:02 time: 0.352770 data_time: 0.031002 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.851040 2023/08/09 17:04:23 - mmengine - INFO - Epoch(train) [144][170/442] lr: 5.000000e-04 eta: 2:52:59 time: 0.351485 data_time: 0.030564 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.809722 2023/08/09 17:04:27 - mmengine - INFO - Epoch(train) [144][180/442] lr: 5.000000e-04 eta: 2:52:55 time: 0.357419 data_time: 0.030680 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.797890 2023/08/09 17:04:30 - mmengine - INFO - Epoch(train) [144][190/442] lr: 5.000000e-04 eta: 2:52:52 time: 0.358124 data_time: 0.030706 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.802601 2023/08/09 17:04:34 - mmengine - INFO - Epoch(train) [144][200/442] lr: 5.000000e-04 eta: 2:52:48 time: 0.358359 data_time: 0.030731 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.784869 2023/08/09 17:04:37 - mmengine - INFO - Epoch(train) [144][210/442] lr: 5.000000e-04 eta: 2:52:45 time: 0.358263 data_time: 0.030673 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.825908 2023/08/09 17:04:41 - mmengine - INFO - Epoch(train) [144][220/442] lr: 5.000000e-04 eta: 2:52:42 time: 0.360767 data_time: 0.034042 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.795472 2023/08/09 17:04:45 - mmengine - INFO - Epoch(train) [144][230/442] lr: 5.000000e-04 eta: 2:52:39 time: 0.359506 data_time: 0.034567 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.888580 2023/08/09 17:04:49 - mmengine - INFO - Epoch(train) [144][240/442] lr: 5.000000e-04 eta: 2:52:36 time: 0.367163 data_time: 0.035243 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.826257 2023/08/09 17:04:52 - mmengine - INFO - Epoch(train) [144][250/442] lr: 5.000000e-04 eta: 2:52:32 time: 0.367743 data_time: 0.036103 memory: 4565 loss: 0.000897 loss_kpt: 0.000897 acc_pose: 0.812384 2023/08/09 17:04:56 - mmengine - INFO - Epoch(train) [144][260/442] lr: 5.000000e-04 eta: 2:52:29 time: 0.367744 data_time: 0.036843 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.809101 2023/08/09 17:04:59 - mmengine - INFO - Epoch(train) [144][270/442] lr: 5.000000e-04 eta: 2:52:25 time: 0.363746 data_time: 0.033357 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.856560 2023/08/09 17:05:03 - mmengine - INFO - Epoch(train) [144][280/442] lr: 5.000000e-04 eta: 2:52:22 time: 0.360262 data_time: 0.033189 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.857909 2023/08/09 17:05:06 - mmengine - INFO - Epoch(train) [144][290/442] lr: 5.000000e-04 eta: 2:52:18 time: 0.352794 data_time: 0.032617 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.842551 2023/08/09 17:05:10 - mmengine - INFO - Epoch(train) [144][300/442] lr: 5.000000e-04 eta: 2:52:15 time: 0.351945 data_time: 0.031774 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.744144 2023/08/09 17:05:14 - mmengine - INFO - Epoch(train) [144][310/442] lr: 5.000000e-04 eta: 2:52:11 time: 0.352965 data_time: 0.031300 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.812919 2023/08/09 17:05:17 - mmengine - INFO - Epoch(train) [144][320/442] lr: 5.000000e-04 eta: 2:52:08 time: 0.352674 data_time: 0.031631 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.721589 2023/08/09 17:05:20 - mmengine - INFO - Epoch(train) [144][330/442] lr: 5.000000e-04 eta: 2:52:04 time: 0.351523 data_time: 0.030976 memory: 4565 loss: 0.000897 loss_kpt: 0.000897 acc_pose: 0.866979 2023/08/09 17:05:24 - mmengine - INFO - Epoch(train) [144][340/442] lr: 5.000000e-04 eta: 2:52:01 time: 0.354311 data_time: 0.030841 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.811893 2023/08/09 17:05:28 - mmengine - INFO - Epoch(train) [144][350/442] lr: 5.000000e-04 eta: 2:51:57 time: 0.354041 data_time: 0.030841 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.899446 2023/08/09 17:05:31 - mmengine - INFO - Epoch(train) [144][360/442] lr: 5.000000e-04 eta: 2:51:54 time: 0.352919 data_time: 0.030576 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.832591 2023/08/09 17:05:35 - mmengine - INFO - Epoch(train) [144][370/442] lr: 5.000000e-04 eta: 2:51:50 time: 0.354266 data_time: 0.030523 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.841474 2023/08/09 17:05:38 - mmengine - INFO - Epoch(train) [144][380/442] lr: 5.000000e-04 eta: 2:51:47 time: 0.356209 data_time: 0.030988 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.829658 2023/08/09 17:05:42 - mmengine - INFO - Epoch(train) [144][390/442] lr: 5.000000e-04 eta: 2:51:43 time: 0.352663 data_time: 0.031073 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.858386 2023/08/09 17:05:45 - mmengine - INFO - Epoch(train) [144][400/442] lr: 5.000000e-04 eta: 2:51:40 time: 0.353092 data_time: 0.031092 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.760755 2023/08/09 17:05:49 - mmengine - INFO - Epoch(train) [144][410/442] lr: 5.000000e-04 eta: 2:51:36 time: 0.352131 data_time: 0.031018 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.804150 2023/08/09 17:05:52 - mmengine - INFO - Epoch(train) [144][420/442] lr: 5.000000e-04 eta: 2:51:33 time: 0.353997 data_time: 0.030866 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.877599 2023/08/09 17:05:56 - mmengine - INFO - Epoch(train) [144][430/442] lr: 5.000000e-04 eta: 2:51:29 time: 0.355072 data_time: 0.030577 memory: 4565 loss: 0.000957 loss_kpt: 0.000957 acc_pose: 0.832844 2023/08/09 17:06:00 - mmengine - INFO - Epoch(train) [144][440/442] lr: 5.000000e-04 eta: 2:51:26 time: 0.356524 data_time: 0.031171 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.855642 2023/08/09 17:06:00 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:06:04 - mmengine - INFO - Epoch(train) [145][ 10/442] lr: 5.000000e-04 eta: 2:51:22 time: 0.359395 data_time: 0.035356 memory: 4565 loss: 0.000948 loss_kpt: 0.000948 acc_pose: 0.838429 2023/08/09 17:06:08 - mmengine - INFO - Epoch(train) [145][ 20/442] lr: 5.000000e-04 eta: 2:51:18 time: 0.359576 data_time: 0.035289 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.861497 2023/08/09 17:06:11 - mmengine - INFO - Epoch(train) [145][ 30/442] lr: 5.000000e-04 eta: 2:51:15 time: 0.355833 data_time: 0.034909 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.830155 2023/08/09 17:06:15 - mmengine - INFO - Epoch(train) [145][ 40/442] lr: 5.000000e-04 eta: 2:51:11 time: 0.354395 data_time: 0.034976 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.840383 2023/08/09 17:06:18 - mmengine - INFO - Epoch(train) [145][ 50/442] lr: 5.000000e-04 eta: 2:51:08 time: 0.355573 data_time: 0.034755 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.847825 2023/08/09 17:06:22 - mmengine - INFO - Epoch(train) [145][ 60/442] lr: 5.000000e-04 eta: 2:51:04 time: 0.354543 data_time: 0.030722 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.858265 2023/08/09 17:06:25 - mmengine - INFO - Epoch(train) [145][ 70/442] lr: 5.000000e-04 eta: 2:51:01 time: 0.356209 data_time: 0.030731 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.815118 2023/08/09 17:06:29 - mmengine - INFO - Epoch(train) [145][ 80/442] lr: 5.000000e-04 eta: 2:50:57 time: 0.354963 data_time: 0.030943 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.819213 2023/08/09 17:06:32 - mmengine - INFO - Epoch(train) [145][ 90/442] lr: 5.000000e-04 eta: 2:50:54 time: 0.354466 data_time: 0.030692 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.886004 2023/08/09 17:06:36 - mmengine - INFO - Epoch(train) [145][100/442] lr: 5.000000e-04 eta: 2:50:50 time: 0.352913 data_time: 0.030470 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.859505 2023/08/09 17:06:39 - mmengine - INFO - Epoch(train) [145][110/442] lr: 5.000000e-04 eta: 2:50:46 time: 0.349296 data_time: 0.030061 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.922531 2023/08/09 17:06:43 - mmengine - INFO - Epoch(train) [145][120/442] lr: 5.000000e-04 eta: 2:50:43 time: 0.348528 data_time: 0.030309 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.829740 2023/08/09 17:06:46 - mmengine - INFO - Epoch(train) [145][130/442] lr: 5.000000e-04 eta: 2:50:39 time: 0.349974 data_time: 0.030133 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.815637 2023/08/09 17:06:50 - mmengine - INFO - Epoch(train) [145][140/442] lr: 5.000000e-04 eta: 2:50:36 time: 0.349955 data_time: 0.030490 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.838452 2023/08/09 17:06:53 - mmengine - INFO - Epoch(train) [145][150/442] lr: 5.000000e-04 eta: 2:50:32 time: 0.352174 data_time: 0.033564 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.805486 2023/08/09 17:06:57 - mmengine - INFO - Epoch(train) [145][160/442] lr: 5.000000e-04 eta: 2:50:29 time: 0.351335 data_time: 0.033577 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.828435 2023/08/09 17:07:00 - mmengine - INFO - Epoch(train) [145][170/442] lr: 5.000000e-04 eta: 2:50:25 time: 0.349382 data_time: 0.033293 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.841978 2023/08/09 17:07:04 - mmengine - INFO - Epoch(train) [145][180/442] lr: 5.000000e-04 eta: 2:50:21 time: 0.348947 data_time: 0.033595 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.840391 2023/08/09 17:07:07 - mmengine - INFO - Epoch(train) [145][190/442] lr: 5.000000e-04 eta: 2:50:18 time: 0.349927 data_time: 0.033449 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.861613 2023/08/09 17:07:11 - mmengine - INFO - Epoch(train) [145][200/442] lr: 5.000000e-04 eta: 2:50:14 time: 0.348395 data_time: 0.030608 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.899411 2023/08/09 17:07:14 - mmengine - INFO - Epoch(train) [145][210/442] lr: 5.000000e-04 eta: 2:50:11 time: 0.350562 data_time: 0.030562 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.805520 2023/08/09 17:07:18 - mmengine - INFO - Epoch(train) [145][220/442] lr: 5.000000e-04 eta: 2:50:08 time: 0.359604 data_time: 0.030937 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.837459 2023/08/09 17:07:22 - mmengine - INFO - Epoch(train) [145][230/442] lr: 5.000000e-04 eta: 2:50:05 time: 0.366986 data_time: 0.030967 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.859579 2023/08/09 17:07:26 - mmengine - INFO - Epoch(train) [145][240/442] lr: 5.000000e-04 eta: 2:50:02 time: 0.373473 data_time: 0.031205 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.789063 2023/08/09 17:07:30 - mmengine - INFO - Epoch(train) [145][250/442] lr: 5.000000e-04 eta: 2:49:59 time: 0.379567 data_time: 0.031665 memory: 4565 loss: 0.000952 loss_kpt: 0.000952 acc_pose: 0.849813 2023/08/09 17:07:33 - mmengine - INFO - Epoch(train) [145][260/442] lr: 5.000000e-04 eta: 2:49:56 time: 0.378426 data_time: 0.031725 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.891231 2023/08/09 17:07:37 - mmengine - INFO - Epoch(train) [145][270/442] lr: 5.000000e-04 eta: 2:49:52 time: 0.371077 data_time: 0.032019 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.815548 2023/08/09 17:07:40 - mmengine - INFO - Epoch(train) [145][280/442] lr: 5.000000e-04 eta: 2:49:48 time: 0.363198 data_time: 0.031720 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.781520 2023/08/09 17:07:44 - mmengine - INFO - Epoch(train) [145][290/442] lr: 5.000000e-04 eta: 2:49:45 time: 0.355085 data_time: 0.031271 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.896233 2023/08/09 17:07:47 - mmengine - INFO - Epoch(train) [145][300/442] lr: 5.000000e-04 eta: 2:49:41 time: 0.347364 data_time: 0.030464 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.887059 2023/08/09 17:07:51 - mmengine - INFO - Epoch(train) [145][310/442] lr: 5.000000e-04 eta: 2:49:37 time: 0.346395 data_time: 0.030400 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.854897 2023/08/09 17:07:54 - mmengine - INFO - Epoch(train) [145][320/442] lr: 5.000000e-04 eta: 2:49:34 time: 0.350242 data_time: 0.033031 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.836733 2023/08/09 17:07:58 - mmengine - INFO - Epoch(train) [145][330/442] lr: 5.000000e-04 eta: 2:49:31 time: 0.353056 data_time: 0.033274 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.826149 2023/08/09 17:08:01 - mmengine - INFO - Epoch(train) [145][340/442] lr: 5.000000e-04 eta: 2:49:27 time: 0.353845 data_time: 0.033409 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.864117 2023/08/09 17:08:05 - mmengine - INFO - Epoch(train) [145][350/442] lr: 5.000000e-04 eta: 2:49:24 time: 0.354864 data_time: 0.033330 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.881497 2023/08/09 17:08:06 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:08:08 - mmengine - INFO - Epoch(train) [145][360/442] lr: 5.000000e-04 eta: 2:49:20 time: 0.355149 data_time: 0.033266 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.878234 2023/08/09 17:08:12 - mmengine - INFO - Epoch(train) [145][370/442] lr: 5.000000e-04 eta: 2:49:16 time: 0.350579 data_time: 0.029813 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.813620 2023/08/09 17:08:15 - mmengine - INFO - Epoch(train) [145][380/442] lr: 5.000000e-04 eta: 2:49:13 time: 0.348829 data_time: 0.029666 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.820914 2023/08/09 17:08:19 - mmengine - INFO - Epoch(train) [145][390/442] lr: 5.000000e-04 eta: 2:49:09 time: 0.349786 data_time: 0.029698 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.812460 2023/08/09 17:08:23 - mmengine - INFO - Epoch(train) [145][400/442] lr: 5.000000e-04 eta: 2:49:06 time: 0.351927 data_time: 0.030423 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.828792 2023/08/09 17:08:26 - mmengine - INFO - Epoch(train) [145][410/442] lr: 5.000000e-04 eta: 2:49:03 time: 0.354061 data_time: 0.031480 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.864529 2023/08/09 17:08:30 - mmengine - INFO - Epoch(train) [145][420/442] lr: 5.000000e-04 eta: 2:48:59 time: 0.355270 data_time: 0.031837 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.855013 2023/08/09 17:08:33 - mmengine - INFO - Epoch(train) [145][430/442] lr: 5.000000e-04 eta: 2:48:56 time: 0.357461 data_time: 0.031818 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.746446 2023/08/09 17:08:37 - mmengine - INFO - Epoch(train) [145][440/442] lr: 5.000000e-04 eta: 2:48:52 time: 0.360065 data_time: 0.035706 memory: 4565 loss: 0.000940 loss_kpt: 0.000940 acc_pose: 0.878000 2023/08/09 17:08:38 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:08:41 - mmengine - INFO - Epoch(train) [146][ 10/442] lr: 5.000000e-04 eta: 2:48:49 time: 0.361881 data_time: 0.038637 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.874973 2023/08/09 17:08:45 - mmengine - INFO - Epoch(train) [146][ 20/442] lr: 5.000000e-04 eta: 2:48:45 time: 0.360780 data_time: 0.037949 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.867061 2023/08/09 17:08:48 - mmengine - INFO - Epoch(train) [146][ 30/442] lr: 5.000000e-04 eta: 2:48:41 time: 0.356547 data_time: 0.038147 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.862431 2023/08/09 17:08:52 - mmengine - INFO - Epoch(train) [146][ 40/442] lr: 5.000000e-04 eta: 2:48:38 time: 0.352752 data_time: 0.034761 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.811961 2023/08/09 17:08:55 - mmengine - INFO - Epoch(train) [146][ 50/442] lr: 5.000000e-04 eta: 2:48:34 time: 0.356785 data_time: 0.035342 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.845801 2023/08/09 17:08:59 - mmengine - INFO - Epoch(train) [146][ 60/442] lr: 5.000000e-04 eta: 2:48:31 time: 0.350920 data_time: 0.031656 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.867953 2023/08/09 17:09:02 - mmengine - INFO - Epoch(train) [146][ 70/442] lr: 5.000000e-04 eta: 2:48:27 time: 0.350826 data_time: 0.031734 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.836570 2023/08/09 17:09:06 - mmengine - INFO - Epoch(train) [146][ 80/442] lr: 5.000000e-04 eta: 2:48:24 time: 0.352043 data_time: 0.031728 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.882595 2023/08/09 17:09:09 - mmengine - INFO - Epoch(train) [146][ 90/442] lr: 5.000000e-04 eta: 2:48:20 time: 0.353808 data_time: 0.031763 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.812141 2023/08/09 17:09:13 - mmengine - INFO - Epoch(train) [146][100/442] lr: 5.000000e-04 eta: 2:48:17 time: 0.350110 data_time: 0.031026 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.816806 2023/08/09 17:09:16 - mmengine - INFO - Epoch(train) [146][110/442] lr: 5.000000e-04 eta: 2:48:13 time: 0.349640 data_time: 0.030722 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.813932 2023/08/09 17:09:20 - mmengine - INFO - Epoch(train) [146][120/442] lr: 5.000000e-04 eta: 2:48:09 time: 0.348670 data_time: 0.030538 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.824927 2023/08/09 17:09:23 - mmengine - INFO - Epoch(train) [146][130/442] lr: 5.000000e-04 eta: 2:48:06 time: 0.350422 data_time: 0.030327 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.822703 2023/08/09 17:09:27 - mmengine - INFO - Epoch(train) [146][140/442] lr: 5.000000e-04 eta: 2:48:02 time: 0.349996 data_time: 0.030394 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.850863 2023/08/09 17:09:30 - mmengine - INFO - Epoch(train) [146][150/442] lr: 5.000000e-04 eta: 2:47:59 time: 0.350261 data_time: 0.030520 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.836508 2023/08/09 17:09:34 - mmengine - INFO - Epoch(train) [146][160/442] lr: 5.000000e-04 eta: 2:47:55 time: 0.351515 data_time: 0.030722 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.862051 2023/08/09 17:09:37 - mmengine - INFO - Epoch(train) [146][170/442] lr: 5.000000e-04 eta: 2:47:51 time: 0.351929 data_time: 0.030685 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.893796 2023/08/09 17:09:41 - mmengine - INFO - Epoch(train) [146][180/442] lr: 5.000000e-04 eta: 2:47:48 time: 0.348779 data_time: 0.030611 memory: 4565 loss: 0.000940 loss_kpt: 0.000940 acc_pose: 0.868599 2023/08/09 17:09:44 - mmengine - INFO - Epoch(train) [146][190/442] lr: 5.000000e-04 eta: 2:47:44 time: 0.347938 data_time: 0.030506 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.885462 2023/08/09 17:09:48 - mmengine - INFO - Epoch(train) [146][200/442] lr: 5.000000e-04 eta: 2:47:41 time: 0.348283 data_time: 0.030445 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.862803 2023/08/09 17:09:52 - mmengine - INFO - Epoch(train) [146][210/442] lr: 5.000000e-04 eta: 2:47:37 time: 0.351021 data_time: 0.030938 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.799107 2023/08/09 17:09:55 - mmengine - INFO - Epoch(train) [146][220/442] lr: 5.000000e-04 eta: 2:47:34 time: 0.352878 data_time: 0.031564 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.811125 2023/08/09 17:09:59 - mmengine - INFO - Epoch(train) [146][230/442] lr: 5.000000e-04 eta: 2:47:30 time: 0.354618 data_time: 0.032463 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.860164 2023/08/09 17:10:02 - mmengine - INFO - Epoch(train) [146][240/442] lr: 5.000000e-04 eta: 2:47:27 time: 0.357970 data_time: 0.032601 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.829481 2023/08/09 17:10:06 - mmengine - INFO - Epoch(train) [146][250/442] lr: 5.000000e-04 eta: 2:47:23 time: 0.357692 data_time: 0.033089 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.847322 2023/08/09 17:10:09 - mmengine - INFO - Epoch(train) [146][260/442] lr: 5.000000e-04 eta: 2:47:20 time: 0.354478 data_time: 0.032495 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.844604 2023/08/09 17:10:13 - mmengine - INFO - Epoch(train) [146][270/442] lr: 5.000000e-04 eta: 2:47:17 time: 0.355474 data_time: 0.031935 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.845643 2023/08/09 17:10:17 - mmengine - INFO - Epoch(train) [146][280/442] lr: 5.000000e-04 eta: 2:47:13 time: 0.359758 data_time: 0.031477 memory: 4565 loss: 0.000897 loss_kpt: 0.000897 acc_pose: 0.820575 2023/08/09 17:10:20 - mmengine - INFO - Epoch(train) [146][290/442] lr: 5.000000e-04 eta: 2:47:10 time: 0.361963 data_time: 0.031689 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.846814 2023/08/09 17:10:24 - mmengine - INFO - Epoch(train) [146][300/442] lr: 5.000000e-04 eta: 2:47:07 time: 0.361350 data_time: 0.031123 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.888788 2023/08/09 17:10:27 - mmengine - INFO - Epoch(train) [146][310/442] lr: 5.000000e-04 eta: 2:47:03 time: 0.360508 data_time: 0.031016 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.893694 2023/08/09 17:10:31 - mmengine - INFO - Epoch(train) [146][320/442] lr: 5.000000e-04 eta: 2:46:59 time: 0.357054 data_time: 0.031121 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.878655 2023/08/09 17:10:34 - mmengine - INFO - Epoch(train) [146][330/442] lr: 5.000000e-04 eta: 2:46:56 time: 0.353872 data_time: 0.031352 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.820925 2023/08/09 17:10:38 - mmengine - INFO - Epoch(train) [146][340/442] lr: 5.000000e-04 eta: 2:46:53 time: 0.354231 data_time: 0.031731 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.844466 2023/08/09 17:10:42 - mmengine - INFO - Epoch(train) [146][350/442] lr: 5.000000e-04 eta: 2:46:49 time: 0.356631 data_time: 0.032299 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.802257 2023/08/09 17:10:45 - mmengine - INFO - Epoch(train) [146][360/442] lr: 5.000000e-04 eta: 2:46:46 time: 0.359472 data_time: 0.033290 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.853040 2023/08/09 17:10:49 - mmengine - INFO - Epoch(train) [146][370/442] lr: 5.000000e-04 eta: 2:46:42 time: 0.360452 data_time: 0.033155 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.831822 2023/08/09 17:10:52 - mmengine - INFO - Epoch(train) [146][380/442] lr: 5.000000e-04 eta: 2:46:39 time: 0.358735 data_time: 0.032663 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.842502 2023/08/09 17:10:56 - mmengine - INFO - Epoch(train) [146][390/442] lr: 5.000000e-04 eta: 2:46:35 time: 0.354536 data_time: 0.032039 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.809545 2023/08/09 17:10:59 - mmengine - INFO - Epoch(train) [146][400/442] lr: 5.000000e-04 eta: 2:46:32 time: 0.353027 data_time: 0.031449 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.804613 2023/08/09 17:11:03 - mmengine - INFO - Epoch(train) [146][410/442] lr: 5.000000e-04 eta: 2:46:29 time: 0.357518 data_time: 0.030770 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.836732 2023/08/09 17:11:07 - mmengine - INFO - Epoch(train) [146][420/442] lr: 5.000000e-04 eta: 2:46:25 time: 0.359319 data_time: 0.031084 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.841668 2023/08/09 17:11:10 - mmengine - INFO - Epoch(train) [146][430/442] lr: 5.000000e-04 eta: 2:46:22 time: 0.363630 data_time: 0.035179 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.772250 2023/08/09 17:11:14 - mmengine - INFO - Epoch(train) [146][440/442] lr: 5.000000e-04 eta: 2:46:19 time: 0.363592 data_time: 0.036203 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.790351 2023/08/09 17:11:15 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:11:18 - mmengine - INFO - Epoch(train) [147][ 10/442] lr: 5.000000e-04 eta: 2:46:14 time: 0.364491 data_time: 0.040512 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.844312 2023/08/09 17:11:22 - mmengine - INFO - Epoch(train) [147][ 20/442] lr: 5.000000e-04 eta: 2:46:11 time: 0.357472 data_time: 0.041397 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.860325 2023/08/09 17:11:25 - mmengine - INFO - Epoch(train) [147][ 30/442] lr: 5.000000e-04 eta: 2:46:07 time: 0.355529 data_time: 0.041121 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.860833 2023/08/09 17:11:29 - mmengine - INFO - Epoch(train) [147][ 40/442] lr: 5.000000e-04 eta: 2:46:04 time: 0.350062 data_time: 0.037131 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.727375 2023/08/09 17:11:32 - mmengine - INFO - Epoch(train) [147][ 50/442] lr: 5.000000e-04 eta: 2:46:00 time: 0.349312 data_time: 0.036631 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.842574 2023/08/09 17:11:36 - mmengine - INFO - Epoch(train) [147][ 60/442] lr: 5.000000e-04 eta: 2:45:56 time: 0.344619 data_time: 0.031835 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.846338 2023/08/09 17:11:39 - mmengine - INFO - Epoch(train) [147][ 70/442] lr: 5.000000e-04 eta: 2:45:52 time: 0.343269 data_time: 0.030801 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.891869 2023/08/09 17:11:42 - mmengine - INFO - Epoch(train) [147][ 80/442] lr: 5.000000e-04 eta: 2:45:49 time: 0.341129 data_time: 0.030615 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.811316 2023/08/09 17:11:46 - mmengine - INFO - Epoch(train) [147][ 90/442] lr: 5.000000e-04 eta: 2:45:45 time: 0.340513 data_time: 0.030577 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.847147 2023/08/09 17:11:49 - mmengine - INFO - Epoch(train) [147][100/442] lr: 5.000000e-04 eta: 2:45:41 time: 0.341180 data_time: 0.030596 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.746574 2023/08/09 17:11:53 - mmengine - INFO - Epoch(train) [147][110/442] lr: 5.000000e-04 eta: 2:45:38 time: 0.343666 data_time: 0.030809 memory: 4565 loss: 0.000943 loss_kpt: 0.000943 acc_pose: 0.863825 2023/08/09 17:11:56 - mmengine - INFO - Epoch(train) [147][120/442] lr: 5.000000e-04 eta: 2:45:34 time: 0.346497 data_time: 0.031238 memory: 4565 loss: 0.000940 loss_kpt: 0.000940 acc_pose: 0.878466 2023/08/09 17:12:00 - mmengine - INFO - Epoch(train) [147][130/442] lr: 5.000000e-04 eta: 2:45:31 time: 0.349921 data_time: 0.031167 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.856444 2023/08/09 17:12:03 - mmengine - INFO - Epoch(train) [147][140/442] lr: 5.000000e-04 eta: 2:45:27 time: 0.351374 data_time: 0.031130 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.826106 2023/08/09 17:12:07 - mmengine - INFO - Epoch(train) [147][150/442] lr: 5.000000e-04 eta: 2:45:23 time: 0.348920 data_time: 0.031040 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.860098 2023/08/09 17:12:10 - mmengine - INFO - Epoch(train) [147][160/442] lr: 5.000000e-04 eta: 2:45:20 time: 0.353819 data_time: 0.031050 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.859477 2023/08/09 17:12:14 - mmengine - INFO - Epoch(train) [147][170/442] lr: 5.000000e-04 eta: 2:45:17 time: 0.353638 data_time: 0.030707 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.803933 2023/08/09 17:12:17 - mmengine - INFO - Epoch(train) [147][180/442] lr: 5.000000e-04 eta: 2:45:13 time: 0.351803 data_time: 0.031032 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.829267 2023/08/09 17:12:21 - mmengine - INFO - Epoch(train) [147][190/442] lr: 5.000000e-04 eta: 2:45:09 time: 0.350463 data_time: 0.031429 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.812717 2023/08/09 17:12:24 - mmengine - INFO - Epoch(train) [147][200/442] lr: 5.000000e-04 eta: 2:45:06 time: 0.351263 data_time: 0.032492 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.883520 2023/08/09 17:12:28 - mmengine - INFO - Epoch(train) [147][210/442] lr: 5.000000e-04 eta: 2:45:02 time: 0.344651 data_time: 0.033065 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.875606 2023/08/09 17:12:31 - mmengine - INFO - Epoch(train) [147][220/442] lr: 5.000000e-04 eta: 2:44:58 time: 0.344020 data_time: 0.033902 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.877069 2023/08/09 17:12:35 - mmengine - INFO - Epoch(train) [147][230/442] lr: 5.000000e-04 eta: 2:44:55 time: 0.346807 data_time: 0.037763 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.875916 2023/08/09 17:12:38 - mmengine - INFO - Epoch(train) [147][240/442] lr: 5.000000e-04 eta: 2:44:51 time: 0.347491 data_time: 0.038143 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.853306 2023/08/09 17:12:42 - mmengine - INFO - Epoch(train) [147][250/442] lr: 5.000000e-04 eta: 2:44:48 time: 0.352177 data_time: 0.037452 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.823466 2023/08/09 17:12:45 - mmengine - INFO - Epoch(train) [147][260/442] lr: 5.000000e-04 eta: 2:44:44 time: 0.351220 data_time: 0.036634 memory: 4565 loss: 0.000928 loss_kpt: 0.000928 acc_pose: 0.838954 2023/08/09 17:12:49 - mmengine - INFO - Epoch(train) [147][270/442] lr: 5.000000e-04 eta: 2:44:40 time: 0.349666 data_time: 0.036053 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.794522 2023/08/09 17:12:52 - mmengine - INFO - Epoch(train) [147][280/442] lr: 5.000000e-04 eta: 2:44:36 time: 0.344582 data_time: 0.031891 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.793480 2023/08/09 17:12:55 - mmengine - INFO - Epoch(train) [147][290/442] lr: 5.000000e-04 eta: 2:44:33 time: 0.344264 data_time: 0.031055 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.798405 2023/08/09 17:12:59 - mmengine - INFO - Epoch(train) [147][300/442] lr: 5.000000e-04 eta: 2:44:29 time: 0.340024 data_time: 0.030698 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.845245 2023/08/09 17:13:02 - mmengine - INFO - Epoch(train) [147][310/442] lr: 5.000000e-04 eta: 2:44:25 time: 0.341148 data_time: 0.030949 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.761700 2023/08/09 17:13:06 - mmengine - INFO - Epoch(train) [147][320/442] lr: 5.000000e-04 eta: 2:44:22 time: 0.346406 data_time: 0.031024 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.841453 2023/08/09 17:13:10 - mmengine - INFO - Epoch(train) [147][330/442] lr: 5.000000e-04 eta: 2:44:19 time: 0.356397 data_time: 0.031221 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.848432 2023/08/09 17:13:14 - mmengine - INFO - Epoch(train) [147][340/442] lr: 5.000000e-04 eta: 2:44:16 time: 0.365421 data_time: 0.031577 memory: 4565 loss: 0.000915 loss_kpt: 0.000915 acc_pose: 0.862045 2023/08/09 17:13:18 - mmengine - INFO - Epoch(train) [147][350/442] lr: 5.000000e-04 eta: 2:44:13 time: 0.373609 data_time: 0.031759 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.828206 2023/08/09 17:13:21 - mmengine - INFO - Epoch(train) [147][360/442] lr: 5.000000e-04 eta: 2:44:10 time: 0.374405 data_time: 0.031806 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.823631 2023/08/09 17:13:25 - mmengine - INFO - Epoch(train) [147][370/442] lr: 5.000000e-04 eta: 2:44:06 time: 0.372881 data_time: 0.031788 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.883873 2023/08/09 17:13:28 - mmengine - INFO - Epoch(train) [147][380/442] lr: 5.000000e-04 eta: 2:44:03 time: 0.365208 data_time: 0.032017 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.841235 2023/08/09 17:13:32 - mmengine - INFO - Epoch(train) [147][390/442] lr: 5.000000e-04 eta: 2:43:59 time: 0.355124 data_time: 0.031949 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.758179 2023/08/09 17:13:35 - mmengine - INFO - Epoch(train) [147][400/442] lr: 5.000000e-04 eta: 2:43:55 time: 0.346377 data_time: 0.031595 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.837850 2023/08/09 17:13:38 - mmengine - INFO - Epoch(train) [147][410/442] lr: 5.000000e-04 eta: 2:43:51 time: 0.344508 data_time: 0.031300 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.791645 2023/08/09 17:13:42 - mmengine - INFO - Epoch(train) [147][420/442] lr: 5.000000e-04 eta: 2:43:48 time: 0.344795 data_time: 0.030846 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.757619 2023/08/09 17:13:45 - mmengine - INFO - Epoch(train) [147][430/442] lr: 5.000000e-04 eta: 2:43:44 time: 0.344283 data_time: 0.030822 memory: 4565 loss: 0.000941 loss_kpt: 0.000941 acc_pose: 0.782286 2023/08/09 17:13:49 - mmengine - INFO - Epoch(train) [147][440/442] lr: 5.000000e-04 eta: 2:43:41 time: 0.344912 data_time: 0.030762 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.766539 2023/08/09 17:13:49 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:13:53 - mmengine - INFO - Epoch(train) [148][ 10/442] lr: 5.000000e-04 eta: 2:43:36 time: 0.349529 data_time: 0.035036 memory: 4565 loss: 0.000938 loss_kpt: 0.000938 acc_pose: 0.913712 2023/08/09 17:13:57 - mmengine - INFO - Epoch(train) [148][ 20/442] lr: 5.000000e-04 eta: 2:43:33 time: 0.350487 data_time: 0.035329 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.827863 2023/08/09 17:13:59 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:14:00 - mmengine - INFO - Epoch(train) [148][ 30/442] lr: 5.000000e-04 eta: 2:43:29 time: 0.345884 data_time: 0.035430 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.835147 2023/08/09 17:14:03 - mmengine - INFO - Epoch(train) [148][ 40/442] lr: 5.000000e-04 eta: 2:43:25 time: 0.344734 data_time: 0.034863 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.851434 2023/08/09 17:14:07 - mmengine - INFO - Epoch(train) [148][ 50/442] lr: 5.000000e-04 eta: 2:43:22 time: 0.346051 data_time: 0.035444 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.897981 2023/08/09 17:14:10 - mmengine - INFO - Epoch(train) [148][ 60/442] lr: 5.000000e-04 eta: 2:43:18 time: 0.344843 data_time: 0.031407 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.856878 2023/08/09 17:14:14 - mmengine - INFO - Epoch(train) [148][ 70/442] lr: 5.000000e-04 eta: 2:43:15 time: 0.347236 data_time: 0.031373 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.841160 2023/08/09 17:14:17 - mmengine - INFO - Epoch(train) [148][ 80/442] lr: 5.000000e-04 eta: 2:43:11 time: 0.346954 data_time: 0.031277 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.846479 2023/08/09 17:14:21 - mmengine - INFO - Epoch(train) [148][ 90/442] lr: 5.000000e-04 eta: 2:43:07 time: 0.347048 data_time: 0.031167 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.744965 2023/08/09 17:14:24 - mmengine - INFO - Epoch(train) [148][100/442] lr: 5.000000e-04 eta: 2:43:03 time: 0.346410 data_time: 0.030970 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.886215 2023/08/09 17:14:27 - mmengine - INFO - Epoch(train) [148][110/442] lr: 5.000000e-04 eta: 2:43:00 time: 0.342174 data_time: 0.030510 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.875319 2023/08/09 17:14:31 - mmengine - INFO - Epoch(train) [148][120/442] lr: 5.000000e-04 eta: 2:42:56 time: 0.342056 data_time: 0.030675 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.865780 2023/08/09 17:14:34 - mmengine - INFO - Epoch(train) [148][130/442] lr: 5.000000e-04 eta: 2:42:52 time: 0.343256 data_time: 0.030750 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.797472 2023/08/09 17:14:38 - mmengine - INFO - Epoch(train) [148][140/442] lr: 5.000000e-04 eta: 2:42:49 time: 0.347511 data_time: 0.031283 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.793369 2023/08/09 17:14:41 - mmengine - INFO - Epoch(train) [148][150/442] lr: 5.000000e-04 eta: 2:42:45 time: 0.346639 data_time: 0.031729 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.873255 2023/08/09 17:14:45 - mmengine - INFO - Epoch(train) [148][160/442] lr: 5.000000e-04 eta: 2:42:42 time: 0.346710 data_time: 0.032308 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.865644 2023/08/09 17:14:49 - mmengine - INFO - Epoch(train) [148][170/442] lr: 5.000000e-04 eta: 2:42:38 time: 0.351739 data_time: 0.032661 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.761463 2023/08/09 17:14:52 - mmengine - INFO - Epoch(train) [148][180/442] lr: 5.000000e-04 eta: 2:42:35 time: 0.356010 data_time: 0.033272 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.869201 2023/08/09 17:14:56 - mmengine - INFO - Epoch(train) [148][190/442] lr: 5.000000e-04 eta: 2:42:31 time: 0.352962 data_time: 0.032819 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.863468 2023/08/09 17:14:59 - mmengine - INFO - Epoch(train) [148][200/442] lr: 5.000000e-04 eta: 2:42:28 time: 0.357565 data_time: 0.032962 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.875188 2023/08/09 17:15:03 - mmengine - INFO - Epoch(train) [148][210/442] lr: 5.000000e-04 eta: 2:42:24 time: 0.357529 data_time: 0.032375 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.872989 2023/08/09 17:15:06 - mmengine - INFO - Epoch(train) [148][220/442] lr: 5.000000e-04 eta: 2:42:21 time: 0.349327 data_time: 0.031626 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.885848 2023/08/09 17:15:09 - mmengine - INFO - Epoch(train) [148][230/442] lr: 5.000000e-04 eta: 2:42:17 time: 0.344233 data_time: 0.030956 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.891904 2023/08/09 17:15:13 - mmengine - INFO - Epoch(train) [148][240/442] lr: 5.000000e-04 eta: 2:42:13 time: 0.343599 data_time: 0.031028 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.837384 2023/08/09 17:15:16 - mmengine - INFO - Epoch(train) [148][250/442] lr: 5.000000e-04 eta: 2:42:09 time: 0.339926 data_time: 0.030610 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.901124 2023/08/09 17:15:20 - mmengine - INFO - Epoch(train) [148][260/442] lr: 5.000000e-04 eta: 2:42:06 time: 0.340665 data_time: 0.030710 memory: 4565 loss: 0.000947 loss_kpt: 0.000947 acc_pose: 0.897386 2023/08/09 17:15:23 - mmengine - INFO - Epoch(train) [148][270/442] lr: 5.000000e-04 eta: 2:42:02 time: 0.342910 data_time: 0.031226 memory: 4565 loss: 0.000954 loss_kpt: 0.000954 acc_pose: 0.850540 2023/08/09 17:15:27 - mmengine - INFO - Epoch(train) [148][280/442] lr: 5.000000e-04 eta: 2:41:58 time: 0.342852 data_time: 0.031329 memory: 4565 loss: 0.000950 loss_kpt: 0.000950 acc_pose: 0.769235 2023/08/09 17:15:30 - mmengine - INFO - Epoch(train) [148][290/442] lr: 5.000000e-04 eta: 2:41:55 time: 0.341907 data_time: 0.031371 memory: 4565 loss: 0.000931 loss_kpt: 0.000931 acc_pose: 0.791279 2023/08/09 17:15:34 - mmengine - INFO - Epoch(train) [148][300/442] lr: 5.000000e-04 eta: 2:41:51 time: 0.345338 data_time: 0.034875 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.822207 2023/08/09 17:15:37 - mmengine - INFO - Epoch(train) [148][310/442] lr: 5.000000e-04 eta: 2:41:47 time: 0.345468 data_time: 0.034922 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.795451 2023/08/09 17:15:40 - mmengine - INFO - Epoch(train) [148][320/442] lr: 5.000000e-04 eta: 2:41:44 time: 0.344456 data_time: 0.034881 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.899292 2023/08/09 17:15:44 - mmengine - INFO - Epoch(train) [148][330/442] lr: 5.000000e-04 eta: 2:41:40 time: 0.347488 data_time: 0.035395 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.838507 2023/08/09 17:15:48 - mmengine - INFO - Epoch(train) [148][340/442] lr: 5.000000e-04 eta: 2:41:37 time: 0.352138 data_time: 0.035694 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.849298 2023/08/09 17:15:51 - mmengine - INFO - Epoch(train) [148][350/442] lr: 5.000000e-04 eta: 2:41:33 time: 0.347767 data_time: 0.032637 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.835043 2023/08/09 17:15:54 - mmengine - INFO - Epoch(train) [148][360/442] lr: 5.000000e-04 eta: 2:41:29 time: 0.346978 data_time: 0.033159 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.821936 2023/08/09 17:15:58 - mmengine - INFO - Epoch(train) [148][370/442] lr: 5.000000e-04 eta: 2:41:26 time: 0.346132 data_time: 0.032824 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.845668 2023/08/09 17:16:01 - mmengine - INFO - Epoch(train) [148][380/442] lr: 5.000000e-04 eta: 2:41:22 time: 0.344467 data_time: 0.032221 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.799453 2023/08/09 17:16:05 - mmengine - INFO - Epoch(train) [148][390/442] lr: 5.000000e-04 eta: 2:41:19 time: 0.346102 data_time: 0.032188 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.885936 2023/08/09 17:16:08 - mmengine - INFO - Epoch(train) [148][400/442] lr: 5.000000e-04 eta: 2:41:15 time: 0.348387 data_time: 0.031582 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.870391 2023/08/09 17:16:12 - mmengine - INFO - Epoch(train) [148][410/442] lr: 5.000000e-04 eta: 2:41:11 time: 0.348192 data_time: 0.030767 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.847795 2023/08/09 17:16:15 - mmengine - INFO - Epoch(train) [148][420/442] lr: 5.000000e-04 eta: 2:41:08 time: 0.348175 data_time: 0.030626 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.849102 2023/08/09 17:16:19 - mmengine - INFO - Epoch(train) [148][430/442] lr: 5.000000e-04 eta: 2:41:04 time: 0.347529 data_time: 0.030493 memory: 4565 loss: 0.000933 loss_kpt: 0.000933 acc_pose: 0.833611 2023/08/09 17:16:22 - mmengine - INFO - Epoch(train) [148][440/442] lr: 5.000000e-04 eta: 2:41:00 time: 0.342326 data_time: 0.030295 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.803128 2023/08/09 17:16:23 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:16:27 - mmengine - INFO - Epoch(train) [149][ 10/442] lr: 5.000000e-04 eta: 2:40:56 time: 0.348110 data_time: 0.034864 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.859604 2023/08/09 17:16:30 - mmengine - INFO - Epoch(train) [149][ 20/442] lr: 5.000000e-04 eta: 2:40:53 time: 0.354498 data_time: 0.035185 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.877846 2023/08/09 17:16:34 - mmengine - INFO - Epoch(train) [149][ 30/442] lr: 5.000000e-04 eta: 2:40:50 time: 0.365290 data_time: 0.035647 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.822772 2023/08/09 17:16:38 - mmengine - INFO - Epoch(train) [149][ 40/442] lr: 5.000000e-04 eta: 2:40:47 time: 0.375529 data_time: 0.036021 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.788759 2023/08/09 17:16:42 - mmengine - INFO - Epoch(train) [149][ 50/442] lr: 5.000000e-04 eta: 2:40:44 time: 0.385330 data_time: 0.036375 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.785259 2023/08/09 17:16:46 - mmengine - INFO - Epoch(train) [149][ 60/442] lr: 5.000000e-04 eta: 2:40:42 time: 0.386281 data_time: 0.031675 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.748924 2023/08/09 17:16:49 - mmengine - INFO - Epoch(train) [149][ 70/442] lr: 5.000000e-04 eta: 2:40:38 time: 0.382978 data_time: 0.031609 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.855322 2023/08/09 17:16:53 - mmengine - INFO - Epoch(train) [149][ 80/442] lr: 5.000000e-04 eta: 2:40:35 time: 0.375288 data_time: 0.031159 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.841213 2023/08/09 17:16:56 - mmengine - INFO - Epoch(train) [149][ 90/442] lr: 5.000000e-04 eta: 2:40:31 time: 0.367175 data_time: 0.031218 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.773010 2023/08/09 17:17:00 - mmengine - INFO - Epoch(train) [149][100/442] lr: 5.000000e-04 eta: 2:40:27 time: 0.359381 data_time: 0.030642 memory: 4565 loss: 0.000932 loss_kpt: 0.000932 acc_pose: 0.870241 2023/08/09 17:17:03 - mmengine - INFO - Epoch(train) [149][110/442] lr: 5.000000e-04 eta: 2:40:24 time: 0.351575 data_time: 0.030372 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.894142 2023/08/09 17:17:07 - mmengine - INFO - Epoch(train) [149][120/442] lr: 5.000000e-04 eta: 2:40:20 time: 0.351584 data_time: 0.030715 memory: 4565 loss: 0.000946 loss_kpt: 0.000946 acc_pose: 0.847586 2023/08/09 17:17:11 - mmengine - INFO - Epoch(train) [149][130/442] lr: 5.000000e-04 eta: 2:40:17 time: 0.352434 data_time: 0.031203 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.860468 2023/08/09 17:17:14 - mmengine - INFO - Epoch(train) [149][140/442] lr: 5.000000e-04 eta: 2:40:13 time: 0.352452 data_time: 0.030914 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.903013 2023/08/09 17:17:18 - mmengine - INFO - Epoch(train) [149][150/442] lr: 5.000000e-04 eta: 2:40:10 time: 0.358701 data_time: 0.031388 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.826036 2023/08/09 17:17:21 - mmengine - INFO - Epoch(train) [149][160/442] lr: 5.000000e-04 eta: 2:40:07 time: 0.358946 data_time: 0.031385 memory: 4565 loss: 0.000919 loss_kpt: 0.000919 acc_pose: 0.869450 2023/08/09 17:17:25 - mmengine - INFO - Epoch(train) [149][170/442] lr: 5.000000e-04 eta: 2:40:03 time: 0.358164 data_time: 0.030997 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.874141 2023/08/09 17:17:28 - mmengine - INFO - Epoch(train) [149][180/442] lr: 5.000000e-04 eta: 2:40:00 time: 0.356027 data_time: 0.030555 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.824496 2023/08/09 17:17:32 - mmengine - INFO - Epoch(train) [149][190/442] lr: 5.000000e-04 eta: 2:39:56 time: 0.359835 data_time: 0.034418 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.846181 2023/08/09 17:17:36 - mmengine - INFO - Epoch(train) [149][200/442] lr: 5.000000e-04 eta: 2:39:53 time: 0.355046 data_time: 0.034244 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.868766 2023/08/09 17:17:39 - mmengine - INFO - Epoch(train) [149][210/442] lr: 5.000000e-04 eta: 2:39:49 time: 0.357206 data_time: 0.034587 memory: 4565 loss: 0.000871 loss_kpt: 0.000871 acc_pose: 0.827930 2023/08/09 17:17:43 - mmengine - INFO - Epoch(train) [149][220/442] lr: 5.000000e-04 eta: 2:39:46 time: 0.356918 data_time: 0.034634 memory: 4565 loss: 0.000870 loss_kpt: 0.000870 acc_pose: 0.832677 2023/08/09 17:17:46 - mmengine - INFO - Epoch(train) [149][230/442] lr: 5.000000e-04 eta: 2:39:42 time: 0.357004 data_time: 0.034577 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.810409 2023/08/09 17:17:50 - mmengine - INFO - Epoch(train) [149][240/442] lr: 5.000000e-04 eta: 2:39:39 time: 0.352537 data_time: 0.030609 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.867245 2023/08/09 17:17:53 - mmengine - INFO - Epoch(train) [149][250/442] lr: 5.000000e-04 eta: 2:39:35 time: 0.351335 data_time: 0.030671 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.832474 2023/08/09 17:17:57 - mmengine - INFO - Epoch(train) [149][260/442] lr: 5.000000e-04 eta: 2:39:32 time: 0.349911 data_time: 0.030426 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.769896 2023/08/09 17:18:00 - mmengine - INFO - Epoch(train) [149][270/442] lr: 5.000000e-04 eta: 2:39:28 time: 0.351183 data_time: 0.030573 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.888265 2023/08/09 17:18:04 - mmengine - INFO - Epoch(train) [149][280/442] lr: 5.000000e-04 eta: 2:39:25 time: 0.355261 data_time: 0.030862 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.802465 2023/08/09 17:18:08 - mmengine - INFO - Epoch(train) [149][290/442] lr: 5.000000e-04 eta: 2:39:21 time: 0.355135 data_time: 0.031066 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.903082 2023/08/09 17:18:11 - mmengine - INFO - Epoch(train) [149][300/442] lr: 5.000000e-04 eta: 2:39:18 time: 0.354820 data_time: 0.030896 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.758358 2023/08/09 17:18:15 - mmengine - INFO - Epoch(train) [149][310/442] lr: 5.000000e-04 eta: 2:39:14 time: 0.354909 data_time: 0.030810 memory: 4565 loss: 0.000870 loss_kpt: 0.000870 acc_pose: 0.789251 2023/08/09 17:18:18 - mmengine - INFO - Epoch(train) [149][320/442] lr: 5.000000e-04 eta: 2:39:11 time: 0.353911 data_time: 0.030452 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.811488 2023/08/09 17:18:22 - mmengine - INFO - Epoch(train) [149][330/442] lr: 5.000000e-04 eta: 2:39:07 time: 0.351291 data_time: 0.030537 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.761124 2023/08/09 17:18:25 - mmengine - INFO - Epoch(train) [149][340/442] lr: 5.000000e-04 eta: 2:39:04 time: 0.353749 data_time: 0.030464 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.766859 2023/08/09 17:18:29 - mmengine - INFO - Epoch(train) [149][350/442] lr: 5.000000e-04 eta: 2:39:00 time: 0.355224 data_time: 0.030454 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.846047 2023/08/09 17:18:32 - mmengine - INFO - Epoch(train) [149][360/442] lr: 5.000000e-04 eta: 2:38:57 time: 0.359114 data_time: 0.033576 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.818017 2023/08/09 17:18:36 - mmengine - INFO - Epoch(train) [149][370/442] lr: 5.000000e-04 eta: 2:38:53 time: 0.358798 data_time: 0.033608 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.861457 2023/08/09 17:18:39 - mmengine - INFO - Epoch(train) [149][380/442] lr: 5.000000e-04 eta: 2:38:50 time: 0.357175 data_time: 0.033154 memory: 4565 loss: 0.000934 loss_kpt: 0.000934 acc_pose: 0.872545 2023/08/09 17:18:43 - mmengine - INFO - Epoch(train) [149][390/442] lr: 5.000000e-04 eta: 2:38:47 time: 0.359229 data_time: 0.033498 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.819807 2023/08/09 17:18:47 - mmengine - INFO - Epoch(train) [149][400/442] lr: 5.000000e-04 eta: 2:38:43 time: 0.358920 data_time: 0.033533 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.823208 2023/08/09 17:18:51 - mmengine - INFO - Epoch(train) [149][410/442] lr: 5.000000e-04 eta: 2:38:40 time: 0.362101 data_time: 0.030954 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.880749 2023/08/09 17:18:54 - mmengine - INFO - Epoch(train) [149][420/442] lr: 5.000000e-04 eta: 2:38:37 time: 0.367920 data_time: 0.031146 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.822834 2023/08/09 17:18:58 - mmengine - INFO - Epoch(train) [149][430/442] lr: 5.000000e-04 eta: 2:38:34 time: 0.375429 data_time: 0.031612 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.856260 2023/08/09 17:19:02 - mmengine - INFO - Epoch(train) [149][440/442] lr: 5.000000e-04 eta: 2:38:31 time: 0.376428 data_time: 0.031383 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.784701 2023/08/09 17:19:03 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:19:06 - mmengine - INFO - Epoch(train) [150][ 10/442] lr: 5.000000e-04 eta: 2:38:27 time: 0.376741 data_time: 0.034802 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.815599 2023/08/09 17:19:10 - mmengine - INFO - Epoch(train) [150][ 20/442] lr: 5.000000e-04 eta: 2:38:23 time: 0.368473 data_time: 0.034693 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.794337 2023/08/09 17:19:13 - mmengine - INFO - Epoch(train) [150][ 30/442] lr: 5.000000e-04 eta: 2:38:19 time: 0.361158 data_time: 0.034464 memory: 4565 loss: 0.000945 loss_kpt: 0.000945 acc_pose: 0.801717 2023/08/09 17:19:17 - mmengine - INFO - Epoch(train) [150][ 40/442] lr: 5.000000e-04 eta: 2:38:16 time: 0.352101 data_time: 0.034197 memory: 4565 loss: 0.000926 loss_kpt: 0.000926 acc_pose: 0.813455 2023/08/09 17:19:20 - mmengine - INFO - Epoch(train) [150][ 50/442] lr: 5.000000e-04 eta: 2:38:12 time: 0.348248 data_time: 0.034103 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.846401 2023/08/09 17:19:23 - mmengine - INFO - Epoch(train) [150][ 60/442] lr: 5.000000e-04 eta: 2:38:08 time: 0.342135 data_time: 0.030213 memory: 4565 loss: 0.000925 loss_kpt: 0.000925 acc_pose: 0.780934 2023/08/09 17:19:27 - mmengine - INFO - Epoch(train) [150][ 70/442] lr: 5.000000e-04 eta: 2:38:05 time: 0.342001 data_time: 0.030071 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.817921 2023/08/09 17:19:31 - mmengine - INFO - Epoch(train) [150][ 80/442] lr: 5.000000e-04 eta: 2:38:01 time: 0.346418 data_time: 0.030222 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.859304 2023/08/09 17:19:34 - mmengine - INFO - Epoch(train) [150][ 90/442] lr: 5.000000e-04 eta: 2:37:58 time: 0.347921 data_time: 0.030630 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.810035 2023/08/09 17:19:38 - mmengine - INFO - Epoch(train) [150][100/442] lr: 5.000000e-04 eta: 2:37:54 time: 0.348960 data_time: 0.030724 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.864864 2023/08/09 17:19:41 - mmengine - INFO - Epoch(train) [150][110/442] lr: 5.000000e-04 eta: 2:37:51 time: 0.353929 data_time: 0.033632 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.874658 2023/08/09 17:19:45 - mmengine - INFO - Epoch(train) [150][120/442] lr: 5.000000e-04 eta: 2:37:47 time: 0.354487 data_time: 0.033526 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.816628 2023/08/09 17:19:48 - mmengine - INFO - Epoch(train) [150][130/442] lr: 5.000000e-04 eta: 2:37:44 time: 0.351613 data_time: 0.033256 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.777926 2023/08/09 17:19:52 - mmengine - INFO - Epoch(train) [150][140/442] lr: 5.000000e-04 eta: 2:37:40 time: 0.351901 data_time: 0.033436 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.937783 2023/08/09 17:19:52 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:19:55 - mmengine - INFO - Epoch(train) [150][150/442] lr: 5.000000e-04 eta: 2:37:36 time: 0.351223 data_time: 0.033543 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.899337 2023/08/09 17:19:59 - mmengine - INFO - Epoch(train) [150][160/442] lr: 5.000000e-04 eta: 2:37:33 time: 0.347510 data_time: 0.030783 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.836126 2023/08/09 17:20:02 - mmengine - INFO - Epoch(train) [150][170/442] lr: 5.000000e-04 eta: 2:37:29 time: 0.346466 data_time: 0.030844 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.839999 2023/08/09 17:20:06 - mmengine - INFO - Epoch(train) [150][180/442] lr: 5.000000e-04 eta: 2:37:25 time: 0.346692 data_time: 0.031084 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.868958 2023/08/09 17:20:09 - mmengine - INFO - Epoch(train) [150][190/442] lr: 5.000000e-04 eta: 2:37:22 time: 0.345705 data_time: 0.031232 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.788589 2023/08/09 17:20:12 - mmengine - INFO - Epoch(train) [150][200/442] lr: 5.000000e-04 eta: 2:37:18 time: 0.346337 data_time: 0.031954 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.840534 2023/08/09 17:20:16 - mmengine - INFO - Epoch(train) [150][210/442] lr: 5.000000e-04 eta: 2:37:15 time: 0.348219 data_time: 0.031860 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.852793 2023/08/09 17:20:20 - mmengine - INFO - Epoch(train) [150][220/442] lr: 5.000000e-04 eta: 2:37:11 time: 0.350508 data_time: 0.032112 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.823551 2023/08/09 17:20:23 - mmengine - INFO - Epoch(train) [150][230/442] lr: 5.000000e-04 eta: 2:37:07 time: 0.348209 data_time: 0.032063 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.805573 2023/08/09 17:20:26 - mmengine - INFO - Epoch(train) [150][240/442] lr: 5.000000e-04 eta: 2:37:04 time: 0.347756 data_time: 0.031521 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.850538 2023/08/09 17:20:30 - mmengine - INFO - Epoch(train) [150][250/442] lr: 5.000000e-04 eta: 2:37:00 time: 0.351922 data_time: 0.034529 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.861770 2023/08/09 17:20:34 - mmengine - INFO - Epoch(train) [150][260/442] lr: 5.000000e-04 eta: 2:36:57 time: 0.350808 data_time: 0.034516 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.841368 2023/08/09 17:20:37 - mmengine - INFO - Epoch(train) [150][270/442] lr: 5.000000e-04 eta: 2:36:54 time: 0.358512 data_time: 0.034664 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.838041 2023/08/09 17:20:41 - mmengine - INFO - Epoch(train) [150][280/442] lr: 5.000000e-04 eta: 2:36:51 time: 0.368947 data_time: 0.034976 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.778163 2023/08/09 17:20:45 - mmengine - INFO - Epoch(train) [150][290/442] lr: 5.000000e-04 eta: 2:36:48 time: 0.370824 data_time: 0.034987 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.820352 2023/08/09 17:20:48 - mmengine - INFO - Epoch(train) [150][300/442] lr: 5.000000e-04 eta: 2:36:44 time: 0.366422 data_time: 0.031474 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.860252 2023/08/09 17:20:52 - mmengine - INFO - Epoch(train) [150][310/442] lr: 5.000000e-04 eta: 2:36:40 time: 0.366825 data_time: 0.031440 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.774217 2023/08/09 17:20:55 - mmengine - INFO - Epoch(train) [150][320/442] lr: 5.000000e-04 eta: 2:36:37 time: 0.359276 data_time: 0.031087 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.849865 2023/08/09 17:20:59 - mmengine - INFO - Epoch(train) [150][330/442] lr: 5.000000e-04 eta: 2:36:33 time: 0.352419 data_time: 0.030759 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.889845 2023/08/09 17:21:03 - mmengine - INFO - Epoch(train) [150][340/442] lr: 5.000000e-04 eta: 2:36:30 time: 0.353260 data_time: 0.030929 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.847167 2023/08/09 17:21:06 - mmengine - INFO - Epoch(train) [150][350/442] lr: 5.000000e-04 eta: 2:36:26 time: 0.355523 data_time: 0.031084 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.893092 2023/08/09 17:21:10 - mmengine - INFO - Epoch(train) [150][360/442] lr: 5.000000e-04 eta: 2:36:23 time: 0.354869 data_time: 0.031149 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.825531 2023/08/09 17:21:13 - mmengine - INFO - Epoch(train) [150][370/442] lr: 5.000000e-04 eta: 2:36:20 time: 0.358157 data_time: 0.031223 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.851953 2023/08/09 17:21:17 - mmengine - INFO - Epoch(train) [150][380/442] lr: 5.000000e-04 eta: 2:36:17 time: 0.364928 data_time: 0.031525 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.879412 2023/08/09 17:21:21 - mmengine - INFO - Epoch(train) [150][390/442] lr: 5.000000e-04 eta: 2:36:13 time: 0.365280 data_time: 0.031512 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.851527 2023/08/09 17:21:24 - mmengine - INFO - Epoch(train) [150][400/442] lr: 5.000000e-04 eta: 2:36:10 time: 0.363949 data_time: 0.031305 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.823391 2023/08/09 17:21:28 - mmengine - INFO - Epoch(train) [150][410/442] lr: 5.000000e-04 eta: 2:36:06 time: 0.366815 data_time: 0.031785 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.863617 2023/08/09 17:21:32 - mmengine - INFO - Epoch(train) [150][420/442] lr: 5.000000e-04 eta: 2:36:03 time: 0.362515 data_time: 0.031636 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.831943 2023/08/09 17:21:35 - mmengine - INFO - Epoch(train) [150][430/442] lr: 5.000000e-04 eta: 2:35:59 time: 0.354016 data_time: 0.031210 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.786773 2023/08/09 17:21:39 - mmengine - INFO - Epoch(train) [150][440/442] lr: 5.000000e-04 eta: 2:35:56 time: 0.355515 data_time: 0.034204 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.821478 2023/08/09 17:21:39 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:21:39 - mmengine - INFO - Saving checkpoint at 150 epochs 2023/08/09 17:21:45 - mmengine - INFO - Epoch(val) [150][ 10/108] eta: 0:00:20 time: 0.196470 data_time: 0.012635 memory: 4565 2023/08/09 17:21:47 - mmengine - INFO - Epoch(val) [150][ 20/108] eta: 0:00:17 time: 0.196781 data_time: 0.012748 memory: 1624 2023/08/09 17:21:49 - mmengine - INFO - Epoch(val) [150][ 30/108] eta: 0:00:15 time: 0.197369 data_time: 0.013166 memory: 1624 2023/08/09 17:21:51 - mmengine - INFO - Epoch(val) [150][ 40/108] eta: 0:00:13 time: 0.197595 data_time: 0.013304 memory: 1624 2023/08/09 17:21:53 - mmengine - INFO - Epoch(val) [150][ 50/108] eta: 0:00:11 time: 0.199617 data_time: 0.013572 memory: 1624 2023/08/09 17:21:55 - mmengine - INFO - Epoch(val) [150][ 60/108] eta: 0:00:09 time: 0.197171 data_time: 0.011646 memory: 1624 2023/08/09 17:21:57 - mmengine - INFO - Epoch(val) [150][ 70/108] eta: 0:00:07 time: 0.197017 data_time: 0.011557 memory: 1624 2023/08/09 17:21:59 - mmengine - INFO - Epoch(val) [150][ 80/108] eta: 0:00:05 time: 0.196556 data_time: 0.011167 memory: 1624 2023/08/09 17:22:01 - mmengine - INFO - Epoch(val) [150][ 90/108] eta: 0:00:03 time: 0.196445 data_time: 0.011104 memory: 1624 2023/08/09 17:22:02 - mmengine - INFO - Epoch(val) [150][100/108] eta: 0:00:01 time: 0.196353 data_time: 0.010978 memory: 1624 2023/08/09 17:22:04 - mmengine - INFO - Evaluating PCKAccuracy (normalized by ``"bbox_size"``)... 2023/08/09 17:22:04 - mmengine - INFO - Evaluating AUC... 2023/08/09 17:22:05 - mmengine - INFO - Evaluating EPE... 2023/08/09 17:22:05 - mmengine - INFO - Epoch(val) [150][108/108] PCK: 0.961196 AUC: 0.609000 EPE: 14.943885 data_time: 0.012031 time: 0.195940 2023/08/09 17:22:08 - mmengine - INFO - Epoch(train) [151][ 10/442] lr: 5.000000e-04 eta: 2:35:52 time: 0.360115 data_time: 0.038006 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.832422 2023/08/09 17:22:12 - mmengine - INFO - Epoch(train) [151][ 20/442] lr: 5.000000e-04 eta: 2:35:49 time: 0.361589 data_time: 0.037710 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.794762 2023/08/09 17:22:16 - mmengine - INFO - Epoch(train) [151][ 30/442] lr: 5.000000e-04 eta: 2:35:45 time: 0.362809 data_time: 0.037936 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.827364 2023/08/09 17:22:19 - mmengine - INFO - Epoch(train) [151][ 40/442] lr: 5.000000e-04 eta: 2:35:42 time: 0.362931 data_time: 0.038293 memory: 4565 loss: 0.000915 loss_kpt: 0.000915 acc_pose: 0.860019 2023/08/09 17:22:23 - mmengine - INFO - Epoch(train) [151][ 50/442] lr: 5.000000e-04 eta: 2:35:38 time: 0.360679 data_time: 0.035272 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.893870 2023/08/09 17:22:26 - mmengine - INFO - Epoch(train) [151][ 60/442] lr: 5.000000e-04 eta: 2:35:34 time: 0.354001 data_time: 0.031102 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.802733 2023/08/09 17:22:30 - mmengine - INFO - Epoch(train) [151][ 70/442] lr: 5.000000e-04 eta: 2:35:31 time: 0.350158 data_time: 0.031081 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.906685 2023/08/09 17:22:33 - mmengine - INFO - Epoch(train) [151][ 80/442] lr: 5.000000e-04 eta: 2:35:27 time: 0.350966 data_time: 0.030982 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.828626 2023/08/09 17:22:37 - mmengine - INFO - Epoch(train) [151][ 90/442] lr: 5.000000e-04 eta: 2:35:24 time: 0.352827 data_time: 0.030994 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.839904 2023/08/09 17:22:40 - mmengine - INFO - Epoch(train) [151][100/442] lr: 5.000000e-04 eta: 2:35:20 time: 0.353476 data_time: 0.030929 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.876755 2023/08/09 17:22:44 - mmengine - INFO - Epoch(train) [151][110/442] lr: 5.000000e-04 eta: 2:35:17 time: 0.354850 data_time: 0.030976 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.829444 2023/08/09 17:22:48 - mmengine - INFO - Epoch(train) [151][120/442] lr: 5.000000e-04 eta: 2:35:14 time: 0.357958 data_time: 0.030946 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.871442 2023/08/09 17:22:51 - mmengine - INFO - Epoch(train) [151][130/442] lr: 5.000000e-04 eta: 2:35:10 time: 0.356286 data_time: 0.030801 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.910494 2023/08/09 17:22:55 - mmengine - INFO - Epoch(train) [151][140/442] lr: 5.000000e-04 eta: 2:35:06 time: 0.355699 data_time: 0.030708 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.853415 2023/08/09 17:22:58 - mmengine - INFO - Epoch(train) [151][150/442] lr: 5.000000e-04 eta: 2:35:03 time: 0.356855 data_time: 0.031074 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.840564 2023/08/09 17:23:02 - mmengine - INFO - Epoch(train) [151][160/442] lr: 5.000000e-04 eta: 2:35:00 time: 0.359322 data_time: 0.031055 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.844953 2023/08/09 17:23:05 - mmengine - INFO - Epoch(train) [151][170/442] lr: 5.000000e-04 eta: 2:34:56 time: 0.355462 data_time: 0.031039 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.843984 2023/08/09 17:23:09 - mmengine - INFO - Epoch(train) [151][180/442] lr: 5.000000e-04 eta: 2:34:53 time: 0.355703 data_time: 0.031712 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.852932 2023/08/09 17:23:12 - mmengine - INFO - Epoch(train) [151][190/442] lr: 5.000000e-04 eta: 2:34:49 time: 0.355170 data_time: 0.032191 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.902635 2023/08/09 17:23:16 - mmengine - INFO - Epoch(train) [151][200/442] lr: 5.000000e-04 eta: 2:34:46 time: 0.355473 data_time: 0.032894 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.816406 2023/08/09 17:23:20 - mmengine - INFO - Epoch(train) [151][210/442] lr: 5.000000e-04 eta: 2:34:42 time: 0.353426 data_time: 0.033653 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.905802 2023/08/09 17:23:23 - mmengine - INFO - Epoch(train) [151][220/442] lr: 5.000000e-04 eta: 2:34:39 time: 0.355165 data_time: 0.033731 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.828290 2023/08/09 17:23:27 - mmengine - INFO - Epoch(train) [151][230/442] lr: 5.000000e-04 eta: 2:34:35 time: 0.354977 data_time: 0.033257 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.790497 2023/08/09 17:23:30 - mmengine - INFO - Epoch(train) [151][240/442] lr: 5.000000e-04 eta: 2:34:32 time: 0.354709 data_time: 0.032593 memory: 4565 loss: 0.000942 loss_kpt: 0.000942 acc_pose: 0.806524 2023/08/09 17:23:34 - mmengine - INFO - Epoch(train) [151][250/442] lr: 5.000000e-04 eta: 2:34:28 time: 0.354246 data_time: 0.031662 memory: 4565 loss: 0.000935 loss_kpt: 0.000935 acc_pose: 0.896380 2023/08/09 17:23:37 - mmengine - INFO - Epoch(train) [151][260/442] lr: 5.000000e-04 eta: 2:34:24 time: 0.353032 data_time: 0.030872 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.792678 2023/08/09 17:23:41 - mmengine - INFO - Epoch(train) [151][270/442] lr: 5.000000e-04 eta: 2:34:21 time: 0.352475 data_time: 0.030899 memory: 4565 loss: 0.000930 loss_kpt: 0.000930 acc_pose: 0.868514 2023/08/09 17:23:44 - mmengine - INFO - Epoch(train) [151][280/442] lr: 5.000000e-04 eta: 2:34:17 time: 0.353512 data_time: 0.030814 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.806897 2023/08/09 17:23:48 - mmengine - INFO - Epoch(train) [151][290/442] lr: 5.000000e-04 eta: 2:34:14 time: 0.353283 data_time: 0.030912 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.804081 2023/08/09 17:23:51 - mmengine - INFO - Epoch(train) [151][300/442] lr: 5.000000e-04 eta: 2:34:10 time: 0.351957 data_time: 0.030947 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.908340 2023/08/09 17:23:55 - mmengine - INFO - Epoch(train) [151][310/442] lr: 5.000000e-04 eta: 2:34:07 time: 0.357208 data_time: 0.034132 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.862834 2023/08/09 17:23:59 - mmengine - INFO - Epoch(train) [151][320/442] lr: 5.000000e-04 eta: 2:34:04 time: 0.356410 data_time: 0.033831 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.888873 2023/08/09 17:24:02 - mmengine - INFO - Epoch(train) [151][330/442] lr: 5.000000e-04 eta: 2:34:00 time: 0.356070 data_time: 0.034126 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.808970 2023/08/09 17:24:06 - mmengine - INFO - Epoch(train) [151][340/442] lr: 5.000000e-04 eta: 2:33:57 time: 0.357931 data_time: 0.034034 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.849335 2023/08/09 17:24:09 - mmengine - INFO - Epoch(train) [151][350/442] lr: 5.000000e-04 eta: 2:33:53 time: 0.361041 data_time: 0.034438 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.812841 2023/08/09 17:24:13 - mmengine - INFO - Epoch(train) [151][360/442] lr: 5.000000e-04 eta: 2:33:50 time: 0.355153 data_time: 0.031244 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.829292 2023/08/09 17:24:16 - mmengine - INFO - Epoch(train) [151][370/442] lr: 5.000000e-04 eta: 2:33:46 time: 0.354747 data_time: 0.031213 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.844358 2023/08/09 17:24:20 - mmengine - INFO - Epoch(train) [151][380/442] lr: 5.000000e-04 eta: 2:33:43 time: 0.353974 data_time: 0.030825 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.789668 2023/08/09 17:24:23 - mmengine - INFO - Epoch(train) [151][390/442] lr: 5.000000e-04 eta: 2:33:39 time: 0.352243 data_time: 0.030759 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.849567 2023/08/09 17:24:27 - mmengine - INFO - Epoch(train) [151][400/442] lr: 5.000000e-04 eta: 2:33:36 time: 0.353826 data_time: 0.030317 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.844597 2023/08/09 17:24:31 - mmengine - INFO - Epoch(train) [151][410/442] lr: 5.000000e-04 eta: 2:33:32 time: 0.356705 data_time: 0.030624 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.864391 2023/08/09 17:24:34 - mmengine - INFO - Epoch(train) [151][420/442] lr: 5.000000e-04 eta: 2:33:29 time: 0.357338 data_time: 0.030960 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.822282 2023/08/09 17:24:38 - mmengine - INFO - Epoch(train) [151][430/442] lr: 5.000000e-04 eta: 2:33:25 time: 0.356568 data_time: 0.030874 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.885665 2023/08/09 17:24:41 - mmengine - INFO - Epoch(train) [151][440/442] lr: 5.000000e-04 eta: 2:33:22 time: 0.356225 data_time: 0.030951 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.854833 2023/08/09 17:24:42 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:24:46 - mmengine - INFO - Epoch(train) [152][ 10/442] lr: 5.000000e-04 eta: 2:33:18 time: 0.358364 data_time: 0.035726 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.795115 2023/08/09 17:24:49 - mmengine - INFO - Epoch(train) [152][ 20/442] lr: 5.000000e-04 eta: 2:33:14 time: 0.356160 data_time: 0.035560 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.861623 2023/08/09 17:24:53 - mmengine - INFO - Epoch(train) [152][ 30/442] lr: 5.000000e-04 eta: 2:33:11 time: 0.357351 data_time: 0.035393 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.836939 2023/08/09 17:24:56 - mmengine - INFO - Epoch(train) [152][ 40/442] lr: 5.000000e-04 eta: 2:33:07 time: 0.357903 data_time: 0.035500 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.826041 2023/08/09 17:25:00 - mmengine - INFO - Epoch(train) [152][ 50/442] lr: 5.000000e-04 eta: 2:33:04 time: 0.357647 data_time: 0.036172 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.840520 2023/08/09 17:25:03 - mmengine - INFO - Epoch(train) [152][ 60/442] lr: 5.000000e-04 eta: 2:33:00 time: 0.355910 data_time: 0.034240 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.882543 2023/08/09 17:25:07 - mmengine - INFO - Epoch(train) [152][ 70/442] lr: 5.000000e-04 eta: 2:32:57 time: 0.355015 data_time: 0.034097 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.871875 2023/08/09 17:25:10 - mmengine - INFO - Epoch(train) [152][ 80/442] lr: 5.000000e-04 eta: 2:32:53 time: 0.354140 data_time: 0.034092 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.839059 2023/08/09 17:25:14 - mmengine - INFO - Epoch(train) [152][ 90/442] lr: 5.000000e-04 eta: 2:32:50 time: 0.356754 data_time: 0.034154 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.805212 2023/08/09 17:25:18 - mmengine - INFO - Epoch(train) [152][100/442] lr: 5.000000e-04 eta: 2:32:46 time: 0.357740 data_time: 0.034005 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.866694 2023/08/09 17:25:21 - mmengine - INFO - Epoch(train) [152][110/442] lr: 5.000000e-04 eta: 2:32:43 time: 0.353558 data_time: 0.030755 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.812686 2023/08/09 17:25:25 - mmengine - INFO - Epoch(train) [152][120/442] lr: 5.000000e-04 eta: 2:32:39 time: 0.353113 data_time: 0.030744 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.867268 2023/08/09 17:25:28 - mmengine - INFO - Epoch(train) [152][130/442] lr: 5.000000e-04 eta: 2:32:36 time: 0.352783 data_time: 0.030691 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.886894 2023/08/09 17:25:32 - mmengine - INFO - Epoch(train) [152][140/442] lr: 5.000000e-04 eta: 2:32:32 time: 0.350261 data_time: 0.030572 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.858767 2023/08/09 17:25:35 - mmengine - INFO - Epoch(train) [152][150/442] lr: 5.000000e-04 eta: 2:32:28 time: 0.350292 data_time: 0.030516 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.765573 2023/08/09 17:25:39 - mmengine - INFO - Epoch(train) [152][160/442] lr: 5.000000e-04 eta: 2:32:25 time: 0.353827 data_time: 0.030575 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.845117 2023/08/09 17:25:42 - mmengine - INFO - Epoch(train) [152][170/442] lr: 5.000000e-04 eta: 2:32:22 time: 0.355498 data_time: 0.030830 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.880393 2023/08/09 17:25:46 - mmengine - INFO - Epoch(train) [152][180/442] lr: 5.000000e-04 eta: 2:32:18 time: 0.355987 data_time: 0.030808 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.848303 2023/08/09 17:25:49 - mmengine - INFO - Epoch(train) [152][190/442] lr: 5.000000e-04 eta: 2:32:14 time: 0.355203 data_time: 0.030719 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.858494 2023/08/09 17:25:53 - mmengine - INFO - Epoch(train) [152][200/442] lr: 5.000000e-04 eta: 2:32:11 time: 0.354249 data_time: 0.030723 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.840938 2023/08/09 17:25:57 - mmengine - INFO - Epoch(train) [152][210/442] lr: 5.000000e-04 eta: 2:32:08 time: 0.352916 data_time: 0.030775 memory: 4565 loss: 0.000871 loss_kpt: 0.000871 acc_pose: 0.766735 2023/08/09 17:26:00 - mmengine - INFO - Epoch(train) [152][220/442] lr: 5.000000e-04 eta: 2:32:04 time: 0.354614 data_time: 0.030576 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.844659 2023/08/09 17:26:04 - mmengine - INFO - Epoch(train) [152][230/442] lr: 5.000000e-04 eta: 2:32:01 time: 0.356273 data_time: 0.030718 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.799491 2023/08/09 17:26:07 - mmengine - INFO - Epoch(train) [152][240/442] lr: 5.000000e-04 eta: 2:31:57 time: 0.356136 data_time: 0.030805 memory: 4565 loss: 0.000880 loss_kpt: 0.000880 acc_pose: 0.814742 2023/08/09 17:26:11 - mmengine - INFO - Epoch(train) [152][250/442] lr: 5.000000e-04 eta: 2:31:54 time: 0.356206 data_time: 0.030724 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.904568 2023/08/09 17:26:14 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:26:14 - mmengine - INFO - Epoch(train) [152][260/442] lr: 5.000000e-04 eta: 2:31:50 time: 0.355518 data_time: 0.030940 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.873084 2023/08/09 17:26:18 - mmengine - INFO - Epoch(train) [152][270/442] lr: 5.000000e-04 eta: 2:31:47 time: 0.353814 data_time: 0.031299 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.884890 2023/08/09 17:26:21 - mmengine - INFO - Epoch(train) [152][280/442] lr: 5.000000e-04 eta: 2:31:43 time: 0.353016 data_time: 0.031443 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.786206 2023/08/09 17:26:25 - mmengine - INFO - Epoch(train) [152][290/442] lr: 5.000000e-04 eta: 2:31:40 time: 0.355091 data_time: 0.031653 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.797988 2023/08/09 17:26:28 - mmengine - INFO - Epoch(train) [152][300/442] lr: 5.000000e-04 eta: 2:31:36 time: 0.354471 data_time: 0.031590 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.818180 2023/08/09 17:26:32 - mmengine - INFO - Epoch(train) [152][310/442] lr: 5.000000e-04 eta: 2:31:32 time: 0.352574 data_time: 0.031153 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.843163 2023/08/09 17:26:35 - mmengine - INFO - Epoch(train) [152][320/442] lr: 5.000000e-04 eta: 2:31:29 time: 0.351660 data_time: 0.030924 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.897240 2023/08/09 17:26:39 - mmengine - INFO - Epoch(train) [152][330/442] lr: 5.000000e-04 eta: 2:31:25 time: 0.353618 data_time: 0.031585 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.765880 2023/08/09 17:26:43 - mmengine - INFO - Epoch(train) [152][340/442] lr: 5.000000e-04 eta: 2:31:22 time: 0.357303 data_time: 0.031547 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.838545 2023/08/09 17:26:47 - mmengine - INFO - Epoch(train) [152][350/442] lr: 5.000000e-04 eta: 2:31:19 time: 0.366172 data_time: 0.032081 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.767263 2023/08/09 17:26:51 - mmengine - INFO - Epoch(train) [152][360/442] lr: 5.000000e-04 eta: 2:31:16 time: 0.370851 data_time: 0.035767 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.803477 2023/08/09 17:26:54 - mmengine - INFO - Epoch(train) [152][370/442] lr: 5.000000e-04 eta: 2:31:12 time: 0.370409 data_time: 0.035526 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.855940 2023/08/09 17:26:57 - mmengine - INFO - Epoch(train) [152][380/442] lr: 5.000000e-04 eta: 2:31:09 time: 0.367188 data_time: 0.034562 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.857841 2023/08/09 17:27:01 - mmengine - INFO - Epoch(train) [152][390/442] lr: 5.000000e-04 eta: 2:31:05 time: 0.362041 data_time: 0.034303 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.902899 2023/08/09 17:27:05 - mmengine - INFO - Epoch(train) [152][400/442] lr: 5.000000e-04 eta: 2:31:02 time: 0.354667 data_time: 0.034468 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.869482 2023/08/09 17:27:08 - mmengine - INFO - Epoch(train) [152][410/442] lr: 5.000000e-04 eta: 2:30:58 time: 0.352656 data_time: 0.031794 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.814918 2023/08/09 17:27:12 - mmengine - INFO - Epoch(train) [152][420/442] lr: 5.000000e-04 eta: 2:30:55 time: 0.354790 data_time: 0.032748 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.747184 2023/08/09 17:27:15 - mmengine - INFO - Epoch(train) [152][430/442] lr: 5.000000e-04 eta: 2:30:51 time: 0.355683 data_time: 0.033554 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.888561 2023/08/09 17:27:19 - mmengine - INFO - Epoch(train) [152][440/442] lr: 5.000000e-04 eta: 2:30:48 time: 0.355285 data_time: 0.033766 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.836313 2023/08/09 17:27:19 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:27:23 - mmengine - INFO - Epoch(train) [153][ 10/442] lr: 5.000000e-04 eta: 2:30:44 time: 0.355668 data_time: 0.036145 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.834770 2023/08/09 17:27:27 - mmengine - INFO - Epoch(train) [153][ 20/442] lr: 5.000000e-04 eta: 2:30:40 time: 0.357043 data_time: 0.035421 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.812125 2023/08/09 17:27:30 - mmengine - INFO - Epoch(train) [153][ 30/442] lr: 5.000000e-04 eta: 2:30:37 time: 0.357552 data_time: 0.035325 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.873693 2023/08/09 17:27:34 - mmengine - INFO - Epoch(train) [153][ 40/442] lr: 5.000000e-04 eta: 2:30:34 time: 0.362288 data_time: 0.034836 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.819434 2023/08/09 17:27:38 - mmengine - INFO - Epoch(train) [153][ 50/442] lr: 5.000000e-04 eta: 2:30:30 time: 0.364584 data_time: 0.035271 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.882348 2023/08/09 17:27:41 - mmengine - INFO - Epoch(train) [153][ 60/442] lr: 5.000000e-04 eta: 2:30:27 time: 0.361141 data_time: 0.031639 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.846728 2023/08/09 17:27:45 - mmengine - INFO - Epoch(train) [153][ 70/442] lr: 5.000000e-04 eta: 2:30:23 time: 0.358862 data_time: 0.031868 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.775268 2023/08/09 17:27:48 - mmengine - INFO - Epoch(train) [153][ 80/442] lr: 5.000000e-04 eta: 2:30:19 time: 0.357120 data_time: 0.031029 memory: 4565 loss: 0.000927 loss_kpt: 0.000927 acc_pose: 0.798254 2023/08/09 17:27:52 - mmengine - INFO - Epoch(train) [153][ 90/442] lr: 5.000000e-04 eta: 2:30:16 time: 0.353698 data_time: 0.031074 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.919724 2023/08/09 17:27:56 - mmengine - INFO - Epoch(train) [153][100/442] lr: 5.000000e-04 eta: 2:30:13 time: 0.359130 data_time: 0.032046 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.867356 2023/08/09 17:27:59 - mmengine - INFO - Epoch(train) [153][110/442] lr: 5.000000e-04 eta: 2:30:09 time: 0.360609 data_time: 0.032634 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.865124 2023/08/09 17:28:03 - mmengine - INFO - Epoch(train) [153][120/442] lr: 5.000000e-04 eta: 2:30:06 time: 0.361125 data_time: 0.033158 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.816786 2023/08/09 17:28:06 - mmengine - INFO - Epoch(train) [153][130/442] lr: 5.000000e-04 eta: 2:30:02 time: 0.360433 data_time: 0.033851 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.855173 2023/08/09 17:28:10 - mmengine - INFO - Epoch(train) [153][140/442] lr: 5.000000e-04 eta: 2:29:59 time: 0.358497 data_time: 0.033704 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.821733 2023/08/09 17:28:13 - mmengine - INFO - Epoch(train) [153][150/442] lr: 5.000000e-04 eta: 2:29:55 time: 0.353283 data_time: 0.032907 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.880877 2023/08/09 17:28:17 - mmengine - INFO - Epoch(train) [153][160/442] lr: 5.000000e-04 eta: 2:29:52 time: 0.351052 data_time: 0.032295 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.841762 2023/08/09 17:28:20 - mmengine - INFO - Epoch(train) [153][170/442] lr: 5.000000e-04 eta: 2:29:48 time: 0.351460 data_time: 0.031847 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.885045 2023/08/09 17:28:24 - mmengine - INFO - Epoch(train) [153][180/442] lr: 5.000000e-04 eta: 2:29:45 time: 0.353827 data_time: 0.031192 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.870127 2023/08/09 17:28:27 - mmengine - INFO - Epoch(train) [153][190/442] lr: 5.000000e-04 eta: 2:29:41 time: 0.353278 data_time: 0.030982 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.848783 2023/08/09 17:28:31 - mmengine - INFO - Epoch(train) [153][200/442] lr: 5.000000e-04 eta: 2:29:38 time: 0.354552 data_time: 0.031105 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.838192 2023/08/09 17:28:35 - mmengine - INFO - Epoch(train) [153][210/442] lr: 5.000000e-04 eta: 2:29:34 time: 0.355279 data_time: 0.031186 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.925937 2023/08/09 17:28:38 - mmengine - INFO - Epoch(train) [153][220/442] lr: 5.000000e-04 eta: 2:29:31 time: 0.355880 data_time: 0.030952 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.791455 2023/08/09 17:28:42 - mmengine - INFO - Epoch(train) [153][230/442] lr: 5.000000e-04 eta: 2:29:27 time: 0.354578 data_time: 0.031191 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.767452 2023/08/09 17:28:45 - mmengine - INFO - Epoch(train) [153][240/442] lr: 5.000000e-04 eta: 2:29:24 time: 0.357903 data_time: 0.031534 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.838160 2023/08/09 17:28:49 - mmengine - INFO - Epoch(train) [153][250/442] lr: 5.000000e-04 eta: 2:29:20 time: 0.355647 data_time: 0.031152 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.817023 2023/08/09 17:28:52 - mmengine - INFO - Epoch(train) [153][260/442] lr: 5.000000e-04 eta: 2:29:17 time: 0.354975 data_time: 0.031091 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.844503 2023/08/09 17:28:56 - mmengine - INFO - Epoch(train) [153][270/442] lr: 5.000000e-04 eta: 2:29:13 time: 0.353271 data_time: 0.031008 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.886023 2023/08/09 17:28:59 - mmengine - INFO - Epoch(train) [153][280/442] lr: 5.000000e-04 eta: 2:29:10 time: 0.353467 data_time: 0.030936 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.787117 2023/08/09 17:29:03 - mmengine - INFO - Epoch(train) [153][290/442] lr: 5.000000e-04 eta: 2:29:06 time: 0.355211 data_time: 0.030911 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.820758 2023/08/09 17:29:07 - mmengine - INFO - Epoch(train) [153][300/442] lr: 5.000000e-04 eta: 2:29:03 time: 0.358185 data_time: 0.031346 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.844495 2023/08/09 17:29:10 - mmengine - INFO - Epoch(train) [153][310/442] lr: 5.000000e-04 eta: 2:28:59 time: 0.357299 data_time: 0.031313 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.812253 2023/08/09 17:29:14 - mmengine - INFO - Epoch(train) [153][320/442] lr: 5.000000e-04 eta: 2:28:56 time: 0.359375 data_time: 0.031304 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.862511 2023/08/09 17:29:17 - mmengine - INFO - Epoch(train) [153][330/442] lr: 5.000000e-04 eta: 2:28:52 time: 0.357746 data_time: 0.031154 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.791602 2023/08/09 17:29:21 - mmengine - INFO - Epoch(train) [153][340/442] lr: 5.000000e-04 eta: 2:28:49 time: 0.353251 data_time: 0.031027 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.875959 2023/08/09 17:29:24 - mmengine - INFO - Epoch(train) [153][350/442] lr: 5.000000e-04 eta: 2:28:45 time: 0.352798 data_time: 0.031033 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.832349 2023/08/09 17:29:28 - mmengine - INFO - Epoch(train) [153][360/442] lr: 5.000000e-04 eta: 2:28:42 time: 0.354605 data_time: 0.031489 memory: 4565 loss: 0.000871 loss_kpt: 0.000871 acc_pose: 0.749518 2023/08/09 17:29:31 - mmengine - INFO - Epoch(train) [153][370/442] lr: 5.000000e-04 eta: 2:28:38 time: 0.353557 data_time: 0.031840 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.888430 2023/08/09 17:29:35 - mmengine - INFO - Epoch(train) [153][380/442] lr: 5.000000e-04 eta: 2:28:35 time: 0.353989 data_time: 0.031980 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.836294 2023/08/09 17:29:38 - mmengine - INFO - Epoch(train) [153][390/442] lr: 5.000000e-04 eta: 2:28:31 time: 0.353935 data_time: 0.031780 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.859233 2023/08/09 17:29:42 - mmengine - INFO - Epoch(train) [153][400/442] lr: 5.000000e-04 eta: 2:28:28 time: 0.352212 data_time: 0.031391 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.854538 2023/08/09 17:29:46 - mmengine - INFO - Epoch(train) [153][410/442] lr: 5.000000e-04 eta: 2:28:24 time: 0.351880 data_time: 0.031082 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.808622 2023/08/09 17:29:49 - mmengine - INFO - Epoch(train) [153][420/442] lr: 5.000000e-04 eta: 2:28:21 time: 0.351532 data_time: 0.031132 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.830326 2023/08/09 17:29:53 - mmengine - INFO - Epoch(train) [153][430/442] lr: 5.000000e-04 eta: 2:28:17 time: 0.352702 data_time: 0.031374 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.848349 2023/08/09 17:29:56 - mmengine - INFO - Epoch(train) [153][440/442] lr: 5.000000e-04 eta: 2:28:13 time: 0.351995 data_time: 0.031495 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.827839 2023/08/09 17:29:57 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:30:00 - mmengine - INFO - Epoch(train) [154][ 10/442] lr: 5.000000e-04 eta: 2:28:09 time: 0.354461 data_time: 0.035552 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.833401 2023/08/09 17:30:04 - mmengine - INFO - Epoch(train) [154][ 20/442] lr: 5.000000e-04 eta: 2:28:06 time: 0.356504 data_time: 0.035235 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.808293 2023/08/09 17:30:08 - mmengine - INFO - Epoch(train) [154][ 30/442] lr: 5.000000e-04 eta: 2:28:02 time: 0.356797 data_time: 0.034953 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.849556 2023/08/09 17:30:11 - mmengine - INFO - Epoch(train) [154][ 40/442] lr: 5.000000e-04 eta: 2:27:59 time: 0.358857 data_time: 0.035395 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.840099 2023/08/09 17:30:15 - mmengine - INFO - Epoch(train) [154][ 50/442] lr: 5.000000e-04 eta: 2:27:56 time: 0.362577 data_time: 0.036317 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.866511 2023/08/09 17:30:18 - mmengine - INFO - Epoch(train) [154][ 60/442] lr: 5.000000e-04 eta: 2:27:52 time: 0.357685 data_time: 0.031960 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.815805 2023/08/09 17:30:22 - mmengine - INFO - Epoch(train) [154][ 70/442] lr: 5.000000e-04 eta: 2:27:48 time: 0.354325 data_time: 0.032187 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.843473 2023/08/09 17:30:25 - mmengine - INFO - Epoch(train) [154][ 80/442] lr: 5.000000e-04 eta: 2:27:45 time: 0.353967 data_time: 0.032128 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.820868 2023/08/09 17:30:29 - mmengine - INFO - Epoch(train) [154][ 90/442] lr: 5.000000e-04 eta: 2:27:41 time: 0.350494 data_time: 0.031318 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.829818 2023/08/09 17:30:33 - mmengine - INFO - Epoch(train) [154][100/442] lr: 5.000000e-04 eta: 2:27:38 time: 0.352646 data_time: 0.030995 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.889854 2023/08/09 17:30:36 - mmengine - INFO - Epoch(train) [154][110/442] lr: 5.000000e-04 eta: 2:27:35 time: 0.356258 data_time: 0.031231 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.837990 2023/08/09 17:30:40 - mmengine - INFO - Epoch(train) [154][120/442] lr: 5.000000e-04 eta: 2:27:31 time: 0.357367 data_time: 0.031474 memory: 4565 loss: 0.000897 loss_kpt: 0.000897 acc_pose: 0.876028 2023/08/09 17:30:43 - mmengine - INFO - Epoch(train) [154][130/442] lr: 5.000000e-04 eta: 2:27:27 time: 0.356869 data_time: 0.031539 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.906017 2023/08/09 17:30:47 - mmengine - INFO - Epoch(train) [154][140/442] lr: 5.000000e-04 eta: 2:27:24 time: 0.356568 data_time: 0.031322 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.784211 2023/08/09 17:30:50 - mmengine - INFO - Epoch(train) [154][150/442] lr: 5.000000e-04 eta: 2:27:20 time: 0.353265 data_time: 0.030932 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.821549 2023/08/09 17:30:54 - mmengine - INFO - Epoch(train) [154][160/442] lr: 5.000000e-04 eta: 2:27:17 time: 0.356912 data_time: 0.030810 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.905740 2023/08/09 17:30:58 - mmengine - INFO - Epoch(train) [154][170/442] lr: 5.000000e-04 eta: 2:27:14 time: 0.356398 data_time: 0.030443 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.819032 2023/08/09 17:31:01 - mmengine - INFO - Epoch(train) [154][180/442] lr: 5.000000e-04 eta: 2:27:10 time: 0.358329 data_time: 0.030640 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.822923 2023/08/09 17:31:05 - mmengine - INFO - Epoch(train) [154][190/442] lr: 5.000000e-04 eta: 2:27:07 time: 0.357482 data_time: 0.030689 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.832267 2023/08/09 17:31:08 - mmengine - INFO - Epoch(train) [154][200/442] lr: 5.000000e-04 eta: 2:27:03 time: 0.357220 data_time: 0.030654 memory: 4565 loss: 0.000897 loss_kpt: 0.000897 acc_pose: 0.828472 2023/08/09 17:31:12 - mmengine - INFO - Epoch(train) [154][210/442] lr: 5.000000e-04 eta: 2:26:59 time: 0.350496 data_time: 0.030890 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.809471 2023/08/09 17:31:15 - mmengine - INFO - Epoch(train) [154][220/442] lr: 5.000000e-04 eta: 2:26:56 time: 0.349006 data_time: 0.031172 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.926103 2023/08/09 17:31:19 - mmengine - INFO - Epoch(train) [154][230/442] lr: 5.000000e-04 eta: 2:26:52 time: 0.351243 data_time: 0.034181 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.865094 2023/08/09 17:31:22 - mmengine - INFO - Epoch(train) [154][240/442] lr: 5.000000e-04 eta: 2:26:49 time: 0.353738 data_time: 0.034505 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.830519 2023/08/09 17:31:26 - mmengine - INFO - Epoch(train) [154][250/442] lr: 5.000000e-04 eta: 2:26:45 time: 0.353699 data_time: 0.034583 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.843705 2023/08/09 17:31:29 - mmengine - INFO - Epoch(train) [154][260/442] lr: 5.000000e-04 eta: 2:26:42 time: 0.353390 data_time: 0.034023 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.896335 2023/08/09 17:31:33 - mmengine - INFO - Epoch(train) [154][270/442] lr: 5.000000e-04 eta: 2:26:38 time: 0.354544 data_time: 0.033658 memory: 4565 loss: 0.000936 loss_kpt: 0.000936 acc_pose: 0.798515 2023/08/09 17:31:36 - mmengine - INFO - Epoch(train) [154][280/442] lr: 5.000000e-04 eta: 2:26:35 time: 0.351031 data_time: 0.030394 memory: 4565 loss: 0.000937 loss_kpt: 0.000937 acc_pose: 0.786054 2023/08/09 17:31:40 - mmengine - INFO - Epoch(train) [154][290/442] lr: 5.000000e-04 eta: 2:26:31 time: 0.351413 data_time: 0.030348 memory: 4565 loss: 0.000939 loss_kpt: 0.000939 acc_pose: 0.854487 2023/08/09 17:31:43 - mmengine - INFO - Epoch(train) [154][300/442] lr: 5.000000e-04 eta: 2:26:28 time: 0.352744 data_time: 0.030342 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.876470 2023/08/09 17:31:47 - mmengine - INFO - Epoch(train) [154][310/442] lr: 5.000000e-04 eta: 2:26:24 time: 0.357318 data_time: 0.030543 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.804260 2023/08/09 17:31:51 - mmengine - INFO - Epoch(train) [154][320/442] lr: 5.000000e-04 eta: 2:26:21 time: 0.357174 data_time: 0.030466 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.874904 2023/08/09 17:31:54 - mmengine - INFO - Epoch(train) [154][330/442] lr: 5.000000e-04 eta: 2:26:17 time: 0.358064 data_time: 0.030733 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.843836 2023/08/09 17:31:58 - mmengine - INFO - Epoch(train) [154][340/442] lr: 5.000000e-04 eta: 2:26:14 time: 0.360082 data_time: 0.031282 memory: 4565 loss: 0.000856 loss_kpt: 0.000856 acc_pose: 0.921402 2023/08/09 17:32:01 - mmengine - INFO - Epoch(train) [154][350/442] lr: 5.000000e-04 eta: 2:26:10 time: 0.360671 data_time: 0.031618 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.910839 2023/08/09 17:32:05 - mmengine - INFO - Epoch(train) [154][360/442] lr: 5.000000e-04 eta: 2:26:07 time: 0.358410 data_time: 0.032088 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.751227 2023/08/09 17:32:09 - mmengine - INFO - Epoch(train) [154][370/442] lr: 5.000000e-04 eta: 2:26:04 time: 0.360519 data_time: 0.032757 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.736101 2023/08/09 17:32:10 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:32:12 - mmengine - INFO - Epoch(train) [154][380/442] lr: 5.000000e-04 eta: 2:26:00 time: 0.358774 data_time: 0.032612 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.763518 2023/08/09 17:32:16 - mmengine - INFO - Epoch(train) [154][390/442] lr: 5.000000e-04 eta: 2:25:56 time: 0.354329 data_time: 0.032076 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.904534 2023/08/09 17:32:19 - mmengine - INFO - Epoch(train) [154][400/442] lr: 5.000000e-04 eta: 2:25:53 time: 0.354219 data_time: 0.032352 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.733959 2023/08/09 17:32:23 - mmengine - INFO - Epoch(train) [154][410/442] lr: 5.000000e-04 eta: 2:25:49 time: 0.352349 data_time: 0.032126 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.830647 2023/08/09 17:32:26 - mmengine - INFO - Epoch(train) [154][420/442] lr: 5.000000e-04 eta: 2:25:46 time: 0.353050 data_time: 0.031771 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.907281 2023/08/09 17:32:30 - mmengine - INFO - Epoch(train) [154][430/442] lr: 5.000000e-04 eta: 2:25:43 time: 0.355930 data_time: 0.031834 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.890395 2023/08/09 17:32:33 - mmengine - INFO - Epoch(train) [154][440/442] lr: 5.000000e-04 eta: 2:25:39 time: 0.357012 data_time: 0.031677 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.888150 2023/08/09 17:32:34 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:32:38 - mmengine - INFO - Epoch(train) [155][ 10/442] lr: 5.000000e-04 eta: 2:25:35 time: 0.360313 data_time: 0.034620 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.788521 2023/08/09 17:32:41 - mmengine - INFO - Epoch(train) [155][ 20/442] lr: 5.000000e-04 eta: 2:25:31 time: 0.357720 data_time: 0.034423 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.881184 2023/08/09 17:32:45 - mmengine - INFO - Epoch(train) [155][ 30/442] lr: 5.000000e-04 eta: 2:25:28 time: 0.351069 data_time: 0.034365 memory: 4565 loss: 0.000864 loss_kpt: 0.000864 acc_pose: 0.801254 2023/08/09 17:32:48 - mmengine - INFO - Epoch(train) [155][ 40/442] lr: 5.000000e-04 eta: 2:25:24 time: 0.350093 data_time: 0.034184 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.884449 2023/08/09 17:32:52 - mmengine - INFO - Epoch(train) [155][ 50/442] lr: 5.000000e-04 eta: 2:25:20 time: 0.349942 data_time: 0.034710 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.803621 2023/08/09 17:32:55 - mmengine - INFO - Epoch(train) [155][ 60/442] lr: 5.000000e-04 eta: 2:25:17 time: 0.343408 data_time: 0.030857 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.899051 2023/08/09 17:32:58 - mmengine - INFO - Epoch(train) [155][ 70/442] lr: 5.000000e-04 eta: 2:25:13 time: 0.343281 data_time: 0.030971 memory: 4565 loss: 0.000878 loss_kpt: 0.000878 acc_pose: 0.827771 2023/08/09 17:33:02 - mmengine - INFO - Epoch(train) [155][ 80/442] lr: 5.000000e-04 eta: 2:25:09 time: 0.343546 data_time: 0.030945 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.843631 2023/08/09 17:33:05 - mmengine - INFO - Epoch(train) [155][ 90/442] lr: 5.000000e-04 eta: 2:25:06 time: 0.341940 data_time: 0.030864 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.820829 2023/08/09 17:33:09 - mmengine - INFO - Epoch(train) [155][100/442] lr: 5.000000e-04 eta: 2:25:02 time: 0.342378 data_time: 0.030921 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.816627 2023/08/09 17:33:12 - mmengine - INFO - Epoch(train) [155][110/442] lr: 5.000000e-04 eta: 2:24:58 time: 0.342196 data_time: 0.030923 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.902049 2023/08/09 17:33:16 - mmengine - INFO - Epoch(train) [155][120/442] lr: 5.000000e-04 eta: 2:24:55 time: 0.344943 data_time: 0.030969 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.873301 2023/08/09 17:33:19 - mmengine - INFO - Epoch(train) [155][130/442] lr: 5.000000e-04 eta: 2:24:51 time: 0.346210 data_time: 0.031174 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.873659 2023/08/09 17:33:23 - mmengine - INFO - Epoch(train) [155][140/442] lr: 5.000000e-04 eta: 2:24:48 time: 0.346341 data_time: 0.031379 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.840553 2023/08/09 17:33:26 - mmengine - INFO - Epoch(train) [155][150/442] lr: 5.000000e-04 eta: 2:24:44 time: 0.345111 data_time: 0.031540 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.785956 2023/08/09 17:33:29 - mmengine - INFO - Epoch(train) [155][160/442] lr: 5.000000e-04 eta: 2:24:40 time: 0.344392 data_time: 0.031878 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.891533 2023/08/09 17:33:33 - mmengine - INFO - Epoch(train) [155][170/442] lr: 5.000000e-04 eta: 2:24:37 time: 0.342012 data_time: 0.031955 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.896841 2023/08/09 17:33:36 - mmengine - INFO - Epoch(train) [155][180/442] lr: 5.000000e-04 eta: 2:24:33 time: 0.342058 data_time: 0.031737 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.812624 2023/08/09 17:33:40 - mmengine - INFO - Epoch(train) [155][190/442] lr: 5.000000e-04 eta: 2:24:29 time: 0.344598 data_time: 0.031996 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.865663 2023/08/09 17:33:43 - mmengine - INFO - Epoch(train) [155][200/442] lr: 5.000000e-04 eta: 2:24:26 time: 0.346738 data_time: 0.031773 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.769762 2023/08/09 17:33:47 - mmengine - INFO - Epoch(train) [155][210/442] lr: 5.000000e-04 eta: 2:24:22 time: 0.348274 data_time: 0.031274 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.826314 2023/08/09 17:33:50 - mmengine - INFO - Epoch(train) [155][220/442] lr: 5.000000e-04 eta: 2:24:19 time: 0.351411 data_time: 0.030871 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.841954 2023/08/09 17:33:54 - mmengine - INFO - Epoch(train) [155][230/442] lr: 5.000000e-04 eta: 2:24:15 time: 0.350053 data_time: 0.030786 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.832004 2023/08/09 17:33:57 - mmengine - INFO - Epoch(train) [155][240/442] lr: 5.000000e-04 eta: 2:24:11 time: 0.349197 data_time: 0.030689 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.897980 2023/08/09 17:34:01 - mmengine - INFO - Epoch(train) [155][250/442] lr: 5.000000e-04 eta: 2:24:08 time: 0.348627 data_time: 0.031569 memory: 4565 loss: 0.000878 loss_kpt: 0.000878 acc_pose: 0.883177 2023/08/09 17:34:04 - mmengine - INFO - Epoch(train) [155][260/442] lr: 5.000000e-04 eta: 2:24:04 time: 0.348437 data_time: 0.031932 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.801648 2023/08/09 17:34:08 - mmengine - INFO - Epoch(train) [155][270/442] lr: 5.000000e-04 eta: 2:24:01 time: 0.346476 data_time: 0.032018 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.828674 2023/08/09 17:34:11 - mmengine - INFO - Epoch(train) [155][280/442] lr: 5.000000e-04 eta: 2:23:57 time: 0.346024 data_time: 0.032136 memory: 4565 loss: 0.000870 loss_kpt: 0.000870 acc_pose: 0.894415 2023/08/09 17:34:15 - mmengine - INFO - Epoch(train) [155][290/442] lr: 5.000000e-04 eta: 2:23:53 time: 0.343784 data_time: 0.031727 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.791532 2023/08/09 17:34:18 - mmengine - INFO - Epoch(train) [155][300/442] lr: 5.000000e-04 eta: 2:23:50 time: 0.342765 data_time: 0.030755 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.885260 2023/08/09 17:34:21 - mmengine - INFO - Epoch(train) [155][310/442] lr: 5.000000e-04 eta: 2:23:46 time: 0.343519 data_time: 0.030788 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.839647 2023/08/09 17:34:25 - mmengine - INFO - Epoch(train) [155][320/442] lr: 5.000000e-04 eta: 2:23:42 time: 0.343670 data_time: 0.030941 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.850221 2023/08/09 17:34:28 - mmengine - INFO - Epoch(train) [155][330/442] lr: 5.000000e-04 eta: 2:23:39 time: 0.345691 data_time: 0.030917 memory: 4565 loss: 0.000897 loss_kpt: 0.000897 acc_pose: 0.874486 2023/08/09 17:34:32 - mmengine - INFO - Epoch(train) [155][340/442] lr: 5.000000e-04 eta: 2:23:35 time: 0.347850 data_time: 0.031416 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.869161 2023/08/09 17:34:35 - mmengine - INFO - Epoch(train) [155][350/442] lr: 5.000000e-04 eta: 2:23:32 time: 0.348039 data_time: 0.031414 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.831123 2023/08/09 17:34:39 - mmengine - INFO - Epoch(train) [155][360/442] lr: 5.000000e-04 eta: 2:23:28 time: 0.345716 data_time: 0.031077 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.838466 2023/08/09 17:34:42 - mmengine - INFO - Epoch(train) [155][370/442] lr: 5.000000e-04 eta: 2:23:24 time: 0.344997 data_time: 0.031483 memory: 4565 loss: 0.000878 loss_kpt: 0.000878 acc_pose: 0.855614 2023/08/09 17:34:46 - mmengine - INFO - Epoch(train) [155][380/442] lr: 5.000000e-04 eta: 2:23:21 time: 0.347639 data_time: 0.031573 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.848070 2023/08/09 17:34:49 - mmengine - INFO - Epoch(train) [155][390/442] lr: 5.000000e-04 eta: 2:23:18 time: 0.350259 data_time: 0.031431 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.868789 2023/08/09 17:34:53 - mmengine - INFO - Epoch(train) [155][400/442] lr: 5.000000e-04 eta: 2:23:14 time: 0.359827 data_time: 0.031695 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.842719 2023/08/09 17:34:57 - mmengine - INFO - Epoch(train) [155][410/442] lr: 5.000000e-04 eta: 2:23:12 time: 0.373771 data_time: 0.032084 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.814815 2023/08/09 17:35:01 - mmengine - INFO - Epoch(train) [155][420/442] lr: 5.000000e-04 eta: 2:23:08 time: 0.373678 data_time: 0.031517 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.863322 2023/08/09 17:35:04 - mmengine - INFO - Epoch(train) [155][430/442] lr: 5.000000e-04 eta: 2:23:04 time: 0.371330 data_time: 0.031387 memory: 4565 loss: 0.000912 loss_kpt: 0.000912 acc_pose: 0.797061 2023/08/09 17:35:08 - mmengine - INFO - Epoch(train) [155][440/442] lr: 5.000000e-04 eta: 2:23:01 time: 0.368748 data_time: 0.031380 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.844899 2023/08/09 17:35:09 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:35:12 - mmengine - INFO - Epoch(train) [156][ 10/442] lr: 5.000000e-04 eta: 2:22:57 time: 0.363694 data_time: 0.034636 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.833054 2023/08/09 17:35:16 - mmengine - INFO - Epoch(train) [156][ 20/442] lr: 5.000000e-04 eta: 2:22:53 time: 0.353652 data_time: 0.034436 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.796446 2023/08/09 17:35:19 - mmengine - INFO - Epoch(train) [156][ 30/442] lr: 5.000000e-04 eta: 2:22:50 time: 0.354530 data_time: 0.034437 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.842587 2023/08/09 17:35:23 - mmengine - INFO - Epoch(train) [156][ 40/442] lr: 5.000000e-04 eta: 2:22:46 time: 0.354480 data_time: 0.034494 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.816257 2023/08/09 17:35:26 - mmengine - INFO - Epoch(train) [156][ 50/442] lr: 5.000000e-04 eta: 2:22:43 time: 0.356831 data_time: 0.034398 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.824160 2023/08/09 17:35:30 - mmengine - INFO - Epoch(train) [156][ 60/442] lr: 5.000000e-04 eta: 2:22:39 time: 0.352331 data_time: 0.031161 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.849191 2023/08/09 17:35:34 - mmengine - INFO - Epoch(train) [156][ 70/442] lr: 5.000000e-04 eta: 2:22:36 time: 0.353200 data_time: 0.031401 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.836612 2023/08/09 17:35:37 - mmengine - INFO - Epoch(train) [156][ 80/442] lr: 5.000000e-04 eta: 2:22:32 time: 0.353186 data_time: 0.031536 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.894872 2023/08/09 17:35:41 - mmengine - INFO - Epoch(train) [156][ 90/442] lr: 5.000000e-04 eta: 2:22:29 time: 0.354593 data_time: 0.031488 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.832610 2023/08/09 17:35:44 - mmengine - INFO - Epoch(train) [156][100/442] lr: 5.000000e-04 eta: 2:22:25 time: 0.354384 data_time: 0.031830 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.870018 2023/08/09 17:35:48 - mmengine - INFO - Epoch(train) [156][110/442] lr: 5.000000e-04 eta: 2:22:22 time: 0.353168 data_time: 0.031485 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.811972 2023/08/09 17:35:51 - mmengine - INFO - Epoch(train) [156][120/442] lr: 5.000000e-04 eta: 2:22:18 time: 0.354373 data_time: 0.031521 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.825747 2023/08/09 17:35:55 - mmengine - INFO - Epoch(train) [156][130/442] lr: 5.000000e-04 eta: 2:22:15 time: 0.354094 data_time: 0.031434 memory: 4565 loss: 0.000880 loss_kpt: 0.000880 acc_pose: 0.850326 2023/08/09 17:35:58 - mmengine - INFO - Epoch(train) [156][140/442] lr: 5.000000e-04 eta: 2:22:11 time: 0.353704 data_time: 0.031621 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.838207 2023/08/09 17:36:02 - mmengine - INFO - Epoch(train) [156][150/442] lr: 5.000000e-04 eta: 2:22:07 time: 0.353624 data_time: 0.031191 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.793862 2023/08/09 17:36:05 - mmengine - INFO - Epoch(train) [156][160/442] lr: 5.000000e-04 eta: 2:22:04 time: 0.355822 data_time: 0.030897 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.846566 2023/08/09 17:36:09 - mmengine - INFO - Epoch(train) [156][170/442] lr: 5.000000e-04 eta: 2:22:00 time: 0.353931 data_time: 0.030462 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.851503 2023/08/09 17:36:13 - mmengine - INFO - Epoch(train) [156][180/442] lr: 5.000000e-04 eta: 2:21:57 time: 0.355981 data_time: 0.030438 memory: 4565 loss: 0.000916 loss_kpt: 0.000916 acc_pose: 0.744097 2023/08/09 17:36:16 - mmengine - INFO - Epoch(train) [156][190/442] lr: 5.000000e-04 eta: 2:21:54 time: 0.356472 data_time: 0.030445 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.772318 2023/08/09 17:36:20 - mmengine - INFO - Epoch(train) [156][200/442] lr: 5.000000e-04 eta: 2:21:50 time: 0.358800 data_time: 0.030951 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.801275 2023/08/09 17:36:23 - mmengine - INFO - Epoch(train) [156][210/442] lr: 5.000000e-04 eta: 2:21:47 time: 0.357664 data_time: 0.031530 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.882235 2023/08/09 17:36:27 - mmengine - INFO - Epoch(train) [156][220/442] lr: 5.000000e-04 eta: 2:21:43 time: 0.357334 data_time: 0.032097 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.795765 2023/08/09 17:36:30 - mmengine - INFO - Epoch(train) [156][230/442] lr: 5.000000e-04 eta: 2:21:40 time: 0.357789 data_time: 0.032164 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.778184 2023/08/09 17:36:34 - mmengine - INFO - Epoch(train) [156][240/442] lr: 5.000000e-04 eta: 2:21:36 time: 0.355880 data_time: 0.032067 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.813814 2023/08/09 17:36:37 - mmengine - INFO - Epoch(train) [156][250/442] lr: 5.000000e-04 eta: 2:21:33 time: 0.354474 data_time: 0.031863 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.886214 2023/08/09 17:36:41 - mmengine - INFO - Epoch(train) [156][260/442] lr: 5.000000e-04 eta: 2:21:29 time: 0.353284 data_time: 0.031410 memory: 4565 loss: 0.000864 loss_kpt: 0.000864 acc_pose: 0.884052 2023/08/09 17:36:45 - mmengine - INFO - Epoch(train) [156][270/442] lr: 5.000000e-04 eta: 2:21:25 time: 0.353496 data_time: 0.030990 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.911050 2023/08/09 17:36:48 - mmengine - INFO - Epoch(train) [156][280/442] lr: 5.000000e-04 eta: 2:21:22 time: 0.350767 data_time: 0.030841 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.834789 2023/08/09 17:36:51 - mmengine - INFO - Epoch(train) [156][290/442] lr: 5.000000e-04 eta: 2:21:18 time: 0.350005 data_time: 0.030719 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.825127 2023/08/09 17:36:55 - mmengine - INFO - Epoch(train) [156][300/442] lr: 5.000000e-04 eta: 2:21:15 time: 0.350040 data_time: 0.030475 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.869721 2023/08/09 17:36:59 - mmengine - INFO - Epoch(train) [156][310/442] lr: 5.000000e-04 eta: 2:21:11 time: 0.352686 data_time: 0.030866 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.840073 2023/08/09 17:37:02 - mmengine - INFO - Epoch(train) [156][320/442] lr: 5.000000e-04 eta: 2:21:08 time: 0.355957 data_time: 0.030826 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.836828 2023/08/09 17:37:06 - mmengine - INFO - Epoch(train) [156][330/442] lr: 5.000000e-04 eta: 2:21:05 time: 0.358354 data_time: 0.031474 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.825971 2023/08/09 17:37:09 - mmengine - INFO - Epoch(train) [156][340/442] lr: 5.000000e-04 eta: 2:21:01 time: 0.358949 data_time: 0.031459 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.839128 2023/08/09 17:37:13 - mmengine - INFO - Epoch(train) [156][350/442] lr: 5.000000e-04 eta: 2:20:57 time: 0.358905 data_time: 0.031567 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.837999 2023/08/09 17:37:17 - mmengine - INFO - Epoch(train) [156][360/442] lr: 5.000000e-04 eta: 2:20:54 time: 0.358038 data_time: 0.031098 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.782056 2023/08/09 17:37:20 - mmengine - INFO - Epoch(train) [156][370/442] lr: 5.000000e-04 eta: 2:20:51 time: 0.359143 data_time: 0.031182 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.795384 2023/08/09 17:37:24 - mmengine - INFO - Epoch(train) [156][380/442] lr: 5.000000e-04 eta: 2:20:47 time: 0.357655 data_time: 0.030508 memory: 4565 loss: 0.000907 loss_kpt: 0.000907 acc_pose: 0.809241 2023/08/09 17:37:27 - mmengine - INFO - Epoch(train) [156][390/442] lr: 5.000000e-04 eta: 2:20:44 time: 0.359511 data_time: 0.030511 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.860859 2023/08/09 17:37:31 - mmengine - INFO - Epoch(train) [156][400/442] lr: 5.000000e-04 eta: 2:20:40 time: 0.362626 data_time: 0.033739 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.841353 2023/08/09 17:37:35 - mmengine - INFO - Epoch(train) [156][410/442] lr: 5.000000e-04 eta: 2:20:37 time: 0.360437 data_time: 0.033736 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.811790 2023/08/09 17:37:38 - mmengine - INFO - Epoch(train) [156][420/442] lr: 5.000000e-04 eta: 2:20:33 time: 0.355865 data_time: 0.033492 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.866110 2023/08/09 17:37:42 - mmengine - INFO - Epoch(train) [156][430/442] lr: 5.000000e-04 eta: 2:20:30 time: 0.356468 data_time: 0.034007 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.774794 2023/08/09 17:37:45 - mmengine - INFO - Epoch(train) [156][440/442] lr: 5.000000e-04 eta: 2:20:26 time: 0.357499 data_time: 0.034244 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.851937 2023/08/09 17:37:46 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:37:50 - mmengine - INFO - Epoch(train) [157][ 10/442] lr: 5.000000e-04 eta: 2:20:22 time: 0.356791 data_time: 0.034536 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.883593 2023/08/09 17:37:53 - mmengine - INFO - Epoch(train) [157][ 20/442] lr: 5.000000e-04 eta: 2:20:19 time: 0.359055 data_time: 0.034763 memory: 4565 loss: 0.000866 loss_kpt: 0.000866 acc_pose: 0.879918 2023/08/09 17:37:57 - mmengine - INFO - Epoch(train) [157][ 30/442] lr: 5.000000e-04 eta: 2:20:15 time: 0.359570 data_time: 0.034710 memory: 4565 loss: 0.000846 loss_kpt: 0.000846 acc_pose: 0.870088 2023/08/09 17:38:00 - mmengine - INFO - Epoch(train) [157][ 40/442] lr: 5.000000e-04 eta: 2:20:12 time: 0.356750 data_time: 0.034142 memory: 4565 loss: 0.000832 loss_kpt: 0.000832 acc_pose: 0.842929 2023/08/09 17:38:03 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:38:04 - mmengine - INFO - Epoch(train) [157][ 50/442] lr: 5.000000e-04 eta: 2:20:08 time: 0.355434 data_time: 0.034195 memory: 4565 loss: 0.000832 loss_kpt: 0.000832 acc_pose: 0.831871 2023/08/09 17:38:07 - mmengine - INFO - Epoch(train) [157][ 60/442] lr: 5.000000e-04 eta: 2:20:05 time: 0.352912 data_time: 0.030475 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.882084 2023/08/09 17:38:11 - mmengine - INFO - Epoch(train) [157][ 70/442] lr: 5.000000e-04 eta: 2:20:01 time: 0.351480 data_time: 0.030282 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.857633 2023/08/09 17:38:15 - mmengine - INFO - Epoch(train) [157][ 80/442] lr: 5.000000e-04 eta: 2:19:58 time: 0.354772 data_time: 0.030551 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.902540 2023/08/09 17:38:18 - mmengine - INFO - Epoch(train) [157][ 90/442] lr: 5.000000e-04 eta: 2:19:54 time: 0.355512 data_time: 0.030573 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.811130 2023/08/09 17:38:22 - mmengine - INFO - Epoch(train) [157][100/442] lr: 5.000000e-04 eta: 2:19:51 time: 0.355985 data_time: 0.030526 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.780536 2023/08/09 17:38:25 - mmengine - INFO - Epoch(train) [157][110/442] lr: 5.000000e-04 eta: 2:19:47 time: 0.353531 data_time: 0.030351 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.898942 2023/08/09 17:38:29 - mmengine - INFO - Epoch(train) [157][120/442] lr: 5.000000e-04 eta: 2:19:43 time: 0.352819 data_time: 0.030648 memory: 4565 loss: 0.000856 loss_kpt: 0.000856 acc_pose: 0.828769 2023/08/09 17:38:32 - mmengine - INFO - Epoch(train) [157][130/442] lr: 5.000000e-04 eta: 2:19:40 time: 0.350659 data_time: 0.031134 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.849313 2023/08/09 17:38:36 - mmengine - INFO - Epoch(train) [157][140/442] lr: 5.000000e-04 eta: 2:19:36 time: 0.351038 data_time: 0.031289 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.864208 2023/08/09 17:38:40 - mmengine - INFO - Epoch(train) [157][150/442] lr: 5.000000e-04 eta: 2:19:33 time: 0.359144 data_time: 0.031698 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.862415 2023/08/09 17:38:43 - mmengine - INFO - Epoch(train) [157][160/442] lr: 5.000000e-04 eta: 2:19:30 time: 0.368429 data_time: 0.032350 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.813900 2023/08/09 17:38:47 - mmengine - INFO - Epoch(train) [157][170/442] lr: 5.000000e-04 eta: 2:19:27 time: 0.379301 data_time: 0.035564 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.810491 2023/08/09 17:38:51 - mmengine - INFO - Epoch(train) [157][180/442] lr: 5.000000e-04 eta: 2:19:24 time: 0.383559 data_time: 0.035143 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.855678 2023/08/09 17:38:55 - mmengine - INFO - Epoch(train) [157][190/442] lr: 5.000000e-04 eta: 2:19:21 time: 0.389492 data_time: 0.035614 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.873443 2023/08/09 17:38:59 - mmengine - INFO - Epoch(train) [157][200/442] lr: 5.000000e-04 eta: 2:19:17 time: 0.382014 data_time: 0.035232 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.749565 2023/08/09 17:39:02 - mmengine - INFO - Epoch(train) [157][210/442] lr: 5.000000e-04 eta: 2:19:14 time: 0.376284 data_time: 0.034947 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.877966 2023/08/09 17:39:06 - mmengine - INFO - Epoch(train) [157][220/442] lr: 5.000000e-04 eta: 2:19:10 time: 0.365078 data_time: 0.031532 memory: 4565 loss: 0.000908 loss_kpt: 0.000908 acc_pose: 0.820925 2023/08/09 17:39:09 - mmengine - INFO - Epoch(train) [157][230/442] lr: 5.000000e-04 eta: 2:19:07 time: 0.359257 data_time: 0.031480 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.847980 2023/08/09 17:39:13 - mmengine - INFO - Epoch(train) [157][240/442] lr: 5.000000e-04 eta: 2:19:03 time: 0.355224 data_time: 0.030993 memory: 4565 loss: 0.000897 loss_kpt: 0.000897 acc_pose: 0.848080 2023/08/09 17:39:16 - mmengine - INFO - Epoch(train) [157][250/442] lr: 5.000000e-04 eta: 2:19:00 time: 0.355696 data_time: 0.031258 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.807249 2023/08/09 17:39:20 - mmengine - INFO - Epoch(train) [157][260/442] lr: 5.000000e-04 eta: 2:18:56 time: 0.354034 data_time: 0.031388 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.758567 2023/08/09 17:39:24 - mmengine - INFO - Epoch(train) [157][270/442] lr: 5.000000e-04 eta: 2:18:53 time: 0.359561 data_time: 0.032045 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.842233 2023/08/09 17:39:28 - mmengine - INFO - Epoch(train) [157][280/442] lr: 5.000000e-04 eta: 2:18:50 time: 0.367104 data_time: 0.032127 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.866899 2023/08/09 17:39:31 - mmengine - INFO - Epoch(train) [157][290/442] lr: 5.000000e-04 eta: 2:18:47 time: 0.372319 data_time: 0.032340 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.853785 2023/08/09 17:39:35 - mmengine - INFO - Epoch(train) [157][300/442] lr: 5.000000e-04 eta: 2:18:44 time: 0.378759 data_time: 0.032329 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.818468 2023/08/09 17:39:39 - mmengine - INFO - Epoch(train) [157][310/442] lr: 5.000000e-04 eta: 2:18:41 time: 0.386998 data_time: 0.032516 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.830952 2023/08/09 17:39:43 - mmengine - INFO - Epoch(train) [157][320/442] lr: 5.000000e-04 eta: 2:18:37 time: 0.384867 data_time: 0.031771 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.823985 2023/08/09 17:39:47 - mmengine - INFO - Epoch(train) [157][330/442] lr: 5.000000e-04 eta: 2:18:34 time: 0.378823 data_time: 0.031694 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.847594 2023/08/09 17:39:50 - mmengine - INFO - Epoch(train) [157][340/442] lr: 5.000000e-04 eta: 2:18:30 time: 0.371634 data_time: 0.031435 memory: 4565 loss: 0.000880 loss_kpt: 0.000880 acc_pose: 0.846371 2023/08/09 17:39:54 - mmengine - INFO - Epoch(train) [157][350/442] lr: 5.000000e-04 eta: 2:18:27 time: 0.363848 data_time: 0.031185 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.841826 2023/08/09 17:39:57 - mmengine - INFO - Epoch(train) [157][360/442] lr: 5.000000e-04 eta: 2:18:23 time: 0.354148 data_time: 0.030626 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.878162 2023/08/09 17:40:01 - mmengine - INFO - Epoch(train) [157][370/442] lr: 5.000000e-04 eta: 2:18:19 time: 0.350856 data_time: 0.031093 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.894487 2023/08/09 17:40:04 - mmengine - INFO - Epoch(train) [157][380/442] lr: 5.000000e-04 eta: 2:18:16 time: 0.349320 data_time: 0.031329 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.820408 2023/08/09 17:40:08 - mmengine - INFO - Epoch(train) [157][390/442] lr: 5.000000e-04 eta: 2:18:12 time: 0.348161 data_time: 0.031455 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.861765 2023/08/09 17:40:11 - mmengine - INFO - Epoch(train) [157][400/442] lr: 5.000000e-04 eta: 2:18:08 time: 0.346509 data_time: 0.032007 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.825240 2023/08/09 17:40:14 - mmengine - INFO - Epoch(train) [157][410/442] lr: 5.000000e-04 eta: 2:18:05 time: 0.344478 data_time: 0.032020 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.874330 2023/08/09 17:40:18 - mmengine - INFO - Epoch(train) [157][420/442] lr: 5.000000e-04 eta: 2:18:01 time: 0.342342 data_time: 0.031537 memory: 4565 loss: 0.000866 loss_kpt: 0.000866 acc_pose: 0.854143 2023/08/09 17:40:21 - mmengine - INFO - Epoch(train) [157][430/442] lr: 5.000000e-04 eta: 2:17:57 time: 0.340156 data_time: 0.031130 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.867033 2023/08/09 17:40:24 - mmengine - INFO - Epoch(train) [157][440/442] lr: 5.000000e-04 eta: 2:17:54 time: 0.338821 data_time: 0.031013 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.854840 2023/08/09 17:40:25 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:40:29 - mmengine - INFO - Epoch(train) [158][ 10/442] lr: 5.000000e-04 eta: 2:17:50 time: 0.345873 data_time: 0.034404 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.873149 2023/08/09 17:40:32 - mmengine - INFO - Epoch(train) [158][ 20/442] lr: 5.000000e-04 eta: 2:17:46 time: 0.348098 data_time: 0.034590 memory: 4565 loss: 0.000864 loss_kpt: 0.000864 acc_pose: 0.842966 2023/08/09 17:40:36 - mmengine - INFO - Epoch(train) [158][ 30/442] lr: 5.000000e-04 eta: 2:17:43 time: 0.352264 data_time: 0.037808 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.870966 2023/08/09 17:40:39 - mmengine - INFO - Epoch(train) [158][ 40/442] lr: 5.000000e-04 eta: 2:17:39 time: 0.354025 data_time: 0.038364 memory: 4565 loss: 0.000853 loss_kpt: 0.000853 acc_pose: 0.845433 2023/08/09 17:40:43 - mmengine - INFO - Epoch(train) [158][ 50/442] lr: 5.000000e-04 eta: 2:17:35 time: 0.355922 data_time: 0.038618 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.795569 2023/08/09 17:40:46 - mmengine - INFO - Epoch(train) [158][ 60/442] lr: 5.000000e-04 eta: 2:17:32 time: 0.349946 data_time: 0.034817 memory: 4565 loss: 0.000866 loss_kpt: 0.000866 acc_pose: 0.881280 2023/08/09 17:40:50 - mmengine - INFO - Epoch(train) [158][ 70/442] lr: 5.000000e-04 eta: 2:17:28 time: 0.352095 data_time: 0.035037 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.770681 2023/08/09 17:40:53 - mmengine - INFO - Epoch(train) [158][ 80/442] lr: 5.000000e-04 eta: 2:17:25 time: 0.349624 data_time: 0.031837 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.890438 2023/08/09 17:40:57 - mmengine - INFO - Epoch(train) [158][ 90/442] lr: 5.000000e-04 eta: 2:17:21 time: 0.348651 data_time: 0.031364 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.908994 2023/08/09 17:41:00 - mmengine - INFO - Epoch(train) [158][100/442] lr: 5.000000e-04 eta: 2:17:17 time: 0.346746 data_time: 0.031348 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.776789 2023/08/09 17:41:04 - mmengine - INFO - Epoch(train) [158][110/442] lr: 5.000000e-04 eta: 2:17:14 time: 0.345033 data_time: 0.030923 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.967708 2023/08/09 17:41:07 - mmengine - INFO - Epoch(train) [158][120/442] lr: 5.000000e-04 eta: 2:17:10 time: 0.340610 data_time: 0.030434 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.814203 2023/08/09 17:41:10 - mmengine - INFO - Epoch(train) [158][130/442] lr: 5.000000e-04 eta: 2:17:06 time: 0.339310 data_time: 0.031031 memory: 4565 loss: 0.000871 loss_kpt: 0.000871 acc_pose: 0.868423 2023/08/09 17:41:14 - mmengine - INFO - Epoch(train) [158][140/442] lr: 5.000000e-04 eta: 2:17:03 time: 0.339377 data_time: 0.031669 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.774191 2023/08/09 17:41:17 - mmengine - INFO - Epoch(train) [158][150/442] lr: 5.000000e-04 eta: 2:16:59 time: 0.342553 data_time: 0.032233 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.819392 2023/08/09 17:41:21 - mmengine - INFO - Epoch(train) [158][160/442] lr: 5.000000e-04 eta: 2:16:55 time: 0.342693 data_time: 0.032220 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.851482 2023/08/09 17:41:24 - mmengine - INFO - Epoch(train) [158][170/442] lr: 5.000000e-04 eta: 2:16:52 time: 0.345750 data_time: 0.032171 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.851165 2023/08/09 17:41:28 - mmengine - INFO - Epoch(train) [158][180/442] lr: 5.000000e-04 eta: 2:16:48 time: 0.346068 data_time: 0.031578 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.833474 2023/08/09 17:41:31 - mmengine - INFO - Epoch(train) [158][190/442] lr: 5.000000e-04 eta: 2:16:45 time: 0.346599 data_time: 0.030888 memory: 4565 loss: 0.000880 loss_kpt: 0.000880 acc_pose: 0.817504 2023/08/09 17:41:35 - mmengine - INFO - Epoch(train) [158][200/442] lr: 5.000000e-04 eta: 2:16:41 time: 0.346752 data_time: 0.030585 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.868138 2023/08/09 17:41:38 - mmengine - INFO - Epoch(train) [158][210/442] lr: 5.000000e-04 eta: 2:16:37 time: 0.347144 data_time: 0.030736 memory: 4565 loss: 0.000897 loss_kpt: 0.000897 acc_pose: 0.899868 2023/08/09 17:41:42 - mmengine - INFO - Epoch(train) [158][220/442] lr: 5.000000e-04 eta: 2:16:34 time: 0.350337 data_time: 0.030971 memory: 4565 loss: 0.000921 loss_kpt: 0.000921 acc_pose: 0.801533 2023/08/09 17:41:45 - mmengine - INFO - Epoch(train) [158][230/442] lr: 5.000000e-04 eta: 2:16:30 time: 0.349614 data_time: 0.031208 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.886972 2023/08/09 17:41:49 - mmengine - INFO - Epoch(train) [158][240/442] lr: 5.000000e-04 eta: 2:16:27 time: 0.348626 data_time: 0.031132 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.821257 2023/08/09 17:41:52 - mmengine - INFO - Epoch(train) [158][250/442] lr: 5.000000e-04 eta: 2:16:23 time: 0.345835 data_time: 0.030899 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.767940 2023/08/09 17:41:55 - mmengine - INFO - Epoch(train) [158][260/442] lr: 5.000000e-04 eta: 2:16:19 time: 0.345458 data_time: 0.030764 memory: 4565 loss: 0.000909 loss_kpt: 0.000909 acc_pose: 0.848695 2023/08/09 17:41:59 - mmengine - INFO - Epoch(train) [158][270/442] lr: 5.000000e-04 eta: 2:16:16 time: 0.340784 data_time: 0.030744 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.873798 2023/08/09 17:42:02 - mmengine - INFO - Epoch(train) [158][280/442] lr: 5.000000e-04 eta: 2:16:12 time: 0.342075 data_time: 0.030525 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.882619 2023/08/09 17:42:06 - mmengine - INFO - Epoch(train) [158][290/442] lr: 5.000000e-04 eta: 2:16:09 time: 0.342757 data_time: 0.030538 memory: 4565 loss: 0.000897 loss_kpt: 0.000897 acc_pose: 0.833115 2023/08/09 17:42:09 - mmengine - INFO - Epoch(train) [158][300/442] lr: 5.000000e-04 eta: 2:16:05 time: 0.343452 data_time: 0.030622 memory: 4565 loss: 0.000897 loss_kpt: 0.000897 acc_pose: 0.780447 2023/08/09 17:42:13 - mmengine - INFO - Epoch(train) [158][310/442] lr: 5.000000e-04 eta: 2:16:01 time: 0.343811 data_time: 0.031002 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.855788 2023/08/09 17:42:16 - mmengine - INFO - Epoch(train) [158][320/442] lr: 5.000000e-04 eta: 2:15:58 time: 0.343739 data_time: 0.031168 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.831024 2023/08/09 17:42:20 - mmengine - INFO - Epoch(train) [158][330/442] lr: 5.000000e-04 eta: 2:15:54 time: 0.343664 data_time: 0.031156 memory: 4565 loss: 0.000923 loss_kpt: 0.000923 acc_pose: 0.803090 2023/08/09 17:42:23 - mmengine - INFO - Epoch(train) [158][340/442] lr: 5.000000e-04 eta: 2:15:50 time: 0.346044 data_time: 0.031479 memory: 4565 loss: 0.000929 loss_kpt: 0.000929 acc_pose: 0.856708 2023/08/09 17:42:27 - mmengine - INFO - Epoch(train) [158][350/442] lr: 5.000000e-04 eta: 2:15:47 time: 0.346855 data_time: 0.031850 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.838971 2023/08/09 17:42:30 - mmengine - INFO - Epoch(train) [158][360/442] lr: 5.000000e-04 eta: 2:15:43 time: 0.345609 data_time: 0.031471 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.848312 2023/08/09 17:42:33 - mmengine - INFO - Epoch(train) [158][370/442] lr: 5.000000e-04 eta: 2:15:39 time: 0.344192 data_time: 0.031164 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.819528 2023/08/09 17:42:37 - mmengine - INFO - Epoch(train) [158][380/442] lr: 5.000000e-04 eta: 2:15:36 time: 0.342456 data_time: 0.031157 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.794280 2023/08/09 17:42:40 - mmengine - INFO - Epoch(train) [158][390/442] lr: 5.000000e-04 eta: 2:15:32 time: 0.339948 data_time: 0.031281 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.858928 2023/08/09 17:42:44 - mmengine - INFO - Epoch(train) [158][400/442] lr: 5.000000e-04 eta: 2:15:28 time: 0.339109 data_time: 0.031088 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.801093 2023/08/09 17:42:47 - mmengine - INFO - Epoch(train) [158][410/442] lr: 5.000000e-04 eta: 2:15:25 time: 0.340434 data_time: 0.031103 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.879456 2023/08/09 17:42:51 - mmengine - INFO - Epoch(train) [158][420/442] lr: 5.000000e-04 eta: 2:15:21 time: 0.343041 data_time: 0.031200 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.841089 2023/08/09 17:42:54 - mmengine - INFO - Epoch(train) [158][430/442] lr: 5.000000e-04 eta: 2:15:18 time: 0.343817 data_time: 0.031083 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.801352 2023/08/09 17:42:57 - mmengine - INFO - Epoch(train) [158][440/442] lr: 5.000000e-04 eta: 2:15:14 time: 0.343478 data_time: 0.030664 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.886593 2023/08/09 17:42:58 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:43:02 - mmengine - INFO - Epoch(train) [159][ 10/442] lr: 5.000000e-04 eta: 2:15:10 time: 0.349422 data_time: 0.034604 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.868773 2023/08/09 17:43:05 - mmengine - INFO - Epoch(train) [159][ 20/442] lr: 5.000000e-04 eta: 2:15:07 time: 0.354398 data_time: 0.037801 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.795049 2023/08/09 17:43:09 - mmengine - INFO - Epoch(train) [159][ 30/442] lr: 5.000000e-04 eta: 2:15:03 time: 0.355699 data_time: 0.038594 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.855611 2023/08/09 17:43:13 - mmengine - INFO - Epoch(train) [159][ 40/442] lr: 5.000000e-04 eta: 2:15:00 time: 0.359516 data_time: 0.038798 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.815864 2023/08/09 17:43:16 - mmengine - INFO - Epoch(train) [159][ 50/442] lr: 5.000000e-04 eta: 2:14:56 time: 0.365889 data_time: 0.039501 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.842563 2023/08/09 17:43:20 - mmengine - INFO - Epoch(train) [159][ 60/442] lr: 5.000000e-04 eta: 2:14:53 time: 0.360860 data_time: 0.035026 memory: 4565 loss: 0.000830 loss_kpt: 0.000830 acc_pose: 0.831071 2023/08/09 17:43:23 - mmengine - INFO - Epoch(train) [159][ 70/442] lr: 5.000000e-04 eta: 2:14:49 time: 0.357447 data_time: 0.032094 memory: 4565 loss: 0.000839 loss_kpt: 0.000839 acc_pose: 0.823277 2023/08/09 17:43:27 - mmengine - INFO - Epoch(train) [159][ 80/442] lr: 5.000000e-04 eta: 2:14:46 time: 0.357160 data_time: 0.031360 memory: 4565 loss: 0.000838 loss_kpt: 0.000838 acc_pose: 0.901886 2023/08/09 17:43:30 - mmengine - INFO - Epoch(train) [159][ 90/442] lr: 5.000000e-04 eta: 2:14:42 time: 0.356613 data_time: 0.031186 memory: 4565 loss: 0.000837 loss_kpt: 0.000837 acc_pose: 0.887314 2023/08/09 17:43:34 - mmengine - INFO - Epoch(train) [159][100/442] lr: 5.000000e-04 eta: 2:14:39 time: 0.355402 data_time: 0.031469 memory: 4565 loss: 0.000858 loss_kpt: 0.000858 acc_pose: 0.750314 2023/08/09 17:43:38 - mmengine - INFO - Epoch(train) [159][110/442] lr: 5.000000e-04 eta: 2:14:35 time: 0.355062 data_time: 0.031581 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.872089 2023/08/09 17:43:41 - mmengine - INFO - Epoch(train) [159][120/442] lr: 5.000000e-04 eta: 2:14:32 time: 0.354401 data_time: 0.031958 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.911828 2023/08/09 17:43:45 - mmengine - INFO - Epoch(train) [159][130/442] lr: 5.000000e-04 eta: 2:14:28 time: 0.354314 data_time: 0.032034 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.879772 2023/08/09 17:43:48 - mmengine - INFO - Epoch(train) [159][140/442] lr: 5.000000e-04 eta: 2:14:24 time: 0.352661 data_time: 0.032285 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.875317 2023/08/09 17:43:52 - mmengine - INFO - Epoch(train) [159][150/442] lr: 5.000000e-04 eta: 2:14:21 time: 0.351354 data_time: 0.031770 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.834620 2023/08/09 17:43:55 - mmengine - INFO - Epoch(train) [159][160/442] lr: 5.000000e-04 eta: 2:14:17 time: 0.351541 data_time: 0.031693 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.839444 2023/08/09 17:43:57 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:43:59 - mmengine - INFO - Epoch(train) [159][170/442] lr: 5.000000e-04 eta: 2:14:14 time: 0.354867 data_time: 0.030949 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.811782 2023/08/09 17:44:02 - mmengine - INFO - Epoch(train) [159][180/442] lr: 5.000000e-04 eta: 2:14:10 time: 0.354254 data_time: 0.030695 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.888474 2023/08/09 17:44:06 - mmengine - INFO - Epoch(train) [159][190/442] lr: 5.000000e-04 eta: 2:14:07 time: 0.353774 data_time: 0.030486 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.853136 2023/08/09 17:44:09 - mmengine - INFO - Epoch(train) [159][200/442] lr: 5.000000e-04 eta: 2:14:03 time: 0.352957 data_time: 0.030379 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.846091 2023/08/09 17:44:13 - mmengine - INFO - Epoch(train) [159][210/442] lr: 5.000000e-04 eta: 2:14:00 time: 0.353468 data_time: 0.030502 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.875736 2023/08/09 17:44:16 - mmengine - INFO - Epoch(train) [159][220/442] lr: 5.000000e-04 eta: 2:13:56 time: 0.352099 data_time: 0.030587 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.885766 2023/08/09 17:44:20 - mmengine - INFO - Epoch(train) [159][230/442] lr: 5.000000e-04 eta: 2:13:53 time: 0.354557 data_time: 0.031017 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.818382 2023/08/09 17:44:24 - mmengine - INFO - Epoch(train) [159][240/442] lr: 5.000000e-04 eta: 2:13:49 time: 0.356584 data_time: 0.031238 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.880725 2023/08/09 17:44:27 - mmengine - INFO - Epoch(train) [159][250/442] lr: 5.000000e-04 eta: 2:13:46 time: 0.357177 data_time: 0.031153 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.881282 2023/08/09 17:44:31 - mmengine - INFO - Epoch(train) [159][260/442] lr: 5.000000e-04 eta: 2:13:42 time: 0.359518 data_time: 0.034087 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.898920 2023/08/09 17:44:34 - mmengine - INFO - Epoch(train) [159][270/442] lr: 5.000000e-04 eta: 2:13:39 time: 0.357542 data_time: 0.033905 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.805603 2023/08/09 17:44:38 - mmengine - INFO - Epoch(train) [159][280/442] lr: 5.000000e-04 eta: 2:13:35 time: 0.356971 data_time: 0.033813 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.834284 2023/08/09 17:44:41 - mmengine - INFO - Epoch(train) [159][290/442] lr: 5.000000e-04 eta: 2:13:32 time: 0.356306 data_time: 0.034470 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.920630 2023/08/09 17:44:45 - mmengine - INFO - Epoch(train) [159][300/442] lr: 5.000000e-04 eta: 2:13:29 time: 0.359729 data_time: 0.034733 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.728006 2023/08/09 17:44:49 - mmengine - INFO - Epoch(train) [159][310/442] lr: 5.000000e-04 eta: 2:13:25 time: 0.356264 data_time: 0.031771 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.833565 2023/08/09 17:44:52 - mmengine - INFO - Epoch(train) [159][320/442] lr: 5.000000e-04 eta: 2:13:21 time: 0.355179 data_time: 0.031899 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.827641 2023/08/09 17:44:56 - mmengine - INFO - Epoch(train) [159][330/442] lr: 5.000000e-04 eta: 2:13:18 time: 0.353360 data_time: 0.031617 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.838523 2023/08/09 17:44:59 - mmengine - INFO - Epoch(train) [159][340/442] lr: 5.000000e-04 eta: 2:13:14 time: 0.356898 data_time: 0.031038 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.820470 2023/08/09 17:45:03 - mmengine - INFO - Epoch(train) [159][350/442] lr: 5.000000e-04 eta: 2:13:11 time: 0.354191 data_time: 0.031045 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.907814 2023/08/09 17:45:06 - mmengine - INFO - Epoch(train) [159][360/442] lr: 5.000000e-04 eta: 2:13:07 time: 0.355561 data_time: 0.031033 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.884444 2023/08/09 17:45:10 - mmengine - INFO - Epoch(train) [159][370/442] lr: 5.000000e-04 eta: 2:13:04 time: 0.355641 data_time: 0.030925 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.935222 2023/08/09 17:45:13 - mmengine - INFO - Epoch(train) [159][380/442] lr: 5.000000e-04 eta: 2:13:00 time: 0.355859 data_time: 0.031098 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.878576 2023/08/09 17:45:17 - mmengine - INFO - Epoch(train) [159][390/442] lr: 5.000000e-04 eta: 2:12:57 time: 0.351149 data_time: 0.030622 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.843738 2023/08/09 17:45:20 - mmengine - INFO - Epoch(train) [159][400/442] lr: 5.000000e-04 eta: 2:12:53 time: 0.351264 data_time: 0.030465 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.846004 2023/08/09 17:45:24 - mmengine - INFO - Epoch(train) [159][410/442] lr: 5.000000e-04 eta: 2:12:50 time: 0.352017 data_time: 0.030532 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.820718 2023/08/09 17:45:28 - mmengine - INFO - Epoch(train) [159][420/442] lr: 5.000000e-04 eta: 2:12:46 time: 0.356495 data_time: 0.030666 memory: 4565 loss: 0.000910 loss_kpt: 0.000910 acc_pose: 0.886279 2023/08/09 17:45:31 - mmengine - INFO - Epoch(train) [159][430/442] lr: 5.000000e-04 eta: 2:12:43 time: 0.357993 data_time: 0.030926 memory: 4565 loss: 0.000917 loss_kpt: 0.000917 acc_pose: 0.808265 2023/08/09 17:45:35 - mmengine - INFO - Epoch(train) [159][440/442] lr: 5.000000e-04 eta: 2:12:39 time: 0.358861 data_time: 0.031417 memory: 4565 loss: 0.000924 loss_kpt: 0.000924 acc_pose: 0.815372 2023/08/09 17:45:35 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:45:39 - mmengine - INFO - Epoch(train) [160][ 10/442] lr: 5.000000e-04 eta: 2:12:35 time: 0.360138 data_time: 0.035156 memory: 4565 loss: 0.000913 loss_kpt: 0.000913 acc_pose: 0.856459 2023/08/09 17:45:43 - mmengine - INFO - Epoch(train) [160][ 20/442] lr: 5.000000e-04 eta: 2:12:32 time: 0.358210 data_time: 0.035040 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.817563 2023/08/09 17:45:46 - mmengine - INFO - Epoch(train) [160][ 30/442] lr: 5.000000e-04 eta: 2:12:28 time: 0.355087 data_time: 0.034961 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.831184 2023/08/09 17:45:50 - mmengine - INFO - Epoch(train) [160][ 40/442] lr: 5.000000e-04 eta: 2:12:25 time: 0.358135 data_time: 0.038511 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.760199 2023/08/09 17:45:53 - mmengine - INFO - Epoch(train) [160][ 50/442] lr: 5.000000e-04 eta: 2:12:21 time: 0.359434 data_time: 0.038492 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.858524 2023/08/09 17:45:57 - mmengine - INFO - Epoch(train) [160][ 60/442] lr: 5.000000e-04 eta: 2:12:18 time: 0.355417 data_time: 0.034470 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.855371 2023/08/09 17:46:00 - mmengine - INFO - Epoch(train) [160][ 70/442] lr: 5.000000e-04 eta: 2:12:14 time: 0.355987 data_time: 0.034377 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.858458 2023/08/09 17:46:04 - mmengine - INFO - Epoch(train) [160][ 80/442] lr: 5.000000e-04 eta: 2:12:11 time: 0.354459 data_time: 0.034017 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.883698 2023/08/09 17:46:08 - mmengine - INFO - Epoch(train) [160][ 90/442] lr: 5.000000e-04 eta: 2:12:07 time: 0.351786 data_time: 0.030335 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.825941 2023/08/09 17:46:11 - mmengine - INFO - Epoch(train) [160][100/442] lr: 5.000000e-04 eta: 2:12:04 time: 0.352998 data_time: 0.030395 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.889259 2023/08/09 17:46:15 - mmengine - INFO - Epoch(train) [160][110/442] lr: 5.000000e-04 eta: 2:12:00 time: 0.355136 data_time: 0.030813 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.836971 2023/08/09 17:46:18 - mmengine - INFO - Epoch(train) [160][120/442] lr: 5.000000e-04 eta: 2:11:57 time: 0.354151 data_time: 0.030672 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.783087 2023/08/09 17:46:22 - mmengine - INFO - Epoch(train) [160][130/442] lr: 5.000000e-04 eta: 2:11:53 time: 0.353965 data_time: 0.031021 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.897473 2023/08/09 17:46:25 - mmengine - INFO - Epoch(train) [160][140/442] lr: 5.000000e-04 eta: 2:11:49 time: 0.353952 data_time: 0.030925 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.844295 2023/08/09 17:46:29 - mmengine - INFO - Epoch(train) [160][150/442] lr: 5.000000e-04 eta: 2:11:46 time: 0.351924 data_time: 0.030872 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.819438 2023/08/09 17:46:32 - mmengine - INFO - Epoch(train) [160][160/442] lr: 5.000000e-04 eta: 2:11:42 time: 0.352127 data_time: 0.031178 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.844001 2023/08/09 17:46:36 - mmengine - INFO - Epoch(train) [160][170/442] lr: 5.000000e-04 eta: 2:11:39 time: 0.353240 data_time: 0.031512 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.814516 2023/08/09 17:46:40 - mmengine - INFO - Epoch(train) [160][180/442] lr: 5.000000e-04 eta: 2:11:36 time: 0.359691 data_time: 0.031834 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.841611 2023/08/09 17:46:44 - mmengine - INFO - Epoch(train) [160][190/442] lr: 5.000000e-04 eta: 2:11:32 time: 0.366065 data_time: 0.032160 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.803586 2023/08/09 17:46:48 - mmengine - INFO - Epoch(train) [160][200/442] lr: 5.000000e-04 eta: 2:11:29 time: 0.377479 data_time: 0.035671 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.907483 2023/08/09 17:46:51 - mmengine - INFO - Epoch(train) [160][210/442] lr: 5.000000e-04 eta: 2:11:26 time: 0.381088 data_time: 0.035345 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.834520 2023/08/09 17:46:55 - mmengine - INFO - Epoch(train) [160][220/442] lr: 5.000000e-04 eta: 2:11:23 time: 0.382452 data_time: 0.035210 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.838122 2023/08/09 17:46:59 - mmengine - INFO - Epoch(train) [160][230/442] lr: 5.000000e-04 eta: 2:11:20 time: 0.383257 data_time: 0.035489 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.891462 2023/08/09 17:47:02 - mmengine - INFO - Epoch(train) [160][240/442] lr: 5.000000e-04 eta: 2:11:16 time: 0.376810 data_time: 0.035402 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.821234 2023/08/09 17:47:06 - mmengine - INFO - Epoch(train) [160][250/442] lr: 5.000000e-04 eta: 2:11:12 time: 0.365400 data_time: 0.031810 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.878992 2023/08/09 17:47:09 - mmengine - INFO - Epoch(train) [160][260/442] lr: 5.000000e-04 eta: 2:11:09 time: 0.360158 data_time: 0.031668 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.804165 2023/08/09 17:47:13 - mmengine - INFO - Epoch(train) [160][270/442] lr: 5.000000e-04 eta: 2:11:05 time: 0.358431 data_time: 0.031707 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.877208 2023/08/09 17:47:17 - mmengine - INFO - Epoch(train) [160][280/442] lr: 5.000000e-04 eta: 2:11:02 time: 0.355528 data_time: 0.031284 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.847330 2023/08/09 17:47:20 - mmengine - INFO - Epoch(train) [160][290/442] lr: 5.000000e-04 eta: 2:10:59 time: 0.356711 data_time: 0.031292 memory: 4565 loss: 0.000846 loss_kpt: 0.000846 acc_pose: 0.883501 2023/08/09 17:47:24 - mmengine - INFO - Epoch(train) [160][300/442] lr: 5.000000e-04 eta: 2:10:55 time: 0.361249 data_time: 0.031411 memory: 4565 loss: 0.000855 loss_kpt: 0.000855 acc_pose: 0.862831 2023/08/09 17:47:28 - mmengine - INFO - Epoch(train) [160][310/442] lr: 5.000000e-04 eta: 2:10:52 time: 0.361790 data_time: 0.031353 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.824187 2023/08/09 17:47:31 - mmengine - INFO - Epoch(train) [160][320/442] lr: 5.000000e-04 eta: 2:10:48 time: 0.360869 data_time: 0.031006 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.774223 2023/08/09 17:47:34 - mmengine - INFO - Epoch(train) [160][330/442] lr: 5.000000e-04 eta: 2:10:44 time: 0.356958 data_time: 0.030653 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.807098 2023/08/09 17:47:38 - mmengine - INFO - Epoch(train) [160][340/442] lr: 5.000000e-04 eta: 2:10:41 time: 0.357655 data_time: 0.030523 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.751097 2023/08/09 17:47:42 - mmengine - INFO - Epoch(train) [160][350/442] lr: 5.000000e-04 eta: 2:10:38 time: 0.355079 data_time: 0.030812 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.856998 2023/08/09 17:47:45 - mmengine - INFO - Epoch(train) [160][360/442] lr: 5.000000e-04 eta: 2:10:34 time: 0.357375 data_time: 0.030685 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.793013 2023/08/09 17:47:49 - mmengine - INFO - Epoch(train) [160][370/442] lr: 5.000000e-04 eta: 2:10:31 time: 0.363453 data_time: 0.035067 memory: 4565 loss: 0.000891 loss_kpt: 0.000891 acc_pose: 0.799883 2023/08/09 17:47:53 - mmengine - INFO - Epoch(train) [160][380/442] lr: 5.000000e-04 eta: 2:10:27 time: 0.365124 data_time: 0.035407 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.816019 2023/08/09 17:47:56 - mmengine - INFO - Epoch(train) [160][390/442] lr: 5.000000e-04 eta: 2:10:24 time: 0.363704 data_time: 0.035956 memory: 4565 loss: 0.000918 loss_kpt: 0.000918 acc_pose: 0.822289 2023/08/09 17:48:00 - mmengine - INFO - Epoch(train) [160][400/442] lr: 5.000000e-04 eta: 2:10:20 time: 0.361941 data_time: 0.035335 memory: 4565 loss: 0.000922 loss_kpt: 0.000922 acc_pose: 0.830976 2023/08/09 17:48:03 - mmengine - INFO - Epoch(train) [160][410/442] lr: 5.000000e-04 eta: 2:10:17 time: 0.359607 data_time: 0.035396 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.797374 2023/08/09 17:48:07 - mmengine - INFO - Epoch(train) [160][420/442] lr: 5.000000e-04 eta: 2:10:13 time: 0.354234 data_time: 0.031287 memory: 4565 loss: 0.000920 loss_kpt: 0.000920 acc_pose: 0.832258 2023/08/09 17:48:10 - mmengine - INFO - Epoch(train) [160][430/442] lr: 5.000000e-04 eta: 2:10:10 time: 0.354403 data_time: 0.031537 memory: 4565 loss: 0.000903 loss_kpt: 0.000903 acc_pose: 0.771944 2023/08/09 17:48:14 - mmengine - INFO - Epoch(train) [160][440/442] lr: 5.000000e-04 eta: 2:10:06 time: 0.353926 data_time: 0.031378 memory: 4565 loss: 0.000899 loss_kpt: 0.000899 acc_pose: 0.868448 2023/08/09 17:48:15 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:48:15 - mmengine - INFO - Saving checkpoint at 160 epochs 2023/08/09 17:48:20 - mmengine - INFO - Epoch(val) [160][ 10/108] eta: 0:00:20 time: 0.196642 data_time: 0.012917 memory: 4565 2023/08/09 17:48:22 - mmengine - INFO - Epoch(val) [160][ 20/108] eta: 0:00:17 time: 0.196641 data_time: 0.012989 memory: 1624 2023/08/09 17:48:24 - mmengine - INFO - Epoch(val) [160][ 30/108] eta: 0:00:15 time: 0.196783 data_time: 0.013046 memory: 1624 2023/08/09 17:48:26 - mmengine - INFO - Epoch(val) [160][ 40/108] eta: 0:00:13 time: 0.197187 data_time: 0.013223 memory: 1624 2023/08/09 17:48:28 - mmengine - INFO - Epoch(val) [160][ 50/108] eta: 0:00:11 time: 0.199189 data_time: 0.013363 memory: 1624 2023/08/09 17:48:30 - mmengine - INFO - Epoch(val) [160][ 60/108] eta: 0:00:09 time: 0.197241 data_time: 0.011440 memory: 1624 2023/08/09 17:48:32 - mmengine - INFO - Epoch(val) [160][ 70/108] eta: 0:00:07 time: 0.197299 data_time: 0.011521 memory: 1624 2023/08/09 17:48:34 - mmengine - INFO - Epoch(val) [160][ 80/108] eta: 0:00:05 time: 0.197103 data_time: 0.011484 memory: 1624 2023/08/09 17:48:36 - mmengine - INFO - Epoch(val) [160][ 90/108] eta: 0:00:03 time: 0.196763 data_time: 0.011397 memory: 1624 2023/08/09 17:48:38 - mmengine - INFO - Epoch(val) [160][100/108] eta: 0:00:01 time: 0.196851 data_time: 0.011479 memory: 1624 2023/08/09 17:48:40 - mmengine - INFO - Evaluating PCKAccuracy (normalized by ``"bbox_size"``)... 2023/08/09 17:48:40 - mmengine - INFO - Evaluating AUC... 2023/08/09 17:48:40 - mmengine - INFO - Evaluating EPE... 2023/08/09 17:48:40 - mmengine - INFO - Epoch(val) [160][108/108] PCK: 0.962736 AUC: 0.605230 EPE: 14.791320 data_time: 0.012179 time: 0.196005 2023/08/09 17:48:44 - mmengine - INFO - Epoch(train) [161][ 10/442] lr: 5.000000e-04 eta: 2:10:02 time: 0.355660 data_time: 0.036544 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.890183 2023/08/09 17:48:47 - mmengine - INFO - Epoch(train) [161][ 20/442] lr: 5.000000e-04 eta: 2:09:59 time: 0.353420 data_time: 0.036786 memory: 4565 loss: 0.000880 loss_kpt: 0.000880 acc_pose: 0.797928 2023/08/09 17:48:51 - mmengine - INFO - Epoch(train) [161][ 30/442] lr: 5.000000e-04 eta: 2:09:55 time: 0.355023 data_time: 0.040099 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.887957 2023/08/09 17:48:54 - mmengine - INFO - Epoch(train) [161][ 40/442] lr: 5.000000e-04 eta: 2:09:52 time: 0.353140 data_time: 0.039951 memory: 4565 loss: 0.000855 loss_kpt: 0.000855 acc_pose: 0.881346 2023/08/09 17:48:58 - mmengine - INFO - Epoch(train) [161][ 50/442] lr: 5.000000e-04 eta: 2:09:48 time: 0.351940 data_time: 0.039943 memory: 4565 loss: 0.000848 loss_kpt: 0.000848 acc_pose: 0.843051 2023/08/09 17:49:01 - mmengine - INFO - Epoch(train) [161][ 60/442] lr: 5.000000e-04 eta: 2:09:44 time: 0.347052 data_time: 0.034738 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.832115 2023/08/09 17:49:04 - mmengine - INFO - Epoch(train) [161][ 70/442] lr: 5.000000e-04 eta: 2:09:41 time: 0.346337 data_time: 0.034643 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.844263 2023/08/09 17:49:08 - mmengine - INFO - Epoch(train) [161][ 80/442] lr: 5.000000e-04 eta: 2:09:37 time: 0.342388 data_time: 0.031333 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.851649 2023/08/09 17:49:11 - mmengine - INFO - Epoch(train) [161][ 90/442] lr: 5.000000e-04 eta: 2:09:33 time: 0.340766 data_time: 0.030951 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.855025 2023/08/09 17:49:15 - mmengine - INFO - Epoch(train) [161][100/442] lr: 5.000000e-04 eta: 2:09:30 time: 0.341501 data_time: 0.030754 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.861204 2023/08/09 17:49:19 - mmengine - INFO - Epoch(train) [161][110/442] lr: 5.000000e-04 eta: 2:09:26 time: 0.351770 data_time: 0.031863 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.868248 2023/08/09 17:49:23 - mmengine - INFO - Epoch(train) [161][120/442] lr: 5.000000e-04 eta: 2:09:23 time: 0.361619 data_time: 0.032104 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.865039 2023/08/09 17:49:26 - mmengine - INFO - Epoch(train) [161][130/442] lr: 5.000000e-04 eta: 2:09:20 time: 0.371059 data_time: 0.032441 memory: 4565 loss: 0.000853 loss_kpt: 0.000853 acc_pose: 0.855672 2023/08/09 17:49:30 - mmengine - INFO - Epoch(train) [161][140/442] lr: 5.000000e-04 eta: 2:09:17 time: 0.380161 data_time: 0.032742 memory: 4565 loss: 0.000856 loss_kpt: 0.000856 acc_pose: 0.856847 2023/08/09 17:49:34 - mmengine - INFO - Epoch(train) [161][150/442] lr: 5.000000e-04 eta: 2:09:14 time: 0.390583 data_time: 0.033498 memory: 4565 loss: 0.000837 loss_kpt: 0.000837 acc_pose: 0.842750 2023/08/09 17:49:38 - mmengine - INFO - Epoch(train) [161][160/442] lr: 5.000000e-04 eta: 2:09:11 time: 0.394496 data_time: 0.034336 memory: 4565 loss: 0.000837 loss_kpt: 0.000837 acc_pose: 0.898673 2023/08/09 17:49:42 - mmengine - INFO - Epoch(train) [161][170/442] lr: 5.000000e-04 eta: 2:09:07 time: 0.390142 data_time: 0.034239 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.882082 2023/08/09 17:49:45 - mmengine - INFO - Epoch(train) [161][180/442] lr: 5.000000e-04 eta: 2:09:04 time: 0.380291 data_time: 0.033566 memory: 4565 loss: 0.000838 loss_kpt: 0.000838 acc_pose: 0.873750 2023/08/09 17:49:49 - mmengine - INFO - Epoch(train) [161][190/442] lr: 5.000000e-04 eta: 2:09:00 time: 0.370628 data_time: 0.033180 memory: 4565 loss: 0.000852 loss_kpt: 0.000852 acc_pose: 0.861828 2023/08/09 17:49:52 - mmengine - INFO - Epoch(train) [161][200/442] lr: 5.000000e-04 eta: 2:08:56 time: 0.358892 data_time: 0.032242 memory: 4565 loss: 0.000880 loss_kpt: 0.000880 acc_pose: 0.829602 2023/08/09 17:49:56 - mmengine - INFO - Epoch(train) [161][210/442] lr: 5.000000e-04 eta: 2:08:53 time: 0.345708 data_time: 0.030376 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.843282 2023/08/09 17:49:59 - mmengine - INFO - Epoch(train) [161][220/442] lr: 5.000000e-04 eta: 2:08:49 time: 0.341314 data_time: 0.030302 memory: 4565 loss: 0.000871 loss_kpt: 0.000871 acc_pose: 0.892883 2023/08/09 17:50:03 - mmengine - INFO - Epoch(train) [161][230/442] lr: 5.000000e-04 eta: 2:08:46 time: 0.343748 data_time: 0.030748 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.805648 2023/08/09 17:50:06 - mmengine - INFO - Epoch(train) [161][240/442] lr: 5.000000e-04 eta: 2:08:42 time: 0.343418 data_time: 0.030881 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.854149 2023/08/09 17:50:09 - mmengine - INFO - Epoch(train) [161][250/442] lr: 5.000000e-04 eta: 2:08:38 time: 0.343858 data_time: 0.031262 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.799251 2023/08/09 17:50:13 - mmengine - INFO - Epoch(train) [161][260/442] lr: 5.000000e-04 eta: 2:08:35 time: 0.342353 data_time: 0.031199 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.810193 2023/08/09 17:50:16 - mmengine - INFO - Epoch(train) [161][270/442] lr: 5.000000e-04 eta: 2:08:31 time: 0.342075 data_time: 0.031657 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.898327 2023/08/09 17:50:20 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:50:20 - mmengine - INFO - Epoch(train) [161][280/442] lr: 5.000000e-04 eta: 2:08:27 time: 0.341645 data_time: 0.032060 memory: 4565 loss: 0.000896 loss_kpt: 0.000896 acc_pose: 0.876502 2023/08/09 17:50:23 - mmengine - INFO - Epoch(train) [161][290/442] lr: 5.000000e-04 eta: 2:08:24 time: 0.344752 data_time: 0.032998 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.888921 2023/08/09 17:50:27 - mmengine - INFO - Epoch(train) [161][300/442] lr: 5.000000e-04 eta: 2:08:20 time: 0.346196 data_time: 0.033003 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.889677 2023/08/09 17:50:30 - mmengine - INFO - Epoch(train) [161][310/442] lr: 5.000000e-04 eta: 2:08:17 time: 0.349356 data_time: 0.032981 memory: 4565 loss: 0.000870 loss_kpt: 0.000870 acc_pose: 0.829341 2023/08/09 17:50:34 - mmengine - INFO - Epoch(train) [161][320/442] lr: 5.000000e-04 eta: 2:08:13 time: 0.348262 data_time: 0.032334 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.858167 2023/08/09 17:50:37 - mmengine - INFO - Epoch(train) [161][330/442] lr: 5.000000e-04 eta: 2:08:09 time: 0.346462 data_time: 0.032039 memory: 4565 loss: 0.000855 loss_kpt: 0.000855 acc_pose: 0.864096 2023/08/09 17:50:40 - mmengine - INFO - Epoch(train) [161][340/442] lr: 5.000000e-04 eta: 2:08:06 time: 0.343980 data_time: 0.031628 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.812631 2023/08/09 17:50:44 - mmengine - INFO - Epoch(train) [161][350/442] lr: 5.000000e-04 eta: 2:08:03 time: 0.351126 data_time: 0.031596 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.813673 2023/08/09 17:50:48 - mmengine - INFO - Epoch(train) [161][360/442] lr: 5.000000e-04 eta: 2:07:59 time: 0.360973 data_time: 0.032508 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.821246 2023/08/09 17:50:52 - mmengine - INFO - Epoch(train) [161][370/442] lr: 5.000000e-04 eta: 2:07:56 time: 0.370693 data_time: 0.033043 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.875406 2023/08/09 17:50:56 - mmengine - INFO - Epoch(train) [161][380/442] lr: 5.000000e-04 eta: 2:07:53 time: 0.370156 data_time: 0.032696 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.853377 2023/08/09 17:50:59 - mmengine - INFO - Epoch(train) [161][390/442] lr: 5.000000e-04 eta: 2:07:49 time: 0.369755 data_time: 0.032103 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.875760 2023/08/09 17:51:02 - mmengine - INFO - Epoch(train) [161][400/442] lr: 5.000000e-04 eta: 2:07:45 time: 0.361361 data_time: 0.032069 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.846387 2023/08/09 17:51:06 - mmengine - INFO - Epoch(train) [161][410/442] lr: 5.000000e-04 eta: 2:07:42 time: 0.350076 data_time: 0.031326 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.862808 2023/08/09 17:51:09 - mmengine - INFO - Epoch(train) [161][420/442] lr: 5.000000e-04 eta: 2:07:38 time: 0.342077 data_time: 0.030913 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.835990 2023/08/09 17:51:13 - mmengine - INFO - Epoch(train) [161][430/442] lr: 5.000000e-04 eta: 2:07:34 time: 0.343781 data_time: 0.031449 memory: 4565 loss: 0.000853 loss_kpt: 0.000853 acc_pose: 0.843670 2023/08/09 17:51:16 - mmengine - INFO - Epoch(train) [161][440/442] lr: 5.000000e-04 eta: 2:07:31 time: 0.344339 data_time: 0.032149 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.890859 2023/08/09 17:51:17 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:51:21 - mmengine - INFO - Epoch(train) [162][ 10/442] lr: 5.000000e-04 eta: 2:07:27 time: 0.349819 data_time: 0.035244 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.809098 2023/08/09 17:51:24 - mmengine - INFO - Epoch(train) [162][ 20/442] lr: 5.000000e-04 eta: 2:07:23 time: 0.348690 data_time: 0.035144 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.866433 2023/08/09 17:51:27 - mmengine - INFO - Epoch(train) [162][ 30/442] lr: 5.000000e-04 eta: 2:07:19 time: 0.347608 data_time: 0.035177 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.877018 2023/08/09 17:51:31 - mmengine - INFO - Epoch(train) [162][ 40/442] lr: 5.000000e-04 eta: 2:07:16 time: 0.347554 data_time: 0.034517 memory: 4565 loss: 0.000878 loss_kpt: 0.000878 acc_pose: 0.865947 2023/08/09 17:51:34 - mmengine - INFO - Epoch(train) [162][ 50/442] lr: 5.000000e-04 eta: 2:07:12 time: 0.352531 data_time: 0.035408 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.873495 2023/08/09 17:51:38 - mmengine - INFO - Epoch(train) [162][ 60/442] lr: 5.000000e-04 eta: 2:07:09 time: 0.347476 data_time: 0.031617 memory: 4565 loss: 0.000856 loss_kpt: 0.000856 acc_pose: 0.840355 2023/08/09 17:51:42 - mmengine - INFO - Epoch(train) [162][ 70/442] lr: 5.000000e-04 eta: 2:07:05 time: 0.349686 data_time: 0.031741 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.816882 2023/08/09 17:51:45 - mmengine - INFO - Epoch(train) [162][ 80/442] lr: 5.000000e-04 eta: 2:07:02 time: 0.351267 data_time: 0.031882 memory: 4565 loss: 0.000852 loss_kpt: 0.000852 acc_pose: 0.784565 2023/08/09 17:51:49 - mmengine - INFO - Epoch(train) [162][ 90/442] lr: 5.000000e-04 eta: 2:06:58 time: 0.354892 data_time: 0.032325 memory: 4565 loss: 0.000855 loss_kpt: 0.000855 acc_pose: 0.845823 2023/08/09 17:51:52 - mmengine - INFO - Epoch(train) [162][100/442] lr: 5.000000e-04 eta: 2:06:55 time: 0.355020 data_time: 0.031567 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.829150 2023/08/09 17:51:56 - mmengine - INFO - Epoch(train) [162][110/442] lr: 5.000000e-04 eta: 2:06:51 time: 0.356589 data_time: 0.031634 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.841437 2023/08/09 17:51:59 - mmengine - INFO - Epoch(train) [162][120/442] lr: 5.000000e-04 eta: 2:06:48 time: 0.356927 data_time: 0.032012 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.869381 2023/08/09 17:52:03 - mmengine - INFO - Epoch(train) [162][130/442] lr: 5.000000e-04 eta: 2:06:44 time: 0.357005 data_time: 0.031923 memory: 4565 loss: 0.000852 loss_kpt: 0.000852 acc_pose: 0.844311 2023/08/09 17:52:06 - mmengine - INFO - Epoch(train) [162][140/442] lr: 5.000000e-04 eta: 2:06:41 time: 0.354597 data_time: 0.031431 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.816254 2023/08/09 17:52:10 - mmengine - INFO - Epoch(train) [162][150/442] lr: 5.000000e-04 eta: 2:06:37 time: 0.352484 data_time: 0.031228 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.809965 2023/08/09 17:52:13 - mmengine - INFO - Epoch(train) [162][160/442] lr: 5.000000e-04 eta: 2:06:34 time: 0.352408 data_time: 0.031162 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.886991 2023/08/09 17:52:17 - mmengine - INFO - Epoch(train) [162][170/442] lr: 5.000000e-04 eta: 2:06:30 time: 0.355345 data_time: 0.030925 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.865403 2023/08/09 17:52:21 - mmengine - INFO - Epoch(train) [162][180/442] lr: 5.000000e-04 eta: 2:06:27 time: 0.356244 data_time: 0.030919 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.823370 2023/08/09 17:52:24 - mmengine - INFO - Epoch(train) [162][190/442] lr: 5.000000e-04 eta: 2:06:23 time: 0.358203 data_time: 0.034237 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.789591 2023/08/09 17:52:28 - mmengine - INFO - Epoch(train) [162][200/442] lr: 5.000000e-04 eta: 2:06:20 time: 0.357080 data_time: 0.034274 memory: 4565 loss: 0.000861 loss_kpt: 0.000861 acc_pose: 0.831823 2023/08/09 17:52:31 - mmengine - INFO - Epoch(train) [162][210/442] lr: 5.000000e-04 eta: 2:06:16 time: 0.354979 data_time: 0.034240 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.867374 2023/08/09 17:52:35 - mmengine - INFO - Epoch(train) [162][220/442] lr: 5.000000e-04 eta: 2:06:12 time: 0.352414 data_time: 0.034057 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.863233 2023/08/09 17:52:39 - mmengine - INFO - Epoch(train) [162][230/442] lr: 5.000000e-04 eta: 2:06:09 time: 0.357385 data_time: 0.034207 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.879174 2023/08/09 17:52:42 - mmengine - INFO - Epoch(train) [162][240/442] lr: 5.000000e-04 eta: 2:06:06 time: 0.356776 data_time: 0.031604 memory: 4565 loss: 0.000878 loss_kpt: 0.000878 acc_pose: 0.840736 2023/08/09 17:52:46 - mmengine - INFO - Epoch(train) [162][250/442] lr: 5.000000e-04 eta: 2:06:02 time: 0.357872 data_time: 0.031780 memory: 4565 loss: 0.000878 loss_kpt: 0.000878 acc_pose: 0.876467 2023/08/09 17:52:49 - mmengine - INFO - Epoch(train) [162][260/442] lr: 5.000000e-04 eta: 2:05:59 time: 0.358927 data_time: 0.032164 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.900556 2023/08/09 17:52:53 - mmengine - INFO - Epoch(train) [162][270/442] lr: 5.000000e-04 eta: 2:05:55 time: 0.357482 data_time: 0.032128 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.855780 2023/08/09 17:52:56 - mmengine - INFO - Epoch(train) [162][280/442] lr: 5.000000e-04 eta: 2:05:51 time: 0.351700 data_time: 0.031934 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.763989 2023/08/09 17:53:00 - mmengine - INFO - Epoch(train) [162][290/442] lr: 5.000000e-04 eta: 2:05:48 time: 0.350790 data_time: 0.031454 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.842381 2023/08/09 17:53:03 - mmengine - INFO - Epoch(train) [162][300/442] lr: 5.000000e-04 eta: 2:05:44 time: 0.351780 data_time: 0.031685 memory: 4565 loss: 0.000906 loss_kpt: 0.000906 acc_pose: 0.864964 2023/08/09 17:53:07 - mmengine - INFO - Epoch(train) [162][310/442] lr: 5.000000e-04 eta: 2:05:41 time: 0.352353 data_time: 0.032113 memory: 4565 loss: 0.000914 loss_kpt: 0.000914 acc_pose: 0.710422 2023/08/09 17:53:10 - mmengine - INFO - Epoch(train) [162][320/442] lr: 5.000000e-04 eta: 2:05:37 time: 0.351709 data_time: 0.032270 memory: 4565 loss: 0.000905 loss_kpt: 0.000905 acc_pose: 0.762137 2023/08/09 17:53:14 - mmengine - INFO - Epoch(train) [162][330/442] lr: 5.000000e-04 eta: 2:05:34 time: 0.350381 data_time: 0.032186 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.853873 2023/08/09 17:53:17 - mmengine - INFO - Epoch(train) [162][340/442] lr: 5.000000e-04 eta: 2:05:30 time: 0.349142 data_time: 0.031817 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.831541 2023/08/09 17:53:21 - mmengine - INFO - Epoch(train) [162][350/442] lr: 5.000000e-04 eta: 2:05:26 time: 0.347892 data_time: 0.031254 memory: 4565 loss: 0.000858 loss_kpt: 0.000858 acc_pose: 0.896650 2023/08/09 17:53:24 - mmengine - INFO - Epoch(train) [162][360/442] lr: 5.000000e-04 eta: 2:05:23 time: 0.348096 data_time: 0.030450 memory: 4565 loss: 0.000845 loss_kpt: 0.000845 acc_pose: 0.855534 2023/08/09 17:53:28 - mmengine - INFO - Epoch(train) [162][370/442] lr: 5.000000e-04 eta: 2:05:20 time: 0.354672 data_time: 0.033544 memory: 4565 loss: 0.000843 loss_kpt: 0.000843 acc_pose: 0.831739 2023/08/09 17:53:32 - mmengine - INFO - Epoch(train) [162][380/442] lr: 5.000000e-04 eta: 2:05:16 time: 0.358377 data_time: 0.033997 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.827633 2023/08/09 17:53:35 - mmengine - INFO - Epoch(train) [162][390/442] lr: 5.000000e-04 eta: 2:05:13 time: 0.359003 data_time: 0.034713 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.829165 2023/08/09 17:53:39 - mmengine - INFO - Epoch(train) [162][400/442] lr: 5.000000e-04 eta: 2:05:09 time: 0.359147 data_time: 0.035324 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.853232 2023/08/09 17:53:42 - mmengine - INFO - Epoch(train) [162][410/442] lr: 5.000000e-04 eta: 2:05:06 time: 0.358326 data_time: 0.035511 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.834767 2023/08/09 17:53:46 - mmengine - INFO - Epoch(train) [162][420/442] lr: 5.000000e-04 eta: 2:05:02 time: 0.354062 data_time: 0.032323 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.833816 2023/08/09 17:53:49 - mmengine - INFO - Epoch(train) [162][430/442] lr: 5.000000e-04 eta: 2:04:58 time: 0.351139 data_time: 0.032107 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.848736 2023/08/09 17:53:53 - mmengine - INFO - Epoch(train) [162][440/442] lr: 5.000000e-04 eta: 2:04:55 time: 0.353187 data_time: 0.031826 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.826532 2023/08/09 17:53:53 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:53:57 - mmengine - INFO - Epoch(train) [163][ 10/442] lr: 5.000000e-04 eta: 2:04:51 time: 0.354103 data_time: 0.034694 memory: 4565 loss: 0.000878 loss_kpt: 0.000878 acc_pose: 0.852581 2023/08/09 17:54:01 - mmengine - INFO - Epoch(train) [163][ 20/442] lr: 5.000000e-04 eta: 2:04:47 time: 0.353760 data_time: 0.034863 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.797744 2023/08/09 17:54:04 - mmengine - INFO - Epoch(train) [163][ 30/442] lr: 5.000000e-04 eta: 2:04:44 time: 0.352927 data_time: 0.034610 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.840294 2023/08/09 17:54:08 - mmengine - INFO - Epoch(train) [163][ 40/442] lr: 5.000000e-04 eta: 2:04:40 time: 0.353647 data_time: 0.034696 memory: 4565 loss: 0.000855 loss_kpt: 0.000855 acc_pose: 0.829069 2023/08/09 17:54:11 - mmengine - INFO - Epoch(train) [163][ 50/442] lr: 5.000000e-04 eta: 2:04:37 time: 0.356780 data_time: 0.035031 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.900411 2023/08/09 17:54:15 - mmengine - INFO - Epoch(train) [163][ 60/442] lr: 5.000000e-04 eta: 2:04:33 time: 0.354939 data_time: 0.031575 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.798659 2023/08/09 17:54:18 - mmengine - INFO - Epoch(train) [163][ 70/442] lr: 5.000000e-04 eta: 2:04:30 time: 0.357697 data_time: 0.031238 memory: 4565 loss: 0.000856 loss_kpt: 0.000856 acc_pose: 0.867844 2023/08/09 17:54:22 - mmengine - INFO - Epoch(train) [163][ 80/442] lr: 5.000000e-04 eta: 2:04:26 time: 0.360722 data_time: 0.031373 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.812213 2023/08/09 17:54:26 - mmengine - INFO - Epoch(train) [163][ 90/442] lr: 5.000000e-04 eta: 2:04:23 time: 0.361351 data_time: 0.031057 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.902977 2023/08/09 17:54:29 - mmengine - INFO - Epoch(train) [163][100/442] lr: 5.000000e-04 eta: 2:04:19 time: 0.363637 data_time: 0.031280 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.823147 2023/08/09 17:54:33 - mmengine - INFO - Epoch(train) [163][110/442] lr: 5.000000e-04 eta: 2:04:16 time: 0.364435 data_time: 0.031752 memory: 4565 loss: 0.000870 loss_kpt: 0.000870 acc_pose: 0.829623 2023/08/09 17:54:37 - mmengine - INFO - Epoch(train) [163][120/442] lr: 5.000000e-04 eta: 2:04:13 time: 0.363519 data_time: 0.032112 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.900799 2023/08/09 17:54:40 - mmengine - INFO - Epoch(train) [163][130/442] lr: 5.000000e-04 eta: 2:04:09 time: 0.361148 data_time: 0.032862 memory: 4565 loss: 0.000848 loss_kpt: 0.000848 acc_pose: 0.955197 2023/08/09 17:54:44 - mmengine - INFO - Epoch(train) [163][140/442] lr: 5.000000e-04 eta: 2:04:05 time: 0.359798 data_time: 0.032578 memory: 4565 loss: 0.000833 loss_kpt: 0.000833 acc_pose: 0.834988 2023/08/09 17:54:47 - mmengine - INFO - Epoch(train) [163][150/442] lr: 5.000000e-04 eta: 2:04:02 time: 0.357640 data_time: 0.032421 memory: 4565 loss: 0.000826 loss_kpt: 0.000826 acc_pose: 0.876858 2023/08/09 17:54:51 - mmengine - INFO - Epoch(train) [163][160/442] lr: 5.000000e-04 eta: 2:03:58 time: 0.356280 data_time: 0.031542 memory: 4565 loss: 0.000831 loss_kpt: 0.000831 acc_pose: 0.858083 2023/08/09 17:54:54 - mmengine - INFO - Epoch(train) [163][170/442] lr: 5.000000e-04 eta: 2:03:55 time: 0.356622 data_time: 0.031254 memory: 4565 loss: 0.000853 loss_kpt: 0.000853 acc_pose: 0.916925 2023/08/09 17:54:58 - mmengine - INFO - Epoch(train) [163][180/442] lr: 5.000000e-04 eta: 2:03:52 time: 0.357941 data_time: 0.030790 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.892505 2023/08/09 17:55:02 - mmengine - INFO - Epoch(train) [163][190/442] lr: 5.000000e-04 eta: 2:03:48 time: 0.358801 data_time: 0.031168 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.742465 2023/08/09 17:55:05 - mmengine - INFO - Epoch(train) [163][200/442] lr: 5.000000e-04 eta: 2:03:44 time: 0.356878 data_time: 0.030839 memory: 4565 loss: 0.000894 loss_kpt: 0.000894 acc_pose: 0.847781 2023/08/09 17:55:09 - mmengine - INFO - Epoch(train) [163][210/442] lr: 5.000000e-04 eta: 2:03:41 time: 0.355168 data_time: 0.031167 memory: 4565 loss: 0.000893 loss_kpt: 0.000893 acc_pose: 0.871414 2023/08/09 17:55:12 - mmengine - INFO - Epoch(train) [163][220/442] lr: 5.000000e-04 eta: 2:03:37 time: 0.352350 data_time: 0.030896 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.831198 2023/08/09 17:55:16 - mmengine - INFO - Epoch(train) [163][230/442] lr: 5.000000e-04 eta: 2:03:34 time: 0.350211 data_time: 0.030661 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.874580 2023/08/09 17:55:19 - mmengine - INFO - Epoch(train) [163][240/442] lr: 5.000000e-04 eta: 2:03:30 time: 0.349091 data_time: 0.030356 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.894177 2023/08/09 17:55:23 - mmengine - INFO - Epoch(train) [163][250/442] lr: 5.000000e-04 eta: 2:03:27 time: 0.351310 data_time: 0.030806 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.872134 2023/08/09 17:55:26 - mmengine - INFO - Epoch(train) [163][260/442] lr: 5.000000e-04 eta: 2:03:23 time: 0.354712 data_time: 0.033869 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.887700 2023/08/09 17:55:30 - mmengine - INFO - Epoch(train) [163][270/442] lr: 5.000000e-04 eta: 2:03:20 time: 0.355297 data_time: 0.034169 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.810676 2023/08/09 17:55:33 - mmengine - INFO - Epoch(train) [163][280/442] lr: 5.000000e-04 eta: 2:03:16 time: 0.357402 data_time: 0.034081 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.833688 2023/08/09 17:55:37 - mmengine - INFO - Epoch(train) [163][290/442] lr: 5.000000e-04 eta: 2:03:13 time: 0.357662 data_time: 0.034355 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.859863 2023/08/09 17:55:41 - mmengine - INFO - Epoch(train) [163][300/442] lr: 5.000000e-04 eta: 2:03:09 time: 0.357049 data_time: 0.034018 memory: 4565 loss: 0.000841 loss_kpt: 0.000841 acc_pose: 0.916865 2023/08/09 17:55:44 - mmengine - INFO - Epoch(train) [163][310/442] lr: 5.000000e-04 eta: 2:03:06 time: 0.354831 data_time: 0.030866 memory: 4565 loss: 0.000853 loss_kpt: 0.000853 acc_pose: 0.878839 2023/08/09 17:55:48 - mmengine - INFO - Epoch(train) [163][320/442] lr: 5.000000e-04 eta: 2:03:02 time: 0.355780 data_time: 0.030964 memory: 4565 loss: 0.000843 loss_kpt: 0.000843 acc_pose: 0.845382 2023/08/09 17:55:51 - mmengine - INFO - Epoch(train) [163][330/442] lr: 5.000000e-04 eta: 2:02:59 time: 0.353376 data_time: 0.031045 memory: 4565 loss: 0.000837 loss_kpt: 0.000837 acc_pose: 0.840475 2023/08/09 17:55:55 - mmengine - INFO - Epoch(train) [163][340/442] lr: 5.000000e-04 eta: 2:02:55 time: 0.352746 data_time: 0.030766 memory: 4565 loss: 0.000840 loss_kpt: 0.000840 acc_pose: 0.859957 2023/08/09 17:55:58 - mmengine - INFO - Epoch(train) [163][350/442] lr: 5.000000e-04 eta: 2:02:51 time: 0.350974 data_time: 0.030851 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.885281 2023/08/09 17:56:02 - mmengine - INFO - Epoch(train) [163][360/442] lr: 5.000000e-04 eta: 2:02:48 time: 0.350664 data_time: 0.030648 memory: 4565 loss: 0.000866 loss_kpt: 0.000866 acc_pose: 0.821909 2023/08/09 17:56:05 - mmengine - INFO - Epoch(train) [163][370/442] lr: 5.000000e-04 eta: 2:02:44 time: 0.351156 data_time: 0.031225 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.860676 2023/08/09 17:56:09 - mmengine - INFO - Epoch(train) [163][380/442] lr: 5.000000e-04 eta: 2:02:41 time: 0.355931 data_time: 0.031748 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.767460 2023/08/09 17:56:13 - mmengine - INFO - Epoch(train) [163][390/442] lr: 5.000000e-04 eta: 2:02:38 time: 0.362548 data_time: 0.032435 memory: 4565 loss: 0.000901 loss_kpt: 0.000901 acc_pose: 0.854437 2023/08/09 17:56:15 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:56:16 - mmengine - INFO - Epoch(train) [163][400/442] lr: 5.000000e-04 eta: 2:02:34 time: 0.363071 data_time: 0.032529 memory: 4565 loss: 0.000911 loss_kpt: 0.000911 acc_pose: 0.837639 2023/08/09 17:56:20 - mmengine - INFO - Epoch(train) [163][410/442] lr: 5.000000e-04 eta: 2:02:31 time: 0.363278 data_time: 0.033014 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.809638 2023/08/09 17:56:23 - mmengine - INFO - Epoch(train) [163][420/442] lr: 5.000000e-04 eta: 2:02:27 time: 0.362056 data_time: 0.032190 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.838212 2023/08/09 17:56:27 - mmengine - INFO - Epoch(train) [163][430/442] lr: 5.000000e-04 eta: 2:02:24 time: 0.362113 data_time: 0.035157 memory: 4565 loss: 0.000871 loss_kpt: 0.000871 acc_pose: 0.852615 2023/08/09 17:56:31 - mmengine - INFO - Epoch(train) [163][440/442] lr: 5.000000e-04 eta: 2:02:20 time: 0.357447 data_time: 0.034668 memory: 4565 loss: 0.000852 loss_kpt: 0.000852 acc_pose: 0.876966 2023/08/09 17:56:31 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:56:35 - mmengine - INFO - Epoch(train) [164][ 10/442] lr: 5.000000e-04 eta: 2:02:16 time: 0.358622 data_time: 0.037311 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.899351 2023/08/09 17:56:38 - mmengine - INFO - Epoch(train) [164][ 20/442] lr: 5.000000e-04 eta: 2:02:12 time: 0.356571 data_time: 0.037684 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.823335 2023/08/09 17:56:42 - mmengine - INFO - Epoch(train) [164][ 30/442] lr: 5.000000e-04 eta: 2:02:09 time: 0.357130 data_time: 0.037672 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.894215 2023/08/09 17:56:45 - mmengine - INFO - Epoch(train) [164][ 40/442] lr: 5.000000e-04 eta: 2:02:05 time: 0.352803 data_time: 0.034295 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.812969 2023/08/09 17:56:49 - mmengine - INFO - Epoch(train) [164][ 50/442] lr: 5.000000e-04 eta: 2:02:02 time: 0.350738 data_time: 0.034548 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.878573 2023/08/09 17:56:52 - mmengine - INFO - Epoch(train) [164][ 60/442] lr: 5.000000e-04 eta: 2:01:58 time: 0.348632 data_time: 0.031388 memory: 4565 loss: 0.000866 loss_kpt: 0.000866 acc_pose: 0.864254 2023/08/09 17:56:56 - mmengine - INFO - Epoch(train) [164][ 70/442] lr: 5.000000e-04 eta: 2:01:55 time: 0.350392 data_time: 0.031328 memory: 4565 loss: 0.000870 loss_kpt: 0.000870 acc_pose: 0.821262 2023/08/09 17:56:59 - mmengine - INFO - Epoch(train) [164][ 80/442] lr: 5.000000e-04 eta: 2:01:51 time: 0.348357 data_time: 0.031927 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.817363 2023/08/09 17:57:03 - mmengine - INFO - Epoch(train) [164][ 90/442] lr: 5.000000e-04 eta: 2:01:47 time: 0.347590 data_time: 0.032647 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.930477 2023/08/09 17:57:06 - mmengine - INFO - Epoch(train) [164][100/442] lr: 5.000000e-04 eta: 2:01:44 time: 0.346876 data_time: 0.033229 memory: 4565 loss: 0.000848 loss_kpt: 0.000848 acc_pose: 0.839934 2023/08/09 17:57:10 - mmengine - INFO - Epoch(train) [164][110/442] lr: 5.000000e-04 eta: 2:01:40 time: 0.345844 data_time: 0.033406 memory: 4565 loss: 0.000839 loss_kpt: 0.000839 acc_pose: 0.815662 2023/08/09 17:57:13 - mmengine - INFO - Epoch(train) [164][120/442] lr: 5.000000e-04 eta: 2:01:37 time: 0.345004 data_time: 0.033226 memory: 4565 loss: 0.000836 loss_kpt: 0.000836 acc_pose: 0.775499 2023/08/09 17:57:17 - mmengine - INFO - Epoch(train) [164][130/442] lr: 5.000000e-04 eta: 2:01:33 time: 0.346500 data_time: 0.033353 memory: 4565 loss: 0.000843 loss_kpt: 0.000843 acc_pose: 0.875730 2023/08/09 17:57:20 - mmengine - INFO - Epoch(train) [164][140/442] lr: 5.000000e-04 eta: 2:01:29 time: 0.345695 data_time: 0.032675 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.848427 2023/08/09 17:57:24 - mmengine - INFO - Epoch(train) [164][150/442] lr: 5.000000e-04 eta: 2:01:26 time: 0.346371 data_time: 0.032023 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.861544 2023/08/09 17:57:27 - mmengine - INFO - Epoch(train) [164][160/442] lr: 5.000000e-04 eta: 2:01:22 time: 0.349259 data_time: 0.031491 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.840457 2023/08/09 17:57:31 - mmengine - INFO - Epoch(train) [164][170/442] lr: 5.000000e-04 eta: 2:01:19 time: 0.351384 data_time: 0.031400 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.862958 2023/08/09 17:57:34 - mmengine - INFO - Epoch(train) [164][180/442] lr: 5.000000e-04 eta: 2:01:15 time: 0.349973 data_time: 0.031131 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.722003 2023/08/09 17:57:38 - mmengine - INFO - Epoch(train) [164][190/442] lr: 5.000000e-04 eta: 2:01:12 time: 0.350488 data_time: 0.031140 memory: 4565 loss: 0.000904 loss_kpt: 0.000904 acc_pose: 0.840860 2023/08/09 17:57:41 - mmengine - INFO - Epoch(train) [164][200/442] lr: 5.000000e-04 eta: 2:01:08 time: 0.350705 data_time: 0.031119 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.820698 2023/08/09 17:57:45 - mmengine - INFO - Epoch(train) [164][210/442] lr: 5.000000e-04 eta: 2:01:05 time: 0.349034 data_time: 0.031097 memory: 4565 loss: 0.000895 loss_kpt: 0.000895 acc_pose: 0.888966 2023/08/09 17:57:48 - mmengine - INFO - Epoch(train) [164][220/442] lr: 5.000000e-04 eta: 2:01:01 time: 0.345270 data_time: 0.031208 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.852966 2023/08/09 17:57:51 - mmengine - INFO - Epoch(train) [164][230/442] lr: 5.000000e-04 eta: 2:00:57 time: 0.343434 data_time: 0.030742 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.872544 2023/08/09 17:57:55 - mmengine - INFO - Epoch(train) [164][240/442] lr: 5.000000e-04 eta: 2:00:54 time: 0.342365 data_time: 0.030780 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.864493 2023/08/09 17:57:58 - mmengine - INFO - Epoch(train) [164][250/442] lr: 5.000000e-04 eta: 2:00:50 time: 0.341875 data_time: 0.030926 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.822966 2023/08/09 17:58:02 - mmengine - INFO - Epoch(train) [164][260/442] lr: 5.000000e-04 eta: 2:00:47 time: 0.345183 data_time: 0.034511 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.875636 2023/08/09 17:58:06 - mmengine - INFO - Epoch(train) [164][270/442] lr: 5.000000e-04 eta: 2:00:43 time: 0.356226 data_time: 0.034982 memory: 4565 loss: 0.000861 loss_kpt: 0.000861 acc_pose: 0.811166 2023/08/09 17:58:10 - mmengine - INFO - Epoch(train) [164][280/442] lr: 5.000000e-04 eta: 2:00:40 time: 0.362947 data_time: 0.035191 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.834425 2023/08/09 17:58:13 - mmengine - INFO - Epoch(train) [164][290/442] lr: 5.000000e-04 eta: 2:00:36 time: 0.363527 data_time: 0.035158 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.875605 2023/08/09 17:58:16 - mmengine - INFO - Epoch(train) [164][300/442] lr: 5.000000e-04 eta: 2:00:33 time: 0.362838 data_time: 0.034828 memory: 4565 loss: 0.000871 loss_kpt: 0.000871 acc_pose: 0.868424 2023/08/09 17:58:20 - mmengine - INFO - Epoch(train) [164][310/442] lr: 5.000000e-04 eta: 2:00:29 time: 0.360777 data_time: 0.031457 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.812176 2023/08/09 17:58:24 - mmengine - INFO - Epoch(train) [164][320/442] lr: 5.000000e-04 eta: 2:00:26 time: 0.353437 data_time: 0.034307 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.812504 2023/08/09 17:58:27 - mmengine - INFO - Epoch(train) [164][330/442] lr: 5.000000e-04 eta: 2:00:22 time: 0.348409 data_time: 0.034148 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.866958 2023/08/09 17:58:30 - mmengine - INFO - Epoch(train) [164][340/442] lr: 5.000000e-04 eta: 2:00:18 time: 0.349375 data_time: 0.034121 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.859089 2023/08/09 17:58:34 - mmengine - INFO - Epoch(train) [164][350/442] lr: 5.000000e-04 eta: 2:00:15 time: 0.350406 data_time: 0.034389 memory: 4565 loss: 0.000847 loss_kpt: 0.000847 acc_pose: 0.858843 2023/08/09 17:58:37 - mmengine - INFO - Epoch(train) [164][360/442] lr: 5.000000e-04 eta: 2:00:11 time: 0.347458 data_time: 0.034346 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.832841 2023/08/09 17:58:41 - mmengine - INFO - Epoch(train) [164][370/442] lr: 5.000000e-04 eta: 2:00:08 time: 0.345170 data_time: 0.030975 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.870754 2023/08/09 17:58:44 - mmengine - INFO - Epoch(train) [164][380/442] lr: 5.000000e-04 eta: 2:00:04 time: 0.345329 data_time: 0.031072 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.837290 2023/08/09 17:58:48 - mmengine - INFO - Epoch(train) [164][390/442] lr: 5.000000e-04 eta: 2:00:00 time: 0.345035 data_time: 0.031211 memory: 4565 loss: 0.000870 loss_kpt: 0.000870 acc_pose: 0.815542 2023/08/09 17:58:51 - mmengine - INFO - Epoch(train) [164][400/442] lr: 5.000000e-04 eta: 1:59:57 time: 0.344315 data_time: 0.031005 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.844081 2023/08/09 17:58:55 - mmengine - INFO - Epoch(train) [164][410/442] lr: 5.000000e-04 eta: 1:59:53 time: 0.343534 data_time: 0.030724 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.841981 2023/08/09 17:58:58 - mmengine - INFO - Epoch(train) [164][420/442] lr: 5.000000e-04 eta: 1:59:50 time: 0.342306 data_time: 0.030589 memory: 4565 loss: 0.000889 loss_kpt: 0.000889 acc_pose: 0.872680 2023/08/09 17:59:01 - mmengine - INFO - Epoch(train) [164][430/442] lr: 5.000000e-04 eta: 1:59:46 time: 0.340931 data_time: 0.030607 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.896561 2023/08/09 17:59:05 - mmengine - INFO - Epoch(train) [164][440/442] lr: 5.000000e-04 eta: 1:59:42 time: 0.343026 data_time: 0.030493 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.876667 2023/08/09 17:59:06 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 17:59:09 - mmengine - INFO - Epoch(train) [165][ 10/442] lr: 5.000000e-04 eta: 1:59:38 time: 0.347448 data_time: 0.034235 memory: 4565 loss: 0.000843 loss_kpt: 0.000843 acc_pose: 0.874699 2023/08/09 17:59:13 - mmengine - INFO - Epoch(train) [165][ 20/442] lr: 5.000000e-04 eta: 1:59:35 time: 0.349366 data_time: 0.035093 memory: 4565 loss: 0.000833 loss_kpt: 0.000833 acc_pose: 0.833663 2023/08/09 17:59:16 - mmengine - INFO - Epoch(train) [165][ 30/442] lr: 5.000000e-04 eta: 1:59:31 time: 0.349598 data_time: 0.034888 memory: 4565 loss: 0.000821 loss_kpt: 0.000821 acc_pose: 0.917230 2023/08/09 17:59:20 - mmengine - INFO - Epoch(train) [165][ 40/442] lr: 5.000000e-04 eta: 1:59:27 time: 0.349928 data_time: 0.038044 memory: 4565 loss: 0.000837 loss_kpt: 0.000837 acc_pose: 0.796333 2023/08/09 17:59:23 - mmengine - INFO - Epoch(train) [165][ 50/442] lr: 5.000000e-04 eta: 1:59:24 time: 0.350596 data_time: 0.038391 memory: 4565 loss: 0.000841 loss_kpt: 0.000841 acc_pose: 0.895490 2023/08/09 17:59:27 - mmengine - INFO - Epoch(train) [165][ 60/442] lr: 5.000000e-04 eta: 1:59:20 time: 0.346681 data_time: 0.034295 memory: 4565 loss: 0.000855 loss_kpt: 0.000855 acc_pose: 0.806691 2023/08/09 17:59:30 - mmengine - INFO - Epoch(train) [165][ 70/442] lr: 5.000000e-04 eta: 1:59:17 time: 0.346501 data_time: 0.034349 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.881627 2023/08/09 17:59:34 - mmengine - INFO - Epoch(train) [165][ 80/442] lr: 5.000000e-04 eta: 1:59:13 time: 0.348944 data_time: 0.034700 memory: 4565 loss: 0.000878 loss_kpt: 0.000878 acc_pose: 0.835389 2023/08/09 17:59:37 - mmengine - INFO - Epoch(train) [165][ 90/442] lr: 5.000000e-04 eta: 1:59:10 time: 0.347368 data_time: 0.031362 memory: 4565 loss: 0.000880 loss_kpt: 0.000880 acc_pose: 0.786806 2023/08/09 17:59:41 - mmengine - INFO - Epoch(train) [165][100/442] lr: 5.000000e-04 eta: 1:59:06 time: 0.348172 data_time: 0.031317 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.861012 2023/08/09 17:59:44 - mmengine - INFO - Epoch(train) [165][110/442] lr: 5.000000e-04 eta: 1:59:02 time: 0.348436 data_time: 0.031177 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.883852 2023/08/09 17:59:48 - mmengine - INFO - Epoch(train) [165][120/442] lr: 5.000000e-04 eta: 1:58:59 time: 0.349111 data_time: 0.030435 memory: 4565 loss: 0.000864 loss_kpt: 0.000864 acc_pose: 0.891543 2023/08/09 17:59:51 - mmengine - INFO - Epoch(train) [165][130/442] lr: 5.000000e-04 eta: 1:58:55 time: 0.351810 data_time: 0.030277 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.847319 2023/08/09 17:59:55 - mmengine - INFO - Epoch(train) [165][140/442] lr: 5.000000e-04 eta: 1:58:52 time: 0.353158 data_time: 0.030610 memory: 4565 loss: 0.000838 loss_kpt: 0.000838 acc_pose: 0.865802 2023/08/09 17:59:58 - mmengine - INFO - Epoch(train) [165][150/442] lr: 5.000000e-04 eta: 1:58:48 time: 0.354763 data_time: 0.030866 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.811674 2023/08/09 18:00:02 - mmengine - INFO - Epoch(train) [165][160/442] lr: 5.000000e-04 eta: 1:58:45 time: 0.354564 data_time: 0.030933 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.849601 2023/08/09 18:00:05 - mmengine - INFO - Epoch(train) [165][170/442] lr: 5.000000e-04 eta: 1:58:41 time: 0.353160 data_time: 0.030783 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.805172 2023/08/09 18:00:09 - mmengine - INFO - Epoch(train) [165][180/442] lr: 5.000000e-04 eta: 1:58:38 time: 0.348854 data_time: 0.030613 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.779141 2023/08/09 18:00:12 - mmengine - INFO - Epoch(train) [165][190/442] lr: 5.000000e-04 eta: 1:58:34 time: 0.347891 data_time: 0.030337 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.875736 2023/08/09 18:00:16 - mmengine - INFO - Epoch(train) [165][200/442] lr: 5.000000e-04 eta: 1:58:30 time: 0.348054 data_time: 0.030206 memory: 4565 loss: 0.000880 loss_kpt: 0.000880 acc_pose: 0.857876 2023/08/09 18:00:19 - mmengine - INFO - Epoch(train) [165][210/442] lr: 5.000000e-04 eta: 1:58:27 time: 0.350344 data_time: 0.030425 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.799964 2023/08/09 18:00:23 - mmengine - INFO - Epoch(train) [165][220/442] lr: 5.000000e-04 eta: 1:58:23 time: 0.351581 data_time: 0.030589 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.805255 2023/08/09 18:00:26 - mmengine - INFO - Epoch(train) [165][230/442] lr: 5.000000e-04 eta: 1:58:20 time: 0.354917 data_time: 0.031109 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.735274 2023/08/09 18:00:30 - mmengine - INFO - Epoch(train) [165][240/442] lr: 5.000000e-04 eta: 1:58:16 time: 0.356105 data_time: 0.031047 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.813784 2023/08/09 18:00:34 - mmengine - INFO - Epoch(train) [165][250/442] lr: 5.000000e-04 eta: 1:58:13 time: 0.357954 data_time: 0.030981 memory: 4565 loss: 0.000861 loss_kpt: 0.000861 acc_pose: 0.892693 2023/08/09 18:00:37 - mmengine - INFO - Epoch(train) [165][260/442] lr: 5.000000e-04 eta: 1:58:10 time: 0.358866 data_time: 0.030846 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.786049 2023/08/09 18:00:41 - mmengine - INFO - Epoch(train) [165][270/442] lr: 5.000000e-04 eta: 1:58:06 time: 0.362147 data_time: 0.031324 memory: 4565 loss: 0.000870 loss_kpt: 0.000870 acc_pose: 0.902586 2023/08/09 18:00:44 - mmengine - INFO - Epoch(train) [165][280/442] lr: 5.000000e-04 eta: 1:58:03 time: 0.360551 data_time: 0.031268 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.821396 2023/08/09 18:00:48 - mmengine - INFO - Epoch(train) [165][290/442] lr: 5.000000e-04 eta: 1:57:59 time: 0.359588 data_time: 0.031314 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.872468 2023/08/09 18:00:51 - mmengine - INFO - Epoch(train) [165][300/442] lr: 5.000000e-04 eta: 1:57:56 time: 0.357087 data_time: 0.031264 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.801367 2023/08/09 18:00:55 - mmengine - INFO - Epoch(train) [165][310/442] lr: 5.000000e-04 eta: 1:57:52 time: 0.355005 data_time: 0.031315 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.841590 2023/08/09 18:00:59 - mmengine - INFO - Epoch(train) [165][320/442] lr: 5.000000e-04 eta: 1:57:49 time: 0.355075 data_time: 0.030869 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.903849 2023/08/09 18:01:02 - mmengine - INFO - Epoch(train) [165][330/442] lr: 5.000000e-04 eta: 1:57:45 time: 0.356005 data_time: 0.030557 memory: 4565 loss: 0.000878 loss_kpt: 0.000878 acc_pose: 0.886094 2023/08/09 18:01:06 - mmengine - INFO - Epoch(train) [165][340/442] lr: 5.000000e-04 eta: 1:57:42 time: 0.358054 data_time: 0.030749 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.890072 2023/08/09 18:01:09 - mmengine - INFO - Epoch(train) [165][350/442] lr: 5.000000e-04 eta: 1:57:38 time: 0.358422 data_time: 0.030719 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.922760 2023/08/09 18:01:13 - mmengine - INFO - Epoch(train) [165][360/442] lr: 5.000000e-04 eta: 1:57:35 time: 0.357968 data_time: 0.030616 memory: 4565 loss: 0.000880 loss_kpt: 0.000880 acc_pose: 0.843055 2023/08/09 18:01:16 - mmengine - INFO - Epoch(train) [165][370/442] lr: 5.000000e-04 eta: 1:57:31 time: 0.354088 data_time: 0.030501 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.889987 2023/08/09 18:01:20 - mmengine - INFO - Epoch(train) [165][380/442] lr: 5.000000e-04 eta: 1:57:27 time: 0.352949 data_time: 0.030501 memory: 4565 loss: 0.000890 loss_kpt: 0.000890 acc_pose: 0.838449 2023/08/09 18:01:24 - mmengine - INFO - Epoch(train) [165][390/442] lr: 5.000000e-04 eta: 1:57:24 time: 0.352661 data_time: 0.030434 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.828409 2023/08/09 18:01:27 - mmengine - INFO - Epoch(train) [165][400/442] lr: 5.000000e-04 eta: 1:57:20 time: 0.353628 data_time: 0.030608 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.853472 2023/08/09 18:01:31 - mmengine - INFO - Epoch(train) [165][410/442] lr: 5.000000e-04 eta: 1:57:17 time: 0.356815 data_time: 0.030625 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.877613 2023/08/09 18:01:34 - mmengine - INFO - Epoch(train) [165][420/442] lr: 5.000000e-04 eta: 1:57:13 time: 0.357043 data_time: 0.030704 memory: 4565 loss: 0.000880 loss_kpt: 0.000880 acc_pose: 0.889571 2023/08/09 18:01:38 - mmengine - INFO - Epoch(train) [165][430/442] lr: 5.000000e-04 eta: 1:57:10 time: 0.356993 data_time: 0.030673 memory: 4565 loss: 0.000871 loss_kpt: 0.000871 acc_pose: 0.824042 2023/08/09 18:01:41 - mmengine - INFO - Epoch(train) [165][440/442] lr: 5.000000e-04 eta: 1:57:06 time: 0.356532 data_time: 0.030605 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.854789 2023/08/09 18:01:42 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:01:46 - mmengine - INFO - Epoch(train) [166][ 10/442] lr: 5.000000e-04 eta: 1:57:02 time: 0.358008 data_time: 0.033952 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.898433 2023/08/09 18:01:49 - mmengine - INFO - Epoch(train) [166][ 20/442] lr: 5.000000e-04 eta: 1:56:59 time: 0.359407 data_time: 0.037323 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.860090 2023/08/09 18:01:53 - mmengine - INFO - Epoch(train) [166][ 30/442] lr: 5.000000e-04 eta: 1:56:55 time: 0.361027 data_time: 0.037639 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.810596 2023/08/09 18:01:57 - mmengine - INFO - Epoch(train) [166][ 40/442] lr: 5.000000e-04 eta: 1:56:52 time: 0.360867 data_time: 0.037581 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.775505 2023/08/09 18:02:00 - mmengine - INFO - Epoch(train) [166][ 50/442] lr: 5.000000e-04 eta: 1:56:48 time: 0.360986 data_time: 0.037876 memory: 4565 loss: 0.000888 loss_kpt: 0.000888 acc_pose: 0.871660 2023/08/09 18:02:04 - mmengine - INFO - Epoch(train) [166][ 60/442] lr: 5.000000e-04 eta: 1:56:45 time: 0.355779 data_time: 0.033965 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.889582 2023/08/09 18:02:07 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:02:07 - mmengine - INFO - Epoch(train) [166][ 70/442] lr: 5.000000e-04 eta: 1:56:41 time: 0.351733 data_time: 0.030626 memory: 4565 loss: 0.000887 loss_kpt: 0.000887 acc_pose: 0.862219 2023/08/09 18:02:11 - mmengine - INFO - Epoch(train) [166][ 80/442] lr: 5.000000e-04 eta: 1:56:38 time: 0.350112 data_time: 0.030320 memory: 4565 loss: 0.000881 loss_kpt: 0.000881 acc_pose: 0.827265 2023/08/09 18:02:14 - mmengine - INFO - Epoch(train) [166][ 90/442] lr: 5.000000e-04 eta: 1:56:34 time: 0.353013 data_time: 0.030539 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.815337 2023/08/09 18:02:18 - mmengine - INFO - Epoch(train) [166][100/442] lr: 5.000000e-04 eta: 1:56:31 time: 0.355180 data_time: 0.030532 memory: 4565 loss: 0.000875 loss_kpt: 0.000875 acc_pose: 0.750384 2023/08/09 18:02:21 - mmengine - INFO - Epoch(train) [166][110/442] lr: 5.000000e-04 eta: 1:56:27 time: 0.355671 data_time: 0.030656 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.802755 2023/08/09 18:02:25 - mmengine - INFO - Epoch(train) [166][120/442] lr: 5.000000e-04 eta: 1:56:24 time: 0.358240 data_time: 0.030392 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.838479 2023/08/09 18:02:28 - mmengine - INFO - Epoch(train) [166][130/442] lr: 5.000000e-04 eta: 1:56:20 time: 0.358407 data_time: 0.030475 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.807977 2023/08/09 18:02:32 - mmengine - INFO - Epoch(train) [166][140/442] lr: 5.000000e-04 eta: 1:56:17 time: 0.356530 data_time: 0.030549 memory: 4565 loss: 0.000833 loss_kpt: 0.000833 acc_pose: 0.911515 2023/08/09 18:02:36 - mmengine - INFO - Epoch(train) [166][150/442] lr: 5.000000e-04 eta: 1:56:13 time: 0.354796 data_time: 0.030915 memory: 4565 loss: 0.000828 loss_kpt: 0.000828 acc_pose: 0.778432 2023/08/09 18:02:39 - mmengine - INFO - Epoch(train) [166][160/442] lr: 5.000000e-04 eta: 1:56:10 time: 0.355149 data_time: 0.030881 memory: 4565 loss: 0.000830 loss_kpt: 0.000830 acc_pose: 0.850714 2023/08/09 18:02:43 - mmengine - INFO - Epoch(train) [166][170/442] lr: 5.000000e-04 eta: 1:56:06 time: 0.352524 data_time: 0.031124 memory: 4565 loss: 0.000822 loss_kpt: 0.000822 acc_pose: 0.912299 2023/08/09 18:02:46 - mmengine - INFO - Epoch(train) [166][180/442] lr: 5.000000e-04 eta: 1:56:03 time: 0.359392 data_time: 0.031305 memory: 4565 loss: 0.000821 loss_kpt: 0.000821 acc_pose: 0.838519 2023/08/09 18:02:50 - mmengine - INFO - Epoch(train) [166][190/442] lr: 5.000000e-04 eta: 1:56:00 time: 0.368840 data_time: 0.031532 memory: 4565 loss: 0.000839 loss_kpt: 0.000839 acc_pose: 0.941367 2023/08/09 18:02:54 - mmengine - INFO - Epoch(train) [166][200/442] lr: 5.000000e-04 eta: 1:55:56 time: 0.373011 data_time: 0.031263 memory: 4565 loss: 0.000845 loss_kpt: 0.000845 acc_pose: 0.842348 2023/08/09 18:02:58 - mmengine - INFO - Epoch(train) [166][210/442] lr: 5.000000e-04 eta: 1:55:53 time: 0.380891 data_time: 0.032477 memory: 4565 loss: 0.000839 loss_kpt: 0.000839 acc_pose: 0.881161 2023/08/09 18:03:02 - mmengine - INFO - Epoch(train) [166][220/442] lr: 5.000000e-04 eta: 1:55:50 time: 0.389333 data_time: 0.032837 memory: 4565 loss: 0.000840 loss_kpt: 0.000840 acc_pose: 0.887270 2023/08/09 18:03:06 - mmengine - INFO - Epoch(train) [166][230/442] lr: 5.000000e-04 eta: 1:55:47 time: 0.389943 data_time: 0.033107 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.865986 2023/08/09 18:03:10 - mmengine - INFO - Epoch(train) [166][240/442] lr: 5.000000e-04 eta: 1:55:43 time: 0.382557 data_time: 0.032922 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.841712 2023/08/09 18:03:13 - mmengine - INFO - Epoch(train) [166][250/442] lr: 5.000000e-04 eta: 1:55:40 time: 0.377184 data_time: 0.032822 memory: 4565 loss: 0.000843 loss_kpt: 0.000843 acc_pose: 0.866846 2023/08/09 18:03:17 - mmengine - INFO - Epoch(train) [166][260/442] lr: 5.000000e-04 eta: 1:55:36 time: 0.369541 data_time: 0.031801 memory: 4565 loss: 0.000848 loss_kpt: 0.000848 acc_pose: 0.849382 2023/08/09 18:03:21 - mmengine - INFO - Epoch(train) [166][270/442] lr: 5.000000e-04 eta: 1:55:33 time: 0.369510 data_time: 0.032013 memory: 4565 loss: 0.000855 loss_kpt: 0.000855 acc_pose: 0.882568 2023/08/09 18:03:24 - mmengine - INFO - Epoch(train) [166][280/442] lr: 5.000000e-04 eta: 1:55:29 time: 0.363588 data_time: 0.031468 memory: 4565 loss: 0.000837 loss_kpt: 0.000837 acc_pose: 0.921068 2023/08/09 18:03:28 - mmengine - INFO - Epoch(train) [166][290/442] lr: 5.000000e-04 eta: 1:55:26 time: 0.359638 data_time: 0.031117 memory: 4565 loss: 0.000841 loss_kpt: 0.000841 acc_pose: 0.866711 2023/08/09 18:03:31 - mmengine - INFO - Epoch(train) [166][300/442] lr: 5.000000e-04 eta: 1:55:22 time: 0.358769 data_time: 0.030883 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.813251 2023/08/09 18:03:35 - mmengine - INFO - Epoch(train) [166][310/442] lr: 5.000000e-04 eta: 1:55:19 time: 0.358147 data_time: 0.030680 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.780721 2023/08/09 18:03:38 - mmengine - INFO - Epoch(train) [166][320/442] lr: 5.000000e-04 eta: 1:55:15 time: 0.349900 data_time: 0.029960 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.845572 2023/08/09 18:03:42 - mmengine - INFO - Epoch(train) [166][330/442] lr: 5.000000e-04 eta: 1:55:12 time: 0.351648 data_time: 0.030165 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.862688 2023/08/09 18:03:45 - mmengine - INFO - Epoch(train) [166][340/442] lr: 5.000000e-04 eta: 1:55:08 time: 0.354256 data_time: 0.030239 memory: 4565 loss: 0.000900 loss_kpt: 0.000900 acc_pose: 0.799013 2023/08/09 18:03:49 - mmengine - INFO - Epoch(train) [166][350/442] lr: 5.000000e-04 eta: 1:55:05 time: 0.358271 data_time: 0.033773 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.809134 2023/08/09 18:03:53 - mmengine - INFO - Epoch(train) [166][360/442] lr: 5.000000e-04 eta: 1:55:01 time: 0.358244 data_time: 0.033929 memory: 4565 loss: 0.000902 loss_kpt: 0.000902 acc_pose: 0.863617 2023/08/09 18:03:56 - mmengine - INFO - Epoch(train) [166][370/442] lr: 5.000000e-04 eta: 1:54:57 time: 0.358359 data_time: 0.034270 memory: 4565 loss: 0.000898 loss_kpt: 0.000898 acc_pose: 0.823024 2023/08/09 18:04:00 - mmengine - INFO - Epoch(train) [166][380/442] lr: 5.000000e-04 eta: 1:54:54 time: 0.355290 data_time: 0.034283 memory: 4565 loss: 0.000892 loss_kpt: 0.000892 acc_pose: 0.787740 2023/08/09 18:04:03 - mmengine - INFO - Epoch(train) [166][390/442] lr: 5.000000e-04 eta: 1:54:50 time: 0.354509 data_time: 0.034575 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.886166 2023/08/09 18:04:07 - mmengine - INFO - Epoch(train) [166][400/442] lr: 5.000000e-04 eta: 1:54:47 time: 0.353689 data_time: 0.031244 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.819872 2023/08/09 18:04:10 - mmengine - INFO - Epoch(train) [166][410/442] lr: 5.000000e-04 eta: 1:54:43 time: 0.354731 data_time: 0.031326 memory: 4565 loss: 0.000848 loss_kpt: 0.000848 acc_pose: 0.897153 2023/08/09 18:04:14 - mmengine - INFO - Epoch(train) [166][420/442] lr: 5.000000e-04 eta: 1:54:40 time: 0.353884 data_time: 0.030985 memory: 4565 loss: 0.000842 loss_kpt: 0.000842 acc_pose: 0.879870 2023/08/09 18:04:17 - mmengine - INFO - Epoch(train) [166][430/442] lr: 5.000000e-04 eta: 1:54:36 time: 0.353300 data_time: 0.030978 memory: 4565 loss: 0.000837 loss_kpt: 0.000837 acc_pose: 0.892270 2023/08/09 18:04:21 - mmengine - INFO - Epoch(train) [166][440/442] lr: 5.000000e-04 eta: 1:54:33 time: 0.352203 data_time: 0.030537 memory: 4565 loss: 0.000843 loss_kpt: 0.000843 acc_pose: 0.901623 2023/08/09 18:04:21 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:04:25 - mmengine - INFO - Epoch(train) [167][ 10/442] lr: 5.000000e-04 eta: 1:54:29 time: 0.357730 data_time: 0.034430 memory: 4565 loss: 0.000858 loss_kpt: 0.000858 acc_pose: 0.831539 2023/08/09 18:04:29 - mmengine - INFO - Epoch(train) [167][ 20/442] lr: 5.000000e-04 eta: 1:54:25 time: 0.357950 data_time: 0.034761 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.873114 2023/08/09 18:04:32 - mmengine - INFO - Epoch(train) [167][ 30/442] lr: 5.000000e-04 eta: 1:54:22 time: 0.360501 data_time: 0.034874 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.879379 2023/08/09 18:04:36 - mmengine - INFO - Epoch(train) [167][ 40/442] lr: 5.000000e-04 eta: 1:54:18 time: 0.361193 data_time: 0.034888 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.802485 2023/08/09 18:04:39 - mmengine - INFO - Epoch(train) [167][ 50/442] lr: 5.000000e-04 eta: 1:54:15 time: 0.361923 data_time: 0.035201 memory: 4565 loss: 0.000847 loss_kpt: 0.000847 acc_pose: 0.924583 2023/08/09 18:04:43 - mmengine - INFO - Epoch(train) [167][ 60/442] lr: 5.000000e-04 eta: 1:54:11 time: 0.353955 data_time: 0.031036 memory: 4565 loss: 0.000834 loss_kpt: 0.000834 acc_pose: 0.888468 2023/08/09 18:04:47 - mmengine - INFO - Epoch(train) [167][ 70/442] lr: 5.000000e-04 eta: 1:54:08 time: 0.353660 data_time: 0.030903 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.817749 2023/08/09 18:04:50 - mmengine - INFO - Epoch(train) [167][ 80/442] lr: 5.000000e-04 eta: 1:54:04 time: 0.351582 data_time: 0.030921 memory: 4565 loss: 0.000864 loss_kpt: 0.000864 acc_pose: 0.842213 2023/08/09 18:04:54 - mmengine - INFO - Epoch(train) [167][ 90/442] lr: 5.000000e-04 eta: 1:54:01 time: 0.354796 data_time: 0.031623 memory: 4565 loss: 0.000854 loss_kpt: 0.000854 acc_pose: 0.870420 2023/08/09 18:04:57 - mmengine - INFO - Epoch(train) [167][100/442] lr: 5.000000e-04 eta: 1:53:57 time: 0.358793 data_time: 0.034987 memory: 4565 loss: 0.000861 loss_kpt: 0.000861 acc_pose: 0.769597 2023/08/09 18:05:01 - mmengine - INFO - Epoch(train) [167][110/442] lr: 5.000000e-04 eta: 1:53:54 time: 0.357688 data_time: 0.035013 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.870087 2023/08/09 18:05:04 - mmengine - INFO - Epoch(train) [167][120/442] lr: 5.000000e-04 eta: 1:53:50 time: 0.358055 data_time: 0.034804 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.775539 2023/08/09 18:05:08 - mmengine - INFO - Epoch(train) [167][130/442] lr: 5.000000e-04 eta: 1:53:47 time: 0.358734 data_time: 0.034691 memory: 4565 loss: 0.000864 loss_kpt: 0.000864 acc_pose: 0.841453 2023/08/09 18:05:12 - mmengine - INFO - Epoch(train) [167][140/442] lr: 5.000000e-04 eta: 1:53:43 time: 0.358641 data_time: 0.034146 memory: 4565 loss: 0.000858 loss_kpt: 0.000858 acc_pose: 0.908176 2023/08/09 18:05:16 - mmengine - INFO - Epoch(train) [167][150/442] lr: 5.000000e-04 eta: 1:53:40 time: 0.364172 data_time: 0.031327 memory: 4565 loss: 0.000864 loss_kpt: 0.000864 acc_pose: 0.879705 2023/08/09 18:05:19 - mmengine - INFO - Epoch(train) [167][160/442] lr: 5.000000e-04 eta: 1:53:36 time: 0.365552 data_time: 0.031304 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.859409 2023/08/09 18:05:23 - mmengine - INFO - Epoch(train) [167][170/442] lr: 5.000000e-04 eta: 1:53:33 time: 0.366363 data_time: 0.031842 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.806444 2023/08/09 18:05:26 - mmengine - INFO - Epoch(train) [167][180/442] lr: 5.000000e-04 eta: 1:53:29 time: 0.366747 data_time: 0.032393 memory: 4565 loss: 0.000871 loss_kpt: 0.000871 acc_pose: 0.873851 2023/08/09 18:05:30 - mmengine - INFO - Epoch(train) [167][190/442] lr: 5.000000e-04 eta: 1:53:26 time: 0.364657 data_time: 0.032807 memory: 4565 loss: 0.000864 loss_kpt: 0.000864 acc_pose: 0.896866 2023/08/09 18:05:34 - mmengine - INFO - Epoch(train) [167][200/442] lr: 5.000000e-04 eta: 1:53:22 time: 0.359884 data_time: 0.032612 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.882276 2023/08/09 18:05:37 - mmengine - INFO - Epoch(train) [167][210/442] lr: 5.000000e-04 eta: 1:53:19 time: 0.358607 data_time: 0.032690 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.826459 2023/08/09 18:05:41 - mmengine - INFO - Epoch(train) [167][220/442] lr: 5.000000e-04 eta: 1:53:15 time: 0.357780 data_time: 0.032258 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.936249 2023/08/09 18:05:44 - mmengine - INFO - Epoch(train) [167][230/442] lr: 5.000000e-04 eta: 1:53:12 time: 0.356494 data_time: 0.031752 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.776205 2023/08/09 18:05:48 - mmengine - INFO - Epoch(train) [167][240/442] lr: 5.000000e-04 eta: 1:53:08 time: 0.355884 data_time: 0.031189 memory: 4565 loss: 0.000861 loss_kpt: 0.000861 acc_pose: 0.866691 2023/08/09 18:05:51 - mmengine - INFO - Epoch(train) [167][250/442] lr: 5.000000e-04 eta: 1:53:05 time: 0.352165 data_time: 0.031169 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.852234 2023/08/09 18:05:55 - mmengine - INFO - Epoch(train) [167][260/442] lr: 5.000000e-04 eta: 1:53:01 time: 0.352970 data_time: 0.031036 memory: 4565 loss: 0.000856 loss_kpt: 0.000856 acc_pose: 0.869132 2023/08/09 18:05:58 - mmengine - INFO - Epoch(train) [167][270/442] lr: 5.000000e-04 eta: 1:52:58 time: 0.355315 data_time: 0.031485 memory: 4565 loss: 0.000866 loss_kpt: 0.000866 acc_pose: 0.907118 2023/08/09 18:06:02 - mmengine - INFO - Epoch(train) [167][280/442] lr: 5.000000e-04 eta: 1:52:54 time: 0.357201 data_time: 0.031668 memory: 4565 loss: 0.000848 loss_kpt: 0.000848 acc_pose: 0.891026 2023/08/09 18:06:06 - mmengine - INFO - Epoch(train) [167][290/442] lr: 5.000000e-04 eta: 1:52:51 time: 0.356224 data_time: 0.031678 memory: 4565 loss: 0.000852 loss_kpt: 0.000852 acc_pose: 0.865759 2023/08/09 18:06:09 - mmengine - INFO - Epoch(train) [167][300/442] lr: 5.000000e-04 eta: 1:52:47 time: 0.357703 data_time: 0.034424 memory: 4565 loss: 0.000855 loss_kpt: 0.000855 acc_pose: 0.869073 2023/08/09 18:06:13 - mmengine - INFO - Epoch(train) [167][310/442] lr: 5.000000e-04 eta: 1:52:44 time: 0.355796 data_time: 0.034280 memory: 4565 loss: 0.000840 loss_kpt: 0.000840 acc_pose: 0.907276 2023/08/09 18:06:16 - mmengine - INFO - Epoch(train) [167][320/442] lr: 5.000000e-04 eta: 1:52:40 time: 0.352652 data_time: 0.033839 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.885321 2023/08/09 18:06:20 - mmengine - INFO - Epoch(train) [167][330/442] lr: 5.000000e-04 eta: 1:52:37 time: 0.352782 data_time: 0.033567 memory: 4565 loss: 0.000858 loss_kpt: 0.000858 acc_pose: 0.879784 2023/08/09 18:06:23 - mmengine - INFO - Epoch(train) [167][340/442] lr: 5.000000e-04 eta: 1:52:33 time: 0.353535 data_time: 0.034296 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.878925 2023/08/09 18:06:27 - mmengine - INFO - Epoch(train) [167][350/442] lr: 5.000000e-04 eta: 1:52:30 time: 0.355721 data_time: 0.031251 memory: 4565 loss: 0.000854 loss_kpt: 0.000854 acc_pose: 0.889228 2023/08/09 18:06:30 - mmengine - INFO - Epoch(train) [167][360/442] lr: 5.000000e-04 eta: 1:52:26 time: 0.355892 data_time: 0.031279 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.754071 2023/08/09 18:06:34 - mmengine - INFO - Epoch(train) [167][370/442] lr: 5.000000e-04 eta: 1:52:23 time: 0.357205 data_time: 0.031170 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.933476 2023/08/09 18:06:38 - mmengine - INFO - Epoch(train) [167][380/442] lr: 5.000000e-04 eta: 1:52:19 time: 0.355643 data_time: 0.031167 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.904196 2023/08/09 18:06:41 - mmengine - INFO - Epoch(train) [167][390/442] lr: 5.000000e-04 eta: 1:52:15 time: 0.355452 data_time: 0.030570 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.865246 2023/08/09 18:06:45 - mmengine - INFO - Epoch(train) [167][400/442] lr: 5.000000e-04 eta: 1:52:12 time: 0.351557 data_time: 0.030541 memory: 4565 loss: 0.000854 loss_kpt: 0.000854 acc_pose: 0.825714 2023/08/09 18:06:48 - mmengine - INFO - Epoch(train) [167][410/442] lr: 5.000000e-04 eta: 1:52:09 time: 0.356176 data_time: 0.030710 memory: 4565 loss: 0.000861 loss_kpt: 0.000861 acc_pose: 0.889337 2023/08/09 18:06:52 - mmengine - INFO - Epoch(train) [167][420/442] lr: 5.000000e-04 eta: 1:52:05 time: 0.355365 data_time: 0.030772 memory: 4565 loss: 0.000877 loss_kpt: 0.000877 acc_pose: 0.881776 2023/08/09 18:06:55 - mmengine - INFO - Epoch(train) [167][430/442] lr: 5.000000e-04 eta: 1:52:01 time: 0.354919 data_time: 0.030792 memory: 4565 loss: 0.000866 loss_kpt: 0.000866 acc_pose: 0.930802 2023/08/09 18:06:59 - mmengine - INFO - Epoch(train) [167][440/442] lr: 5.000000e-04 eta: 1:51:58 time: 0.353633 data_time: 0.030700 memory: 4565 loss: 0.000871 loss_kpt: 0.000871 acc_pose: 0.870942 2023/08/09 18:06:59 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:07:03 - mmengine - INFO - Epoch(train) [168][ 10/442] lr: 5.000000e-04 eta: 1:51:54 time: 0.354901 data_time: 0.034040 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.883455 2023/08/09 18:07:07 - mmengine - INFO - Epoch(train) [168][ 20/442] lr: 5.000000e-04 eta: 1:51:50 time: 0.352723 data_time: 0.034195 memory: 4565 loss: 0.000864 loss_kpt: 0.000864 acc_pose: 0.824486 2023/08/09 18:07:10 - mmengine - INFO - Epoch(train) [168][ 30/442] lr: 5.000000e-04 eta: 1:51:47 time: 0.353948 data_time: 0.034359 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.876812 2023/08/09 18:07:14 - mmengine - INFO - Epoch(train) [168][ 40/442] lr: 5.000000e-04 eta: 1:51:43 time: 0.365834 data_time: 0.035081 memory: 4565 loss: 0.000845 loss_kpt: 0.000845 acc_pose: 0.855742 2023/08/09 18:07:18 - mmengine - INFO - Epoch(train) [168][ 50/442] lr: 5.000000e-04 eta: 1:51:40 time: 0.372000 data_time: 0.035810 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.834588 2023/08/09 18:07:22 - mmengine - INFO - Epoch(train) [168][ 60/442] lr: 5.000000e-04 eta: 1:51:37 time: 0.374803 data_time: 0.035806 memory: 4565 loss: 0.000835 loss_kpt: 0.000835 acc_pose: 0.829424 2023/08/09 18:07:25 - mmengine - INFO - Epoch(train) [168][ 70/442] lr: 5.000000e-04 eta: 1:51:33 time: 0.374577 data_time: 0.035676 memory: 4565 loss: 0.000838 loss_kpt: 0.000838 acc_pose: 0.826445 2023/08/09 18:07:29 - mmengine - INFO - Epoch(train) [168][ 80/442] lr: 5.000000e-04 eta: 1:51:30 time: 0.375099 data_time: 0.035962 memory: 4565 loss: 0.000836 loss_kpt: 0.000836 acc_pose: 0.886127 2023/08/09 18:07:33 - mmengine - INFO - Epoch(train) [168][ 90/442] lr: 5.000000e-04 eta: 1:51:26 time: 0.364522 data_time: 0.035238 memory: 4565 loss: 0.000858 loss_kpt: 0.000858 acc_pose: 0.860116 2023/08/09 18:07:36 - mmengine - INFO - Epoch(train) [168][100/442] lr: 5.000000e-04 eta: 1:51:23 time: 0.361275 data_time: 0.035122 memory: 4565 loss: 0.000856 loss_kpt: 0.000856 acc_pose: 0.824166 2023/08/09 18:07:40 - mmengine - INFO - Epoch(train) [168][110/442] lr: 5.000000e-04 eta: 1:51:19 time: 0.354680 data_time: 0.031446 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.858381 2023/08/09 18:07:43 - mmengine - INFO - Epoch(train) [168][120/442] lr: 5.000000e-04 eta: 1:51:16 time: 0.355661 data_time: 0.031381 memory: 4565 loss: 0.000856 loss_kpt: 0.000856 acc_pose: 0.851427 2023/08/09 18:07:47 - mmengine - INFO - Epoch(train) [168][130/442] lr: 5.000000e-04 eta: 1:51:12 time: 0.353792 data_time: 0.031115 memory: 4565 loss: 0.000835 loss_kpt: 0.000835 acc_pose: 0.864703 2023/08/09 18:07:50 - mmengine - INFO - Epoch(train) [168][140/442] lr: 5.000000e-04 eta: 1:51:09 time: 0.354958 data_time: 0.031238 memory: 4565 loss: 0.000823 loss_kpt: 0.000823 acc_pose: 0.848117 2023/08/09 18:07:54 - mmengine - INFO - Epoch(train) [168][150/442] lr: 5.000000e-04 eta: 1:51:05 time: 0.355686 data_time: 0.031115 memory: 4565 loss: 0.000823 loss_kpt: 0.000823 acc_pose: 0.888280 2023/08/09 18:07:57 - mmengine - INFO - Epoch(train) [168][160/442] lr: 5.000000e-04 eta: 1:51:02 time: 0.357086 data_time: 0.031179 memory: 4565 loss: 0.000837 loss_kpt: 0.000837 acc_pose: 0.781249 2023/08/09 18:08:01 - mmengine - INFO - Epoch(train) [168][170/442] lr: 5.000000e-04 eta: 1:50:58 time: 0.356377 data_time: 0.031633 memory: 4565 loss: 0.000845 loss_kpt: 0.000845 acc_pose: 0.859435 2023/08/09 18:08:05 - mmengine - INFO - Epoch(train) [168][180/442] lr: 5.000000e-04 eta: 1:50:55 time: 0.356420 data_time: 0.031441 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.853670 2023/08/09 18:08:07 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:08:08 - mmengine - INFO - Epoch(train) [168][190/442] lr: 5.000000e-04 eta: 1:50:51 time: 0.354765 data_time: 0.031332 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.914256 2023/08/09 18:08:12 - mmengine - INFO - Epoch(train) [168][200/442] lr: 5.000000e-04 eta: 1:50:47 time: 0.356093 data_time: 0.031262 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.786009 2023/08/09 18:08:15 - mmengine - INFO - Epoch(train) [168][210/442] lr: 5.000000e-04 eta: 1:50:44 time: 0.355909 data_time: 0.031298 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.812125 2023/08/09 18:08:19 - mmengine - INFO - Epoch(train) [168][220/442] lr: 5.000000e-04 eta: 1:50:40 time: 0.356333 data_time: 0.031355 memory: 4565 loss: 0.000846 loss_kpt: 0.000846 acc_pose: 0.856821 2023/08/09 18:08:22 - mmengine - INFO - Epoch(train) [168][230/442] lr: 5.000000e-04 eta: 1:50:37 time: 0.356517 data_time: 0.031298 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.856139 2023/08/09 18:08:26 - mmengine - INFO - Epoch(train) [168][240/442] lr: 5.000000e-04 eta: 1:50:33 time: 0.356859 data_time: 0.031464 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.893686 2023/08/09 18:08:29 - mmengine - INFO - Epoch(train) [168][250/442] lr: 5.000000e-04 eta: 1:50:30 time: 0.354383 data_time: 0.031436 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.784354 2023/08/09 18:08:33 - mmengine - INFO - Epoch(train) [168][260/442] lr: 5.000000e-04 eta: 1:50:26 time: 0.356132 data_time: 0.034558 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.776779 2023/08/09 18:08:37 - mmengine - INFO - Epoch(train) [168][270/442] lr: 5.000000e-04 eta: 1:50:23 time: 0.355444 data_time: 0.034018 memory: 4565 loss: 0.000855 loss_kpt: 0.000855 acc_pose: 0.878478 2023/08/09 18:08:40 - mmengine - INFO - Epoch(train) [168][280/442] lr: 5.000000e-04 eta: 1:50:19 time: 0.354986 data_time: 0.034203 memory: 4565 loss: 0.000853 loss_kpt: 0.000853 acc_pose: 0.934615 2023/08/09 18:08:44 - mmengine - INFO - Epoch(train) [168][290/442] lr: 5.000000e-04 eta: 1:50:16 time: 0.356086 data_time: 0.034198 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.913545 2023/08/09 18:08:47 - mmengine - INFO - Epoch(train) [168][300/442] lr: 5.000000e-04 eta: 1:50:12 time: 0.356498 data_time: 0.034167 memory: 4565 loss: 0.000838 loss_kpt: 0.000838 acc_pose: 0.875300 2023/08/09 18:08:51 - mmengine - INFO - Epoch(train) [168][310/442] lr: 5.000000e-04 eta: 1:50:09 time: 0.355864 data_time: 0.031386 memory: 4565 loss: 0.000838 loss_kpt: 0.000838 acc_pose: 0.842430 2023/08/09 18:08:54 - mmengine - INFO - Epoch(train) [168][320/442] lr: 5.000000e-04 eta: 1:50:05 time: 0.356959 data_time: 0.031438 memory: 4565 loss: 0.000822 loss_kpt: 0.000822 acc_pose: 0.849051 2023/08/09 18:08:58 - mmengine - INFO - Epoch(train) [168][330/442] lr: 5.000000e-04 eta: 1:50:02 time: 0.358399 data_time: 0.031404 memory: 4565 loss: 0.000816 loss_kpt: 0.000816 acc_pose: 0.900796 2023/08/09 18:09:02 - mmengine - INFO - Epoch(train) [168][340/442] lr: 5.000000e-04 eta: 1:49:58 time: 0.357749 data_time: 0.031538 memory: 4565 loss: 0.000814 loss_kpt: 0.000814 acc_pose: 0.905290 2023/08/09 18:09:05 - mmengine - INFO - Epoch(train) [168][350/442] lr: 5.000000e-04 eta: 1:49:55 time: 0.358545 data_time: 0.031818 memory: 4565 loss: 0.000834 loss_kpt: 0.000834 acc_pose: 0.781993 2023/08/09 18:09:09 - mmengine - INFO - Epoch(train) [168][360/442] lr: 5.000000e-04 eta: 1:49:51 time: 0.359247 data_time: 0.031326 memory: 4565 loss: 0.000846 loss_kpt: 0.000846 acc_pose: 0.831390 2023/08/09 18:09:12 - mmengine - INFO - Epoch(train) [168][370/442] lr: 5.000000e-04 eta: 1:49:48 time: 0.357512 data_time: 0.031238 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.864774 2023/08/09 18:09:16 - mmengine - INFO - Epoch(train) [168][380/442] lr: 5.000000e-04 eta: 1:49:44 time: 0.356823 data_time: 0.031196 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.882682 2023/08/09 18:09:19 - mmengine - INFO - Epoch(train) [168][390/442] lr: 5.000000e-04 eta: 1:49:41 time: 0.356441 data_time: 0.030851 memory: 4565 loss: 0.000878 loss_kpt: 0.000878 acc_pose: 0.862804 2023/08/09 18:09:23 - mmengine - INFO - Epoch(train) [168][400/442] lr: 5.000000e-04 eta: 1:49:37 time: 0.355896 data_time: 0.030811 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.914043 2023/08/09 18:09:26 - mmengine - INFO - Epoch(train) [168][410/442] lr: 5.000000e-04 eta: 1:49:34 time: 0.352728 data_time: 0.030822 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.842033 2023/08/09 18:09:30 - mmengine - INFO - Epoch(train) [168][420/442] lr: 5.000000e-04 eta: 1:49:30 time: 0.354509 data_time: 0.031147 memory: 4565 loss: 0.000853 loss_kpt: 0.000853 acc_pose: 0.877811 2023/08/09 18:09:34 - mmengine - INFO - Epoch(train) [168][430/442] lr: 5.000000e-04 eta: 1:49:27 time: 0.353126 data_time: 0.031004 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.858323 2023/08/09 18:09:37 - mmengine - INFO - Epoch(train) [168][440/442] lr: 5.000000e-04 eta: 1:49:23 time: 0.352672 data_time: 0.030884 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.851704 2023/08/09 18:09:38 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:09:42 - mmengine - INFO - Epoch(train) [169][ 10/442] lr: 5.000000e-04 eta: 1:49:19 time: 0.358376 data_time: 0.034314 memory: 4565 loss: 0.000838 loss_kpt: 0.000838 acc_pose: 0.857485 2023/08/09 18:09:45 - mmengine - INFO - Epoch(train) [169][ 20/442] lr: 5.000000e-04 eta: 1:49:16 time: 0.359900 data_time: 0.034056 memory: 4565 loss: 0.000835 loss_kpt: 0.000835 acc_pose: 0.903278 2023/08/09 18:09:49 - mmengine - INFO - Epoch(train) [169][ 30/442] lr: 5.000000e-04 eta: 1:49:12 time: 0.360913 data_time: 0.034208 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.858412 2023/08/09 18:09:52 - mmengine - INFO - Epoch(train) [169][ 40/442] lr: 5.000000e-04 eta: 1:49:08 time: 0.362265 data_time: 0.034731 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.774945 2023/08/09 18:09:56 - mmengine - INFO - Epoch(train) [169][ 50/442] lr: 5.000000e-04 eta: 1:49:05 time: 0.364300 data_time: 0.035173 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.789093 2023/08/09 18:09:59 - mmengine - INFO - Epoch(train) [169][ 60/442] lr: 5.000000e-04 eta: 1:49:01 time: 0.356875 data_time: 0.030982 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.909879 2023/08/09 18:10:03 - mmengine - INFO - Epoch(train) [169][ 70/442] lr: 5.000000e-04 eta: 1:48:58 time: 0.357081 data_time: 0.030922 memory: 4565 loss: 0.000873 loss_kpt: 0.000873 acc_pose: 0.860403 2023/08/09 18:10:07 - mmengine - INFO - Epoch(train) [169][ 80/442] lr: 5.000000e-04 eta: 1:48:54 time: 0.355773 data_time: 0.030863 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.905111 2023/08/09 18:10:10 - mmengine - INFO - Epoch(train) [169][ 90/442] lr: 5.000000e-04 eta: 1:48:51 time: 0.357037 data_time: 0.030528 memory: 4565 loss: 0.000878 loss_kpt: 0.000878 acc_pose: 0.898495 2023/08/09 18:10:14 - mmengine - INFO - Epoch(train) [169][100/442] lr: 5.000000e-04 eta: 1:48:47 time: 0.358357 data_time: 0.030934 memory: 4565 loss: 0.000876 loss_kpt: 0.000876 acc_pose: 0.816795 2023/08/09 18:10:17 - mmengine - INFO - Epoch(train) [169][110/442] lr: 5.000000e-04 eta: 1:48:44 time: 0.358268 data_time: 0.031647 memory: 4565 loss: 0.000870 loss_kpt: 0.000870 acc_pose: 0.918933 2023/08/09 18:10:21 - mmengine - INFO - Epoch(train) [169][120/442] lr: 5.000000e-04 eta: 1:48:40 time: 0.354502 data_time: 0.031685 memory: 4565 loss: 0.000861 loss_kpt: 0.000861 acc_pose: 0.905225 2023/08/09 18:10:24 - mmengine - INFO - Epoch(train) [169][130/442] lr: 5.000000e-04 eta: 1:48:37 time: 0.353282 data_time: 0.031487 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.865916 2023/08/09 18:10:28 - mmengine - INFO - Epoch(train) [169][140/442] lr: 5.000000e-04 eta: 1:48:33 time: 0.350587 data_time: 0.031334 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.839786 2023/08/09 18:10:31 - mmengine - INFO - Epoch(train) [169][150/442] lr: 5.000000e-04 eta: 1:48:30 time: 0.349736 data_time: 0.031182 memory: 4565 loss: 0.000830 loss_kpt: 0.000830 acc_pose: 0.798514 2023/08/09 18:10:35 - mmengine - INFO - Epoch(train) [169][160/442] lr: 5.000000e-04 eta: 1:48:26 time: 0.349025 data_time: 0.030551 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.800954 2023/08/09 18:10:38 - mmengine - INFO - Epoch(train) [169][170/442] lr: 5.000000e-04 eta: 1:48:23 time: 0.350992 data_time: 0.030529 memory: 4565 loss: 0.000853 loss_kpt: 0.000853 acc_pose: 0.892957 2023/08/09 18:10:42 - mmengine - INFO - Epoch(train) [169][180/442] lr: 5.000000e-04 eta: 1:48:19 time: 0.351863 data_time: 0.030429 memory: 4565 loss: 0.000858 loss_kpt: 0.000858 acc_pose: 0.787517 2023/08/09 18:10:45 - mmengine - INFO - Epoch(train) [169][190/442] lr: 5.000000e-04 eta: 1:48:15 time: 0.351921 data_time: 0.030369 memory: 4565 loss: 0.000859 loss_kpt: 0.000859 acc_pose: 0.849942 2023/08/09 18:10:49 - mmengine - INFO - Epoch(train) [169][200/442] lr: 5.000000e-04 eta: 1:48:12 time: 0.351110 data_time: 0.029994 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.766927 2023/08/09 18:10:53 - mmengine - INFO - Epoch(train) [169][210/442] lr: 5.000000e-04 eta: 1:48:08 time: 0.354208 data_time: 0.030190 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.861979 2023/08/09 18:10:56 - mmengine - INFO - Epoch(train) [169][220/442] lr: 5.000000e-04 eta: 1:48:05 time: 0.353977 data_time: 0.030523 memory: 4565 loss: 0.000866 loss_kpt: 0.000866 acc_pose: 0.902316 2023/08/09 18:11:00 - mmengine - INFO - Epoch(train) [169][230/442] lr: 5.000000e-04 eta: 1:48:01 time: 0.354450 data_time: 0.030959 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.813074 2023/08/09 18:11:03 - mmengine - INFO - Epoch(train) [169][240/442] lr: 5.000000e-04 eta: 1:47:58 time: 0.354861 data_time: 0.031442 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.870227 2023/08/09 18:11:07 - mmengine - INFO - Epoch(train) [169][250/442] lr: 5.000000e-04 eta: 1:47:54 time: 0.354254 data_time: 0.031554 memory: 4565 loss: 0.000850 loss_kpt: 0.000850 acc_pose: 0.829157 2023/08/09 18:11:10 - mmengine - INFO - Epoch(train) [169][260/442] lr: 5.000000e-04 eta: 1:47:51 time: 0.353343 data_time: 0.034731 memory: 4565 loss: 0.000863 loss_kpt: 0.000863 acc_pose: 0.839527 2023/08/09 18:11:14 - mmengine - INFO - Epoch(train) [169][270/442] lr: 5.000000e-04 eta: 1:47:47 time: 0.353448 data_time: 0.034595 memory: 4565 loss: 0.000870 loss_kpt: 0.000870 acc_pose: 0.816414 2023/08/09 18:11:17 - mmengine - INFO - Epoch(train) [169][280/442] lr: 5.000000e-04 eta: 1:47:44 time: 0.355221 data_time: 0.034828 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.852827 2023/08/09 18:11:21 - mmengine - INFO - Epoch(train) [169][290/442] lr: 5.000000e-04 eta: 1:47:40 time: 0.356124 data_time: 0.034797 memory: 4565 loss: 0.000885 loss_kpt: 0.000885 acc_pose: 0.798614 2023/08/09 18:11:25 - mmengine - INFO - Epoch(train) [169][300/442] lr: 5.000000e-04 eta: 1:47:37 time: 0.357532 data_time: 0.035126 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.808574 2023/08/09 18:11:28 - mmengine - INFO - Epoch(train) [169][310/442] lr: 5.000000e-04 eta: 1:47:33 time: 0.357658 data_time: 0.031731 memory: 4565 loss: 0.000884 loss_kpt: 0.000884 acc_pose: 0.811049 2023/08/09 18:11:32 - mmengine - INFO - Epoch(train) [169][320/442] lr: 5.000000e-04 eta: 1:47:30 time: 0.356672 data_time: 0.031502 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.875489 2023/08/09 18:11:35 - mmengine - INFO - Epoch(train) [169][330/442] lr: 5.000000e-04 eta: 1:47:26 time: 0.355265 data_time: 0.030901 memory: 4565 loss: 0.000861 loss_kpt: 0.000861 acc_pose: 0.871424 2023/08/09 18:11:39 - mmengine - INFO - Epoch(train) [169][340/442] lr: 5.000000e-04 eta: 1:47:23 time: 0.354744 data_time: 0.030837 memory: 4565 loss: 0.000842 loss_kpt: 0.000842 acc_pose: 0.903364 2023/08/09 18:11:42 - mmengine - INFO - Epoch(train) [169][350/442] lr: 5.000000e-04 eta: 1:47:19 time: 0.354417 data_time: 0.030701 memory: 4565 loss: 0.000842 loss_kpt: 0.000842 acc_pose: 0.844542 2023/08/09 18:11:46 - mmengine - INFO - Epoch(train) [169][360/442] lr: 5.000000e-04 eta: 1:47:16 time: 0.353542 data_time: 0.030945 memory: 4565 loss: 0.000856 loss_kpt: 0.000856 acc_pose: 0.866891 2023/08/09 18:11:49 - mmengine - INFO - Epoch(train) [169][370/442] lr: 5.000000e-04 eta: 1:47:12 time: 0.352830 data_time: 0.031166 memory: 4565 loss: 0.000869 loss_kpt: 0.000869 acc_pose: 0.839701 2023/08/09 18:11:53 - mmengine - INFO - Epoch(train) [169][380/442] lr: 5.000000e-04 eta: 1:47:08 time: 0.351548 data_time: 0.031266 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.826343 2023/08/09 18:11:56 - mmengine - INFO - Epoch(train) [169][390/442] lr: 5.000000e-04 eta: 1:47:05 time: 0.351769 data_time: 0.030961 memory: 4565 loss: 0.000886 loss_kpt: 0.000886 acc_pose: 0.830645 2023/08/09 18:12:00 - mmengine - INFO - Epoch(train) [169][400/442] lr: 5.000000e-04 eta: 1:47:01 time: 0.350958 data_time: 0.030839 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.820124 2023/08/09 18:12:03 - mmengine - INFO - Epoch(train) [169][410/442] lr: 5.000000e-04 eta: 1:46:58 time: 0.350952 data_time: 0.030710 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.858665 2023/08/09 18:12:07 - mmengine - INFO - Epoch(train) [169][420/442] lr: 5.000000e-04 eta: 1:46:54 time: 0.352946 data_time: 0.030850 memory: 4565 loss: 0.000882 loss_kpt: 0.000882 acc_pose: 0.895457 2023/08/09 18:12:11 - mmengine - INFO - Epoch(train) [169][430/442] lr: 5.000000e-04 eta: 1:46:51 time: 0.355345 data_time: 0.031048 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.876320 2023/08/09 18:12:14 - mmengine - INFO - Epoch(train) [169][440/442] lr: 5.000000e-04 eta: 1:46:47 time: 0.354949 data_time: 0.030890 memory: 4565 loss: 0.000879 loss_kpt: 0.000879 acc_pose: 0.858222 2023/08/09 18:12:15 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:12:18 - mmengine - INFO - Epoch(train) [170][ 10/442] lr: 5.000000e-04 eta: 1:46:43 time: 0.357157 data_time: 0.034100 memory: 4565 loss: 0.000858 loss_kpt: 0.000858 acc_pose: 0.872028 2023/08/09 18:12:22 - mmengine - INFO - Epoch(train) [170][ 20/442] lr: 5.000000e-04 eta: 1:46:40 time: 0.360364 data_time: 0.034516 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.842909 2023/08/09 18:12:26 - mmengine - INFO - Epoch(train) [170][ 30/442] lr: 5.000000e-04 eta: 1:46:36 time: 0.359833 data_time: 0.034379 memory: 4565 loss: 0.000832 loss_kpt: 0.000832 acc_pose: 0.815966 2023/08/09 18:12:29 - mmengine - INFO - Epoch(train) [170][ 40/442] lr: 5.000000e-04 eta: 1:46:33 time: 0.359084 data_time: 0.034209 memory: 4565 loss: 0.000823 loss_kpt: 0.000823 acc_pose: 0.860576 2023/08/09 18:12:33 - mmengine - INFO - Epoch(train) [170][ 50/442] lr: 5.000000e-04 eta: 1:46:29 time: 0.365874 data_time: 0.038819 memory: 4565 loss: 0.000822 loss_kpt: 0.000822 acc_pose: 0.808340 2023/08/09 18:12:37 - mmengine - INFO - Epoch(train) [170][ 60/442] lr: 5.000000e-04 eta: 1:46:26 time: 0.362979 data_time: 0.035253 memory: 4565 loss: 0.000843 loss_kpt: 0.000843 acc_pose: 0.836206 2023/08/09 18:12:40 - mmengine - INFO - Epoch(train) [170][ 70/442] lr: 5.000000e-04 eta: 1:46:22 time: 0.360581 data_time: 0.035158 memory: 4565 loss: 0.000829 loss_kpt: 0.000829 acc_pose: 0.836362 2023/08/09 18:12:44 - mmengine - INFO - Epoch(train) [170][ 80/442] lr: 5.000000e-04 eta: 1:46:19 time: 0.366512 data_time: 0.035303 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.831654 2023/08/09 18:12:48 - mmengine - INFO - Epoch(train) [170][ 90/442] lr: 5.000000e-04 eta: 1:46:16 time: 0.375176 data_time: 0.036493 memory: 4565 loss: 0.000853 loss_kpt: 0.000853 acc_pose: 0.894877 2023/08/09 18:12:52 - mmengine - INFO - Epoch(train) [170][100/442] lr: 5.000000e-04 eta: 1:46:12 time: 0.379020 data_time: 0.033995 memory: 4565 loss: 0.000868 loss_kpt: 0.000868 acc_pose: 0.944024 2023/08/09 18:12:56 - mmengine - INFO - Epoch(train) [170][110/442] lr: 5.000000e-04 eta: 1:46:09 time: 0.380122 data_time: 0.034524 memory: 4565 loss: 0.000867 loss_kpt: 0.000867 acc_pose: 0.836934 2023/08/09 18:12:59 - mmengine - INFO - Epoch(train) [170][120/442] lr: 5.000000e-04 eta: 1:46:05 time: 0.377334 data_time: 0.034095 memory: 4565 loss: 0.000871 loss_kpt: 0.000871 acc_pose: 0.850925 2023/08/09 18:13:03 - mmengine - INFO - Epoch(train) [170][130/442] lr: 5.000000e-04 eta: 1:46:02 time: 0.369491 data_time: 0.033846 memory: 4565 loss: 0.000853 loss_kpt: 0.000853 acc_pose: 0.896632 2023/08/09 18:13:06 - mmengine - INFO - Epoch(train) [170][140/442] lr: 5.000000e-04 eta: 1:45:58 time: 0.359298 data_time: 0.032656 memory: 4565 loss: 0.000848 loss_kpt: 0.000848 acc_pose: 0.842915 2023/08/09 18:13:10 - mmengine - INFO - Epoch(train) [170][150/442] lr: 5.000000e-04 eta: 1:45:55 time: 0.352772 data_time: 0.031318 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.857464 2023/08/09 18:13:13 - mmengine - INFO - Epoch(train) [170][160/442] lr: 5.000000e-04 eta: 1:45:51 time: 0.352030 data_time: 0.030943 memory: 4565 loss: 0.000843 loss_kpt: 0.000843 acc_pose: 0.846728 2023/08/09 18:13:17 - mmengine - INFO - Epoch(train) [170][170/442] lr: 5.000000e-04 eta: 1:45:48 time: 0.353894 data_time: 0.031363 memory: 4565 loss: 0.000860 loss_kpt: 0.000860 acc_pose: 0.809544 2023/08/09 18:13:20 - mmengine - INFO - Epoch(train) [170][180/442] lr: 5.000000e-04 eta: 1:45:44 time: 0.355132 data_time: 0.031441 memory: 4565 loss: 0.000880 loss_kpt: 0.000880 acc_pose: 0.778937 2023/08/09 18:13:24 - mmengine - INFO - Epoch(train) [170][190/442] lr: 5.000000e-04 eta: 1:45:41 time: 0.359528 data_time: 0.031448 memory: 4565 loss: 0.000874 loss_kpt: 0.000874 acc_pose: 0.826242 2023/08/09 18:13:28 - mmengine - INFO - Epoch(train) [170][200/442] lr: 5.000000e-04 eta: 1:45:37 time: 0.357006 data_time: 0.031374 memory: 4565 loss: 0.000883 loss_kpt: 0.000883 acc_pose: 0.784433 2023/08/09 18:13:31 - mmengine - INFO - Epoch(train) [170][210/442] lr: 5.000000e-04 eta: 1:45:34 time: 0.356755 data_time: 0.031225 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.834666 2023/08/09 18:13:35 - mmengine - INFO - Epoch(train) [170][220/442] lr: 5.000000e-04 eta: 1:45:30 time: 0.357738 data_time: 0.031112 memory: 4565 loss: 0.000862 loss_kpt: 0.000862 acc_pose: 0.796263 2023/08/09 18:13:38 - mmengine - INFO - Epoch(train) [170][230/442] lr: 5.000000e-04 eta: 1:45:27 time: 0.359019 data_time: 0.031300 memory: 4565 loss: 0.000839 loss_kpt: 0.000839 acc_pose: 0.940329 2023/08/09 18:13:42 - mmengine - INFO - Epoch(train) [170][240/442] lr: 5.000000e-04 eta: 1:45:23 time: 0.359466 data_time: 0.031646 memory: 4565 loss: 0.000853 loss_kpt: 0.000853 acc_pose: 0.809195 2023/08/09 18:13:46 - mmengine - INFO - Epoch(train) [170][250/442] lr: 5.000000e-04 eta: 1:45:20 time: 0.359646 data_time: 0.031455 memory: 4565 loss: 0.000838 loss_kpt: 0.000838 acc_pose: 0.845864 2023/08/09 18:13:49 - mmengine - INFO - Epoch(train) [170][260/442] lr: 5.000000e-04 eta: 1:45:16 time: 0.358780 data_time: 0.031422 memory: 4565 loss: 0.000834 loss_kpt: 0.000834 acc_pose: 0.882095 2023/08/09 18:13:53 - mmengine - INFO - Epoch(train) [170][270/442] lr: 5.000000e-04 eta: 1:45:13 time: 0.358751 data_time: 0.031048 memory: 4565 loss: 0.000829 loss_kpt: 0.000829 acc_pose: 0.801473 2023/08/09 18:13:56 - mmengine - INFO - Epoch(train) [170][280/442] lr: 5.000000e-04 eta: 1:45:09 time: 0.358524 data_time: 0.030873 memory: 4565 loss: 0.000832 loss_kpt: 0.000832 acc_pose: 0.857041 2023/08/09 18:14:00 - mmengine - INFO - Epoch(train) [170][290/442] lr: 5.000000e-04 eta: 1:45:06 time: 0.357539 data_time: 0.030924 memory: 4565 loss: 0.000829 loss_kpt: 0.000829 acc_pose: 0.838523 2023/08/09 18:14:03 - mmengine - INFO - Epoch(train) [170][300/442] lr: 5.000000e-04 eta: 1:45:02 time: 0.359151 data_time: 0.030937 memory: 4565 loss: 0.000822 loss_kpt: 0.000822 acc_pose: 0.921851 2023/08/09 18:14:04 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:14:07 - mmengine - INFO - Epoch(train) [170][310/442] lr: 5.000000e-04 eta: 1:44:59 time: 0.360173 data_time: 0.031023 memory: 4565 loss: 0.000831 loss_kpt: 0.000831 acc_pose: 0.871154 2023/08/09 18:14:11 - mmengine - INFO - Epoch(train) [170][320/442] lr: 5.000000e-04 eta: 1:44:55 time: 0.358031 data_time: 0.031293 memory: 4565 loss: 0.000840 loss_kpt: 0.000840 acc_pose: 0.886924 2023/08/09 18:14:14 - mmengine - INFO - Epoch(train) [170][330/442] lr: 5.000000e-04 eta: 1:44:51 time: 0.356377 data_time: 0.031236 memory: 4565 loss: 0.000830 loss_kpt: 0.000830 acc_pose: 0.891273 2023/08/09 18:14:18 - mmengine - INFO - Epoch(train) [170][340/442] lr: 5.000000e-04 eta: 1:44:48 time: 0.356719 data_time: 0.031180 memory: 4565 loss: 0.000830 loss_kpt: 0.000830 acc_pose: 0.831428 2023/08/09 18:14:21 - mmengine - INFO - Epoch(train) [170][350/442] lr: 5.000000e-04 eta: 1:44:45 time: 0.358750 data_time: 0.032213 memory: 4565 loss: 0.000854 loss_kpt: 0.000854 acc_pose: 0.834316 2023/08/09 18:14:25 - mmengine - INFO - Epoch(train) [170][360/442] lr: 5.000000e-04 eta: 1:44:41 time: 0.364464 data_time: 0.032879 memory: 4565 loss: 0.000855 loss_kpt: 0.000855 acc_pose: 0.890588 2023/08/09 18:14:29 - mmengine - INFO - Epoch(train) [170][370/442] lr: 5.000000e-04 eta: 1:44:38 time: 0.365225 data_time: 0.033003 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.883888 2023/08/09 18:14:32 - mmengine - INFO - Epoch(train) [170][380/442] lr: 5.000000e-04 eta: 1:44:34 time: 0.364893 data_time: 0.033004 memory: 4565 loss: 0.000872 loss_kpt: 0.000872 acc_pose: 0.823027 2023/08/09 18:14:36 - mmengine - INFO - Epoch(train) [170][390/442] lr: 5.000000e-04 eta: 1:44:31 time: 0.369604 data_time: 0.033268 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.833522 2023/08/09 18:14:40 - mmengine - INFO - Epoch(train) [170][400/442] lr: 5.000000e-04 eta: 1:44:27 time: 0.368372 data_time: 0.032250 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.862271 2023/08/09 18:14:43 - mmengine - INFO - Epoch(train) [170][410/442] lr: 5.000000e-04 eta: 1:44:24 time: 0.363132 data_time: 0.031731 memory: 4565 loss: 0.000846 loss_kpt: 0.000846 acc_pose: 0.813608 2023/08/09 18:14:47 - mmengine - INFO - Epoch(train) [170][420/442] lr: 5.000000e-04 eta: 1:44:20 time: 0.363343 data_time: 0.031846 memory: 4565 loss: 0.000854 loss_kpt: 0.000854 acc_pose: 0.871280 2023/08/09 18:14:50 - mmengine - INFO - Epoch(train) [170][430/442] lr: 5.000000e-04 eta: 1:44:17 time: 0.363925 data_time: 0.032051 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.787171 2023/08/09 18:14:54 - mmengine - INFO - Epoch(train) [170][440/442] lr: 5.000000e-04 eta: 1:44:13 time: 0.355416 data_time: 0.031510 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.880358 2023/08/09 18:14:55 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:14:55 - mmengine - INFO - Saving checkpoint at 170 epochs 2023/08/09 18:15:00 - mmengine - INFO - Epoch(val) [170][ 10/108] eta: 0:00:20 time: 0.196549 data_time: 0.012999 memory: 4565 2023/08/09 18:15:02 - mmengine - INFO - Epoch(val) [170][ 20/108] eta: 0:00:17 time: 0.196668 data_time: 0.013032 memory: 1624 2023/08/09 18:15:04 - mmengine - INFO - Epoch(val) [170][ 30/108] eta: 0:00:15 time: 0.196774 data_time: 0.012998 memory: 1624 2023/08/09 18:15:06 - mmengine - INFO - Epoch(val) [170][ 40/108] eta: 0:00:13 time: 0.197102 data_time: 0.013082 memory: 1624 2023/08/09 18:15:08 - mmengine - INFO - Epoch(val) [170][ 50/108] eta: 0:00:11 time: 0.199252 data_time: 0.013191 memory: 1624 2023/08/09 18:15:10 - mmengine - INFO - Epoch(val) [170][ 60/108] eta: 0:00:09 time: 0.197748 data_time: 0.011782 memory: 1624 2023/08/09 18:15:12 - mmengine - INFO - Epoch(val) [170][ 70/108] eta: 0:00:07 time: 0.198267 data_time: 0.012009 memory: 1624 2023/08/09 18:15:14 - mmengine - INFO - Epoch(val) [170][ 80/108] eta: 0:00:05 time: 0.198086 data_time: 0.011903 memory: 1624 2023/08/09 18:15:16 - mmengine - INFO - Epoch(val) [170][ 90/108] eta: 0:00:03 time: 0.197654 data_time: 0.011751 memory: 1624 2023/08/09 18:15:18 - mmengine - INFO - Epoch(val) [170][100/108] eta: 0:00:01 time: 0.197559 data_time: 0.011721 memory: 1624 2023/08/09 18:15:20 - mmengine - INFO - Evaluating PCKAccuracy (normalized by ``"bbox_size"``)... 2023/08/09 18:15:20 - mmengine - INFO - Evaluating AUC... 2023/08/09 18:15:20 - mmengine - INFO - Evaluating EPE... 2023/08/09 18:15:20 - mmengine - INFO - Epoch(val) [170][108/108] PCK: 0.960413 AUC: 0.603462 EPE: 15.073898 data_time: 0.012187 time: 0.196303 2023/08/09 18:15:24 - mmengine - INFO - Epoch(train) [171][ 10/442] lr: 5.000000e-05 eta: 1:44:09 time: 0.354401 data_time: 0.034763 memory: 4565 loss: 0.000865 loss_kpt: 0.000865 acc_pose: 0.913913 2023/08/09 18:15:27 - mmengine - INFO - Epoch(train) [171][ 20/442] lr: 5.000000e-05 eta: 1:44:06 time: 0.354699 data_time: 0.034995 memory: 4565 loss: 0.000857 loss_kpt: 0.000857 acc_pose: 0.899723 2023/08/09 18:15:31 - mmengine - INFO - Epoch(train) [171][ 30/442] lr: 5.000000e-05 eta: 1:44:02 time: 0.354752 data_time: 0.035003 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.845547 2023/08/09 18:15:35 - mmengine - INFO - Epoch(train) [171][ 40/442] lr: 5.000000e-05 eta: 1:43:59 time: 0.359687 data_time: 0.035649 memory: 4565 loss: 0.000837 loss_kpt: 0.000837 acc_pose: 0.867237 2023/08/09 18:15:38 - mmengine - INFO - Epoch(train) [171][ 50/442] lr: 5.000000e-05 eta: 1:43:55 time: 0.360954 data_time: 0.036088 memory: 4565 loss: 0.000838 loss_kpt: 0.000838 acc_pose: 0.848295 2023/08/09 18:15:42 - mmengine - INFO - Epoch(train) [171][ 60/442] lr: 5.000000e-05 eta: 1:43:51 time: 0.356615 data_time: 0.032257 memory: 4565 loss: 0.000831 loss_kpt: 0.000831 acc_pose: 0.926192 2023/08/09 18:15:45 - mmengine - INFO - Epoch(train) [171][ 70/442] lr: 5.000000e-05 eta: 1:43:48 time: 0.354711 data_time: 0.031750 memory: 4565 loss: 0.000835 loss_kpt: 0.000835 acc_pose: 0.895547 2023/08/09 18:15:49 - mmengine - INFO - Epoch(train) [171][ 80/442] lr: 5.000000e-05 eta: 1:43:44 time: 0.353642 data_time: 0.031265 memory: 4565 loss: 0.000836 loss_kpt: 0.000836 acc_pose: 0.899694 2023/08/09 18:15:52 - mmengine - INFO - Epoch(train) [171][ 90/442] lr: 5.000000e-05 eta: 1:43:41 time: 0.350203 data_time: 0.030766 memory: 4565 loss: 0.000844 loss_kpt: 0.000844 acc_pose: 0.870860 2023/08/09 18:15:56 - mmengine - INFO - Epoch(train) [171][100/442] lr: 5.000000e-05 eta: 1:43:37 time: 0.351919 data_time: 0.030976 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.785807 2023/08/09 18:16:00 - mmengine - INFO - Epoch(train) [171][110/442] lr: 5.000000e-05 eta: 1:43:34 time: 0.361561 data_time: 0.031631 memory: 4565 loss: 0.000834 loss_kpt: 0.000834 acc_pose: 0.864732 2023/08/09 18:16:04 - mmengine - INFO - Epoch(train) [171][120/442] lr: 5.000000e-05 eta: 1:43:31 time: 0.369252 data_time: 0.032013 memory: 4565 loss: 0.000823 loss_kpt: 0.000823 acc_pose: 0.886938 2023/08/09 18:16:07 - mmengine - INFO - Epoch(train) [171][130/442] lr: 5.000000e-05 eta: 1:43:27 time: 0.377049 data_time: 0.032293 memory: 4565 loss: 0.000818 loss_kpt: 0.000818 acc_pose: 0.833320 2023/08/09 18:16:11 - mmengine - INFO - Epoch(train) [171][140/442] lr: 5.000000e-05 eta: 1:43:24 time: 0.383667 data_time: 0.032457 memory: 4565 loss: 0.000817 loss_kpt: 0.000817 acc_pose: 0.856122 2023/08/09 18:16:15 - mmengine - INFO - Epoch(train) [171][150/442] lr: 5.000000e-05 eta: 1:43:21 time: 0.386093 data_time: 0.032626 memory: 4565 loss: 0.000807 loss_kpt: 0.000807 acc_pose: 0.923268 2023/08/09 18:16:19 - mmengine - INFO - Epoch(train) [171][160/442] lr: 5.000000e-05 eta: 1:43:17 time: 0.378674 data_time: 0.032697 memory: 4565 loss: 0.000834 loss_kpt: 0.000834 acc_pose: 0.893477 2023/08/09 18:16:22 - mmengine - INFO - Epoch(train) [171][170/442] lr: 5.000000e-05 eta: 1:43:14 time: 0.377909 data_time: 0.032642 memory: 4565 loss: 0.000851 loss_kpt: 0.000851 acc_pose: 0.893157 2023/08/09 18:16:26 - mmengine - INFO - Epoch(train) [171][180/442] lr: 5.000000e-05 eta: 1:43:10 time: 0.369885 data_time: 0.032359 memory: 4565 loss: 0.000856 loss_kpt: 0.000856 acc_pose: 0.717851 2023/08/09 18:16:29 - mmengine - INFO - Epoch(train) [171][190/442] lr: 5.000000e-05 eta: 1:43:07 time: 0.360968 data_time: 0.031824 memory: 4565 loss: 0.000848 loss_kpt: 0.000848 acc_pose: 0.868794 2023/08/09 18:16:33 - mmengine - INFO - Epoch(train) [171][200/442] lr: 5.000000e-05 eta: 1:43:03 time: 0.357611 data_time: 0.031582 memory: 4565 loss: 0.000849 loss_kpt: 0.000849 acc_pose: 0.845854 2023/08/09 18:16:36 - mmengine - INFO - Epoch(train) [171][210/442] lr: 5.000000e-05 eta: 1:43:00 time: 0.356340 data_time: 0.031422 memory: 4565 loss: 0.000838 loss_kpt: 0.000838 acc_pose: 0.802776 2023/08/09 18:16:40 - mmengine - INFO - Epoch(train) [171][220/442] lr: 5.000000e-05 eta: 1:42:56 time: 0.350861 data_time: 0.031910 memory: 4565 loss: 0.000816 loss_kpt: 0.000816 acc_pose: 0.818269 2023/08/09 18:16:44 - mmengine - INFO - Epoch(train) [171][230/442] lr: 5.000000e-05 eta: 1:42:53 time: 0.351599 data_time: 0.032311 memory: 4565 loss: 0.000807 loss_kpt: 0.000807 acc_pose: 0.849595 2023/08/09 18:16:47 - mmengine - INFO - Epoch(train) [171][240/442] lr: 5.000000e-05 eta: 1:42:49 time: 0.351932 data_time: 0.032552 memory: 4565 loss: 0.000823 loss_kpt: 0.000823 acc_pose: 0.837622 2023/08/09 18:16:51 - mmengine - INFO - Epoch(train) [171][250/442] lr: 5.000000e-05 eta: 1:42:45 time: 0.351044 data_time: 0.032345 memory: 4565 loss: 0.000820 loss_kpt: 0.000820 acc_pose: 0.886844 2023/08/09 18:16:54 - mmengine - INFO - Epoch(train) [171][260/442] lr: 5.000000e-05 eta: 1:42:42 time: 0.351031 data_time: 0.031893 memory: 4565 loss: 0.000806 loss_kpt: 0.000806 acc_pose: 0.840662 2023/08/09 18:16:58 - mmengine - INFO - Epoch(train) [171][270/442] lr: 5.000000e-05 eta: 1:42:38 time: 0.351871 data_time: 0.031303 memory: 4565 loss: 0.000801 loss_kpt: 0.000801 acc_pose: 0.876444 2023/08/09 18:17:01 - mmengine - INFO - Epoch(train) [171][280/442] lr: 5.000000e-05 eta: 1:42:35 time: 0.353088 data_time: 0.030888 memory: 4565 loss: 0.000802 loss_kpt: 0.000802 acc_pose: 0.885332 2023/08/09 18:17:05 - mmengine - INFO - Epoch(train) [171][290/442] lr: 5.000000e-05 eta: 1:42:31 time: 0.357182 data_time: 0.030880 memory: 4565 loss: 0.000783 loss_kpt: 0.000783 acc_pose: 0.865835 2023/08/09 18:17:09 - mmengine - INFO - Epoch(train) [171][300/442] lr: 5.000000e-05 eta: 1:42:28 time: 0.364390 data_time: 0.031405 memory: 4565 loss: 0.000776 loss_kpt: 0.000776 acc_pose: 0.818598 2023/08/09 18:17:13 - mmengine - INFO - Epoch(train) [171][310/442] lr: 5.000000e-05 eta: 1:42:25 time: 0.372102 data_time: 0.031701 memory: 4565 loss: 0.000791 loss_kpt: 0.000791 acc_pose: 0.965214 2023/08/09 18:17:17 - mmengine - INFO - Epoch(train) [171][320/442] lr: 5.000000e-05 eta: 1:42:21 time: 0.378069 data_time: 0.032007 memory: 4565 loss: 0.000789 loss_kpt: 0.000789 acc_pose: 0.772098 2023/08/09 18:17:21 - mmengine - INFO - Epoch(train) [171][330/442] lr: 5.000000e-05 eta: 1:42:18 time: 0.384906 data_time: 0.032905 memory: 4565 loss: 0.000784 loss_kpt: 0.000784 acc_pose: 0.877778 2023/08/09 18:17:24 - mmengine - INFO - Epoch(train) [171][340/442] lr: 5.000000e-05 eta: 1:42:15 time: 0.386575 data_time: 0.033585 memory: 4565 loss: 0.000786 loss_kpt: 0.000786 acc_pose: 0.825649 2023/08/09 18:17:28 - mmengine - INFO - Epoch(train) [171][350/442] lr: 5.000000e-05 eta: 1:42:11 time: 0.381870 data_time: 0.033568 memory: 4565 loss: 0.000790 loss_kpt: 0.000790 acc_pose: 0.919221 2023/08/09 18:17:32 - mmengine - INFO - Epoch(train) [171][360/442] lr: 5.000000e-05 eta: 1:42:08 time: 0.378283 data_time: 0.034104 memory: 4565 loss: 0.000783 loss_kpt: 0.000783 acc_pose: 0.902709 2023/08/09 18:17:35 - mmengine - INFO - Epoch(train) [171][370/442] lr: 5.000000e-05 eta: 1:42:04 time: 0.372173 data_time: 0.034313 memory: 4565 loss: 0.000798 loss_kpt: 0.000798 acc_pose: 0.911472 2023/08/09 18:17:39 - mmengine - INFO - Epoch(train) [171][380/442] lr: 5.000000e-05 eta: 1:42:01 time: 0.364674 data_time: 0.034357 memory: 4565 loss: 0.000799 loss_kpt: 0.000799 acc_pose: 0.873370 2023/08/09 18:17:42 - mmengine - INFO - Epoch(train) [171][390/442] lr: 5.000000e-05 eta: 1:41:57 time: 0.361397 data_time: 0.034277 memory: 4565 loss: 0.000797 loss_kpt: 0.000797 acc_pose: 0.876732 2023/08/09 18:17:46 - mmengine - INFO - Epoch(train) [171][400/442] lr: 5.000000e-05 eta: 1:41:54 time: 0.361044 data_time: 0.034381 memory: 4565 loss: 0.000794 loss_kpt: 0.000794 acc_pose: 0.916417 2023/08/09 18:17:50 - mmengine - INFO - Epoch(train) [171][410/442] lr: 5.000000e-05 eta: 1:41:50 time: 0.358997 data_time: 0.034119 memory: 4565 loss: 0.000797 loss_kpt: 0.000797 acc_pose: 0.880018 2023/08/09 18:17:53 - mmengine - INFO - Epoch(train) [171][420/442] lr: 5.000000e-05 eta: 1:41:47 time: 0.361375 data_time: 0.033576 memory: 4565 loss: 0.000793 loss_kpt: 0.000793 acc_pose: 0.822590 2023/08/09 18:17:57 - mmengine - INFO - Epoch(train) [171][430/442] lr: 5.000000e-05 eta: 1:41:43 time: 0.361135 data_time: 0.032676 memory: 4565 loss: 0.000780 loss_kpt: 0.000780 acc_pose: 0.856445 2023/08/09 18:18:00 - mmengine - INFO - Epoch(train) [171][440/442] lr: 5.000000e-05 eta: 1:41:40 time: 0.360129 data_time: 0.032114 memory: 4565 loss: 0.000783 loss_kpt: 0.000783 acc_pose: 0.902601 2023/08/09 18:18:01 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:18:05 - mmengine - INFO - Epoch(train) [172][ 10/442] lr: 5.000000e-05 eta: 1:41:36 time: 0.360558 data_time: 0.034937 memory: 4565 loss: 0.000778 loss_kpt: 0.000778 acc_pose: 0.909195 2023/08/09 18:18:08 - mmengine - INFO - Epoch(train) [172][ 20/442] lr: 5.000000e-05 eta: 1:41:32 time: 0.356732 data_time: 0.034858 memory: 4565 loss: 0.000783 loss_kpt: 0.000783 acc_pose: 0.831728 2023/08/09 18:18:12 - mmengine - INFO - Epoch(train) [172][ 30/442] lr: 5.000000e-05 eta: 1:41:29 time: 0.356189 data_time: 0.035334 memory: 4565 loss: 0.000779 loss_kpt: 0.000779 acc_pose: 0.921613 2023/08/09 18:18:15 - mmengine - INFO - Epoch(train) [172][ 40/442] lr: 5.000000e-05 eta: 1:41:25 time: 0.356427 data_time: 0.035371 memory: 4565 loss: 0.000782 loss_kpt: 0.000782 acc_pose: 0.890030 2023/08/09 18:18:19 - mmengine - INFO - Epoch(train) [172][ 50/442] lr: 5.000000e-05 eta: 1:41:21 time: 0.356685 data_time: 0.035684 memory: 4565 loss: 0.000780 loss_kpt: 0.000780 acc_pose: 0.863980 2023/08/09 18:18:22 - mmengine - INFO - Epoch(train) [172][ 60/442] lr: 5.000000e-05 eta: 1:41:18 time: 0.352653 data_time: 0.032353 memory: 4565 loss: 0.000776 loss_kpt: 0.000776 acc_pose: 0.829210 2023/08/09 18:18:26 - mmengine - INFO - Epoch(train) [172][ 70/442] lr: 5.000000e-05 eta: 1:41:14 time: 0.351464 data_time: 0.032173 memory: 4565 loss: 0.000771 loss_kpt: 0.000771 acc_pose: 0.836736 2023/08/09 18:18:30 - mmengine - INFO - Epoch(train) [172][ 80/442] lr: 5.000000e-05 eta: 1:41:11 time: 0.353695 data_time: 0.031817 memory: 4565 loss: 0.000776 loss_kpt: 0.000776 acc_pose: 0.880638 2023/08/09 18:18:33 - mmengine - INFO - Epoch(train) [172][ 90/442] lr: 5.000000e-05 eta: 1:41:07 time: 0.357650 data_time: 0.032061 memory: 4565 loss: 0.000773 loss_kpt: 0.000773 acc_pose: 0.880213 2023/08/09 18:18:37 - mmengine - INFO - Epoch(train) [172][100/442] lr: 5.000000e-05 eta: 1:41:04 time: 0.360005 data_time: 0.032532 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.892025 2023/08/09 18:18:41 - mmengine - INFO - Epoch(train) [172][110/442] lr: 5.000000e-05 eta: 1:41:01 time: 0.366255 data_time: 0.037403 memory: 4565 loss: 0.000769 loss_kpt: 0.000769 acc_pose: 0.811578 2023/08/09 18:18:44 - mmengine - INFO - Epoch(train) [172][120/442] lr: 5.000000e-05 eta: 1:40:57 time: 0.365988 data_time: 0.037324 memory: 4565 loss: 0.000774 loss_kpt: 0.000774 acc_pose: 0.873792 2023/08/09 18:18:48 - mmengine - INFO - Epoch(train) [172][130/442] lr: 5.000000e-05 eta: 1:40:53 time: 0.363339 data_time: 0.037121 memory: 4565 loss: 0.000764 loss_kpt: 0.000764 acc_pose: 0.846144 2023/08/09 18:18:51 - mmengine - INFO - Epoch(train) [172][140/442] lr: 5.000000e-05 eta: 1:40:50 time: 0.358074 data_time: 0.036642 memory: 4565 loss: 0.000765 loss_kpt: 0.000765 acc_pose: 0.868289 2023/08/09 18:18:55 - mmengine - INFO - Epoch(train) [172][150/442] lr: 5.000000e-05 eta: 1:40:46 time: 0.357258 data_time: 0.036396 memory: 4565 loss: 0.000774 loss_kpt: 0.000774 acc_pose: 0.887850 2023/08/09 18:18:58 - mmengine - INFO - Epoch(train) [172][160/442] lr: 5.000000e-05 eta: 1:40:43 time: 0.351528 data_time: 0.030877 memory: 4565 loss: 0.000775 loss_kpt: 0.000775 acc_pose: 0.887938 2023/08/09 18:19:02 - mmengine - INFO - Epoch(train) [172][170/442] lr: 5.000000e-05 eta: 1:40:39 time: 0.353517 data_time: 0.031136 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.896284 2023/08/09 18:19:05 - mmengine - INFO - Epoch(train) [172][180/442] lr: 5.000000e-05 eta: 1:40:36 time: 0.353013 data_time: 0.031121 memory: 4565 loss: 0.000778 loss_kpt: 0.000778 acc_pose: 0.887368 2023/08/09 18:19:09 - mmengine - INFO - Epoch(train) [172][190/442] lr: 5.000000e-05 eta: 1:40:32 time: 0.352668 data_time: 0.031086 memory: 4565 loss: 0.000797 loss_kpt: 0.000797 acc_pose: 0.810316 2023/08/09 18:19:12 - mmengine - INFO - Epoch(train) [172][200/442] lr: 5.000000e-05 eta: 1:40:29 time: 0.350971 data_time: 0.030913 memory: 4565 loss: 0.000787 loss_kpt: 0.000787 acc_pose: 0.915352 2023/08/09 18:19:16 - mmengine - INFO - Epoch(train) [172][210/442] lr: 5.000000e-05 eta: 1:40:25 time: 0.350634 data_time: 0.031138 memory: 4565 loss: 0.000795 loss_kpt: 0.000795 acc_pose: 0.835393 2023/08/09 18:19:19 - mmengine - INFO - Epoch(train) [172][220/442] lr: 5.000000e-05 eta: 1:40:22 time: 0.350025 data_time: 0.031005 memory: 4565 loss: 0.000794 loss_kpt: 0.000794 acc_pose: 0.802201 2023/08/09 18:19:23 - mmengine - INFO - Epoch(train) [172][230/442] lr: 5.000000e-05 eta: 1:40:18 time: 0.352914 data_time: 0.031060 memory: 4565 loss: 0.000788 loss_kpt: 0.000788 acc_pose: 0.934745 2023/08/09 18:19:27 - mmengine - INFO - Epoch(train) [172][240/442] lr: 5.000000e-05 eta: 1:40:14 time: 0.353597 data_time: 0.031486 memory: 4565 loss: 0.000778 loss_kpt: 0.000778 acc_pose: 0.891846 2023/08/09 18:19:30 - mmengine - INFO - Epoch(train) [172][250/442] lr: 5.000000e-05 eta: 1:40:11 time: 0.358149 data_time: 0.031491 memory: 4565 loss: 0.000784 loss_kpt: 0.000784 acc_pose: 0.882912 2023/08/09 18:19:34 - mmengine - INFO - Epoch(train) [172][260/442] lr: 5.000000e-05 eta: 1:40:07 time: 0.358691 data_time: 0.031320 memory: 4565 loss: 0.000788 loss_kpt: 0.000788 acc_pose: 0.900211 2023/08/09 18:19:37 - mmengine - INFO - Epoch(train) [172][270/442] lr: 5.000000e-05 eta: 1:40:04 time: 0.359052 data_time: 0.031230 memory: 4565 loss: 0.000796 loss_kpt: 0.000796 acc_pose: 0.888665 2023/08/09 18:19:41 - mmengine - INFO - Epoch(train) [172][280/442] lr: 5.000000e-05 eta: 1:40:01 time: 0.360401 data_time: 0.031365 memory: 4565 loss: 0.000799 loss_kpt: 0.000799 acc_pose: 0.900804 2023/08/09 18:19:45 - mmengine - INFO - Epoch(train) [172][290/442] lr: 5.000000e-05 eta: 1:39:57 time: 0.362906 data_time: 0.031091 memory: 4565 loss: 0.000791 loss_kpt: 0.000791 acc_pose: 0.927015 2023/08/09 18:19:48 - mmengine - INFO - Epoch(train) [172][300/442] lr: 5.000000e-05 eta: 1:39:54 time: 0.364393 data_time: 0.035635 memory: 4565 loss: 0.000794 loss_kpt: 0.000794 acc_pose: 0.906646 2023/08/09 18:19:52 - mmengine - INFO - Epoch(train) [172][310/442] lr: 5.000000e-05 eta: 1:39:50 time: 0.364372 data_time: 0.035609 memory: 4565 loss: 0.000783 loss_kpt: 0.000783 acc_pose: 0.839835 2023/08/09 18:19:56 - mmengine - INFO - Epoch(train) [172][320/442] lr: 5.000000e-05 eta: 1:39:47 time: 0.364046 data_time: 0.035602 memory: 4565 loss: 0.000777 loss_kpt: 0.000777 acc_pose: 0.845451 2023/08/09 18:19:59 - mmengine - INFO - Epoch(train) [172][330/442] lr: 5.000000e-05 eta: 1:39:43 time: 0.360800 data_time: 0.035596 memory: 4565 loss: 0.000777 loss_kpt: 0.000777 acc_pose: 0.874250 2023/08/09 18:20:03 - mmengine - INFO - Epoch(train) [172][340/442] lr: 5.000000e-05 eta: 1:39:40 time: 0.359229 data_time: 0.035686 memory: 4565 loss: 0.000788 loss_kpt: 0.000788 acc_pose: 0.888824 2023/08/09 18:20:06 - mmengine - INFO - Epoch(train) [172][350/442] lr: 5.000000e-05 eta: 1:39:36 time: 0.354127 data_time: 0.031342 memory: 4565 loss: 0.000775 loss_kpt: 0.000775 acc_pose: 0.909588 2023/08/09 18:20:10 - mmengine - INFO - Epoch(train) [172][360/442] lr: 5.000000e-05 eta: 1:39:32 time: 0.355219 data_time: 0.031320 memory: 4565 loss: 0.000790 loss_kpt: 0.000790 acc_pose: 0.885043 2023/08/09 18:20:13 - mmengine - INFO - Epoch(train) [172][370/442] lr: 5.000000e-05 eta: 1:39:29 time: 0.354792 data_time: 0.031332 memory: 4565 loss: 0.000786 loss_kpt: 0.000786 acc_pose: 0.872698 2023/08/09 18:20:17 - mmengine - INFO - Epoch(train) [172][380/442] lr: 5.000000e-05 eta: 1:39:25 time: 0.354171 data_time: 0.031257 memory: 4565 loss: 0.000790 loss_kpt: 0.000790 acc_pose: 0.898924 2023/08/09 18:20:20 - mmengine - INFO - Epoch(train) [172][390/442] lr: 5.000000e-05 eta: 1:39:22 time: 0.354257 data_time: 0.031138 memory: 4565 loss: 0.000787 loss_kpt: 0.000787 acc_pose: 0.920818 2023/08/09 18:20:24 - mmengine - INFO - Epoch(train) [172][400/442] lr: 5.000000e-05 eta: 1:39:18 time: 0.354883 data_time: 0.031093 memory: 4565 loss: 0.000809 loss_kpt: 0.000809 acc_pose: 0.900204 2023/08/09 18:20:28 - mmengine - INFO - Epoch(train) [172][410/442] lr: 5.000000e-05 eta: 1:39:15 time: 0.357999 data_time: 0.031036 memory: 4565 loss: 0.000801 loss_kpt: 0.000801 acc_pose: 0.906757 2023/08/09 18:20:31 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:20:31 - mmengine - INFO - Epoch(train) [172][420/442] lr: 5.000000e-05 eta: 1:39:11 time: 0.359940 data_time: 0.031581 memory: 4565 loss: 0.000802 loss_kpt: 0.000802 acc_pose: 0.871914 2023/08/09 18:20:35 - mmengine - INFO - Epoch(train) [172][430/442] lr: 5.000000e-05 eta: 1:39:08 time: 0.359998 data_time: 0.031694 memory: 4565 loss: 0.000798 loss_kpt: 0.000798 acc_pose: 0.866324 2023/08/09 18:20:38 - mmengine - INFO - Epoch(train) [172][440/442] lr: 5.000000e-05 eta: 1:39:04 time: 0.358162 data_time: 0.031586 memory: 4565 loss: 0.000791 loss_kpt: 0.000791 acc_pose: 0.827178 2023/08/09 18:20:39 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:20:43 - mmengine - INFO - Epoch(train) [173][ 10/442] lr: 5.000000e-05 eta: 1:39:00 time: 0.354647 data_time: 0.034722 memory: 4565 loss: 0.000775 loss_kpt: 0.000775 acc_pose: 0.902318 2023/08/09 18:20:46 - mmengine - INFO - Epoch(train) [173][ 20/442] lr: 5.000000e-05 eta: 1:38:56 time: 0.350527 data_time: 0.034797 memory: 4565 loss: 0.000762 loss_kpt: 0.000762 acc_pose: 0.821585 2023/08/09 18:20:50 - mmengine - INFO - Epoch(train) [173][ 30/442] lr: 5.000000e-05 eta: 1:38:53 time: 0.348917 data_time: 0.034453 memory: 4565 loss: 0.000765 loss_kpt: 0.000765 acc_pose: 0.821480 2023/08/09 18:20:53 - mmengine - INFO - Epoch(train) [173][ 40/442] lr: 5.000000e-05 eta: 1:38:49 time: 0.348534 data_time: 0.034507 memory: 4565 loss: 0.000761 loss_kpt: 0.000761 acc_pose: 0.929328 2023/08/09 18:20:56 - mmengine - INFO - Epoch(train) [173][ 50/442] lr: 5.000000e-05 eta: 1:38:46 time: 0.349523 data_time: 0.035405 memory: 4565 loss: 0.000762 loss_kpt: 0.000762 acc_pose: 0.854012 2023/08/09 18:21:00 - mmengine - INFO - Epoch(train) [173][ 60/442] lr: 5.000000e-05 eta: 1:38:42 time: 0.348652 data_time: 0.032542 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.866506 2023/08/09 18:21:03 - mmengine - INFO - Epoch(train) [173][ 70/442] lr: 5.000000e-05 eta: 1:38:39 time: 0.349087 data_time: 0.033194 memory: 4565 loss: 0.000755 loss_kpt: 0.000755 acc_pose: 0.858269 2023/08/09 18:21:07 - mmengine - INFO - Epoch(train) [173][ 80/442] lr: 5.000000e-05 eta: 1:38:35 time: 0.347970 data_time: 0.033498 memory: 4565 loss: 0.000772 loss_kpt: 0.000772 acc_pose: 0.864484 2023/08/09 18:21:10 - mmengine - INFO - Epoch(train) [173][ 90/442] lr: 5.000000e-05 eta: 1:38:31 time: 0.349999 data_time: 0.033497 memory: 4565 loss: 0.000788 loss_kpt: 0.000788 acc_pose: 0.867878 2023/08/09 18:21:14 - mmengine - INFO - Epoch(train) [173][100/442] lr: 5.000000e-05 eta: 1:38:28 time: 0.350307 data_time: 0.032888 memory: 4565 loss: 0.000793 loss_kpt: 0.000793 acc_pose: 0.824097 2023/08/09 18:21:17 - mmengine - INFO - Epoch(train) [173][110/442] lr: 5.000000e-05 eta: 1:38:24 time: 0.348879 data_time: 0.032260 memory: 4565 loss: 0.000799 loss_kpt: 0.000799 acc_pose: 0.915874 2023/08/09 18:21:21 - mmengine - INFO - Epoch(train) [173][120/442] lr: 5.000000e-05 eta: 1:38:21 time: 0.347450 data_time: 0.031456 memory: 4565 loss: 0.000795 loss_kpt: 0.000795 acc_pose: 0.901466 2023/08/09 18:21:24 - mmengine - INFO - Epoch(train) [173][130/442] lr: 5.000000e-05 eta: 1:38:17 time: 0.346032 data_time: 0.030899 memory: 4565 loss: 0.000779 loss_kpt: 0.000779 acc_pose: 0.873579 2023/08/09 18:21:28 - mmengine - INFO - Epoch(train) [173][140/442] lr: 5.000000e-05 eta: 1:38:13 time: 0.342249 data_time: 0.030695 memory: 4565 loss: 0.000769 loss_kpt: 0.000769 acc_pose: 0.892557 2023/08/09 18:21:31 - mmengine - INFO - Epoch(train) [173][150/442] lr: 5.000000e-05 eta: 1:38:10 time: 0.342193 data_time: 0.030768 memory: 4565 loss: 0.000769 loss_kpt: 0.000769 acc_pose: 0.822173 2023/08/09 18:21:35 - mmengine - INFO - Epoch(train) [173][160/442] lr: 5.000000e-05 eta: 1:38:06 time: 0.340866 data_time: 0.030641 memory: 4565 loss: 0.000758 loss_kpt: 0.000758 acc_pose: 0.909601 2023/08/09 18:21:38 - mmengine - INFO - Epoch(train) [173][170/442] lr: 5.000000e-05 eta: 1:38:03 time: 0.341896 data_time: 0.030719 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.910077 2023/08/09 18:21:41 - mmengine - INFO - Epoch(train) [173][180/442] lr: 5.000000e-05 eta: 1:37:59 time: 0.343647 data_time: 0.031665 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.862947 2023/08/09 18:21:45 - mmengine - INFO - Epoch(train) [173][190/442] lr: 5.000000e-05 eta: 1:37:55 time: 0.345408 data_time: 0.032604 memory: 4565 loss: 0.000769 loss_kpt: 0.000769 acc_pose: 0.885069 2023/08/09 18:21:48 - mmengine - INFO - Epoch(train) [173][200/442] lr: 5.000000e-05 eta: 1:37:52 time: 0.344756 data_time: 0.033433 memory: 4565 loss: 0.000771 loss_kpt: 0.000771 acc_pose: 0.910567 2023/08/09 18:21:52 - mmengine - INFO - Epoch(train) [173][210/442] lr: 5.000000e-05 eta: 1:37:48 time: 0.346789 data_time: 0.033238 memory: 4565 loss: 0.000780 loss_kpt: 0.000780 acc_pose: 0.861181 2023/08/09 18:21:55 - mmengine - INFO - Epoch(train) [173][220/442] lr: 5.000000e-05 eta: 1:37:45 time: 0.347049 data_time: 0.033386 memory: 4565 loss: 0.000793 loss_kpt: 0.000793 acc_pose: 0.881107 2023/08/09 18:21:59 - mmengine - INFO - Epoch(train) [173][230/442] lr: 5.000000e-05 eta: 1:37:41 time: 0.347092 data_time: 0.032616 memory: 4565 loss: 0.000805 loss_kpt: 0.000805 acc_pose: 0.893785 2023/08/09 18:22:02 - mmengine - INFO - Epoch(train) [173][240/442] lr: 5.000000e-05 eta: 1:37:38 time: 0.347575 data_time: 0.031793 memory: 4565 loss: 0.000798 loss_kpt: 0.000798 acc_pose: 0.809905 2023/08/09 18:22:06 - mmengine - INFO - Epoch(train) [173][250/442] lr: 5.000000e-05 eta: 1:37:34 time: 0.350243 data_time: 0.034185 memory: 4565 loss: 0.000803 loss_kpt: 0.000803 acc_pose: 0.862837 2023/08/09 18:22:09 - mmengine - INFO - Epoch(train) [173][260/442] lr: 5.000000e-05 eta: 1:37:30 time: 0.347141 data_time: 0.034319 memory: 4565 loss: 0.000804 loss_kpt: 0.000804 acc_pose: 0.887931 2023/08/09 18:22:13 - mmengine - INFO - Epoch(train) [173][270/442] lr: 5.000000e-05 eta: 1:37:27 time: 0.346528 data_time: 0.034033 memory: 4565 loss: 0.000798 loss_kpt: 0.000798 acc_pose: 0.878555 2023/08/09 18:22:16 - mmengine - INFO - Epoch(train) [173][280/442] lr: 5.000000e-05 eta: 1:37:23 time: 0.346537 data_time: 0.033957 memory: 4565 loss: 0.000794 loss_kpt: 0.000794 acc_pose: 0.923242 2023/08/09 18:22:20 - mmengine - INFO - Epoch(train) [173][290/442] lr: 5.000000e-05 eta: 1:37:20 time: 0.352674 data_time: 0.034192 memory: 4565 loss: 0.000781 loss_kpt: 0.000781 acc_pose: 0.883861 2023/08/09 18:22:24 - mmengine - INFO - Epoch(train) [173][300/442] lr: 5.000000e-05 eta: 1:37:17 time: 0.358344 data_time: 0.031879 memory: 4565 loss: 0.000774 loss_kpt: 0.000774 acc_pose: 0.902970 2023/08/09 18:22:27 - mmengine - INFO - Epoch(train) [173][310/442] lr: 5.000000e-05 eta: 1:37:13 time: 0.361251 data_time: 0.032546 memory: 4565 loss: 0.000773 loss_kpt: 0.000773 acc_pose: 0.879392 2023/08/09 18:22:31 - mmengine - INFO - Epoch(train) [173][320/442] lr: 5.000000e-05 eta: 1:37:09 time: 0.361354 data_time: 0.032670 memory: 4565 loss: 0.000771 loss_kpt: 0.000771 acc_pose: 0.898554 2023/08/09 18:22:34 - mmengine - INFO - Epoch(train) [173][330/442] lr: 5.000000e-05 eta: 1:37:06 time: 0.362853 data_time: 0.032588 memory: 4565 loss: 0.000780 loss_kpt: 0.000780 acc_pose: 0.862822 2023/08/09 18:22:38 - mmengine - INFO - Epoch(train) [173][340/442] lr: 5.000000e-05 eta: 1:37:02 time: 0.354526 data_time: 0.032173 memory: 4565 loss: 0.000781 loss_kpt: 0.000781 acc_pose: 0.811376 2023/08/09 18:22:41 - mmengine - INFO - Epoch(train) [173][350/442] lr: 5.000000e-05 eta: 1:36:59 time: 0.345888 data_time: 0.031135 memory: 4565 loss: 0.000771 loss_kpt: 0.000771 acc_pose: 0.883842 2023/08/09 18:22:45 - mmengine - INFO - Epoch(train) [173][360/442] lr: 5.000000e-05 eta: 1:36:55 time: 0.343905 data_time: 0.030515 memory: 4565 loss: 0.000769 loss_kpt: 0.000769 acc_pose: 0.955327 2023/08/09 18:22:48 - mmengine - INFO - Epoch(train) [173][370/442] lr: 5.000000e-05 eta: 1:36:51 time: 0.344464 data_time: 0.030739 memory: 4565 loss: 0.000775 loss_kpt: 0.000775 acc_pose: 0.851054 2023/08/09 18:22:51 - mmengine - INFO - Epoch(train) [173][380/442] lr: 5.000000e-05 eta: 1:36:48 time: 0.342325 data_time: 0.031283 memory: 4565 loss: 0.000762 loss_kpt: 0.000762 acc_pose: 0.815262 2023/08/09 18:22:55 - mmengine - INFO - Epoch(train) [173][390/442] lr: 5.000000e-05 eta: 1:36:44 time: 0.342367 data_time: 0.031556 memory: 4565 loss: 0.000767 loss_kpt: 0.000767 acc_pose: 0.907015 2023/08/09 18:22:58 - mmengine - INFO - Epoch(train) [173][400/442] lr: 5.000000e-05 eta: 1:36:41 time: 0.342418 data_time: 0.031654 memory: 4565 loss: 0.000775 loss_kpt: 0.000775 acc_pose: 0.857527 2023/08/09 18:23:02 - mmengine - INFO - Epoch(train) [173][410/442] lr: 5.000000e-05 eta: 1:36:37 time: 0.342611 data_time: 0.031637 memory: 4565 loss: 0.000772 loss_kpt: 0.000772 acc_pose: 0.860822 2023/08/09 18:23:05 - mmengine - INFO - Epoch(train) [173][420/442] lr: 5.000000e-05 eta: 1:36:33 time: 0.344995 data_time: 0.031653 memory: 4565 loss: 0.000788 loss_kpt: 0.000788 acc_pose: 0.805471 2023/08/09 18:23:09 - mmengine - INFO - Epoch(train) [173][430/442] lr: 5.000000e-05 eta: 1:36:30 time: 0.346043 data_time: 0.031473 memory: 4565 loss: 0.000798 loss_kpt: 0.000798 acc_pose: 0.905275 2023/08/09 18:23:12 - mmengine - INFO - Epoch(train) [173][440/442] lr: 5.000000e-05 eta: 1:36:26 time: 0.351527 data_time: 0.031611 memory: 4565 loss: 0.000798 loss_kpt: 0.000798 acc_pose: 0.930534 2023/08/09 18:23:13 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:23:17 - mmengine - INFO - Epoch(train) [174][ 10/442] lr: 5.000000e-05 eta: 1:36:22 time: 0.358315 data_time: 0.035297 memory: 4565 loss: 0.000810 loss_kpt: 0.000810 acc_pose: 0.891987 2023/08/09 18:23:20 - mmengine - INFO - Epoch(train) [174][ 20/442] lr: 5.000000e-05 eta: 1:36:19 time: 0.358811 data_time: 0.035332 memory: 4565 loss: 0.000803 loss_kpt: 0.000803 acc_pose: 0.821054 2023/08/09 18:23:24 - mmengine - INFO - Epoch(train) [174][ 30/442] lr: 5.000000e-05 eta: 1:36:15 time: 0.357207 data_time: 0.035037 memory: 4565 loss: 0.000787 loss_kpt: 0.000787 acc_pose: 0.825372 2023/08/09 18:23:27 - mmengine - INFO - Epoch(train) [174][ 40/442] lr: 5.000000e-05 eta: 1:36:12 time: 0.358747 data_time: 0.035352 memory: 4565 loss: 0.000783 loss_kpt: 0.000783 acc_pose: 0.830860 2023/08/09 18:23:31 - mmengine - INFO - Epoch(train) [174][ 50/442] lr: 5.000000e-05 eta: 1:36:08 time: 0.358276 data_time: 0.035764 memory: 4565 loss: 0.000778 loss_kpt: 0.000778 acc_pose: 0.870596 2023/08/09 18:23:35 - mmengine - INFO - Epoch(train) [174][ 60/442] lr: 5.000000e-05 eta: 1:36:05 time: 0.352714 data_time: 0.031845 memory: 4565 loss: 0.000764 loss_kpt: 0.000764 acc_pose: 0.862246 2023/08/09 18:23:38 - mmengine - INFO - Epoch(train) [174][ 70/442] lr: 5.000000e-05 eta: 1:36:01 time: 0.352814 data_time: 0.032049 memory: 4565 loss: 0.000776 loss_kpt: 0.000776 acc_pose: 0.809514 2023/08/09 18:23:42 - mmengine - INFO - Epoch(train) [174][ 80/442] lr: 5.000000e-05 eta: 1:35:57 time: 0.354272 data_time: 0.031805 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.919100 2023/08/09 18:23:45 - mmengine - INFO - Epoch(train) [174][ 90/442] lr: 5.000000e-05 eta: 1:35:54 time: 0.352991 data_time: 0.031304 memory: 4565 loss: 0.000768 loss_kpt: 0.000768 acc_pose: 0.888464 2023/08/09 18:23:49 - mmengine - INFO - Epoch(train) [174][100/442] lr: 5.000000e-05 eta: 1:35:50 time: 0.351652 data_time: 0.030578 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.900263 2023/08/09 18:23:52 - mmengine - INFO - Epoch(train) [174][110/442] lr: 5.000000e-05 eta: 1:35:47 time: 0.351965 data_time: 0.030882 memory: 4565 loss: 0.000774 loss_kpt: 0.000774 acc_pose: 0.902076 2023/08/09 18:23:56 - mmengine - INFO - Epoch(train) [174][120/442] lr: 5.000000e-05 eta: 1:35:43 time: 0.352604 data_time: 0.030552 memory: 4565 loss: 0.000749 loss_kpt: 0.000749 acc_pose: 0.915258 2023/08/09 18:23:59 - mmengine - INFO - Epoch(train) [174][130/442] lr: 5.000000e-05 eta: 1:35:40 time: 0.352168 data_time: 0.031042 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.838055 2023/08/09 18:24:03 - mmengine - INFO - Epoch(train) [174][140/442] lr: 5.000000e-05 eta: 1:35:36 time: 0.352195 data_time: 0.031009 memory: 4565 loss: 0.000751 loss_kpt: 0.000751 acc_pose: 0.861969 2023/08/09 18:24:06 - mmengine - INFO - Epoch(train) [174][150/442] lr: 5.000000e-05 eta: 1:35:33 time: 0.352289 data_time: 0.031444 memory: 4565 loss: 0.000757 loss_kpt: 0.000757 acc_pose: 0.915094 2023/08/09 18:24:10 - mmengine - INFO - Epoch(train) [174][160/442] lr: 5.000000e-05 eta: 1:35:29 time: 0.354559 data_time: 0.031146 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.828249 2023/08/09 18:24:13 - mmengine - INFO - Epoch(train) [174][170/442] lr: 5.000000e-05 eta: 1:35:26 time: 0.355343 data_time: 0.031404 memory: 4565 loss: 0.000762 loss_kpt: 0.000762 acc_pose: 0.866835 2023/08/09 18:24:17 - mmengine - INFO - Epoch(train) [174][180/442] lr: 5.000000e-05 eta: 1:35:22 time: 0.355913 data_time: 0.031103 memory: 4565 loss: 0.000756 loss_kpt: 0.000756 acc_pose: 0.804471 2023/08/09 18:24:21 - mmengine - INFO - Epoch(train) [174][190/442] lr: 5.000000e-05 eta: 1:35:19 time: 0.358046 data_time: 0.031464 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.878459 2023/08/09 18:24:24 - mmengine - INFO - Epoch(train) [174][200/442] lr: 5.000000e-05 eta: 1:35:15 time: 0.357708 data_time: 0.030986 memory: 4565 loss: 0.000761 loss_kpt: 0.000761 acc_pose: 0.870697 2023/08/09 18:24:28 - mmengine - INFO - Epoch(train) [174][210/442] lr: 5.000000e-05 eta: 1:35:11 time: 0.354278 data_time: 0.030907 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.859714 2023/08/09 18:24:31 - mmengine - INFO - Epoch(train) [174][220/442] lr: 5.000000e-05 eta: 1:35:08 time: 0.354785 data_time: 0.030501 memory: 4565 loss: 0.000769 loss_kpt: 0.000769 acc_pose: 0.831293 2023/08/09 18:24:35 - mmengine - INFO - Epoch(train) [174][230/442] lr: 5.000000e-05 eta: 1:35:04 time: 0.353464 data_time: 0.030363 memory: 4565 loss: 0.000760 loss_kpt: 0.000760 acc_pose: 0.882773 2023/08/09 18:24:38 - mmengine - INFO - Epoch(train) [174][240/442] lr: 5.000000e-05 eta: 1:35:01 time: 0.352418 data_time: 0.030469 memory: 4565 loss: 0.000762 loss_kpt: 0.000762 acc_pose: 0.876098 2023/08/09 18:24:42 - mmengine - INFO - Epoch(train) [174][250/442] lr: 5.000000e-05 eta: 1:34:57 time: 0.356827 data_time: 0.031095 memory: 4565 loss: 0.000770 loss_kpt: 0.000770 acc_pose: 0.891591 2023/08/09 18:24:45 - mmengine - INFO - Epoch(train) [174][260/442] lr: 5.000000e-05 eta: 1:34:54 time: 0.357015 data_time: 0.031090 memory: 4565 loss: 0.000771 loss_kpt: 0.000771 acc_pose: 0.871050 2023/08/09 18:24:49 - mmengine - INFO - Epoch(train) [174][270/442] lr: 5.000000e-05 eta: 1:34:50 time: 0.354453 data_time: 0.031172 memory: 4565 loss: 0.000769 loss_kpt: 0.000769 acc_pose: 0.838717 2023/08/09 18:24:52 - mmengine - INFO - Epoch(train) [174][280/442] lr: 5.000000e-05 eta: 1:34:47 time: 0.353753 data_time: 0.031366 memory: 4565 loss: 0.000779 loss_kpt: 0.000779 acc_pose: 0.925351 2023/08/09 18:24:56 - mmengine - INFO - Epoch(train) [174][290/442] lr: 5.000000e-05 eta: 1:34:43 time: 0.353817 data_time: 0.030956 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.868375 2023/08/09 18:24:59 - mmengine - INFO - Epoch(train) [174][300/442] lr: 5.000000e-05 eta: 1:34:40 time: 0.349827 data_time: 0.030491 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.899976 2023/08/09 18:25:03 - mmengine - INFO - Epoch(train) [174][310/442] lr: 5.000000e-05 eta: 1:34:36 time: 0.353346 data_time: 0.033922 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.940118 2023/08/09 18:25:07 - mmengine - INFO - Epoch(train) [174][320/442] lr: 5.000000e-05 eta: 1:34:33 time: 0.356300 data_time: 0.034339 memory: 4565 loss: 0.000749 loss_kpt: 0.000749 acc_pose: 0.884770 2023/08/09 18:25:10 - mmengine - INFO - Epoch(train) [174][330/442] lr: 5.000000e-05 eta: 1:34:29 time: 0.360449 data_time: 0.038099 memory: 4565 loss: 0.000751 loss_kpt: 0.000751 acc_pose: 0.828493 2023/08/09 18:25:14 - mmengine - INFO - Epoch(train) [174][340/442] lr: 5.000000e-05 eta: 1:34:26 time: 0.359311 data_time: 0.037988 memory: 4565 loss: 0.000755 loss_kpt: 0.000755 acc_pose: 0.926155 2023/08/09 18:25:17 - mmengine - INFO - Epoch(train) [174][350/442] lr: 5.000000e-05 eta: 1:34:22 time: 0.360095 data_time: 0.038148 memory: 4565 loss: 0.000755 loss_kpt: 0.000755 acc_pose: 0.898475 2023/08/09 18:25:21 - mmengine - INFO - Epoch(train) [174][360/442] lr: 5.000000e-05 eta: 1:34:19 time: 0.356533 data_time: 0.034767 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.867235 2023/08/09 18:25:25 - mmengine - INFO - Epoch(train) [174][370/442] lr: 5.000000e-05 eta: 1:34:15 time: 0.355432 data_time: 0.034669 memory: 4565 loss: 0.000762 loss_kpt: 0.000762 acc_pose: 0.904915 2023/08/09 18:25:28 - mmengine - INFO - Epoch(train) [174][380/442] lr: 5.000000e-05 eta: 1:34:11 time: 0.352790 data_time: 0.031068 memory: 4565 loss: 0.000776 loss_kpt: 0.000776 acc_pose: 0.807725 2023/08/09 18:25:32 - mmengine - INFO - Epoch(train) [174][390/442] lr: 5.000000e-05 eta: 1:34:08 time: 0.353288 data_time: 0.031410 memory: 4565 loss: 0.000786 loss_kpt: 0.000786 acc_pose: 0.870440 2023/08/09 18:25:35 - mmengine - INFO - Epoch(train) [174][400/442] lr: 5.000000e-05 eta: 1:34:04 time: 0.352079 data_time: 0.031197 memory: 4565 loss: 0.000796 loss_kpt: 0.000796 acc_pose: 0.884506 2023/08/09 18:25:39 - mmengine - INFO - Epoch(train) [174][410/442] lr: 5.000000e-05 eta: 1:34:01 time: 0.351660 data_time: 0.031114 memory: 4565 loss: 0.000797 loss_kpt: 0.000797 acc_pose: 0.914225 2023/08/09 18:25:42 - mmengine - INFO - Epoch(train) [174][420/442] lr: 5.000000e-05 eta: 1:33:57 time: 0.353320 data_time: 0.030926 memory: 4565 loss: 0.000784 loss_kpt: 0.000784 acc_pose: 0.891372 2023/08/09 18:25:46 - mmengine - INFO - Epoch(train) [174][430/442] lr: 5.000000e-05 eta: 1:33:54 time: 0.352703 data_time: 0.030743 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.911918 2023/08/09 18:25:49 - mmengine - INFO - Epoch(train) [174][440/442] lr: 5.000000e-05 eta: 1:33:50 time: 0.352480 data_time: 0.030527 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.893349 2023/08/09 18:25:50 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:25:54 - mmengine - INFO - Epoch(train) [175][ 10/442] lr: 5.000000e-05 eta: 1:33:46 time: 0.357149 data_time: 0.034449 memory: 4565 loss: 0.000749 loss_kpt: 0.000749 acc_pose: 0.894195 2023/08/09 18:25:57 - mmengine - INFO - Epoch(train) [175][ 20/442] lr: 5.000000e-05 eta: 1:33:42 time: 0.356466 data_time: 0.034329 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.877395 2023/08/09 18:26:01 - mmengine - INFO - Epoch(train) [175][ 30/442] lr: 5.000000e-05 eta: 1:33:39 time: 0.353275 data_time: 0.034273 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.881534 2023/08/09 18:26:04 - mmengine - INFO - Epoch(train) [175][ 40/442] lr: 5.000000e-05 eta: 1:33:35 time: 0.353803 data_time: 0.034931 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.853939 2023/08/09 18:26:08 - mmengine - INFO - Epoch(train) [175][ 50/442] lr: 5.000000e-05 eta: 1:33:32 time: 0.358757 data_time: 0.038984 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.880237 2023/08/09 18:26:12 - mmengine - INFO - Epoch(train) [175][ 60/442] lr: 5.000000e-05 eta: 1:33:29 time: 0.363893 data_time: 0.035799 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.882791 2023/08/09 18:26:16 - mmengine - INFO - Epoch(train) [175][ 70/442] lr: 5.000000e-05 eta: 1:33:25 time: 0.375667 data_time: 0.036291 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.953217 2023/08/09 18:26:20 - mmengine - INFO - Epoch(train) [175][ 80/442] lr: 5.000000e-05 eta: 1:33:22 time: 0.379809 data_time: 0.036268 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.844815 2023/08/09 18:26:23 - mmengine - INFO - Epoch(train) [175][ 90/442] lr: 5.000000e-05 eta: 1:33:18 time: 0.378439 data_time: 0.035469 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.853465 2023/08/09 18:26:24 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:26:27 - mmengine - INFO - Epoch(train) [175][100/442] lr: 5.000000e-05 eta: 1:33:15 time: 0.377272 data_time: 0.031616 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.813778 2023/08/09 18:26:30 - mmengine - INFO - Epoch(train) [175][110/442] lr: 5.000000e-05 eta: 1:33:11 time: 0.368254 data_time: 0.030890 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.910299 2023/08/09 18:26:34 - mmengine - INFO - Epoch(train) [175][120/442] lr: 5.000000e-05 eta: 1:33:08 time: 0.358707 data_time: 0.030803 memory: 4565 loss: 0.000764 loss_kpt: 0.000764 acc_pose: 0.902410 2023/08/09 18:26:38 - mmengine - INFO - Epoch(train) [175][130/442] lr: 5.000000e-05 eta: 1:33:04 time: 0.358396 data_time: 0.031884 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.857397 2023/08/09 18:26:41 - mmengine - INFO - Epoch(train) [175][140/442] lr: 5.000000e-05 eta: 1:33:01 time: 0.358362 data_time: 0.032458 memory: 4565 loss: 0.000776 loss_kpt: 0.000776 acc_pose: 0.835850 2023/08/09 18:26:45 - mmengine - INFO - Epoch(train) [175][150/442] lr: 5.000000e-05 eta: 1:32:57 time: 0.355159 data_time: 0.032947 memory: 4565 loss: 0.000751 loss_kpt: 0.000751 acc_pose: 0.846677 2023/08/09 18:26:48 - mmengine - INFO - Epoch(train) [175][160/442] lr: 5.000000e-05 eta: 1:32:54 time: 0.353619 data_time: 0.033312 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.862622 2023/08/09 18:26:51 - mmengine - INFO - Epoch(train) [175][170/442] lr: 5.000000e-05 eta: 1:32:50 time: 0.351866 data_time: 0.033760 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.848718 2023/08/09 18:26:55 - mmengine - INFO - Epoch(train) [175][180/442] lr: 5.000000e-05 eta: 1:32:47 time: 0.350461 data_time: 0.033467 memory: 4565 loss: 0.000755 loss_kpt: 0.000755 acc_pose: 0.851496 2023/08/09 18:26:59 - mmengine - INFO - Epoch(train) [175][190/442] lr: 5.000000e-05 eta: 1:32:43 time: 0.351295 data_time: 0.033096 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.877511 2023/08/09 18:27:02 - mmengine - INFO - Epoch(train) [175][200/442] lr: 5.000000e-05 eta: 1:32:39 time: 0.351896 data_time: 0.032654 memory: 4565 loss: 0.000768 loss_kpt: 0.000768 acc_pose: 0.906443 2023/08/09 18:27:06 - mmengine - INFO - Epoch(train) [175][210/442] lr: 5.000000e-05 eta: 1:32:36 time: 0.352347 data_time: 0.032233 memory: 4565 loss: 0.000773 loss_kpt: 0.000773 acc_pose: 0.881568 2023/08/09 18:27:09 - mmengine - INFO - Epoch(train) [175][220/442] lr: 5.000000e-05 eta: 1:32:32 time: 0.352588 data_time: 0.031580 memory: 4565 loss: 0.000773 loss_kpt: 0.000773 acc_pose: 0.954492 2023/08/09 18:27:13 - mmengine - INFO - Epoch(train) [175][230/442] lr: 5.000000e-05 eta: 1:32:29 time: 0.350452 data_time: 0.030685 memory: 4565 loss: 0.000768 loss_kpt: 0.000768 acc_pose: 0.774868 2023/08/09 18:27:16 - mmengine - INFO - Epoch(train) [175][240/442] lr: 5.000000e-05 eta: 1:32:25 time: 0.350827 data_time: 0.030507 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.886620 2023/08/09 18:27:20 - mmengine - INFO - Epoch(train) [175][250/442] lr: 5.000000e-05 eta: 1:32:22 time: 0.351299 data_time: 0.030753 memory: 4565 loss: 0.000758 loss_kpt: 0.000758 acc_pose: 0.902177 2023/08/09 18:27:23 - mmengine - INFO - Epoch(train) [175][260/442] lr: 5.000000e-05 eta: 1:32:18 time: 0.355489 data_time: 0.030904 memory: 4565 loss: 0.000757 loss_kpt: 0.000757 acc_pose: 0.900972 2023/08/09 18:27:27 - mmengine - INFO - Epoch(train) [175][270/442] lr: 5.000000e-05 eta: 1:32:15 time: 0.354890 data_time: 0.030799 memory: 4565 loss: 0.000755 loss_kpt: 0.000755 acc_pose: 0.893351 2023/08/09 18:27:30 - mmengine - INFO - Epoch(train) [175][280/442] lr: 5.000000e-05 eta: 1:32:11 time: 0.354473 data_time: 0.030794 memory: 4565 loss: 0.000764 loss_kpt: 0.000764 acc_pose: 0.871191 2023/08/09 18:27:34 - mmengine - INFO - Epoch(train) [175][290/442] lr: 5.000000e-05 eta: 1:32:08 time: 0.355367 data_time: 0.033874 memory: 4565 loss: 0.000757 loss_kpt: 0.000757 acc_pose: 0.917261 2023/08/09 18:27:37 - mmengine - INFO - Epoch(train) [175][300/442] lr: 5.000000e-05 eta: 1:32:04 time: 0.354227 data_time: 0.033757 memory: 4565 loss: 0.000772 loss_kpt: 0.000772 acc_pose: 0.819661 2023/08/09 18:27:41 - mmengine - INFO - Epoch(train) [175][310/442] lr: 5.000000e-05 eta: 1:32:01 time: 0.350873 data_time: 0.033800 memory: 4565 loss: 0.000780 loss_kpt: 0.000780 acc_pose: 0.894370 2023/08/09 18:27:44 - mmengine - INFO - Epoch(train) [175][320/442] lr: 5.000000e-05 eta: 1:31:57 time: 0.352137 data_time: 0.034211 memory: 4565 loss: 0.000777 loss_kpt: 0.000777 acc_pose: 0.938714 2023/08/09 18:27:48 - mmengine - INFO - Epoch(train) [175][330/442] lr: 5.000000e-05 eta: 1:31:53 time: 0.354487 data_time: 0.035279 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.811142 2023/08/09 18:27:52 - mmengine - INFO - Epoch(train) [175][340/442] lr: 5.000000e-05 eta: 1:31:50 time: 0.356442 data_time: 0.033070 memory: 4565 loss: 0.000773 loss_kpt: 0.000773 acc_pose: 0.842684 2023/08/09 18:27:55 - mmengine - INFO - Epoch(train) [175][350/442] lr: 5.000000e-05 eta: 1:31:46 time: 0.357215 data_time: 0.034228 memory: 4565 loss: 0.000757 loss_kpt: 0.000757 acc_pose: 0.845933 2023/08/09 18:27:59 - mmengine - INFO - Epoch(train) [175][360/442] lr: 5.000000e-05 eta: 1:31:43 time: 0.356221 data_time: 0.034374 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.934957 2023/08/09 18:28:02 - mmengine - INFO - Epoch(train) [175][370/442] lr: 5.000000e-05 eta: 1:31:39 time: 0.356360 data_time: 0.034409 memory: 4565 loss: 0.000773 loss_kpt: 0.000773 acc_pose: 0.862870 2023/08/09 18:28:06 - mmengine - INFO - Epoch(train) [175][380/442] lr: 5.000000e-05 eta: 1:31:36 time: 0.357713 data_time: 0.033544 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.847615 2023/08/09 18:28:10 - mmengine - INFO - Epoch(train) [175][390/442] lr: 5.000000e-05 eta: 1:31:32 time: 0.357014 data_time: 0.033132 memory: 4565 loss: 0.000755 loss_kpt: 0.000755 acc_pose: 0.907860 2023/08/09 18:28:13 - mmengine - INFO - Epoch(train) [175][400/442] lr: 5.000000e-05 eta: 1:31:29 time: 0.356262 data_time: 0.031889 memory: 4565 loss: 0.000762 loss_kpt: 0.000762 acc_pose: 0.872642 2023/08/09 18:28:17 - mmengine - INFO - Epoch(train) [175][410/442] lr: 5.000000e-05 eta: 1:31:25 time: 0.356036 data_time: 0.031354 memory: 4565 loss: 0.000749 loss_kpt: 0.000749 acc_pose: 0.840828 2023/08/09 18:28:20 - mmengine - INFO - Epoch(train) [175][420/442] lr: 5.000000e-05 eta: 1:31:22 time: 0.357648 data_time: 0.030953 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.885255 2023/08/09 18:28:24 - mmengine - INFO - Epoch(train) [175][430/442] lr: 5.000000e-05 eta: 1:31:18 time: 0.359947 data_time: 0.031143 memory: 4565 loss: 0.000767 loss_kpt: 0.000767 acc_pose: 0.878010 2023/08/09 18:28:28 - mmengine - INFO - Epoch(train) [175][440/442] lr: 5.000000e-05 eta: 1:31:15 time: 0.360419 data_time: 0.030964 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.915068 2023/08/09 18:28:28 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:28:32 - mmengine - INFO - Epoch(train) [176][ 10/442] lr: 5.000000e-05 eta: 1:31:11 time: 0.363539 data_time: 0.035043 memory: 4565 loss: 0.000758 loss_kpt: 0.000758 acc_pose: 0.824881 2023/08/09 18:28:35 - mmengine - INFO - Epoch(train) [176][ 20/442] lr: 5.000000e-05 eta: 1:31:07 time: 0.359135 data_time: 0.035138 memory: 4565 loss: 0.000765 loss_kpt: 0.000765 acc_pose: 0.879600 2023/08/09 18:28:39 - mmengine - INFO - Epoch(train) [176][ 30/442] lr: 5.000000e-05 eta: 1:31:03 time: 0.356937 data_time: 0.035082 memory: 4565 loss: 0.000764 loss_kpt: 0.000764 acc_pose: 0.941319 2023/08/09 18:28:42 - mmengine - INFO - Epoch(train) [176][ 40/442] lr: 5.000000e-05 eta: 1:31:00 time: 0.348005 data_time: 0.034642 memory: 4565 loss: 0.000769 loss_kpt: 0.000769 acc_pose: 0.892025 2023/08/09 18:28:46 - mmengine - INFO - Epoch(train) [176][ 50/442] lr: 5.000000e-05 eta: 1:30:56 time: 0.345221 data_time: 0.034692 memory: 4565 loss: 0.000757 loss_kpt: 0.000757 acc_pose: 0.861006 2023/08/09 18:28:49 - mmengine - INFO - Epoch(train) [176][ 60/442] lr: 5.000000e-05 eta: 1:30:53 time: 0.343241 data_time: 0.030609 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.870347 2023/08/09 18:28:53 - mmengine - INFO - Epoch(train) [176][ 70/442] lr: 5.000000e-05 eta: 1:30:49 time: 0.344718 data_time: 0.030881 memory: 4565 loss: 0.000761 loss_kpt: 0.000761 acc_pose: 0.871239 2023/08/09 18:28:56 - mmengine - INFO - Epoch(train) [176][ 80/442] lr: 5.000000e-05 eta: 1:30:46 time: 0.347973 data_time: 0.031281 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.911029 2023/08/09 18:29:00 - mmengine - INFO - Epoch(train) [176][ 90/442] lr: 5.000000e-05 eta: 1:30:42 time: 0.347502 data_time: 0.031326 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.899058 2023/08/09 18:29:03 - mmengine - INFO - Epoch(train) [176][100/442] lr: 5.000000e-05 eta: 1:30:38 time: 0.347525 data_time: 0.031317 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.856494 2023/08/09 18:29:07 - mmengine - INFO - Epoch(train) [176][110/442] lr: 5.000000e-05 eta: 1:30:35 time: 0.347312 data_time: 0.032339 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.911407 2023/08/09 18:29:10 - mmengine - INFO - Epoch(train) [176][120/442] lr: 5.000000e-05 eta: 1:30:31 time: 0.348432 data_time: 0.032231 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.864457 2023/08/09 18:29:14 - mmengine - INFO - Epoch(train) [176][130/442] lr: 5.000000e-05 eta: 1:30:28 time: 0.349208 data_time: 0.032415 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.802025 2023/08/09 18:29:17 - mmengine - INFO - Epoch(train) [176][140/442] lr: 5.000000e-05 eta: 1:30:24 time: 0.352939 data_time: 0.032839 memory: 4565 loss: 0.000755 loss_kpt: 0.000755 acc_pose: 0.867711 2023/08/09 18:29:21 - mmengine - INFO - Epoch(train) [176][150/442] lr: 5.000000e-05 eta: 1:30:21 time: 0.354676 data_time: 0.033066 memory: 4565 loss: 0.000768 loss_kpt: 0.000768 acc_pose: 0.907755 2023/08/09 18:29:24 - mmengine - INFO - Epoch(train) [176][160/442] lr: 5.000000e-05 eta: 1:30:17 time: 0.352700 data_time: 0.031805 memory: 4565 loss: 0.000777 loss_kpt: 0.000777 acc_pose: 0.919822 2023/08/09 18:29:28 - mmengine - INFO - Epoch(train) [176][170/442] lr: 5.000000e-05 eta: 1:30:14 time: 0.351822 data_time: 0.031864 memory: 4565 loss: 0.000778 loss_kpt: 0.000778 acc_pose: 0.901026 2023/08/09 18:29:31 - mmengine - INFO - Epoch(train) [176][180/442] lr: 5.000000e-05 eta: 1:30:10 time: 0.350133 data_time: 0.031751 memory: 4565 loss: 0.000779 loss_kpt: 0.000779 acc_pose: 0.924733 2023/08/09 18:29:35 - mmengine - INFO - Epoch(train) [176][190/442] lr: 5.000000e-05 eta: 1:30:06 time: 0.349901 data_time: 0.031335 memory: 4565 loss: 0.000773 loss_kpt: 0.000773 acc_pose: 0.899556 2023/08/09 18:29:38 - mmengine - INFO - Epoch(train) [176][200/442] lr: 5.000000e-05 eta: 1:30:03 time: 0.354324 data_time: 0.031861 memory: 4565 loss: 0.000774 loss_kpt: 0.000774 acc_pose: 0.908692 2023/08/09 18:29:42 - mmengine - INFO - Epoch(train) [176][210/442] lr: 5.000000e-05 eta: 1:29:59 time: 0.355403 data_time: 0.032062 memory: 4565 loss: 0.000775 loss_kpt: 0.000775 acc_pose: 0.922645 2023/08/09 18:29:45 - mmengine - INFO - Epoch(train) [176][220/442] lr: 5.000000e-05 eta: 1:29:56 time: 0.356097 data_time: 0.031834 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.910745 2023/08/09 18:29:49 - mmengine - INFO - Epoch(train) [176][230/442] lr: 5.000000e-05 eta: 1:29:52 time: 0.359171 data_time: 0.031475 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.906257 2023/08/09 18:29:53 - mmengine - INFO - Epoch(train) [176][240/442] lr: 5.000000e-05 eta: 1:29:49 time: 0.358113 data_time: 0.031464 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.911720 2023/08/09 18:29:56 - mmengine - INFO - Epoch(train) [176][250/442] lr: 5.000000e-05 eta: 1:29:45 time: 0.354274 data_time: 0.030865 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.858934 2023/08/09 18:30:00 - mmengine - INFO - Epoch(train) [176][260/442] lr: 5.000000e-05 eta: 1:29:42 time: 0.353419 data_time: 0.030763 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.904001 2023/08/09 18:30:03 - mmengine - INFO - Epoch(train) [176][270/442] lr: 5.000000e-05 eta: 1:29:38 time: 0.354879 data_time: 0.031332 memory: 4565 loss: 0.000749 loss_kpt: 0.000749 acc_pose: 0.839315 2023/08/09 18:30:07 - mmengine - INFO - Epoch(train) [176][280/442] lr: 5.000000e-05 eta: 1:29:35 time: 0.352762 data_time: 0.031346 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.927309 2023/08/09 18:30:10 - mmengine - INFO - Epoch(train) [176][290/442] lr: 5.000000e-05 eta: 1:29:31 time: 0.352381 data_time: 0.031445 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.902657 2023/08/09 18:30:14 - mmengine - INFO - Epoch(train) [176][300/442] lr: 5.000000e-05 eta: 1:29:28 time: 0.352002 data_time: 0.031560 memory: 4565 loss: 0.000753 loss_kpt: 0.000753 acc_pose: 0.878354 2023/08/09 18:30:17 - mmengine - INFO - Epoch(train) [176][310/442] lr: 5.000000e-05 eta: 1:29:24 time: 0.351675 data_time: 0.031731 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.911307 2023/08/09 18:30:21 - mmengine - INFO - Epoch(train) [176][320/442] lr: 5.000000e-05 eta: 1:29:20 time: 0.350950 data_time: 0.031658 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.891930 2023/08/09 18:30:24 - mmengine - INFO - Epoch(train) [176][330/442] lr: 5.000000e-05 eta: 1:29:17 time: 0.350140 data_time: 0.031678 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.866841 2023/08/09 18:30:28 - mmengine - INFO - Epoch(train) [176][340/442] lr: 5.000000e-05 eta: 1:29:13 time: 0.355578 data_time: 0.031913 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.860451 2023/08/09 18:30:32 - mmengine - INFO - Epoch(train) [176][350/442] lr: 5.000000e-05 eta: 1:29:10 time: 0.355902 data_time: 0.031958 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.855761 2023/08/09 18:30:35 - mmengine - INFO - Epoch(train) [176][360/442] lr: 5.000000e-05 eta: 1:29:06 time: 0.358693 data_time: 0.032082 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.896073 2023/08/09 18:30:39 - mmengine - INFO - Epoch(train) [176][370/442] lr: 5.000000e-05 eta: 1:29:03 time: 0.357730 data_time: 0.032175 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.888545 2023/08/09 18:30:42 - mmengine - INFO - Epoch(train) [176][380/442] lr: 5.000000e-05 eta: 1:28:59 time: 0.358010 data_time: 0.032480 memory: 4565 loss: 0.000758 loss_kpt: 0.000758 acc_pose: 0.795624 2023/08/09 18:30:46 - mmengine - INFO - Epoch(train) [176][390/442] lr: 5.000000e-05 eta: 1:28:56 time: 0.353426 data_time: 0.032925 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.904914 2023/08/09 18:30:49 - mmengine - INFO - Epoch(train) [176][400/442] lr: 5.000000e-05 eta: 1:28:52 time: 0.355875 data_time: 0.033654 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.960443 2023/08/09 18:30:53 - mmengine - INFO - Epoch(train) [176][410/442] lr: 5.000000e-05 eta: 1:28:49 time: 0.352807 data_time: 0.033409 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.949083 2023/08/09 18:30:56 - mmengine - INFO - Epoch(train) [176][420/442] lr: 5.000000e-05 eta: 1:28:45 time: 0.352417 data_time: 0.032808 memory: 4565 loss: 0.000749 loss_kpt: 0.000749 acc_pose: 0.848677 2023/08/09 18:31:00 - mmengine - INFO - Epoch(train) [176][430/442] lr: 5.000000e-05 eta: 1:28:42 time: 0.350810 data_time: 0.032444 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.900825 2023/08/09 18:31:03 - mmengine - INFO - Epoch(train) [176][440/442] lr: 5.000000e-05 eta: 1:28:38 time: 0.349818 data_time: 0.031753 memory: 4565 loss: 0.000767 loss_kpt: 0.000767 acc_pose: 0.876326 2023/08/09 18:31:04 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:31:08 - mmengine - INFO - Epoch(train) [177][ 10/442] lr: 5.000000e-05 eta: 1:28:34 time: 0.348415 data_time: 0.034658 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.947272 2023/08/09 18:31:11 - mmengine - INFO - Epoch(train) [177][ 20/442] lr: 5.000000e-05 eta: 1:28:30 time: 0.349693 data_time: 0.034487 memory: 4565 loss: 0.000765 loss_kpt: 0.000765 acc_pose: 0.931965 2023/08/09 18:31:15 - mmengine - INFO - Epoch(train) [177][ 30/442] lr: 5.000000e-05 eta: 1:28:27 time: 0.348608 data_time: 0.034884 memory: 4565 loss: 0.000767 loss_kpt: 0.000767 acc_pose: 0.944736 2023/08/09 18:31:18 - mmengine - INFO - Epoch(train) [177][ 40/442] lr: 5.000000e-05 eta: 1:28:23 time: 0.350312 data_time: 0.035501 memory: 4565 loss: 0.000756 loss_kpt: 0.000756 acc_pose: 0.888090 2023/08/09 18:31:22 - mmengine - INFO - Epoch(train) [177][ 50/442] lr: 5.000000e-05 eta: 1:28:19 time: 0.352616 data_time: 0.039491 memory: 4565 loss: 0.000753 loss_kpt: 0.000753 acc_pose: 0.859785 2023/08/09 18:31:25 - mmengine - INFO - Epoch(train) [177][ 60/442] lr: 5.000000e-05 eta: 1:28:16 time: 0.350248 data_time: 0.035778 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.809997 2023/08/09 18:31:29 - mmengine - INFO - Epoch(train) [177][ 70/442] lr: 5.000000e-05 eta: 1:28:12 time: 0.349246 data_time: 0.035833 memory: 4565 loss: 0.000767 loss_kpt: 0.000767 acc_pose: 0.887760 2023/08/09 18:31:32 - mmengine - INFO - Epoch(train) [177][ 80/442] lr: 5.000000e-05 eta: 1:28:09 time: 0.349252 data_time: 0.035494 memory: 4565 loss: 0.000751 loss_kpt: 0.000751 acc_pose: 0.849876 2023/08/09 18:31:35 - mmengine - INFO - Epoch(train) [177][ 90/442] lr: 5.000000e-05 eta: 1:28:05 time: 0.348943 data_time: 0.035225 memory: 4565 loss: 0.000755 loss_kpt: 0.000755 acc_pose: 0.895045 2023/08/09 18:31:39 - mmengine - INFO - Epoch(train) [177][100/442] lr: 5.000000e-05 eta: 1:28:02 time: 0.352359 data_time: 0.031626 memory: 4565 loss: 0.000748 loss_kpt: 0.000748 acc_pose: 0.887554 2023/08/09 18:31:43 - mmengine - INFO - Epoch(train) [177][110/442] lr: 5.000000e-05 eta: 1:27:58 time: 0.359701 data_time: 0.031534 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.891378 2023/08/09 18:31:47 - mmengine - INFO - Epoch(train) [177][120/442] lr: 5.000000e-05 eta: 1:27:55 time: 0.368158 data_time: 0.031941 memory: 4565 loss: 0.000748 loss_kpt: 0.000748 acc_pose: 0.830452 2023/08/09 18:31:51 - mmengine - INFO - Epoch(train) [177][130/442] lr: 5.000000e-05 eta: 1:27:52 time: 0.370805 data_time: 0.032050 memory: 4565 loss: 0.000762 loss_kpt: 0.000762 acc_pose: 0.910931 2023/08/09 18:31:54 - mmengine - INFO - Epoch(train) [177][140/442] lr: 5.000000e-05 eta: 1:27:48 time: 0.370708 data_time: 0.032463 memory: 4565 loss: 0.000761 loss_kpt: 0.000761 acc_pose: 0.942185 2023/08/09 18:31:58 - mmengine - INFO - Epoch(train) [177][150/442] lr: 5.000000e-05 eta: 1:27:44 time: 0.369344 data_time: 0.032604 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.900339 2023/08/09 18:32:01 - mmengine - INFO - Epoch(train) [177][160/442] lr: 5.000000e-05 eta: 1:27:41 time: 0.363542 data_time: 0.032272 memory: 4565 loss: 0.000751 loss_kpt: 0.000751 acc_pose: 0.807165 2023/08/09 18:32:05 - mmengine - INFO - Epoch(train) [177][170/442] lr: 5.000000e-05 eta: 1:27:37 time: 0.359100 data_time: 0.031959 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.860066 2023/08/09 18:32:09 - mmengine - INFO - Epoch(train) [177][180/442] lr: 5.000000e-05 eta: 1:27:34 time: 0.365446 data_time: 0.032284 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.845328 2023/08/09 18:32:13 - mmengine - INFO - Epoch(train) [177][190/442] lr: 5.000000e-05 eta: 1:27:31 time: 0.369593 data_time: 0.031722 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.867998 2023/08/09 18:32:16 - mmengine - INFO - Epoch(train) [177][200/442] lr: 5.000000e-05 eta: 1:27:27 time: 0.367850 data_time: 0.031921 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.885158 2023/08/09 18:32:19 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:32:20 - mmengine - INFO - Epoch(train) [177][210/442] lr: 5.000000e-05 eta: 1:27:24 time: 0.367098 data_time: 0.032055 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.873297 2023/08/09 18:32:23 - mmengine - INFO - Epoch(train) [177][220/442] lr: 5.000000e-05 eta: 1:27:20 time: 0.363712 data_time: 0.032193 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.856200 2023/08/09 18:32:27 - mmengine - INFO - Epoch(train) [177][230/442] lr: 5.000000e-05 eta: 1:27:17 time: 0.358779 data_time: 0.031709 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.863415 2023/08/09 18:32:30 - mmengine - INFO - Epoch(train) [177][240/442] lr: 5.000000e-05 eta: 1:27:13 time: 0.354188 data_time: 0.031525 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.866943 2023/08/09 18:32:34 - mmengine - INFO - Epoch(train) [177][250/442] lr: 5.000000e-05 eta: 1:27:09 time: 0.352685 data_time: 0.030986 memory: 4565 loss: 0.000760 loss_kpt: 0.000760 acc_pose: 0.857668 2023/08/09 18:32:37 - mmengine - INFO - Epoch(train) [177][260/442] lr: 5.000000e-05 eta: 1:27:06 time: 0.352741 data_time: 0.030912 memory: 4565 loss: 0.000764 loss_kpt: 0.000764 acc_pose: 0.887841 2023/08/09 18:32:41 - mmengine - INFO - Epoch(train) [177][270/442] lr: 5.000000e-05 eta: 1:27:02 time: 0.353693 data_time: 0.030790 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.907929 2023/08/09 18:32:44 - mmengine - INFO - Epoch(train) [177][280/442] lr: 5.000000e-05 eta: 1:26:59 time: 0.352014 data_time: 0.030936 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.835880 2023/08/09 18:32:48 - mmengine - INFO - Epoch(train) [177][290/442] lr: 5.000000e-05 eta: 1:26:55 time: 0.352615 data_time: 0.030833 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.924003 2023/08/09 18:32:51 - mmengine - INFO - Epoch(train) [177][300/442] lr: 5.000000e-05 eta: 1:26:52 time: 0.353198 data_time: 0.030757 memory: 4565 loss: 0.000756 loss_kpt: 0.000756 acc_pose: 0.898566 2023/08/09 18:32:55 - mmengine - INFO - Epoch(train) [177][310/442] lr: 5.000000e-05 eta: 1:26:48 time: 0.352199 data_time: 0.030543 memory: 4565 loss: 0.000757 loss_kpt: 0.000757 acc_pose: 0.845138 2023/08/09 18:32:58 - mmengine - INFO - Epoch(train) [177][320/442] lr: 5.000000e-05 eta: 1:26:45 time: 0.350855 data_time: 0.030280 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.858749 2023/08/09 18:33:02 - mmengine - INFO - Epoch(train) [177][330/442] lr: 5.000000e-05 eta: 1:26:41 time: 0.353426 data_time: 0.030311 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.893438 2023/08/09 18:33:06 - mmengine - INFO - Epoch(train) [177][340/442] lr: 5.000000e-05 eta: 1:26:38 time: 0.354169 data_time: 0.030876 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.912615 2023/08/09 18:33:09 - mmengine - INFO - Epoch(train) [177][350/442] lr: 5.000000e-05 eta: 1:26:34 time: 0.355360 data_time: 0.031326 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.877369 2023/08/09 18:33:13 - mmengine - INFO - Epoch(train) [177][360/442] lr: 5.000000e-05 eta: 1:26:30 time: 0.354920 data_time: 0.031520 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.889767 2023/08/09 18:33:16 - mmengine - INFO - Epoch(train) [177][370/442] lr: 5.000000e-05 eta: 1:26:27 time: 0.354042 data_time: 0.031501 memory: 4565 loss: 0.000756 loss_kpt: 0.000756 acc_pose: 0.856820 2023/08/09 18:33:20 - mmengine - INFO - Epoch(train) [177][380/442] lr: 5.000000e-05 eta: 1:26:23 time: 0.350841 data_time: 0.031340 memory: 4565 loss: 0.000787 loss_kpt: 0.000787 acc_pose: 0.906439 2023/08/09 18:33:23 - mmengine - INFO - Epoch(train) [177][390/442] lr: 5.000000e-05 eta: 1:26:20 time: 0.350919 data_time: 0.031989 memory: 4565 loss: 0.000778 loss_kpt: 0.000778 acc_pose: 0.891896 2023/08/09 18:33:27 - mmengine - INFO - Epoch(train) [177][400/442] lr: 5.000000e-05 eta: 1:26:16 time: 0.351138 data_time: 0.032086 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.892418 2023/08/09 18:33:30 - mmengine - INFO - Epoch(train) [177][410/442] lr: 5.000000e-05 eta: 1:26:13 time: 0.353771 data_time: 0.032141 memory: 4565 loss: 0.000748 loss_kpt: 0.000748 acc_pose: 0.928707 2023/08/09 18:33:34 - mmengine - INFO - Epoch(train) [177][420/442] lr: 5.000000e-05 eta: 1:26:09 time: 0.354518 data_time: 0.032257 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.860302 2023/08/09 18:33:37 - mmengine - INFO - Epoch(train) [177][430/442] lr: 5.000000e-05 eta: 1:26:06 time: 0.353427 data_time: 0.032104 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.868456 2023/08/09 18:33:41 - mmengine - INFO - Epoch(train) [177][440/442] lr: 5.000000e-05 eta: 1:26:02 time: 0.352082 data_time: 0.030971 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.827969 2023/08/09 18:33:41 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:33:45 - mmengine - INFO - Epoch(train) [178][ 10/442] lr: 5.000000e-05 eta: 1:25:58 time: 0.350798 data_time: 0.034088 memory: 4565 loss: 0.000767 loss_kpt: 0.000767 acc_pose: 0.830661 2023/08/09 18:33:48 - mmengine - INFO - Epoch(train) [178][ 20/442] lr: 5.000000e-05 eta: 1:25:54 time: 0.347875 data_time: 0.034352 memory: 4565 loss: 0.000761 loss_kpt: 0.000761 acc_pose: 0.904795 2023/08/09 18:33:52 - mmengine - INFO - Epoch(train) [178][ 30/442] lr: 5.000000e-05 eta: 1:25:51 time: 0.353973 data_time: 0.038229 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.871599 2023/08/09 18:33:56 - mmengine - INFO - Epoch(train) [178][ 40/442] lr: 5.000000e-05 eta: 1:25:47 time: 0.352363 data_time: 0.038559 memory: 4565 loss: 0.000762 loss_kpt: 0.000762 acc_pose: 0.897338 2023/08/09 18:33:59 - mmengine - INFO - Epoch(train) [178][ 50/442] lr: 5.000000e-05 eta: 1:25:44 time: 0.352497 data_time: 0.039598 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.866350 2023/08/09 18:34:02 - mmengine - INFO - Epoch(train) [178][ 60/442] lr: 5.000000e-05 eta: 1:25:40 time: 0.348574 data_time: 0.035577 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.888745 2023/08/09 18:34:06 - mmengine - INFO - Epoch(train) [178][ 70/442] lr: 5.000000e-05 eta: 1:25:36 time: 0.347879 data_time: 0.035224 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.869607 2023/08/09 18:34:09 - mmengine - INFO - Epoch(train) [178][ 80/442] lr: 5.000000e-05 eta: 1:25:33 time: 0.342001 data_time: 0.031769 memory: 4565 loss: 0.000751 loss_kpt: 0.000751 acc_pose: 0.819312 2023/08/09 18:34:13 - mmengine - INFO - Epoch(train) [178][ 90/442] lr: 5.000000e-05 eta: 1:25:29 time: 0.346307 data_time: 0.031698 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.858164 2023/08/09 18:34:16 - mmengine - INFO - Epoch(train) [178][100/442] lr: 5.000000e-05 eta: 1:25:26 time: 0.348663 data_time: 0.031409 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.853071 2023/08/09 18:34:20 - mmengine - INFO - Epoch(train) [178][110/442] lr: 5.000000e-05 eta: 1:25:22 time: 0.348323 data_time: 0.031550 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.875014 2023/08/09 18:34:23 - mmengine - INFO - Epoch(train) [178][120/442] lr: 5.000000e-05 eta: 1:25:19 time: 0.348661 data_time: 0.031525 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.908880 2023/08/09 18:34:27 - mmengine - INFO - Epoch(train) [178][130/442] lr: 5.000000e-05 eta: 1:25:15 time: 0.354269 data_time: 0.031350 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.837023 2023/08/09 18:34:31 - mmengine - INFO - Epoch(train) [178][140/442] lr: 5.000000e-05 eta: 1:25:12 time: 0.357267 data_time: 0.031425 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.899669 2023/08/09 18:34:34 - mmengine - INFO - Epoch(train) [178][150/442] lr: 5.000000e-05 eta: 1:25:08 time: 0.356042 data_time: 0.031264 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.926874 2023/08/09 18:34:38 - mmengine - INFO - Epoch(train) [178][160/442] lr: 5.000000e-05 eta: 1:25:05 time: 0.359427 data_time: 0.031571 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.868239 2023/08/09 18:34:41 - mmengine - INFO - Epoch(train) [178][170/442] lr: 5.000000e-05 eta: 1:25:01 time: 0.361417 data_time: 0.031552 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.867264 2023/08/09 18:34:45 - mmengine - INFO - Epoch(train) [178][180/442] lr: 5.000000e-05 eta: 1:24:57 time: 0.354237 data_time: 0.031299 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.885958 2023/08/09 18:34:48 - mmengine - INFO - Epoch(train) [178][190/442] lr: 5.000000e-05 eta: 1:24:54 time: 0.349017 data_time: 0.030964 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.920657 2023/08/09 18:34:52 - mmengine - INFO - Epoch(train) [178][200/442] lr: 5.000000e-05 eta: 1:24:50 time: 0.348278 data_time: 0.030914 memory: 4565 loss: 0.000748 loss_kpt: 0.000748 acc_pose: 0.870414 2023/08/09 18:34:55 - mmengine - INFO - Epoch(train) [178][210/442] lr: 5.000000e-05 eta: 1:24:47 time: 0.347766 data_time: 0.030698 memory: 4565 loss: 0.000760 loss_kpt: 0.000760 acc_pose: 0.900537 2023/08/09 18:34:59 - mmengine - INFO - Epoch(train) [178][220/442] lr: 5.000000e-05 eta: 1:24:43 time: 0.346658 data_time: 0.030918 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.913743 2023/08/09 18:35:02 - mmengine - INFO - Epoch(train) [178][230/442] lr: 5.000000e-05 eta: 1:24:40 time: 0.347613 data_time: 0.031176 memory: 4565 loss: 0.000753 loss_kpt: 0.000753 acc_pose: 0.858538 2023/08/09 18:35:06 - mmengine - INFO - Epoch(train) [178][240/442] lr: 5.000000e-05 eta: 1:24:36 time: 0.345339 data_time: 0.031191 memory: 4565 loss: 0.000758 loss_kpt: 0.000758 acc_pose: 0.840883 2023/08/09 18:35:09 - mmengine - INFO - Epoch(train) [178][250/442] lr: 5.000000e-05 eta: 1:24:32 time: 0.344895 data_time: 0.031022 memory: 4565 loss: 0.000751 loss_kpt: 0.000751 acc_pose: 0.918156 2023/08/09 18:35:12 - mmengine - INFO - Epoch(train) [178][260/442] lr: 5.000000e-05 eta: 1:24:29 time: 0.341551 data_time: 0.030832 memory: 4565 loss: 0.000734 loss_kpt: 0.000734 acc_pose: 0.901587 2023/08/09 18:35:16 - mmengine - INFO - Epoch(train) [178][270/442] lr: 5.000000e-05 eta: 1:24:25 time: 0.342846 data_time: 0.030856 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.939217 2023/08/09 18:35:19 - mmengine - INFO - Epoch(train) [178][280/442] lr: 5.000000e-05 eta: 1:24:22 time: 0.343683 data_time: 0.031249 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.852194 2023/08/09 18:35:23 - mmengine - INFO - Epoch(train) [178][290/442] lr: 5.000000e-05 eta: 1:24:18 time: 0.347595 data_time: 0.032461 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.865781 2023/08/09 18:35:27 - mmengine - INFO - Epoch(train) [178][300/442] lr: 5.000000e-05 eta: 1:24:15 time: 0.350029 data_time: 0.032844 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.848022 2023/08/09 18:35:30 - mmengine - INFO - Epoch(train) [178][310/442] lr: 5.000000e-05 eta: 1:24:11 time: 0.354134 data_time: 0.033034 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.904878 2023/08/09 18:35:34 - mmengine - INFO - Epoch(train) [178][320/442] lr: 5.000000e-05 eta: 1:24:07 time: 0.352191 data_time: 0.032896 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.895034 2023/08/09 18:35:37 - mmengine - INFO - Epoch(train) [178][330/442] lr: 5.000000e-05 eta: 1:24:04 time: 0.350695 data_time: 0.032359 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.875896 2023/08/09 18:35:40 - mmengine - INFO - Epoch(train) [178][340/442] lr: 5.000000e-05 eta: 1:24:00 time: 0.349100 data_time: 0.031545 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.889006 2023/08/09 18:35:44 - mmengine - INFO - Epoch(train) [178][350/442] lr: 5.000000e-05 eta: 1:23:57 time: 0.350453 data_time: 0.031590 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.921483 2023/08/09 18:35:48 - mmengine - INFO - Epoch(train) [178][360/442] lr: 5.000000e-05 eta: 1:23:53 time: 0.352471 data_time: 0.031422 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.843508 2023/08/09 18:35:51 - mmengine - INFO - Epoch(train) [178][370/442] lr: 5.000000e-05 eta: 1:23:50 time: 0.352454 data_time: 0.031333 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.906129 2023/08/09 18:35:55 - mmengine - INFO - Epoch(train) [178][380/442] lr: 5.000000e-05 eta: 1:23:46 time: 0.353797 data_time: 0.031256 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.931121 2023/08/09 18:35:58 - mmengine - INFO - Epoch(train) [178][390/442] lr: 5.000000e-05 eta: 1:23:43 time: 0.354439 data_time: 0.030955 memory: 4565 loss: 0.000751 loss_kpt: 0.000751 acc_pose: 0.862432 2023/08/09 18:36:02 - mmengine - INFO - Epoch(train) [178][400/442] lr: 5.000000e-05 eta: 1:23:39 time: 0.353440 data_time: 0.030612 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.906557 2023/08/09 18:36:05 - mmengine - INFO - Epoch(train) [178][410/442] lr: 5.000000e-05 eta: 1:23:36 time: 0.350538 data_time: 0.031108 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.848050 2023/08/09 18:36:09 - mmengine - INFO - Epoch(train) [178][420/442] lr: 5.000000e-05 eta: 1:23:32 time: 0.352854 data_time: 0.031394 memory: 4565 loss: 0.000766 loss_kpt: 0.000766 acc_pose: 0.856138 2023/08/09 18:36:12 - mmengine - INFO - Epoch(train) [178][430/442] lr: 5.000000e-05 eta: 1:23:28 time: 0.351762 data_time: 0.031509 memory: 4565 loss: 0.000771 loss_kpt: 0.000771 acc_pose: 0.836719 2023/08/09 18:36:16 - mmengine - INFO - Epoch(train) [178][440/442] lr: 5.000000e-05 eta: 1:23:25 time: 0.349411 data_time: 0.031459 memory: 4565 loss: 0.000776 loss_kpt: 0.000776 acc_pose: 0.880047 2023/08/09 18:36:16 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:36:20 - mmengine - INFO - Epoch(train) [179][ 10/442] lr: 5.000000e-05 eta: 1:23:21 time: 0.352634 data_time: 0.034525 memory: 4565 loss: 0.000787 loss_kpt: 0.000787 acc_pose: 0.910469 2023/08/09 18:36:24 - mmengine - INFO - Epoch(train) [179][ 20/442] lr: 5.000000e-05 eta: 1:23:17 time: 0.353836 data_time: 0.034488 memory: 4565 loss: 0.000782 loss_kpt: 0.000782 acc_pose: 0.923433 2023/08/09 18:36:27 - mmengine - INFO - Epoch(train) [179][ 30/442] lr: 5.000000e-05 eta: 1:23:14 time: 0.353805 data_time: 0.034098 memory: 4565 loss: 0.000783 loss_kpt: 0.000783 acc_pose: 0.968612 2023/08/09 18:36:31 - mmengine - INFO - Epoch(train) [179][ 40/442] lr: 5.000000e-05 eta: 1:23:10 time: 0.357455 data_time: 0.034220 memory: 4565 loss: 0.000765 loss_kpt: 0.000765 acc_pose: 0.927888 2023/08/09 18:36:34 - mmengine - INFO - Epoch(train) [179][ 50/442] lr: 5.000000e-05 eta: 1:23:07 time: 0.361646 data_time: 0.034723 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.947850 2023/08/09 18:36:38 - mmengine - INFO - Epoch(train) [179][ 60/442] lr: 5.000000e-05 eta: 1:23:03 time: 0.355584 data_time: 0.031218 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.767630 2023/08/09 18:36:41 - mmengine - INFO - Epoch(train) [179][ 70/442] lr: 5.000000e-05 eta: 1:22:59 time: 0.354314 data_time: 0.030718 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.928707 2023/08/09 18:36:45 - mmengine - INFO - Epoch(train) [179][ 80/442] lr: 5.000000e-05 eta: 1:22:56 time: 0.354871 data_time: 0.030800 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.889580 2023/08/09 18:36:49 - mmengine - INFO - Epoch(train) [179][ 90/442] lr: 5.000000e-05 eta: 1:22:52 time: 0.356759 data_time: 0.031307 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.919295 2023/08/09 18:36:52 - mmengine - INFO - Epoch(train) [179][100/442] lr: 5.000000e-05 eta: 1:22:49 time: 0.358505 data_time: 0.031297 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.845088 2023/08/09 18:36:56 - mmengine - INFO - Epoch(train) [179][110/442] lr: 5.000000e-05 eta: 1:22:46 time: 0.361068 data_time: 0.031261 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.837947 2023/08/09 18:37:00 - mmengine - INFO - Epoch(train) [179][120/442] lr: 5.000000e-05 eta: 1:22:42 time: 0.361695 data_time: 0.031351 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.849481 2023/08/09 18:37:03 - mmengine - INFO - Epoch(train) [179][130/442] lr: 5.000000e-05 eta: 1:22:38 time: 0.360093 data_time: 0.031120 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.872026 2023/08/09 18:37:07 - mmengine - INFO - Epoch(train) [179][140/442] lr: 5.000000e-05 eta: 1:22:35 time: 0.357648 data_time: 0.030539 memory: 4565 loss: 0.000753 loss_kpt: 0.000753 acc_pose: 0.901091 2023/08/09 18:37:10 - mmengine - INFO - Epoch(train) [179][150/442] lr: 5.000000e-05 eta: 1:22:31 time: 0.356783 data_time: 0.030351 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.905546 2023/08/09 18:37:14 - mmengine - INFO - Epoch(train) [179][160/442] lr: 5.000000e-05 eta: 1:22:28 time: 0.356216 data_time: 0.030542 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.895797 2023/08/09 18:37:17 - mmengine - INFO - Epoch(train) [179][170/442] lr: 5.000000e-05 eta: 1:22:24 time: 0.357456 data_time: 0.030830 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.806277 2023/08/09 18:37:21 - mmengine - INFO - Epoch(train) [179][180/442] lr: 5.000000e-05 eta: 1:22:21 time: 0.360789 data_time: 0.034190 memory: 4565 loss: 0.000756 loss_kpt: 0.000756 acc_pose: 0.960040 2023/08/09 18:37:25 - mmengine - INFO - Epoch(train) [179][190/442] lr: 5.000000e-05 eta: 1:22:17 time: 0.359745 data_time: 0.033914 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.875875 2023/08/09 18:37:28 - mmengine - INFO - Epoch(train) [179][200/442] lr: 5.000000e-05 eta: 1:22:14 time: 0.358719 data_time: 0.033964 memory: 4565 loss: 0.000749 loss_kpt: 0.000749 acc_pose: 0.877976 2023/08/09 18:37:32 - mmengine - INFO - Epoch(train) [179][210/442] lr: 5.000000e-05 eta: 1:22:10 time: 0.356790 data_time: 0.033650 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.836431 2023/08/09 18:37:35 - mmengine - INFO - Epoch(train) [179][220/442] lr: 5.000000e-05 eta: 1:22:07 time: 0.357106 data_time: 0.033579 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.860918 2023/08/09 18:37:39 - mmengine - INFO - Epoch(train) [179][230/442] lr: 5.000000e-05 eta: 1:22:03 time: 0.354834 data_time: 0.030290 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.904649 2023/08/09 18:37:42 - mmengine - INFO - Epoch(train) [179][240/442] lr: 5.000000e-05 eta: 1:22:00 time: 0.357948 data_time: 0.030991 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.902365 2023/08/09 18:37:46 - mmengine - INFO - Epoch(train) [179][250/442] lr: 5.000000e-05 eta: 1:21:56 time: 0.356891 data_time: 0.031086 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.888940 2023/08/09 18:37:50 - mmengine - INFO - Epoch(train) [179][260/442] lr: 5.000000e-05 eta: 1:21:53 time: 0.356921 data_time: 0.031084 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.866075 2023/08/09 18:37:53 - mmengine - INFO - Epoch(train) [179][270/442] lr: 5.000000e-05 eta: 1:21:49 time: 0.357447 data_time: 0.030768 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.863747 2023/08/09 18:37:57 - mmengine - INFO - Epoch(train) [179][280/442] lr: 5.000000e-05 eta: 1:21:46 time: 0.356947 data_time: 0.030911 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.860922 2023/08/09 18:38:00 - mmengine - INFO - Epoch(train) [179][290/442] lr: 5.000000e-05 eta: 1:21:42 time: 0.354714 data_time: 0.030471 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.879321 2023/08/09 18:38:04 - mmengine - INFO - Epoch(train) [179][300/442] lr: 5.000000e-05 eta: 1:21:39 time: 0.361645 data_time: 0.031290 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.902475 2023/08/09 18:38:08 - mmengine - INFO - Epoch(train) [179][310/442] lr: 5.000000e-05 eta: 1:21:35 time: 0.368248 data_time: 0.031548 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.852301 2023/08/09 18:38:12 - mmengine - INFO - Epoch(train) [179][320/442] lr: 5.000000e-05 eta: 1:21:32 time: 0.372751 data_time: 0.032010 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.870325 2023/08/09 18:38:13 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:38:15 - mmengine - INFO - Epoch(train) [179][330/442] lr: 5.000000e-05 eta: 1:21:28 time: 0.371832 data_time: 0.031815 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.883826 2023/08/09 18:38:19 - mmengine - INFO - Epoch(train) [179][340/442] lr: 5.000000e-05 eta: 1:21:25 time: 0.371930 data_time: 0.031699 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.860102 2023/08/09 18:38:23 - mmengine - INFO - Epoch(train) [179][350/442] lr: 5.000000e-05 eta: 1:21:21 time: 0.369532 data_time: 0.034124 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.836717 2023/08/09 18:38:26 - mmengine - INFO - Epoch(train) [179][360/442] lr: 5.000000e-05 eta: 1:21:18 time: 0.365272 data_time: 0.033999 memory: 4565 loss: 0.000758 loss_kpt: 0.000758 acc_pose: 0.862431 2023/08/09 18:38:30 - mmengine - INFO - Epoch(train) [179][370/442] lr: 5.000000e-05 eta: 1:21:14 time: 0.362697 data_time: 0.033500 memory: 4565 loss: 0.000760 loss_kpt: 0.000760 acc_pose: 0.912302 2023/08/09 18:38:34 - mmengine - INFO - Epoch(train) [179][380/442] lr: 5.000000e-05 eta: 1:21:11 time: 0.364025 data_time: 0.033544 memory: 4565 loss: 0.000761 loss_kpt: 0.000761 acc_pose: 0.903065 2023/08/09 18:38:37 - mmengine - INFO - Epoch(train) [179][390/442] lr: 5.000000e-05 eta: 1:21:07 time: 0.363308 data_time: 0.033433 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.871837 2023/08/09 18:38:41 - mmengine - INFO - Epoch(train) [179][400/442] lr: 5.000000e-05 eta: 1:21:04 time: 0.359090 data_time: 0.030209 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.856240 2023/08/09 18:38:44 - mmengine - INFO - Epoch(train) [179][410/442] lr: 5.000000e-05 eta: 1:21:00 time: 0.358867 data_time: 0.030382 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.853481 2023/08/09 18:38:48 - mmengine - INFO - Epoch(train) [179][420/442] lr: 5.000000e-05 eta: 1:20:57 time: 0.360054 data_time: 0.030680 memory: 4565 loss: 0.000749 loss_kpt: 0.000749 acc_pose: 0.917051 2023/08/09 18:38:52 - mmengine - INFO - Epoch(train) [179][430/442] lr: 5.000000e-05 eta: 1:20:53 time: 0.359640 data_time: 0.030673 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.937189 2023/08/09 18:38:55 - mmengine - INFO - Epoch(train) [179][440/442] lr: 5.000000e-05 eta: 1:20:50 time: 0.362100 data_time: 0.030909 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.909714 2023/08/09 18:38:56 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:38:59 - mmengine - INFO - Epoch(train) [180][ 10/442] lr: 5.000000e-05 eta: 1:20:46 time: 0.364472 data_time: 0.034506 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.841820 2023/08/09 18:39:03 - mmengine - INFO - Epoch(train) [180][ 20/442] lr: 5.000000e-05 eta: 1:20:42 time: 0.360545 data_time: 0.034399 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.892071 2023/08/09 18:39:07 - mmengine - INFO - Epoch(train) [180][ 30/442] lr: 5.000000e-05 eta: 1:20:38 time: 0.357499 data_time: 0.034530 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.893621 2023/08/09 18:39:10 - mmengine - INFO - Epoch(train) [180][ 40/442] lr: 5.000000e-05 eta: 1:20:35 time: 0.355463 data_time: 0.034658 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.929045 2023/08/09 18:39:14 - mmengine - INFO - Epoch(train) [180][ 50/442] lr: 5.000000e-05 eta: 1:20:31 time: 0.358314 data_time: 0.035425 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.877904 2023/08/09 18:39:17 - mmengine - INFO - Epoch(train) [180][ 60/442] lr: 5.000000e-05 eta: 1:20:28 time: 0.354654 data_time: 0.031399 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.937575 2023/08/09 18:39:21 - mmengine - INFO - Epoch(train) [180][ 70/442] lr: 5.000000e-05 eta: 1:20:24 time: 0.355964 data_time: 0.031155 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.904654 2023/08/09 18:39:24 - mmengine - INFO - Epoch(train) [180][ 80/442] lr: 5.000000e-05 eta: 1:20:21 time: 0.357101 data_time: 0.031136 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.877930 2023/08/09 18:39:28 - mmengine - INFO - Epoch(train) [180][ 90/442] lr: 5.000000e-05 eta: 1:20:17 time: 0.356450 data_time: 0.031041 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.886969 2023/08/09 18:39:32 - mmengine - INFO - Epoch(train) [180][100/442] lr: 5.000000e-05 eta: 1:20:14 time: 0.356581 data_time: 0.030840 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.883771 2023/08/09 18:39:35 - mmengine - INFO - Epoch(train) [180][110/442] lr: 5.000000e-05 eta: 1:20:10 time: 0.358194 data_time: 0.031011 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.885048 2023/08/09 18:39:39 - mmengine - INFO - Epoch(train) [180][120/442] lr: 5.000000e-05 eta: 1:20:07 time: 0.357501 data_time: 0.030995 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.922554 2023/08/09 18:39:42 - mmengine - INFO - Epoch(train) [180][130/442] lr: 5.000000e-05 eta: 1:20:03 time: 0.355841 data_time: 0.030856 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.899846 2023/08/09 18:39:46 - mmengine - INFO - Epoch(train) [180][140/442] lr: 5.000000e-05 eta: 1:20:00 time: 0.359493 data_time: 0.030937 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.876999 2023/08/09 18:39:50 - mmengine - INFO - Epoch(train) [180][150/442] lr: 5.000000e-05 eta: 1:19:56 time: 0.359061 data_time: 0.030993 memory: 4565 loss: 0.000749 loss_kpt: 0.000749 acc_pose: 0.857821 2023/08/09 18:39:53 - mmengine - INFO - Epoch(train) [180][160/442] lr: 5.000000e-05 eta: 1:19:53 time: 0.359709 data_time: 0.031245 memory: 4565 loss: 0.000751 loss_kpt: 0.000751 acc_pose: 0.876639 2023/08/09 18:39:57 - mmengine - INFO - Epoch(train) [180][170/442] lr: 5.000000e-05 eta: 1:19:49 time: 0.359914 data_time: 0.031330 memory: 4565 loss: 0.000765 loss_kpt: 0.000765 acc_pose: 0.901678 2023/08/09 18:40:00 - mmengine - INFO - Epoch(train) [180][180/442] lr: 5.000000e-05 eta: 1:19:46 time: 0.359550 data_time: 0.031559 memory: 4565 loss: 0.000758 loss_kpt: 0.000758 acc_pose: 0.905364 2023/08/09 18:40:04 - mmengine - INFO - Epoch(train) [180][190/442] lr: 5.000000e-05 eta: 1:19:42 time: 0.355889 data_time: 0.031455 memory: 4565 loss: 0.000755 loss_kpt: 0.000755 acc_pose: 0.820980 2023/08/09 18:40:07 - mmengine - INFO - Epoch(train) [180][200/442] lr: 5.000000e-05 eta: 1:19:39 time: 0.356137 data_time: 0.031307 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.913197 2023/08/09 18:40:11 - mmengine - INFO - Epoch(train) [180][210/442] lr: 5.000000e-05 eta: 1:19:35 time: 0.354696 data_time: 0.031005 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.843551 2023/08/09 18:40:15 - mmengine - INFO - Epoch(train) [180][220/442] lr: 5.000000e-05 eta: 1:19:32 time: 0.355963 data_time: 0.030899 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.824991 2023/08/09 18:40:18 - mmengine - INFO - Epoch(train) [180][230/442] lr: 5.000000e-05 eta: 1:19:28 time: 0.359601 data_time: 0.031237 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.955363 2023/08/09 18:40:22 - mmengine - INFO - Epoch(train) [180][240/442] lr: 5.000000e-05 eta: 1:19:25 time: 0.361744 data_time: 0.031449 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.913352 2023/08/09 18:40:25 - mmengine - INFO - Epoch(train) [180][250/442] lr: 5.000000e-05 eta: 1:19:21 time: 0.359852 data_time: 0.031306 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.861919 2023/08/09 18:40:29 - mmengine - INFO - Epoch(train) [180][260/442] lr: 5.000000e-05 eta: 1:19:17 time: 0.358685 data_time: 0.031139 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.897827 2023/08/09 18:40:32 - mmengine - INFO - Epoch(train) [180][270/442] lr: 5.000000e-05 eta: 1:19:14 time: 0.356732 data_time: 0.031126 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.828946 2023/08/09 18:40:36 - mmengine - INFO - Epoch(train) [180][280/442] lr: 5.000000e-05 eta: 1:19:10 time: 0.356737 data_time: 0.030641 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.891973 2023/08/09 18:40:40 - mmengine - INFO - Epoch(train) [180][290/442] lr: 5.000000e-05 eta: 1:19:07 time: 0.356402 data_time: 0.030791 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.929285 2023/08/09 18:40:43 - mmengine - INFO - Epoch(train) [180][300/442] lr: 5.000000e-05 eta: 1:19:03 time: 0.359358 data_time: 0.031332 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.921539 2023/08/09 18:40:47 - mmengine - INFO - Epoch(train) [180][310/442] lr: 5.000000e-05 eta: 1:19:00 time: 0.360101 data_time: 0.031339 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.851566 2023/08/09 18:40:51 - mmengine - INFO - Epoch(train) [180][320/442] lr: 5.000000e-05 eta: 1:18:56 time: 0.364236 data_time: 0.034730 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.793233 2023/08/09 18:40:54 - mmengine - INFO - Epoch(train) [180][330/442] lr: 5.000000e-05 eta: 1:18:53 time: 0.360882 data_time: 0.034630 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.862254 2023/08/09 18:40:58 - mmengine - INFO - Epoch(train) [180][340/442] lr: 5.000000e-05 eta: 1:18:49 time: 0.361102 data_time: 0.034156 memory: 4565 loss: 0.000763 loss_kpt: 0.000763 acc_pose: 0.847790 2023/08/09 18:41:01 - mmengine - INFO - Epoch(train) [180][350/442] lr: 5.000000e-05 eta: 1:18:46 time: 0.361109 data_time: 0.033980 memory: 4565 loss: 0.000762 loss_kpt: 0.000762 acc_pose: 0.939568 2023/08/09 18:41:05 - mmengine - INFO - Epoch(train) [180][360/442] lr: 5.000000e-05 eta: 1:18:42 time: 0.362678 data_time: 0.034026 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.873113 2023/08/09 18:41:09 - mmengine - INFO - Epoch(train) [180][370/442] lr: 5.000000e-05 eta: 1:18:39 time: 0.367475 data_time: 0.031328 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.897298 2023/08/09 18:41:13 - mmengine - INFO - Epoch(train) [180][380/442] lr: 5.000000e-05 eta: 1:18:36 time: 0.374552 data_time: 0.032009 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.848248 2023/08/09 18:41:17 - mmengine - INFO - Epoch(train) [180][390/442] lr: 5.000000e-05 eta: 1:18:32 time: 0.377915 data_time: 0.032419 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.897335 2023/08/09 18:41:20 - mmengine - INFO - Epoch(train) [180][400/442] lr: 5.000000e-05 eta: 1:18:29 time: 0.375180 data_time: 0.032237 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.836142 2023/08/09 18:41:24 - mmengine - INFO - Epoch(train) [180][410/442] lr: 5.000000e-05 eta: 1:18:25 time: 0.374114 data_time: 0.032529 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.915403 2023/08/09 18:41:27 - mmengine - INFO - Epoch(train) [180][420/442] lr: 5.000000e-05 eta: 1:18:22 time: 0.368479 data_time: 0.031960 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.851917 2023/08/09 18:41:31 - mmengine - INFO - Epoch(train) [180][430/442] lr: 5.000000e-05 eta: 1:18:18 time: 0.362446 data_time: 0.031379 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.881132 2023/08/09 18:41:35 - mmengine - INFO - Epoch(train) [180][440/442] lr: 5.000000e-05 eta: 1:18:15 time: 0.357016 data_time: 0.030999 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.934976 2023/08/09 18:41:35 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:41:35 - mmengine - INFO - Saving checkpoint at 180 epochs 2023/08/09 18:41:41 - mmengine - INFO - Epoch(val) [180][ 10/108] eta: 0:00:20 time: 0.196934 data_time: 0.013212 memory: 4565 2023/08/09 18:41:43 - mmengine - INFO - Epoch(val) [180][ 20/108] eta: 0:00:18 time: 0.197577 data_time: 0.013807 memory: 1624 2023/08/09 18:41:45 - mmengine - INFO - Epoch(val) [180][ 30/108] eta: 0:00:15 time: 0.198277 data_time: 0.014330 memory: 1624 2023/08/09 18:41:47 - mmengine - INFO - Epoch(val) [180][ 40/108] eta: 0:00:13 time: 0.198542 data_time: 0.014412 memory: 1624 2023/08/09 18:41:49 - mmengine - INFO - Epoch(val) [180][ 50/108] eta: 0:00:11 time: 0.200596 data_time: 0.014552 memory: 1624 2023/08/09 18:41:51 - mmengine - INFO - Epoch(val) [180][ 60/108] eta: 0:00:09 time: 0.198263 data_time: 0.012373 memory: 1624 2023/08/09 18:41:53 - mmengine - INFO - Epoch(val) [180][ 70/108] eta: 0:00:07 time: 0.198161 data_time: 0.012244 memory: 1624 2023/08/09 18:41:55 - mmengine - INFO - Epoch(val) [180][ 80/108] eta: 0:00:05 time: 0.197535 data_time: 0.011936 memory: 1624 2023/08/09 18:41:57 - mmengine - INFO - Epoch(val) [180][ 90/108] eta: 0:00:03 time: 0.197444 data_time: 0.011979 memory: 1624 2023/08/09 18:41:59 - mmengine - INFO - Epoch(val) [180][100/108] eta: 0:00:01 time: 0.197586 data_time: 0.012171 memory: 1624 2023/08/09 18:42:00 - mmengine - INFO - Evaluating PCKAccuracy (normalized by ``"bbox_size"``)... 2023/08/09 18:42:01 - mmengine - INFO - Evaluating AUC... 2023/08/09 18:42:01 - mmengine - INFO - Evaluating EPE... 2023/08/09 18:42:01 - mmengine - INFO - Epoch(val) [180][108/108] PCK: 0.961933 AUC: 0.605234 EPE: 14.794098 data_time: 0.013088 time: 0.198543 2023/08/09 18:42:04 - mmengine - INFO - Epoch(train) [181][ 10/442] lr: 5.000000e-05 eta: 1:18:10 time: 0.357023 data_time: 0.034376 memory: 4565 loss: 0.000756 loss_kpt: 0.000756 acc_pose: 0.812878 2023/08/09 18:42:08 - mmengine - INFO - Epoch(train) [181][ 20/442] lr: 5.000000e-05 eta: 1:18:07 time: 0.351706 data_time: 0.034223 memory: 4565 loss: 0.000755 loss_kpt: 0.000755 acc_pose: 0.921312 2023/08/09 18:42:11 - mmengine - INFO - Epoch(train) [181][ 30/442] lr: 5.000000e-05 eta: 1:18:03 time: 0.349694 data_time: 0.034322 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.852011 2023/08/09 18:42:15 - mmengine - INFO - Epoch(train) [181][ 40/442] lr: 5.000000e-05 eta: 1:18:00 time: 0.349544 data_time: 0.034835 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.889868 2023/08/09 18:42:18 - mmengine - INFO - Epoch(train) [181][ 50/442] lr: 5.000000e-05 eta: 1:17:56 time: 0.349811 data_time: 0.035463 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.883153 2023/08/09 18:42:22 - mmengine - INFO - Epoch(train) [181][ 60/442] lr: 5.000000e-05 eta: 1:17:52 time: 0.347062 data_time: 0.031611 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.875398 2023/08/09 18:42:25 - mmengine - INFO - Epoch(train) [181][ 70/442] lr: 5.000000e-05 eta: 1:17:49 time: 0.348683 data_time: 0.031526 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.877110 2023/08/09 18:42:29 - mmengine - INFO - Epoch(train) [181][ 80/442] lr: 5.000000e-05 eta: 1:17:45 time: 0.348404 data_time: 0.031394 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.862483 2023/08/09 18:42:32 - mmengine - INFO - Epoch(train) [181][ 90/442] lr: 5.000000e-05 eta: 1:17:42 time: 0.346457 data_time: 0.030777 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.851820 2023/08/09 18:42:36 - mmengine - INFO - Epoch(train) [181][100/442] lr: 5.000000e-05 eta: 1:17:38 time: 0.346971 data_time: 0.030556 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.927841 2023/08/09 18:42:39 - mmengine - INFO - Epoch(train) [181][110/442] lr: 5.000000e-05 eta: 1:17:35 time: 0.347619 data_time: 0.030548 memory: 4565 loss: 0.000748 loss_kpt: 0.000748 acc_pose: 0.939926 2023/08/09 18:42:43 - mmengine - INFO - Epoch(train) [181][120/442] lr: 5.000000e-05 eta: 1:17:31 time: 0.345391 data_time: 0.031293 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.859196 2023/08/09 18:42:46 - mmengine - INFO - Epoch(train) [181][130/442] lr: 5.000000e-05 eta: 1:17:27 time: 0.344435 data_time: 0.031820 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.835665 2023/08/09 18:42:49 - mmengine - INFO - Epoch(train) [181][140/442] lr: 5.000000e-05 eta: 1:17:24 time: 0.343525 data_time: 0.032188 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.859382 2023/08/09 18:42:53 - mmengine - INFO - Epoch(train) [181][150/442] lr: 5.000000e-05 eta: 1:17:20 time: 0.345987 data_time: 0.032892 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.855563 2023/08/09 18:42:56 - mmengine - INFO - Epoch(train) [181][160/442] lr: 5.000000e-05 eta: 1:17:17 time: 0.346212 data_time: 0.032959 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.826810 2023/08/09 18:43:00 - mmengine - INFO - Epoch(train) [181][170/442] lr: 5.000000e-05 eta: 1:17:13 time: 0.347090 data_time: 0.032459 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.905021 2023/08/09 18:43:03 - mmengine - INFO - Epoch(train) [181][180/442] lr: 5.000000e-05 eta: 1:17:10 time: 0.348646 data_time: 0.031997 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.915161 2023/08/09 18:43:07 - mmengine - INFO - Epoch(train) [181][190/442] lr: 5.000000e-05 eta: 1:17:06 time: 0.348182 data_time: 0.031600 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.896774 2023/08/09 18:43:10 - mmengine - INFO - Epoch(train) [181][200/442] lr: 5.000000e-05 eta: 1:17:02 time: 0.348034 data_time: 0.031060 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.900915 2023/08/09 18:43:14 - mmengine - INFO - Epoch(train) [181][210/442] lr: 5.000000e-05 eta: 1:16:59 time: 0.348534 data_time: 0.030794 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.900274 2023/08/09 18:43:17 - mmengine - INFO - Epoch(train) [181][220/442] lr: 5.000000e-05 eta: 1:16:55 time: 0.347903 data_time: 0.030587 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.940887 2023/08/09 18:43:21 - mmengine - INFO - Epoch(train) [181][230/442] lr: 5.000000e-05 eta: 1:16:52 time: 0.347248 data_time: 0.030658 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.909138 2023/08/09 18:43:24 - mmengine - INFO - Epoch(train) [181][240/442] lr: 5.000000e-05 eta: 1:16:48 time: 0.350390 data_time: 0.031051 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.936166 2023/08/09 18:43:28 - mmengine - INFO - Epoch(train) [181][250/442] lr: 5.000000e-05 eta: 1:16:45 time: 0.347794 data_time: 0.030836 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.920617 2023/08/09 18:43:31 - mmengine - INFO - Epoch(train) [181][260/442] lr: 5.000000e-05 eta: 1:16:41 time: 0.347464 data_time: 0.031004 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.882947 2023/08/09 18:43:35 - mmengine - INFO - Epoch(train) [181][270/442] lr: 5.000000e-05 eta: 1:16:38 time: 0.347991 data_time: 0.031041 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.926344 2023/08/09 18:43:38 - mmengine - INFO - Epoch(train) [181][280/442] lr: 5.000000e-05 eta: 1:16:34 time: 0.349119 data_time: 0.030756 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.834416 2023/08/09 18:43:42 - mmengine - INFO - Epoch(train) [181][290/442] lr: 5.000000e-05 eta: 1:16:30 time: 0.348281 data_time: 0.030809 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.896965 2023/08/09 18:43:45 - mmengine - INFO - Epoch(train) [181][300/442] lr: 5.000000e-05 eta: 1:16:27 time: 0.348531 data_time: 0.030910 memory: 4565 loss: 0.000761 loss_kpt: 0.000761 acc_pose: 0.861903 2023/08/09 18:43:49 - mmengine - INFO - Epoch(train) [181][310/442] lr: 5.000000e-05 eta: 1:16:23 time: 0.352379 data_time: 0.031072 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.941887 2023/08/09 18:43:52 - mmengine - INFO - Epoch(train) [181][320/442] lr: 5.000000e-05 eta: 1:16:20 time: 0.352692 data_time: 0.030978 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.899082 2023/08/09 18:43:56 - mmengine - INFO - Epoch(train) [181][330/442] lr: 5.000000e-05 eta: 1:16:16 time: 0.350697 data_time: 0.031096 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.852824 2023/08/09 18:43:59 - mmengine - INFO - Epoch(train) [181][340/442] lr: 5.000000e-05 eta: 1:16:13 time: 0.351439 data_time: 0.030697 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.923878 2023/08/09 18:44:03 - mmengine - INFO - Epoch(train) [181][350/442] lr: 5.000000e-05 eta: 1:16:09 time: 0.351273 data_time: 0.030659 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.855592 2023/08/09 18:44:06 - mmengine - INFO - Epoch(train) [181][360/442] lr: 5.000000e-05 eta: 1:16:06 time: 0.349671 data_time: 0.033743 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.910818 2023/08/09 18:44:10 - mmengine - INFO - Epoch(train) [181][370/442] lr: 5.000000e-05 eta: 1:16:02 time: 0.350759 data_time: 0.034052 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.847245 2023/08/09 18:44:13 - mmengine - INFO - Epoch(train) [181][380/442] lr: 5.000000e-05 eta: 1:15:58 time: 0.350530 data_time: 0.033978 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.917586 2023/08/09 18:44:17 - mmengine - INFO - Epoch(train) [181][390/442] lr: 5.000000e-05 eta: 1:15:55 time: 0.347542 data_time: 0.034634 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.902109 2023/08/09 18:44:20 - mmengine - INFO - Epoch(train) [181][400/442] lr: 5.000000e-05 eta: 1:15:51 time: 0.346983 data_time: 0.035251 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.826832 2023/08/09 18:44:24 - mmengine - INFO - Epoch(train) [181][410/442] lr: 5.000000e-05 eta: 1:15:48 time: 0.343498 data_time: 0.032687 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.877527 2023/08/09 18:44:27 - mmengine - INFO - Epoch(train) [181][420/442] lr: 5.000000e-05 eta: 1:15:44 time: 0.342531 data_time: 0.032881 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.825875 2023/08/09 18:44:31 - mmengine - INFO - Epoch(train) [181][430/442] lr: 5.000000e-05 eta: 1:15:41 time: 0.344183 data_time: 0.033106 memory: 4565 loss: 0.000749 loss_kpt: 0.000749 acc_pose: 0.857624 2023/08/09 18:44:34 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:44:34 - mmengine - INFO - Epoch(train) [181][440/442] lr: 5.000000e-05 eta: 1:15:37 time: 0.345265 data_time: 0.032702 memory: 4565 loss: 0.000755 loss_kpt: 0.000755 acc_pose: 0.883735 2023/08/09 18:44:35 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:44:38 - mmengine - INFO - Epoch(train) [182][ 10/442] lr: 5.000000e-05 eta: 1:15:33 time: 0.347659 data_time: 0.035353 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.862210 2023/08/09 18:44:42 - mmengine - INFO - Epoch(train) [182][ 20/442] lr: 5.000000e-05 eta: 1:15:29 time: 0.347638 data_time: 0.034685 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.964205 2023/08/09 18:44:45 - mmengine - INFO - Epoch(train) [182][ 30/442] lr: 5.000000e-05 eta: 1:15:26 time: 0.348485 data_time: 0.037401 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.849734 2023/08/09 18:44:49 - mmengine - INFO - Epoch(train) [182][ 40/442] lr: 5.000000e-05 eta: 1:15:22 time: 0.351003 data_time: 0.037375 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.961833 2023/08/09 18:44:52 - mmengine - INFO - Epoch(train) [182][ 50/442] lr: 5.000000e-05 eta: 1:15:19 time: 0.354054 data_time: 0.037843 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.902381 2023/08/09 18:44:56 - mmengine - INFO - Epoch(train) [182][ 60/442] lr: 5.000000e-05 eta: 1:15:15 time: 0.352495 data_time: 0.034474 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.836978 2023/08/09 18:44:59 - mmengine - INFO - Epoch(train) [182][ 70/442] lr: 5.000000e-05 eta: 1:15:11 time: 0.352231 data_time: 0.034706 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.761829 2023/08/09 18:45:03 - mmengine - INFO - Epoch(train) [182][ 80/442] lr: 5.000000e-05 eta: 1:15:08 time: 0.348706 data_time: 0.031574 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.918173 2023/08/09 18:45:06 - mmengine - INFO - Epoch(train) [182][ 90/442] lr: 5.000000e-05 eta: 1:15:04 time: 0.346351 data_time: 0.031619 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.891624 2023/08/09 18:45:10 - mmengine - INFO - Epoch(train) [182][100/442] lr: 5.000000e-05 eta: 1:15:01 time: 0.343666 data_time: 0.031253 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.847284 2023/08/09 18:45:13 - mmengine - INFO - Epoch(train) [182][110/442] lr: 5.000000e-05 eta: 1:14:57 time: 0.343071 data_time: 0.031230 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.863316 2023/08/09 18:45:17 - mmengine - INFO - Epoch(train) [182][120/442] lr: 5.000000e-05 eta: 1:14:54 time: 0.344789 data_time: 0.030921 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.900037 2023/08/09 18:45:20 - mmengine - INFO - Epoch(train) [182][130/442] lr: 5.000000e-05 eta: 1:14:50 time: 0.348953 data_time: 0.031251 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.953493 2023/08/09 18:45:24 - mmengine - INFO - Epoch(train) [182][140/442] lr: 5.000000e-05 eta: 1:14:46 time: 0.347744 data_time: 0.031002 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.911092 2023/08/09 18:45:27 - mmengine - INFO - Epoch(train) [182][150/442] lr: 5.000000e-05 eta: 1:14:43 time: 0.348344 data_time: 0.031096 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.875821 2023/08/09 18:45:30 - mmengine - INFO - Epoch(train) [182][160/442] lr: 5.000000e-05 eta: 1:14:39 time: 0.346539 data_time: 0.030676 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.832012 2023/08/09 18:45:34 - mmengine - INFO - Epoch(train) [182][170/442] lr: 5.000000e-05 eta: 1:14:36 time: 0.345260 data_time: 0.030792 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.917975 2023/08/09 18:45:38 - mmengine - INFO - Epoch(train) [182][180/442] lr: 5.000000e-05 eta: 1:14:32 time: 0.348503 data_time: 0.030595 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.903365 2023/08/09 18:45:41 - mmengine - INFO - Epoch(train) [182][190/442] lr: 5.000000e-05 eta: 1:14:29 time: 0.351134 data_time: 0.030860 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.885106 2023/08/09 18:45:45 - mmengine - INFO - Epoch(train) [182][200/442] lr: 5.000000e-05 eta: 1:14:25 time: 0.350221 data_time: 0.030869 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.858218 2023/08/09 18:45:48 - mmengine - INFO - Epoch(train) [182][210/442] lr: 5.000000e-05 eta: 1:14:21 time: 0.350263 data_time: 0.031000 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.862336 2023/08/09 18:45:51 - mmengine - INFO - Epoch(train) [182][220/442] lr: 5.000000e-05 eta: 1:14:18 time: 0.349635 data_time: 0.030924 memory: 4565 loss: 0.000748 loss_kpt: 0.000748 acc_pose: 0.867583 2023/08/09 18:45:55 - mmengine - INFO - Epoch(train) [182][230/442] lr: 5.000000e-05 eta: 1:14:14 time: 0.343483 data_time: 0.031210 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.849683 2023/08/09 18:45:58 - mmengine - INFO - Epoch(train) [182][240/442] lr: 5.000000e-05 eta: 1:14:11 time: 0.344429 data_time: 0.031378 memory: 4565 loss: 0.000757 loss_kpt: 0.000757 acc_pose: 0.906497 2023/08/09 18:46:02 - mmengine - INFO - Epoch(train) [182][250/442] lr: 5.000000e-05 eta: 1:14:07 time: 0.347143 data_time: 0.031430 memory: 4565 loss: 0.000758 loss_kpt: 0.000758 acc_pose: 0.869285 2023/08/09 18:46:05 - mmengine - INFO - Epoch(train) [182][260/442] lr: 5.000000e-05 eta: 1:14:04 time: 0.350676 data_time: 0.031674 memory: 4565 loss: 0.000753 loss_kpt: 0.000753 acc_pose: 0.862382 2023/08/09 18:46:09 - mmengine - INFO - Epoch(train) [182][270/442] lr: 5.000000e-05 eta: 1:14:00 time: 0.352169 data_time: 0.031682 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.904551 2023/08/09 18:46:12 - mmengine - INFO - Epoch(train) [182][280/442] lr: 5.000000e-05 eta: 1:13:57 time: 0.353027 data_time: 0.031067 memory: 4565 loss: 0.000753 loss_kpt: 0.000753 acc_pose: 0.916448 2023/08/09 18:46:16 - mmengine - INFO - Epoch(train) [182][290/442] lr: 5.000000e-05 eta: 1:13:53 time: 0.351184 data_time: 0.030697 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.871575 2023/08/09 18:46:19 - mmengine - INFO - Epoch(train) [182][300/442] lr: 5.000000e-05 eta: 1:13:49 time: 0.351426 data_time: 0.030752 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.869682 2023/08/09 18:46:23 - mmengine - INFO - Epoch(train) [182][310/442] lr: 5.000000e-05 eta: 1:13:46 time: 0.351109 data_time: 0.030723 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.896691 2023/08/09 18:46:27 - mmengine - INFO - Epoch(train) [182][320/442] lr: 5.000000e-05 eta: 1:13:42 time: 0.355460 data_time: 0.030980 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.892809 2023/08/09 18:46:30 - mmengine - INFO - Epoch(train) [182][330/442] lr: 5.000000e-05 eta: 1:13:39 time: 0.358021 data_time: 0.031078 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.854549 2023/08/09 18:46:34 - mmengine - INFO - Epoch(train) [182][340/442] lr: 5.000000e-05 eta: 1:13:35 time: 0.357895 data_time: 0.031036 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.847142 2023/08/09 18:46:37 - mmengine - INFO - Epoch(train) [182][350/442] lr: 5.000000e-05 eta: 1:13:32 time: 0.357399 data_time: 0.030928 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.818053 2023/08/09 18:46:41 - mmengine - INFO - Epoch(train) [182][360/442] lr: 5.000000e-05 eta: 1:13:28 time: 0.360140 data_time: 0.030629 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.884401 2023/08/09 18:46:45 - mmengine - INFO - Epoch(train) [182][370/442] lr: 5.000000e-05 eta: 1:13:25 time: 0.357039 data_time: 0.030506 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.894166 2023/08/09 18:46:48 - mmengine - INFO - Epoch(train) [182][380/442] lr: 5.000000e-05 eta: 1:13:21 time: 0.356509 data_time: 0.030609 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.818249 2023/08/09 18:46:52 - mmengine - INFO - Epoch(train) [182][390/442] lr: 5.000000e-05 eta: 1:13:18 time: 0.358000 data_time: 0.031117 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.874549 2023/08/09 18:46:55 - mmengine - INFO - Epoch(train) [182][400/442] lr: 5.000000e-05 eta: 1:13:14 time: 0.358455 data_time: 0.031040 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.929994 2023/08/09 18:46:59 - mmengine - INFO - Epoch(train) [182][410/442] lr: 5.000000e-05 eta: 1:13:11 time: 0.354350 data_time: 0.031194 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.892488 2023/08/09 18:47:02 - mmengine - INFO - Epoch(train) [182][420/442] lr: 5.000000e-05 eta: 1:13:07 time: 0.353307 data_time: 0.031178 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.915626 2023/08/09 18:47:06 - mmengine - INFO - Epoch(train) [182][430/442] lr: 5.000000e-05 eta: 1:13:04 time: 0.351714 data_time: 0.031286 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.897555 2023/08/09 18:47:09 - mmengine - INFO - Epoch(train) [182][440/442] lr: 5.000000e-05 eta: 1:13:00 time: 0.351177 data_time: 0.031108 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.887065 2023/08/09 18:47:10 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:47:14 - mmengine - INFO - Epoch(train) [183][ 10/442] lr: 5.000000e-05 eta: 1:12:56 time: 0.355396 data_time: 0.034850 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.896193 2023/08/09 18:47:17 - mmengine - INFO - Epoch(train) [183][ 20/442] lr: 5.000000e-05 eta: 1:12:52 time: 0.355649 data_time: 0.034689 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.912665 2023/08/09 18:47:21 - mmengine - INFO - Epoch(train) [183][ 30/442] lr: 5.000000e-05 eta: 1:12:49 time: 0.358251 data_time: 0.034563 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.891258 2023/08/09 18:47:24 - mmengine - INFO - Epoch(train) [183][ 40/442] lr: 5.000000e-05 eta: 1:12:45 time: 0.358108 data_time: 0.034360 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.828845 2023/08/09 18:47:28 - mmengine - INFO - Epoch(train) [183][ 50/442] lr: 5.000000e-05 eta: 1:12:42 time: 0.359420 data_time: 0.034595 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.888597 2023/08/09 18:47:32 - mmengine - INFO - Epoch(train) [183][ 60/442] lr: 5.000000e-05 eta: 1:12:38 time: 0.355054 data_time: 0.030614 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.883979 2023/08/09 18:47:35 - mmengine - INFO - Epoch(train) [183][ 70/442] lr: 5.000000e-05 eta: 1:12:35 time: 0.356667 data_time: 0.031035 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.886145 2023/08/09 18:47:39 - mmengine - INFO - Epoch(train) [183][ 80/442] lr: 5.000000e-05 eta: 1:12:31 time: 0.353950 data_time: 0.031094 memory: 4565 loss: 0.000748 loss_kpt: 0.000748 acc_pose: 0.884229 2023/08/09 18:47:42 - mmengine - INFO - Epoch(train) [183][ 90/442] lr: 5.000000e-05 eta: 1:12:28 time: 0.353561 data_time: 0.031031 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.906549 2023/08/09 18:47:46 - mmengine - INFO - Epoch(train) [183][100/442] lr: 5.000000e-05 eta: 1:12:24 time: 0.353276 data_time: 0.030973 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.908462 2023/08/09 18:47:49 - mmengine - INFO - Epoch(train) [183][110/442] lr: 5.000000e-05 eta: 1:12:20 time: 0.351501 data_time: 0.031062 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.853522 2023/08/09 18:47:53 - mmengine - INFO - Epoch(train) [183][120/442] lr: 5.000000e-05 eta: 1:12:17 time: 0.353758 data_time: 0.034257 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.950438 2023/08/09 18:47:56 - mmengine - INFO - Epoch(train) [183][130/442] lr: 5.000000e-05 eta: 1:12:13 time: 0.354233 data_time: 0.034336 memory: 4565 loss: 0.000734 loss_kpt: 0.000734 acc_pose: 0.932753 2023/08/09 18:48:00 - mmengine - INFO - Epoch(train) [183][140/442] lr: 5.000000e-05 eta: 1:12:10 time: 0.355678 data_time: 0.035110 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.870067 2023/08/09 18:48:03 - mmengine - INFO - Epoch(train) [183][150/442] lr: 5.000000e-05 eta: 1:12:06 time: 0.355297 data_time: 0.035060 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.872471 2023/08/09 18:48:07 - mmengine - INFO - Epoch(train) [183][160/442] lr: 5.000000e-05 eta: 1:12:03 time: 0.355891 data_time: 0.034949 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.919836 2023/08/09 18:48:11 - mmengine - INFO - Epoch(train) [183][170/442] lr: 5.000000e-05 eta: 1:11:59 time: 0.354312 data_time: 0.031338 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.845612 2023/08/09 18:48:14 - mmengine - INFO - Epoch(train) [183][180/442] lr: 5.000000e-05 eta: 1:11:56 time: 0.355089 data_time: 0.031870 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.921703 2023/08/09 18:48:18 - mmengine - INFO - Epoch(train) [183][190/442] lr: 5.000000e-05 eta: 1:11:52 time: 0.356255 data_time: 0.032010 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.891973 2023/08/09 18:48:21 - mmengine - INFO - Epoch(train) [183][200/442] lr: 5.000000e-05 eta: 1:11:49 time: 0.360967 data_time: 0.032652 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.932684 2023/08/09 18:48:25 - mmengine - INFO - Epoch(train) [183][210/442] lr: 5.000000e-05 eta: 1:11:45 time: 0.360281 data_time: 0.032676 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.801042 2023/08/09 18:48:28 - mmengine - INFO - Epoch(train) [183][220/442] lr: 5.000000e-05 eta: 1:11:42 time: 0.358158 data_time: 0.032701 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.927160 2023/08/09 18:48:32 - mmengine - INFO - Epoch(train) [183][230/442] lr: 5.000000e-05 eta: 1:11:38 time: 0.356870 data_time: 0.032064 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.961457 2023/08/09 18:48:36 - mmengine - INFO - Epoch(train) [183][240/442] lr: 5.000000e-05 eta: 1:11:35 time: 0.354917 data_time: 0.031226 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.931239 2023/08/09 18:48:39 - mmengine - INFO - Epoch(train) [183][250/442] lr: 5.000000e-05 eta: 1:11:31 time: 0.352352 data_time: 0.030832 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.875037 2023/08/09 18:48:43 - mmengine - INFO - Epoch(train) [183][260/442] lr: 5.000000e-05 eta: 1:11:28 time: 0.355551 data_time: 0.031096 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.892933 2023/08/09 18:48:46 - mmengine - INFO - Epoch(train) [183][270/442] lr: 5.000000e-05 eta: 1:11:24 time: 0.356624 data_time: 0.031434 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.907486 2023/08/09 18:48:50 - mmengine - INFO - Epoch(train) [183][280/442] lr: 5.000000e-05 eta: 1:11:20 time: 0.357539 data_time: 0.031461 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.831412 2023/08/09 18:48:53 - mmengine - INFO - Epoch(train) [183][290/442] lr: 5.000000e-05 eta: 1:11:17 time: 0.357522 data_time: 0.031471 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.908355 2023/08/09 18:48:57 - mmengine - INFO - Epoch(train) [183][300/442] lr: 5.000000e-05 eta: 1:11:13 time: 0.356128 data_time: 0.031170 memory: 4565 loss: 0.000748 loss_kpt: 0.000748 acc_pose: 0.822110 2023/08/09 18:49:01 - mmengine - INFO - Epoch(train) [183][310/442] lr: 5.000000e-05 eta: 1:11:10 time: 0.356072 data_time: 0.031046 memory: 4565 loss: 0.000753 loss_kpt: 0.000753 acc_pose: 0.846501 2023/08/09 18:49:04 - mmengine - INFO - Epoch(train) [183][320/442] lr: 5.000000e-05 eta: 1:11:06 time: 0.359789 data_time: 0.034523 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.888425 2023/08/09 18:49:08 - mmengine - INFO - Epoch(train) [183][330/442] lr: 5.000000e-05 eta: 1:11:03 time: 0.360415 data_time: 0.034630 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.863109 2023/08/09 18:49:11 - mmengine - INFO - Epoch(train) [183][340/442] lr: 5.000000e-05 eta: 1:10:59 time: 0.361234 data_time: 0.034664 memory: 4565 loss: 0.000748 loss_kpt: 0.000748 acc_pose: 0.875422 2023/08/09 18:49:15 - mmengine - INFO - Epoch(train) [183][350/442] lr: 5.000000e-05 eta: 1:10:56 time: 0.360949 data_time: 0.035032 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.923803 2023/08/09 18:49:18 - mmengine - INFO - Epoch(train) [183][360/442] lr: 5.000000e-05 eta: 1:10:52 time: 0.357844 data_time: 0.034829 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.850667 2023/08/09 18:49:22 - mmengine - INFO - Epoch(train) [183][370/442] lr: 5.000000e-05 eta: 1:10:49 time: 0.353146 data_time: 0.031166 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.835860 2023/08/09 18:49:26 - mmengine - INFO - Epoch(train) [183][380/442] lr: 5.000000e-05 eta: 1:10:45 time: 0.354164 data_time: 0.031274 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.896418 2023/08/09 18:49:29 - mmengine - INFO - Epoch(train) [183][390/442] lr: 5.000000e-05 eta: 1:10:42 time: 0.356750 data_time: 0.031429 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.877971 2023/08/09 18:49:33 - mmengine - INFO - Epoch(train) [183][400/442] lr: 5.000000e-05 eta: 1:10:38 time: 0.358744 data_time: 0.031178 memory: 4565 loss: 0.000749 loss_kpt: 0.000749 acc_pose: 0.762527 2023/08/09 18:49:37 - mmengine - INFO - Epoch(train) [183][410/442] lr: 5.000000e-05 eta: 1:10:35 time: 0.360132 data_time: 0.031189 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.952638 2023/08/09 18:49:40 - mmengine - INFO - Epoch(train) [183][420/442] lr: 5.000000e-05 eta: 1:10:31 time: 0.361162 data_time: 0.031096 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.890804 2023/08/09 18:49:44 - mmengine - INFO - Epoch(train) [183][430/442] lr: 5.000000e-05 eta: 1:10:28 time: 0.360014 data_time: 0.030881 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.883938 2023/08/09 18:49:47 - mmengine - INFO - Epoch(train) [183][440/442] lr: 5.000000e-05 eta: 1:10:24 time: 0.358316 data_time: 0.030611 memory: 4565 loss: 0.000757 loss_kpt: 0.000757 acc_pose: 0.842637 2023/08/09 18:49:48 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:49:52 - mmengine - INFO - Epoch(train) [184][ 10/442] lr: 5.000000e-05 eta: 1:10:20 time: 0.359836 data_time: 0.034091 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.906992 2023/08/09 18:49:55 - mmengine - INFO - Epoch(train) [184][ 20/442] lr: 5.000000e-05 eta: 1:10:16 time: 0.357534 data_time: 0.034478 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.931614 2023/08/09 18:49:59 - mmengine - INFO - Epoch(train) [184][ 30/442] lr: 5.000000e-05 eta: 1:10:13 time: 0.354345 data_time: 0.034432 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.952457 2023/08/09 18:50:02 - mmengine - INFO - Epoch(train) [184][ 40/442] lr: 5.000000e-05 eta: 1:10:09 time: 0.350177 data_time: 0.034455 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.858451 2023/08/09 18:50:05 - mmengine - INFO - Epoch(train) [184][ 50/442] lr: 5.000000e-05 eta: 1:10:06 time: 0.348923 data_time: 0.034763 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.937153 2023/08/09 18:50:09 - mmengine - INFO - Epoch(train) [184][ 60/442] lr: 5.000000e-05 eta: 1:10:02 time: 0.346892 data_time: 0.031048 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.928454 2023/08/09 18:50:13 - mmengine - INFO - Epoch(train) [184][ 70/442] lr: 5.000000e-05 eta: 1:09:59 time: 0.347082 data_time: 0.030788 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.895104 2023/08/09 18:50:16 - mmengine - INFO - Epoch(train) [184][ 80/442] lr: 5.000000e-05 eta: 1:09:55 time: 0.348951 data_time: 0.031282 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.897380 2023/08/09 18:50:19 - mmengine - INFO - Epoch(train) [184][ 90/442] lr: 5.000000e-05 eta: 1:09:51 time: 0.349144 data_time: 0.031172 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.862431 2023/08/09 18:50:23 - mmengine - INFO - Epoch(train) [184][100/442] lr: 5.000000e-05 eta: 1:09:48 time: 0.348709 data_time: 0.031322 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.882355 2023/08/09 18:50:26 - mmengine - INFO - Epoch(train) [184][110/442] lr: 5.000000e-05 eta: 1:09:44 time: 0.343507 data_time: 0.031133 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.897405 2023/08/09 18:50:28 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:50:30 - mmengine - INFO - Epoch(train) [184][120/442] lr: 5.000000e-05 eta: 1:09:41 time: 0.342701 data_time: 0.030925 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.869848 2023/08/09 18:50:33 - mmengine - INFO - Epoch(train) [184][130/442] lr: 5.000000e-05 eta: 1:09:37 time: 0.343004 data_time: 0.030895 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.934461 2023/08/09 18:50:37 - mmengine - INFO - Epoch(train) [184][140/442] lr: 5.000000e-05 eta: 1:09:34 time: 0.345320 data_time: 0.030845 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.862775 2023/08/09 18:50:40 - mmengine - INFO - Epoch(train) [184][150/442] lr: 5.000000e-05 eta: 1:09:30 time: 0.349143 data_time: 0.030889 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.818046 2023/08/09 18:50:44 - mmengine - INFO - Epoch(train) [184][160/442] lr: 5.000000e-05 eta: 1:09:26 time: 0.349830 data_time: 0.030746 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.905837 2023/08/09 18:50:47 - mmengine - INFO - Epoch(train) [184][170/442] lr: 5.000000e-05 eta: 1:09:23 time: 0.349279 data_time: 0.030860 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.866128 2023/08/09 18:50:51 - mmengine - INFO - Epoch(train) [184][180/442] lr: 5.000000e-05 eta: 1:09:19 time: 0.347384 data_time: 0.030437 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.898504 2023/08/09 18:50:54 - mmengine - INFO - Epoch(train) [184][190/442] lr: 5.000000e-05 eta: 1:09:16 time: 0.347389 data_time: 0.030734 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.828003 2023/08/09 18:50:58 - mmengine - INFO - Epoch(train) [184][200/442] lr: 5.000000e-05 eta: 1:09:12 time: 0.346532 data_time: 0.030833 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.905102 2023/08/09 18:51:01 - mmengine - INFO - Epoch(train) [184][210/442] lr: 5.000000e-05 eta: 1:09:09 time: 0.347769 data_time: 0.031139 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.867559 2023/08/09 18:51:05 - mmengine - INFO - Epoch(train) [184][220/442] lr: 5.000000e-05 eta: 1:09:05 time: 0.348839 data_time: 0.031007 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.896993 2023/08/09 18:51:08 - mmengine - INFO - Epoch(train) [184][230/442] lr: 5.000000e-05 eta: 1:09:02 time: 0.351982 data_time: 0.034392 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.910706 2023/08/09 18:51:12 - mmengine - INFO - Epoch(train) [184][240/442] lr: 5.000000e-05 eta: 1:08:58 time: 0.350180 data_time: 0.034153 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.842571 2023/08/09 18:51:15 - mmengine - INFO - Epoch(train) [184][250/442] lr: 5.000000e-05 eta: 1:08:54 time: 0.346994 data_time: 0.033881 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.866501 2023/08/09 18:51:18 - mmengine - INFO - Epoch(train) [184][260/442] lr: 5.000000e-05 eta: 1:08:51 time: 0.346120 data_time: 0.034050 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.881553 2023/08/09 18:51:22 - mmengine - INFO - Epoch(train) [184][270/442] lr: 5.000000e-05 eta: 1:08:47 time: 0.345348 data_time: 0.034343 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.858257 2023/08/09 18:51:25 - mmengine - INFO - Epoch(train) [184][280/442] lr: 5.000000e-05 eta: 1:08:44 time: 0.344454 data_time: 0.031256 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.920124 2023/08/09 18:51:29 - mmengine - INFO - Epoch(train) [184][290/442] lr: 5.000000e-05 eta: 1:08:40 time: 0.346411 data_time: 0.031177 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.899417 2023/08/09 18:51:32 - mmengine - INFO - Epoch(train) [184][300/442] lr: 5.000000e-05 eta: 1:08:37 time: 0.346836 data_time: 0.031217 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.912161 2023/08/09 18:51:36 - mmengine - INFO - Epoch(train) [184][310/442] lr: 5.000000e-05 eta: 1:08:33 time: 0.346088 data_time: 0.030773 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.907500 2023/08/09 18:51:39 - mmengine - INFO - Epoch(train) [184][320/442] lr: 5.000000e-05 eta: 1:08:29 time: 0.345733 data_time: 0.030631 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.856780 2023/08/09 18:51:43 - mmengine - INFO - Epoch(train) [184][330/442] lr: 5.000000e-05 eta: 1:08:26 time: 0.345808 data_time: 0.030554 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.867016 2023/08/09 18:51:46 - mmengine - INFO - Epoch(train) [184][340/442] lr: 5.000000e-05 eta: 1:08:22 time: 0.348712 data_time: 0.033744 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.864135 2023/08/09 18:51:50 - mmengine - INFO - Epoch(train) [184][350/442] lr: 5.000000e-05 eta: 1:08:19 time: 0.349453 data_time: 0.034250 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.883148 2023/08/09 18:51:53 - mmengine - INFO - Epoch(train) [184][360/442] lr: 5.000000e-05 eta: 1:08:15 time: 0.349293 data_time: 0.034241 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.925334 2023/08/09 18:51:57 - mmengine - INFO - Epoch(train) [184][370/442] lr: 5.000000e-05 eta: 1:08:12 time: 0.350540 data_time: 0.034065 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.888207 2023/08/09 18:52:00 - mmengine - INFO - Epoch(train) [184][380/442] lr: 5.000000e-05 eta: 1:08:08 time: 0.352396 data_time: 0.034076 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.900904 2023/08/09 18:52:04 - mmengine - INFO - Epoch(train) [184][390/442] lr: 5.000000e-05 eta: 1:08:05 time: 0.348274 data_time: 0.031089 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.901539 2023/08/09 18:52:07 - mmengine - INFO - Epoch(train) [184][400/442] lr: 5.000000e-05 eta: 1:08:01 time: 0.348693 data_time: 0.030822 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.847403 2023/08/09 18:52:11 - mmengine - INFO - Epoch(train) [184][410/442] lr: 5.000000e-05 eta: 1:07:57 time: 0.350490 data_time: 0.031348 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.838316 2023/08/09 18:52:14 - mmengine - INFO - Epoch(train) [184][420/442] lr: 5.000000e-05 eta: 1:07:54 time: 0.349017 data_time: 0.031377 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.834589 2023/08/09 18:52:18 - mmengine - INFO - Epoch(train) [184][430/442] lr: 5.000000e-05 eta: 1:07:50 time: 0.348123 data_time: 0.031149 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.880697 2023/08/09 18:52:21 - mmengine - INFO - Epoch(train) [184][440/442] lr: 5.000000e-05 eta: 1:07:47 time: 0.347614 data_time: 0.031190 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.872678 2023/08/09 18:52:22 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:52:26 - mmengine - INFO - Epoch(train) [185][ 10/442] lr: 5.000000e-05 eta: 1:07:43 time: 0.350962 data_time: 0.034926 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.951944 2023/08/09 18:52:29 - mmengine - INFO - Epoch(train) [185][ 20/442] lr: 5.000000e-05 eta: 1:07:39 time: 0.353108 data_time: 0.035139 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.896482 2023/08/09 18:52:33 - mmengine - INFO - Epoch(train) [185][ 30/442] lr: 5.000000e-05 eta: 1:07:35 time: 0.355745 data_time: 0.035414 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.943504 2023/08/09 18:52:36 - mmengine - INFO - Epoch(train) [185][ 40/442] lr: 5.000000e-05 eta: 1:07:32 time: 0.352933 data_time: 0.035414 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.903777 2023/08/09 18:52:39 - mmengine - INFO - Epoch(train) [185][ 50/442] lr: 5.000000e-05 eta: 1:07:28 time: 0.353228 data_time: 0.035750 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.837347 2023/08/09 18:52:43 - mmengine - INFO - Epoch(train) [185][ 60/442] lr: 5.000000e-05 eta: 1:07:25 time: 0.345744 data_time: 0.031217 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.958291 2023/08/09 18:52:46 - mmengine - INFO - Epoch(train) [185][ 70/442] lr: 5.000000e-05 eta: 1:07:21 time: 0.342379 data_time: 0.031099 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.900072 2023/08/09 18:52:50 - mmengine - INFO - Epoch(train) [185][ 80/442] lr: 5.000000e-05 eta: 1:07:18 time: 0.342758 data_time: 0.030996 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.848043 2023/08/09 18:52:54 - mmengine - INFO - Epoch(train) [185][ 90/442] lr: 5.000000e-05 eta: 1:07:14 time: 0.350070 data_time: 0.031127 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.905982 2023/08/09 18:52:57 - mmengine - INFO - Epoch(train) [185][100/442] lr: 5.000000e-05 eta: 1:07:11 time: 0.356762 data_time: 0.035088 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.893635 2023/08/09 18:53:01 - mmengine - INFO - Epoch(train) [185][110/442] lr: 5.000000e-05 eta: 1:07:07 time: 0.359495 data_time: 0.035159 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.899876 2023/08/09 18:53:04 - mmengine - INFO - Epoch(train) [185][120/442] lr: 5.000000e-05 eta: 1:07:04 time: 0.364033 data_time: 0.034992 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.926752 2023/08/09 18:53:08 - mmengine - INFO - Epoch(train) [185][130/442] lr: 5.000000e-05 eta: 1:07:00 time: 0.362809 data_time: 0.034859 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.930118 2023/08/09 18:53:12 - mmengine - INFO - Epoch(train) [185][140/442] lr: 5.000000e-05 eta: 1:06:57 time: 0.358197 data_time: 0.034885 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.883465 2023/08/09 18:53:15 - mmengine - INFO - Epoch(train) [185][150/442] lr: 5.000000e-05 eta: 1:06:53 time: 0.355266 data_time: 0.031004 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.795822 2023/08/09 18:53:19 - mmengine - INFO - Epoch(train) [185][160/442] lr: 5.000000e-05 eta: 1:06:49 time: 0.358495 data_time: 0.031356 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.826041 2023/08/09 18:53:22 - mmengine - INFO - Epoch(train) [185][170/442] lr: 5.000000e-05 eta: 1:06:46 time: 0.359220 data_time: 0.031584 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.883891 2023/08/09 18:53:26 - mmengine - INFO - Epoch(train) [185][180/442] lr: 5.000000e-05 eta: 1:06:42 time: 0.359200 data_time: 0.031441 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.947349 2023/08/09 18:53:29 - mmengine - INFO - Epoch(train) [185][190/442] lr: 5.000000e-05 eta: 1:06:39 time: 0.358572 data_time: 0.031330 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.835746 2023/08/09 18:53:33 - mmengine - INFO - Epoch(train) [185][200/442] lr: 5.000000e-05 eta: 1:06:35 time: 0.358922 data_time: 0.031319 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.897249 2023/08/09 18:53:37 - mmengine - INFO - Epoch(train) [185][210/442] lr: 5.000000e-05 eta: 1:06:32 time: 0.356763 data_time: 0.031002 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.873584 2023/08/09 18:53:40 - mmengine - INFO - Epoch(train) [185][220/442] lr: 5.000000e-05 eta: 1:06:28 time: 0.354898 data_time: 0.030932 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.920974 2023/08/09 18:53:44 - mmengine - INFO - Epoch(train) [185][230/442] lr: 5.000000e-05 eta: 1:06:25 time: 0.363639 data_time: 0.031487 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.877813 2023/08/09 18:53:48 - mmengine - INFO - Epoch(train) [185][240/442] lr: 5.000000e-05 eta: 1:06:21 time: 0.368408 data_time: 0.031656 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.912900 2023/08/09 18:53:52 - mmengine - INFO - Epoch(train) [185][250/442] lr: 5.000000e-05 eta: 1:06:18 time: 0.370498 data_time: 0.031583 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.821933 2023/08/09 18:53:55 - mmengine - INFO - Epoch(train) [185][260/442] lr: 5.000000e-05 eta: 1:06:14 time: 0.370657 data_time: 0.031610 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.822696 2023/08/09 18:53:59 - mmengine - INFO - Epoch(train) [185][270/442] lr: 5.000000e-05 eta: 1:06:11 time: 0.369790 data_time: 0.031695 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.837357 2023/08/09 18:54:02 - mmengine - INFO - Epoch(train) [185][280/442] lr: 5.000000e-05 eta: 1:06:07 time: 0.361747 data_time: 0.031415 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.852302 2023/08/09 18:54:06 - mmengine - INFO - Epoch(train) [185][290/442] lr: 5.000000e-05 eta: 1:06:04 time: 0.357346 data_time: 0.031610 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.921642 2023/08/09 18:54:09 - mmengine - INFO - Epoch(train) [185][300/442] lr: 5.000000e-05 eta: 1:06:00 time: 0.356863 data_time: 0.032277 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.918921 2023/08/09 18:54:13 - mmengine - INFO - Epoch(train) [185][310/442] lr: 5.000000e-05 eta: 1:05:57 time: 0.356561 data_time: 0.032891 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.867221 2023/08/09 18:54:17 - mmengine - INFO - Epoch(train) [185][320/442] lr: 5.000000e-05 eta: 1:05:53 time: 0.356252 data_time: 0.033220 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.913585 2023/08/09 18:54:20 - mmengine - INFO - Epoch(train) [185][330/442] lr: 5.000000e-05 eta: 1:05:50 time: 0.357961 data_time: 0.033757 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.890962 2023/08/09 18:54:24 - mmengine - INFO - Epoch(train) [185][340/442] lr: 5.000000e-05 eta: 1:05:46 time: 0.359860 data_time: 0.033507 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.904832 2023/08/09 18:54:27 - mmengine - INFO - Epoch(train) [185][350/442] lr: 5.000000e-05 eta: 1:05:43 time: 0.357866 data_time: 0.033557 memory: 4565 loss: 0.000734 loss_kpt: 0.000734 acc_pose: 0.884579 2023/08/09 18:54:31 - mmengine - INFO - Epoch(train) [185][360/442] lr: 5.000000e-05 eta: 1:05:39 time: 0.357336 data_time: 0.032779 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.874936 2023/08/09 18:54:35 - mmengine - INFO - Epoch(train) [185][370/442] lr: 5.000000e-05 eta: 1:05:36 time: 0.359808 data_time: 0.032140 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.916075 2023/08/09 18:54:38 - mmengine - INFO - Epoch(train) [185][380/442] lr: 5.000000e-05 eta: 1:05:32 time: 0.357711 data_time: 0.031389 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.921306 2023/08/09 18:54:42 - mmengine - INFO - Epoch(train) [185][390/442] lr: 5.000000e-05 eta: 1:05:29 time: 0.355966 data_time: 0.031142 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.882767 2023/08/09 18:54:45 - mmengine - INFO - Epoch(train) [185][400/442] lr: 5.000000e-05 eta: 1:05:25 time: 0.356546 data_time: 0.030680 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.865625 2023/08/09 18:54:49 - mmengine - INFO - Epoch(train) [185][410/442] lr: 5.000000e-05 eta: 1:05:22 time: 0.358619 data_time: 0.030811 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.889310 2023/08/09 18:54:52 - mmengine - INFO - Epoch(train) [185][420/442] lr: 5.000000e-05 eta: 1:05:18 time: 0.356266 data_time: 0.030810 memory: 4565 loss: 0.000734 loss_kpt: 0.000734 acc_pose: 0.881092 2023/08/09 18:54:56 - mmengine - INFO - Epoch(train) [185][430/442] lr: 5.000000e-05 eta: 1:05:14 time: 0.355951 data_time: 0.030803 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.880116 2023/08/09 18:54:59 - mmengine - INFO - Epoch(train) [185][440/442] lr: 5.000000e-05 eta: 1:05:11 time: 0.354294 data_time: 0.030799 memory: 4565 loss: 0.000748 loss_kpt: 0.000748 acc_pose: 0.893718 2023/08/09 18:55:00 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:55:04 - mmengine - INFO - Epoch(train) [186][ 10/442] lr: 5.000000e-05 eta: 1:05:07 time: 0.352416 data_time: 0.033945 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.846894 2023/08/09 18:55:07 - mmengine - INFO - Epoch(train) [186][ 20/442] lr: 5.000000e-05 eta: 1:05:03 time: 0.348942 data_time: 0.034010 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.851408 2023/08/09 18:55:11 - mmengine - INFO - Epoch(train) [186][ 30/442] lr: 5.000000e-05 eta: 1:04:59 time: 0.348123 data_time: 0.034356 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.847836 2023/08/09 18:55:14 - mmengine - INFO - Epoch(train) [186][ 40/442] lr: 5.000000e-05 eta: 1:04:56 time: 0.348809 data_time: 0.034838 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.890372 2023/08/09 18:55:18 - mmengine - INFO - Epoch(train) [186][ 50/442] lr: 5.000000e-05 eta: 1:04:52 time: 0.355825 data_time: 0.038473 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.888365 2023/08/09 18:55:21 - mmengine - INFO - Epoch(train) [186][ 60/442] lr: 5.000000e-05 eta: 1:04:49 time: 0.352873 data_time: 0.034783 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.905272 2023/08/09 18:55:25 - mmengine - INFO - Epoch(train) [186][ 70/442] lr: 5.000000e-05 eta: 1:04:45 time: 0.351666 data_time: 0.034582 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.898714 2023/08/09 18:55:28 - mmengine - INFO - Epoch(train) [186][ 80/442] lr: 5.000000e-05 eta: 1:04:42 time: 0.350691 data_time: 0.034310 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.874832 2023/08/09 18:55:32 - mmengine - INFO - Epoch(train) [186][ 90/442] lr: 5.000000e-05 eta: 1:04:38 time: 0.350715 data_time: 0.034104 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.902274 2023/08/09 18:55:35 - mmengine - INFO - Epoch(train) [186][100/442] lr: 5.000000e-05 eta: 1:04:35 time: 0.345252 data_time: 0.031101 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.904774 2023/08/09 18:55:39 - mmengine - INFO - Epoch(train) [186][110/442] lr: 5.000000e-05 eta: 1:04:31 time: 0.346120 data_time: 0.031340 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.852401 2023/08/09 18:55:42 - mmengine - INFO - Epoch(train) [186][120/442] lr: 5.000000e-05 eta: 1:04:28 time: 0.346163 data_time: 0.031423 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.890617 2023/08/09 18:55:45 - mmengine - INFO - Epoch(train) [186][130/442] lr: 5.000000e-05 eta: 1:04:24 time: 0.346011 data_time: 0.031493 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.866358 2023/08/09 18:55:49 - mmengine - INFO - Epoch(train) [186][140/442] lr: 5.000000e-05 eta: 1:04:20 time: 0.344785 data_time: 0.031266 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.874450 2023/08/09 18:55:52 - mmengine - INFO - Epoch(train) [186][150/442] lr: 5.000000e-05 eta: 1:04:17 time: 0.343595 data_time: 0.031043 memory: 4565 loss: 0.000746 loss_kpt: 0.000746 acc_pose: 0.959921 2023/08/09 18:55:56 - mmengine - INFO - Epoch(train) [186][160/442] lr: 5.000000e-05 eta: 1:04:13 time: 0.343436 data_time: 0.031117 memory: 4565 loss: 0.000753 loss_kpt: 0.000753 acc_pose: 0.913133 2023/08/09 18:55:59 - mmengine - INFO - Epoch(train) [186][170/442] lr: 5.000000e-05 eta: 1:04:10 time: 0.347990 data_time: 0.031288 memory: 4565 loss: 0.000759 loss_kpt: 0.000759 acc_pose: 0.860853 2023/08/09 18:56:03 - mmengine - INFO - Epoch(train) [186][180/442] lr: 5.000000e-05 eta: 1:04:06 time: 0.347431 data_time: 0.031345 memory: 4565 loss: 0.000762 loss_kpt: 0.000762 acc_pose: 0.924324 2023/08/09 18:56:06 - mmengine - INFO - Epoch(train) [186][190/442] lr: 5.000000e-05 eta: 1:04:03 time: 0.346351 data_time: 0.031330 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.840903 2023/08/09 18:56:10 - mmengine - INFO - Epoch(train) [186][200/442] lr: 5.000000e-05 eta: 1:03:59 time: 0.346114 data_time: 0.031397 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.884750 2023/08/09 18:56:13 - mmengine - INFO - Epoch(train) [186][210/442] lr: 5.000000e-05 eta: 1:03:55 time: 0.345198 data_time: 0.031213 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.811066 2023/08/09 18:56:16 - mmengine - INFO - Epoch(train) [186][220/442] lr: 5.000000e-05 eta: 1:03:52 time: 0.342310 data_time: 0.031679 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.902458 2023/08/09 18:56:20 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:56:20 - mmengine - INFO - Epoch(train) [186][230/442] lr: 5.000000e-05 eta: 1:03:48 time: 0.343551 data_time: 0.032078 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.854501 2023/08/09 18:56:23 - mmengine - INFO - Epoch(train) [186][240/442] lr: 5.000000e-05 eta: 1:03:45 time: 0.344539 data_time: 0.032743 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.909175 2023/08/09 18:56:27 - mmengine - INFO - Epoch(train) [186][250/442] lr: 5.000000e-05 eta: 1:03:41 time: 0.347589 data_time: 0.035814 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.868771 2023/08/09 18:56:30 - mmengine - INFO - Epoch(train) [186][260/442] lr: 5.000000e-05 eta: 1:03:38 time: 0.347198 data_time: 0.035857 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.920109 2023/08/09 18:56:34 - mmengine - INFO - Epoch(train) [186][270/442] lr: 5.000000e-05 eta: 1:03:34 time: 0.345318 data_time: 0.035339 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.917109 2023/08/09 18:56:37 - mmengine - INFO - Epoch(train) [186][280/442] lr: 5.000000e-05 eta: 1:03:30 time: 0.345049 data_time: 0.034972 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.855252 2023/08/09 18:56:41 - mmengine - INFO - Epoch(train) [186][290/442] lr: 5.000000e-05 eta: 1:03:27 time: 0.349659 data_time: 0.034527 memory: 4565 loss: 0.000752 loss_kpt: 0.000752 acc_pose: 0.853382 2023/08/09 18:56:44 - mmengine - INFO - Epoch(train) [186][300/442] lr: 5.000000e-05 eta: 1:03:23 time: 0.348988 data_time: 0.031668 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.911084 2023/08/09 18:56:48 - mmengine - INFO - Epoch(train) [186][310/442] lr: 5.000000e-05 eta: 1:03:20 time: 0.349542 data_time: 0.031514 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.918172 2023/08/09 18:56:51 - mmengine - INFO - Epoch(train) [186][320/442] lr: 5.000000e-05 eta: 1:03:16 time: 0.349372 data_time: 0.031332 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.845895 2023/08/09 18:56:55 - mmengine - INFO - Epoch(train) [186][330/442] lr: 5.000000e-05 eta: 1:03:13 time: 0.348361 data_time: 0.031092 memory: 4565 loss: 0.000748 loss_kpt: 0.000748 acc_pose: 0.904027 2023/08/09 18:56:58 - mmengine - INFO - Epoch(train) [186][340/442] lr: 5.000000e-05 eta: 1:03:09 time: 0.344359 data_time: 0.031198 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.898526 2023/08/09 18:57:02 - mmengine - INFO - Epoch(train) [186][350/442] lr: 5.000000e-05 eta: 1:03:06 time: 0.342706 data_time: 0.030957 memory: 4565 loss: 0.000734 loss_kpt: 0.000734 acc_pose: 0.875259 2023/08/09 18:57:05 - mmengine - INFO - Epoch(train) [186][360/442] lr: 5.000000e-05 eta: 1:03:02 time: 0.342450 data_time: 0.031330 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.881581 2023/08/09 18:57:08 - mmengine - INFO - Epoch(train) [186][370/442] lr: 5.000000e-05 eta: 1:02:58 time: 0.344636 data_time: 0.032280 memory: 4565 loss: 0.000750 loss_kpt: 0.000750 acc_pose: 0.840435 2023/08/09 18:57:12 - mmengine - INFO - Epoch(train) [186][380/442] lr: 5.000000e-05 eta: 1:02:55 time: 0.345069 data_time: 0.033131 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.907650 2023/08/09 18:57:15 - mmengine - INFO - Epoch(train) [186][390/442] lr: 5.000000e-05 eta: 1:02:51 time: 0.344774 data_time: 0.033736 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.893487 2023/08/09 18:57:19 - mmengine - INFO - Epoch(train) [186][400/442] lr: 5.000000e-05 eta: 1:02:48 time: 0.346824 data_time: 0.034455 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.878935 2023/08/09 18:57:22 - mmengine - INFO - Epoch(train) [186][410/442] lr: 5.000000e-05 eta: 1:02:44 time: 0.347637 data_time: 0.034718 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.899209 2023/08/09 18:57:26 - mmengine - INFO - Epoch(train) [186][420/442] lr: 5.000000e-05 eta: 1:02:41 time: 0.347542 data_time: 0.034114 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.833866 2023/08/09 18:57:29 - mmengine - INFO - Epoch(train) [186][430/442] lr: 5.000000e-05 eta: 1:02:37 time: 0.349134 data_time: 0.033445 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.889730 2023/08/09 18:57:33 - mmengine - INFO - Epoch(train) [186][440/442] lr: 5.000000e-05 eta: 1:02:34 time: 0.355467 data_time: 0.033216 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.928806 2023/08/09 18:57:34 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 18:57:38 - mmengine - INFO - Epoch(train) [187][ 10/442] lr: 5.000000e-05 eta: 1:02:30 time: 0.368380 data_time: 0.039325 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.922923 2023/08/09 18:57:42 - mmengine - INFO - Epoch(train) [187][ 20/442] lr: 5.000000e-05 eta: 1:02:26 time: 0.370540 data_time: 0.039056 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.910417 2023/08/09 18:57:45 - mmengine - INFO - Epoch(train) [187][ 30/442] lr: 5.000000e-05 eta: 1:02:22 time: 0.369241 data_time: 0.039498 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.853872 2023/08/09 18:57:49 - mmengine - INFO - Epoch(train) [187][ 40/442] lr: 5.000000e-05 eta: 1:02:19 time: 0.369933 data_time: 0.039414 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.889818 2023/08/09 18:57:52 - mmengine - INFO - Epoch(train) [187][ 50/442] lr: 5.000000e-05 eta: 1:02:15 time: 0.367056 data_time: 0.039568 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.839032 2023/08/09 18:57:56 - mmengine - INFO - Epoch(train) [187][ 60/442] lr: 5.000000e-05 eta: 1:02:12 time: 0.350904 data_time: 0.032304 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.868837 2023/08/09 18:57:59 - mmengine - INFO - Epoch(train) [187][ 70/442] lr: 5.000000e-05 eta: 1:02:08 time: 0.347029 data_time: 0.032250 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.951734 2023/08/09 18:58:02 - mmengine - INFO - Epoch(train) [187][ 80/442] lr: 5.000000e-05 eta: 1:02:05 time: 0.346734 data_time: 0.031474 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.872019 2023/08/09 18:58:06 - mmengine - INFO - Epoch(train) [187][ 90/442] lr: 5.000000e-05 eta: 1:02:01 time: 0.352203 data_time: 0.031442 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.911668 2023/08/09 18:58:10 - mmengine - INFO - Epoch(train) [187][100/442] lr: 5.000000e-05 eta: 1:01:58 time: 0.349323 data_time: 0.031100 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.900204 2023/08/09 18:58:13 - mmengine - INFO - Epoch(train) [187][110/442] lr: 5.000000e-05 eta: 1:01:54 time: 0.350248 data_time: 0.031361 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.880474 2023/08/09 18:58:17 - mmengine - INFO - Epoch(train) [187][120/442] lr: 5.000000e-05 eta: 1:01:51 time: 0.352444 data_time: 0.031519 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.903765 2023/08/09 18:58:20 - mmengine - INFO - Epoch(train) [187][130/442] lr: 5.000000e-05 eta: 1:01:47 time: 0.352278 data_time: 0.031645 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.877037 2023/08/09 18:58:23 - mmengine - INFO - Epoch(train) [187][140/442] lr: 5.000000e-05 eta: 1:01:43 time: 0.344003 data_time: 0.031476 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.868287 2023/08/09 18:58:27 - mmengine - INFO - Epoch(train) [187][150/442] lr: 5.000000e-05 eta: 1:01:40 time: 0.343794 data_time: 0.031880 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.849569 2023/08/09 18:58:30 - mmengine - INFO - Epoch(train) [187][160/442] lr: 5.000000e-05 eta: 1:01:36 time: 0.344123 data_time: 0.031631 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.876949 2023/08/09 18:58:34 - mmengine - INFO - Epoch(train) [187][170/442] lr: 5.000000e-05 eta: 1:01:33 time: 0.348200 data_time: 0.034767 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.933102 2023/08/09 18:58:38 - mmengine - INFO - Epoch(train) [187][180/442] lr: 5.000000e-05 eta: 1:01:29 time: 0.351814 data_time: 0.034765 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.934689 2023/08/09 18:58:41 - mmengine - INFO - Epoch(train) [187][190/442] lr: 5.000000e-05 eta: 1:01:26 time: 0.353653 data_time: 0.034725 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.944134 2023/08/09 18:58:45 - mmengine - INFO - Epoch(train) [187][200/442] lr: 5.000000e-05 eta: 1:01:22 time: 0.354693 data_time: 0.034133 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.909478 2023/08/09 18:58:48 - mmengine - INFO - Epoch(train) [187][210/442] lr: 5.000000e-05 eta: 1:01:19 time: 0.354113 data_time: 0.033823 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.862015 2023/08/09 18:58:52 - mmengine - INFO - Epoch(train) [187][220/442] lr: 5.000000e-05 eta: 1:01:15 time: 0.349985 data_time: 0.030317 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.875229 2023/08/09 18:58:55 - mmengine - INFO - Epoch(train) [187][230/442] lr: 5.000000e-05 eta: 1:01:12 time: 0.355084 data_time: 0.030232 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.853985 2023/08/09 18:58:59 - mmengine - INFO - Epoch(train) [187][240/442] lr: 5.000000e-05 eta: 1:01:08 time: 0.356049 data_time: 0.030398 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.930339 2023/08/09 18:59:03 - mmengine - INFO - Epoch(train) [187][250/442] lr: 5.000000e-05 eta: 1:01:04 time: 0.358939 data_time: 0.030721 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.892000 2023/08/09 18:59:06 - mmengine - INFO - Epoch(train) [187][260/442] lr: 5.000000e-05 eta: 1:01:01 time: 0.359279 data_time: 0.030723 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.845736 2023/08/09 18:59:10 - mmengine - INFO - Epoch(train) [187][270/442] lr: 5.000000e-05 eta: 1:00:57 time: 0.359537 data_time: 0.030825 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.921704 2023/08/09 18:59:13 - mmengine - INFO - Epoch(train) [187][280/442] lr: 5.000000e-05 eta: 1:00:54 time: 0.353856 data_time: 0.030840 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.910889 2023/08/09 18:59:17 - mmengine - INFO - Epoch(train) [187][290/442] lr: 5.000000e-05 eta: 1:00:50 time: 0.353135 data_time: 0.030678 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.889820 2023/08/09 18:59:20 - mmengine - INFO - Epoch(train) [187][300/442] lr: 5.000000e-05 eta: 1:00:47 time: 0.352978 data_time: 0.030853 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.859047 2023/08/09 18:59:24 - mmengine - INFO - Epoch(train) [187][310/442] lr: 5.000000e-05 eta: 1:00:43 time: 0.354820 data_time: 0.031074 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.882224 2023/08/09 18:59:27 - mmengine - INFO - Epoch(train) [187][320/442] lr: 5.000000e-05 eta: 1:00:40 time: 0.354861 data_time: 0.030940 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.905608 2023/08/09 18:59:31 - mmengine - INFO - Epoch(train) [187][330/442] lr: 5.000000e-05 eta: 1:00:36 time: 0.353362 data_time: 0.030879 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.894197 2023/08/09 18:59:34 - mmengine - INFO - Epoch(train) [187][340/442] lr: 5.000000e-05 eta: 1:00:33 time: 0.353135 data_time: 0.030915 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.840873 2023/08/09 18:59:38 - mmengine - INFO - Epoch(train) [187][350/442] lr: 5.000000e-05 eta: 1:00:29 time: 0.351851 data_time: 0.030520 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.825164 2023/08/09 18:59:42 - mmengine - INFO - Epoch(train) [187][360/442] lr: 5.000000e-05 eta: 1:00:26 time: 0.355101 data_time: 0.034030 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.867569 2023/08/09 18:59:45 - mmengine - INFO - Epoch(train) [187][370/442] lr: 5.000000e-05 eta: 1:00:22 time: 0.358550 data_time: 0.034205 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.855057 2023/08/09 18:59:49 - mmengine - INFO - Epoch(train) [187][380/442] lr: 5.000000e-05 eta: 1:00:19 time: 0.360355 data_time: 0.034521 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.858812 2023/08/09 18:59:52 - mmengine - INFO - Epoch(train) [187][390/442] lr: 5.000000e-05 eta: 1:00:15 time: 0.361165 data_time: 0.034809 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.941817 2023/08/09 18:59:56 - mmengine - INFO - Epoch(train) [187][400/442] lr: 5.000000e-05 eta: 1:00:11 time: 0.360978 data_time: 0.034852 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.871226 2023/08/09 18:59:59 - mmengine - INFO - Epoch(train) [187][410/442] lr: 5.000000e-05 eta: 1:00:08 time: 0.356143 data_time: 0.031094 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.909285 2023/08/09 19:00:03 - mmengine - INFO - Epoch(train) [187][420/442] lr: 5.000000e-05 eta: 1:00:04 time: 0.353513 data_time: 0.031216 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.934659 2023/08/09 19:00:07 - mmengine - INFO - Epoch(train) [187][430/442] lr: 5.000000e-05 eta: 1:00:01 time: 0.359082 data_time: 0.031477 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.929499 2023/08/09 19:00:11 - mmengine - INFO - Epoch(train) [187][440/442] lr: 5.000000e-05 eta: 0:59:58 time: 0.367505 data_time: 0.031704 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.903896 2023/08/09 19:00:11 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:00:15 - mmengine - INFO - Epoch(train) [188][ 10/442] lr: 5.000000e-05 eta: 0:59:53 time: 0.371331 data_time: 0.035137 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.842768 2023/08/09 19:00:19 - mmengine - INFO - Epoch(train) [188][ 20/442] lr: 5.000000e-05 eta: 0:59:50 time: 0.371198 data_time: 0.035154 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.903522 2023/08/09 19:00:22 - mmengine - INFO - Epoch(train) [188][ 30/442] lr: 5.000000e-05 eta: 0:59:46 time: 0.371105 data_time: 0.034927 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.924308 2023/08/09 19:00:26 - mmengine - INFO - Epoch(train) [188][ 40/442] lr: 5.000000e-05 eta: 0:59:43 time: 0.365496 data_time: 0.035353 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.935417 2023/08/09 19:00:30 - mmengine - INFO - Epoch(train) [188][ 50/442] lr: 5.000000e-05 eta: 0:59:39 time: 0.364087 data_time: 0.035827 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.868231 2023/08/09 19:00:33 - mmengine - INFO - Epoch(train) [188][ 60/442] lr: 5.000000e-05 eta: 0:59:36 time: 0.360687 data_time: 0.032649 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.844699 2023/08/09 19:00:37 - mmengine - INFO - Epoch(train) [188][ 70/442] lr: 5.000000e-05 eta: 0:59:32 time: 0.360728 data_time: 0.032833 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.888275 2023/08/09 19:00:40 - mmengine - INFO - Epoch(train) [188][ 80/442] lr: 5.000000e-05 eta: 0:59:29 time: 0.360273 data_time: 0.033052 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.939486 2023/08/09 19:00:44 - mmengine - INFO - Epoch(train) [188][ 90/442] lr: 5.000000e-05 eta: 0:59:25 time: 0.357618 data_time: 0.031906 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.906063 2023/08/09 19:00:47 - mmengine - INFO - Epoch(train) [188][100/442] lr: 5.000000e-05 eta: 0:59:22 time: 0.353806 data_time: 0.031450 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.942653 2023/08/09 19:00:51 - mmengine - INFO - Epoch(train) [188][110/442] lr: 5.000000e-05 eta: 0:59:18 time: 0.356607 data_time: 0.034599 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.882454 2023/08/09 19:00:55 - mmengine - INFO - Epoch(train) [188][120/442] lr: 5.000000e-05 eta: 0:59:15 time: 0.357392 data_time: 0.034512 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.935308 2023/08/09 19:00:58 - mmengine - INFO - Epoch(train) [188][130/442] lr: 5.000000e-05 eta: 0:59:11 time: 0.358747 data_time: 0.034805 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.912735 2023/08/09 19:01:02 - mmengine - INFO - Epoch(train) [188][140/442] lr: 5.000000e-05 eta: 0:59:07 time: 0.358312 data_time: 0.034841 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.941041 2023/08/09 19:01:05 - mmengine - INFO - Epoch(train) [188][150/442] lr: 5.000000e-05 eta: 0:59:04 time: 0.358410 data_time: 0.034640 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.899191 2023/08/09 19:01:09 - mmengine - INFO - Epoch(train) [188][160/442] lr: 5.000000e-05 eta: 0:59:00 time: 0.354164 data_time: 0.030941 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.945974 2023/08/09 19:01:12 - mmengine - INFO - Epoch(train) [188][170/442] lr: 5.000000e-05 eta: 0:58:57 time: 0.353999 data_time: 0.031110 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.920088 2023/08/09 19:01:16 - mmengine - INFO - Epoch(train) [188][180/442] lr: 5.000000e-05 eta: 0:58:53 time: 0.356711 data_time: 0.030752 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.904012 2023/08/09 19:01:20 - mmengine - INFO - Epoch(train) [188][190/442] lr: 5.000000e-05 eta: 0:58:50 time: 0.358125 data_time: 0.030999 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.881203 2023/08/09 19:01:23 - mmengine - INFO - Epoch(train) [188][200/442] lr: 5.000000e-05 eta: 0:58:46 time: 0.357237 data_time: 0.031030 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.922890 2023/08/09 19:01:27 - mmengine - INFO - Epoch(train) [188][210/442] lr: 5.000000e-05 eta: 0:58:43 time: 0.356354 data_time: 0.030992 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.910106 2023/08/09 19:01:30 - mmengine - INFO - Epoch(train) [188][220/442] lr: 5.000000e-05 eta: 0:58:39 time: 0.355495 data_time: 0.030693 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.902043 2023/08/09 19:01:34 - mmengine - INFO - Epoch(train) [188][230/442] lr: 5.000000e-05 eta: 0:58:36 time: 0.351895 data_time: 0.030782 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.830383 2023/08/09 19:01:37 - mmengine - INFO - Epoch(train) [188][240/442] lr: 5.000000e-05 eta: 0:58:32 time: 0.352301 data_time: 0.030744 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.863292 2023/08/09 19:01:41 - mmengine - INFO - Epoch(train) [188][250/442] lr: 5.000000e-05 eta: 0:58:29 time: 0.353127 data_time: 0.031200 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.922395 2023/08/09 19:01:44 - mmengine - INFO - Epoch(train) [188][260/442] lr: 5.000000e-05 eta: 0:58:25 time: 0.354032 data_time: 0.032440 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.846158 2023/08/09 19:01:48 - mmengine - INFO - Epoch(train) [188][270/442] lr: 5.000000e-05 eta: 0:58:21 time: 0.354418 data_time: 0.033416 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.853514 2023/08/09 19:01:51 - mmengine - INFO - Epoch(train) [188][280/442] lr: 5.000000e-05 eta: 0:58:18 time: 0.353436 data_time: 0.034070 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.937397 2023/08/09 19:01:55 - mmengine - INFO - Epoch(train) [188][290/442] lr: 5.000000e-05 eta: 0:58:14 time: 0.352298 data_time: 0.034073 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.886395 2023/08/09 19:01:59 - mmengine - INFO - Epoch(train) [188][300/442] lr: 5.000000e-05 eta: 0:58:11 time: 0.355505 data_time: 0.033901 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.882097 2023/08/09 19:02:02 - mmengine - INFO - Epoch(train) [188][310/442] lr: 5.000000e-05 eta: 0:58:07 time: 0.359581 data_time: 0.036458 memory: 4565 loss: 0.000754 loss_kpt: 0.000754 acc_pose: 0.891037 2023/08/09 19:02:06 - mmengine - INFO - Epoch(train) [188][320/442] lr: 5.000000e-05 eta: 0:58:04 time: 0.360775 data_time: 0.035807 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.907803 2023/08/09 19:02:09 - mmengine - INFO - Epoch(train) [188][330/442] lr: 5.000000e-05 eta: 0:58:00 time: 0.361979 data_time: 0.035142 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.872284 2023/08/09 19:02:13 - mmengine - INFO - Epoch(train) [188][340/442] lr: 5.000000e-05 eta: 0:57:57 time: 0.362173 data_time: 0.034975 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.940438 2023/08/09 19:02:15 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:02:17 - mmengine - INFO - Epoch(train) [188][350/442] lr: 5.000000e-05 eta: 0:57:53 time: 0.358240 data_time: 0.034860 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.869511 2023/08/09 19:02:20 - mmengine - INFO - Epoch(train) [188][360/442] lr: 5.000000e-05 eta: 0:57:50 time: 0.355633 data_time: 0.031109 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.883752 2023/08/09 19:02:24 - mmengine - INFO - Epoch(train) [188][370/442] lr: 5.000000e-05 eta: 0:57:46 time: 0.356926 data_time: 0.031340 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.898594 2023/08/09 19:02:27 - mmengine - INFO - Epoch(train) [188][380/442] lr: 5.000000e-05 eta: 0:57:43 time: 0.358115 data_time: 0.031784 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.890718 2023/08/09 19:02:31 - mmengine - INFO - Epoch(train) [188][390/442] lr: 5.000000e-05 eta: 0:57:39 time: 0.357399 data_time: 0.031782 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.898892 2023/08/09 19:02:34 - mmengine - INFO - Epoch(train) [188][400/442] lr: 5.000000e-05 eta: 0:57:36 time: 0.357475 data_time: 0.031955 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.904908 2023/08/09 19:02:38 - mmengine - INFO - Epoch(train) [188][410/442] lr: 5.000000e-05 eta: 0:57:32 time: 0.355162 data_time: 0.032082 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.875144 2023/08/09 19:02:41 - mmengine - INFO - Epoch(train) [188][420/442] lr: 5.000000e-05 eta: 0:57:29 time: 0.352589 data_time: 0.031734 memory: 4565 loss: 0.000734 loss_kpt: 0.000734 acc_pose: 0.906572 2023/08/09 19:02:45 - mmengine - INFO - Epoch(train) [188][430/442] lr: 5.000000e-05 eta: 0:57:25 time: 0.355843 data_time: 0.031429 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.832807 2023/08/09 19:02:49 - mmengine - INFO - Epoch(train) [188][440/442] lr: 5.000000e-05 eta: 0:57:22 time: 0.360599 data_time: 0.031706 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.893475 2023/08/09 19:02:50 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:02:53 - mmengine - INFO - Epoch(train) [189][ 10/442] lr: 5.000000e-05 eta: 0:57:17 time: 0.363846 data_time: 0.035225 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.917386 2023/08/09 19:02:57 - mmengine - INFO - Epoch(train) [189][ 20/442] lr: 5.000000e-05 eta: 0:57:14 time: 0.364077 data_time: 0.035319 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.895492 2023/08/09 19:03:00 - mmengine - INFO - Epoch(train) [189][ 30/442] lr: 5.000000e-05 eta: 0:57:10 time: 0.364051 data_time: 0.035244 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.839384 2023/08/09 19:03:04 - mmengine - INFO - Epoch(train) [189][ 40/442] lr: 5.000000e-05 eta: 0:57:07 time: 0.357603 data_time: 0.035384 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.885011 2023/08/09 19:03:08 - mmengine - INFO - Epoch(train) [189][ 50/442] lr: 5.000000e-05 eta: 0:57:03 time: 0.359262 data_time: 0.038859 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.913393 2023/08/09 19:03:11 - mmengine - INFO - Epoch(train) [189][ 60/442] lr: 5.000000e-05 eta: 0:57:00 time: 0.356016 data_time: 0.035369 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.889060 2023/08/09 19:03:15 - mmengine - INFO - Epoch(train) [189][ 70/442] lr: 5.000000e-05 eta: 0:56:56 time: 0.357211 data_time: 0.035302 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.892942 2023/08/09 19:03:18 - mmengine - INFO - Epoch(train) [189][ 80/442] lr: 5.000000e-05 eta: 0:56:53 time: 0.357646 data_time: 0.035345 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.866506 2023/08/09 19:03:22 - mmengine - INFO - Epoch(train) [189][ 90/442] lr: 5.000000e-05 eta: 0:56:49 time: 0.357615 data_time: 0.034999 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.930569 2023/08/09 19:03:25 - mmengine - INFO - Epoch(train) [189][100/442] lr: 5.000000e-05 eta: 0:56:46 time: 0.354012 data_time: 0.031656 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.854887 2023/08/09 19:03:29 - mmengine - INFO - Epoch(train) [189][110/442] lr: 5.000000e-05 eta: 0:56:42 time: 0.357039 data_time: 0.031229 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.918345 2023/08/09 19:03:33 - mmengine - INFO - Epoch(train) [189][120/442] lr: 5.000000e-05 eta: 0:56:39 time: 0.357199 data_time: 0.031227 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.867934 2023/08/09 19:03:36 - mmengine - INFO - Epoch(train) [189][130/442] lr: 5.000000e-05 eta: 0:56:35 time: 0.359700 data_time: 0.031715 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.865882 2023/08/09 19:03:40 - mmengine - INFO - Epoch(train) [189][140/442] lr: 5.000000e-05 eta: 0:56:31 time: 0.359921 data_time: 0.032144 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.929500 2023/08/09 19:03:43 - mmengine - INFO - Epoch(train) [189][150/442] lr: 5.000000e-05 eta: 0:56:28 time: 0.358896 data_time: 0.031926 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.888070 2023/08/09 19:03:47 - mmengine - INFO - Epoch(train) [189][160/442] lr: 5.000000e-05 eta: 0:56:24 time: 0.354528 data_time: 0.031744 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.880496 2023/08/09 19:03:50 - mmengine - INFO - Epoch(train) [189][170/442] lr: 5.000000e-05 eta: 0:56:21 time: 0.353599 data_time: 0.031697 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.888413 2023/08/09 19:03:54 - mmengine - INFO - Epoch(train) [189][180/442] lr: 5.000000e-05 eta: 0:56:17 time: 0.351450 data_time: 0.031265 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.868247 2023/08/09 19:03:58 - mmengine - INFO - Epoch(train) [189][190/442] lr: 5.000000e-05 eta: 0:56:14 time: 0.355039 data_time: 0.034377 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.802983 2023/08/09 19:04:01 - mmengine - INFO - Epoch(train) [189][200/442] lr: 5.000000e-05 eta: 0:56:10 time: 0.357184 data_time: 0.034874 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.848707 2023/08/09 19:04:05 - mmengine - INFO - Epoch(train) [189][210/442] lr: 5.000000e-05 eta: 0:56:07 time: 0.357622 data_time: 0.035132 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.920566 2023/08/09 19:04:08 - mmengine - INFO - Epoch(train) [189][220/442] lr: 5.000000e-05 eta: 0:56:03 time: 0.356606 data_time: 0.034962 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.869895 2023/08/09 19:04:12 - mmengine - INFO - Epoch(train) [189][230/442] lr: 5.000000e-05 eta: 0:56:00 time: 0.358311 data_time: 0.034841 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.840777 2023/08/09 19:04:15 - mmengine - INFO - Epoch(train) [189][240/442] lr: 5.000000e-05 eta: 0:55:56 time: 0.355517 data_time: 0.031553 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.908182 2023/08/09 19:04:19 - mmengine - INFO - Epoch(train) [189][250/442] lr: 5.000000e-05 eta: 0:55:53 time: 0.356061 data_time: 0.032603 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.917439 2023/08/09 19:04:23 - mmengine - INFO - Epoch(train) [189][260/442] lr: 5.000000e-05 eta: 0:55:49 time: 0.357341 data_time: 0.032970 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.894413 2023/08/09 19:04:26 - mmengine - INFO - Epoch(train) [189][270/442] lr: 5.000000e-05 eta: 0:55:46 time: 0.356849 data_time: 0.032829 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.876419 2023/08/09 19:04:29 - mmengine - INFO - Epoch(train) [189][280/442] lr: 5.000000e-05 eta: 0:55:42 time: 0.353621 data_time: 0.032711 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.880116 2023/08/09 19:04:33 - mmengine - INFO - Epoch(train) [189][290/442] lr: 5.000000e-05 eta: 0:55:38 time: 0.352641 data_time: 0.032267 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.865784 2023/08/09 19:04:37 - mmengine - INFO - Epoch(train) [189][300/442] lr: 5.000000e-05 eta: 0:55:35 time: 0.350815 data_time: 0.030733 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.865471 2023/08/09 19:04:40 - mmengine - INFO - Epoch(train) [189][310/442] lr: 5.000000e-05 eta: 0:55:31 time: 0.350200 data_time: 0.030325 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.943989 2023/08/09 19:04:44 - mmengine - INFO - Epoch(train) [189][320/442] lr: 5.000000e-05 eta: 0:55:28 time: 0.354004 data_time: 0.031544 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.870976 2023/08/09 19:04:47 - mmengine - INFO - Epoch(train) [189][330/442] lr: 5.000000e-05 eta: 0:55:24 time: 0.354332 data_time: 0.031574 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.891745 2023/08/09 19:04:51 - mmengine - INFO - Epoch(train) [189][340/442] lr: 5.000000e-05 eta: 0:55:21 time: 0.358013 data_time: 0.034840 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.857915 2023/08/09 19:04:55 - mmengine - INFO - Epoch(train) [189][350/442] lr: 5.000000e-05 eta: 0:55:17 time: 0.361042 data_time: 0.034907 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.839498 2023/08/09 19:04:58 - mmengine - INFO - Epoch(train) [189][360/442] lr: 5.000000e-05 eta: 0:55:14 time: 0.362240 data_time: 0.034679 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.866184 2023/08/09 19:05:02 - mmengine - INFO - Epoch(train) [189][370/442] lr: 5.000000e-05 eta: 0:55:10 time: 0.360326 data_time: 0.033607 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.924805 2023/08/09 19:05:05 - mmengine - INFO - Epoch(train) [189][380/442] lr: 5.000000e-05 eta: 0:55:07 time: 0.362482 data_time: 0.033752 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.807387 2023/08/09 19:05:09 - mmengine - INFO - Epoch(train) [189][390/442] lr: 5.000000e-05 eta: 0:55:03 time: 0.361383 data_time: 0.031796 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.881634 2023/08/09 19:05:12 - mmengine - INFO - Epoch(train) [189][400/442] lr: 5.000000e-05 eta: 0:55:00 time: 0.357651 data_time: 0.031830 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.899757 2023/08/09 19:05:16 - mmengine - INFO - Epoch(train) [189][410/442] lr: 5.000000e-05 eta: 0:54:56 time: 0.355675 data_time: 0.031881 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.895595 2023/08/09 19:05:19 - mmengine - INFO - Epoch(train) [189][420/442] lr: 5.000000e-05 eta: 0:54:53 time: 0.353807 data_time: 0.031853 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.923720 2023/08/09 19:05:23 - mmengine - INFO - Epoch(train) [189][430/442] lr: 5.000000e-05 eta: 0:54:49 time: 0.352978 data_time: 0.032108 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.927703 2023/08/09 19:05:27 - mmengine - INFO - Epoch(train) [189][440/442] lr: 5.000000e-05 eta: 0:54:45 time: 0.352380 data_time: 0.031149 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.886399 2023/08/09 19:05:27 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:05:31 - mmengine - INFO - Epoch(train) [190][ 10/442] lr: 5.000000e-05 eta: 0:54:41 time: 0.356630 data_time: 0.035203 memory: 4565 loss: 0.000734 loss_kpt: 0.000734 acc_pose: 0.911412 2023/08/09 19:05:34 - mmengine - INFO - Epoch(train) [190][ 20/442] lr: 5.000000e-05 eta: 0:54:38 time: 0.355020 data_time: 0.035637 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.936822 2023/08/09 19:05:38 - mmengine - INFO - Epoch(train) [190][ 30/442] lr: 5.000000e-05 eta: 0:54:34 time: 0.357778 data_time: 0.036114 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.878287 2023/08/09 19:05:42 - mmengine - INFO - Epoch(train) [190][ 40/442] lr: 5.000000e-05 eta: 0:54:31 time: 0.358950 data_time: 0.039295 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.869199 2023/08/09 19:05:45 - mmengine - INFO - Epoch(train) [190][ 50/442] lr: 5.000000e-05 eta: 0:54:27 time: 0.356967 data_time: 0.039925 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.839427 2023/08/09 19:05:49 - mmengine - INFO - Epoch(train) [190][ 60/442] lr: 5.000000e-05 eta: 0:54:24 time: 0.351451 data_time: 0.036086 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.854475 2023/08/09 19:05:52 - mmengine - INFO - Epoch(train) [190][ 70/442] lr: 5.000000e-05 eta: 0:54:20 time: 0.353215 data_time: 0.036199 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.938013 2023/08/09 19:05:56 - mmengine - INFO - Epoch(train) [190][ 80/442] lr: 5.000000e-05 eta: 0:54:16 time: 0.349702 data_time: 0.035965 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.849839 2023/08/09 19:05:59 - mmengine - INFO - Epoch(train) [190][ 90/442] lr: 5.000000e-05 eta: 0:54:13 time: 0.345604 data_time: 0.032830 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.929517 2023/08/09 19:06:02 - mmengine - INFO - Epoch(train) [190][100/442] lr: 5.000000e-05 eta: 0:54:09 time: 0.344540 data_time: 0.032377 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.901911 2023/08/09 19:06:06 - mmengine - INFO - Epoch(train) [190][110/442] lr: 5.000000e-05 eta: 0:54:06 time: 0.342995 data_time: 0.031858 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.955272 2023/08/09 19:06:09 - mmengine - INFO - Epoch(train) [190][120/442] lr: 5.000000e-05 eta: 0:54:02 time: 0.341840 data_time: 0.031124 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.928677 2023/08/09 19:06:13 - mmengine - INFO - Epoch(train) [190][130/442] lr: 5.000000e-05 eta: 0:53:59 time: 0.342288 data_time: 0.030978 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.907914 2023/08/09 19:06:16 - mmengine - INFO - Epoch(train) [190][140/442] lr: 5.000000e-05 eta: 0:53:55 time: 0.345249 data_time: 0.031050 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.890285 2023/08/09 19:06:20 - mmengine - INFO - Epoch(train) [190][150/442] lr: 5.000000e-05 eta: 0:53:51 time: 0.347192 data_time: 0.031633 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.901169 2023/08/09 19:06:23 - mmengine - INFO - Epoch(train) [190][160/442] lr: 5.000000e-05 eta: 0:53:48 time: 0.347912 data_time: 0.032410 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.940873 2023/08/09 19:06:27 - mmengine - INFO - Epoch(train) [190][170/442] lr: 5.000000e-05 eta: 0:53:44 time: 0.350033 data_time: 0.033231 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.858145 2023/08/09 19:06:30 - mmengine - INFO - Epoch(train) [190][180/442] lr: 5.000000e-05 eta: 0:53:41 time: 0.349120 data_time: 0.033601 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.920532 2023/08/09 19:06:34 - mmengine - INFO - Epoch(train) [190][190/442] lr: 5.000000e-05 eta: 0:53:37 time: 0.348068 data_time: 0.033300 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.851078 2023/08/09 19:06:38 - mmengine - INFO - Epoch(train) [190][200/442] lr: 5.000000e-05 eta: 0:53:34 time: 0.356488 data_time: 0.033011 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.883904 2023/08/09 19:06:41 - mmengine - INFO - Epoch(train) [190][210/442] lr: 5.000000e-05 eta: 0:53:30 time: 0.359458 data_time: 0.032952 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.913583 2023/08/09 19:06:45 - mmengine - INFO - Epoch(train) [190][220/442] lr: 5.000000e-05 eta: 0:53:27 time: 0.357119 data_time: 0.032279 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.915161 2023/08/09 19:06:48 - mmengine - INFO - Epoch(train) [190][230/442] lr: 5.000000e-05 eta: 0:53:23 time: 0.356716 data_time: 0.031864 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.865755 2023/08/09 19:06:51 - mmengine - INFO - Epoch(train) [190][240/442] lr: 5.000000e-05 eta: 0:53:20 time: 0.354426 data_time: 0.031698 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.935564 2023/08/09 19:06:55 - mmengine - INFO - Epoch(train) [190][250/442] lr: 5.000000e-05 eta: 0:53:16 time: 0.344119 data_time: 0.031287 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.926080 2023/08/09 19:06:58 - mmengine - INFO - Epoch(train) [190][260/442] lr: 5.000000e-05 eta: 0:53:12 time: 0.344841 data_time: 0.034041 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.928267 2023/08/09 19:07:02 - mmengine - INFO - Epoch(train) [190][270/442] lr: 5.000000e-05 eta: 0:53:09 time: 0.345976 data_time: 0.034938 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.860769 2023/08/09 19:07:05 - mmengine - INFO - Epoch(train) [190][280/442] lr: 5.000000e-05 eta: 0:53:05 time: 0.346237 data_time: 0.034975 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.906797 2023/08/09 19:07:09 - mmengine - INFO - Epoch(train) [190][290/442] lr: 5.000000e-05 eta: 0:53:02 time: 0.346108 data_time: 0.035119 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.943025 2023/08/09 19:07:12 - mmengine - INFO - Epoch(train) [190][300/442] lr: 5.000000e-05 eta: 0:52:58 time: 0.348414 data_time: 0.035080 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.938278 2023/08/09 19:07:16 - mmengine - INFO - Epoch(train) [190][310/442] lr: 5.000000e-05 eta: 0:52:55 time: 0.345168 data_time: 0.031643 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.902352 2023/08/09 19:07:19 - mmengine - INFO - Epoch(train) [190][320/442] lr: 5.000000e-05 eta: 0:52:51 time: 0.344433 data_time: 0.031294 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.888431 2023/08/09 19:07:23 - mmengine - INFO - Epoch(train) [190][330/442] lr: 5.000000e-05 eta: 0:52:48 time: 0.346149 data_time: 0.031367 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.860954 2023/08/09 19:07:26 - mmengine - INFO - Epoch(train) [190][340/442] lr: 5.000000e-05 eta: 0:52:44 time: 0.348650 data_time: 0.031681 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.874480 2023/08/09 19:07:30 - mmengine - INFO - Epoch(train) [190][350/442] lr: 5.000000e-05 eta: 0:52:40 time: 0.346412 data_time: 0.032140 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.897382 2023/08/09 19:07:33 - mmengine - INFO - Epoch(train) [190][360/442] lr: 5.000000e-05 eta: 0:52:37 time: 0.345596 data_time: 0.032677 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.837678 2023/08/09 19:07:37 - mmengine - INFO - Epoch(train) [190][370/442] lr: 5.000000e-05 eta: 0:52:33 time: 0.348882 data_time: 0.036804 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.845687 2023/08/09 19:07:40 - mmengine - INFO - Epoch(train) [190][380/442] lr: 5.000000e-05 eta: 0:52:30 time: 0.348169 data_time: 0.036624 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.875880 2023/08/09 19:07:44 - mmengine - INFO - Epoch(train) [190][390/442] lr: 5.000000e-05 eta: 0:52:26 time: 0.348167 data_time: 0.036094 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.906400 2023/08/09 19:07:47 - mmengine - INFO - Epoch(train) [190][400/442] lr: 5.000000e-05 eta: 0:52:23 time: 0.349298 data_time: 0.036131 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.881558 2023/08/09 19:07:51 - mmengine - INFO - Epoch(train) [190][410/442] lr: 5.000000e-05 eta: 0:52:19 time: 0.357507 data_time: 0.035963 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.864361 2023/08/09 19:07:54 - mmengine - INFO - Epoch(train) [190][420/442] lr: 5.000000e-05 eta: 0:52:16 time: 0.354033 data_time: 0.031645 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.912633 2023/08/09 19:07:58 - mmengine - INFO - Epoch(train) [190][430/442] lr: 5.000000e-05 eta: 0:52:12 time: 0.352753 data_time: 0.031670 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.883297 2023/08/09 19:08:01 - mmengine - INFO - Epoch(train) [190][440/442] lr: 5.000000e-05 eta: 0:52:09 time: 0.351380 data_time: 0.031694 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.957562 2023/08/09 19:08:02 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:08:02 - mmengine - INFO - Saving checkpoint at 190 epochs 2023/08/09 19:08:07 - mmengine - INFO - Epoch(val) [190][ 10/108] eta: 0:00:20 time: 0.200655 data_time: 0.013648 memory: 4565 2023/08/09 19:08:09 - mmengine - INFO - Epoch(val) [190][ 20/108] eta: 0:00:17 time: 0.200691 data_time: 0.013486 memory: 1624 2023/08/09 19:08:11 - mmengine - INFO - Epoch(val) [190][ 30/108] eta: 0:00:15 time: 0.200758 data_time: 0.013524 memory: 1624 2023/08/09 19:08:13 - mmengine - INFO - Epoch(val) [190][ 40/108] eta: 0:00:13 time: 0.201294 data_time: 0.013915 memory: 1624 2023/08/09 19:08:15 - mmengine - INFO - Epoch(val) [190][ 50/108] eta: 0:00:11 time: 0.200250 data_time: 0.014291 memory: 1624 2023/08/09 19:08:17 - mmengine - INFO - Epoch(val) [190][ 60/108] eta: 0:00:09 time: 0.198229 data_time: 0.012679 memory: 1624 2023/08/09 19:08:19 - mmengine - INFO - Epoch(val) [190][ 70/108] eta: 0:00:07 time: 0.198385 data_time: 0.013003 memory: 1624 2023/08/09 19:08:21 - mmengine - INFO - Epoch(val) [190][ 80/108] eta: 0:00:05 time: 0.198692 data_time: 0.013253 memory: 1624 2023/08/09 19:08:23 - mmengine - INFO - Epoch(val) [190][ 90/108] eta: 0:00:03 time: 0.198441 data_time: 0.013130 memory: 1624 2023/08/09 19:08:25 - mmengine - INFO - Epoch(val) [190][100/108] eta: 0:00:01 time: 0.198422 data_time: 0.013131 memory: 1624 2023/08/09 19:08:27 - mmengine - INFO - Evaluating PCKAccuracy (normalized by ``"bbox_size"``)... 2023/08/09 19:08:27 - mmengine - INFO - Evaluating AUC... 2023/08/09 19:08:27 - mmengine - INFO - Evaluating EPE... 2023/08/09 19:08:28 - mmengine - INFO - Epoch(val) [190][108/108] PCK: 0.961801 AUC: 0.604008 EPE: 14.875853 data_time: 0.013478 time: 0.197523 2023/08/09 19:08:31 - mmengine - INFO - Epoch(train) [191][ 10/442] lr: 5.000000e-05 eta: 0:52:04 time: 0.358430 data_time: 0.035355 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.900614 2023/08/09 19:08:35 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:08:35 - mmengine - INFO - Epoch(train) [191][ 20/442] lr: 5.000000e-05 eta: 0:52:01 time: 0.356269 data_time: 0.038159 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.887210 2023/08/09 19:08:38 - mmengine - INFO - Epoch(train) [191][ 30/442] lr: 5.000000e-05 eta: 0:51:57 time: 0.357446 data_time: 0.038169 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.888020 2023/08/09 19:08:42 - mmengine - INFO - Epoch(train) [191][ 40/442] lr: 5.000000e-05 eta: 0:51:54 time: 0.357294 data_time: 0.038349 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.856983 2023/08/09 19:08:45 - mmengine - INFO - Epoch(train) [191][ 50/442] lr: 5.000000e-05 eta: 0:51:50 time: 0.355007 data_time: 0.038628 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.843808 2023/08/09 19:08:49 - mmengine - INFO - Epoch(train) [191][ 60/442] lr: 5.000000e-05 eta: 0:51:47 time: 0.348402 data_time: 0.034465 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.878019 2023/08/09 19:08:52 - mmengine - INFO - Epoch(train) [191][ 70/442] lr: 5.000000e-05 eta: 0:51:43 time: 0.345131 data_time: 0.031197 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.866458 2023/08/09 19:08:56 - mmengine - INFO - Epoch(train) [191][ 80/442] lr: 5.000000e-05 eta: 0:51:39 time: 0.344238 data_time: 0.031136 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.913319 2023/08/09 19:08:59 - mmengine - INFO - Epoch(train) [191][ 90/442] lr: 5.000000e-05 eta: 0:51:36 time: 0.348274 data_time: 0.031528 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.932063 2023/08/09 19:09:03 - mmengine - INFO - Epoch(train) [191][100/442] lr: 5.000000e-05 eta: 0:51:32 time: 0.351751 data_time: 0.032070 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.913023 2023/08/09 19:09:06 - mmengine - INFO - Epoch(train) [191][110/442] lr: 5.000000e-05 eta: 0:51:29 time: 0.351883 data_time: 0.032505 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.901868 2023/08/09 19:09:10 - mmengine - INFO - Epoch(train) [191][120/442] lr: 5.000000e-05 eta: 0:51:25 time: 0.349362 data_time: 0.033095 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.825765 2023/08/09 19:09:13 - mmengine - INFO - Epoch(train) [191][130/442] lr: 5.000000e-05 eta: 0:51:22 time: 0.348731 data_time: 0.033327 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.892233 2023/08/09 19:09:17 - mmengine - INFO - Epoch(train) [191][140/442] lr: 5.000000e-05 eta: 0:51:18 time: 0.345580 data_time: 0.033565 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.883978 2023/08/09 19:09:20 - mmengine - INFO - Epoch(train) [191][150/442] lr: 5.000000e-05 eta: 0:51:15 time: 0.342647 data_time: 0.033370 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.912423 2023/08/09 19:09:23 - mmengine - INFO - Epoch(train) [191][160/442] lr: 5.000000e-05 eta: 0:51:11 time: 0.342881 data_time: 0.032723 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.936201 2023/08/09 19:09:27 - mmengine - INFO - Epoch(train) [191][170/442] lr: 5.000000e-05 eta: 0:51:07 time: 0.342366 data_time: 0.032076 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.884050 2023/08/09 19:09:30 - mmengine - INFO - Epoch(train) [191][180/442] lr: 5.000000e-05 eta: 0:51:04 time: 0.344529 data_time: 0.034940 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.917199 2023/08/09 19:09:34 - mmengine - INFO - Epoch(train) [191][190/442] lr: 5.000000e-05 eta: 0:51:00 time: 0.344739 data_time: 0.034006 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.834921 2023/08/09 19:09:37 - mmengine - INFO - Epoch(train) [191][200/442] lr: 5.000000e-05 eta: 0:50:57 time: 0.345389 data_time: 0.034092 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.847194 2023/08/09 19:09:41 - mmengine - INFO - Epoch(train) [191][210/442] lr: 5.000000e-05 eta: 0:50:53 time: 0.344587 data_time: 0.034196 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.852049 2023/08/09 19:09:44 - mmengine - INFO - Epoch(train) [191][220/442] lr: 5.000000e-05 eta: 0:50:50 time: 0.346451 data_time: 0.034177 memory: 4565 loss: 0.000734 loss_kpt: 0.000734 acc_pose: 0.848714 2023/08/09 19:09:48 - mmengine - INFO - Epoch(train) [191][230/442] lr: 5.000000e-05 eta: 0:50:46 time: 0.348841 data_time: 0.031370 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.902162 2023/08/09 19:09:51 - mmengine - INFO - Epoch(train) [191][240/442] lr: 5.000000e-05 eta: 0:50:43 time: 0.348159 data_time: 0.031407 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.850551 2023/08/09 19:09:55 - mmengine - INFO - Epoch(train) [191][250/442] lr: 5.000000e-05 eta: 0:50:39 time: 0.347212 data_time: 0.031187 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.874492 2023/08/09 19:09:58 - mmengine - INFO - Epoch(train) [191][260/442] lr: 5.000000e-05 eta: 0:50:35 time: 0.347586 data_time: 0.031710 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.912104 2023/08/09 19:10:02 - mmengine - INFO - Epoch(train) [191][270/442] lr: 5.000000e-05 eta: 0:50:32 time: 0.347346 data_time: 0.031918 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.911490 2023/08/09 19:10:05 - mmengine - INFO - Epoch(train) [191][280/442] lr: 5.000000e-05 eta: 0:50:28 time: 0.342921 data_time: 0.031413 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.943998 2023/08/09 19:10:08 - mmengine - INFO - Epoch(train) [191][290/442] lr: 5.000000e-05 eta: 0:50:25 time: 0.344501 data_time: 0.032014 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.891983 2023/08/09 19:10:12 - mmengine - INFO - Epoch(train) [191][300/442] lr: 5.000000e-05 eta: 0:50:21 time: 0.345554 data_time: 0.032177 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.866328 2023/08/09 19:10:15 - mmengine - INFO - Epoch(train) [191][310/442] lr: 5.000000e-05 eta: 0:50:18 time: 0.344819 data_time: 0.031436 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.922467 2023/08/09 19:10:19 - mmengine - INFO - Epoch(train) [191][320/442] lr: 5.000000e-05 eta: 0:50:14 time: 0.343575 data_time: 0.031360 memory: 4565 loss: 0.000740 loss_kpt: 0.000740 acc_pose: 0.910729 2023/08/09 19:10:22 - mmengine - INFO - Epoch(train) [191][330/442] lr: 5.000000e-05 eta: 0:50:10 time: 0.342681 data_time: 0.031514 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.896953 2023/08/09 19:10:26 - mmengine - INFO - Epoch(train) [191][340/442] lr: 5.000000e-05 eta: 0:50:07 time: 0.344342 data_time: 0.034500 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.902401 2023/08/09 19:10:29 - mmengine - INFO - Epoch(train) [191][350/442] lr: 5.000000e-05 eta: 0:50:03 time: 0.346641 data_time: 0.034174 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.938319 2023/08/09 19:10:33 - mmengine - INFO - Epoch(train) [191][360/442] lr: 5.000000e-05 eta: 0:50:00 time: 0.349637 data_time: 0.034831 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.843581 2023/08/09 19:10:36 - mmengine - INFO - Epoch(train) [191][370/442] lr: 5.000000e-05 eta: 0:49:56 time: 0.353444 data_time: 0.035152 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.911149 2023/08/09 19:10:40 - mmengine - INFO - Epoch(train) [191][380/442] lr: 5.000000e-05 eta: 0:49:53 time: 0.355350 data_time: 0.035072 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.917757 2023/08/09 19:10:43 - mmengine - INFO - Epoch(train) [191][390/442] lr: 5.000000e-05 eta: 0:49:49 time: 0.353242 data_time: 0.031566 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.845538 2023/08/09 19:10:47 - mmengine - INFO - Epoch(train) [191][400/442] lr: 5.000000e-05 eta: 0:49:46 time: 0.351515 data_time: 0.031499 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.881577 2023/08/09 19:10:50 - mmengine - INFO - Epoch(train) [191][410/442] lr: 5.000000e-05 eta: 0:49:42 time: 0.350530 data_time: 0.030868 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.961278 2023/08/09 19:10:54 - mmengine - INFO - Epoch(train) [191][420/442] lr: 5.000000e-05 eta: 0:49:39 time: 0.350173 data_time: 0.030450 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.801512 2023/08/09 19:10:58 - mmengine - INFO - Epoch(train) [191][430/442] lr: 5.000000e-05 eta: 0:49:35 time: 0.352385 data_time: 0.030972 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.891117 2023/08/09 19:11:01 - mmengine - INFO - Epoch(train) [191][440/442] lr: 5.000000e-05 eta: 0:49:32 time: 0.353464 data_time: 0.031012 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.864530 2023/08/09 19:11:02 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:11:05 - mmengine - INFO - Epoch(train) [192][ 10/442] lr: 5.000000e-05 eta: 0:49:27 time: 0.355649 data_time: 0.034523 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.848164 2023/08/09 19:11:09 - mmengine - INFO - Epoch(train) [192][ 20/442] lr: 5.000000e-05 eta: 0:49:24 time: 0.355146 data_time: 0.034374 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.878418 2023/08/09 19:11:13 - mmengine - INFO - Epoch(train) [192][ 30/442] lr: 5.000000e-05 eta: 0:49:20 time: 0.359124 data_time: 0.034340 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.965415 2023/08/09 19:11:16 - mmengine - INFO - Epoch(train) [192][ 40/442] lr: 5.000000e-05 eta: 0:49:17 time: 0.357699 data_time: 0.033840 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.886458 2023/08/09 19:11:20 - mmengine - INFO - Epoch(train) [192][ 50/442] lr: 5.000000e-05 eta: 0:49:13 time: 0.362072 data_time: 0.035187 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.936392 2023/08/09 19:11:23 - mmengine - INFO - Epoch(train) [192][ 60/442] lr: 5.000000e-05 eta: 0:49:10 time: 0.359380 data_time: 0.032195 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.911138 2023/08/09 19:11:27 - mmengine - INFO - Epoch(train) [192][ 70/442] lr: 5.000000e-05 eta: 0:49:06 time: 0.363394 data_time: 0.032505 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.905235 2023/08/09 19:11:31 - mmengine - INFO - Epoch(train) [192][ 80/442] lr: 5.000000e-05 eta: 0:49:03 time: 0.358935 data_time: 0.032486 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.853670 2023/08/09 19:11:34 - mmengine - INFO - Epoch(train) [192][ 90/442] lr: 5.000000e-05 eta: 0:48:59 time: 0.359243 data_time: 0.032605 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.835674 2023/08/09 19:11:38 - mmengine - INFO - Epoch(train) [192][100/442] lr: 5.000000e-05 eta: 0:48:56 time: 0.356673 data_time: 0.032401 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.865114 2023/08/09 19:11:41 - mmengine - INFO - Epoch(train) [192][110/442] lr: 5.000000e-05 eta: 0:48:52 time: 0.356925 data_time: 0.031610 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.948592 2023/08/09 19:11:45 - mmengine - INFO - Epoch(train) [192][120/442] lr: 5.000000e-05 eta: 0:48:49 time: 0.357790 data_time: 0.032207 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.871909 2023/08/09 19:11:49 - mmengine - INFO - Epoch(train) [192][130/442] lr: 5.000000e-05 eta: 0:48:45 time: 0.359317 data_time: 0.033272 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.884820 2023/08/09 19:11:52 - mmengine - INFO - Epoch(train) [192][140/442] lr: 5.000000e-05 eta: 0:48:41 time: 0.357986 data_time: 0.033493 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.871348 2023/08/09 19:11:56 - mmengine - INFO - Epoch(train) [192][150/442] lr: 5.000000e-05 eta: 0:48:38 time: 0.358399 data_time: 0.033092 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.893668 2023/08/09 19:11:59 - mmengine - INFO - Epoch(train) [192][160/442] lr: 5.000000e-05 eta: 0:48:34 time: 0.358103 data_time: 0.033538 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.971145 2023/08/09 19:12:03 - mmengine - INFO - Epoch(train) [192][170/442] lr: 5.000000e-05 eta: 0:48:31 time: 0.358871 data_time: 0.034085 memory: 4565 loss: 0.000747 loss_kpt: 0.000747 acc_pose: 0.891073 2023/08/09 19:12:07 - mmengine - INFO - Epoch(train) [192][180/442] lr: 5.000000e-05 eta: 0:48:27 time: 0.358438 data_time: 0.033476 memory: 4565 loss: 0.000745 loss_kpt: 0.000745 acc_pose: 0.894524 2023/08/09 19:12:10 - mmengine - INFO - Epoch(train) [192][190/442] lr: 5.000000e-05 eta: 0:48:24 time: 0.360855 data_time: 0.033404 memory: 4565 loss: 0.000735 loss_kpt: 0.000735 acc_pose: 0.889311 2023/08/09 19:12:14 - mmengine - INFO - Epoch(train) [192][200/442] lr: 5.000000e-05 eta: 0:48:20 time: 0.360125 data_time: 0.033104 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.877803 2023/08/09 19:12:17 - mmengine - INFO - Epoch(train) [192][210/442] lr: 5.000000e-05 eta: 0:48:17 time: 0.358882 data_time: 0.032836 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.898172 2023/08/09 19:12:21 - mmengine - INFO - Epoch(train) [192][220/442] lr: 5.000000e-05 eta: 0:48:13 time: 0.354757 data_time: 0.031635 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.860637 2023/08/09 19:12:24 - mmengine - INFO - Epoch(train) [192][230/442] lr: 5.000000e-05 eta: 0:48:10 time: 0.354444 data_time: 0.031504 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.862266 2023/08/09 19:12:28 - mmengine - INFO - Epoch(train) [192][240/442] lr: 5.000000e-05 eta: 0:48:06 time: 0.354270 data_time: 0.031695 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.890841 2023/08/09 19:12:31 - mmengine - INFO - Epoch(train) [192][250/442] lr: 5.000000e-05 eta: 0:48:03 time: 0.355869 data_time: 0.031924 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.929879 2023/08/09 19:12:35 - mmengine - INFO - Epoch(train) [192][260/442] lr: 5.000000e-05 eta: 0:47:59 time: 0.357771 data_time: 0.031709 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.839557 2023/08/09 19:12:39 - mmengine - INFO - Epoch(train) [192][270/442] lr: 5.000000e-05 eta: 0:47:56 time: 0.359326 data_time: 0.034691 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.925409 2023/08/09 19:12:42 - mmengine - INFO - Epoch(train) [192][280/442] lr: 5.000000e-05 eta: 0:47:52 time: 0.357801 data_time: 0.034315 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.893090 2023/08/09 19:12:46 - mmengine - INFO - Epoch(train) [192][290/442] lr: 5.000000e-05 eta: 0:47:49 time: 0.356132 data_time: 0.033931 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.866907 2023/08/09 19:12:49 - mmengine - INFO - Epoch(train) [192][300/442] lr: 5.000000e-05 eta: 0:47:45 time: 0.357611 data_time: 0.033845 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.877028 2023/08/09 19:12:53 - mmengine - INFO - Epoch(train) [192][310/442] lr: 5.000000e-05 eta: 0:47:41 time: 0.356927 data_time: 0.034036 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.898146 2023/08/09 19:12:56 - mmengine - INFO - Epoch(train) [192][320/442] lr: 5.000000e-05 eta: 0:47:38 time: 0.355954 data_time: 0.031135 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.892849 2023/08/09 19:13:00 - mmengine - INFO - Epoch(train) [192][330/442] lr: 5.000000e-05 eta: 0:47:34 time: 0.356677 data_time: 0.031449 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.883407 2023/08/09 19:13:04 - mmengine - INFO - Epoch(train) [192][340/442] lr: 5.000000e-05 eta: 0:47:31 time: 0.356836 data_time: 0.031425 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.884885 2023/08/09 19:13:07 - mmengine - INFO - Epoch(train) [192][350/442] lr: 5.000000e-05 eta: 0:47:27 time: 0.353286 data_time: 0.031279 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.895417 2023/08/09 19:13:11 - mmengine - INFO - Epoch(train) [192][360/442] lr: 5.000000e-05 eta: 0:47:24 time: 0.352090 data_time: 0.031163 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.850066 2023/08/09 19:13:14 - mmengine - INFO - Epoch(train) [192][370/442] lr: 5.000000e-05 eta: 0:47:20 time: 0.351353 data_time: 0.031194 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.879759 2023/08/09 19:13:18 - mmengine - INFO - Epoch(train) [192][380/442] lr: 5.000000e-05 eta: 0:47:17 time: 0.351701 data_time: 0.031124 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.906205 2023/08/09 19:13:21 - mmengine - INFO - Epoch(train) [192][390/442] lr: 5.000000e-05 eta: 0:47:13 time: 0.354726 data_time: 0.031476 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.882711 2023/08/09 19:13:25 - mmengine - INFO - Epoch(train) [192][400/442] lr: 5.000000e-05 eta: 0:47:10 time: 0.355029 data_time: 0.031409 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.899743 2023/08/09 19:13:28 - mmengine - INFO - Epoch(train) [192][410/442] lr: 5.000000e-05 eta: 0:47:06 time: 0.354930 data_time: 0.031342 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.913043 2023/08/09 19:13:32 - mmengine - INFO - Epoch(train) [192][420/442] lr: 5.000000e-05 eta: 0:47:03 time: 0.353950 data_time: 0.031111 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.906349 2023/08/09 19:13:35 - mmengine - INFO - Epoch(train) [192][430/442] lr: 5.000000e-05 eta: 0:46:59 time: 0.352667 data_time: 0.031031 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.947798 2023/08/09 19:13:39 - mmengine - INFO - Epoch(train) [192][440/442] lr: 5.000000e-05 eta: 0:46:55 time: 0.352854 data_time: 0.030870 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.882586 2023/08/09 19:13:40 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:13:43 - mmengine - INFO - Epoch(train) [193][ 10/442] lr: 5.000000e-05 eta: 0:46:51 time: 0.357280 data_time: 0.034769 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.912771 2023/08/09 19:13:47 - mmengine - INFO - Epoch(train) [193][ 20/442] lr: 5.000000e-05 eta: 0:46:48 time: 0.359075 data_time: 0.035089 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.930699 2023/08/09 19:13:50 - mmengine - INFO - Epoch(train) [193][ 30/442] lr: 5.000000e-05 eta: 0:46:44 time: 0.357233 data_time: 0.035212 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.862920 2023/08/09 19:13:54 - mmengine - INFO - Epoch(train) [193][ 40/442] lr: 5.000000e-05 eta: 0:46:41 time: 0.355318 data_time: 0.035146 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.898247 2023/08/09 19:13:57 - mmengine - INFO - Epoch(train) [193][ 50/442] lr: 5.000000e-05 eta: 0:46:37 time: 0.351815 data_time: 0.035124 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.893931 2023/08/09 19:14:01 - mmengine - INFO - Epoch(train) [193][ 60/442] lr: 5.000000e-05 eta: 0:46:33 time: 0.344955 data_time: 0.031074 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.823821 2023/08/09 19:14:04 - mmengine - INFO - Epoch(train) [193][ 70/442] lr: 5.000000e-05 eta: 0:46:30 time: 0.342359 data_time: 0.031063 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.878941 2023/08/09 19:14:08 - mmengine - INFO - Epoch(train) [193][ 80/442] lr: 5.000000e-05 eta: 0:46:26 time: 0.344215 data_time: 0.031381 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.865314 2023/08/09 19:14:11 - mmengine - INFO - Epoch(train) [193][ 90/442] lr: 5.000000e-05 eta: 0:46:23 time: 0.343290 data_time: 0.031310 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.829603 2023/08/09 19:14:14 - mmengine - INFO - Epoch(train) [193][100/442] lr: 5.000000e-05 eta: 0:46:19 time: 0.343221 data_time: 0.031482 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.884857 2023/08/09 19:14:18 - mmengine - INFO - Epoch(train) [193][110/442] lr: 5.000000e-05 eta: 0:46:16 time: 0.342907 data_time: 0.031484 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.850839 2023/08/09 19:14:21 - mmengine - INFO - Epoch(train) [193][120/442] lr: 5.000000e-05 eta: 0:46:12 time: 0.342170 data_time: 0.031138 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.839486 2023/08/09 19:14:25 - mmengine - INFO - Epoch(train) [193][130/442] lr: 5.000000e-05 eta: 0:46:09 time: 0.342012 data_time: 0.030906 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.832597 2023/08/09 19:14:27 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:14:28 - mmengine - INFO - Epoch(train) [193][140/442] lr: 5.000000e-05 eta: 0:46:05 time: 0.345094 data_time: 0.031065 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.865920 2023/08/09 19:14:32 - mmengine - INFO - Epoch(train) [193][150/442] lr: 5.000000e-05 eta: 0:46:01 time: 0.345792 data_time: 0.031134 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.839050 2023/08/09 19:14:35 - mmengine - INFO - Epoch(train) [193][160/442] lr: 5.000000e-05 eta: 0:45:58 time: 0.345635 data_time: 0.031157 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.956249 2023/08/09 19:14:38 - mmengine - INFO - Epoch(train) [193][170/442] lr: 5.000000e-05 eta: 0:45:54 time: 0.345090 data_time: 0.031122 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.884171 2023/08/09 19:14:42 - mmengine - INFO - Epoch(train) [193][180/442] lr: 5.000000e-05 eta: 0:45:51 time: 0.344717 data_time: 0.031046 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.803503 2023/08/09 19:14:45 - mmengine - INFO - Epoch(train) [193][190/442] lr: 5.000000e-05 eta: 0:45:47 time: 0.342700 data_time: 0.030916 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.902597 2023/08/09 19:14:49 - mmengine - INFO - Epoch(train) [193][200/442] lr: 5.000000e-05 eta: 0:45:44 time: 0.345486 data_time: 0.030888 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.876905 2023/08/09 19:14:53 - mmengine - INFO - Epoch(train) [193][210/442] lr: 5.000000e-05 eta: 0:45:40 time: 0.350565 data_time: 0.034294 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.923488 2023/08/09 19:14:56 - mmengine - INFO - Epoch(train) [193][220/442] lr: 5.000000e-05 eta: 0:45:37 time: 0.352299 data_time: 0.034712 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.929157 2023/08/09 19:15:00 - mmengine - INFO - Epoch(train) [193][230/442] lr: 5.000000e-05 eta: 0:45:33 time: 0.354351 data_time: 0.034842 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.944049 2023/08/09 19:15:04 - mmengine - INFO - Epoch(train) [193][240/442] lr: 5.000000e-05 eta: 0:45:30 time: 0.362638 data_time: 0.035084 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.959768 2023/08/09 19:15:07 - mmengine - INFO - Epoch(train) [193][250/442] lr: 5.000000e-05 eta: 0:45:26 time: 0.359061 data_time: 0.035802 memory: 4565 loss: 0.000682 loss_kpt: 0.000682 acc_pose: 0.903027 2023/08/09 19:15:10 - mmengine - INFO - Epoch(train) [193][260/442] lr: 5.000000e-05 eta: 0:45:22 time: 0.355170 data_time: 0.033327 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.808561 2023/08/09 19:15:14 - mmengine - INFO - Epoch(train) [193][270/442] lr: 5.000000e-05 eta: 0:45:19 time: 0.354490 data_time: 0.033143 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.926570 2023/08/09 19:15:17 - mmengine - INFO - Epoch(train) [193][280/442] lr: 5.000000e-05 eta: 0:45:15 time: 0.352591 data_time: 0.033189 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.828373 2023/08/09 19:15:21 - mmengine - INFO - Epoch(train) [193][290/442] lr: 5.000000e-05 eta: 0:45:12 time: 0.344760 data_time: 0.032943 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.875664 2023/08/09 19:15:24 - mmengine - INFO - Epoch(train) [193][300/442] lr: 5.000000e-05 eta: 0:45:08 time: 0.344399 data_time: 0.031948 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.874343 2023/08/09 19:15:28 - mmengine - INFO - Epoch(train) [193][310/442] lr: 5.000000e-05 eta: 0:45:05 time: 0.343657 data_time: 0.030976 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.867329 2023/08/09 19:15:31 - mmengine - INFO - Epoch(train) [193][320/442] lr: 5.000000e-05 eta: 0:45:01 time: 0.343622 data_time: 0.030667 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.858586 2023/08/09 19:15:34 - mmengine - INFO - Epoch(train) [193][330/442] lr: 5.000000e-05 eta: 0:44:58 time: 0.342198 data_time: 0.030410 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.844793 2023/08/09 19:15:38 - mmengine - INFO - Epoch(train) [193][340/442] lr: 5.000000e-05 eta: 0:44:54 time: 0.342105 data_time: 0.030454 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.912955 2023/08/09 19:15:41 - mmengine - INFO - Epoch(train) [193][350/442] lr: 5.000000e-05 eta: 0:44:50 time: 0.345780 data_time: 0.031042 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.918017 2023/08/09 19:15:45 - mmengine - INFO - Epoch(train) [193][360/442] lr: 5.000000e-05 eta: 0:44:47 time: 0.345980 data_time: 0.030919 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.905746 2023/08/09 19:15:48 - mmengine - INFO - Epoch(train) [193][370/442] lr: 5.000000e-05 eta: 0:44:43 time: 0.348219 data_time: 0.030955 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.852077 2023/08/09 19:15:52 - mmengine - INFO - Epoch(train) [193][380/442] lr: 5.000000e-05 eta: 0:44:40 time: 0.348307 data_time: 0.031003 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.928067 2023/08/09 19:15:55 - mmengine - INFO - Epoch(train) [193][390/442] lr: 5.000000e-05 eta: 0:44:36 time: 0.347990 data_time: 0.031116 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.789823 2023/08/09 19:15:59 - mmengine - INFO - Epoch(train) [193][400/442] lr: 5.000000e-05 eta: 0:44:33 time: 0.348588 data_time: 0.030780 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.884006 2023/08/09 19:16:02 - mmengine - INFO - Epoch(train) [193][410/442] lr: 5.000000e-05 eta: 0:44:29 time: 0.349253 data_time: 0.031187 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.847630 2023/08/09 19:16:06 - mmengine - INFO - Epoch(train) [193][420/442] lr: 5.000000e-05 eta: 0:44:26 time: 0.347786 data_time: 0.031272 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.928395 2023/08/09 19:16:09 - mmengine - INFO - Epoch(train) [193][430/442] lr: 5.000000e-05 eta: 0:44:22 time: 0.347302 data_time: 0.031241 memory: 4565 loss: 0.000678 loss_kpt: 0.000678 acc_pose: 0.917934 2023/08/09 19:16:13 - mmengine - INFO - Epoch(train) [193][440/442] lr: 5.000000e-05 eta: 0:44:18 time: 0.346047 data_time: 0.031017 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.899002 2023/08/09 19:16:13 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:16:17 - mmengine - INFO - Epoch(train) [194][ 10/442] lr: 5.000000e-05 eta: 0:44:14 time: 0.345008 data_time: 0.034204 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.908058 2023/08/09 19:16:20 - mmengine - INFO - Epoch(train) [194][ 20/442] lr: 5.000000e-05 eta: 0:44:11 time: 0.343785 data_time: 0.033828 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.878221 2023/08/09 19:16:24 - mmengine - INFO - Epoch(train) [194][ 30/442] lr: 5.000000e-05 eta: 0:44:07 time: 0.343902 data_time: 0.033907 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.914559 2023/08/09 19:16:27 - mmengine - INFO - Epoch(train) [194][ 40/442] lr: 5.000000e-05 eta: 0:44:04 time: 0.346627 data_time: 0.034311 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.885613 2023/08/09 19:16:31 - mmengine - INFO - Epoch(train) [194][ 50/442] lr: 5.000000e-05 eta: 0:44:00 time: 0.349103 data_time: 0.034757 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.851927 2023/08/09 19:16:34 - mmengine - INFO - Epoch(train) [194][ 60/442] lr: 5.000000e-05 eta: 0:43:56 time: 0.344415 data_time: 0.031144 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.894816 2023/08/09 19:16:38 - mmengine - INFO - Epoch(train) [194][ 70/442] lr: 5.000000e-05 eta: 0:43:53 time: 0.343556 data_time: 0.031478 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.881412 2023/08/09 19:16:41 - mmengine - INFO - Epoch(train) [194][ 80/442] lr: 5.000000e-05 eta: 0:43:49 time: 0.343241 data_time: 0.031405 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.841541 2023/08/09 19:16:44 - mmengine - INFO - Epoch(train) [194][ 90/442] lr: 5.000000e-05 eta: 0:43:46 time: 0.341959 data_time: 0.031234 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.881606 2023/08/09 19:16:48 - mmengine - INFO - Epoch(train) [194][100/442] lr: 5.000000e-05 eta: 0:43:42 time: 0.345247 data_time: 0.031332 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.894188 2023/08/09 19:16:51 - mmengine - INFO - Epoch(train) [194][110/442] lr: 5.000000e-05 eta: 0:43:39 time: 0.347390 data_time: 0.031591 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.919433 2023/08/09 19:16:55 - mmengine - INFO - Epoch(train) [194][120/442] lr: 5.000000e-05 eta: 0:43:35 time: 0.349739 data_time: 0.031512 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.886477 2023/08/09 19:16:58 - mmengine - INFO - Epoch(train) [194][130/442] lr: 5.000000e-05 eta: 0:43:32 time: 0.350041 data_time: 0.031402 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.904035 2023/08/09 19:17:02 - mmengine - INFO - Epoch(train) [194][140/442] lr: 5.000000e-05 eta: 0:43:28 time: 0.349407 data_time: 0.031309 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.926315 2023/08/09 19:17:05 - mmengine - INFO - Epoch(train) [194][150/442] lr: 5.000000e-05 eta: 0:43:25 time: 0.347469 data_time: 0.031267 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.886335 2023/08/09 19:17:09 - mmengine - INFO - Epoch(train) [194][160/442] lr: 5.000000e-05 eta: 0:43:21 time: 0.346403 data_time: 0.031280 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.874129 2023/08/09 19:17:12 - mmengine - INFO - Epoch(train) [194][170/442] lr: 5.000000e-05 eta: 0:43:17 time: 0.345023 data_time: 0.031018 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.890926 2023/08/09 19:17:16 - mmengine - INFO - Epoch(train) [194][180/442] lr: 5.000000e-05 eta: 0:43:14 time: 0.345626 data_time: 0.031291 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.876759 2023/08/09 19:17:19 - mmengine - INFO - Epoch(train) [194][190/442] lr: 5.000000e-05 eta: 0:43:10 time: 0.345763 data_time: 0.031290 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.870952 2023/08/09 19:17:23 - mmengine - INFO - Epoch(train) [194][200/442] lr: 5.000000e-05 eta: 0:43:07 time: 0.346195 data_time: 0.034423 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.912288 2023/08/09 19:17:26 - mmengine - INFO - Epoch(train) [194][210/442] lr: 5.000000e-05 eta: 0:43:03 time: 0.345397 data_time: 0.034126 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.909923 2023/08/09 19:17:30 - mmengine - INFO - Epoch(train) [194][220/442] lr: 5.000000e-05 eta: 0:43:00 time: 0.347449 data_time: 0.034132 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.837500 2023/08/09 19:17:33 - mmengine - INFO - Epoch(train) [194][230/442] lr: 5.000000e-05 eta: 0:42:56 time: 0.346751 data_time: 0.033965 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.884254 2023/08/09 19:17:37 - mmengine - INFO - Epoch(train) [194][240/442] lr: 5.000000e-05 eta: 0:42:53 time: 0.347449 data_time: 0.034419 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.833035 2023/08/09 19:17:40 - mmengine - INFO - Epoch(train) [194][250/442] lr: 5.000000e-05 eta: 0:42:49 time: 0.345909 data_time: 0.032121 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.894084 2023/08/09 19:17:43 - mmengine - INFO - Epoch(train) [194][260/442] lr: 5.000000e-05 eta: 0:42:45 time: 0.345905 data_time: 0.032931 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.863835 2023/08/09 19:17:47 - mmengine - INFO - Epoch(train) [194][270/442] lr: 5.000000e-05 eta: 0:42:42 time: 0.343080 data_time: 0.033783 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.910848 2023/08/09 19:17:50 - mmengine - INFO - Epoch(train) [194][280/442] lr: 5.000000e-05 eta: 0:42:38 time: 0.342907 data_time: 0.034486 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.903188 2023/08/09 19:17:54 - mmengine - INFO - Epoch(train) [194][290/442] lr: 5.000000e-05 eta: 0:42:35 time: 0.342434 data_time: 0.034452 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.896341 2023/08/09 19:17:57 - mmengine - INFO - Epoch(train) [194][300/442] lr: 5.000000e-05 eta: 0:42:31 time: 0.342058 data_time: 0.034126 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.932476 2023/08/09 19:18:01 - mmengine - INFO - Epoch(train) [194][310/442] lr: 5.000000e-05 eta: 0:42:28 time: 0.342920 data_time: 0.033541 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.889220 2023/08/09 19:18:04 - mmengine - INFO - Epoch(train) [194][320/442] lr: 5.000000e-05 eta: 0:42:24 time: 0.343549 data_time: 0.033033 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.907784 2023/08/09 19:18:07 - mmengine - INFO - Epoch(train) [194][330/442] lr: 5.000000e-05 eta: 0:42:20 time: 0.342204 data_time: 0.032240 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.894417 2023/08/09 19:18:11 - mmengine - INFO - Epoch(train) [194][340/442] lr: 5.000000e-05 eta: 0:42:17 time: 0.343507 data_time: 0.031670 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.907917 2023/08/09 19:18:14 - mmengine - INFO - Epoch(train) [194][350/442] lr: 5.000000e-05 eta: 0:42:13 time: 0.343382 data_time: 0.030830 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.889201 2023/08/09 19:18:18 - mmengine - INFO - Epoch(train) [194][360/442] lr: 5.000000e-05 eta: 0:42:10 time: 0.343372 data_time: 0.030669 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.890795 2023/08/09 19:18:21 - mmengine - INFO - Epoch(train) [194][370/442] lr: 5.000000e-05 eta: 0:42:06 time: 0.345390 data_time: 0.030916 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.900007 2023/08/09 19:18:25 - mmengine - INFO - Epoch(train) [194][380/442] lr: 5.000000e-05 eta: 0:42:03 time: 0.347125 data_time: 0.031537 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.864297 2023/08/09 19:18:28 - mmengine - INFO - Epoch(train) [194][390/442] lr: 5.000000e-05 eta: 0:41:59 time: 0.346564 data_time: 0.032171 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.838472 2023/08/09 19:18:32 - mmengine - INFO - Epoch(train) [194][400/442] lr: 5.000000e-05 eta: 0:41:56 time: 0.344987 data_time: 0.032413 memory: 4565 loss: 0.000744 loss_kpt: 0.000744 acc_pose: 0.885514 2023/08/09 19:18:35 - mmengine - INFO - Epoch(train) [194][410/442] lr: 5.000000e-05 eta: 0:41:52 time: 0.344416 data_time: 0.032336 memory: 4565 loss: 0.000741 loss_kpt: 0.000741 acc_pose: 0.910475 2023/08/09 19:18:38 - mmengine - INFO - Epoch(train) [194][420/442] lr: 5.000000e-05 eta: 0:41:49 time: 0.342541 data_time: 0.031831 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.919680 2023/08/09 19:18:42 - mmengine - INFO - Epoch(train) [194][430/442] lr: 5.000000e-05 eta: 0:41:45 time: 0.346627 data_time: 0.034481 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.859520 2023/08/09 19:18:46 - mmengine - INFO - Epoch(train) [194][440/442] lr: 5.000000e-05 eta: 0:41:41 time: 0.347536 data_time: 0.034054 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.880802 2023/08/09 19:18:46 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:18:50 - mmengine - INFO - Epoch(train) [195][ 10/442] lr: 5.000000e-05 eta: 0:41:37 time: 0.358284 data_time: 0.037884 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.863393 2023/08/09 19:18:54 - mmengine - INFO - Epoch(train) [195][ 20/442] lr: 5.000000e-05 eta: 0:41:34 time: 0.367571 data_time: 0.038102 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.837647 2023/08/09 19:18:58 - mmengine - INFO - Epoch(train) [195][ 30/442] lr: 5.000000e-05 eta: 0:41:30 time: 0.370959 data_time: 0.038243 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.877608 2023/08/09 19:19:01 - mmengine - INFO - Epoch(train) [195][ 40/442] lr: 5.000000e-05 eta: 0:41:27 time: 0.367706 data_time: 0.035722 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.932592 2023/08/09 19:19:05 - mmengine - INFO - Epoch(train) [195][ 50/442] lr: 5.000000e-05 eta: 0:41:23 time: 0.368884 data_time: 0.035855 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.932735 2023/08/09 19:19:08 - mmengine - INFO - Epoch(train) [195][ 60/442] lr: 5.000000e-05 eta: 0:41:20 time: 0.361686 data_time: 0.031958 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.909708 2023/08/09 19:19:12 - mmengine - INFO - Epoch(train) [195][ 70/442] lr: 5.000000e-05 eta: 0:41:16 time: 0.354780 data_time: 0.032117 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.886952 2023/08/09 19:19:15 - mmengine - INFO - Epoch(train) [195][ 80/442] lr: 5.000000e-05 eta: 0:41:13 time: 0.353381 data_time: 0.031870 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.941053 2023/08/09 19:19:19 - mmengine - INFO - Epoch(train) [195][ 90/442] lr: 5.000000e-05 eta: 0:41:09 time: 0.353107 data_time: 0.031186 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.857439 2023/08/09 19:19:22 - mmengine - INFO - Epoch(train) [195][100/442] lr: 5.000000e-05 eta: 0:41:06 time: 0.353401 data_time: 0.031157 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.872126 2023/08/09 19:19:26 - mmengine - INFO - Epoch(train) [195][110/442] lr: 5.000000e-05 eta: 0:41:02 time: 0.351466 data_time: 0.031013 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.902289 2023/08/09 19:19:29 - mmengine - INFO - Epoch(train) [195][120/442] lr: 5.000000e-05 eta: 0:40:58 time: 0.351076 data_time: 0.030653 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.883264 2023/08/09 19:19:33 - mmengine - INFO - Epoch(train) [195][130/442] lr: 5.000000e-05 eta: 0:40:55 time: 0.352268 data_time: 0.030899 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.878928 2023/08/09 19:19:37 - mmengine - INFO - Epoch(train) [195][140/442] lr: 5.000000e-05 eta: 0:40:51 time: 0.353861 data_time: 0.031081 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.934701 2023/08/09 19:19:40 - mmengine - INFO - Epoch(train) [195][150/442] lr: 5.000000e-05 eta: 0:40:48 time: 0.354897 data_time: 0.031340 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.880951 2023/08/09 19:19:44 - mmengine - INFO - Epoch(train) [195][160/442] lr: 5.000000e-05 eta: 0:40:44 time: 0.359356 data_time: 0.031641 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.885516 2023/08/09 19:19:48 - mmengine - INFO - Epoch(train) [195][170/442] lr: 5.000000e-05 eta: 0:40:41 time: 0.363447 data_time: 0.031790 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.906857 2023/08/09 19:19:51 - mmengine - INFO - Epoch(train) [195][180/442] lr: 5.000000e-05 eta: 0:40:37 time: 0.366206 data_time: 0.031661 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.943235 2023/08/09 19:19:55 - mmengine - INFO - Epoch(train) [195][190/442] lr: 5.000000e-05 eta: 0:40:34 time: 0.367386 data_time: 0.031686 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.904512 2023/08/09 19:19:59 - mmengine - INFO - Epoch(train) [195][200/442] lr: 5.000000e-05 eta: 0:40:30 time: 0.367977 data_time: 0.031869 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.888018 2023/08/09 19:20:02 - mmengine - INFO - Epoch(train) [195][210/442] lr: 5.000000e-05 eta: 0:40:27 time: 0.366755 data_time: 0.031977 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.908606 2023/08/09 19:20:06 - mmengine - INFO - Epoch(train) [195][220/442] lr: 5.000000e-05 eta: 0:40:23 time: 0.362958 data_time: 0.031797 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.926847 2023/08/09 19:20:09 - mmengine - INFO - Epoch(train) [195][230/442] lr: 5.000000e-05 eta: 0:40:20 time: 0.358307 data_time: 0.031754 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.864651 2023/08/09 19:20:13 - mmengine - INFO - Epoch(train) [195][240/442] lr: 5.000000e-05 eta: 0:40:16 time: 0.357478 data_time: 0.031544 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.906749 2023/08/09 19:20:16 - mmengine - INFO - Epoch(train) [195][250/442] lr: 5.000000e-05 eta: 0:40:13 time: 0.357151 data_time: 0.031150 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.896997 2023/08/09 19:20:17 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:20:20 - mmengine - INFO - Epoch(train) [195][260/442] lr: 5.000000e-05 eta: 0:40:09 time: 0.356144 data_time: 0.031160 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.900447 2023/08/09 19:20:24 - mmengine - INFO - Epoch(train) [195][270/442] lr: 5.000000e-05 eta: 0:40:06 time: 0.356919 data_time: 0.031311 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.878267 2023/08/09 19:20:27 - mmengine - INFO - Epoch(train) [195][280/442] lr: 5.000000e-05 eta: 0:40:02 time: 0.356934 data_time: 0.031442 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.855868 2023/08/09 19:20:31 - mmengine - INFO - Epoch(train) [195][290/442] lr: 5.000000e-05 eta: 0:39:58 time: 0.355092 data_time: 0.031639 memory: 4565 loss: 0.000743 loss_kpt: 0.000743 acc_pose: 0.876351 2023/08/09 19:20:34 - mmengine - INFO - Epoch(train) [195][300/442] lr: 5.000000e-05 eta: 0:39:55 time: 0.354320 data_time: 0.031748 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.881287 2023/08/09 19:20:38 - mmengine - INFO - Epoch(train) [195][310/442] lr: 5.000000e-05 eta: 0:39:51 time: 0.354489 data_time: 0.031456 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.880379 2023/08/09 19:20:41 - mmengine - INFO - Epoch(train) [195][320/442] lr: 5.000000e-05 eta: 0:39:48 time: 0.354566 data_time: 0.031535 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.861957 2023/08/09 19:20:45 - mmengine - INFO - Epoch(train) [195][330/442] lr: 5.000000e-05 eta: 0:39:44 time: 0.358481 data_time: 0.031524 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.836802 2023/08/09 19:20:49 - mmengine - INFO - Epoch(train) [195][340/442] lr: 5.000000e-05 eta: 0:39:41 time: 0.360972 data_time: 0.031569 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.840137 2023/08/09 19:20:52 - mmengine - INFO - Epoch(train) [195][350/442] lr: 5.000000e-05 eta: 0:39:37 time: 0.361498 data_time: 0.031495 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.903682 2023/08/09 19:20:56 - mmengine - INFO - Epoch(train) [195][360/442] lr: 5.000000e-05 eta: 0:39:34 time: 0.359179 data_time: 0.031465 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.905984 2023/08/09 19:20:59 - mmengine - INFO - Epoch(train) [195][370/442] lr: 5.000000e-05 eta: 0:39:30 time: 0.357808 data_time: 0.031247 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.935710 2023/08/09 19:21:03 - mmengine - INFO - Epoch(train) [195][380/442] lr: 5.000000e-05 eta: 0:39:27 time: 0.353978 data_time: 0.031331 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.828360 2023/08/09 19:21:06 - mmengine - INFO - Epoch(train) [195][390/442] lr: 5.000000e-05 eta: 0:39:23 time: 0.354841 data_time: 0.031605 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.846360 2023/08/09 19:21:10 - mmengine - INFO - Epoch(train) [195][400/442] lr: 5.000000e-05 eta: 0:39:20 time: 0.354515 data_time: 0.031665 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.916458 2023/08/09 19:21:14 - mmengine - INFO - Epoch(train) [195][410/442] lr: 5.000000e-05 eta: 0:39:16 time: 0.356743 data_time: 0.031718 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.895672 2023/08/09 19:21:17 - mmengine - INFO - Epoch(train) [195][420/442] lr: 5.000000e-05 eta: 0:39:13 time: 0.360379 data_time: 0.034780 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.929230 2023/08/09 19:21:21 - mmengine - INFO - Epoch(train) [195][430/442] lr: 5.000000e-05 eta: 0:39:09 time: 0.359519 data_time: 0.034506 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.889676 2023/08/09 19:21:24 - mmengine - INFO - Epoch(train) [195][440/442] lr: 5.000000e-05 eta: 0:39:06 time: 0.355659 data_time: 0.034044 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.919655 2023/08/09 19:21:25 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:21:29 - mmengine - INFO - Epoch(train) [196][ 10/442] lr: 5.000000e-05 eta: 0:39:01 time: 0.356151 data_time: 0.038120 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.928894 2023/08/09 19:21:32 - mmengine - INFO - Epoch(train) [196][ 20/442] lr: 5.000000e-05 eta: 0:38:58 time: 0.353690 data_time: 0.038025 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.851613 2023/08/09 19:21:36 - mmengine - INFO - Epoch(train) [196][ 30/442] lr: 5.000000e-05 eta: 0:38:54 time: 0.353072 data_time: 0.035371 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.958245 2023/08/09 19:21:39 - mmengine - INFO - Epoch(train) [196][ 40/442] lr: 5.000000e-05 eta: 0:38:51 time: 0.358351 data_time: 0.035794 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.908347 2023/08/09 19:21:43 - mmengine - INFO - Epoch(train) [196][ 50/442] lr: 5.000000e-05 eta: 0:38:47 time: 0.358234 data_time: 0.036481 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.862480 2023/08/09 19:21:46 - mmengine - INFO - Epoch(train) [196][ 60/442] lr: 5.000000e-05 eta: 0:38:44 time: 0.352533 data_time: 0.032296 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.913263 2023/08/09 19:21:50 - mmengine - INFO - Epoch(train) [196][ 70/442] lr: 5.000000e-05 eta: 0:38:40 time: 0.352879 data_time: 0.032206 memory: 4565 loss: 0.000729 loss_kpt: 0.000729 acc_pose: 0.864891 2023/08/09 19:21:53 - mmengine - INFO - Epoch(train) [196][ 80/442] lr: 5.000000e-05 eta: 0:38:36 time: 0.349313 data_time: 0.031794 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.860454 2023/08/09 19:21:57 - mmengine - INFO - Epoch(train) [196][ 90/442] lr: 5.000000e-05 eta: 0:38:33 time: 0.343388 data_time: 0.031774 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.892642 2023/08/09 19:22:00 - mmengine - INFO - Epoch(train) [196][100/442] lr: 5.000000e-05 eta: 0:38:29 time: 0.345284 data_time: 0.031878 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.848893 2023/08/09 19:22:04 - mmengine - INFO - Epoch(train) [196][110/442] lr: 5.000000e-05 eta: 0:38:26 time: 0.347652 data_time: 0.031421 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.819430 2023/08/09 19:22:07 - mmengine - INFO - Epoch(train) [196][120/442] lr: 5.000000e-05 eta: 0:38:22 time: 0.346212 data_time: 0.031396 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.960599 2023/08/09 19:22:10 - mmengine - INFO - Epoch(train) [196][130/442] lr: 5.000000e-05 eta: 0:38:19 time: 0.345017 data_time: 0.031406 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.921212 2023/08/09 19:22:14 - mmengine - INFO - Epoch(train) [196][140/442] lr: 5.000000e-05 eta: 0:38:15 time: 0.345531 data_time: 0.031080 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.880846 2023/08/09 19:22:18 - mmengine - INFO - Epoch(train) [196][150/442] lr: 5.000000e-05 eta: 0:38:12 time: 0.349553 data_time: 0.034797 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.802832 2023/08/09 19:22:21 - mmengine - INFO - Epoch(train) [196][160/442] lr: 5.000000e-05 eta: 0:38:08 time: 0.348022 data_time: 0.035103 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.930021 2023/08/09 19:22:25 - mmengine - INFO - Epoch(train) [196][170/442] lr: 5.000000e-05 eta: 0:38:05 time: 0.350026 data_time: 0.035319 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.870150 2023/08/09 19:22:28 - mmengine - INFO - Epoch(train) [196][180/442] lr: 5.000000e-05 eta: 0:38:01 time: 0.352667 data_time: 0.035187 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.883607 2023/08/09 19:22:31 - mmengine - INFO - Epoch(train) [196][190/442] lr: 5.000000e-05 eta: 0:37:57 time: 0.351758 data_time: 0.035347 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.771208 2023/08/09 19:22:35 - mmengine - INFO - Epoch(train) [196][200/442] lr: 5.000000e-05 eta: 0:37:54 time: 0.346052 data_time: 0.031560 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.875337 2023/08/09 19:22:38 - mmengine - INFO - Epoch(train) [196][210/442] lr: 5.000000e-05 eta: 0:37:50 time: 0.345296 data_time: 0.031301 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.830672 2023/08/09 19:22:42 - mmengine - INFO - Epoch(train) [196][220/442] lr: 5.000000e-05 eta: 0:37:47 time: 0.345369 data_time: 0.031565 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.877982 2023/08/09 19:22:45 - mmengine - INFO - Epoch(train) [196][230/442] lr: 5.000000e-05 eta: 0:37:43 time: 0.344418 data_time: 0.031914 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.827189 2023/08/09 19:22:49 - mmengine - INFO - Epoch(train) [196][240/442] lr: 5.000000e-05 eta: 0:37:40 time: 0.345087 data_time: 0.031926 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.905592 2023/08/09 19:22:52 - mmengine - INFO - Epoch(train) [196][250/442] lr: 5.000000e-05 eta: 0:37:36 time: 0.344932 data_time: 0.031623 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.818222 2023/08/09 19:22:56 - mmengine - INFO - Epoch(train) [196][260/442] lr: 5.000000e-05 eta: 0:37:33 time: 0.344657 data_time: 0.031720 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.910907 2023/08/09 19:22:59 - mmengine - INFO - Epoch(train) [196][270/442] lr: 5.000000e-05 eta: 0:37:29 time: 0.343894 data_time: 0.031275 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.894986 2023/08/09 19:23:02 - mmengine - INFO - Epoch(train) [196][280/442] lr: 5.000000e-05 eta: 0:37:25 time: 0.342899 data_time: 0.031246 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.835693 2023/08/09 19:23:06 - mmengine - INFO - Epoch(train) [196][290/442] lr: 5.000000e-05 eta: 0:37:22 time: 0.344913 data_time: 0.031211 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.836766 2023/08/09 19:23:09 - mmengine - INFO - Epoch(train) [196][300/442] lr: 5.000000e-05 eta: 0:37:18 time: 0.346443 data_time: 0.031444 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.922204 2023/08/09 19:23:13 - mmengine - INFO - Epoch(train) [196][310/442] lr: 5.000000e-05 eta: 0:37:15 time: 0.351165 data_time: 0.031413 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.819217 2023/08/09 19:23:17 - mmengine - INFO - Epoch(train) [196][320/442] lr: 5.000000e-05 eta: 0:37:11 time: 0.354299 data_time: 0.032227 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.904114 2023/08/09 19:23:20 - mmengine - INFO - Epoch(train) [196][330/442] lr: 5.000000e-05 eta: 0:37:08 time: 0.355607 data_time: 0.032823 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.902133 2023/08/09 19:23:24 - mmengine - INFO - Epoch(train) [196][340/442] lr: 5.000000e-05 eta: 0:37:04 time: 0.353319 data_time: 0.032776 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.923683 2023/08/09 19:23:27 - mmengine - INFO - Epoch(train) [196][350/442] lr: 5.000000e-05 eta: 0:37:01 time: 0.352468 data_time: 0.032753 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.900893 2023/08/09 19:23:31 - mmengine - INFO - Epoch(train) [196][360/442] lr: 5.000000e-05 eta: 0:36:57 time: 0.348847 data_time: 0.032792 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.911728 2023/08/09 19:23:34 - mmengine - INFO - Epoch(train) [196][370/442] lr: 5.000000e-05 eta: 0:36:54 time: 0.347729 data_time: 0.032372 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.929660 2023/08/09 19:23:38 - mmengine - INFO - Epoch(train) [196][380/442] lr: 5.000000e-05 eta: 0:36:50 time: 0.346125 data_time: 0.031835 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.892833 2023/08/09 19:23:41 - mmengine - INFO - Epoch(train) [196][390/442] lr: 5.000000e-05 eta: 0:36:47 time: 0.345583 data_time: 0.031794 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.857212 2023/08/09 19:23:44 - mmengine - INFO - Epoch(train) [196][400/442] lr: 5.000000e-05 eta: 0:36:43 time: 0.345669 data_time: 0.031432 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.776100 2023/08/09 19:23:48 - mmengine - INFO - Epoch(train) [196][410/442] lr: 5.000000e-05 eta: 0:36:39 time: 0.345061 data_time: 0.031374 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.897989 2023/08/09 19:23:51 - mmengine - INFO - Epoch(train) [196][420/442] lr: 5.000000e-05 eta: 0:36:36 time: 0.343934 data_time: 0.031186 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.898502 2023/08/09 19:23:55 - mmengine - INFO - Epoch(train) [196][430/442] lr: 5.000000e-05 eta: 0:36:32 time: 0.345532 data_time: 0.032531 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.864869 2023/08/09 19:23:59 - mmengine - INFO - Epoch(train) [196][440/442] lr: 5.000000e-05 eta: 0:36:29 time: 0.350467 data_time: 0.032762 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.919414 2023/08/09 19:23:59 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:24:03 - mmengine - INFO - Epoch(train) [197][ 10/442] lr: 5.000000e-05 eta: 0:36:25 time: 0.354035 data_time: 0.036657 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.960269 2023/08/09 19:24:06 - mmengine - INFO - Epoch(train) [197][ 20/442] lr: 5.000000e-05 eta: 0:36:21 time: 0.355909 data_time: 0.036798 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.898377 2023/08/09 19:24:10 - mmengine - INFO - Epoch(train) [197][ 30/442] lr: 5.000000e-05 eta: 0:36:17 time: 0.354367 data_time: 0.035990 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.858782 2023/08/09 19:24:14 - mmengine - INFO - Epoch(train) [197][ 40/442] lr: 5.000000e-05 eta: 0:36:14 time: 0.359045 data_time: 0.038867 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.907451 2023/08/09 19:24:17 - mmengine - INFO - Epoch(train) [197][ 50/442] lr: 5.000000e-05 eta: 0:36:10 time: 0.360058 data_time: 0.039358 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.884703 2023/08/09 19:24:21 - mmengine - INFO - Epoch(train) [197][ 60/442] lr: 5.000000e-05 eta: 0:36:07 time: 0.359034 data_time: 0.035258 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.858126 2023/08/09 19:24:24 - mmengine - INFO - Epoch(train) [197][ 70/442] lr: 5.000000e-05 eta: 0:36:03 time: 0.359582 data_time: 0.035275 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.894875 2023/08/09 19:24:28 - mmengine - INFO - Epoch(train) [197][ 80/442] lr: 5.000000e-05 eta: 0:36:00 time: 0.360797 data_time: 0.035204 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.761154 2023/08/09 19:24:31 - mmengine - INFO - Epoch(train) [197][ 90/442] lr: 5.000000e-05 eta: 0:35:56 time: 0.358130 data_time: 0.031261 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.878702 2023/08/09 19:24:35 - mmengine - INFO - Epoch(train) [197][100/442] lr: 5.000000e-05 eta: 0:35:53 time: 0.356282 data_time: 0.030660 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.918667 2023/08/09 19:24:39 - mmengine - INFO - Epoch(train) [197][110/442] lr: 5.000000e-05 eta: 0:35:49 time: 0.356087 data_time: 0.030765 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.949784 2023/08/09 19:24:42 - mmengine - INFO - Epoch(train) [197][120/442] lr: 5.000000e-05 eta: 0:35:46 time: 0.357565 data_time: 0.030976 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.885590 2023/08/09 19:24:46 - mmengine - INFO - Epoch(train) [197][130/442] lr: 5.000000e-05 eta: 0:35:42 time: 0.364516 data_time: 0.031297 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.927998 2023/08/09 19:24:50 - mmengine - INFO - Epoch(train) [197][140/442] lr: 5.000000e-05 eta: 0:35:39 time: 0.365532 data_time: 0.031378 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.907366 2023/08/09 19:24:53 - mmengine - INFO - Epoch(train) [197][150/442] lr: 5.000000e-05 eta: 0:35:35 time: 0.365463 data_time: 0.031355 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.864017 2023/08/09 19:24:57 - mmengine - INFO - Epoch(train) [197][160/442] lr: 5.000000e-05 eta: 0:35:32 time: 0.364546 data_time: 0.031280 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.879058 2023/08/09 19:25:00 - mmengine - INFO - Epoch(train) [197][170/442] lr: 5.000000e-05 eta: 0:35:28 time: 0.364372 data_time: 0.030987 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.917310 2023/08/09 19:25:04 - mmengine - INFO - Epoch(train) [197][180/442] lr: 5.000000e-05 eta: 0:35:25 time: 0.358813 data_time: 0.030977 memory: 4565 loss: 0.000726 loss_kpt: 0.000726 acc_pose: 0.914100 2023/08/09 19:25:08 - mmengine - INFO - Epoch(train) [197][190/442] lr: 5.000000e-05 eta: 0:35:21 time: 0.357694 data_time: 0.031129 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.865107 2023/08/09 19:25:11 - mmengine - INFO - Epoch(train) [197][200/442] lr: 5.000000e-05 eta: 0:35:18 time: 0.357917 data_time: 0.031946 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.922179 2023/08/09 19:25:15 - mmengine - INFO - Epoch(train) [197][210/442] lr: 5.000000e-05 eta: 0:35:14 time: 0.356948 data_time: 0.032333 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.895047 2023/08/09 19:25:18 - mmengine - INFO - Epoch(train) [197][220/442] lr: 5.000000e-05 eta: 0:35:10 time: 0.354835 data_time: 0.032246 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.864620 2023/08/09 19:25:22 - mmengine - INFO - Epoch(train) [197][230/442] lr: 5.000000e-05 eta: 0:35:07 time: 0.352626 data_time: 0.032170 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.858213 2023/08/09 19:25:25 - mmengine - INFO - Epoch(train) [197][240/442] lr: 5.000000e-05 eta: 0:35:03 time: 0.355654 data_time: 0.035500 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.877506 2023/08/09 19:25:29 - mmengine - INFO - Epoch(train) [197][250/442] lr: 5.000000e-05 eta: 0:35:00 time: 0.356356 data_time: 0.034816 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.834194 2023/08/09 19:25:33 - mmengine - INFO - Epoch(train) [197][260/442] lr: 5.000000e-05 eta: 0:34:56 time: 0.357991 data_time: 0.035047 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.893283 2023/08/09 19:25:36 - mmengine - INFO - Epoch(train) [197][270/442] lr: 5.000000e-05 eta: 0:34:53 time: 0.360086 data_time: 0.034925 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.947731 2023/08/09 19:25:40 - mmengine - INFO - Epoch(train) [197][280/442] lr: 5.000000e-05 eta: 0:34:49 time: 0.359525 data_time: 0.034687 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.892400 2023/08/09 19:25:43 - mmengine - INFO - Epoch(train) [197][290/442] lr: 5.000000e-05 eta: 0:34:46 time: 0.357515 data_time: 0.031218 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.894202 2023/08/09 19:25:47 - mmengine - INFO - Epoch(train) [197][300/442] lr: 5.000000e-05 eta: 0:34:42 time: 0.358381 data_time: 0.031246 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.883383 2023/08/09 19:25:51 - mmengine - INFO - Epoch(train) [197][310/442] lr: 5.000000e-05 eta: 0:34:39 time: 0.359348 data_time: 0.030973 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.852893 2023/08/09 19:25:54 - mmengine - INFO - Epoch(train) [197][320/442] lr: 5.000000e-05 eta: 0:34:35 time: 0.361159 data_time: 0.031537 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.878109 2023/08/09 19:25:58 - mmengine - INFO - Epoch(train) [197][330/442] lr: 5.000000e-05 eta: 0:34:32 time: 0.364058 data_time: 0.031673 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.893010 2023/08/09 19:26:02 - mmengine - INFO - Epoch(train) [197][340/442] lr: 5.000000e-05 eta: 0:34:28 time: 0.365492 data_time: 0.031877 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.869837 2023/08/09 19:26:05 - mmengine - INFO - Epoch(train) [197][350/442] lr: 5.000000e-05 eta: 0:34:25 time: 0.364456 data_time: 0.031741 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.922307 2023/08/09 19:26:09 - mmengine - INFO - Epoch(train) [197][360/442] lr: 5.000000e-05 eta: 0:34:21 time: 0.363887 data_time: 0.031397 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.898516 2023/08/09 19:26:12 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:26:12 - mmengine - INFO - Epoch(train) [197][370/442] lr: 5.000000e-05 eta: 0:34:18 time: 0.361816 data_time: 0.031058 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.899631 2023/08/09 19:26:16 - mmengine - INFO - Epoch(train) [197][380/442] lr: 5.000000e-05 eta: 0:34:14 time: 0.364684 data_time: 0.031536 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.870092 2023/08/09 19:26:20 - mmengine - INFO - Epoch(train) [197][390/442] lr: 5.000000e-05 eta: 0:34:11 time: 0.370556 data_time: 0.032354 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.903271 2023/08/09 19:26:24 - mmengine - INFO - Epoch(train) [197][400/442] lr: 5.000000e-05 eta: 0:34:07 time: 0.372745 data_time: 0.033244 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.912562 2023/08/09 19:26:28 - mmengine - INFO - Epoch(train) [197][410/442] lr: 5.000000e-05 eta: 0:34:04 time: 0.376304 data_time: 0.033966 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.882995 2023/08/09 19:26:31 - mmengine - INFO - Epoch(train) [197][420/442] lr: 5.000000e-05 eta: 0:34:00 time: 0.374602 data_time: 0.034805 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.868122 2023/08/09 19:26:35 - mmengine - INFO - Epoch(train) [197][430/442] lr: 5.000000e-05 eta: 0:33:57 time: 0.374905 data_time: 0.034868 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.909571 2023/08/09 19:26:39 - mmengine - INFO - Epoch(train) [197][440/442] lr: 5.000000e-05 eta: 0:33:53 time: 0.371911 data_time: 0.037710 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.915928 2023/08/09 19:26:39 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:26:43 - mmengine - INFO - Epoch(train) [198][ 10/442] lr: 5.000000e-05 eta: 0:33:49 time: 0.376038 data_time: 0.041019 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.884533 2023/08/09 19:26:47 - mmengine - INFO - Epoch(train) [198][ 20/442] lr: 5.000000e-05 eta: 0:33:45 time: 0.375547 data_time: 0.040960 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.876144 2023/08/09 19:26:51 - mmengine - INFO - Epoch(train) [198][ 30/442] lr: 5.000000e-05 eta: 0:33:42 time: 0.374787 data_time: 0.040249 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.900630 2023/08/09 19:26:54 - mmengine - INFO - Epoch(train) [198][ 40/442] lr: 5.000000e-05 eta: 0:33:38 time: 0.364085 data_time: 0.036151 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.925777 2023/08/09 19:26:58 - mmengine - INFO - Epoch(train) [198][ 50/442] lr: 5.000000e-05 eta: 0:33:35 time: 0.362234 data_time: 0.036409 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.889595 2023/08/09 19:27:01 - mmengine - INFO - Epoch(train) [198][ 60/442] lr: 5.000000e-05 eta: 0:33:31 time: 0.353940 data_time: 0.032245 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.936715 2023/08/09 19:27:05 - mmengine - INFO - Epoch(train) [198][ 70/442] lr: 5.000000e-05 eta: 0:33:28 time: 0.347813 data_time: 0.031890 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.930279 2023/08/09 19:27:08 - mmengine - INFO - Epoch(train) [198][ 80/442] lr: 5.000000e-05 eta: 0:33:24 time: 0.346861 data_time: 0.031742 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.917095 2023/08/09 19:27:11 - mmengine - INFO - Epoch(train) [198][ 90/442] lr: 5.000000e-05 eta: 0:33:20 time: 0.346091 data_time: 0.031460 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.833509 2023/08/09 19:27:15 - mmengine - INFO - Epoch(train) [198][100/442] lr: 5.000000e-05 eta: 0:33:17 time: 0.347176 data_time: 0.031177 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.880625 2023/08/09 19:27:18 - mmengine - INFO - Epoch(train) [198][110/442] lr: 5.000000e-05 eta: 0:33:13 time: 0.342929 data_time: 0.030703 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.940860 2023/08/09 19:27:22 - mmengine - INFO - Epoch(train) [198][120/442] lr: 5.000000e-05 eta: 0:33:10 time: 0.342546 data_time: 0.030512 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.953180 2023/08/09 19:27:25 - mmengine - INFO - Epoch(train) [198][130/442] lr: 5.000000e-05 eta: 0:33:06 time: 0.343430 data_time: 0.031591 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.889377 2023/08/09 19:27:29 - mmengine - INFO - Epoch(train) [198][140/442] lr: 5.000000e-05 eta: 0:33:03 time: 0.346833 data_time: 0.032399 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.954865 2023/08/09 19:27:32 - mmengine - INFO - Epoch(train) [198][150/442] lr: 5.000000e-05 eta: 0:32:59 time: 0.347875 data_time: 0.032639 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.893470 2023/08/09 19:27:36 - mmengine - INFO - Epoch(train) [198][160/442] lr: 5.000000e-05 eta: 0:32:56 time: 0.354191 data_time: 0.032802 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.878129 2023/08/09 19:27:40 - mmengine - INFO - Epoch(train) [198][170/442] lr: 5.000000e-05 eta: 0:32:52 time: 0.357123 data_time: 0.033129 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.897373 2023/08/09 19:27:43 - mmengine - INFO - Epoch(train) [198][180/442] lr: 5.000000e-05 eta: 0:32:49 time: 0.359467 data_time: 0.035139 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.844910 2023/08/09 19:27:47 - mmengine - INFO - Epoch(train) [198][190/442] lr: 5.000000e-05 eta: 0:32:45 time: 0.358339 data_time: 0.034691 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.927661 2023/08/09 19:27:50 - mmengine - INFO - Epoch(train) [198][200/442] lr: 5.000000e-05 eta: 0:32:42 time: 0.358254 data_time: 0.034921 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.909002 2023/08/09 19:27:54 - mmengine - INFO - Epoch(train) [198][210/442] lr: 5.000000e-05 eta: 0:32:38 time: 0.356584 data_time: 0.035204 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.856235 2023/08/09 19:27:57 - mmengine - INFO - Epoch(train) [198][220/442] lr: 5.000000e-05 eta: 0:32:34 time: 0.357039 data_time: 0.034932 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.883423 2023/08/09 19:28:01 - mmengine - INFO - Epoch(train) [198][230/442] lr: 5.000000e-05 eta: 0:32:31 time: 0.354673 data_time: 0.031897 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.908432 2023/08/09 19:28:05 - mmengine - INFO - Epoch(train) [198][240/442] lr: 5.000000e-05 eta: 0:32:27 time: 0.356905 data_time: 0.031790 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.926601 2023/08/09 19:28:08 - mmengine - INFO - Epoch(train) [198][250/442] lr: 5.000000e-05 eta: 0:32:24 time: 0.356216 data_time: 0.031518 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.915766 2023/08/09 19:28:12 - mmengine - INFO - Epoch(train) [198][260/442] lr: 5.000000e-05 eta: 0:32:20 time: 0.356744 data_time: 0.031218 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.863843 2023/08/09 19:28:16 - mmengine - INFO - Epoch(train) [198][270/442] lr: 5.000000e-05 eta: 0:32:17 time: 0.363653 data_time: 0.031522 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.742909 2023/08/09 19:28:20 - mmengine - INFO - Epoch(train) [198][280/442] lr: 5.000000e-05 eta: 0:32:13 time: 0.371054 data_time: 0.032030 memory: 4565 loss: 0.000732 loss_kpt: 0.000732 acc_pose: 0.851366 2023/08/09 19:28:23 - mmengine - INFO - Epoch(train) [198][290/442] lr: 5.000000e-05 eta: 0:32:10 time: 0.375592 data_time: 0.032280 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.891677 2023/08/09 19:28:27 - mmengine - INFO - Epoch(train) [198][300/442] lr: 5.000000e-05 eta: 0:32:06 time: 0.376445 data_time: 0.032215 memory: 4565 loss: 0.000734 loss_kpt: 0.000734 acc_pose: 0.897634 2023/08/09 19:28:31 - mmengine - INFO - Epoch(train) [198][310/442] lr: 5.000000e-05 eta: 0:32:03 time: 0.377397 data_time: 0.032111 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.901006 2023/08/09 19:28:34 - mmengine - INFO - Epoch(train) [198][320/442] lr: 5.000000e-05 eta: 0:31:59 time: 0.369715 data_time: 0.031586 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.893446 2023/08/09 19:28:38 - mmengine - INFO - Epoch(train) [198][330/442] lr: 5.000000e-05 eta: 0:31:56 time: 0.363848 data_time: 0.031535 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.889573 2023/08/09 19:28:41 - mmengine - INFO - Epoch(train) [198][340/442] lr: 5.000000e-05 eta: 0:31:52 time: 0.359498 data_time: 0.031459 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.872779 2023/08/09 19:28:45 - mmengine - INFO - Epoch(train) [198][350/442] lr: 5.000000e-05 eta: 0:31:49 time: 0.358479 data_time: 0.031405 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.905356 2023/08/09 19:28:48 - mmengine - INFO - Epoch(train) [198][360/442] lr: 5.000000e-05 eta: 0:31:45 time: 0.356171 data_time: 0.031359 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.882528 2023/08/09 19:28:52 - mmengine - INFO - Epoch(train) [198][370/442] lr: 5.000000e-05 eta: 0:31:42 time: 0.355910 data_time: 0.031494 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.872836 2023/08/09 19:28:56 - mmengine - INFO - Epoch(train) [198][380/442] lr: 5.000000e-05 eta: 0:31:38 time: 0.357236 data_time: 0.030962 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.887621 2023/08/09 19:28:59 - mmengine - INFO - Epoch(train) [198][390/442] lr: 5.000000e-05 eta: 0:31:35 time: 0.356390 data_time: 0.030946 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.870547 2023/08/09 19:29:03 - mmengine - INFO - Epoch(train) [198][400/442] lr: 5.000000e-05 eta: 0:31:31 time: 0.356710 data_time: 0.031038 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.850609 2023/08/09 19:29:06 - mmengine - INFO - Epoch(train) [198][410/442] lr: 5.000000e-05 eta: 0:31:27 time: 0.356979 data_time: 0.031641 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.912877 2023/08/09 19:29:10 - mmengine - INFO - Epoch(train) [198][420/442] lr: 5.000000e-05 eta: 0:31:24 time: 0.356246 data_time: 0.031628 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.897490 2023/08/09 19:29:13 - mmengine - INFO - Epoch(train) [198][430/442] lr: 5.000000e-05 eta: 0:31:20 time: 0.353348 data_time: 0.031602 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.934241 2023/08/09 19:29:17 - mmengine - INFO - Epoch(train) [198][440/442] lr: 5.000000e-05 eta: 0:31:17 time: 0.351146 data_time: 0.031516 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.885837 2023/08/09 19:29:17 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:29:21 - mmengine - INFO - Epoch(train) [199][ 10/442] lr: 5.000000e-05 eta: 0:31:13 time: 0.353282 data_time: 0.035020 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.852431 2023/08/09 19:29:25 - mmengine - INFO - Epoch(train) [199][ 20/442] lr: 5.000000e-05 eta: 0:31:09 time: 0.356328 data_time: 0.034755 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.877135 2023/08/09 19:29:28 - mmengine - INFO - Epoch(train) [199][ 30/442] lr: 5.000000e-05 eta: 0:31:06 time: 0.358363 data_time: 0.034826 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.830371 2023/08/09 19:29:32 - mmengine - INFO - Epoch(train) [199][ 40/442] lr: 5.000000e-05 eta: 0:31:02 time: 0.358099 data_time: 0.034914 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.917457 2023/08/09 19:29:35 - mmengine - INFO - Epoch(train) [199][ 50/442] lr: 5.000000e-05 eta: 0:30:58 time: 0.359724 data_time: 0.035105 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.886972 2023/08/09 19:29:39 - mmengine - INFO - Epoch(train) [199][ 60/442] lr: 5.000000e-05 eta: 0:30:55 time: 0.355073 data_time: 0.030982 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.950358 2023/08/09 19:29:42 - mmengine - INFO - Epoch(train) [199][ 70/442] lr: 5.000000e-05 eta: 0:30:51 time: 0.351774 data_time: 0.030731 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.866475 2023/08/09 19:29:46 - mmengine - INFO - Epoch(train) [199][ 80/442] lr: 5.000000e-05 eta: 0:30:48 time: 0.353229 data_time: 0.030614 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.905363 2023/08/09 19:29:50 - mmengine - INFO - Epoch(train) [199][ 90/442] lr: 5.000000e-05 eta: 0:30:44 time: 0.353830 data_time: 0.030889 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.932780 2023/08/09 19:29:53 - mmengine - INFO - Epoch(train) [199][100/442] lr: 5.000000e-05 eta: 0:30:41 time: 0.355998 data_time: 0.031453 memory: 4565 loss: 0.000681 loss_kpt: 0.000681 acc_pose: 0.914897 2023/08/09 19:29:57 - mmengine - INFO - Epoch(train) [199][110/442] lr: 5.000000e-05 eta: 0:30:37 time: 0.356567 data_time: 0.031531 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.936138 2023/08/09 19:30:00 - mmengine - INFO - Epoch(train) [199][120/442] lr: 5.000000e-05 eta: 0:30:34 time: 0.356201 data_time: 0.031668 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.878244 2023/08/09 19:30:04 - mmengine - INFO - Epoch(train) [199][130/442] lr: 5.000000e-05 eta: 0:30:30 time: 0.354712 data_time: 0.031648 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.932154 2023/08/09 19:30:07 - mmengine - INFO - Epoch(train) [199][140/442] lr: 5.000000e-05 eta: 0:30:27 time: 0.354967 data_time: 0.031635 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.937044 2023/08/09 19:30:11 - mmengine - INFO - Epoch(train) [199][150/442] lr: 5.000000e-05 eta: 0:30:23 time: 0.358289 data_time: 0.031215 memory: 4565 loss: 0.000675 loss_kpt: 0.000675 acc_pose: 0.921714 2023/08/09 19:30:15 - mmengine - INFO - Epoch(train) [199][160/442] lr: 5.000000e-05 eta: 0:30:20 time: 0.360162 data_time: 0.031212 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.869886 2023/08/09 19:30:18 - mmengine - INFO - Epoch(train) [199][170/442] lr: 5.000000e-05 eta: 0:30:16 time: 0.361039 data_time: 0.031463 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.863262 2023/08/09 19:30:22 - mmengine - INFO - Epoch(train) [199][180/442] lr: 5.000000e-05 eta: 0:30:13 time: 0.358775 data_time: 0.031463 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.878432 2023/08/09 19:30:25 - mmengine - INFO - Epoch(train) [199][190/442] lr: 5.000000e-05 eta: 0:30:09 time: 0.357638 data_time: 0.031232 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.864340 2023/08/09 19:30:29 - mmengine - INFO - Epoch(train) [199][200/442] lr: 5.000000e-05 eta: 0:30:05 time: 0.355338 data_time: 0.031375 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.869965 2023/08/09 19:30:33 - mmengine - INFO - Epoch(train) [199][210/442] lr: 5.000000e-05 eta: 0:30:02 time: 0.356119 data_time: 0.031360 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.928642 2023/08/09 19:30:36 - mmengine - INFO - Epoch(train) [199][220/442] lr: 5.000000e-05 eta: 0:29:58 time: 0.357560 data_time: 0.031050 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.926125 2023/08/09 19:30:40 - mmengine - INFO - Epoch(train) [199][230/442] lr: 5.000000e-05 eta: 0:29:55 time: 0.360639 data_time: 0.031499 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.830620 2023/08/09 19:30:43 - mmengine - INFO - Epoch(train) [199][240/442] lr: 5.000000e-05 eta: 0:29:51 time: 0.361482 data_time: 0.031752 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.843493 2023/08/09 19:30:47 - mmengine - INFO - Epoch(train) [199][250/442] lr: 5.000000e-05 eta: 0:29:48 time: 0.358549 data_time: 0.031363 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.891287 2023/08/09 19:30:50 - mmengine - INFO - Epoch(train) [199][260/442] lr: 5.000000e-05 eta: 0:29:44 time: 0.354873 data_time: 0.031394 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.887252 2023/08/09 19:30:54 - mmengine - INFO - Epoch(train) [199][270/442] lr: 5.000000e-05 eta: 0:29:41 time: 0.352629 data_time: 0.031489 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.913039 2023/08/09 19:30:57 - mmengine - INFO - Epoch(train) [199][280/442] lr: 5.000000e-05 eta: 0:29:37 time: 0.352045 data_time: 0.031297 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.906797 2023/08/09 19:31:01 - mmengine - INFO - Epoch(train) [199][290/442] lr: 5.000000e-05 eta: 0:29:34 time: 0.354078 data_time: 0.030997 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.883404 2023/08/09 19:31:05 - mmengine - INFO - Epoch(train) [199][300/442] lr: 5.000000e-05 eta: 0:29:30 time: 0.358317 data_time: 0.031327 memory: 4565 loss: 0.000672 loss_kpt: 0.000672 acc_pose: 0.931945 2023/08/09 19:31:08 - mmengine - INFO - Epoch(train) [199][310/442] lr: 5.000000e-05 eta: 0:29:27 time: 0.358143 data_time: 0.031354 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.945011 2023/08/09 19:31:12 - mmengine - INFO - Epoch(train) [199][320/442] lr: 5.000000e-05 eta: 0:29:23 time: 0.360574 data_time: 0.031219 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.798356 2023/08/09 19:31:15 - mmengine - INFO - Epoch(train) [199][330/442] lr: 5.000000e-05 eta: 0:29:20 time: 0.358271 data_time: 0.030822 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.825443 2023/08/09 19:31:19 - mmengine - INFO - Epoch(train) [199][340/442] lr: 5.000000e-05 eta: 0:29:16 time: 0.356807 data_time: 0.031234 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.915182 2023/08/09 19:31:23 - mmengine - INFO - Epoch(train) [199][350/442] lr: 5.000000e-05 eta: 0:29:12 time: 0.355292 data_time: 0.031308 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.922109 2023/08/09 19:31:26 - mmengine - INFO - Epoch(train) [199][360/442] lr: 5.000000e-05 eta: 0:29:09 time: 0.360277 data_time: 0.031646 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.885378 2023/08/09 19:31:30 - mmengine - INFO - Epoch(train) [199][370/442] lr: 5.000000e-05 eta: 0:29:05 time: 0.357601 data_time: 0.031559 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.862597 2023/08/09 19:31:33 - mmengine - INFO - Epoch(train) [199][380/442] lr: 5.000000e-05 eta: 0:29:02 time: 0.358007 data_time: 0.031657 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.862605 2023/08/09 19:31:37 - mmengine - INFO - Epoch(train) [199][390/442] lr: 5.000000e-05 eta: 0:28:58 time: 0.357360 data_time: 0.031281 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.904314 2023/08/09 19:31:40 - mmengine - INFO - Epoch(train) [199][400/442] lr: 5.000000e-05 eta: 0:28:55 time: 0.355696 data_time: 0.031265 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.877458 2023/08/09 19:31:44 - mmengine - INFO - Epoch(train) [199][410/442] lr: 5.000000e-05 eta: 0:28:51 time: 0.352862 data_time: 0.030868 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.944834 2023/08/09 19:31:47 - mmengine - INFO - Epoch(train) [199][420/442] lr: 5.000000e-05 eta: 0:28:48 time: 0.353720 data_time: 0.030955 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.929875 2023/08/09 19:31:51 - mmengine - INFO - Epoch(train) [199][430/442] lr: 5.000000e-05 eta: 0:28:44 time: 0.355519 data_time: 0.031123 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.880120 2023/08/09 19:31:55 - mmengine - INFO - Epoch(train) [199][440/442] lr: 5.000000e-05 eta: 0:28:41 time: 0.358166 data_time: 0.031035 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.813703 2023/08/09 19:31:55 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:31:59 - mmengine - INFO - Epoch(train) [200][ 10/442] lr: 5.000000e-05 eta: 0:28:36 time: 0.361168 data_time: 0.034438 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.938112 2023/08/09 19:32:03 - mmengine - INFO - Epoch(train) [200][ 20/442] lr: 5.000000e-05 eta: 0:28:33 time: 0.358724 data_time: 0.034191 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.857343 2023/08/09 19:32:06 - mmengine - INFO - Epoch(train) [200][ 30/442] lr: 5.000000e-05 eta: 0:28:29 time: 0.357257 data_time: 0.034071 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.908125 2023/08/09 19:32:10 - mmengine - INFO - Epoch(train) [200][ 40/442] lr: 5.000000e-05 eta: 0:28:26 time: 0.353303 data_time: 0.033871 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.927869 2023/08/09 19:32:10 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:32:13 - mmengine - INFO - Epoch(train) [200][ 50/442] lr: 5.000000e-05 eta: 0:28:22 time: 0.357166 data_time: 0.034803 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.892834 2023/08/09 19:32:17 - mmengine - INFO - Epoch(train) [200][ 60/442] lr: 5.000000e-05 eta: 0:28:19 time: 0.352351 data_time: 0.031295 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.911690 2023/08/09 19:32:20 - mmengine - INFO - Epoch(train) [200][ 70/442] lr: 5.000000e-05 eta: 0:28:15 time: 0.352787 data_time: 0.031751 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.879170 2023/08/09 19:32:24 - mmengine - INFO - Epoch(train) [200][ 80/442] lr: 5.000000e-05 eta: 0:28:12 time: 0.353648 data_time: 0.032335 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.893841 2023/08/09 19:32:27 - mmengine - INFO - Epoch(train) [200][ 90/442] lr: 5.000000e-05 eta: 0:28:08 time: 0.353172 data_time: 0.032445 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.892201 2023/08/09 19:32:31 - mmengine - INFO - Epoch(train) [200][100/442] lr: 5.000000e-05 eta: 0:28:05 time: 0.353497 data_time: 0.032135 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.905101 2023/08/09 19:32:35 - mmengine - INFO - Epoch(train) [200][110/442] lr: 5.000000e-05 eta: 0:28:01 time: 0.355339 data_time: 0.031904 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.944146 2023/08/09 19:32:38 - mmengine - INFO - Epoch(train) [200][120/442] lr: 5.000000e-05 eta: 0:27:58 time: 0.357029 data_time: 0.031677 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.926905 2023/08/09 19:32:42 - mmengine - INFO - Epoch(train) [200][130/442] lr: 5.000000e-05 eta: 0:27:54 time: 0.357149 data_time: 0.031502 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.892773 2023/08/09 19:32:45 - mmengine - INFO - Epoch(train) [200][140/442] lr: 5.000000e-05 eta: 0:27:50 time: 0.357802 data_time: 0.031537 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.887521 2023/08/09 19:32:49 - mmengine - INFO - Epoch(train) [200][150/442] lr: 5.000000e-05 eta: 0:27:47 time: 0.356795 data_time: 0.032144 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.897168 2023/08/09 19:32:53 - mmengine - INFO - Epoch(train) [200][160/442] lr: 5.000000e-05 eta: 0:27:43 time: 0.358295 data_time: 0.035472 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.912871 2023/08/09 19:32:56 - mmengine - INFO - Epoch(train) [200][170/442] lr: 5.000000e-05 eta: 0:27:40 time: 0.361669 data_time: 0.035452 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.904999 2023/08/09 19:33:00 - mmengine - INFO - Epoch(train) [200][180/442] lr: 5.000000e-05 eta: 0:27:36 time: 0.363922 data_time: 0.035721 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.919548 2023/08/09 19:33:03 - mmengine - INFO - Epoch(train) [200][190/442] lr: 5.000000e-05 eta: 0:27:33 time: 0.364532 data_time: 0.035581 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.904143 2023/08/09 19:33:07 - mmengine - INFO - Epoch(train) [200][200/442] lr: 5.000000e-05 eta: 0:27:29 time: 0.364424 data_time: 0.035023 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.880859 2023/08/09 19:33:11 - mmengine - INFO - Epoch(train) [200][210/442] lr: 5.000000e-05 eta: 0:27:26 time: 0.361988 data_time: 0.031585 memory: 4565 loss: 0.000675 loss_kpt: 0.000675 acc_pose: 0.877039 2023/08/09 19:33:14 - mmengine - INFO - Epoch(train) [200][220/442] lr: 5.000000e-05 eta: 0:27:22 time: 0.359065 data_time: 0.031572 memory: 4565 loss: 0.000677 loss_kpt: 0.000677 acc_pose: 0.889198 2023/08/09 19:33:18 - mmengine - INFO - Epoch(train) [200][230/442] lr: 5.000000e-05 eta: 0:27:19 time: 0.359243 data_time: 0.031099 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.864212 2023/08/09 19:33:21 - mmengine - INFO - Epoch(train) [200][240/442] lr: 5.000000e-05 eta: 0:27:15 time: 0.359978 data_time: 0.031330 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.905361 2023/08/09 19:33:25 - mmengine - INFO - Epoch(train) [200][250/442] lr: 5.000000e-05 eta: 0:27:12 time: 0.359961 data_time: 0.031244 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.844568 2023/08/09 19:33:29 - mmengine - INFO - Epoch(train) [200][260/442] lr: 5.000000e-05 eta: 0:27:08 time: 0.357916 data_time: 0.031008 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.905807 2023/08/09 19:33:32 - mmengine - INFO - Epoch(train) [200][270/442] lr: 5.000000e-05 eta: 0:27:05 time: 0.356956 data_time: 0.030782 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.935506 2023/08/09 19:33:36 - mmengine - INFO - Epoch(train) [200][280/442] lr: 5.000000e-05 eta: 0:27:01 time: 0.353496 data_time: 0.030708 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.898632 2023/08/09 19:33:39 - mmengine - INFO - Epoch(train) [200][290/442] lr: 5.000000e-05 eta: 0:26:57 time: 0.352554 data_time: 0.030831 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.946800 2023/08/09 19:33:43 - mmengine - INFO - Epoch(train) [200][300/442] lr: 5.000000e-05 eta: 0:26:54 time: 0.352015 data_time: 0.030858 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.928504 2023/08/09 19:33:46 - mmengine - INFO - Epoch(train) [200][310/442] lr: 5.000000e-05 eta: 0:26:50 time: 0.356906 data_time: 0.034328 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.852389 2023/08/09 19:33:50 - mmengine - INFO - Epoch(train) [200][320/442] lr: 5.000000e-05 eta: 0:26:47 time: 0.359881 data_time: 0.037948 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.869018 2023/08/09 19:33:54 - mmengine - INFO - Epoch(train) [200][330/442] lr: 5.000000e-05 eta: 0:26:43 time: 0.362751 data_time: 0.038101 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.810871 2023/08/09 19:33:57 - mmengine - INFO - Epoch(train) [200][340/442] lr: 5.000000e-05 eta: 0:26:40 time: 0.362350 data_time: 0.038177 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.847331 2023/08/09 19:34:01 - mmengine - INFO - Epoch(train) [200][350/442] lr: 5.000000e-05 eta: 0:26:36 time: 0.362142 data_time: 0.037887 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.903190 2023/08/09 19:34:04 - mmengine - INFO - Epoch(train) [200][360/442] lr: 5.000000e-05 eta: 0:26:33 time: 0.358882 data_time: 0.034716 memory: 4565 loss: 0.000724 loss_kpt: 0.000724 acc_pose: 0.930357 2023/08/09 19:34:08 - mmengine - INFO - Epoch(train) [200][370/442] lr: 5.000000e-05 eta: 0:26:29 time: 0.355828 data_time: 0.031181 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.903753 2023/08/09 19:34:12 - mmengine - INFO - Epoch(train) [200][380/442] lr: 5.000000e-05 eta: 0:26:26 time: 0.355621 data_time: 0.031379 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.910993 2023/08/09 19:34:15 - mmengine - INFO - Epoch(train) [200][390/442] lr: 5.000000e-05 eta: 0:26:22 time: 0.354552 data_time: 0.030859 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.818274 2023/08/09 19:34:18 - mmengine - INFO - Epoch(train) [200][400/442] lr: 5.000000e-05 eta: 0:26:19 time: 0.353541 data_time: 0.030987 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.941686 2023/08/09 19:34:22 - mmengine - INFO - Epoch(train) [200][410/442] lr: 5.000000e-05 eta: 0:26:15 time: 0.352324 data_time: 0.030984 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.884190 2023/08/09 19:34:26 - mmengine - INFO - Epoch(train) [200][420/442] lr: 5.000000e-05 eta: 0:26:11 time: 0.352101 data_time: 0.031218 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.927211 2023/08/09 19:34:29 - mmengine - INFO - Epoch(train) [200][430/442] lr: 5.000000e-05 eta: 0:26:08 time: 0.350458 data_time: 0.030980 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.939843 2023/08/09 19:34:33 - mmengine - INFO - Epoch(train) [200][440/442] lr: 5.000000e-05 eta: 0:26:04 time: 0.352987 data_time: 0.031889 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.848581 2023/08/09 19:34:33 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:34:33 - mmengine - INFO - Saving checkpoint at 200 epochs 2023/08/09 19:34:39 - mmengine - INFO - Epoch(val) [200][ 10/108] eta: 0:00:20 time: 0.198845 data_time: 0.014502 memory: 4565 2023/08/09 19:34:41 - mmengine - INFO - Epoch(val) [200][ 20/108] eta: 0:00:17 time: 0.198200 data_time: 0.013975 memory: 1624 2023/08/09 19:34:43 - mmengine - INFO - Epoch(val) [200][ 30/108] eta: 0:00:15 time: 0.197620 data_time: 0.013481 memory: 1624 2023/08/09 19:34:45 - mmengine - INFO - Epoch(val) [200][ 40/108] eta: 0:00:13 time: 0.197243 data_time: 0.013026 memory: 1624 2023/08/09 19:34:47 - mmengine - INFO - Epoch(val) [200][ 50/108] eta: 0:00:11 time: 0.201502 data_time: 0.015888 memory: 1624 2023/08/09 19:34:49 - mmengine - INFO - Epoch(val) [200][ 60/108] eta: 0:00:09 time: 0.199141 data_time: 0.013928 memory: 1624 2023/08/09 19:34:51 - mmengine - INFO - Epoch(val) [200][ 70/108] eta: 0:00:07 time: 0.199110 data_time: 0.013930 memory: 1624 2023/08/09 19:34:53 - mmengine - INFO - Epoch(val) [200][ 80/108] eta: 0:00:05 time: 0.199206 data_time: 0.013960 memory: 1624 2023/08/09 19:34:55 - mmengine - INFO - Epoch(val) [200][ 90/108] eta: 0:00:03 time: 0.199109 data_time: 0.013918 memory: 1624 2023/08/09 19:34:57 - mmengine - INFO - Epoch(val) [200][100/108] eta: 0:00:01 time: 0.196087 data_time: 0.010790 memory: 1624 2023/08/09 19:34:58 - mmengine - INFO - Evaluating PCKAccuracy (normalized by ``"bbox_size"``)... 2023/08/09 19:34:58 - mmengine - INFO - Evaluating AUC... 2023/08/09 19:34:59 - mmengine - INFO - Evaluating EPE... 2023/08/09 19:34:59 - mmengine - INFO - Epoch(val) [200][108/108] PCK: 0.961629 AUC: 0.604586 EPE: 14.821460 data_time: 0.013065 time: 0.196882 2023/08/09 19:35:02 - mmengine - INFO - Epoch(train) [201][ 10/442] lr: 5.000000e-06 eta: 0:26:00 time: 0.355093 data_time: 0.035486 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.915305 2023/08/09 19:35:06 - mmengine - INFO - Epoch(train) [201][ 20/442] lr: 5.000000e-06 eta: 0:25:57 time: 0.352371 data_time: 0.035078 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.885070 2023/08/09 19:35:09 - mmengine - INFO - Epoch(train) [201][ 30/442] lr: 5.000000e-06 eta: 0:25:53 time: 0.349315 data_time: 0.035196 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.864788 2023/08/09 19:35:13 - mmengine - INFO - Epoch(train) [201][ 40/442] lr: 5.000000e-06 eta: 0:25:49 time: 0.347098 data_time: 0.034761 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.927932 2023/08/09 19:35:16 - mmengine - INFO - Epoch(train) [201][ 50/442] lr: 5.000000e-06 eta: 0:25:46 time: 0.346646 data_time: 0.034610 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.893573 2023/08/09 19:35:20 - mmengine - INFO - Epoch(train) [201][ 60/442] lr: 5.000000e-06 eta: 0:25:42 time: 0.343156 data_time: 0.031002 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.908248 2023/08/09 19:35:23 - mmengine - INFO - Epoch(train) [201][ 70/442] lr: 5.000000e-06 eta: 0:25:39 time: 0.344578 data_time: 0.031169 memory: 4565 loss: 0.000681 loss_kpt: 0.000681 acc_pose: 0.900935 2023/08/09 19:35:26 - mmengine - INFO - Epoch(train) [201][ 80/442] lr: 5.000000e-06 eta: 0:25:35 time: 0.345081 data_time: 0.031139 memory: 4565 loss: 0.000663 loss_kpt: 0.000663 acc_pose: 0.918395 2023/08/09 19:35:30 - mmengine - INFO - Epoch(train) [201][ 90/442] lr: 5.000000e-06 eta: 0:25:32 time: 0.344374 data_time: 0.031272 memory: 4565 loss: 0.000669 loss_kpt: 0.000669 acc_pose: 0.905453 2023/08/09 19:35:33 - mmengine - INFO - Epoch(train) [201][100/442] lr: 5.000000e-06 eta: 0:25:28 time: 0.342214 data_time: 0.031094 memory: 4565 loss: 0.000673 loss_kpt: 0.000673 acc_pose: 0.923970 2023/08/09 19:35:37 - mmengine - INFO - Epoch(train) [201][110/442] lr: 5.000000e-06 eta: 0:25:25 time: 0.340540 data_time: 0.030860 memory: 4565 loss: 0.000673 loss_kpt: 0.000673 acc_pose: 0.854362 2023/08/09 19:35:40 - mmengine - INFO - Epoch(train) [201][120/442] lr: 5.000000e-06 eta: 0:25:21 time: 0.340056 data_time: 0.030697 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.891125 2023/08/09 19:35:44 - mmengine - INFO - Epoch(train) [201][130/442] lr: 5.000000e-06 eta: 0:25:18 time: 0.347960 data_time: 0.030961 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.877088 2023/08/09 19:35:47 - mmengine - INFO - Epoch(train) [201][140/442] lr: 5.000000e-06 eta: 0:25:14 time: 0.349857 data_time: 0.030763 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.927990 2023/08/09 19:35:51 - mmengine - INFO - Epoch(train) [201][150/442] lr: 5.000000e-06 eta: 0:25:10 time: 0.350955 data_time: 0.030983 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.857465 2023/08/09 19:35:54 - mmengine - INFO - Epoch(train) [201][160/442] lr: 5.000000e-06 eta: 0:25:07 time: 0.351321 data_time: 0.030693 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.867955 2023/08/09 19:35:58 - mmengine - INFO - Epoch(train) [201][170/442] lr: 5.000000e-06 eta: 0:25:03 time: 0.351454 data_time: 0.030725 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.942957 2023/08/09 19:36:01 - mmengine - INFO - Epoch(train) [201][180/442] lr: 5.000000e-06 eta: 0:25:00 time: 0.343530 data_time: 0.030461 memory: 4565 loss: 0.000676 loss_kpt: 0.000676 acc_pose: 0.874353 2023/08/09 19:36:04 - mmengine - INFO - Epoch(train) [201][190/442] lr: 5.000000e-06 eta: 0:24:56 time: 0.342810 data_time: 0.030603 memory: 4565 loss: 0.000675 loss_kpt: 0.000675 acc_pose: 0.899780 2023/08/09 19:36:08 - mmengine - INFO - Epoch(train) [201][200/442] lr: 5.000000e-06 eta: 0:24:53 time: 0.343049 data_time: 0.030813 memory: 4565 loss: 0.000672 loss_kpt: 0.000672 acc_pose: 0.888173 2023/08/09 19:36:11 - mmengine - INFO - Epoch(train) [201][210/442] lr: 5.000000e-06 eta: 0:24:49 time: 0.343554 data_time: 0.030990 memory: 4565 loss: 0.000676 loss_kpt: 0.000676 acc_pose: 0.875932 2023/08/09 19:36:15 - mmengine - INFO - Epoch(train) [201][220/442] lr: 5.000000e-06 eta: 0:24:46 time: 0.342431 data_time: 0.031084 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.858966 2023/08/09 19:36:18 - mmengine - INFO - Epoch(train) [201][230/442] lr: 5.000000e-06 eta: 0:24:42 time: 0.342429 data_time: 0.030949 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.895271 2023/08/09 19:36:22 - mmengine - INFO - Epoch(train) [201][240/442] lr: 5.000000e-06 eta: 0:24:39 time: 0.341533 data_time: 0.031153 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.927223 2023/08/09 19:36:25 - mmengine - INFO - Epoch(train) [201][250/442] lr: 5.000000e-06 eta: 0:24:35 time: 0.340977 data_time: 0.030859 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.909346 2023/08/09 19:36:29 - mmengine - INFO - Epoch(train) [201][260/442] lr: 5.000000e-06 eta: 0:24:31 time: 0.345052 data_time: 0.030898 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.905522 2023/08/09 19:36:32 - mmengine - INFO - Epoch(train) [201][270/442] lr: 5.000000e-06 eta: 0:24:28 time: 0.352414 data_time: 0.031298 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.892083 2023/08/09 19:36:36 - mmengine - INFO - Epoch(train) [201][280/442] lr: 5.000000e-06 eta: 0:24:24 time: 0.361829 data_time: 0.031807 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.869417 2023/08/09 19:36:40 - mmengine - INFO - Epoch(train) [201][290/442] lr: 5.000000e-06 eta: 0:24:21 time: 0.375131 data_time: 0.035638 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.866188 2023/08/09 19:36:44 - mmengine - INFO - Epoch(train) [201][300/442] lr: 5.000000e-06 eta: 0:24:17 time: 0.381592 data_time: 0.036270 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.866615 2023/08/09 19:36:48 - mmengine - INFO - Epoch(train) [201][310/442] lr: 5.000000e-06 eta: 0:24:14 time: 0.378101 data_time: 0.036157 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.870076 2023/08/09 19:36:51 - mmengine - INFO - Epoch(train) [201][320/442] lr: 5.000000e-06 eta: 0:24:10 time: 0.372225 data_time: 0.035728 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.860536 2023/08/09 19:36:54 - mmengine - INFO - Epoch(train) [201][330/442] lr: 5.000000e-06 eta: 0:24:07 time: 0.363818 data_time: 0.035659 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.894920 2023/08/09 19:36:58 - mmengine - INFO - Epoch(train) [201][340/442] lr: 5.000000e-06 eta: 0:24:03 time: 0.350358 data_time: 0.031436 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.880287 2023/08/09 19:37:01 - mmengine - INFO - Epoch(train) [201][350/442] lr: 5.000000e-06 eta: 0:24:00 time: 0.342841 data_time: 0.030688 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.928373 2023/08/09 19:37:05 - mmengine - INFO - Epoch(train) [201][360/442] lr: 5.000000e-06 eta: 0:23:56 time: 0.341209 data_time: 0.030644 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.885099 2023/08/09 19:37:08 - mmengine - INFO - Epoch(train) [201][370/442] lr: 5.000000e-06 eta: 0:23:53 time: 0.339653 data_time: 0.030530 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.886104 2023/08/09 19:37:12 - mmengine - INFO - Epoch(train) [201][380/442] lr: 5.000000e-06 eta: 0:23:49 time: 0.341601 data_time: 0.030308 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.924694 2023/08/09 19:37:15 - mmengine - INFO - Epoch(train) [201][390/442] lr: 5.000000e-06 eta: 0:23:45 time: 0.341852 data_time: 0.030952 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.897551 2023/08/09 19:37:19 - mmengine - INFO - Epoch(train) [201][400/442] lr: 5.000000e-06 eta: 0:23:42 time: 0.344952 data_time: 0.031635 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.914586 2023/08/09 19:37:22 - mmengine - INFO - Epoch(train) [201][410/442] lr: 5.000000e-06 eta: 0:23:38 time: 0.346054 data_time: 0.031965 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.912595 2023/08/09 19:37:25 - mmengine - INFO - Epoch(train) [201][420/442] lr: 5.000000e-06 eta: 0:23:35 time: 0.346895 data_time: 0.031899 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.910066 2023/08/09 19:37:29 - mmengine - INFO - Epoch(train) [201][430/442] lr: 5.000000e-06 eta: 0:23:31 time: 0.345921 data_time: 0.031790 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.920549 2023/08/09 19:37:32 - mmengine - INFO - Epoch(train) [201][440/442] lr: 5.000000e-06 eta: 0:23:28 time: 0.345604 data_time: 0.031292 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.888396 2023/08/09 19:37:33 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:37:37 - mmengine - INFO - Epoch(train) [202][ 10/442] lr: 5.000000e-06 eta: 0:23:24 time: 0.346747 data_time: 0.034098 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.847943 2023/08/09 19:37:40 - mmengine - INFO - Epoch(train) [202][ 20/442] lr: 5.000000e-06 eta: 0:23:20 time: 0.351082 data_time: 0.034333 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.900622 2023/08/09 19:37:44 - mmengine - INFO - Epoch(train) [202][ 30/442] lr: 5.000000e-06 eta: 0:23:16 time: 0.352257 data_time: 0.034549 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.875503 2023/08/09 19:37:47 - mmengine - INFO - Epoch(train) [202][ 40/442] lr: 5.000000e-06 eta: 0:23:13 time: 0.350390 data_time: 0.034532 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.900503 2023/08/09 19:37:51 - mmengine - INFO - Epoch(train) [202][ 50/442] lr: 5.000000e-06 eta: 0:23:09 time: 0.351593 data_time: 0.034977 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.950972 2023/08/09 19:37:54 - mmengine - INFO - Epoch(train) [202][ 60/442] lr: 5.000000e-06 eta: 0:23:06 time: 0.346194 data_time: 0.031059 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.886414 2023/08/09 19:37:57 - mmengine - INFO - Epoch(train) [202][ 70/442] lr: 5.000000e-06 eta: 0:23:02 time: 0.342775 data_time: 0.031037 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.851223 2023/08/09 19:38:01 - mmengine - INFO - Epoch(train) [202][ 80/442] lr: 5.000000e-06 eta: 0:22:59 time: 0.344907 data_time: 0.031298 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.893338 2023/08/09 19:38:04 - mmengine - INFO - Epoch(train) [202][ 90/442] lr: 5.000000e-06 eta: 0:22:55 time: 0.346581 data_time: 0.032058 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.840651 2023/08/09 19:38:08 - mmengine - INFO - Epoch(train) [202][100/442] lr: 5.000000e-06 eta: 0:22:52 time: 0.347574 data_time: 0.032349 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.902292 2023/08/09 19:38:11 - mmengine - INFO - Epoch(train) [202][110/442] lr: 5.000000e-06 eta: 0:22:48 time: 0.347299 data_time: 0.032336 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.919955 2023/08/09 19:38:15 - mmengine - INFO - Epoch(train) [202][120/442] lr: 5.000000e-06 eta: 0:22:45 time: 0.345826 data_time: 0.032326 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.881393 2023/08/09 19:38:18 - mmengine - INFO - Epoch(train) [202][130/442] lr: 5.000000e-06 eta: 0:22:41 time: 0.341937 data_time: 0.031786 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.906593 2023/08/09 19:38:22 - mmengine - INFO - Epoch(train) [202][140/442] lr: 5.000000e-06 eta: 0:22:37 time: 0.341839 data_time: 0.031226 memory: 4565 loss: 0.000668 loss_kpt: 0.000668 acc_pose: 0.876666 2023/08/09 19:38:25 - mmengine - INFO - Epoch(train) [202][150/442] lr: 5.000000e-06 eta: 0:22:34 time: 0.341631 data_time: 0.030821 memory: 4565 loss: 0.000678 loss_kpt: 0.000678 acc_pose: 0.920421 2023/08/09 19:38:28 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:38:29 - mmengine - INFO - Epoch(train) [202][160/442] lr: 5.000000e-06 eta: 0:22:30 time: 0.344201 data_time: 0.030883 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.825149 2023/08/09 19:38:32 - mmengine - INFO - Epoch(train) [202][170/442] lr: 5.000000e-06 eta: 0:22:27 time: 0.346121 data_time: 0.030828 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.895814 2023/08/09 19:38:35 - mmengine - INFO - Epoch(train) [202][180/442] lr: 5.000000e-06 eta: 0:22:23 time: 0.347592 data_time: 0.030814 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.922516 2023/08/09 19:38:39 - mmengine - INFO - Epoch(train) [202][190/442] lr: 5.000000e-06 eta: 0:22:20 time: 0.347712 data_time: 0.030596 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.902574 2023/08/09 19:38:42 - mmengine - INFO - Epoch(train) [202][200/442] lr: 5.000000e-06 eta: 0:22:16 time: 0.347434 data_time: 0.030532 memory: 4565 loss: 0.000682 loss_kpt: 0.000682 acc_pose: 0.867384 2023/08/09 19:38:46 - mmengine - INFO - Epoch(train) [202][210/442] lr: 5.000000e-06 eta: 0:22:13 time: 0.346507 data_time: 0.030437 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.861503 2023/08/09 19:38:49 - mmengine - INFO - Epoch(train) [202][220/442] lr: 5.000000e-06 eta: 0:22:09 time: 0.349757 data_time: 0.033563 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.904300 2023/08/09 19:38:53 - mmengine - INFO - Epoch(train) [202][230/442] lr: 5.000000e-06 eta: 0:22:06 time: 0.349903 data_time: 0.033855 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.893842 2023/08/09 19:38:57 - mmengine - INFO - Epoch(train) [202][240/442] lr: 5.000000e-06 eta: 0:22:02 time: 0.351878 data_time: 0.034272 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.901657 2023/08/09 19:39:00 - mmengine - INFO - Epoch(train) [202][250/442] lr: 5.000000e-06 eta: 0:21:58 time: 0.351120 data_time: 0.034343 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.863758 2023/08/09 19:39:03 - mmengine - INFO - Epoch(train) [202][260/442] lr: 5.000000e-06 eta: 0:21:55 time: 0.349595 data_time: 0.034357 memory: 4565 loss: 0.000731 loss_kpt: 0.000731 acc_pose: 0.896102 2023/08/09 19:39:07 - mmengine - INFO - Epoch(train) [202][270/442] lr: 5.000000e-06 eta: 0:21:51 time: 0.346143 data_time: 0.031414 memory: 4565 loss: 0.000742 loss_kpt: 0.000742 acc_pose: 0.936545 2023/08/09 19:39:10 - mmengine - INFO - Epoch(train) [202][280/442] lr: 5.000000e-06 eta: 0:21:48 time: 0.346770 data_time: 0.031142 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.820011 2023/08/09 19:39:14 - mmengine - INFO - Epoch(train) [202][290/442] lr: 5.000000e-06 eta: 0:21:44 time: 0.345574 data_time: 0.031080 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.898413 2023/08/09 19:39:17 - mmengine - INFO - Epoch(train) [202][300/442] lr: 5.000000e-06 eta: 0:21:41 time: 0.349441 data_time: 0.031635 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.901631 2023/08/09 19:39:21 - mmengine - INFO - Epoch(train) [202][310/442] lr: 5.000000e-06 eta: 0:21:37 time: 0.349467 data_time: 0.031483 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.907677 2023/08/09 19:39:24 - mmengine - INFO - Epoch(train) [202][320/442] lr: 5.000000e-06 eta: 0:21:34 time: 0.349481 data_time: 0.031148 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.932494 2023/08/09 19:39:28 - mmengine - INFO - Epoch(train) [202][330/442] lr: 5.000000e-06 eta: 0:21:30 time: 0.348090 data_time: 0.031117 memory: 4565 loss: 0.000682 loss_kpt: 0.000682 acc_pose: 0.915109 2023/08/09 19:39:31 - mmengine - INFO - Epoch(train) [202][340/442] lr: 5.000000e-06 eta: 0:21:27 time: 0.346342 data_time: 0.030772 memory: 4565 loss: 0.000674 loss_kpt: 0.000674 acc_pose: 0.858783 2023/08/09 19:39:35 - mmengine - INFO - Epoch(train) [202][350/442] lr: 5.000000e-06 eta: 0:21:23 time: 0.343416 data_time: 0.030217 memory: 4565 loss: 0.000669 loss_kpt: 0.000669 acc_pose: 0.894925 2023/08/09 19:39:38 - mmengine - INFO - Epoch(train) [202][360/442] lr: 5.000000e-06 eta: 0:21:19 time: 0.344807 data_time: 0.031010 memory: 4565 loss: 0.000671 loss_kpt: 0.000671 acc_pose: 0.902846 2023/08/09 19:39:42 - mmengine - INFO - Epoch(train) [202][370/442] lr: 5.000000e-06 eta: 0:21:16 time: 0.345954 data_time: 0.031358 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.883321 2023/08/09 19:39:45 - mmengine - INFO - Epoch(train) [202][380/442] lr: 5.000000e-06 eta: 0:21:12 time: 0.345596 data_time: 0.031282 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.936533 2023/08/09 19:39:48 - mmengine - INFO - Epoch(train) [202][390/442] lr: 5.000000e-06 eta: 0:21:09 time: 0.345762 data_time: 0.031247 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.866160 2023/08/09 19:39:52 - mmengine - INFO - Epoch(train) [202][400/442] lr: 5.000000e-06 eta: 0:21:05 time: 0.345490 data_time: 0.031186 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.836566 2023/08/09 19:39:56 - mmengine - INFO - Epoch(train) [202][410/442] lr: 5.000000e-06 eta: 0:21:02 time: 0.353744 data_time: 0.030852 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.947186 2023/08/09 19:40:00 - mmengine - INFO - Epoch(train) [202][420/442] lr: 5.000000e-06 eta: 0:20:58 time: 0.361853 data_time: 0.031236 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.901371 2023/08/09 19:40:04 - mmengine - INFO - Epoch(train) [202][430/442] lr: 5.000000e-06 eta: 0:20:55 time: 0.371357 data_time: 0.031785 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.885347 2023/08/09 19:40:07 - mmengine - INFO - Epoch(train) [202][440/442] lr: 5.000000e-06 eta: 0:20:51 time: 0.370138 data_time: 0.031971 memory: 4565 loss: 0.000670 loss_kpt: 0.000670 acc_pose: 0.869240 2023/08/09 19:40:08 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:40:12 - mmengine - INFO - Epoch(train) [203][ 10/442] lr: 5.000000e-06 eta: 0:20:47 time: 0.378499 data_time: 0.035556 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.933518 2023/08/09 19:40:15 - mmengine - INFO - Epoch(train) [203][ 20/442] lr: 5.000000e-06 eta: 0:20:43 time: 0.368840 data_time: 0.035193 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.870517 2023/08/09 19:40:19 - mmengine - INFO - Epoch(train) [203][ 30/442] lr: 5.000000e-06 eta: 0:20:40 time: 0.360163 data_time: 0.034522 memory: 4565 loss: 0.000675 loss_kpt: 0.000675 acc_pose: 0.947298 2023/08/09 19:40:22 - mmengine - INFO - Epoch(train) [203][ 40/442] lr: 5.000000e-06 eta: 0:20:36 time: 0.355369 data_time: 0.034110 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.831818 2023/08/09 19:40:26 - mmengine - INFO - Epoch(train) [203][ 50/442] lr: 5.000000e-06 eta: 0:20:33 time: 0.360558 data_time: 0.034591 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.916083 2023/08/09 19:40:29 - mmengine - INFO - Epoch(train) [203][ 60/442] lr: 5.000000e-06 eta: 0:20:29 time: 0.352854 data_time: 0.030632 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.861563 2023/08/09 19:40:33 - mmengine - INFO - Epoch(train) [203][ 70/442] lr: 5.000000e-06 eta: 0:20:26 time: 0.352693 data_time: 0.030672 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.958934 2023/08/09 19:40:36 - mmengine - INFO - Epoch(train) [203][ 80/442] lr: 5.000000e-06 eta: 0:20:22 time: 0.352821 data_time: 0.030675 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.941938 2023/08/09 19:40:40 - mmengine - INFO - Epoch(train) [203][ 90/442] lr: 5.000000e-06 eta: 0:20:19 time: 0.351440 data_time: 0.030480 memory: 4565 loss: 0.000682 loss_kpt: 0.000682 acc_pose: 0.916721 2023/08/09 19:40:43 - mmengine - INFO - Epoch(train) [203][100/442] lr: 5.000000e-06 eta: 0:20:15 time: 0.351269 data_time: 0.030266 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.890026 2023/08/09 19:40:47 - mmengine - INFO - Epoch(train) [203][110/442] lr: 5.000000e-06 eta: 0:20:12 time: 0.351831 data_time: 0.030209 memory: 4565 loss: 0.000671 loss_kpt: 0.000671 acc_pose: 0.923295 2023/08/09 19:40:50 - mmengine - INFO - Epoch(train) [203][120/442] lr: 5.000000e-06 eta: 0:20:08 time: 0.353777 data_time: 0.030409 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.829021 2023/08/09 19:40:54 - mmengine - INFO - Epoch(train) [203][130/442] lr: 5.000000e-06 eta: 0:20:05 time: 0.354727 data_time: 0.031118 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.861085 2023/08/09 19:40:58 - mmengine - INFO - Epoch(train) [203][140/442] lr: 5.000000e-06 eta: 0:20:01 time: 0.357115 data_time: 0.032007 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.871624 2023/08/09 19:41:01 - mmengine - INFO - Epoch(train) [203][150/442] lr: 5.000000e-06 eta: 0:19:57 time: 0.358362 data_time: 0.032731 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.935237 2023/08/09 19:41:05 - mmengine - INFO - Epoch(train) [203][160/442] lr: 5.000000e-06 eta: 0:19:54 time: 0.357541 data_time: 0.033608 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.826566 2023/08/09 19:41:08 - mmengine - INFO - Epoch(train) [203][170/442] lr: 5.000000e-06 eta: 0:19:50 time: 0.360333 data_time: 0.033992 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.896315 2023/08/09 19:41:12 - mmengine - INFO - Epoch(train) [203][180/442] lr: 5.000000e-06 eta: 0:19:47 time: 0.360006 data_time: 0.033825 memory: 4565 loss: 0.000715 loss_kpt: 0.000715 acc_pose: 0.827200 2023/08/09 19:41:16 - mmengine - INFO - Epoch(train) [203][190/442] lr: 5.000000e-06 eta: 0:19:43 time: 0.360868 data_time: 0.033758 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.934713 2023/08/09 19:41:19 - mmengine - INFO - Epoch(train) [203][200/442] lr: 5.000000e-06 eta: 0:19:40 time: 0.359200 data_time: 0.034299 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.927488 2023/08/09 19:41:23 - mmengine - INFO - Epoch(train) [203][210/442] lr: 5.000000e-06 eta: 0:19:36 time: 0.359055 data_time: 0.034102 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.932402 2023/08/09 19:41:26 - mmengine - INFO - Epoch(train) [203][220/442] lr: 5.000000e-06 eta: 0:19:33 time: 0.354309 data_time: 0.033721 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.903126 2023/08/09 19:41:30 - mmengine - INFO - Epoch(train) [203][230/442] lr: 5.000000e-06 eta: 0:19:29 time: 0.353824 data_time: 0.033363 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.805605 2023/08/09 19:41:33 - mmengine - INFO - Epoch(train) [203][240/442] lr: 5.000000e-06 eta: 0:19:26 time: 0.351999 data_time: 0.032823 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.822268 2023/08/09 19:41:37 - mmengine - INFO - Epoch(train) [203][250/442] lr: 5.000000e-06 eta: 0:19:22 time: 0.354058 data_time: 0.031668 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.896350 2023/08/09 19:41:40 - mmengine - INFO - Epoch(train) [203][260/442] lr: 5.000000e-06 eta: 0:19:19 time: 0.353749 data_time: 0.031011 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.901475 2023/08/09 19:41:44 - mmengine - INFO - Epoch(train) [203][270/442] lr: 5.000000e-06 eta: 0:19:15 time: 0.357248 data_time: 0.030875 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.850667 2023/08/09 19:41:48 - mmengine - INFO - Epoch(train) [203][280/442] lr: 5.000000e-06 eta: 0:19:12 time: 0.364481 data_time: 0.031061 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.898366 2023/08/09 19:41:52 - mmengine - INFO - Epoch(train) [203][290/442] lr: 5.000000e-06 eta: 0:19:08 time: 0.373391 data_time: 0.031231 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.826579 2023/08/09 19:41:56 - mmengine - INFO - Epoch(train) [203][300/442] lr: 5.000000e-06 eta: 0:19:04 time: 0.373502 data_time: 0.031125 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.810458 2023/08/09 19:41:59 - mmengine - INFO - Epoch(train) [203][310/442] lr: 5.000000e-06 eta: 0:19:01 time: 0.376010 data_time: 0.031701 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.914364 2023/08/09 19:42:03 - mmengine - INFO - Epoch(train) [203][320/442] lr: 5.000000e-06 eta: 0:18:57 time: 0.372653 data_time: 0.031654 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.870450 2023/08/09 19:42:06 - mmengine - INFO - Epoch(train) [203][330/442] lr: 5.000000e-06 eta: 0:18:54 time: 0.364410 data_time: 0.031268 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.916306 2023/08/09 19:42:10 - mmengine - INFO - Epoch(train) [203][340/442] lr: 5.000000e-06 eta: 0:18:50 time: 0.353574 data_time: 0.030928 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.898351 2023/08/09 19:42:13 - mmengine - INFO - Epoch(train) [203][350/442] lr: 5.000000e-06 eta: 0:18:47 time: 0.350578 data_time: 0.030971 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.914866 2023/08/09 19:42:17 - mmengine - INFO - Epoch(train) [203][360/442] lr: 5.000000e-06 eta: 0:18:43 time: 0.349417 data_time: 0.030559 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.912593 2023/08/09 19:42:20 - mmengine - INFO - Epoch(train) [203][370/442] lr: 5.000000e-06 eta: 0:18:40 time: 0.350143 data_time: 0.030657 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.906960 2023/08/09 19:42:24 - mmengine - INFO - Epoch(train) [203][380/442] lr: 5.000000e-06 eta: 0:18:36 time: 0.354048 data_time: 0.030838 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.873225 2023/08/09 19:42:27 - mmengine - INFO - Epoch(train) [203][390/442] lr: 5.000000e-06 eta: 0:18:33 time: 0.355764 data_time: 0.030824 memory: 4565 loss: 0.000681 loss_kpt: 0.000681 acc_pose: 0.894233 2023/08/09 19:42:31 - mmengine - INFO - Epoch(train) [203][400/442] lr: 5.000000e-06 eta: 0:18:29 time: 0.354920 data_time: 0.030795 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.933622 2023/08/09 19:42:34 - mmengine - INFO - Epoch(train) [203][410/442] lr: 5.000000e-06 eta: 0:18:26 time: 0.356325 data_time: 0.033744 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.842040 2023/08/09 19:42:38 - mmengine - INFO - Epoch(train) [203][420/442] lr: 5.000000e-06 eta: 0:18:22 time: 0.358025 data_time: 0.033919 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.918346 2023/08/09 19:42:42 - mmengine - INFO - Epoch(train) [203][430/442] lr: 5.000000e-06 eta: 0:18:18 time: 0.357055 data_time: 0.034420 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.882026 2023/08/09 19:42:45 - mmengine - INFO - Epoch(train) [203][440/442] lr: 5.000000e-06 eta: 0:18:15 time: 0.360974 data_time: 0.034813 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.884670 2023/08/09 19:42:46 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:42:50 - mmengine - INFO - Epoch(train) [204][ 10/442] lr: 5.000000e-06 eta: 0:18:11 time: 0.364177 data_time: 0.038292 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.806659 2023/08/09 19:42:53 - mmengine - INFO - Epoch(train) [204][ 20/442] lr: 5.000000e-06 eta: 0:18:07 time: 0.361808 data_time: 0.035262 memory: 4565 loss: 0.000669 loss_kpt: 0.000669 acc_pose: 0.885550 2023/08/09 19:42:57 - mmengine - INFO - Epoch(train) [204][ 30/442] lr: 5.000000e-06 eta: 0:18:04 time: 0.359778 data_time: 0.034760 memory: 4565 loss: 0.000674 loss_kpt: 0.000674 acc_pose: 0.890887 2023/08/09 19:43:00 - mmengine - INFO - Epoch(train) [204][ 40/442] lr: 5.000000e-06 eta: 0:18:00 time: 0.356726 data_time: 0.034662 memory: 4565 loss: 0.000667 loss_kpt: 0.000667 acc_pose: 0.905459 2023/08/09 19:43:04 - mmengine - INFO - Epoch(train) [204][ 50/442] lr: 5.000000e-06 eta: 0:17:57 time: 0.356608 data_time: 0.034742 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.864306 2023/08/09 19:43:08 - mmengine - INFO - Epoch(train) [204][ 60/442] lr: 5.000000e-06 eta: 0:17:53 time: 0.354637 data_time: 0.031423 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.871879 2023/08/09 19:43:11 - mmengine - INFO - Epoch(train) [204][ 70/442] lr: 5.000000e-06 eta: 0:17:50 time: 0.354106 data_time: 0.031169 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.898389 2023/08/09 19:43:15 - mmengine - INFO - Epoch(train) [204][ 80/442] lr: 5.000000e-06 eta: 0:17:46 time: 0.354328 data_time: 0.031263 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.866868 2023/08/09 19:43:18 - mmengine - INFO - Epoch(train) [204][ 90/442] lr: 5.000000e-06 eta: 0:17:42 time: 0.352664 data_time: 0.030973 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.897943 2023/08/09 19:43:22 - mmengine - INFO - Epoch(train) [204][100/442] lr: 5.000000e-06 eta: 0:17:39 time: 0.353762 data_time: 0.031203 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.826281 2023/08/09 19:43:25 - mmengine - INFO - Epoch(train) [204][110/442] lr: 5.000000e-06 eta: 0:17:35 time: 0.353281 data_time: 0.030864 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.856804 2023/08/09 19:43:29 - mmengine - INFO - Epoch(train) [204][120/442] lr: 5.000000e-06 eta: 0:17:32 time: 0.353402 data_time: 0.030903 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.871540 2023/08/09 19:43:32 - mmengine - INFO - Epoch(train) [204][130/442] lr: 5.000000e-06 eta: 0:17:28 time: 0.353381 data_time: 0.031088 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.963122 2023/08/09 19:43:36 - mmengine - INFO - Epoch(train) [204][140/442] lr: 5.000000e-06 eta: 0:17:25 time: 0.353284 data_time: 0.030789 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.889135 2023/08/09 19:43:39 - mmengine - INFO - Epoch(train) [204][150/442] lr: 5.000000e-06 eta: 0:17:21 time: 0.351345 data_time: 0.030413 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.896299 2023/08/09 19:43:43 - mmengine - INFO - Epoch(train) [204][160/442] lr: 5.000000e-06 eta: 0:17:18 time: 0.350646 data_time: 0.030331 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.913823 2023/08/09 19:43:47 - mmengine - INFO - Epoch(train) [204][170/442] lr: 5.000000e-06 eta: 0:17:14 time: 0.355242 data_time: 0.033847 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.887673 2023/08/09 19:43:50 - mmengine - INFO - Epoch(train) [204][180/442] lr: 5.000000e-06 eta: 0:17:11 time: 0.356185 data_time: 0.034235 memory: 4565 loss: 0.000673 loss_kpt: 0.000673 acc_pose: 0.858118 2023/08/09 19:43:54 - mmengine - INFO - Epoch(train) [204][190/442] lr: 5.000000e-06 eta: 0:17:07 time: 0.357988 data_time: 0.034640 memory: 4565 loss: 0.000677 loss_kpt: 0.000677 acc_pose: 0.872584 2023/08/09 19:43:57 - mmengine - INFO - Epoch(train) [204][200/442] lr: 5.000000e-06 eta: 0:17:04 time: 0.361027 data_time: 0.034575 memory: 4565 loss: 0.000677 loss_kpt: 0.000677 acc_pose: 0.945523 2023/08/09 19:44:01 - mmengine - INFO - Epoch(train) [204][210/442] lr: 5.000000e-06 eta: 0:17:00 time: 0.359902 data_time: 0.034500 memory: 4565 loss: 0.000675 loss_kpt: 0.000675 acc_pose: 0.904406 2023/08/09 19:44:04 - mmengine - INFO - Epoch(train) [204][220/442] lr: 5.000000e-06 eta: 0:16:56 time: 0.356027 data_time: 0.030934 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.861182 2023/08/09 19:44:08 - mmengine - INFO - Epoch(train) [204][230/442] lr: 5.000000e-06 eta: 0:16:53 time: 0.354781 data_time: 0.030665 memory: 4565 loss: 0.000671 loss_kpt: 0.000671 acc_pose: 0.893955 2023/08/09 19:44:11 - mmengine - INFO - Epoch(train) [204][240/442] lr: 5.000000e-06 eta: 0:16:49 time: 0.354363 data_time: 0.030575 memory: 4565 loss: 0.000671 loss_kpt: 0.000671 acc_pose: 0.887855 2023/08/09 19:44:15 - mmengine - INFO - Epoch(train) [204][250/442] lr: 5.000000e-06 eta: 0:16:46 time: 0.352629 data_time: 0.030818 memory: 4565 loss: 0.000674 loss_kpt: 0.000674 acc_pose: 0.846438 2023/08/09 19:44:19 - mmengine - INFO - Epoch(train) [204][260/442] lr: 5.000000e-06 eta: 0:16:42 time: 0.354765 data_time: 0.030905 memory: 4565 loss: 0.000671 loss_kpt: 0.000671 acc_pose: 0.864688 2023/08/09 19:44:22 - mmengine - INFO - Epoch(train) [204][270/442] lr: 5.000000e-06 eta: 0:16:39 time: 0.356406 data_time: 0.030863 memory: 4565 loss: 0.000666 loss_kpt: 0.000666 acc_pose: 0.874105 2023/08/09 19:44:24 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:44:26 - mmengine - INFO - Epoch(train) [204][280/442] lr: 5.000000e-06 eta: 0:16:35 time: 0.356294 data_time: 0.030500 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.907579 2023/08/09 19:44:29 - mmengine - INFO - Epoch(train) [204][290/442] lr: 5.000000e-06 eta: 0:16:32 time: 0.354605 data_time: 0.030184 memory: 4565 loss: 0.000676 loss_kpt: 0.000676 acc_pose: 0.892996 2023/08/09 19:44:33 - mmengine - INFO - Epoch(train) [204][300/442] lr: 5.000000e-06 eta: 0:16:28 time: 0.353678 data_time: 0.030116 memory: 4565 loss: 0.000667 loss_kpt: 0.000667 acc_pose: 0.960852 2023/08/09 19:44:36 - mmengine - INFO - Epoch(train) [204][310/442] lr: 5.000000e-06 eta: 0:16:25 time: 0.352236 data_time: 0.030230 memory: 4565 loss: 0.000681 loss_kpt: 0.000681 acc_pose: 0.913090 2023/08/09 19:44:40 - mmengine - INFO - Epoch(train) [204][320/442] lr: 5.000000e-06 eta: 0:16:21 time: 0.352790 data_time: 0.030444 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.844076 2023/08/09 19:44:43 - mmengine - INFO - Epoch(train) [204][330/442] lr: 5.000000e-06 eta: 0:16:18 time: 0.352635 data_time: 0.030643 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.873138 2023/08/09 19:44:47 - mmengine - INFO - Epoch(train) [204][340/442] lr: 5.000000e-06 eta: 0:16:14 time: 0.352433 data_time: 0.030533 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.940398 2023/08/09 19:44:50 - mmengine - INFO - Epoch(train) [204][350/442] lr: 5.000000e-06 eta: 0:16:10 time: 0.354687 data_time: 0.033423 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.879182 2023/08/09 19:44:54 - mmengine - INFO - Epoch(train) [204][360/442] lr: 5.000000e-06 eta: 0:16:07 time: 0.354507 data_time: 0.033189 memory: 4565 loss: 0.000736 loss_kpt: 0.000736 acc_pose: 0.874539 2023/08/09 19:44:58 - mmengine - INFO - Epoch(train) [204][370/442] lr: 5.000000e-06 eta: 0:16:03 time: 0.353369 data_time: 0.033209 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.900586 2023/08/09 19:45:01 - mmengine - INFO - Epoch(train) [204][380/442] lr: 5.000000e-06 eta: 0:16:00 time: 0.355363 data_time: 0.033347 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.873802 2023/08/09 19:45:05 - mmengine - INFO - Epoch(train) [204][390/442] lr: 5.000000e-06 eta: 0:15:56 time: 0.359118 data_time: 0.033482 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.793429 2023/08/09 19:45:09 - mmengine - INFO - Epoch(train) [204][400/442] lr: 5.000000e-06 eta: 0:15:53 time: 0.366372 data_time: 0.030731 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.875204 2023/08/09 19:45:13 - mmengine - INFO - Epoch(train) [204][410/442] lr: 5.000000e-06 eta: 0:15:49 time: 0.374597 data_time: 0.031672 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.888524 2023/08/09 19:45:17 - mmengine - INFO - Epoch(train) [204][420/442] lr: 5.000000e-06 eta: 0:15:46 time: 0.380330 data_time: 0.031895 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.920933 2023/08/09 19:45:20 - mmengine - INFO - Epoch(train) [204][430/442] lr: 5.000000e-06 eta: 0:15:42 time: 0.383759 data_time: 0.031898 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.899951 2023/08/09 19:45:24 - mmengine - INFO - Epoch(train) [204][440/442] lr: 5.000000e-06 eta: 0:15:39 time: 0.381775 data_time: 0.032100 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.887525 2023/08/09 19:45:25 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:45:28 - mmengine - INFO - Epoch(train) [205][ 10/442] lr: 5.000000e-06 eta: 0:15:34 time: 0.371508 data_time: 0.035852 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.872580 2023/08/09 19:45:32 - mmengine - INFO - Epoch(train) [205][ 20/442] lr: 5.000000e-06 eta: 0:15:31 time: 0.361489 data_time: 0.035146 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.888265 2023/08/09 19:45:35 - mmengine - INFO - Epoch(train) [205][ 30/442] lr: 5.000000e-06 eta: 0:15:27 time: 0.351532 data_time: 0.034757 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.870269 2023/08/09 19:45:38 - mmengine - INFO - Epoch(train) [205][ 40/442] lr: 5.000000e-06 eta: 0:15:24 time: 0.345412 data_time: 0.034667 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.902934 2023/08/09 19:45:42 - mmengine - INFO - Epoch(train) [205][ 50/442] lr: 5.000000e-06 eta: 0:15:20 time: 0.346579 data_time: 0.034851 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.904857 2023/08/09 19:45:46 - mmengine - INFO - Epoch(train) [205][ 60/442] lr: 5.000000e-06 eta: 0:15:17 time: 0.352795 data_time: 0.030823 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.884320 2023/08/09 19:45:49 - mmengine - INFO - Epoch(train) [205][ 70/442] lr: 5.000000e-06 eta: 0:15:13 time: 0.354670 data_time: 0.031074 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.876638 2023/08/09 19:45:53 - mmengine - INFO - Epoch(train) [205][ 80/442] lr: 5.000000e-06 eta: 0:15:10 time: 0.354806 data_time: 0.031471 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.906404 2023/08/09 19:45:56 - mmengine - INFO - Epoch(train) [205][ 90/442] lr: 5.000000e-06 eta: 0:15:06 time: 0.354593 data_time: 0.031444 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.854481 2023/08/09 19:46:00 - mmengine - INFO - Epoch(train) [205][100/442] lr: 5.000000e-06 eta: 0:15:03 time: 0.354099 data_time: 0.031322 memory: 4565 loss: 0.000681 loss_kpt: 0.000681 acc_pose: 0.915737 2023/08/09 19:46:03 - mmengine - INFO - Epoch(train) [205][110/442] lr: 5.000000e-06 eta: 0:14:59 time: 0.344513 data_time: 0.031022 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.913832 2023/08/09 19:46:07 - mmengine - INFO - Epoch(train) [205][120/442] lr: 5.000000e-06 eta: 0:14:55 time: 0.344444 data_time: 0.030961 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.897726 2023/08/09 19:46:10 - mmengine - INFO - Epoch(train) [205][130/442] lr: 5.000000e-06 eta: 0:14:52 time: 0.345942 data_time: 0.030776 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.885570 2023/08/09 19:46:13 - mmengine - INFO - Epoch(train) [205][140/442] lr: 5.000000e-06 eta: 0:14:48 time: 0.346215 data_time: 0.030740 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.925713 2023/08/09 19:46:17 - mmengine - INFO - Epoch(train) [205][150/442] lr: 5.000000e-06 eta: 0:14:45 time: 0.343190 data_time: 0.030698 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.869291 2023/08/09 19:46:20 - mmengine - INFO - Epoch(train) [205][160/442] lr: 5.000000e-06 eta: 0:14:41 time: 0.346694 data_time: 0.030668 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.866471 2023/08/09 19:46:24 - mmengine - INFO - Epoch(train) [205][170/442] lr: 5.000000e-06 eta: 0:14:38 time: 0.344865 data_time: 0.030428 memory: 4565 loss: 0.000730 loss_kpt: 0.000730 acc_pose: 0.852819 2023/08/09 19:46:27 - mmengine - INFO - Epoch(train) [205][180/442] lr: 5.000000e-06 eta: 0:14:34 time: 0.343778 data_time: 0.030467 memory: 4565 loss: 0.000737 loss_kpt: 0.000737 acc_pose: 0.861670 2023/08/09 19:46:31 - mmengine - INFO - Epoch(train) [205][190/442] lr: 5.000000e-06 eta: 0:14:31 time: 0.344430 data_time: 0.030863 memory: 4565 loss: 0.000738 loss_kpt: 0.000738 acc_pose: 0.916217 2023/08/09 19:46:34 - mmengine - INFO - Epoch(train) [205][200/442] lr: 5.000000e-06 eta: 0:14:27 time: 0.346051 data_time: 0.031140 memory: 4565 loss: 0.000720 loss_kpt: 0.000720 acc_pose: 0.909977 2023/08/09 19:46:38 - mmengine - INFO - Epoch(train) [205][210/442] lr: 5.000000e-06 eta: 0:14:24 time: 0.342082 data_time: 0.031211 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.891514 2023/08/09 19:46:41 - mmengine - INFO - Epoch(train) [205][220/442] lr: 5.000000e-06 eta: 0:14:20 time: 0.341919 data_time: 0.031231 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.925001 2023/08/09 19:46:44 - mmengine - INFO - Epoch(train) [205][230/442] lr: 5.000000e-06 eta: 0:14:16 time: 0.341166 data_time: 0.030942 memory: 4565 loss: 0.000673 loss_kpt: 0.000673 acc_pose: 0.902428 2023/08/09 19:46:48 - mmengine - INFO - Epoch(train) [205][240/442] lr: 5.000000e-06 eta: 0:14:13 time: 0.340514 data_time: 0.030708 memory: 4565 loss: 0.000677 loss_kpt: 0.000677 acc_pose: 0.906142 2023/08/09 19:46:51 - mmengine - INFO - Epoch(train) [205][250/442] lr: 5.000000e-06 eta: 0:14:09 time: 0.340953 data_time: 0.030532 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.904777 2023/08/09 19:46:55 - mmengine - INFO - Epoch(train) [205][260/442] lr: 5.000000e-06 eta: 0:14:06 time: 0.342403 data_time: 0.030627 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.887252 2023/08/09 19:46:58 - mmengine - INFO - Epoch(train) [205][270/442] lr: 5.000000e-06 eta: 0:14:02 time: 0.344116 data_time: 0.030809 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.863595 2023/08/09 19:47:01 - mmengine - INFO - Epoch(train) [205][280/442] lr: 5.000000e-06 eta: 0:13:59 time: 0.343980 data_time: 0.030810 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.888714 2023/08/09 19:47:05 - mmengine - INFO - Epoch(train) [205][290/442] lr: 5.000000e-06 eta: 0:13:55 time: 0.343432 data_time: 0.030587 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.904980 2023/08/09 19:47:08 - mmengine - INFO - Epoch(train) [205][300/442] lr: 5.000000e-06 eta: 0:13:52 time: 0.341673 data_time: 0.030668 memory: 4565 loss: 0.000722 loss_kpt: 0.000722 acc_pose: 0.869180 2023/08/09 19:47:12 - mmengine - INFO - Epoch(train) [205][310/442] lr: 5.000000e-06 eta: 0:13:48 time: 0.341548 data_time: 0.031051 memory: 4565 loss: 0.000717 loss_kpt: 0.000717 acc_pose: 0.933778 2023/08/09 19:47:15 - mmengine - INFO - Epoch(train) [205][320/442] lr: 5.000000e-06 eta: 0:13:45 time: 0.341470 data_time: 0.030934 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.889080 2023/08/09 19:47:19 - mmengine - INFO - Epoch(train) [205][330/442] lr: 5.000000e-06 eta: 0:13:41 time: 0.343334 data_time: 0.031344 memory: 4565 loss: 0.000739 loss_kpt: 0.000739 acc_pose: 0.919637 2023/08/09 19:47:22 - mmengine - INFO - Epoch(train) [205][340/442] lr: 5.000000e-06 eta: 0:13:38 time: 0.346872 data_time: 0.034666 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.914037 2023/08/09 19:47:26 - mmengine - INFO - Epoch(train) [205][350/442] lr: 5.000000e-06 eta: 0:13:34 time: 0.346189 data_time: 0.034394 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.916884 2023/08/09 19:47:29 - mmengine - INFO - Epoch(train) [205][360/442] lr: 5.000000e-06 eta: 0:13:30 time: 0.344353 data_time: 0.033902 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.911694 2023/08/09 19:47:33 - mmengine - INFO - Epoch(train) [205][370/442] lr: 5.000000e-06 eta: 0:13:27 time: 0.346365 data_time: 0.033891 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.888304 2023/08/09 19:47:36 - mmengine - INFO - Epoch(train) [205][380/442] lr: 5.000000e-06 eta: 0:13:23 time: 0.346082 data_time: 0.033931 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.887219 2023/08/09 19:47:39 - mmengine - INFO - Epoch(train) [205][390/442] lr: 5.000000e-06 eta: 0:13:20 time: 0.343977 data_time: 0.030878 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.872754 2023/08/09 19:47:43 - mmengine - INFO - Epoch(train) [205][400/442] lr: 5.000000e-06 eta: 0:13:16 time: 0.345639 data_time: 0.031013 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.889160 2023/08/09 19:47:46 - mmengine - INFO - Epoch(train) [205][410/442] lr: 5.000000e-06 eta: 0:13:13 time: 0.346138 data_time: 0.031011 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.946296 2023/08/09 19:47:50 - mmengine - INFO - Epoch(train) [205][420/442] lr: 5.000000e-06 eta: 0:13:09 time: 0.343296 data_time: 0.031005 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.885458 2023/08/09 19:47:53 - mmengine - INFO - Epoch(train) [205][430/442] lr: 5.000000e-06 eta: 0:13:06 time: 0.343979 data_time: 0.030704 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.924247 2023/08/09 19:47:57 - mmengine - INFO - Epoch(train) [205][440/442] lr: 5.000000e-06 eta: 0:13:02 time: 0.343896 data_time: 0.030414 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.924136 2023/08/09 19:47:57 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:48:01 - mmengine - INFO - Epoch(train) [206][ 10/442] lr: 5.000000e-06 eta: 0:12:58 time: 0.349916 data_time: 0.034589 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.915534 2023/08/09 19:48:05 - mmengine - INFO - Epoch(train) [206][ 20/442] lr: 5.000000e-06 eta: 0:12:54 time: 0.353161 data_time: 0.034724 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.914851 2023/08/09 19:48:08 - mmengine - INFO - Epoch(train) [206][ 30/442] lr: 5.000000e-06 eta: 0:12:51 time: 0.353386 data_time: 0.034684 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.910898 2023/08/09 19:48:12 - mmengine - INFO - Epoch(train) [206][ 40/442] lr: 5.000000e-06 eta: 0:12:47 time: 0.353948 data_time: 0.034630 memory: 4565 loss: 0.000663 loss_kpt: 0.000663 acc_pose: 0.895503 2023/08/09 19:48:15 - mmengine - INFO - Epoch(train) [206][ 50/442] lr: 5.000000e-06 eta: 0:12:44 time: 0.355488 data_time: 0.034942 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.850716 2023/08/09 19:48:19 - mmengine - INFO - Epoch(train) [206][ 60/442] lr: 5.000000e-06 eta: 0:12:40 time: 0.349454 data_time: 0.030612 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.816389 2023/08/09 19:48:22 - mmengine - INFO - Epoch(train) [206][ 70/442] lr: 5.000000e-06 eta: 0:12:37 time: 0.348981 data_time: 0.030695 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.947413 2023/08/09 19:48:26 - mmengine - INFO - Epoch(train) [206][ 80/442] lr: 5.000000e-06 eta: 0:12:33 time: 0.350253 data_time: 0.030816 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.854010 2023/08/09 19:48:29 - mmengine - INFO - Epoch(train) [206][ 90/442] lr: 5.000000e-06 eta: 0:12:30 time: 0.354812 data_time: 0.030914 memory: 4565 loss: 0.000725 loss_kpt: 0.000725 acc_pose: 0.859196 2023/08/09 19:48:33 - mmengine - INFO - Epoch(train) [206][100/442] lr: 5.000000e-06 eta: 0:12:26 time: 0.355569 data_time: 0.031170 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.904071 2023/08/09 19:48:36 - mmengine - INFO - Epoch(train) [206][110/442] lr: 5.000000e-06 eta: 0:12:22 time: 0.355135 data_time: 0.030990 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.885241 2023/08/09 19:48:40 - mmengine - INFO - Epoch(train) [206][120/442] lr: 5.000000e-06 eta: 0:12:19 time: 0.353242 data_time: 0.030593 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.868124 2023/08/09 19:48:43 - mmengine - INFO - Epoch(train) [206][130/442] lr: 5.000000e-06 eta: 0:12:15 time: 0.352999 data_time: 0.030369 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.887699 2023/08/09 19:48:47 - mmengine - INFO - Epoch(train) [206][140/442] lr: 5.000000e-06 eta: 0:12:12 time: 0.353606 data_time: 0.030528 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.834772 2023/08/09 19:48:51 - mmengine - INFO - Epoch(train) [206][150/442] lr: 5.000000e-06 eta: 0:12:08 time: 0.358286 data_time: 0.030811 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.846314 2023/08/09 19:48:54 - mmengine - INFO - Epoch(train) [206][160/442] lr: 5.000000e-06 eta: 0:12:05 time: 0.360025 data_time: 0.031104 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.930577 2023/08/09 19:48:58 - mmengine - INFO - Epoch(train) [206][170/442] lr: 5.000000e-06 eta: 0:12:01 time: 0.360855 data_time: 0.031950 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.935330 2023/08/09 19:49:01 - mmengine - INFO - Epoch(train) [206][180/442] lr: 5.000000e-06 eta: 0:11:58 time: 0.360667 data_time: 0.032585 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.909218 2023/08/09 19:49:05 - mmengine - INFO - Epoch(train) [206][190/442] lr: 5.000000e-06 eta: 0:11:54 time: 0.357461 data_time: 0.032347 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.864371 2023/08/09 19:49:09 - mmengine - INFO - Epoch(train) [206][200/442] lr: 5.000000e-06 eta: 0:11:51 time: 0.354555 data_time: 0.032285 memory: 4565 loss: 0.000665 loss_kpt: 0.000665 acc_pose: 0.893955 2023/08/09 19:49:12 - mmengine - INFO - Epoch(train) [206][210/442] lr: 5.000000e-06 eta: 0:11:47 time: 0.355970 data_time: 0.032206 memory: 4565 loss: 0.000666 loss_kpt: 0.000666 acc_pose: 0.909529 2023/08/09 19:49:16 - mmengine - INFO - Epoch(train) [206][220/442] lr: 5.000000e-06 eta: 0:11:44 time: 0.355884 data_time: 0.031523 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.864607 2023/08/09 19:49:19 - mmengine - INFO - Epoch(train) [206][230/442] lr: 5.000000e-06 eta: 0:11:40 time: 0.357431 data_time: 0.030890 memory: 4565 loss: 0.000674 loss_kpt: 0.000674 acc_pose: 0.908135 2023/08/09 19:49:23 - mmengine - INFO - Epoch(train) [206][240/442] lr: 5.000000e-06 eta: 0:11:36 time: 0.355260 data_time: 0.030820 memory: 4565 loss: 0.000669 loss_kpt: 0.000669 acc_pose: 0.886425 2023/08/09 19:49:26 - mmengine - INFO - Epoch(train) [206][250/442] lr: 5.000000e-06 eta: 0:11:33 time: 0.352872 data_time: 0.030386 memory: 4565 loss: 0.000669 loss_kpt: 0.000669 acc_pose: 0.917181 2023/08/09 19:49:30 - mmengine - INFO - Epoch(train) [206][260/442] lr: 5.000000e-06 eta: 0:11:29 time: 0.350541 data_time: 0.030390 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.874259 2023/08/09 19:49:33 - mmengine - INFO - Epoch(train) [206][270/442] lr: 5.000000e-06 eta: 0:11:26 time: 0.351082 data_time: 0.030440 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.893661 2023/08/09 19:49:37 - mmengine - INFO - Epoch(train) [206][280/442] lr: 5.000000e-06 eta: 0:11:22 time: 0.354845 data_time: 0.031062 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.880892 2023/08/09 19:49:41 - mmengine - INFO - Epoch(train) [206][290/442] lr: 5.000000e-06 eta: 0:11:19 time: 0.355467 data_time: 0.031192 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.852675 2023/08/09 19:49:44 - mmengine - INFO - Epoch(train) [206][300/442] lr: 5.000000e-06 eta: 0:11:15 time: 0.355502 data_time: 0.031338 memory: 4565 loss: 0.000718 loss_kpt: 0.000718 acc_pose: 0.845849 2023/08/09 19:49:47 - mmengine - INFO - Epoch(train) [206][310/442] lr: 5.000000e-06 eta: 0:11:12 time: 0.354898 data_time: 0.031149 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.867391 2023/08/09 19:49:51 - mmengine - INFO - Epoch(train) [206][320/442] lr: 5.000000e-06 eta: 0:11:08 time: 0.355546 data_time: 0.031159 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.884009 2023/08/09 19:49:55 - mmengine - INFO - Epoch(train) [206][330/442] lr: 5.000000e-06 eta: 0:11:05 time: 0.354498 data_time: 0.030624 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.887438 2023/08/09 19:49:58 - mmengine - INFO - Epoch(train) [206][340/442] lr: 5.000000e-06 eta: 0:11:01 time: 0.356792 data_time: 0.031403 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.895867 2023/08/09 19:50:02 - mmengine - INFO - Epoch(train) [206][350/442] lr: 5.000000e-06 eta: 0:10:58 time: 0.358374 data_time: 0.031555 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.909203 2023/08/09 19:50:06 - mmengine - INFO - Epoch(train) [206][360/442] lr: 5.000000e-06 eta: 0:10:54 time: 0.362625 data_time: 0.031812 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.872809 2023/08/09 19:50:09 - mmengine - INFO - Epoch(train) [206][370/442] lr: 5.000000e-06 eta: 0:10:51 time: 0.364670 data_time: 0.031766 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.869277 2023/08/09 19:50:13 - mmengine - INFO - Epoch(train) [206][380/442] lr: 5.000000e-06 eta: 0:10:47 time: 0.361530 data_time: 0.031862 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.871537 2023/08/09 19:50:16 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:50:16 - mmengine - INFO - Epoch(train) [206][390/442] lr: 5.000000e-06 eta: 0:10:43 time: 0.361814 data_time: 0.031511 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.919196 2023/08/09 19:50:20 - mmengine - INFO - Epoch(train) [206][400/442] lr: 5.000000e-06 eta: 0:10:40 time: 0.362196 data_time: 0.031357 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.880730 2023/08/09 19:50:24 - mmengine - INFO - Epoch(train) [206][410/442] lr: 5.000000e-06 eta: 0:10:36 time: 0.367408 data_time: 0.031475 memory: 4565 loss: 0.000673 loss_kpt: 0.000673 acc_pose: 0.895817 2023/08/09 19:50:28 - mmengine - INFO - Epoch(train) [206][420/442] lr: 5.000000e-06 eta: 0:10:33 time: 0.372161 data_time: 0.031768 memory: 4565 loss: 0.000672 loss_kpt: 0.000672 acc_pose: 0.833618 2023/08/09 19:50:32 - mmengine - INFO - Epoch(train) [206][430/442] lr: 5.000000e-06 eta: 0:10:29 time: 0.379247 data_time: 0.032170 memory: 4565 loss: 0.000665 loss_kpt: 0.000665 acc_pose: 0.924430 2023/08/09 19:50:36 - mmengine - INFO - Epoch(train) [206][440/442] lr: 5.000000e-06 eta: 0:10:26 time: 0.385546 data_time: 0.032079 memory: 4565 loss: 0.000669 loss_kpt: 0.000669 acc_pose: 0.837603 2023/08/09 19:50:36 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:50:40 - mmengine - INFO - Epoch(train) [207][ 10/442] lr: 5.000000e-06 eta: 0:10:22 time: 0.387821 data_time: 0.036222 memory: 4565 loss: 0.000682 loss_kpt: 0.000682 acc_pose: 0.889541 2023/08/09 19:50:44 - mmengine - INFO - Epoch(train) [207][ 20/442] lr: 5.000000e-06 eta: 0:10:18 time: 0.379720 data_time: 0.035864 memory: 4565 loss: 0.000682 loss_kpt: 0.000682 acc_pose: 0.874614 2023/08/09 19:50:47 - mmengine - INFO - Epoch(train) [207][ 30/442] lr: 5.000000e-06 eta: 0:10:14 time: 0.371981 data_time: 0.035593 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.916529 2023/08/09 19:50:51 - mmengine - INFO - Epoch(train) [207][ 40/442] lr: 5.000000e-06 eta: 0:10:11 time: 0.363570 data_time: 0.035160 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.889377 2023/08/09 19:50:54 - mmengine - INFO - Epoch(train) [207][ 50/442] lr: 5.000000e-06 eta: 0:10:07 time: 0.356752 data_time: 0.035401 memory: 4565 loss: 0.000674 loss_kpt: 0.000674 acc_pose: 0.949524 2023/08/09 19:50:58 - mmengine - INFO - Epoch(train) [207][ 60/442] lr: 5.000000e-06 eta: 0:10:04 time: 0.355375 data_time: 0.030976 memory: 4565 loss: 0.000678 loss_kpt: 0.000678 acc_pose: 0.895307 2023/08/09 19:51:02 - mmengine - INFO - Epoch(train) [207][ 70/442] lr: 5.000000e-06 eta: 0:10:00 time: 0.359027 data_time: 0.031193 memory: 4565 loss: 0.000681 loss_kpt: 0.000681 acc_pose: 0.888427 2023/08/09 19:51:05 - mmengine - INFO - Epoch(train) [207][ 80/442] lr: 5.000000e-06 eta: 0:09:57 time: 0.359653 data_time: 0.031221 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.873997 2023/08/09 19:51:09 - mmengine - INFO - Epoch(train) [207][ 90/442] lr: 5.000000e-06 eta: 0:09:53 time: 0.361312 data_time: 0.031786 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.924779 2023/08/09 19:51:12 - mmengine - INFO - Epoch(train) [207][100/442] lr: 5.000000e-06 eta: 0:09:50 time: 0.361459 data_time: 0.031444 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.915518 2023/08/09 19:51:16 - mmengine - INFO - Epoch(train) [207][110/442] lr: 5.000000e-06 eta: 0:09:46 time: 0.358242 data_time: 0.031850 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.885134 2023/08/09 19:51:19 - mmengine - INFO - Epoch(train) [207][120/442] lr: 5.000000e-06 eta: 0:09:43 time: 0.353680 data_time: 0.031501 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.914270 2023/08/09 19:51:23 - mmengine - INFO - Epoch(train) [207][130/442] lr: 5.000000e-06 eta: 0:09:39 time: 0.354079 data_time: 0.031479 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.822943 2023/08/09 19:51:27 - mmengine - INFO - Epoch(train) [207][140/442] lr: 5.000000e-06 eta: 0:09:36 time: 0.354169 data_time: 0.031221 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.924962 2023/08/09 19:51:30 - mmengine - INFO - Epoch(train) [207][150/442] lr: 5.000000e-06 eta: 0:09:32 time: 0.355844 data_time: 0.031760 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.834771 2023/08/09 19:51:34 - mmengine - INFO - Epoch(train) [207][160/442] lr: 5.000000e-06 eta: 0:09:29 time: 0.356112 data_time: 0.031383 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.916894 2023/08/09 19:51:37 - mmengine - INFO - Epoch(train) [207][170/442] lr: 5.000000e-06 eta: 0:09:25 time: 0.356008 data_time: 0.031345 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.864077 2023/08/09 19:51:41 - mmengine - INFO - Epoch(train) [207][180/442] lr: 5.000000e-06 eta: 0:09:21 time: 0.355125 data_time: 0.031233 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.879648 2023/08/09 19:51:44 - mmengine - INFO - Epoch(train) [207][190/442] lr: 5.000000e-06 eta: 0:09:18 time: 0.353448 data_time: 0.030990 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.912236 2023/08/09 19:51:48 - mmengine - INFO - Epoch(train) [207][200/442] lr: 5.000000e-06 eta: 0:09:14 time: 0.357614 data_time: 0.030838 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.951839 2023/08/09 19:51:52 - mmengine - INFO - Epoch(train) [207][210/442] lr: 5.000000e-06 eta: 0:09:11 time: 0.359721 data_time: 0.031037 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.867585 2023/08/09 19:51:55 - mmengine - INFO - Epoch(train) [207][220/442] lr: 5.000000e-06 eta: 0:09:07 time: 0.359982 data_time: 0.031181 memory: 4565 loss: 0.000677 loss_kpt: 0.000677 acc_pose: 0.858760 2023/08/09 19:51:59 - mmengine - INFO - Epoch(train) [207][230/442] lr: 5.000000e-06 eta: 0:09:04 time: 0.359606 data_time: 0.031244 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.909704 2023/08/09 19:52:03 - mmengine - INFO - Epoch(train) [207][240/442] lr: 5.000000e-06 eta: 0:09:00 time: 0.364804 data_time: 0.031904 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.874000 2023/08/09 19:52:06 - mmengine - INFO - Epoch(train) [207][250/442] lr: 5.000000e-06 eta: 0:08:57 time: 0.363646 data_time: 0.031825 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.878404 2023/08/09 19:52:10 - mmengine - INFO - Epoch(train) [207][260/442] lr: 5.000000e-06 eta: 0:08:53 time: 0.362129 data_time: 0.031730 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.869558 2023/08/09 19:52:13 - mmengine - INFO - Epoch(train) [207][270/442] lr: 5.000000e-06 eta: 0:08:50 time: 0.362169 data_time: 0.031818 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.920729 2023/08/09 19:52:17 - mmengine - INFO - Epoch(train) [207][280/442] lr: 5.000000e-06 eta: 0:08:46 time: 0.364472 data_time: 0.031863 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.946463 2023/08/09 19:52:21 - mmengine - INFO - Epoch(train) [207][290/442] lr: 5.000000e-06 eta: 0:08:43 time: 0.360912 data_time: 0.031413 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.919031 2023/08/09 19:52:25 - mmengine - INFO - Epoch(train) [207][300/442] lr: 5.000000e-06 eta: 0:08:39 time: 0.363616 data_time: 0.031622 memory: 4565 loss: 0.000713 loss_kpt: 0.000713 acc_pose: 0.840408 2023/08/09 19:52:28 - mmengine - INFO - Epoch(train) [207][310/442] lr: 5.000000e-06 eta: 0:08:35 time: 0.369913 data_time: 0.031795 memory: 4565 loss: 0.000719 loss_kpt: 0.000719 acc_pose: 0.848542 2023/08/09 19:52:32 - mmengine - INFO - Epoch(train) [207][320/442] lr: 5.000000e-06 eta: 0:08:32 time: 0.375205 data_time: 0.031998 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.918845 2023/08/09 19:52:36 - mmengine - INFO - Epoch(train) [207][330/442] lr: 5.000000e-06 eta: 0:08:28 time: 0.373698 data_time: 0.032215 memory: 4565 loss: 0.000703 loss_kpt: 0.000703 acc_pose: 0.884243 2023/08/09 19:52:39 - mmengine - INFO - Epoch(train) [207][340/442] lr: 5.000000e-06 eta: 0:08:25 time: 0.373207 data_time: 0.032308 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.914146 2023/08/09 19:52:43 - mmengine - INFO - Epoch(train) [207][350/442] lr: 5.000000e-06 eta: 0:08:21 time: 0.370048 data_time: 0.031724 memory: 4565 loss: 0.000677 loss_kpt: 0.000677 acc_pose: 0.850651 2023/08/09 19:52:47 - mmengine - INFO - Epoch(train) [207][360/442] lr: 5.000000e-06 eta: 0:08:18 time: 0.362105 data_time: 0.031495 memory: 4565 loss: 0.000668 loss_kpt: 0.000668 acc_pose: 0.869682 2023/08/09 19:52:50 - mmengine - INFO - Epoch(train) [207][370/442] lr: 5.000000e-06 eta: 0:08:14 time: 0.356316 data_time: 0.031407 memory: 4565 loss: 0.000665 loss_kpt: 0.000665 acc_pose: 0.905740 2023/08/09 19:52:54 - mmengine - INFO - Epoch(train) [207][380/442] lr: 5.000000e-06 eta: 0:08:11 time: 0.356519 data_time: 0.031217 memory: 4565 loss: 0.000670 loss_kpt: 0.000670 acc_pose: 0.864103 2023/08/09 19:52:57 - mmengine - INFO - Epoch(train) [207][390/442] lr: 5.000000e-06 eta: 0:08:07 time: 0.356513 data_time: 0.031158 memory: 4565 loss: 0.000670 loss_kpt: 0.000670 acc_pose: 0.962262 2023/08/09 19:53:01 - mmengine - INFO - Epoch(train) [207][400/442] lr: 5.000000e-06 eta: 0:08:04 time: 0.353280 data_time: 0.031765 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.814536 2023/08/09 19:53:04 - mmengine - INFO - Epoch(train) [207][410/442] lr: 5.000000e-06 eta: 0:08:00 time: 0.356189 data_time: 0.031666 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.854593 2023/08/09 19:53:08 - mmengine - INFO - Epoch(train) [207][420/442] lr: 5.000000e-06 eta: 0:07:57 time: 0.357261 data_time: 0.031574 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.917643 2023/08/09 19:53:11 - mmengine - INFO - Epoch(train) [207][430/442] lr: 5.000000e-06 eta: 0:07:53 time: 0.356758 data_time: 0.031817 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.860109 2023/08/09 19:53:15 - mmengine - INFO - Epoch(train) [207][440/442] lr: 5.000000e-06 eta: 0:07:49 time: 0.357028 data_time: 0.031647 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.833883 2023/08/09 19:53:16 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:53:19 - mmengine - INFO - Epoch(train) [208][ 10/442] lr: 5.000000e-06 eta: 0:07:45 time: 0.358455 data_time: 0.035168 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.886204 2023/08/09 19:53:23 - mmengine - INFO - Epoch(train) [208][ 20/442] lr: 5.000000e-06 eta: 0:07:42 time: 0.360056 data_time: 0.035092 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.868244 2023/08/09 19:53:27 - mmengine - INFO - Epoch(train) [208][ 30/442] lr: 5.000000e-06 eta: 0:07:38 time: 0.361106 data_time: 0.034913 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.907831 2023/08/09 19:53:30 - mmengine - INFO - Epoch(train) [208][ 40/442] lr: 5.000000e-06 eta: 0:07:35 time: 0.361902 data_time: 0.034760 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.858098 2023/08/09 19:53:34 - mmengine - INFO - Epoch(train) [208][ 50/442] lr: 5.000000e-06 eta: 0:07:31 time: 0.365360 data_time: 0.038517 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.904899 2023/08/09 19:53:37 - mmengine - INFO - Epoch(train) [208][ 60/442] lr: 5.000000e-06 eta: 0:07:28 time: 0.360261 data_time: 0.034224 memory: 4565 loss: 0.000684 loss_kpt: 0.000684 acc_pose: 0.918299 2023/08/09 19:53:41 - mmengine - INFO - Epoch(train) [208][ 70/442] lr: 5.000000e-06 eta: 0:07:24 time: 0.360204 data_time: 0.034342 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.919789 2023/08/09 19:53:45 - mmengine - INFO - Epoch(train) [208][ 80/442] lr: 5.000000e-06 eta: 0:07:20 time: 0.360125 data_time: 0.034480 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.946089 2023/08/09 19:53:48 - mmengine - INFO - Epoch(train) [208][ 90/442] lr: 5.000000e-06 eta: 0:07:17 time: 0.361106 data_time: 0.034383 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.938439 2023/08/09 19:53:52 - mmengine - INFO - Epoch(train) [208][100/442] lr: 5.000000e-06 eta: 0:07:13 time: 0.357940 data_time: 0.031189 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.897063 2023/08/09 19:53:55 - mmengine - INFO - Epoch(train) [208][110/442] lr: 5.000000e-06 eta: 0:07:10 time: 0.357194 data_time: 0.030964 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.947162 2023/08/09 19:53:59 - mmengine - INFO - Epoch(train) [208][120/442] lr: 5.000000e-06 eta: 0:07:06 time: 0.353510 data_time: 0.031062 memory: 4565 loss: 0.000676 loss_kpt: 0.000676 acc_pose: 0.951244 2023/08/09 19:54:03 - mmengine - INFO - Epoch(train) [208][130/442] lr: 5.000000e-06 eta: 0:07:03 time: 0.356347 data_time: 0.031006 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.893088 2023/08/09 19:54:06 - mmengine - INFO - Epoch(train) [208][140/442] lr: 5.000000e-06 eta: 0:06:59 time: 0.355148 data_time: 0.031153 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.898998 2023/08/09 19:54:10 - mmengine - INFO - Epoch(train) [208][150/442] lr: 5.000000e-06 eta: 0:06:56 time: 0.354950 data_time: 0.030928 memory: 4565 loss: 0.000678 loss_kpt: 0.000678 acc_pose: 0.932066 2023/08/09 19:54:13 - mmengine - INFO - Epoch(train) [208][160/442] lr: 5.000000e-06 eta: 0:06:52 time: 0.355659 data_time: 0.031039 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.925540 2023/08/09 19:54:17 - mmengine - INFO - Epoch(train) [208][170/442] lr: 5.000000e-06 eta: 0:06:49 time: 0.355513 data_time: 0.030779 memory: 4565 loss: 0.000681 loss_kpt: 0.000681 acc_pose: 0.909554 2023/08/09 19:54:20 - mmengine - INFO - Epoch(train) [208][180/442] lr: 5.000000e-06 eta: 0:06:45 time: 0.350987 data_time: 0.030683 memory: 4565 loss: 0.000663 loss_kpt: 0.000663 acc_pose: 0.906634 2023/08/09 19:54:24 - mmengine - INFO - Epoch(train) [208][190/442] lr: 5.000000e-06 eta: 0:06:42 time: 0.350205 data_time: 0.030419 memory: 4565 loss: 0.000674 loss_kpt: 0.000674 acc_pose: 0.924624 2023/08/09 19:54:27 - mmengine - INFO - Epoch(train) [208][200/442] lr: 5.000000e-06 eta: 0:06:38 time: 0.351513 data_time: 0.030436 memory: 4565 loss: 0.000672 loss_kpt: 0.000672 acc_pose: 0.872343 2023/08/09 19:54:31 - mmengine - INFO - Epoch(train) [208][210/442] lr: 5.000000e-06 eta: 0:06:34 time: 0.355236 data_time: 0.033821 memory: 4565 loss: 0.000678 loss_kpt: 0.000678 acc_pose: 0.906629 2023/08/09 19:54:34 - mmengine - INFO - Epoch(train) [208][220/442] lr: 5.000000e-06 eta: 0:06:31 time: 0.357574 data_time: 0.034211 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.911103 2023/08/09 19:54:38 - mmengine - INFO - Epoch(train) [208][230/442] lr: 5.000000e-06 eta: 0:06:27 time: 0.358409 data_time: 0.034165 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.910475 2023/08/09 19:54:42 - mmengine - INFO - Epoch(train) [208][240/442] lr: 5.000000e-06 eta: 0:06:24 time: 0.360713 data_time: 0.034271 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.947974 2023/08/09 19:54:45 - mmengine - INFO - Epoch(train) [208][250/442] lr: 5.000000e-06 eta: 0:06:20 time: 0.359305 data_time: 0.034111 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.861606 2023/08/09 19:54:49 - mmengine - INFO - Epoch(train) [208][260/442] lr: 5.000000e-06 eta: 0:06:17 time: 0.356657 data_time: 0.030992 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.890920 2023/08/09 19:54:52 - mmengine - INFO - Epoch(train) [208][270/442] lr: 5.000000e-06 eta: 0:06:13 time: 0.355633 data_time: 0.030911 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.881415 2023/08/09 19:54:56 - mmengine - INFO - Epoch(train) [208][280/442] lr: 5.000000e-06 eta: 0:06:10 time: 0.358804 data_time: 0.031117 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.923432 2023/08/09 19:54:59 - mmengine - INFO - Epoch(train) [208][290/442] lr: 5.000000e-06 eta: 0:06:06 time: 0.356200 data_time: 0.030884 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.903074 2023/08/09 19:55:03 - mmengine - INFO - Epoch(train) [208][300/442] lr: 5.000000e-06 eta: 0:06:03 time: 0.355883 data_time: 0.031613 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.951814 2023/08/09 19:55:06 - mmengine - INFO - Epoch(train) [208][310/442] lr: 5.000000e-06 eta: 0:05:59 time: 0.354215 data_time: 0.031246 memory: 4565 loss: 0.000670 loss_kpt: 0.000670 acc_pose: 0.926741 2023/08/09 19:55:10 - mmengine - INFO - Epoch(train) [208][320/442] lr: 5.000000e-06 eta: 0:05:56 time: 0.354383 data_time: 0.031104 memory: 4565 loss: 0.000682 loss_kpt: 0.000682 acc_pose: 0.941307 2023/08/09 19:55:14 - mmengine - INFO - Epoch(train) [208][330/442] lr: 5.000000e-06 eta: 0:05:52 time: 0.351944 data_time: 0.030730 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.871815 2023/08/09 19:55:17 - mmengine - INFO - Epoch(train) [208][340/442] lr: 5.000000e-06 eta: 0:05:48 time: 0.352512 data_time: 0.030938 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.943097 2023/08/09 19:55:21 - mmengine - INFO - Epoch(train) [208][350/442] lr: 5.000000e-06 eta: 0:05:45 time: 0.353187 data_time: 0.030254 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.914071 2023/08/09 19:55:24 - mmengine - INFO - Epoch(train) [208][360/442] lr: 5.000000e-06 eta: 0:05:41 time: 0.353603 data_time: 0.030336 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.941758 2023/08/09 19:55:28 - mmengine - INFO - Epoch(train) [208][370/442] lr: 5.000000e-06 eta: 0:05:38 time: 0.352178 data_time: 0.030125 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.842207 2023/08/09 19:55:31 - mmengine - INFO - Epoch(train) [208][380/442] lr: 5.000000e-06 eta: 0:05:34 time: 0.353675 data_time: 0.033570 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.923629 2023/08/09 19:55:35 - mmengine - INFO - Epoch(train) [208][390/442] lr: 5.000000e-06 eta: 0:05:31 time: 0.353480 data_time: 0.033411 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.939299 2023/08/09 19:55:38 - mmengine - INFO - Epoch(train) [208][400/442] lr: 5.000000e-06 eta: 0:05:27 time: 0.353373 data_time: 0.033466 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.893621 2023/08/09 19:55:42 - mmengine - INFO - Epoch(train) [208][410/442] lr: 5.000000e-06 eta: 0:05:24 time: 0.354761 data_time: 0.033936 memory: 4565 loss: 0.000693 loss_kpt: 0.000693 acc_pose: 0.836025 2023/08/09 19:55:45 - mmengine - INFO - Epoch(train) [208][420/442] lr: 5.000000e-06 eta: 0:05:20 time: 0.354799 data_time: 0.034078 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.872869 2023/08/09 19:55:49 - mmengine - INFO - Epoch(train) [208][430/442] lr: 5.000000e-06 eta: 0:05:17 time: 0.351437 data_time: 0.030670 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.874588 2023/08/09 19:55:53 - mmengine - INFO - Epoch(train) [208][440/442] lr: 5.000000e-06 eta: 0:05:13 time: 0.353728 data_time: 0.030788 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.844827 2023/08/09 19:55:53 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:55:57 - mmengine - INFO - Epoch(train) [209][ 10/442] lr: 5.000000e-06 eta: 0:05:09 time: 0.355857 data_time: 0.033857 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.883284 2023/08/09 19:56:00 - mmengine - INFO - Epoch(train) [209][ 20/442] lr: 5.000000e-06 eta: 0:05:05 time: 0.356357 data_time: 0.033854 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.890601 2023/08/09 19:56:04 - mmengine - INFO - Epoch(train) [209][ 30/442] lr: 5.000000e-06 eta: 0:05:02 time: 0.358622 data_time: 0.034215 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.877821 2023/08/09 19:56:08 - mmengine - INFO - Epoch(train) [209][ 40/442] lr: 5.000000e-06 eta: 0:04:58 time: 0.355711 data_time: 0.034191 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.865361 2023/08/09 19:56:11 - mmengine - INFO - Epoch(train) [209][ 50/442] lr: 5.000000e-06 eta: 0:04:55 time: 0.356527 data_time: 0.034463 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.861240 2023/08/09 19:56:14 - mmengine - INFO - Epoch(train) [209][ 60/442] lr: 5.000000e-06 eta: 0:04:51 time: 0.351218 data_time: 0.030546 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.882452 2023/08/09 19:56:16 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:56:18 - mmengine - INFO - Epoch(train) [209][ 70/442] lr: 5.000000e-06 eta: 0:04:48 time: 0.349608 data_time: 0.030430 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.920929 2023/08/09 19:56:22 - mmengine - INFO - Epoch(train) [209][ 80/442] lr: 5.000000e-06 eta: 0:04:44 time: 0.349468 data_time: 0.030197 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.823396 2023/08/09 19:56:25 - mmengine - INFO - Epoch(train) [209][ 90/442] lr: 5.000000e-06 eta: 0:04:41 time: 0.354116 data_time: 0.030095 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.862544 2023/08/09 19:56:29 - mmengine - INFO - Epoch(train) [209][100/442] lr: 5.000000e-06 eta: 0:04:37 time: 0.356062 data_time: 0.030256 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.901890 2023/08/09 19:56:32 - mmengine - INFO - Epoch(train) [209][110/442] lr: 5.000000e-06 eta: 0:04:33 time: 0.357104 data_time: 0.030227 memory: 4565 loss: 0.000706 loss_kpt: 0.000706 acc_pose: 0.924728 2023/08/09 19:56:36 - mmengine - INFO - Epoch(train) [209][120/442] lr: 5.000000e-06 eta: 0:04:30 time: 0.357001 data_time: 0.030220 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.968928 2023/08/09 19:56:39 - mmengine - INFO - Epoch(train) [209][130/442] lr: 5.000000e-06 eta: 0:04:26 time: 0.355051 data_time: 0.030103 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.896668 2023/08/09 19:56:43 - mmengine - INFO - Epoch(train) [209][140/442] lr: 5.000000e-06 eta: 0:04:23 time: 0.351786 data_time: 0.030392 memory: 4565 loss: 0.000712 loss_kpt: 0.000712 acc_pose: 0.937462 2023/08/09 19:56:46 - mmengine - INFO - Epoch(train) [209][150/442] lr: 5.000000e-06 eta: 0:04:19 time: 0.351731 data_time: 0.030639 memory: 4565 loss: 0.000723 loss_kpt: 0.000723 acc_pose: 0.930784 2023/08/09 19:56:50 - mmengine - INFO - Epoch(train) [209][160/442] lr: 5.000000e-06 eta: 0:04:16 time: 0.352910 data_time: 0.031075 memory: 4565 loss: 0.000728 loss_kpt: 0.000728 acc_pose: 0.833730 2023/08/09 19:56:53 - mmengine - INFO - Epoch(train) [209][170/442] lr: 5.000000e-06 eta: 0:04:12 time: 0.352788 data_time: 0.030983 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.886160 2023/08/09 19:56:57 - mmengine - INFO - Epoch(train) [209][180/442] lr: 5.000000e-06 eta: 0:04:09 time: 0.352640 data_time: 0.031051 memory: 4565 loss: 0.000733 loss_kpt: 0.000733 acc_pose: 0.915081 2023/08/09 19:57:01 - mmengine - INFO - Epoch(train) [209][190/442] lr: 5.000000e-06 eta: 0:04:05 time: 0.355773 data_time: 0.030802 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.904931 2023/08/09 19:57:04 - mmengine - INFO - Epoch(train) [209][200/442] lr: 5.000000e-06 eta: 0:04:02 time: 0.353956 data_time: 0.030385 memory: 4565 loss: 0.000701 loss_kpt: 0.000701 acc_pose: 0.852798 2023/08/09 19:57:08 - mmengine - INFO - Epoch(train) [209][210/442] lr: 5.000000e-06 eta: 0:03:58 time: 0.352750 data_time: 0.029982 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.909816 2023/08/09 19:57:11 - mmengine - INFO - Epoch(train) [209][220/442] lr: 5.000000e-06 eta: 0:03:55 time: 0.358341 data_time: 0.030318 memory: 4565 loss: 0.000681 loss_kpt: 0.000681 acc_pose: 0.749692 2023/08/09 19:57:15 - mmengine - INFO - Epoch(train) [209][230/442] lr: 5.000000e-06 eta: 0:03:51 time: 0.360736 data_time: 0.030380 memory: 4565 loss: 0.000678 loss_kpt: 0.000678 acc_pose: 0.899872 2023/08/09 19:57:19 - mmengine - INFO - Epoch(train) [209][240/442] lr: 5.000000e-06 eta: 0:03:47 time: 0.359164 data_time: 0.033392 memory: 4565 loss: 0.000673 loss_kpt: 0.000673 acc_pose: 0.886180 2023/08/09 19:57:22 - mmengine - INFO - Epoch(train) [209][250/442] lr: 5.000000e-06 eta: 0:03:44 time: 0.359732 data_time: 0.033635 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.942070 2023/08/09 19:57:26 - mmengine - INFO - Epoch(train) [209][260/442] lr: 5.000000e-06 eta: 0:03:40 time: 0.358411 data_time: 0.033531 memory: 4565 loss: 0.000696 loss_kpt: 0.000696 acc_pose: 0.877625 2023/08/09 19:57:29 - mmengine - INFO - Epoch(train) [209][270/442] lr: 5.000000e-06 eta: 0:03:37 time: 0.354281 data_time: 0.033200 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.865772 2023/08/09 19:57:33 - mmengine - INFO - Epoch(train) [209][280/442] lr: 5.000000e-06 eta: 0:03:33 time: 0.355176 data_time: 0.033197 memory: 4565 loss: 0.000692 loss_kpt: 0.000692 acc_pose: 0.861884 2023/08/09 19:57:36 - mmengine - INFO - Epoch(train) [209][290/442] lr: 5.000000e-06 eta: 0:03:30 time: 0.354762 data_time: 0.030559 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.903190 2023/08/09 19:57:40 - mmengine - INFO - Epoch(train) [209][300/442] lr: 5.000000e-06 eta: 0:03:26 time: 0.353921 data_time: 0.030302 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.922137 2023/08/09 19:57:43 - mmengine - INFO - Epoch(train) [209][310/442] lr: 5.000000e-06 eta: 0:03:23 time: 0.354268 data_time: 0.030472 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.933284 2023/08/09 19:57:47 - mmengine - INFO - Epoch(train) [209][320/442] lr: 5.000000e-06 eta: 0:03:19 time: 0.353535 data_time: 0.030985 memory: 4565 loss: 0.000689 loss_kpt: 0.000689 acc_pose: 0.907418 2023/08/09 19:57:50 - mmengine - INFO - Epoch(train) [209][330/442] lr: 5.000000e-06 eta: 0:03:16 time: 0.351718 data_time: 0.031275 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.873599 2023/08/09 19:57:54 - mmengine - INFO - Epoch(train) [209][340/442] lr: 5.000000e-06 eta: 0:03:12 time: 0.351665 data_time: 0.031008 memory: 4565 loss: 0.000676 loss_kpt: 0.000676 acc_pose: 0.918899 2023/08/09 19:57:58 - mmengine - INFO - Epoch(train) [209][350/442] lr: 5.000000e-06 eta: 0:03:09 time: 0.355553 data_time: 0.031312 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.891531 2023/08/09 19:58:01 - mmengine - INFO - Epoch(train) [209][360/442] lr: 5.000000e-06 eta: 0:03:05 time: 0.356217 data_time: 0.031211 memory: 4565 loss: 0.000665 loss_kpt: 0.000665 acc_pose: 0.952854 2023/08/09 19:58:05 - mmengine - INFO - Epoch(train) [209][370/442] lr: 5.000000e-06 eta: 0:03:01 time: 0.355242 data_time: 0.030700 memory: 4565 loss: 0.000659 loss_kpt: 0.000659 acc_pose: 0.966630 2023/08/09 19:58:08 - mmengine - INFO - Epoch(train) [209][380/442] lr: 5.000000e-06 eta: 0:02:58 time: 0.358320 data_time: 0.033420 memory: 4565 loss: 0.000659 loss_kpt: 0.000659 acc_pose: 0.929769 2023/08/09 19:58:12 - mmengine - INFO - Epoch(train) [209][390/442] lr: 5.000000e-06 eta: 0:02:54 time: 0.356098 data_time: 0.033350 memory: 4565 loss: 0.000672 loss_kpt: 0.000672 acc_pose: 0.892196 2023/08/09 19:58:15 - mmengine - INFO - Epoch(train) [209][400/442] lr: 5.000000e-06 eta: 0:02:51 time: 0.353483 data_time: 0.033264 memory: 4565 loss: 0.000686 loss_kpt: 0.000686 acc_pose: 0.917632 2023/08/09 19:58:19 - mmengine - INFO - Epoch(train) [209][410/442] lr: 5.000000e-06 eta: 0:02:47 time: 0.353288 data_time: 0.033313 memory: 4565 loss: 0.000697 loss_kpt: 0.000697 acc_pose: 0.872939 2023/08/09 19:58:22 - mmengine - INFO - Epoch(train) [209][420/442] lr: 5.000000e-06 eta: 0:02:44 time: 0.355679 data_time: 0.033460 memory: 4565 loss: 0.000691 loss_kpt: 0.000691 acc_pose: 0.939366 2023/08/09 19:58:26 - mmengine - INFO - Epoch(train) [209][430/442] lr: 5.000000e-06 eta: 0:02:40 time: 0.351964 data_time: 0.030537 memory: 4565 loss: 0.000681 loss_kpt: 0.000681 acc_pose: 0.865504 2023/08/09 19:58:29 - mmengine - INFO - Epoch(train) [209][440/442] lr: 5.000000e-06 eta: 0:02:37 time: 0.352602 data_time: 0.030529 memory: 4565 loss: 0.000669 loss_kpt: 0.000669 acc_pose: 0.878813 2023/08/09 19:58:30 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 19:58:34 - mmengine - INFO - Epoch(train) [210][ 10/442] lr: 5.000000e-06 eta: 0:02:32 time: 0.354384 data_time: 0.034209 memory: 4565 loss: 0.000671 loss_kpt: 0.000671 acc_pose: 0.898581 2023/08/09 19:58:37 - mmengine - INFO - Epoch(train) [210][ 20/442] lr: 5.000000e-06 eta: 0:02:29 time: 0.354000 data_time: 0.034356 memory: 4565 loss: 0.000667 loss_kpt: 0.000667 acc_pose: 0.919668 2023/08/09 19:58:41 - mmengine - INFO - Epoch(train) [210][ 30/442] lr: 5.000000e-06 eta: 0:02:25 time: 0.353462 data_time: 0.034257 memory: 4565 loss: 0.000681 loss_kpt: 0.000681 acc_pose: 0.930043 2023/08/09 19:58:44 - mmengine - INFO - Epoch(train) [210][ 40/442] lr: 5.000000e-06 eta: 0:02:22 time: 0.354939 data_time: 0.034310 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.906620 2023/08/09 19:58:48 - mmengine - INFO - Epoch(train) [210][ 50/442] lr: 5.000000e-06 eta: 0:02:18 time: 0.357143 data_time: 0.034771 memory: 4565 loss: 0.000704 loss_kpt: 0.000704 acc_pose: 0.848100 2023/08/09 19:58:52 - mmengine - INFO - Epoch(train) [210][ 60/442] lr: 5.000000e-06 eta: 0:02:15 time: 0.354263 data_time: 0.030664 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.925594 2023/08/09 19:58:55 - mmengine - INFO - Epoch(train) [210][ 70/442] lr: 5.000000e-06 eta: 0:02:11 time: 0.357193 data_time: 0.030610 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.890602 2023/08/09 19:58:59 - mmengine - INFO - Epoch(train) [210][ 80/442] lr: 5.000000e-06 eta: 0:02:08 time: 0.356701 data_time: 0.030585 memory: 4565 loss: 0.000680 loss_kpt: 0.000680 acc_pose: 0.911433 2023/08/09 19:59:02 - mmengine - INFO - Epoch(train) [210][ 90/442] lr: 5.000000e-06 eta: 0:02:04 time: 0.359793 data_time: 0.030503 memory: 4565 loss: 0.000683 loss_kpt: 0.000683 acc_pose: 0.850635 2023/08/09 19:59:06 - mmengine - INFO - Epoch(train) [210][100/442] lr: 5.000000e-06 eta: 0:02:01 time: 0.359994 data_time: 0.030545 memory: 4565 loss: 0.000671 loss_kpt: 0.000671 acc_pose: 0.931683 2023/08/09 19:59:10 - mmengine - INFO - Epoch(train) [210][110/442] lr: 5.000000e-06 eta: 0:01:57 time: 0.360126 data_time: 0.030600 memory: 4565 loss: 0.000673 loss_kpt: 0.000673 acc_pose: 0.926089 2023/08/09 19:59:13 - mmengine - INFO - Epoch(train) [210][120/442] lr: 5.000000e-06 eta: 0:01:53 time: 0.356659 data_time: 0.030539 memory: 4565 loss: 0.000672 loss_kpt: 0.000672 acc_pose: 0.889305 2023/08/09 19:59:17 - mmengine - INFO - Epoch(train) [210][130/442] lr: 5.000000e-06 eta: 0:01:50 time: 0.356283 data_time: 0.030447 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.910012 2023/08/09 19:59:20 - mmengine - INFO - Epoch(train) [210][140/442] lr: 5.000000e-06 eta: 0:01:46 time: 0.351134 data_time: 0.030453 memory: 4565 loss: 0.000669 loss_kpt: 0.000669 acc_pose: 0.903819 2023/08/09 19:59:24 - mmengine - INFO - Epoch(train) [210][150/442] lr: 5.000000e-06 eta: 0:01:43 time: 0.350505 data_time: 0.030470 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.873428 2023/08/09 19:59:27 - mmengine - INFO - Epoch(train) [210][160/442] lr: 5.000000e-06 eta: 0:01:39 time: 0.350109 data_time: 0.030582 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.938542 2023/08/09 19:59:31 - mmengine - INFO - Epoch(train) [210][170/442] lr: 5.000000e-06 eta: 0:01:36 time: 0.351877 data_time: 0.030904 memory: 4565 loss: 0.000694 loss_kpt: 0.000694 acc_pose: 0.930691 2023/08/09 19:59:34 - mmengine - INFO - Epoch(train) [210][180/442] lr: 5.000000e-06 eta: 0:01:32 time: 0.356918 data_time: 0.031988 memory: 4565 loss: 0.000688 loss_kpt: 0.000688 acc_pose: 0.865112 2023/08/09 19:59:38 - mmengine - INFO - Epoch(train) [210][190/442] lr: 5.000000e-06 eta: 0:01:29 time: 0.356623 data_time: 0.031849 memory: 4565 loss: 0.000695 loss_kpt: 0.000695 acc_pose: 0.881973 2023/08/09 19:59:41 - mmengine - INFO - Epoch(train) [210][200/442] lr: 5.000000e-06 eta: 0:01:25 time: 0.355524 data_time: 0.031555 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.937988 2023/08/09 19:59:45 - mmengine - INFO - Epoch(train) [210][210/442] lr: 5.000000e-06 eta: 0:01:22 time: 0.354334 data_time: 0.031368 memory: 4565 loss: 0.000671 loss_kpt: 0.000671 acc_pose: 0.917317 2023/08/09 19:59:48 - mmengine - INFO - Epoch(train) [210][220/442] lr: 5.000000e-06 eta: 0:01:18 time: 0.353900 data_time: 0.031262 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.877614 2023/08/09 19:59:52 - mmengine - INFO - Epoch(train) [210][230/442] lr: 5.000000e-06 eta: 0:01:15 time: 0.352812 data_time: 0.030454 memory: 4565 loss: 0.000674 loss_kpt: 0.000674 acc_pose: 0.913081 2023/08/09 19:59:56 - mmengine - INFO - Epoch(train) [210][240/442] lr: 5.000000e-06 eta: 0:01:11 time: 0.357716 data_time: 0.034018 memory: 4565 loss: 0.000668 loss_kpt: 0.000668 acc_pose: 0.909728 2023/08/09 19:59:59 - mmengine - INFO - Epoch(train) [210][250/442] lr: 5.000000e-06 eta: 0:01:07 time: 0.358005 data_time: 0.034167 memory: 4565 loss: 0.000685 loss_kpt: 0.000685 acc_pose: 0.858438 2023/08/09 20:00:03 - mmengine - INFO - Epoch(train) [210][260/442] lr: 5.000000e-06 eta: 0:01:04 time: 0.358348 data_time: 0.034455 memory: 4565 loss: 0.000679 loss_kpt: 0.000679 acc_pose: 0.936457 2023/08/09 20:00:06 - mmengine - INFO - Epoch(train) [210][270/442] lr: 5.000000e-06 eta: 0:01:00 time: 0.358589 data_time: 0.034495 memory: 4565 loss: 0.000671 loss_kpt: 0.000671 acc_pose: 0.883928 2023/08/09 20:00:10 - mmengine - INFO - Epoch(train) [210][280/442] lr: 5.000000e-06 eta: 0:00:57 time: 0.356672 data_time: 0.034609 memory: 4565 loss: 0.000690 loss_kpt: 0.000690 acc_pose: 0.920872 2023/08/09 20:00:13 - mmengine - INFO - Epoch(train) [210][290/442] lr: 5.000000e-06 eta: 0:00:53 time: 0.352890 data_time: 0.031336 memory: 4565 loss: 0.000702 loss_kpt: 0.000702 acc_pose: 0.919996 2023/08/09 20:00:17 - mmengine - INFO - Epoch(train) [210][300/442] lr: 5.000000e-06 eta: 0:00:50 time: 0.354628 data_time: 0.031884 memory: 4565 loss: 0.000687 loss_kpt: 0.000687 acc_pose: 0.889569 2023/08/09 20:00:21 - mmengine - INFO - Epoch(train) [210][310/442] lr: 5.000000e-06 eta: 0:00:46 time: 0.355471 data_time: 0.031690 memory: 4565 loss: 0.000710 loss_kpt: 0.000710 acc_pose: 0.946379 2023/08/09 20:00:24 - mmengine - INFO - Epoch(train) [210][320/442] lr: 5.000000e-06 eta: 0:00:43 time: 0.354780 data_time: 0.031453 memory: 4565 loss: 0.000709 loss_kpt: 0.000709 acc_pose: 0.927736 2023/08/09 20:00:28 - mmengine - INFO - Epoch(train) [210][330/442] lr: 5.000000e-06 eta: 0:00:39 time: 0.352697 data_time: 0.031216 memory: 4565 loss: 0.000711 loss_kpt: 0.000711 acc_pose: 0.948315 2023/08/09 20:00:31 - mmengine - INFO - Epoch(train) [210][340/442] lr: 5.000000e-06 eta: 0:00:36 time: 0.356356 data_time: 0.034165 memory: 4565 loss: 0.000707 loss_kpt: 0.000707 acc_pose: 0.906526 2023/08/09 20:00:35 - mmengine - INFO - Epoch(train) [210][350/442] lr: 5.000000e-06 eta: 0:00:32 time: 0.356479 data_time: 0.033906 memory: 4565 loss: 0.000705 loss_kpt: 0.000705 acc_pose: 0.896858 2023/08/09 20:00:38 - mmengine - INFO - Epoch(train) [210][360/442] lr: 5.000000e-06 eta: 0:00:29 time: 0.356635 data_time: 0.034015 memory: 4565 loss: 0.000699 loss_kpt: 0.000699 acc_pose: 0.891362 2023/08/09 20:00:42 - mmengine - INFO - Epoch(train) [210][370/442] lr: 5.000000e-06 eta: 0:00:25 time: 0.357382 data_time: 0.034322 memory: 4565 loss: 0.000698 loss_kpt: 0.000698 acc_pose: 0.864548 2023/08/09 20:00:46 - mmengine - INFO - Epoch(train) [210][380/442] lr: 5.000000e-06 eta: 0:00:21 time: 0.360953 data_time: 0.037448 memory: 4565 loss: 0.000708 loss_kpt: 0.000708 acc_pose: 0.811147 2023/08/09 20:00:49 - mmengine - INFO - Epoch(train) [210][390/442] lr: 5.000000e-06 eta: 0:00:18 time: 0.356673 data_time: 0.034267 memory: 4565 loss: 0.000721 loss_kpt: 0.000721 acc_pose: 0.860050 2023/08/09 20:00:53 - mmengine - INFO - Epoch(train) [210][400/442] lr: 5.000000e-06 eta: 0:00:14 time: 0.355422 data_time: 0.033818 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.931256 2023/08/09 20:00:56 - mmengine - INFO - Epoch(train) [210][410/442] lr: 5.000000e-06 eta: 0:00:11 time: 0.355710 data_time: 0.033782 memory: 4565 loss: 0.000716 loss_kpt: 0.000716 acc_pose: 0.863849 2023/08/09 20:01:00 - mmengine - INFO - Epoch(train) [210][420/442] lr: 5.000000e-06 eta: 0:00:07 time: 0.354789 data_time: 0.033594 memory: 4565 loss: 0.000727 loss_kpt: 0.000727 acc_pose: 0.867418 2023/08/09 20:01:03 - mmengine - INFO - Epoch(train) [210][430/442] lr: 5.000000e-06 eta: 0:00:04 time: 0.353131 data_time: 0.030622 memory: 4565 loss: 0.000714 loss_kpt: 0.000714 acc_pose: 0.940578 2023/08/09 20:01:07 - mmengine - INFO - Epoch(train) [210][440/442] lr: 5.000000e-06 eta: 0:00:00 time: 0.355285 data_time: 0.030503 memory: 4565 loss: 0.000700 loss_kpt: 0.000700 acc_pose: 0.880729 2023/08/09 20:01:07 - mmengine - INFO - Exp name: td-hm_hrnet-w48_udp_8xb32-210e_deepfashion_upper-256x192_20230809_153551 2023/08/09 20:01:07 - mmengine - INFO - Saving checkpoint at 210 epochs 2023/08/09 20:01:13 - mmengine - INFO - Epoch(val) [210][ 10/108] eta: 0:00:20 time: 0.196610 data_time: 0.012767 memory: 4565 2023/08/09 20:01:15 - mmengine - INFO - Epoch(val) [210][ 20/108] eta: 0:00:17 time: 0.196567 data_time: 0.012785 memory: 1624 2023/08/09 20:01:17 - mmengine - INFO - Epoch(val) [210][ 30/108] eta: 0:00:15 time: 0.196668 data_time: 0.012866 memory: 1624 2023/08/09 20:01:19 - mmengine - INFO - Epoch(val) [210][ 40/108] eta: 0:00:13 time: 0.197175 data_time: 0.013178 memory: 1624 2023/08/09 20:01:21 - mmengine - INFO - Epoch(val) [210][ 50/108] eta: 0:00:11 time: 0.198980 data_time: 0.013269 memory: 1624 2023/08/09 20:01:23 - mmengine - INFO - Epoch(val) [210][ 60/108] eta: 0:00:09 time: 0.196645 data_time: 0.011380 memory: 1624 2023/08/09 20:01:25 - mmengine - INFO - Epoch(val) [210][ 70/108] eta: 0:00:07 time: 0.196987 data_time: 0.011605 memory: 1624 2023/08/09 20:01:27 - mmengine - INFO - Epoch(val) [210][ 80/108] eta: 0:00:05 time: 0.197017 data_time: 0.011639 memory: 1624 2023/08/09 20:01:29 - mmengine - INFO - Epoch(val) [210][ 90/108] eta: 0:00:03 time: 0.196543 data_time: 0.011413 memory: 1624 2023/08/09 20:01:31 - mmengine - INFO - Epoch(val) [210][100/108] eta: 0:00:01 time: 0.196626 data_time: 0.011423 memory: 1624 2023/08/09 20:01:32 - mmengine - INFO - Evaluating PCKAccuracy (normalized by ``"bbox_size"``)... 2023/08/09 20:01:33 - mmengine - INFO - Evaluating AUC... 2023/08/09 20:01:33 - mmengine - INFO - Evaluating EPE... 2023/08/09 20:01:33 - mmengine - INFO - Epoch(val) [210][108/108] PCK: 0.961774 AUC: 0.604371 EPE: 14.817838 data_time: 0.012121 time: 0.195792