2022/10/27 12:06:04 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.8.13 (default, Mar 28 2022, 11:38:47) [GCC 7.5.0] CUDA available: True numpy_random_seed: 236551078 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/petrelfs/share/cuda-11.3 NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (GCC) 4.8.5 20150623 (Red Hat 4.8.5-44) PyTorch: 1.12.0+cu113 PyTorch compiling details: PyTorch built with: - GCC 9.3 - 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 v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815) - 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 8.2.1 - Built with CuDNN 8.3.2 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/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-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 -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.12.0, 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: 0.13.0+cu113 OpenCV: 4.6.0 MMEngine: 0.1.0 Runtime environment: cudnn_benchmark: False mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} dist_cfg: {'backend': 'nccl'} seed: None Distributed launcher: slurm Distributed training: True GPU number: 8 ------------------------------------------------------------ 2022/10/27 12:06:05 - mmengine - INFO - Config: default_scope = 'mmpose' default_hooks = dict( timer=dict(type='IterTimerHook'), logger=dict(type='LoggerHook', interval=50), param_scheduler=dict(type='ParamSchedulerHook'), checkpoint=dict( type='CheckpointHook', interval=10, max_keep_ckpts=1, save_best='coco/AP', rule='greater'), sampler_seed=dict(type='DistSamplerSeedHook'), visualization=dict(type='PoseVisualizationHook', enable=False)) custom_hooks = [dict(type='SyncBuffersHook')] env_cfg = dict( cudnn_benchmark=False, mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), dist_cfg=dict(backend='nccl')) vis_backends = [dict(type='LocalVisBackend')] visualizer = dict( type='PoseLocalVisualizer', vis_backends=[dict(type='LocalVisBackend')], name='visualizer') log_processor = dict( type='LogProcessor', window_size=50, by_epoch=True, num_digits=6) log_level = 'INFO' load_from = None resume = False file_client_args = dict( backend='petrel', path_mapping=dict({ './data/': 's3://openmmlab/datasets/detection/', 'data/': 's3://openmmlab/datasets/detection/' })) train_cfg = dict(by_epoch=True, max_epochs=210, val_interval=10) val_cfg = dict() test_cfg = dict() optim_wrapper = dict(optimizer=dict(type='Adam', lr=0.0005)) param_scheduler = [ dict( type='LinearLR', begin=0, end=500, start_factor=0.001, by_epoch=False), dict( type='MultiStepLR', begin=0, end=210, milestones=[170, 200], gamma=0.1, by_epoch=True) ] auto_scale_lr = dict(base_batch_size=256) codec = dict( type='MSRAHeatmap', input_size=(288, 384), heatmap_size=(72, 96), sigma=3) model = dict( type='TopdownPoseEstimator', data_preprocessor=dict( type='PoseDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], bgr_to_rgb=True), backbone=dict( type='ResNetV1d', depth=101, init_cfg=dict(type='Pretrained', checkpoint='mmcls://resnet101_v1d')), head=dict( type='HeatmapHead', in_channels=2048, out_channels=17, loss=dict(type='KeypointMSELoss', use_target_weight=True), decoder=dict( type='MSRAHeatmap', input_size=(288, 384), heatmap_size=(72, 96), sigma=3)), test_cfg=dict(flip_test=True, flip_mode='heatmap', shift_heatmap=True)) dataset_type = 'CocoDataset' data_mode = 'topdown' data_root = 'data/coco/' train_pipeline = [ dict( type='LoadImage', file_client_args=dict( backend='petrel', path_mapping=dict({ './data/': 's3://openmmlab/datasets/detection/', 'data/': 's3://openmmlab/datasets/detection/' }))), dict(type='GetBBoxCenterScale'), dict(type='RandomFlip', direction='horizontal'), dict(type='RandomHalfBody'), dict(type='RandomBBoxTransform'), dict(type='TopdownAffine', input_size=(288, 384)), dict( type='GenerateTarget', target_type='heatmap', encoder=dict( type='MSRAHeatmap', input_size=(288, 384), heatmap_size=(72, 96), sigma=3)), dict(type='PackPoseInputs') ] val_pipeline = [ dict( type='LoadImage', file_client_args=dict( backend='petrel', path_mapping=dict({ './data/': 's3://openmmlab/datasets/detection/', 'data/': 's3://openmmlab/datasets/detection/' }))), dict(type='GetBBoxCenterScale'), dict(type='TopdownAffine', input_size=(288, 384)), dict(type='PackPoseInputs') ] train_dataloader = dict( batch_size=32, num_workers=2, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='CocoDataset', data_root='data/coco/', data_mode='topdown', ann_file='annotations/person_keypoints_train2017.json', data_prefix=dict(img='train2017/'), pipeline=[ dict( type='LoadImage', file_client_args=dict( backend='petrel', path_mapping=dict({ './data/': 's3://openmmlab/datasets/detection/', 'data/': 's3://openmmlab/datasets/detection/' }))), dict(type='GetBBoxCenterScale'), dict(type='RandomFlip', direction='horizontal'), dict(type='RandomHalfBody'), dict(type='RandomBBoxTransform'), dict(type='TopdownAffine', input_size=(288, 384)), dict( type='GenerateTarget', target_type='heatmap', encoder=dict( type='MSRAHeatmap', input_size=(288, 384), heatmap_size=(72, 96), sigma=3)), dict(type='PackPoseInputs') ])) val_dataloader = dict( batch_size=32, num_workers=2, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False, round_up=False), dataset=dict( type='CocoDataset', data_root='data/coco/', data_mode='topdown', ann_file='annotations/person_keypoints_val2017.json', bbox_file= 'data/coco/person_detection_results/COCO_val2017_detections_AP_H_56_person.json', data_prefix=dict(img='val2017/'), test_mode=True, pipeline=[ dict( type='LoadImage', file_client_args=dict( backend='petrel', path_mapping=dict({ './data/': 's3://openmmlab/datasets/detection/', 'data/': 's3://openmmlab/datasets/detection/' }))), dict(type='GetBBoxCenterScale'), dict(type='TopdownAffine', input_size=(288, 384)), dict(type='PackPoseInputs') ])) test_dataloader = dict( batch_size=32, num_workers=2, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False, round_up=False), dataset=dict( type='CocoDataset', data_root='data/coco/', data_mode='topdown', ann_file='annotations/person_keypoints_val2017.json', bbox_file= 'data/coco/person_detection_results/COCO_val2017_detections_AP_H_56_person.json', data_prefix=dict(img='val2017/'), test_mode=True, pipeline=[ dict( type='LoadImage', file_client_args=dict( backend='petrel', path_mapping=dict({ './data/': 's3://openmmlab/datasets/detection/', 'data/': 's3://openmmlab/datasets/detection/' }))), dict(type='GetBBoxCenterScale'), dict(type='TopdownAffine', input_size=(288, 384)), dict(type='PackPoseInputs') ])) val_evaluator = dict( type='CocoMetric', ann_file='data/coco/annotations/person_keypoints_val2017.json') test_evaluator = dict( type='CocoMetric', ann_file='data/coco/annotations/person_keypoints_val2017.json') launcher = 'slurm' work_dir = 'work_dirs/20221027/resnetv1d101_384/' 2022/10/27 12:06:51 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "data sampler" registry tree. As a workaround, the current "data sampler" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. 2022/10/27 12:06:51 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "optimizer wrapper constructor" registry tree. As a workaround, the current "optimizer wrapper constructor" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. 2022/10/27 12:06:51 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "optimizer" registry tree. As a workaround, the current "optimizer" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. 2022/10/27 12:06:51 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "optim_wrapper" registry tree. As a workaround, the current "optim_wrapper" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. 2022/10/27 12:06:51 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "parameter scheduler" registry tree. As a workaround, the current "parameter scheduler" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. 2022/10/27 12:06:51 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "parameter scheduler" registry tree. As a workaround, the current "parameter scheduler" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. 2022/10/27 12:06:51 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "parameter scheduler" registry tree. As a workaround, the current "parameter scheduler" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. 2022/10/27 12:06:51 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "parameter scheduler" registry tree. As a workaround, the current "parameter scheduler" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. 2022/10/27 12:06:55 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "data sampler" registry tree. As a workaround, the current "data sampler" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. 2022/10/27 12:06:58 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "weight initializer" registry tree. As a workaround, the current "weight initializer" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. 2022/10/27 12:06:58 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "weight initializer" registry tree. As a workaround, the current "weight initializer" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. 2022/10/27 12:06:58 - mmengine - WARNING - Failed to search registry with scope "mmpose" in the "weight initializer" registry tree. As a workaround, the current "weight initializer" registry in "mmengine" is used to build instance. This may cause unexpected failure when running the built modules. Please check whether "mmpose" is a correct scope, or whether the registry is initialized. Name of parameter - Initialization information backbone.stem.0.conv.weight - torch.Size([32, 3, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.stem.0.bn.weight - torch.Size([32]): PretrainedInit: load from mmcls://resnet101_v1d backbone.stem.0.bn.bias - torch.Size([32]): PretrainedInit: load from mmcls://resnet101_v1d backbone.stem.1.conv.weight - torch.Size([32, 32, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.stem.1.bn.weight - torch.Size([32]): PretrainedInit: load from mmcls://resnet101_v1d backbone.stem.1.bn.bias - torch.Size([32]): PretrainedInit: load from mmcls://resnet101_v1d backbone.stem.2.conv.weight - torch.Size([64, 32, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.stem.2.bn.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.stem.2.bn.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.conv1.weight - torch.Size([64, 64, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.bn1.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.bn1.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.bn2.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.bn2.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.bn3.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.bn3.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.downsample.0.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.downsample.1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.0.downsample.1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.1.conv1.weight - torch.Size([64, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.1.bn1.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.1.bn1.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.1.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.1.bn2.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.1.bn2.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.1.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.1.bn3.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.1.bn3.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.2.conv1.weight - torch.Size([64, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.2.bn1.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.2.bn1.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.2.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.2.bn2.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.2.bn2.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.2.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.2.bn3.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer1.2.bn3.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.conv1.weight - torch.Size([128, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.downsample.1.weight - torch.Size([512, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.downsample.2.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.0.downsample.2.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.1.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.1.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.1.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.1.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.1.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.1.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.1.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.1.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.1.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.2.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.2.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.2.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.2.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.2.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.2.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.2.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.2.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.2.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.3.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.3.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.3.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.3.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.3.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.3.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.3.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.3.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer2.3.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.conv1.weight - torch.Size([256, 512, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.downsample.1.weight - torch.Size([1024, 512, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.downsample.2.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.0.downsample.2.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.1.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.1.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.1.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.1.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.1.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.1.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.1.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.1.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.1.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.2.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.2.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.2.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.2.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.2.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.2.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.2.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.2.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.2.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.3.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.3.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.3.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.3.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.3.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.3.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.3.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.3.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.3.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.4.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.4.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.4.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.4.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.4.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.4.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.4.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.4.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.4.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.5.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.5.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.5.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.5.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.5.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.5.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.5.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.5.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.5.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.6.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.6.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.6.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.6.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.6.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.6.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.6.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.6.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.6.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.7.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.7.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.7.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.7.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.7.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.7.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.7.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.7.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.7.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.8.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.8.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.8.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.8.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.8.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.8.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.8.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.8.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.8.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.9.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.9.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.9.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.9.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.9.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.9.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.9.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.9.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.9.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.10.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.10.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.10.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.10.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.10.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.10.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.10.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.10.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.10.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.11.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.11.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.11.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.11.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.11.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.11.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.11.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.11.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.11.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.12.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.12.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.12.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.12.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.12.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.12.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.12.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.12.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.12.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.13.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.13.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.13.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.13.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.13.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.13.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.13.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.13.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.13.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.14.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.14.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.14.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.14.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.14.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.14.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.14.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.14.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.14.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.15.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.15.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.15.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.15.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.15.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.15.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.15.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.15.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.15.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.16.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.16.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.16.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.16.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.16.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.16.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.16.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.16.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.16.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.17.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.17.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.17.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.17.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.17.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.17.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.17.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.17.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.17.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.18.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.18.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.18.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.18.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.18.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.18.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.18.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.18.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.18.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.19.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.19.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.19.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.19.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.19.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.19.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.19.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.19.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.19.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.20.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.20.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.20.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.20.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.20.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.20.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.20.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.20.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.20.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.21.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.21.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.21.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.21.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.21.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.21.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.21.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.21.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.21.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.22.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.22.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.22.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.22.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.22.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.22.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.22.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.22.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer3.22.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.conv1.weight - torch.Size([512, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.bn1.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.bn1.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.bn2.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.bn2.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.bn3.weight - torch.Size([2048]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.bn3.bias - torch.Size([2048]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.downsample.1.weight - torch.Size([2048, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.downsample.2.weight - torch.Size([2048]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.0.downsample.2.bias - torch.Size([2048]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.1.conv1.weight - torch.Size([512, 2048, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.1.bn1.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.1.bn1.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.1.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.1.bn2.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.1.bn2.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.1.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.1.bn3.weight - torch.Size([2048]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.1.bn3.bias - torch.Size([2048]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.2.conv1.weight - torch.Size([512, 2048, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.2.bn1.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.2.bn1.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.2.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.2.bn2.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.2.bn2.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.2.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.2.bn3.weight - torch.Size([2048]): PretrainedInit: load from mmcls://resnet101_v1d backbone.layer4.2.bn3.bias - torch.Size([2048]): PretrainedInit: load from mmcls://resnet101_v1d head.deconv_layers.0.weight - torch.Size([2048, 256, 4, 4]): NormalInit: mean=0, std=0.001, bias=0 head.deconv_layers.1.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of TopdownPoseEstimator head.deconv_layers.1.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of TopdownPoseEstimator head.deconv_layers.3.weight - torch.Size([256, 256, 4, 4]): NormalInit: mean=0, std=0.001, bias=0 head.deconv_layers.4.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of TopdownPoseEstimator head.deconv_layers.4.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of TopdownPoseEstimator head.deconv_layers.6.weight - torch.Size([256, 256, 4, 4]): NormalInit: mean=0, std=0.001, bias=0 head.deconv_layers.7.weight - torch.Size([256]): The value is the same before and after calling `init_weights` of TopdownPoseEstimator head.deconv_layers.7.bias - torch.Size([256]): The value is the same before and after calling `init_weights` of TopdownPoseEstimator head.final_layer.weight - torch.Size([17, 256, 1, 1]): NormalInit: mean=0, std=0.001, bias=0 head.final_layer.bias - torch.Size([17]): NormalInit: mean=0, std=0.001, bias=0 2022/10/27 12:06:58 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384 by HardDiskBackend. 2022/10/27 12:07:22 - mmengine - INFO - Epoch(train) [1][50/586] lr: 4.954910e-05 eta: 16:09:15 time: 0.472767 data_time: 0.138126 memory: 11131 loss_kpt: 0.002105 acc_pose: 0.207824 loss: 0.002105 2022/10/27 12:07:37 - mmengine - INFO - Epoch(train) [1][100/586] lr: 9.959920e-05 eta: 13:06:24 time: 0.294718 data_time: 0.028650 memory: 11131 loss_kpt: 0.001721 acc_pose: 0.475457 loss: 0.001721 2022/10/27 12:07:51 - mmengine - INFO - Epoch(train) [1][150/586] lr: 1.496493e-04 eta: 11:59:29 time: 0.286213 data_time: 0.026370 memory: 11131 loss_kpt: 0.001432 acc_pose: 0.532845 loss: 0.001432 2022/10/27 12:08:05 - mmengine - INFO - Epoch(train) [1][200/586] lr: 1.996994e-04 eta: 11:23:56 time: 0.282357 data_time: 0.026156 memory: 11131 loss_kpt: 0.001322 acc_pose: 0.513910 loss: 0.001322 2022/10/27 12:08:20 - mmengine - INFO - Epoch(train) [1][250/586] lr: 2.497495e-04 eta: 11:07:23 time: 0.294248 data_time: 0.030699 memory: 11131 loss_kpt: 0.001274 acc_pose: 0.489401 loss: 0.001274 2022/10/27 12:08:35 - mmengine - INFO - Epoch(train) [1][300/586] lr: 2.997996e-04 eta: 10:56:54 time: 0.296092 data_time: 0.036314 memory: 11131 loss_kpt: 0.001243 acc_pose: 0.539644 loss: 0.001243 2022/10/27 12:08:50 - mmengine - INFO - Epoch(train) [1][350/586] lr: 3.498497e-04 eta: 10:50:24 time: 0.299748 data_time: 0.029950 memory: 11131 loss_kpt: 0.001208 acc_pose: 0.464768 loss: 0.001208 2022/10/27 12:09:04 - mmengine - INFO - Epoch(train) [1][400/586] lr: 3.998998e-04 eta: 10:41:40 time: 0.284881 data_time: 0.027258 memory: 11131 loss_kpt: 0.001180 acc_pose: 0.604709 loss: 0.001180 2022/10/27 12:09:18 - mmengine - INFO - Epoch(train) [1][450/586] lr: 4.499499e-04 eta: 10:34:31 time: 0.283584 data_time: 0.028719 memory: 11131 loss_kpt: 0.001156 acc_pose: 0.560681 loss: 0.001156 2022/10/27 12:09:32 - mmengine - INFO - Epoch(train) [1][500/586] lr: 5.000000e-04 eta: 10:29:16 time: 0.286058 data_time: 0.028734 memory: 11131 loss_kpt: 0.001164 acc_pose: 0.615674 loss: 0.001164 2022/10/27 12:09:47 - mmengine - INFO - Epoch(train) [1][550/586] lr: 5.000000e-04 eta: 10:26:16 time: 0.293280 data_time: 0.027274 memory: 11131 loss_kpt: 0.001147 acc_pose: 0.660474 loss: 0.001147 2022/10/27 12:09:58 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:10:12 - mmengine - INFO - Epoch(train) [2][50/586] lr: 5.000000e-04 eta: 9:48:49 time: 0.296783 data_time: 0.037166 memory: 11131 loss_kpt: 0.001106 acc_pose: 0.593202 loss: 0.001106 2022/10/27 12:10:27 - mmengine - INFO - Epoch(train) [2][100/586] lr: 5.000000e-04 eta: 9:47:52 time: 0.283834 data_time: 0.026433 memory: 11131 loss_kpt: 0.001099 acc_pose: 0.560032 loss: 0.001099 2022/10/27 12:10:41 - mmengine - INFO - Epoch(train) [2][150/586] lr: 5.000000e-04 eta: 9:46:34 time: 0.280556 data_time: 0.027530 memory: 11131 loss_kpt: 0.001095 acc_pose: 0.635793 loss: 0.001095 2022/10/27 12:10:56 - mmengine - INFO - Epoch(train) [2][200/586] lr: 5.000000e-04 eta: 9:47:52 time: 0.299702 data_time: 0.029024 memory: 11131 loss_kpt: 0.001083 acc_pose: 0.682166 loss: 0.001083 2022/10/27 12:11:10 - mmengine - INFO - Epoch(train) [2][250/586] lr: 5.000000e-04 eta: 9:47:56 time: 0.290950 data_time: 0.029033 memory: 11131 loss_kpt: 0.001066 acc_pose: 0.719597 loss: 0.001066 2022/10/27 12:11:24 - mmengine - INFO - Epoch(train) [2][300/586] lr: 5.000000e-04 eta: 9:46:54 time: 0.281689 data_time: 0.027235 memory: 11131 loss_kpt: 0.001045 acc_pose: 0.577537 loss: 0.001045 2022/10/27 12:11:39 - mmengine - INFO - Epoch(train) [2][350/586] lr: 5.000000e-04 eta: 9:46:34 time: 0.287460 data_time: 0.028179 memory: 11131 loss_kpt: 0.001041 acc_pose: 0.487222 loss: 0.001041 2022/10/27 12:11:53 - mmengine - INFO - Epoch(train) [2][400/586] lr: 5.000000e-04 eta: 9:45:50 time: 0.283395 data_time: 0.029748 memory: 11131 loss_kpt: 0.001050 acc_pose: 0.723139 loss: 0.001050 2022/10/27 12:11:57 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:12:08 - mmengine - INFO - Epoch(train) [2][450/586] lr: 5.000000e-04 eta: 9:47:06 time: 0.303254 data_time: 0.030402 memory: 11131 loss_kpt: 0.001026 acc_pose: 0.655538 loss: 0.001026 2022/10/27 12:12:22 - mmengine - INFO - Epoch(train) [2][500/586] lr: 5.000000e-04 eta: 9:46:44 time: 0.287246 data_time: 0.027546 memory: 11131 loss_kpt: 0.000972 acc_pose: 0.735960 loss: 0.000972 2022/10/27 12:12:37 - mmengine - INFO - Epoch(train) [2][550/586] lr: 5.000000e-04 eta: 9:46:19 time: 0.286787 data_time: 0.027531 memory: 11131 loss_kpt: 0.000997 acc_pose: 0.621762 loss: 0.000997 2022/10/27 12:12:47 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:13:01 - mmengine - INFO - Epoch(train) [3][50/586] lr: 5.000000e-04 eta: 9:28:51 time: 0.290957 data_time: 0.036693 memory: 11131 loss_kpt: 0.000995 acc_pose: 0.705560 loss: 0.000995 2022/10/27 12:13:16 - mmengine - INFO - Epoch(train) [3][100/586] lr: 5.000000e-04 eta: 9:30:16 time: 0.300944 data_time: 0.030910 memory: 11131 loss_kpt: 0.001010 acc_pose: 0.593680 loss: 0.001010 2022/10/27 12:13:31 - mmengine - INFO - Epoch(train) [3][150/586] lr: 5.000000e-04 eta: 9:30:25 time: 0.285788 data_time: 0.026520 memory: 11131 loss_kpt: 0.000976 acc_pose: 0.709794 loss: 0.000976 2022/10/27 12:13:45 - mmengine - INFO - Epoch(train) [3][200/586] lr: 5.000000e-04 eta: 9:30:45 time: 0.288850 data_time: 0.030254 memory: 11131 loss_kpt: 0.000969 acc_pose: 0.747598 loss: 0.000969 2022/10/27 12:14:00 - mmengine - INFO - Epoch(train) [3][250/586] lr: 5.000000e-04 eta: 9:31:02 time: 0.288775 data_time: 0.028042 memory: 11131 loss_kpt: 0.000967 acc_pose: 0.666725 loss: 0.000967 2022/10/27 12:14:14 - mmengine - INFO - Epoch(train) [3][300/586] lr: 5.000000e-04 eta: 9:31:31 time: 0.292086 data_time: 0.027902 memory: 11131 loss_kpt: 0.000968 acc_pose: 0.729656 loss: 0.000968 2022/10/27 12:14:29 - mmengine - INFO - Epoch(train) [3][350/586] lr: 5.000000e-04 eta: 9:32:24 time: 0.298858 data_time: 0.032517 memory: 11131 loss_kpt: 0.000971 acc_pose: 0.695612 loss: 0.000971 2022/10/27 12:14:43 - mmengine - INFO - Epoch(train) [3][400/586] lr: 5.000000e-04 eta: 9:32:20 time: 0.285027 data_time: 0.027001 memory: 11131 loss_kpt: 0.000949 acc_pose: 0.645127 loss: 0.000949 2022/10/27 12:14:57 - mmengine - INFO - Epoch(train) [3][450/586] lr: 5.000000e-04 eta: 9:32:01 time: 0.281401 data_time: 0.026197 memory: 11131 loss_kpt: 0.000961 acc_pose: 0.695182 loss: 0.000961 2022/10/27 12:15:11 - mmengine - INFO - Epoch(train) [3][500/586] lr: 5.000000e-04 eta: 9:31:41 time: 0.281232 data_time: 0.028345 memory: 11131 loss_kpt: 0.000969 acc_pose: 0.687394 loss: 0.000969 2022/10/27 12:15:26 - mmengine - INFO - Epoch(train) [3][550/586] lr: 5.000000e-04 eta: 9:32:14 time: 0.295863 data_time: 0.028091 memory: 11131 loss_kpt: 0.000953 acc_pose: 0.682210 loss: 0.000953 2022/10/27 12:15:37 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:15:51 - mmengine - INFO - Epoch(train) [4][50/586] lr: 5.000000e-04 eta: 9:20:57 time: 0.292117 data_time: 0.037642 memory: 11131 loss_kpt: 0.000947 acc_pose: 0.700507 loss: 0.000947 2022/10/27 12:16:06 - mmengine - INFO - Epoch(train) [4][100/586] lr: 5.000000e-04 eta: 9:21:04 time: 0.283956 data_time: 0.031588 memory: 11131 loss_kpt: 0.000963 acc_pose: 0.736840 loss: 0.000963 2022/10/27 12:16:20 - mmengine - INFO - Epoch(train) [4][150/586] lr: 5.000000e-04 eta: 9:21:01 time: 0.281141 data_time: 0.026750 memory: 11131 loss_kpt: 0.000919 acc_pose: 0.723813 loss: 0.000919 2022/10/27 12:16:35 - mmengine - INFO - Epoch(train) [4][200/586] lr: 5.000000e-04 eta: 9:22:00 time: 0.301461 data_time: 0.030589 memory: 11131 loss_kpt: 0.000926 acc_pose: 0.694746 loss: 0.000926 2022/10/27 12:16:47 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:16:49 - mmengine - INFO - Epoch(train) [4][250/586] lr: 5.000000e-04 eta: 9:22:14 time: 0.287681 data_time: 0.027136 memory: 11131 loss_kpt: 0.000918 acc_pose: 0.615664 loss: 0.000918 2022/10/27 12:17:03 - mmengine - INFO - Epoch(train) [4][300/586] lr: 5.000000e-04 eta: 9:22:14 time: 0.283224 data_time: 0.029531 memory: 11131 loss_kpt: 0.000934 acc_pose: 0.754923 loss: 0.000934 2022/10/27 12:17:17 - mmengine - INFO - Epoch(train) [4][350/586] lr: 5.000000e-04 eta: 9:22:13 time: 0.283306 data_time: 0.026418 memory: 11131 loss_kpt: 0.000941 acc_pose: 0.698347 loss: 0.000941 2022/10/27 12:17:32 - mmengine - INFO - Epoch(train) [4][400/586] lr: 5.000000e-04 eta: 9:22:28 time: 0.289241 data_time: 0.029461 memory: 11131 loss_kpt: 0.000920 acc_pose: 0.659574 loss: 0.000920 2022/10/27 12:17:47 - mmengine - INFO - Epoch(train) [4][450/586] lr: 5.000000e-04 eta: 9:23:12 time: 0.300464 data_time: 0.030519 memory: 11131 loss_kpt: 0.000912 acc_pose: 0.691148 loss: 0.000912 2022/10/27 12:18:01 - mmengine - INFO - Epoch(train) [4][500/586] lr: 5.000000e-04 eta: 9:23:08 time: 0.283525 data_time: 0.029469 memory: 11131 loss_kpt: 0.000899 acc_pose: 0.646375 loss: 0.000899 2022/10/27 12:18:15 - mmengine - INFO - Epoch(train) [4][550/586] lr: 5.000000e-04 eta: 9:23:01 time: 0.282357 data_time: 0.027572 memory: 11131 loss_kpt: 0.000917 acc_pose: 0.683745 loss: 0.000917 2022/10/27 12:18:25 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:18:40 - mmengine - INFO - Epoch(train) [5][50/586] lr: 5.000000e-04 eta: 9:14:53 time: 0.296774 data_time: 0.038409 memory: 11131 loss_kpt: 0.000914 acc_pose: 0.741311 loss: 0.000914 2022/10/27 12:18:55 - mmengine - INFO - Epoch(train) [5][100/586] lr: 5.000000e-04 eta: 9:15:35 time: 0.298819 data_time: 0.031090 memory: 11131 loss_kpt: 0.000930 acc_pose: 0.641392 loss: 0.000930 2022/10/27 12:19:09 - mmengine - INFO - Epoch(train) [5][150/586] lr: 5.000000e-04 eta: 9:15:42 time: 0.285044 data_time: 0.028097 memory: 11131 loss_kpt: 0.000903 acc_pose: 0.742353 loss: 0.000903 2022/10/27 12:19:23 - mmengine - INFO - Epoch(train) [5][200/586] lr: 5.000000e-04 eta: 9:15:41 time: 0.281821 data_time: 0.028116 memory: 11131 loss_kpt: 0.000896 acc_pose: 0.691514 loss: 0.000896 2022/10/27 12:19:38 - mmengine - INFO - Epoch(train) [5][250/586] lr: 5.000000e-04 eta: 9:15:45 time: 0.284165 data_time: 0.030959 memory: 11131 loss_kpt: 0.000891 acc_pose: 0.717287 loss: 0.000891 2022/10/27 12:19:52 - mmengine - INFO - Epoch(train) [5][300/586] lr: 5.000000e-04 eta: 9:16:00 time: 0.289673 data_time: 0.028828 memory: 11131 loss_kpt: 0.000882 acc_pose: 0.718133 loss: 0.000882 2022/10/27 12:20:07 - mmengine - INFO - Epoch(train) [5][350/586] lr: 5.000000e-04 eta: 9:16:47 time: 0.304009 data_time: 0.031093 memory: 11131 loss_kpt: 0.000894 acc_pose: 0.720915 loss: 0.000894 2022/10/27 12:20:21 - mmengine - INFO - Epoch(train) [5][400/586] lr: 5.000000e-04 eta: 9:16:43 time: 0.282118 data_time: 0.029720 memory: 11131 loss_kpt: 0.000863 acc_pose: 0.763483 loss: 0.000863 2022/10/27 12:20:36 - mmengine - INFO - Epoch(train) [5][450/586] lr: 5.000000e-04 eta: 9:16:40 time: 0.282664 data_time: 0.028505 memory: 11131 loss_kpt: 0.000908 acc_pose: 0.725956 loss: 0.000908 2022/10/27 12:20:50 - mmengine - INFO - Epoch(train) [5][500/586] lr: 5.000000e-04 eta: 9:16:43 time: 0.285856 data_time: 0.029768 memory: 11131 loss_kpt: 0.000889 acc_pose: 0.616418 loss: 0.000889 2022/10/27 12:21:05 - mmengine - INFO - Epoch(train) [5][550/586] lr: 5.000000e-04 eta: 9:17:08 time: 0.296769 data_time: 0.031674 memory: 11131 loss_kpt: 0.000899 acc_pose: 0.763380 loss: 0.000899 2022/10/27 12:21:15 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:21:30 - mmengine - INFO - Epoch(train) [6][50/586] lr: 5.000000e-04 eta: 9:10:28 time: 0.291576 data_time: 0.040647 memory: 11131 loss_kpt: 0.000904 acc_pose: 0.784871 loss: 0.000904 2022/10/27 12:21:35 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:21:44 - mmengine - INFO - Epoch(train) [6][100/586] lr: 5.000000e-04 eta: 9:10:30 time: 0.283190 data_time: 0.027408 memory: 11131 loss_kpt: 0.000875 acc_pose: 0.733586 loss: 0.000875 2022/10/27 12:21:58 - mmengine - INFO - Epoch(train) [6][150/586] lr: 5.000000e-04 eta: 9:10:47 time: 0.290622 data_time: 0.028962 memory: 11131 loss_kpt: 0.000869 acc_pose: 0.647724 loss: 0.000869 2022/10/27 12:22:13 - mmengine - INFO - Epoch(train) [6][200/586] lr: 5.000000e-04 eta: 9:11:22 time: 0.301212 data_time: 0.032410 memory: 11131 loss_kpt: 0.000884 acc_pose: 0.696288 loss: 0.000884 2022/10/27 12:22:28 - mmengine - INFO - Epoch(train) [6][250/586] lr: 5.000000e-04 eta: 9:11:34 time: 0.289429 data_time: 0.028740 memory: 11131 loss_kpt: 0.000861 acc_pose: 0.735205 loss: 0.000861 2022/10/27 12:22:42 - mmengine - INFO - Epoch(train) [6][300/586] lr: 5.000000e-04 eta: 9:11:34 time: 0.283494 data_time: 0.030980 memory: 11131 loss_kpt: 0.000873 acc_pose: 0.791957 loss: 0.000873 2022/10/27 12:22:56 - mmengine - INFO - Epoch(train) [6][350/586] lr: 5.000000e-04 eta: 9:11:29 time: 0.280893 data_time: 0.027290 memory: 11131 loss_kpt: 0.000852 acc_pose: 0.635147 loss: 0.000852 2022/10/27 12:23:11 - mmengine - INFO - Epoch(train) [6][400/586] lr: 5.000000e-04 eta: 9:11:40 time: 0.290439 data_time: 0.031920 memory: 11131 loss_kpt: 0.000843 acc_pose: 0.769453 loss: 0.000843 2022/10/27 12:23:25 - mmengine - INFO - Epoch(train) [6][450/586] lr: 5.000000e-04 eta: 9:12:03 time: 0.296992 data_time: 0.027594 memory: 11131 loss_kpt: 0.000849 acc_pose: 0.722728 loss: 0.000849 2022/10/27 12:23:40 - mmengine - INFO - Epoch(train) [6][500/586] lr: 5.000000e-04 eta: 9:12:02 time: 0.284124 data_time: 0.027484 memory: 11131 loss_kpt: 0.000854 acc_pose: 0.714395 loss: 0.000854 2022/10/27 12:23:54 - mmengine - INFO - Epoch(train) [6][550/586] lr: 5.000000e-04 eta: 9:11:58 time: 0.282527 data_time: 0.027313 memory: 11131 loss_kpt: 0.000865 acc_pose: 0.717134 loss: 0.000865 2022/10/27 12:24:04 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:24:19 - mmengine - INFO - Epoch(train) [7][50/586] lr: 5.000000e-04 eta: 9:06:42 time: 0.302035 data_time: 0.037455 memory: 11131 loss_kpt: 0.000838 acc_pose: 0.646949 loss: 0.000838 2022/10/27 12:24:34 - mmengine - INFO - Epoch(train) [7][100/586] lr: 5.000000e-04 eta: 9:07:02 time: 0.294769 data_time: 0.029418 memory: 11131 loss_kpt: 0.000861 acc_pose: 0.754156 loss: 0.000861 2022/10/27 12:24:48 - mmengine - INFO - Epoch(train) [7][150/586] lr: 5.000000e-04 eta: 9:07:12 time: 0.289354 data_time: 0.028151 memory: 11131 loss_kpt: 0.000815 acc_pose: 0.813275 loss: 0.000815 2022/10/27 12:25:03 - mmengine - INFO - Epoch(train) [7][200/586] lr: 5.000000e-04 eta: 9:07:20 time: 0.288616 data_time: 0.028008 memory: 11131 loss_kpt: 0.000840 acc_pose: 0.693484 loss: 0.000840 2022/10/27 12:25:17 - mmengine - INFO - Epoch(train) [7][250/586] lr: 5.000000e-04 eta: 9:07:21 time: 0.284816 data_time: 0.027963 memory: 11131 loss_kpt: 0.000821 acc_pose: 0.779181 loss: 0.000821 2022/10/27 12:25:32 - mmengine - INFO - Epoch(train) [7][300/586] lr: 5.000000e-04 eta: 9:07:36 time: 0.293397 data_time: 0.029359 memory: 11131 loss_kpt: 0.000850 acc_pose: 0.723832 loss: 0.000850 2022/10/27 12:25:46 - mmengine - INFO - Epoch(train) [7][350/586] lr: 5.000000e-04 eta: 9:07:50 time: 0.293958 data_time: 0.027853 memory: 11131 loss_kpt: 0.000858 acc_pose: 0.729102 loss: 0.000858 2022/10/27 12:26:00 - mmengine - INFO - Epoch(train) [7][400/586] lr: 5.000000e-04 eta: 9:07:47 time: 0.282612 data_time: 0.026206 memory: 11131 loss_kpt: 0.000858 acc_pose: 0.666750 loss: 0.000858 2022/10/27 12:26:15 - mmengine - INFO - Epoch(train) [7][450/586] lr: 5.000000e-04 eta: 9:07:44 time: 0.283374 data_time: 0.032933 memory: 11131 loss_kpt: 0.000847 acc_pose: 0.797379 loss: 0.000847 2022/10/27 12:26:24 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:26:29 - mmengine - INFO - Epoch(train) [7][500/586] lr: 5.000000e-04 eta: 9:07:50 time: 0.288901 data_time: 0.028258 memory: 11131 loss_kpt: 0.000833 acc_pose: 0.709753 loss: 0.000833 2022/10/27 12:26:44 - mmengine - INFO - Epoch(train) [7][550/586] lr: 5.000000e-04 eta: 9:08:02 time: 0.293945 data_time: 0.028154 memory: 11131 loss_kpt: 0.000851 acc_pose: 0.729312 loss: 0.000851 2022/10/27 12:26:54 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:27:09 - mmengine - INFO - Epoch(train) [8][50/586] lr: 5.000000e-04 eta: 9:03:22 time: 0.296331 data_time: 0.039973 memory: 11131 loss_kpt: 0.000832 acc_pose: 0.800236 loss: 0.000832 2022/10/27 12:27:23 - mmengine - INFO - Epoch(train) [8][100/586] lr: 5.000000e-04 eta: 9:03:24 time: 0.284999 data_time: 0.027752 memory: 11131 loss_kpt: 0.000841 acc_pose: 0.722817 loss: 0.000841 2022/10/27 12:27:38 - mmengine - INFO - Epoch(train) [8][150/586] lr: 5.000000e-04 eta: 9:03:36 time: 0.292917 data_time: 0.028330 memory: 11131 loss_kpt: 0.000868 acc_pose: 0.744200 loss: 0.000868 2022/10/27 12:27:53 - mmengine - INFO - Epoch(train) [8][200/586] lr: 5.000000e-04 eta: 9:03:57 time: 0.299790 data_time: 0.028722 memory: 11131 loss_kpt: 0.000799 acc_pose: 0.827787 loss: 0.000799 2022/10/27 12:28:07 - mmengine - INFO - Epoch(train) [8][250/586] lr: 5.000000e-04 eta: 9:04:05 time: 0.291044 data_time: 0.028066 memory: 11131 loss_kpt: 0.000816 acc_pose: 0.654495 loss: 0.000816 2022/10/27 12:28:22 - mmengine - INFO - Epoch(train) [8][300/586] lr: 5.000000e-04 eta: 9:04:12 time: 0.290247 data_time: 0.026808 memory: 11131 loss_kpt: 0.000849 acc_pose: 0.691204 loss: 0.000849 2022/10/27 12:28:36 - mmengine - INFO - Epoch(train) [8][350/586] lr: 5.000000e-04 eta: 9:04:13 time: 0.285931 data_time: 0.027613 memory: 11131 loss_kpt: 0.000827 acc_pose: 0.791468 loss: 0.000827 2022/10/27 12:28:51 - mmengine - INFO - Epoch(train) [8][400/586] lr: 5.000000e-04 eta: 9:04:18 time: 0.289864 data_time: 0.034025 memory: 11131 loss_kpt: 0.000832 acc_pose: 0.634899 loss: 0.000832 2022/10/27 12:29:06 - mmengine - INFO - Epoch(train) [8][450/586] lr: 5.000000e-04 eta: 9:04:35 time: 0.298717 data_time: 0.032364 memory: 11131 loss_kpt: 0.000819 acc_pose: 0.774544 loss: 0.000819 2022/10/27 12:29:20 - mmengine - INFO - Epoch(train) [8][500/586] lr: 5.000000e-04 eta: 9:04:31 time: 0.283846 data_time: 0.028542 memory: 11131 loss_kpt: 0.000825 acc_pose: 0.723739 loss: 0.000825 2022/10/27 12:29:34 - mmengine - INFO - Epoch(train) [8][550/586] lr: 5.000000e-04 eta: 9:04:29 time: 0.284908 data_time: 0.028863 memory: 11131 loss_kpt: 0.000810 acc_pose: 0.784267 loss: 0.000810 2022/10/27 12:29:44 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:29:59 - mmengine - INFO - Epoch(train) [9][50/586] lr: 5.000000e-04 eta: 9:00:32 time: 0.303325 data_time: 0.042928 memory: 11131 loss_kpt: 0.000819 acc_pose: 0.840198 loss: 0.000819 2022/10/27 12:30:15 - mmengine - INFO - Epoch(train) [9][100/586] lr: 5.000000e-04 eta: 9:00:54 time: 0.303632 data_time: 0.028831 memory: 11131 loss_kpt: 0.000818 acc_pose: 0.761507 loss: 0.000818 2022/10/27 12:30:29 - mmengine - INFO - Epoch(train) [9][150/586] lr: 5.000000e-04 eta: 9:00:58 time: 0.288820 data_time: 0.027758 memory: 11131 loss_kpt: 0.000846 acc_pose: 0.740842 loss: 0.000846 2022/10/27 12:30:43 - mmengine - INFO - Epoch(train) [9][200/586] lr: 5.000000e-04 eta: 9:00:58 time: 0.285580 data_time: 0.029310 memory: 11131 loss_kpt: 0.000820 acc_pose: 0.726741 loss: 0.000820 2022/10/27 12:30:58 - mmengine - INFO - Epoch(train) [9][250/586] lr: 5.000000e-04 eta: 9:01:03 time: 0.290255 data_time: 0.026973 memory: 11131 loss_kpt: 0.000830 acc_pose: 0.750133 loss: 0.000830 2022/10/27 12:31:12 - mmengine - INFO - Epoch(train) [9][300/586] lr: 5.000000e-04 eta: 9:01:07 time: 0.290055 data_time: 0.028402 memory: 11131 loss_kpt: 0.000832 acc_pose: 0.834904 loss: 0.000832 2022/10/27 12:31:16 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:31:27 - mmengine - INFO - Epoch(train) [9][350/586] lr: 5.000000e-04 eta: 9:01:14 time: 0.292514 data_time: 0.029671 memory: 11131 loss_kpt: 0.000813 acc_pose: 0.722305 loss: 0.000813 2022/10/27 12:31:41 - mmengine - INFO - Epoch(train) [9][400/586] lr: 5.000000e-04 eta: 9:01:14 time: 0.287556 data_time: 0.027932 memory: 11131 loss_kpt: 0.000821 acc_pose: 0.782630 loss: 0.000821 2022/10/27 12:31:56 - mmengine - INFO - Epoch(train) [9][450/586] lr: 5.000000e-04 eta: 9:01:14 time: 0.286595 data_time: 0.026920 memory: 11131 loss_kpt: 0.000797 acc_pose: 0.767273 loss: 0.000797 2022/10/27 12:32:10 - mmengine - INFO - Epoch(train) [9][500/586] lr: 5.000000e-04 eta: 9:01:15 time: 0.288841 data_time: 0.029386 memory: 11131 loss_kpt: 0.000830 acc_pose: 0.654919 loss: 0.000830 2022/10/27 12:32:25 - mmengine - INFO - Epoch(train) [9][550/586] lr: 5.000000e-04 eta: 9:01:27 time: 0.298003 data_time: 0.027857 memory: 11131 loss_kpt: 0.000818 acc_pose: 0.737205 loss: 0.000818 2022/10/27 12:32:35 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:32:50 - mmengine - INFO - Epoch(train) [10][50/586] lr: 5.000000e-04 eta: 8:57:51 time: 0.300376 data_time: 0.039849 memory: 11131 loss_kpt: 0.000831 acc_pose: 0.767209 loss: 0.000831 2022/10/27 12:33:05 - mmengine - INFO - Epoch(train) [10][100/586] lr: 5.000000e-04 eta: 8:57:52 time: 0.287774 data_time: 0.027639 memory: 11131 loss_kpt: 0.000816 acc_pose: 0.690685 loss: 0.000816 2022/10/27 12:33:20 - mmengine - INFO - Epoch(train) [10][150/586] lr: 5.000000e-04 eta: 8:58:00 time: 0.294094 data_time: 0.028515 memory: 11131 loss_kpt: 0.000812 acc_pose: 0.768962 loss: 0.000812 2022/10/27 12:33:34 - mmengine - INFO - Epoch(train) [10][200/586] lr: 5.000000e-04 eta: 8:58:01 time: 0.288638 data_time: 0.026673 memory: 11131 loss_kpt: 0.000784 acc_pose: 0.735135 loss: 0.000784 2022/10/27 12:33:49 - mmengine - INFO - Epoch(train) [10][250/586] lr: 5.000000e-04 eta: 8:58:07 time: 0.292780 data_time: 0.028884 memory: 11131 loss_kpt: 0.000799 acc_pose: 0.801626 loss: 0.000799 2022/10/27 12:34:03 - mmengine - INFO - Epoch(train) [10][300/586] lr: 5.000000e-04 eta: 8:58:03 time: 0.283996 data_time: 0.031287 memory: 11131 loss_kpt: 0.000792 acc_pose: 0.703660 loss: 0.000792 2022/10/27 12:34:17 - mmengine - INFO - Epoch(train) [10][350/586] lr: 5.000000e-04 eta: 8:58:07 time: 0.291519 data_time: 0.026679 memory: 11131 loss_kpt: 0.000778 acc_pose: 0.747169 loss: 0.000778 2022/10/27 12:34:32 - mmengine - INFO - Epoch(train) [10][400/586] lr: 5.000000e-04 eta: 8:58:07 time: 0.288185 data_time: 0.028098 memory: 11131 loss_kpt: 0.000805 acc_pose: 0.702663 loss: 0.000805 2022/10/27 12:34:46 - mmengine - INFO - Epoch(train) [10][450/586] lr: 5.000000e-04 eta: 8:58:09 time: 0.290505 data_time: 0.029720 memory: 11131 loss_kpt: 0.000809 acc_pose: 0.765299 loss: 0.000809 2022/10/27 12:35:01 - mmengine - INFO - Epoch(train) [10][500/586] lr: 5.000000e-04 eta: 8:58:10 time: 0.289895 data_time: 0.028190 memory: 11131 loss_kpt: 0.000819 acc_pose: 0.699430 loss: 0.000819 2022/10/27 12:35:15 - mmengine - INFO - Epoch(train) [10][550/586] lr: 5.000000e-04 eta: 8:58:06 time: 0.285340 data_time: 0.026629 memory: 11131 loss_kpt: 0.000812 acc_pose: 0.780869 loss: 0.000812 2022/10/27 12:35:25 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:35:25 - mmengine - INFO - Saving checkpoint at 10 epochs 2022/10/27 12:35:39 - mmengine - INFO - Epoch(val) [10][50/407] eta: 0:01:16 time: 0.213723 data_time: 0.094766 memory: 11131 2022/10/27 12:35:46 - mmengine - INFO - Epoch(val) [10][100/407] eta: 0:00:40 time: 0.132801 data_time: 0.012719 memory: 1836 2022/10/27 12:35:53 - mmengine - INFO - Epoch(val) [10][150/407] eta: 0:00:36 time: 0.141359 data_time: 0.016281 memory: 1836 2022/10/27 12:36:00 - mmengine - INFO - Epoch(val) [10][200/407] eta: 0:00:28 time: 0.137503 data_time: 0.016563 memory: 1836 2022/10/27 12:36:07 - mmengine - INFO - Epoch(val) [10][250/407] eta: 0:00:22 time: 0.143329 data_time: 0.022307 memory: 1836 2022/10/27 12:36:14 - mmengine - INFO - Epoch(val) [10][300/407] eta: 0:00:14 time: 0.137210 data_time: 0.017714 memory: 1836 2022/10/27 12:36:21 - mmengine - INFO - Epoch(val) [10][350/407] eta: 0:00:07 time: 0.139715 data_time: 0.020047 memory: 1836 2022/10/27 12:36:27 - mmengine - INFO - Epoch(val) [10][400/407] eta: 0:00:00 time: 0.131138 data_time: 0.014293 memory: 1836 2022/10/27 12:37:13 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 12:37:31 - mmengine - INFO - Epoch(val) [10][407/407] coco/AP: 0.663735 coco/AP .5: 0.868582 coco/AP .75: 0.733750 coco/AP (M): 0.619597 coco/AP (L): 0.738928 coco/AR: 0.720986 coco/AR .5: 0.909635 coco/AR .75: 0.786209 coco/AR (M): 0.671592 coco/AR (L): 0.791193 2022/10/27 12:37:33 - mmengine - INFO - The best checkpoint with 0.6637 coco/AP at 10 epoch is saved to best_coco/AP_epoch_10.pth. 2022/10/27 12:37:48 - mmengine - INFO - Epoch(train) [11][50/586] lr: 5.000000e-04 eta: 8:54:46 time: 0.295156 data_time: 0.037214 memory: 11131 loss_kpt: 0.000788 acc_pose: 0.732214 loss: 0.000788 2022/10/27 12:38:02 - mmengine - INFO - Epoch(train) [11][100/586] lr: 5.000000e-04 eta: 8:54:45 time: 0.286639 data_time: 0.029430 memory: 11131 loss_kpt: 0.000804 acc_pose: 0.749853 loss: 0.000804 2022/10/27 12:38:13 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:38:16 - mmengine - INFO - Epoch(train) [11][150/586] lr: 5.000000e-04 eta: 8:54:46 time: 0.289292 data_time: 0.027651 memory: 11131 loss_kpt: 0.000785 acc_pose: 0.737950 loss: 0.000785 2022/10/27 12:38:31 - mmengine - INFO - Epoch(train) [11][200/586] lr: 5.000000e-04 eta: 8:54:46 time: 0.288629 data_time: 0.030071 memory: 11131 loss_kpt: 0.000784 acc_pose: 0.770310 loss: 0.000784 2022/10/27 12:38:45 - mmengine - INFO - Epoch(train) [11][250/586] lr: 5.000000e-04 eta: 8:54:49 time: 0.291228 data_time: 0.029087 memory: 11131 loss_kpt: 0.000803 acc_pose: 0.782087 loss: 0.000803 2022/10/27 12:39:00 - mmengine - INFO - Epoch(train) [11][300/586] lr: 5.000000e-04 eta: 8:54:47 time: 0.286767 data_time: 0.027790 memory: 11131 loss_kpt: 0.000771 acc_pose: 0.760833 loss: 0.000771 2022/10/27 12:39:14 - mmengine - INFO - Epoch(train) [11][350/586] lr: 5.000000e-04 eta: 8:54:46 time: 0.288045 data_time: 0.030829 memory: 11131 loss_kpt: 0.000788 acc_pose: 0.843223 loss: 0.000788 2022/10/27 12:39:28 - mmengine - INFO - Epoch(train) [11][400/586] lr: 5.000000e-04 eta: 8:54:42 time: 0.285049 data_time: 0.028549 memory: 11131 loss_kpt: 0.000784 acc_pose: 0.738451 loss: 0.000784 2022/10/27 12:39:43 - mmengine - INFO - Epoch(train) [11][450/586] lr: 5.000000e-04 eta: 8:54:39 time: 0.286857 data_time: 0.026847 memory: 11131 loss_kpt: 0.000791 acc_pose: 0.743277 loss: 0.000791 2022/10/27 12:39:57 - mmengine - INFO - Epoch(train) [11][500/586] lr: 5.000000e-04 eta: 8:54:40 time: 0.290109 data_time: 0.032605 memory: 11131 loss_kpt: 0.000787 acc_pose: 0.734208 loss: 0.000787 2022/10/27 12:40:12 - mmengine - INFO - Epoch(train) [11][550/586] lr: 5.000000e-04 eta: 8:54:42 time: 0.292713 data_time: 0.028347 memory: 11131 loss_kpt: 0.000788 acc_pose: 0.734818 loss: 0.000788 2022/10/27 12:40:22 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:40:37 - mmengine - INFO - Epoch(train) [12][50/586] lr: 5.000000e-04 eta: 8:51:38 time: 0.294599 data_time: 0.035142 memory: 11131 loss_kpt: 0.000782 acc_pose: 0.755187 loss: 0.000782 2022/10/27 12:40:51 - mmengine - INFO - Epoch(train) [12][100/586] lr: 5.000000e-04 eta: 8:51:37 time: 0.287567 data_time: 0.029110 memory: 11131 loss_kpt: 0.000757 acc_pose: 0.829812 loss: 0.000757 2022/10/27 12:41:06 - mmengine - INFO - Epoch(train) [12][150/586] lr: 5.000000e-04 eta: 8:51:45 time: 0.297924 data_time: 0.027325 memory: 11131 loss_kpt: 0.000795 acc_pose: 0.828513 loss: 0.000795 2022/10/27 12:41:21 - mmengine - INFO - Epoch(train) [12][200/586] lr: 5.000000e-04 eta: 8:51:44 time: 0.288445 data_time: 0.026725 memory: 11131 loss_kpt: 0.000784 acc_pose: 0.734600 loss: 0.000784 2022/10/27 12:41:35 - mmengine - INFO - Epoch(train) [12][250/586] lr: 5.000000e-04 eta: 8:51:43 time: 0.288631 data_time: 0.030214 memory: 11131 loss_kpt: 0.000789 acc_pose: 0.744537 loss: 0.000789 2022/10/27 12:41:49 - mmengine - INFO - Epoch(train) [12][300/586] lr: 5.000000e-04 eta: 8:51:37 time: 0.283027 data_time: 0.030776 memory: 11131 loss_kpt: 0.000786 acc_pose: 0.773611 loss: 0.000786 2022/10/27 12:42:04 - mmengine - INFO - Epoch(train) [12][350/586] lr: 5.000000e-04 eta: 8:51:45 time: 0.300315 data_time: 0.028454 memory: 11131 loss_kpt: 0.000804 acc_pose: 0.761708 loss: 0.000804 2022/10/27 12:42:19 - mmengine - INFO - Epoch(train) [12][400/586] lr: 5.000000e-04 eta: 8:51:45 time: 0.290675 data_time: 0.028686 memory: 11131 loss_kpt: 0.000764 acc_pose: 0.805042 loss: 0.000764 2022/10/27 12:42:33 - mmengine - INFO - Epoch(train) [12][450/586] lr: 5.000000e-04 eta: 8:51:41 time: 0.286013 data_time: 0.029777 memory: 11131 loss_kpt: 0.000779 acc_pose: 0.790201 loss: 0.000779 2022/10/27 12:42:48 - mmengine - INFO - Epoch(train) [12][500/586] lr: 5.000000e-04 eta: 8:51:42 time: 0.292365 data_time: 0.030444 memory: 11131 loss_kpt: 0.000784 acc_pose: 0.730517 loss: 0.000784 2022/10/27 12:43:02 - mmengine - INFO - Epoch(train) [12][550/586] lr: 5.000000e-04 eta: 8:51:37 time: 0.285557 data_time: 0.028915 memory: 11131 loss_kpt: 0.000797 acc_pose: 0.688826 loss: 0.000797 2022/10/27 12:43:03 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:43:12 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:43:27 - mmengine - INFO - Epoch(train) [13][50/586] lr: 5.000000e-04 eta: 8:48:51 time: 0.298097 data_time: 0.038794 memory: 11131 loss_kpt: 0.000762 acc_pose: 0.698139 loss: 0.000762 2022/10/27 12:43:42 - mmengine - INFO - Epoch(train) [13][100/586] lr: 5.000000e-04 eta: 8:48:55 time: 0.295513 data_time: 0.031511 memory: 11131 loss_kpt: 0.000771 acc_pose: 0.779761 loss: 0.000771 2022/10/27 12:43:56 - mmengine - INFO - Epoch(train) [13][150/586] lr: 5.000000e-04 eta: 8:48:49 time: 0.283604 data_time: 0.028563 memory: 11131 loss_kpt: 0.000777 acc_pose: 0.767156 loss: 0.000777 2022/10/27 12:44:10 - mmengine - INFO - Epoch(train) [13][200/586] lr: 5.000000e-04 eta: 8:48:45 time: 0.285906 data_time: 0.028952 memory: 11131 loss_kpt: 0.000793 acc_pose: 0.689616 loss: 0.000793 2022/10/27 12:44:25 - mmengine - INFO - Epoch(train) [13][250/586] lr: 5.000000e-04 eta: 8:48:47 time: 0.293769 data_time: 0.029041 memory: 11131 loss_kpt: 0.000790 acc_pose: 0.636031 loss: 0.000790 2022/10/27 12:44:40 - mmengine - INFO - Epoch(train) [13][300/586] lr: 5.000000e-04 eta: 8:48:45 time: 0.288123 data_time: 0.030654 memory: 11131 loss_kpt: 0.000789 acc_pose: 0.755433 loss: 0.000789 2022/10/27 12:44:54 - mmengine - INFO - Epoch(train) [13][350/586] lr: 5.000000e-04 eta: 8:48:44 time: 0.290251 data_time: 0.029305 memory: 11131 loss_kpt: 0.000776 acc_pose: 0.748138 loss: 0.000776 2022/10/27 12:45:08 - mmengine - INFO - Epoch(train) [13][400/586] lr: 5.000000e-04 eta: 8:48:39 time: 0.286444 data_time: 0.032131 memory: 11131 loss_kpt: 0.000765 acc_pose: 0.739160 loss: 0.000765 2022/10/27 12:45:23 - mmengine - INFO - Epoch(train) [13][450/586] lr: 5.000000e-04 eta: 8:48:38 time: 0.289629 data_time: 0.026698 memory: 11131 loss_kpt: 0.000777 acc_pose: 0.768062 loss: 0.000777 2022/10/27 12:45:37 - mmengine - INFO - Epoch(train) [13][500/586] lr: 5.000000e-04 eta: 8:48:34 time: 0.288174 data_time: 0.030291 memory: 11131 loss_kpt: 0.000766 acc_pose: 0.736230 loss: 0.000766 2022/10/27 12:45:52 - mmengine - INFO - Epoch(train) [13][550/586] lr: 5.000000e-04 eta: 8:48:32 time: 0.289784 data_time: 0.030875 memory: 11131 loss_kpt: 0.000765 acc_pose: 0.818886 loss: 0.000765 2022/10/27 12:46:02 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:46:17 - mmengine - INFO - Epoch(train) [14][50/586] lr: 5.000000e-04 eta: 8:45:57 time: 0.297881 data_time: 0.036934 memory: 11131 loss_kpt: 0.000746 acc_pose: 0.710697 loss: 0.000746 2022/10/27 12:46:32 - mmengine - INFO - Epoch(train) [14][100/586] lr: 5.000000e-04 eta: 8:45:57 time: 0.290647 data_time: 0.029905 memory: 11131 loss_kpt: 0.000751 acc_pose: 0.789668 loss: 0.000751 2022/10/27 12:46:46 - mmengine - INFO - Epoch(train) [14][150/586] lr: 5.000000e-04 eta: 8:45:53 time: 0.287003 data_time: 0.031484 memory: 11131 loss_kpt: 0.000773 acc_pose: 0.770461 loss: 0.000773 2022/10/27 12:47:01 - mmengine - INFO - Epoch(train) [14][200/586] lr: 5.000000e-04 eta: 8:45:56 time: 0.296828 data_time: 0.030580 memory: 11131 loss_kpt: 0.000759 acc_pose: 0.793037 loss: 0.000759 2022/10/27 12:47:15 - mmengine - INFO - Epoch(train) [14][250/586] lr: 5.000000e-04 eta: 8:45:51 time: 0.285985 data_time: 0.030578 memory: 11131 loss_kpt: 0.000762 acc_pose: 0.759170 loss: 0.000762 2022/10/27 12:47:29 - mmengine - INFO - Epoch(train) [14][300/586] lr: 5.000000e-04 eta: 8:45:47 time: 0.286744 data_time: 0.028297 memory: 11131 loss_kpt: 0.000769 acc_pose: 0.687240 loss: 0.000769 2022/10/27 12:47:44 - mmengine - INFO - Epoch(train) [14][350/586] lr: 5.000000e-04 eta: 8:45:51 time: 0.298167 data_time: 0.033189 memory: 11131 loss_kpt: 0.000765 acc_pose: 0.779485 loss: 0.000765 2022/10/27 12:47:53 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:47:59 - mmengine - INFO - Epoch(train) [14][400/586] lr: 5.000000e-04 eta: 8:45:46 time: 0.287239 data_time: 0.027243 memory: 11131 loss_kpt: 0.000803 acc_pose: 0.820029 loss: 0.000803 2022/10/27 12:48:13 - mmengine - INFO - Epoch(train) [14][450/586] lr: 5.000000e-04 eta: 8:45:44 time: 0.290489 data_time: 0.031096 memory: 11131 loss_kpt: 0.000760 acc_pose: 0.717909 loss: 0.000760 2022/10/27 12:48:28 - mmengine - INFO - Epoch(train) [14][500/586] lr: 5.000000e-04 eta: 8:45:41 time: 0.288557 data_time: 0.031935 memory: 11131 loss_kpt: 0.000766 acc_pose: 0.740114 loss: 0.000766 2022/10/27 12:48:42 - mmengine - INFO - Epoch(train) [14][550/586] lr: 5.000000e-04 eta: 8:45:43 time: 0.296650 data_time: 0.033361 memory: 11131 loss_kpt: 0.000764 acc_pose: 0.788031 loss: 0.000764 2022/10/27 12:48:53 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:49:08 - mmengine - INFO - Epoch(train) [15][50/586] lr: 5.000000e-04 eta: 8:43:17 time: 0.297425 data_time: 0.035995 memory: 11131 loss_kpt: 0.000731 acc_pose: 0.854383 loss: 0.000731 2022/10/27 12:49:22 - mmengine - INFO - Epoch(train) [15][100/586] lr: 5.000000e-04 eta: 8:43:15 time: 0.289206 data_time: 0.028538 memory: 11131 loss_kpt: 0.000766 acc_pose: 0.746753 loss: 0.000766 2022/10/27 12:49:37 - mmengine - INFO - Epoch(train) [15][150/586] lr: 5.000000e-04 eta: 8:43:10 time: 0.287033 data_time: 0.030402 memory: 11131 loss_kpt: 0.000742 acc_pose: 0.780916 loss: 0.000742 2022/10/27 12:49:51 - mmengine - INFO - Epoch(train) [15][200/586] lr: 5.000000e-04 eta: 8:43:08 time: 0.290822 data_time: 0.030200 memory: 11131 loss_kpt: 0.000765 acc_pose: 0.764984 loss: 0.000765 2022/10/27 12:50:06 - mmengine - INFO - Epoch(train) [15][250/586] lr: 5.000000e-04 eta: 8:43:10 time: 0.297026 data_time: 0.034221 memory: 11131 loss_kpt: 0.000736 acc_pose: 0.718083 loss: 0.000736 2022/10/27 12:50:20 - mmengine - INFO - Epoch(train) [15][300/586] lr: 5.000000e-04 eta: 8:43:07 time: 0.288902 data_time: 0.027820 memory: 11131 loss_kpt: 0.000758 acc_pose: 0.799821 loss: 0.000758 2022/10/27 12:50:35 - mmengine - INFO - Epoch(train) [15][350/586] lr: 5.000000e-04 eta: 8:43:00 time: 0.284878 data_time: 0.029296 memory: 11131 loss_kpt: 0.000752 acc_pose: 0.779842 loss: 0.000752 2022/10/27 12:50:49 - mmengine - INFO - Epoch(train) [15][400/586] lr: 5.000000e-04 eta: 8:42:54 time: 0.285168 data_time: 0.029776 memory: 11131 loss_kpt: 0.000760 acc_pose: 0.766763 loss: 0.000760 2022/10/27 12:51:04 - mmengine - INFO - Epoch(train) [15][450/586] lr: 5.000000e-04 eta: 8:42:54 time: 0.294243 data_time: 0.028855 memory: 11131 loss_kpt: 0.000759 acc_pose: 0.734503 loss: 0.000759 2022/10/27 12:51:18 - mmengine - INFO - Epoch(train) [15][500/586] lr: 5.000000e-04 eta: 8:42:50 time: 0.289465 data_time: 0.028656 memory: 11131 loss_kpt: 0.000765 acc_pose: 0.793987 loss: 0.000765 2022/10/27 12:51:32 - mmengine - INFO - Epoch(train) [15][550/586] lr: 5.000000e-04 eta: 8:42:45 time: 0.288524 data_time: 0.028868 memory: 11131 loss_kpt: 0.000765 acc_pose: 0.702788 loss: 0.000765 2022/10/27 12:51:43 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:51:58 - mmengine - INFO - Epoch(train) [16][50/586] lr: 5.000000e-04 eta: 8:40:28 time: 0.295383 data_time: 0.034592 memory: 11131 loss_kpt: 0.000749 acc_pose: 0.779016 loss: 0.000749 2022/10/27 12:52:12 - mmengine - INFO - Epoch(train) [16][100/586] lr: 5.000000e-04 eta: 8:40:27 time: 0.292985 data_time: 0.029170 memory: 11131 loss_kpt: 0.000786 acc_pose: 0.706237 loss: 0.000786 2022/10/27 12:52:27 - mmengine - INFO - Epoch(train) [16][150/586] lr: 5.000000e-04 eta: 8:40:27 time: 0.295614 data_time: 0.038485 memory: 11131 loss_kpt: 0.000757 acc_pose: 0.773850 loss: 0.000757 2022/10/27 12:52:41 - mmengine - INFO - Epoch(train) [16][200/586] lr: 5.000000e-04 eta: 8:40:24 time: 0.290782 data_time: 0.029465 memory: 11131 loss_kpt: 0.000733 acc_pose: 0.786078 loss: 0.000733 2022/10/27 12:52:44 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:52:56 - mmengine - INFO - Epoch(train) [16][250/586] lr: 5.000000e-04 eta: 8:40:18 time: 0.285307 data_time: 0.028850 memory: 11131 loss_kpt: 0.000753 acc_pose: 0.771894 loss: 0.000753 2022/10/27 12:53:10 - mmengine - INFO - Epoch(train) [16][300/586] lr: 5.000000e-04 eta: 8:40:11 time: 0.285329 data_time: 0.027976 memory: 11131 loss_kpt: 0.000759 acc_pose: 0.740545 loss: 0.000759 2022/10/27 12:53:25 - mmengine - INFO - Epoch(train) [16][350/586] lr: 5.000000e-04 eta: 8:40:12 time: 0.296097 data_time: 0.030567 memory: 11131 loss_kpt: 0.000734 acc_pose: 0.789330 loss: 0.000734 2022/10/27 12:53:39 - mmengine - INFO - Epoch(train) [16][400/586] lr: 5.000000e-04 eta: 8:40:08 time: 0.290065 data_time: 0.027767 memory: 11131 loss_kpt: 0.000757 acc_pose: 0.799279 loss: 0.000757 2022/10/27 12:53:54 - mmengine - INFO - Epoch(train) [16][450/586] lr: 5.000000e-04 eta: 8:40:01 time: 0.284527 data_time: 0.028344 memory: 11131 loss_kpt: 0.000759 acc_pose: 0.778508 loss: 0.000759 2022/10/27 12:54:08 - mmengine - INFO - Epoch(train) [16][500/586] lr: 5.000000e-04 eta: 8:39:59 time: 0.293184 data_time: 0.030794 memory: 11131 loss_kpt: 0.000738 acc_pose: 0.719757 loss: 0.000738 2022/10/27 12:54:23 - mmengine - INFO - Epoch(train) [16][550/586] lr: 5.000000e-04 eta: 8:39:57 time: 0.294259 data_time: 0.032520 memory: 11131 loss_kpt: 0.000730 acc_pose: 0.847406 loss: 0.000730 2022/10/27 12:54:33 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:54:48 - mmengine - INFO - Epoch(train) [17][50/586] lr: 5.000000e-04 eta: 8:37:52 time: 0.303340 data_time: 0.041167 memory: 11131 loss_kpt: 0.000753 acc_pose: 0.746184 loss: 0.000753 2022/10/27 12:55:03 - mmengine - INFO - Epoch(train) [17][100/586] lr: 5.000000e-04 eta: 8:37:48 time: 0.289986 data_time: 0.029670 memory: 11131 loss_kpt: 0.000755 acc_pose: 0.798298 loss: 0.000755 2022/10/27 12:55:17 - mmengine - INFO - Epoch(train) [17][150/586] lr: 5.000000e-04 eta: 8:37:42 time: 0.286146 data_time: 0.029108 memory: 11131 loss_kpt: 0.000747 acc_pose: 0.778216 loss: 0.000747 2022/10/27 12:55:32 - mmengine - INFO - Epoch(train) [17][200/586] lr: 5.000000e-04 eta: 8:37:42 time: 0.297002 data_time: 0.029210 memory: 11131 loss_kpt: 0.000759 acc_pose: 0.710235 loss: 0.000759 2022/10/27 12:55:46 - mmengine - INFO - Epoch(train) [17][250/586] lr: 5.000000e-04 eta: 8:37:35 time: 0.284788 data_time: 0.027260 memory: 11131 loss_kpt: 0.000747 acc_pose: 0.857351 loss: 0.000747 2022/10/27 12:56:01 - mmengine - INFO - Epoch(train) [17][300/586] lr: 5.000000e-04 eta: 8:37:32 time: 0.292731 data_time: 0.028915 memory: 11131 loss_kpt: 0.000762 acc_pose: 0.823921 loss: 0.000762 2022/10/27 12:56:15 - mmengine - INFO - Epoch(train) [17][350/586] lr: 5.000000e-04 eta: 8:37:27 time: 0.288391 data_time: 0.029961 memory: 11131 loss_kpt: 0.000751 acc_pose: 0.793716 loss: 0.000751 2022/10/27 12:56:30 - mmengine - INFO - Epoch(train) [17][400/586] lr: 5.000000e-04 eta: 8:37:20 time: 0.284507 data_time: 0.027974 memory: 11131 loss_kpt: 0.000731 acc_pose: 0.813323 loss: 0.000731 2022/10/27 12:56:44 - mmengine - INFO - Epoch(train) [17][450/586] lr: 5.000000e-04 eta: 8:37:19 time: 0.296030 data_time: 0.031976 memory: 11131 loss_kpt: 0.000738 acc_pose: 0.778959 loss: 0.000738 2022/10/27 12:56:59 - mmengine - INFO - Epoch(train) [17][500/586] lr: 5.000000e-04 eta: 8:37:10 time: 0.282562 data_time: 0.028488 memory: 11131 loss_kpt: 0.000747 acc_pose: 0.806909 loss: 0.000747 2022/10/27 12:57:13 - mmengine - INFO - Epoch(train) [17][550/586] lr: 5.000000e-04 eta: 8:37:06 time: 0.290983 data_time: 0.032574 memory: 11131 loss_kpt: 0.000754 acc_pose: 0.816838 loss: 0.000754 2022/10/27 12:57:23 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:57:35 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 12:57:39 - mmengine - INFO - Epoch(train) [18][50/586] lr: 5.000000e-04 eta: 8:35:09 time: 0.307727 data_time: 0.036604 memory: 11131 loss_kpt: 0.000743 acc_pose: 0.826324 loss: 0.000743 2022/10/27 12:57:53 - mmengine - INFO - Epoch(train) [18][100/586] lr: 5.000000e-04 eta: 8:35:03 time: 0.286670 data_time: 0.026859 memory: 11131 loss_kpt: 0.000739 acc_pose: 0.751430 loss: 0.000739 2022/10/27 12:58:07 - mmengine - INFO - Epoch(train) [18][150/586] lr: 5.000000e-04 eta: 8:34:59 time: 0.290690 data_time: 0.032114 memory: 11131 loss_kpt: 0.000746 acc_pose: 0.687269 loss: 0.000746 2022/10/27 12:58:22 - mmengine - INFO - Epoch(train) [18][200/586] lr: 5.000000e-04 eta: 8:34:55 time: 0.291420 data_time: 0.028123 memory: 11131 loss_kpt: 0.000732 acc_pose: 0.831608 loss: 0.000732 2022/10/27 12:58:36 - mmengine - INFO - Epoch(train) [18][250/586] lr: 5.000000e-04 eta: 8:34:48 time: 0.284970 data_time: 0.028603 memory: 11131 loss_kpt: 0.000765 acc_pose: 0.770344 loss: 0.000765 2022/10/27 12:58:51 - mmengine - INFO - Epoch(train) [18][300/586] lr: 5.000000e-04 eta: 8:34:44 time: 0.292107 data_time: 0.030644 memory: 11131 loss_kpt: 0.000757 acc_pose: 0.743438 loss: 0.000757 2022/10/27 12:59:05 - mmengine - INFO - Epoch(train) [18][350/586] lr: 5.000000e-04 eta: 8:34:39 time: 0.288233 data_time: 0.027748 memory: 11131 loss_kpt: 0.000747 acc_pose: 0.763476 loss: 0.000747 2022/10/27 12:59:20 - mmengine - INFO - Epoch(train) [18][400/586] lr: 5.000000e-04 eta: 8:34:33 time: 0.288181 data_time: 0.027303 memory: 11131 loss_kpt: 0.000729 acc_pose: 0.816952 loss: 0.000729 2022/10/27 12:59:34 - mmengine - INFO - Epoch(train) [18][450/586] lr: 5.000000e-04 eta: 8:34:26 time: 0.286566 data_time: 0.030018 memory: 11131 loss_kpt: 0.000722 acc_pose: 0.712296 loss: 0.000722 2022/10/27 12:59:48 - mmengine - INFO - Epoch(train) [18][500/586] lr: 5.000000e-04 eta: 8:34:19 time: 0.287358 data_time: 0.028961 memory: 11131 loss_kpt: 0.000749 acc_pose: 0.731542 loss: 0.000749 2022/10/27 13:00:03 - mmengine - INFO - Epoch(train) [18][550/586] lr: 5.000000e-04 eta: 8:34:18 time: 0.296912 data_time: 0.031186 memory: 11131 loss_kpt: 0.000728 acc_pose: 0.723482 loss: 0.000728 2022/10/27 13:00:14 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:00:28 - mmengine - INFO - Epoch(train) [19][50/586] lr: 5.000000e-04 eta: 8:32:21 time: 0.295262 data_time: 0.037744 memory: 11131 loss_kpt: 0.000731 acc_pose: 0.760411 loss: 0.000731 2022/10/27 13:00:43 - mmengine - INFO - Epoch(train) [19][100/586] lr: 5.000000e-04 eta: 8:32:16 time: 0.290329 data_time: 0.031141 memory: 11131 loss_kpt: 0.000729 acc_pose: 0.828074 loss: 0.000729 2022/10/27 13:00:57 - mmengine - INFO - Epoch(train) [19][150/586] lr: 5.000000e-04 eta: 8:32:11 time: 0.289960 data_time: 0.028889 memory: 11131 loss_kpt: 0.000757 acc_pose: 0.794302 loss: 0.000757 2022/10/27 13:01:12 - mmengine - INFO - Epoch(train) [19][200/586] lr: 5.000000e-04 eta: 8:32:08 time: 0.294460 data_time: 0.028209 memory: 11131 loss_kpt: 0.000726 acc_pose: 0.781329 loss: 0.000726 2022/10/27 13:01:27 - mmengine - INFO - Epoch(train) [19][250/586] lr: 5.000000e-04 eta: 8:32:02 time: 0.287436 data_time: 0.032500 memory: 11131 loss_kpt: 0.000720 acc_pose: 0.797144 loss: 0.000720 2022/10/27 13:01:41 - mmengine - INFO - Epoch(train) [19][300/586] lr: 5.000000e-04 eta: 8:31:58 time: 0.292185 data_time: 0.027510 memory: 11131 loss_kpt: 0.000734 acc_pose: 0.788259 loss: 0.000734 2022/10/27 13:01:56 - mmengine - INFO - Epoch(train) [19][350/586] lr: 5.000000e-04 eta: 8:31:51 time: 0.288062 data_time: 0.029202 memory: 11131 loss_kpt: 0.000729 acc_pose: 0.765146 loss: 0.000729 2022/10/27 13:02:10 - mmengine - INFO - Epoch(train) [19][400/586] lr: 5.000000e-04 eta: 8:31:49 time: 0.295529 data_time: 0.029210 memory: 11131 loss_kpt: 0.000732 acc_pose: 0.774349 loss: 0.000732 2022/10/27 13:02:25 - mmengine - INFO - Epoch(train) [19][450/586] lr: 5.000000e-04 eta: 8:31:40 time: 0.284091 data_time: 0.032209 memory: 11131 loss_kpt: 0.000731 acc_pose: 0.695268 loss: 0.000731 2022/10/27 13:02:25 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:02:39 - mmengine - INFO - Epoch(train) [19][500/586] lr: 5.000000e-04 eta: 8:31:35 time: 0.290772 data_time: 0.029334 memory: 11131 loss_kpt: 0.000753 acc_pose: 0.809414 loss: 0.000753 2022/10/27 13:02:53 - mmengine - INFO - Epoch(train) [19][550/586] lr: 5.000000e-04 eta: 8:31:28 time: 0.286924 data_time: 0.030636 memory: 11131 loss_kpt: 0.000734 acc_pose: 0.864695 loss: 0.000734 2022/10/27 13:03:04 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:03:19 - mmengine - INFO - Epoch(train) [20][50/586] lr: 5.000000e-04 eta: 8:29:39 time: 0.300257 data_time: 0.034610 memory: 11131 loss_kpt: 0.000735 acc_pose: 0.734575 loss: 0.000735 2022/10/27 13:03:33 - mmengine - INFO - Epoch(train) [20][100/586] lr: 5.000000e-04 eta: 8:29:34 time: 0.291678 data_time: 0.027444 memory: 11131 loss_kpt: 0.000723 acc_pose: 0.784198 loss: 0.000723 2022/10/27 13:03:48 - mmengine - INFO - Epoch(train) [20][150/586] lr: 5.000000e-04 eta: 8:29:27 time: 0.286302 data_time: 0.028579 memory: 11131 loss_kpt: 0.000724 acc_pose: 0.774939 loss: 0.000724 2022/10/27 13:04:02 - mmengine - INFO - Epoch(train) [20][200/586] lr: 5.000000e-04 eta: 8:29:21 time: 0.289545 data_time: 0.029500 memory: 11131 loss_kpt: 0.000727 acc_pose: 0.796379 loss: 0.000727 2022/10/27 13:04:17 - mmengine - INFO - Epoch(train) [20][250/586] lr: 5.000000e-04 eta: 8:29:17 time: 0.292487 data_time: 0.029334 memory: 11131 loss_kpt: 0.000735 acc_pose: 0.774297 loss: 0.000735 2022/10/27 13:04:31 - mmengine - INFO - Epoch(train) [20][300/586] lr: 5.000000e-04 eta: 8:29:12 time: 0.292425 data_time: 0.028144 memory: 11131 loss_kpt: 0.000726 acc_pose: 0.855782 loss: 0.000726 2022/10/27 13:04:46 - mmengine - INFO - Epoch(train) [20][350/586] lr: 5.000000e-04 eta: 8:29:06 time: 0.289759 data_time: 0.028216 memory: 11131 loss_kpt: 0.000722 acc_pose: 0.788695 loss: 0.000722 2022/10/27 13:05:00 - mmengine - INFO - Epoch(train) [20][400/586] lr: 5.000000e-04 eta: 8:29:00 time: 0.288133 data_time: 0.028148 memory: 11131 loss_kpt: 0.000718 acc_pose: 0.820583 loss: 0.000718 2022/10/27 13:05:15 - mmengine - INFO - Epoch(train) [20][450/586] lr: 5.000000e-04 eta: 8:28:53 time: 0.287854 data_time: 0.031944 memory: 11131 loss_kpt: 0.000736 acc_pose: 0.805261 loss: 0.000736 2022/10/27 13:05:29 - mmengine - INFO - Epoch(train) [20][500/586] lr: 5.000000e-04 eta: 8:28:47 time: 0.289787 data_time: 0.029401 memory: 11131 loss_kpt: 0.000712 acc_pose: 0.806054 loss: 0.000712 2022/10/27 13:05:44 - mmengine - INFO - Epoch(train) [20][550/586] lr: 5.000000e-04 eta: 8:28:41 time: 0.290578 data_time: 0.029555 memory: 11131 loss_kpt: 0.000708 acc_pose: 0.795767 loss: 0.000708 2022/10/27 13:05:54 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:05:54 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/10/27 13:06:05 - mmengine - INFO - Epoch(val) [20][50/407] eta: 0:00:52 time: 0.145912 data_time: 0.024224 memory: 11131 2022/10/27 13:06:12 - mmengine - INFO - Epoch(val) [20][100/407] eta: 0:00:42 time: 0.139007 data_time: 0.019850 memory: 1836 2022/10/27 13:06:19 - mmengine - INFO - Epoch(val) [20][150/407] eta: 0:00:36 time: 0.142855 data_time: 0.018445 memory: 1836 2022/10/27 13:06:26 - mmengine - INFO - Epoch(val) [20][200/407] eta: 0:00:28 time: 0.138944 data_time: 0.018192 memory: 1836 2022/10/27 13:06:33 - mmengine - INFO - Epoch(val) [20][250/407] eta: 0:00:21 time: 0.136955 data_time: 0.016652 memory: 1836 2022/10/27 13:06:39 - mmengine - INFO - Epoch(val) [20][300/407] eta: 0:00:14 time: 0.133315 data_time: 0.013875 memory: 1836 2022/10/27 13:06:46 - mmengine - INFO - Epoch(val) [20][350/407] eta: 0:00:07 time: 0.133797 data_time: 0.015112 memory: 1836 2022/10/27 13:06:53 - mmengine - INFO - Epoch(val) [20][400/407] eta: 0:00:00 time: 0.128474 data_time: 0.011739 memory: 1836 2022/10/27 13:07:39 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 13:07:56 - mmengine - INFO - Epoch(val) [20][407/407] coco/AP: 0.691500 coco/AP .5: 0.879403 coco/AP .75: 0.763787 coco/AP (M): 0.649123 coco/AP (L): 0.763882 coco/AR: 0.746615 coco/AR .5: 0.918608 coco/AR .75: 0.813130 coco/AR (M): 0.698416 coco/AR (L): 0.815459 2022/10/27 13:07:57 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_10.pth is removed 2022/10/27 13:07:59 - mmengine - INFO - The best checkpoint with 0.6915 coco/AP at 20 epoch is saved to best_coco/AP_epoch_20.pth. 2022/10/27 13:08:13 - mmengine - INFO - Epoch(train) [21][50/586] lr: 5.000000e-04 eta: 8:26:55 time: 0.297960 data_time: 0.040738 memory: 11131 loss_kpt: 0.000716 acc_pose: 0.805889 loss: 0.000716 2022/10/27 13:08:28 - mmengine - INFO - Epoch(train) [21][100/586] lr: 5.000000e-04 eta: 8:26:50 time: 0.290960 data_time: 0.027881 memory: 11131 loss_kpt: 0.000725 acc_pose: 0.774377 loss: 0.000725 2022/10/27 13:08:43 - mmengine - INFO - Epoch(train) [21][150/586] lr: 5.000000e-04 eta: 8:26:44 time: 0.290454 data_time: 0.028959 memory: 11131 loss_kpt: 0.000731 acc_pose: 0.777740 loss: 0.000731 2022/10/27 13:08:57 - mmengine - INFO - Epoch(train) [21][200/586] lr: 5.000000e-04 eta: 8:26:39 time: 0.292613 data_time: 0.031074 memory: 11131 loss_kpt: 0.000709 acc_pose: 0.746108 loss: 0.000709 2022/10/27 13:09:12 - mmengine - INFO - Epoch(train) [21][250/586] lr: 5.000000e-04 eta: 8:26:32 time: 0.287087 data_time: 0.027648 memory: 11131 loss_kpt: 0.000710 acc_pose: 0.797392 loss: 0.000710 2022/10/27 13:09:20 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:09:26 - mmengine - INFO - Epoch(train) [21][300/586] lr: 5.000000e-04 eta: 8:26:25 time: 0.288031 data_time: 0.028291 memory: 11131 loss_kpt: 0.000731 acc_pose: 0.780863 loss: 0.000731 2022/10/27 13:09:40 - mmengine - INFO - Epoch(train) [21][350/586] lr: 5.000000e-04 eta: 8:26:17 time: 0.286320 data_time: 0.028978 memory: 11131 loss_kpt: 0.000727 acc_pose: 0.799118 loss: 0.000727 2022/10/27 13:09:55 - mmengine - INFO - Epoch(train) [21][400/586] lr: 5.000000e-04 eta: 8:26:11 time: 0.290926 data_time: 0.028637 memory: 11131 loss_kpt: 0.000710 acc_pose: 0.831260 loss: 0.000710 2022/10/27 13:10:09 - mmengine - INFO - Epoch(train) [21][450/586] lr: 5.000000e-04 eta: 8:26:04 time: 0.286918 data_time: 0.029683 memory: 11131 loss_kpt: 0.000729 acc_pose: 0.759291 loss: 0.000729 2022/10/27 13:10:24 - mmengine - INFO - Epoch(train) [21][500/586] lr: 5.000000e-04 eta: 8:25:57 time: 0.290078 data_time: 0.031738 memory: 11131 loss_kpt: 0.000714 acc_pose: 0.777119 loss: 0.000714 2022/10/27 13:10:38 - mmengine - INFO - Epoch(train) [21][550/586] lr: 5.000000e-04 eta: 8:25:50 time: 0.287149 data_time: 0.031392 memory: 11131 loss_kpt: 0.000734 acc_pose: 0.756066 loss: 0.000734 2022/10/27 13:10:48 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:11:03 - mmengine - INFO - Epoch(train) [22][50/586] lr: 5.000000e-04 eta: 8:24:11 time: 0.303991 data_time: 0.040618 memory: 11131 loss_kpt: 0.000732 acc_pose: 0.753252 loss: 0.000732 2022/10/27 13:11:18 - mmengine - INFO - Epoch(train) [22][100/586] lr: 5.000000e-04 eta: 8:24:04 time: 0.288170 data_time: 0.031944 memory: 11131 loss_kpt: 0.000743 acc_pose: 0.782131 loss: 0.000743 2022/10/27 13:11:32 - mmengine - INFO - Epoch(train) [22][150/586] lr: 5.000000e-04 eta: 8:23:56 time: 0.286671 data_time: 0.030674 memory: 11131 loss_kpt: 0.000698 acc_pose: 0.831778 loss: 0.000698 2022/10/27 13:11:47 - mmengine - INFO - Epoch(train) [22][200/586] lr: 5.000000e-04 eta: 8:23:50 time: 0.290293 data_time: 0.029528 memory: 11131 loss_kpt: 0.000734 acc_pose: 0.685401 loss: 0.000734 2022/10/27 13:12:01 - mmengine - INFO - Epoch(train) [22][250/586] lr: 5.000000e-04 eta: 8:23:42 time: 0.285891 data_time: 0.029292 memory: 11131 loss_kpt: 0.000695 acc_pose: 0.820554 loss: 0.000695 2022/10/27 13:12:16 - mmengine - INFO - Epoch(train) [22][300/586] lr: 5.000000e-04 eta: 8:23:37 time: 0.294073 data_time: 0.032299 memory: 11131 loss_kpt: 0.000712 acc_pose: 0.832999 loss: 0.000712 2022/10/27 13:12:30 - mmengine - INFO - Epoch(train) [22][350/586] lr: 5.000000e-04 eta: 8:23:27 time: 0.282201 data_time: 0.029438 memory: 11131 loss_kpt: 0.000726 acc_pose: 0.756874 loss: 0.000726 2022/10/27 13:12:44 - mmengine - INFO - Epoch(train) [22][400/586] lr: 5.000000e-04 eta: 8:23:21 time: 0.290637 data_time: 0.030369 memory: 11131 loss_kpt: 0.000697 acc_pose: 0.848189 loss: 0.000697 2022/10/27 13:12:59 - mmengine - INFO - Epoch(train) [22][450/586] lr: 5.000000e-04 eta: 8:23:12 time: 0.285001 data_time: 0.029476 memory: 11131 loss_kpt: 0.000696 acc_pose: 0.837456 loss: 0.000696 2022/10/27 13:13:13 - mmengine - INFO - Epoch(train) [22][500/586] lr: 5.000000e-04 eta: 8:23:06 time: 0.289683 data_time: 0.029927 memory: 11131 loss_kpt: 0.000712 acc_pose: 0.725400 loss: 0.000712 2022/10/27 13:13:28 - mmengine - INFO - Epoch(train) [22][550/586] lr: 5.000000e-04 eta: 8:23:00 time: 0.292109 data_time: 0.028249 memory: 11131 loss_kpt: 0.000724 acc_pose: 0.740909 loss: 0.000724 2022/10/27 13:13:38 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:13:53 - mmengine - INFO - Epoch(train) [23][50/586] lr: 5.000000e-04 eta: 8:21:25 time: 0.303970 data_time: 0.040058 memory: 11131 loss_kpt: 0.000691 acc_pose: 0.834495 loss: 0.000691 2022/10/27 13:14:07 - mmengine - INFO - Epoch(train) [23][100/586] lr: 5.000000e-04 eta: 8:21:18 time: 0.289598 data_time: 0.027476 memory: 11131 loss_kpt: 0.000730 acc_pose: 0.800591 loss: 0.000730 2022/10/27 13:14:10 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:14:22 - mmengine - INFO - Epoch(train) [23][150/586] lr: 5.000000e-04 eta: 8:21:14 time: 0.295164 data_time: 0.028288 memory: 11131 loss_kpt: 0.000717 acc_pose: 0.737583 loss: 0.000717 2022/10/27 13:14:37 - mmengine - INFO - Epoch(train) [23][200/586] lr: 5.000000e-04 eta: 8:21:07 time: 0.288697 data_time: 0.027944 memory: 11131 loss_kpt: 0.000714 acc_pose: 0.826847 loss: 0.000714 2022/10/27 13:14:51 - mmengine - INFO - Epoch(train) [23][250/586] lr: 5.000000e-04 eta: 8:20:59 time: 0.288078 data_time: 0.028555 memory: 11131 loss_kpt: 0.000699 acc_pose: 0.788129 loss: 0.000699 2022/10/27 13:15:05 - mmengine - INFO - Epoch(train) [23][300/586] lr: 5.000000e-04 eta: 8:20:51 time: 0.285590 data_time: 0.028980 memory: 11131 loss_kpt: 0.000712 acc_pose: 0.709035 loss: 0.000712 2022/10/27 13:15:20 - mmengine - INFO - Epoch(train) [23][350/586] lr: 5.000000e-04 eta: 8:20:43 time: 0.287868 data_time: 0.030438 memory: 11131 loss_kpt: 0.000712 acc_pose: 0.804965 loss: 0.000712 2022/10/27 13:15:34 - mmengine - INFO - Epoch(train) [23][400/586] lr: 5.000000e-04 eta: 8:20:36 time: 0.289929 data_time: 0.027616 memory: 11131 loss_kpt: 0.000728 acc_pose: 0.810181 loss: 0.000728 2022/10/27 13:15:49 - mmengine - INFO - Epoch(train) [23][450/586] lr: 5.000000e-04 eta: 8:20:28 time: 0.288094 data_time: 0.031365 memory: 11131 loss_kpt: 0.000702 acc_pose: 0.751762 loss: 0.000702 2022/10/27 13:16:03 - mmengine - INFO - Epoch(train) [23][500/586] lr: 5.000000e-04 eta: 8:20:20 time: 0.286754 data_time: 0.030932 memory: 11131 loss_kpt: 0.000718 acc_pose: 0.791157 loss: 0.000718 2022/10/27 13:16:17 - mmengine - INFO - Epoch(train) [23][550/586] lr: 5.000000e-04 eta: 8:20:11 time: 0.286379 data_time: 0.027834 memory: 11131 loss_kpt: 0.000698 acc_pose: 0.828875 loss: 0.000698 2022/10/27 13:16:28 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:16:43 - mmengine - INFO - Epoch(train) [24][50/586] lr: 5.000000e-04 eta: 8:18:40 time: 0.303717 data_time: 0.039871 memory: 11131 loss_kpt: 0.000715 acc_pose: 0.833510 loss: 0.000715 2022/10/27 13:16:57 - mmengine - INFO - Epoch(train) [24][100/586] lr: 5.000000e-04 eta: 8:18:32 time: 0.286776 data_time: 0.028761 memory: 11131 loss_kpt: 0.000722 acc_pose: 0.815946 loss: 0.000722 2022/10/27 13:17:12 - mmengine - INFO - Epoch(train) [24][150/586] lr: 5.000000e-04 eta: 8:18:24 time: 0.287609 data_time: 0.027375 memory: 11131 loss_kpt: 0.000700 acc_pose: 0.797168 loss: 0.000700 2022/10/27 13:17:26 - mmengine - INFO - Epoch(train) [24][200/586] lr: 5.000000e-04 eta: 8:18:18 time: 0.291254 data_time: 0.028230 memory: 11131 loss_kpt: 0.000713 acc_pose: 0.770436 loss: 0.000713 2022/10/27 13:17:41 - mmengine - INFO - Epoch(train) [24][250/586] lr: 5.000000e-04 eta: 8:18:10 time: 0.288137 data_time: 0.028531 memory: 11131 loss_kpt: 0.000720 acc_pose: 0.771145 loss: 0.000720 2022/10/27 13:17:55 - mmengine - INFO - Epoch(train) [24][300/586] lr: 5.000000e-04 eta: 8:18:03 time: 0.290508 data_time: 0.034118 memory: 11131 loss_kpt: 0.000740 acc_pose: 0.865561 loss: 0.000740 2022/10/27 13:18:09 - mmengine - INFO - Epoch(train) [24][350/586] lr: 5.000000e-04 eta: 8:17:53 time: 0.283109 data_time: 0.030841 memory: 11131 loss_kpt: 0.000687 acc_pose: 0.783759 loss: 0.000687 2022/10/27 13:18:24 - mmengine - INFO - Epoch(train) [24][400/586] lr: 5.000000e-04 eta: 8:17:45 time: 0.287976 data_time: 0.027657 memory: 11131 loss_kpt: 0.000699 acc_pose: 0.788417 loss: 0.000699 2022/10/27 13:18:38 - mmengine - INFO - Epoch(train) [24][450/586] lr: 5.000000e-04 eta: 8:17:37 time: 0.288485 data_time: 0.029306 memory: 11131 loss_kpt: 0.000690 acc_pose: 0.764278 loss: 0.000690 2022/10/27 13:18:53 - mmengine - INFO - Epoch(train) [24][500/586] lr: 5.000000e-04 eta: 8:17:30 time: 0.290196 data_time: 0.028832 memory: 11131 loss_kpt: 0.000740 acc_pose: 0.873922 loss: 0.000740 2022/10/27 13:18:59 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:19:07 - mmengine - INFO - Epoch(train) [24][550/586] lr: 5.000000e-04 eta: 8:17:23 time: 0.291183 data_time: 0.031456 memory: 11131 loss_kpt: 0.000711 acc_pose: 0.825707 loss: 0.000711 2022/10/27 13:19:17 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:19:32 - mmengine - INFO - Epoch(train) [25][50/586] lr: 5.000000e-04 eta: 8:15:54 time: 0.300528 data_time: 0.042886 memory: 11131 loss_kpt: 0.000714 acc_pose: 0.869606 loss: 0.000714 2022/10/27 13:19:47 - mmengine - INFO - Epoch(train) [25][100/586] lr: 5.000000e-04 eta: 8:15:47 time: 0.290843 data_time: 0.031292 memory: 11131 loss_kpt: 0.000716 acc_pose: 0.707079 loss: 0.000716 2022/10/27 13:20:01 - mmengine - INFO - Epoch(train) [25][150/586] lr: 5.000000e-04 eta: 8:15:40 time: 0.290862 data_time: 0.028169 memory: 11131 loss_kpt: 0.000696 acc_pose: 0.772244 loss: 0.000696 2022/10/27 13:20:16 - mmengine - INFO - Epoch(train) [25][200/586] lr: 5.000000e-04 eta: 8:15:32 time: 0.288533 data_time: 0.029432 memory: 11131 loss_kpt: 0.000692 acc_pose: 0.806338 loss: 0.000692 2022/10/27 13:20:30 - mmengine - INFO - Epoch(train) [25][250/586] lr: 5.000000e-04 eta: 8:15:23 time: 0.285216 data_time: 0.028411 memory: 11131 loss_kpt: 0.000689 acc_pose: 0.797319 loss: 0.000689 2022/10/27 13:20:44 - mmengine - INFO - Epoch(train) [25][300/586] lr: 5.000000e-04 eta: 8:15:14 time: 0.284852 data_time: 0.029122 memory: 11131 loss_kpt: 0.000695 acc_pose: 0.752278 loss: 0.000695 2022/10/27 13:20:59 - mmengine - INFO - Epoch(train) [25][350/586] lr: 5.000000e-04 eta: 8:15:06 time: 0.289329 data_time: 0.029764 memory: 11131 loss_kpt: 0.000706 acc_pose: 0.794552 loss: 0.000706 2022/10/27 13:21:13 - mmengine - INFO - Epoch(train) [25][400/586] lr: 5.000000e-04 eta: 8:14:58 time: 0.287780 data_time: 0.029124 memory: 11131 loss_kpt: 0.000705 acc_pose: 0.829715 loss: 0.000705 2022/10/27 13:21:28 - mmengine - INFO - Epoch(train) [25][450/586] lr: 5.000000e-04 eta: 8:14:50 time: 0.288125 data_time: 0.034249 memory: 11131 loss_kpt: 0.000690 acc_pose: 0.811692 loss: 0.000690 2022/10/27 13:21:42 - mmengine - INFO - Epoch(train) [25][500/586] lr: 5.000000e-04 eta: 8:14:41 time: 0.286662 data_time: 0.029136 memory: 11131 loss_kpt: 0.000715 acc_pose: 0.681759 loss: 0.000715 2022/10/27 13:21:56 - mmengine - INFO - Epoch(train) [25][550/586] lr: 5.000000e-04 eta: 8:14:33 time: 0.288526 data_time: 0.029520 memory: 11131 loss_kpt: 0.000724 acc_pose: 0.784768 loss: 0.000724 2022/10/27 13:22:07 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:22:22 - mmengine - INFO - Epoch(train) [26][50/586] lr: 5.000000e-04 eta: 8:13:06 time: 0.298681 data_time: 0.036499 memory: 11131 loss_kpt: 0.000681 acc_pose: 0.767745 loss: 0.000681 2022/10/27 13:22:36 - mmengine - INFO - Epoch(train) [26][100/586] lr: 5.000000e-04 eta: 8:12:59 time: 0.290870 data_time: 0.028989 memory: 11131 loss_kpt: 0.000712 acc_pose: 0.833067 loss: 0.000712 2022/10/27 13:22:50 - mmengine - INFO - Epoch(train) [26][150/586] lr: 5.000000e-04 eta: 8:12:50 time: 0.285745 data_time: 0.027572 memory: 11131 loss_kpt: 0.000698 acc_pose: 0.792393 loss: 0.000698 2022/10/27 13:23:05 - mmengine - INFO - Epoch(train) [26][200/586] lr: 5.000000e-04 eta: 8:12:41 time: 0.287322 data_time: 0.028092 memory: 11131 loss_kpt: 0.000713 acc_pose: 0.756433 loss: 0.000713 2022/10/27 13:23:19 - mmengine - INFO - Epoch(train) [26][250/586] lr: 5.000000e-04 eta: 8:12:34 time: 0.289619 data_time: 0.026680 memory: 11131 loss_kpt: 0.000683 acc_pose: 0.745224 loss: 0.000683 2022/10/27 13:23:34 - mmengine - INFO - Epoch(train) [26][300/586] lr: 5.000000e-04 eta: 8:12:25 time: 0.285829 data_time: 0.026990 memory: 11131 loss_kpt: 0.000691 acc_pose: 0.871043 loss: 0.000691 2022/10/27 13:23:48 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:23:48 - mmengine - INFO - Epoch(train) [26][350/586] lr: 5.000000e-04 eta: 8:12:15 time: 0.283373 data_time: 0.029752 memory: 11131 loss_kpt: 0.000681 acc_pose: 0.785466 loss: 0.000681 2022/10/27 13:24:02 - mmengine - INFO - Epoch(train) [26][400/586] lr: 5.000000e-04 eta: 8:12:05 time: 0.285778 data_time: 0.030057 memory: 11131 loss_kpt: 0.000701 acc_pose: 0.802383 loss: 0.000701 2022/10/27 13:24:16 - mmengine - INFO - Epoch(train) [26][450/586] lr: 5.000000e-04 eta: 8:11:56 time: 0.284854 data_time: 0.029827 memory: 11131 loss_kpt: 0.000699 acc_pose: 0.738485 loss: 0.000699 2022/10/27 13:24:31 - mmengine - INFO - Epoch(train) [26][500/586] lr: 5.000000e-04 eta: 8:11:50 time: 0.295521 data_time: 0.030330 memory: 11131 loss_kpt: 0.000686 acc_pose: 0.787905 loss: 0.000686 2022/10/27 13:24:45 - mmengine - INFO - Epoch(train) [26][550/586] lr: 5.000000e-04 eta: 8:11:41 time: 0.286293 data_time: 0.026933 memory: 11131 loss_kpt: 0.000698 acc_pose: 0.846103 loss: 0.000698 2022/10/27 13:24:55 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:25:10 - mmengine - INFO - Epoch(train) [27][50/586] lr: 5.000000e-04 eta: 8:10:17 time: 0.299203 data_time: 0.035483 memory: 11131 loss_kpt: 0.000697 acc_pose: 0.808805 loss: 0.000697 2022/10/27 13:25:25 - mmengine - INFO - Epoch(train) [27][100/586] lr: 5.000000e-04 eta: 8:10:09 time: 0.289328 data_time: 0.033225 memory: 11131 loss_kpt: 0.000694 acc_pose: 0.804589 loss: 0.000694 2022/10/27 13:25:39 - mmengine - INFO - Epoch(train) [27][150/586] lr: 5.000000e-04 eta: 8:10:02 time: 0.291572 data_time: 0.029984 memory: 11131 loss_kpt: 0.000703 acc_pose: 0.829882 loss: 0.000703 2022/10/27 13:25:54 - mmengine - INFO - Epoch(train) [27][200/586] lr: 5.000000e-04 eta: 8:09:54 time: 0.288599 data_time: 0.029651 memory: 11131 loss_kpt: 0.000705 acc_pose: 0.750725 loss: 0.000705 2022/10/27 13:26:08 - mmengine - INFO - Epoch(train) [27][250/586] lr: 5.000000e-04 eta: 8:09:44 time: 0.285141 data_time: 0.031363 memory: 11131 loss_kpt: 0.000695 acc_pose: 0.771875 loss: 0.000695 2022/10/27 13:26:23 - mmengine - INFO - Epoch(train) [27][300/586] lr: 5.000000e-04 eta: 8:09:36 time: 0.288601 data_time: 0.030862 memory: 11131 loss_kpt: 0.000698 acc_pose: 0.798020 loss: 0.000698 2022/10/27 13:26:37 - mmengine - INFO - Epoch(train) [27][350/586] lr: 5.000000e-04 eta: 8:09:28 time: 0.290333 data_time: 0.028621 memory: 11131 loss_kpt: 0.000705 acc_pose: 0.768504 loss: 0.000705 2022/10/27 13:26:51 - mmengine - INFO - Epoch(train) [27][400/586] lr: 5.000000e-04 eta: 8:09:19 time: 0.285602 data_time: 0.029868 memory: 11131 loss_kpt: 0.000696 acc_pose: 0.767521 loss: 0.000696 2022/10/27 13:27:06 - mmengine - INFO - Epoch(train) [27][450/586] lr: 5.000000e-04 eta: 8:09:10 time: 0.287157 data_time: 0.028259 memory: 11131 loss_kpt: 0.000709 acc_pose: 0.834072 loss: 0.000709 2022/10/27 13:27:20 - mmengine - INFO - Epoch(train) [27][500/586] lr: 5.000000e-04 eta: 8:09:02 time: 0.289562 data_time: 0.031006 memory: 11131 loss_kpt: 0.000712 acc_pose: 0.757670 loss: 0.000712 2022/10/27 13:27:34 - mmengine - INFO - Epoch(train) [27][550/586] lr: 5.000000e-04 eta: 8:08:52 time: 0.284487 data_time: 0.027768 memory: 11131 loss_kpt: 0.000690 acc_pose: 0.822244 loss: 0.000690 2022/10/27 13:27:45 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:28:00 - mmengine - INFO - Epoch(train) [28][50/586] lr: 5.000000e-04 eta: 8:07:29 time: 0.293608 data_time: 0.038123 memory: 11131 loss_kpt: 0.000692 acc_pose: 0.794671 loss: 0.000692 2022/10/27 13:28:14 - mmengine - INFO - Epoch(train) [28][100/586] lr: 5.000000e-04 eta: 8:07:19 time: 0.286496 data_time: 0.035214 memory: 11131 loss_kpt: 0.000688 acc_pose: 0.902626 loss: 0.000688 2022/10/27 13:28:28 - mmengine - INFO - Epoch(train) [28][150/586] lr: 5.000000e-04 eta: 8:07:10 time: 0.286781 data_time: 0.028118 memory: 11131 loss_kpt: 0.000688 acc_pose: 0.810579 loss: 0.000688 2022/10/27 13:28:36 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:28:43 - mmengine - INFO - Epoch(train) [28][200/586] lr: 5.000000e-04 eta: 8:07:01 time: 0.285378 data_time: 0.028643 memory: 11131 loss_kpt: 0.000716 acc_pose: 0.787672 loss: 0.000716 2022/10/27 13:28:57 - mmengine - INFO - Epoch(train) [28][250/586] lr: 5.000000e-04 eta: 8:06:54 time: 0.293184 data_time: 0.028069 memory: 11131 loss_kpt: 0.000686 acc_pose: 0.818585 loss: 0.000686 2022/10/27 13:29:12 - mmengine - INFO - Epoch(train) [28][300/586] lr: 5.000000e-04 eta: 8:06:46 time: 0.289863 data_time: 0.029645 memory: 11131 loss_kpt: 0.000700 acc_pose: 0.757278 loss: 0.000700 2022/10/27 13:29:26 - mmengine - INFO - Epoch(train) [28][350/586] lr: 5.000000e-04 eta: 8:06:37 time: 0.286630 data_time: 0.028152 memory: 11131 loss_kpt: 0.000690 acc_pose: 0.725187 loss: 0.000690 2022/10/27 13:29:40 - mmengine - INFO - Epoch(train) [28][400/586] lr: 5.000000e-04 eta: 8:06:27 time: 0.283535 data_time: 0.027792 memory: 11131 loss_kpt: 0.000677 acc_pose: 0.856220 loss: 0.000677 2022/10/27 13:29:55 - mmengine - INFO - Epoch(train) [28][450/586] lr: 5.000000e-04 eta: 8:06:17 time: 0.287037 data_time: 0.027660 memory: 11131 loss_kpt: 0.000703 acc_pose: 0.817965 loss: 0.000703 2022/10/27 13:30:09 - mmengine - INFO - Epoch(train) [28][500/586] lr: 5.000000e-04 eta: 8:06:08 time: 0.287301 data_time: 0.028283 memory: 11131 loss_kpt: 0.000697 acc_pose: 0.793030 loss: 0.000697 2022/10/27 13:30:23 - mmengine - INFO - Epoch(train) [28][550/586] lr: 5.000000e-04 eta: 8:05:59 time: 0.287282 data_time: 0.033598 memory: 11131 loss_kpt: 0.000692 acc_pose: 0.829489 loss: 0.000692 2022/10/27 13:30:34 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:30:48 - mmengine - INFO - Epoch(train) [29][50/586] lr: 5.000000e-04 eta: 8:04:39 time: 0.294802 data_time: 0.038485 memory: 11131 loss_kpt: 0.000699 acc_pose: 0.840097 loss: 0.000699 2022/10/27 13:31:03 - mmengine - INFO - Epoch(train) [29][100/586] lr: 5.000000e-04 eta: 8:04:31 time: 0.289819 data_time: 0.031439 memory: 11131 loss_kpt: 0.000688 acc_pose: 0.786056 loss: 0.000688 2022/10/27 13:31:17 - mmengine - INFO - Epoch(train) [29][150/586] lr: 5.000000e-04 eta: 8:04:22 time: 0.288917 data_time: 0.031486 memory: 11131 loss_kpt: 0.000700 acc_pose: 0.796118 loss: 0.000700 2022/10/27 13:31:32 - mmengine - INFO - Epoch(train) [29][200/586] lr: 5.000000e-04 eta: 8:04:14 time: 0.288400 data_time: 0.030645 memory: 11131 loss_kpt: 0.000693 acc_pose: 0.844372 loss: 0.000693 2022/10/27 13:31:46 - mmengine - INFO - Epoch(train) [29][250/586] lr: 5.000000e-04 eta: 8:04:04 time: 0.284878 data_time: 0.028950 memory: 11131 loss_kpt: 0.000679 acc_pose: 0.836127 loss: 0.000679 2022/10/27 13:32:00 - mmengine - INFO - Epoch(train) [29][300/586] lr: 5.000000e-04 eta: 8:03:54 time: 0.285918 data_time: 0.029559 memory: 11131 loss_kpt: 0.000687 acc_pose: 0.799635 loss: 0.000687 2022/10/27 13:32:15 - mmengine - INFO - Epoch(train) [29][350/586] lr: 5.000000e-04 eta: 8:03:47 time: 0.293647 data_time: 0.027701 memory: 11131 loss_kpt: 0.000692 acc_pose: 0.847602 loss: 0.000692 2022/10/27 13:32:29 - mmengine - INFO - Epoch(train) [29][400/586] lr: 5.000000e-04 eta: 8:03:37 time: 0.284423 data_time: 0.028929 memory: 11131 loss_kpt: 0.000686 acc_pose: 0.821157 loss: 0.000686 2022/10/27 13:32:44 - mmengine - INFO - Epoch(train) [29][450/586] lr: 5.000000e-04 eta: 8:03:27 time: 0.285329 data_time: 0.034416 memory: 11131 loss_kpt: 0.000677 acc_pose: 0.849742 loss: 0.000677 2022/10/27 13:32:58 - mmengine - INFO - Epoch(train) [29][500/586] lr: 5.000000e-04 eta: 8:03:19 time: 0.288933 data_time: 0.027035 memory: 11131 loss_kpt: 0.000671 acc_pose: 0.804455 loss: 0.000671 2022/10/27 13:33:12 - mmengine - INFO - Epoch(train) [29][550/586] lr: 5.000000e-04 eta: 8:03:09 time: 0.284438 data_time: 0.032819 memory: 11131 loss_kpt: 0.000702 acc_pose: 0.752301 loss: 0.000702 2022/10/27 13:33:23 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:33:25 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:33:38 - mmengine - INFO - Epoch(train) [30][50/586] lr: 5.000000e-04 eta: 8:01:53 time: 0.301981 data_time: 0.039400 memory: 11131 loss_kpt: 0.000674 acc_pose: 0.860762 loss: 0.000674 2022/10/27 13:33:52 - mmengine - INFO - Epoch(train) [30][100/586] lr: 5.000000e-04 eta: 8:01:43 time: 0.284117 data_time: 0.027219 memory: 11131 loss_kpt: 0.000695 acc_pose: 0.870448 loss: 0.000695 2022/10/27 13:34:07 - mmengine - INFO - Epoch(train) [30][150/586] lr: 5.000000e-04 eta: 8:01:35 time: 0.292495 data_time: 0.033438 memory: 11131 loss_kpt: 0.000676 acc_pose: 0.880180 loss: 0.000676 2022/10/27 13:34:21 - mmengine - INFO - Epoch(train) [30][200/586] lr: 5.000000e-04 eta: 8:01:25 time: 0.285294 data_time: 0.029389 memory: 11131 loss_kpt: 0.000694 acc_pose: 0.806121 loss: 0.000694 2022/10/27 13:34:36 - mmengine - INFO - Epoch(train) [30][250/586] lr: 5.000000e-04 eta: 8:01:18 time: 0.293441 data_time: 0.028445 memory: 11131 loss_kpt: 0.000704 acc_pose: 0.746613 loss: 0.000704 2022/10/27 13:34:50 - mmengine - INFO - Epoch(train) [30][300/586] lr: 5.000000e-04 eta: 8:01:09 time: 0.288907 data_time: 0.027275 memory: 11131 loss_kpt: 0.000695 acc_pose: 0.840464 loss: 0.000695 2022/10/27 13:35:04 - mmengine - INFO - Epoch(train) [30][350/586] lr: 5.000000e-04 eta: 8:00:59 time: 0.284911 data_time: 0.029483 memory: 11131 loss_kpt: 0.000679 acc_pose: 0.797577 loss: 0.000679 2022/10/27 13:35:19 - mmengine - INFO - Epoch(train) [30][400/586] lr: 5.000000e-04 eta: 8:00:50 time: 0.287049 data_time: 0.029666 memory: 11131 loss_kpt: 0.000691 acc_pose: 0.797537 loss: 0.000691 2022/10/27 13:35:33 - mmengine - INFO - Epoch(train) [30][450/586] lr: 5.000000e-04 eta: 8:00:41 time: 0.289648 data_time: 0.027203 memory: 11131 loss_kpt: 0.000671 acc_pose: 0.763434 loss: 0.000671 2022/10/27 13:35:48 - mmengine - INFO - Epoch(train) [30][500/586] lr: 5.000000e-04 eta: 8:00:32 time: 0.288966 data_time: 0.028545 memory: 11131 loss_kpt: 0.000682 acc_pose: 0.810486 loss: 0.000682 2022/10/27 13:36:02 - mmengine - INFO - Epoch(train) [30][550/586] lr: 5.000000e-04 eta: 8:00:23 time: 0.287189 data_time: 0.029411 memory: 11131 loss_kpt: 0.000707 acc_pose: 0.761844 loss: 0.000707 2022/10/27 13:36:12 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:36:12 - mmengine - INFO - Saving checkpoint at 30 epochs 2022/10/27 13:36:23 - mmengine - INFO - Epoch(val) [30][50/407] eta: 0:00:54 time: 0.153209 data_time: 0.029551 memory: 11131 2022/10/27 13:36:30 - mmengine - INFO - Epoch(val) [30][100/407] eta: 0:00:41 time: 0.133834 data_time: 0.013198 memory: 1836 2022/10/27 13:36:37 - mmengine - INFO - Epoch(val) [30][150/407] eta: 0:00:35 time: 0.139911 data_time: 0.021703 memory: 1836 2022/10/27 13:36:44 - mmengine - INFO - Epoch(val) [30][200/407] eta: 0:00:29 time: 0.140582 data_time: 0.019428 memory: 1836 2022/10/27 13:36:51 - mmengine - INFO - Epoch(val) [30][250/407] eta: 0:00:21 time: 0.135657 data_time: 0.016072 memory: 1836 2022/10/27 13:36:58 - mmengine - INFO - Epoch(val) [30][300/407] eta: 0:00:15 time: 0.142533 data_time: 0.022767 memory: 1836 2022/10/27 13:37:05 - mmengine - INFO - Epoch(val) [30][350/407] eta: 0:00:08 time: 0.144479 data_time: 0.024380 memory: 1836 2022/10/27 13:37:12 - mmengine - INFO - Epoch(val) [30][400/407] eta: 0:00:00 time: 0.126199 data_time: 0.011076 memory: 1836 2022/10/27 13:37:58 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 13:38:15 - mmengine - INFO - Epoch(val) [30][407/407] coco/AP: 0.707020 coco/AP .5: 0.885495 coco/AP .75: 0.776292 coco/AP (M): 0.664782 coco/AP (L): 0.779383 coco/AR: 0.761004 coco/AR .5: 0.922544 coco/AR .75: 0.823992 coco/AR (M): 0.713193 coco/AR (L): 0.829915 2022/10/27 13:38:15 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_20.pth is removed 2022/10/27 13:38:17 - mmengine - INFO - The best checkpoint with 0.7070 coco/AP at 30 epoch is saved to best_coco/AP_epoch_30.pth. 2022/10/27 13:38:32 - mmengine - INFO - Epoch(train) [31][50/586] lr: 5.000000e-04 eta: 7:59:08 time: 0.296884 data_time: 0.039625 memory: 11131 loss_kpt: 0.000666 acc_pose: 0.765022 loss: 0.000666 2022/10/27 13:38:47 - mmengine - INFO - Epoch(train) [31][100/586] lr: 5.000000e-04 eta: 7:59:02 time: 0.298067 data_time: 0.033649 memory: 11131 loss_kpt: 0.000687 acc_pose: 0.813964 loss: 0.000687 2022/10/27 13:39:01 - mmengine - INFO - Epoch(train) [31][150/586] lr: 5.000000e-04 eta: 7:58:52 time: 0.285218 data_time: 0.030199 memory: 11131 loss_kpt: 0.000665 acc_pose: 0.889709 loss: 0.000665 2022/10/27 13:39:16 - mmengine - INFO - Epoch(train) [31][200/586] lr: 5.000000e-04 eta: 7:58:43 time: 0.288137 data_time: 0.031175 memory: 11131 loss_kpt: 0.000666 acc_pose: 0.832882 loss: 0.000666 2022/10/27 13:39:30 - mmengine - INFO - Epoch(train) [31][250/586] lr: 5.000000e-04 eta: 7:58:33 time: 0.286739 data_time: 0.029222 memory: 11131 loss_kpt: 0.000690 acc_pose: 0.843461 loss: 0.000690 2022/10/27 13:39:45 - mmengine - INFO - Epoch(train) [31][300/586] lr: 5.000000e-04 eta: 7:58:24 time: 0.288343 data_time: 0.028651 memory: 11131 loss_kpt: 0.000672 acc_pose: 0.795695 loss: 0.000672 2022/10/27 13:39:59 - mmengine - INFO - Epoch(train) [31][350/586] lr: 5.000000e-04 eta: 7:58:16 time: 0.292884 data_time: 0.031773 memory: 11131 loss_kpt: 0.000690 acc_pose: 0.771707 loss: 0.000690 2022/10/27 13:40:13 - mmengine - INFO - Epoch(train) [31][400/586] lr: 5.000000e-04 eta: 7:58:06 time: 0.286226 data_time: 0.027310 memory: 11131 loss_kpt: 0.000695 acc_pose: 0.810857 loss: 0.000695 2022/10/27 13:40:19 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:40:28 - mmengine - INFO - Epoch(train) [31][450/586] lr: 5.000000e-04 eta: 7:57:57 time: 0.286062 data_time: 0.029037 memory: 11131 loss_kpt: 0.000693 acc_pose: 0.769034 loss: 0.000693 2022/10/27 13:40:42 - mmengine - INFO - Epoch(train) [31][500/586] lr: 5.000000e-04 eta: 7:57:47 time: 0.285675 data_time: 0.030742 memory: 11131 loss_kpt: 0.000667 acc_pose: 0.762707 loss: 0.000667 2022/10/27 13:40:56 - mmengine - INFO - Epoch(train) [31][550/586] lr: 5.000000e-04 eta: 7:57:36 time: 0.281769 data_time: 0.026897 memory: 11131 loss_kpt: 0.000680 acc_pose: 0.777967 loss: 0.000680 2022/10/27 13:41:07 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:41:22 - mmengine - INFO - Epoch(train) [32][50/586] lr: 5.000000e-04 eta: 7:56:22 time: 0.297573 data_time: 0.041801 memory: 11131 loss_kpt: 0.000670 acc_pose: 0.811080 loss: 0.000670 2022/10/27 13:41:36 - mmengine - INFO - Epoch(train) [32][100/586] lr: 5.000000e-04 eta: 7:56:12 time: 0.283142 data_time: 0.028170 memory: 11131 loss_kpt: 0.000652 acc_pose: 0.746294 loss: 0.000652 2022/10/27 13:41:50 - mmengine - INFO - Epoch(train) [32][150/586] lr: 5.000000e-04 eta: 7:56:01 time: 0.281369 data_time: 0.030049 memory: 11131 loss_kpt: 0.000660 acc_pose: 0.869780 loss: 0.000660 2022/10/27 13:42:05 - mmengine - INFO - Epoch(train) [32][200/586] lr: 5.000000e-04 eta: 7:55:53 time: 0.294748 data_time: 0.034101 memory: 11131 loss_kpt: 0.000664 acc_pose: 0.792823 loss: 0.000664 2022/10/27 13:42:19 - mmengine - INFO - Epoch(train) [32][250/586] lr: 5.000000e-04 eta: 7:55:44 time: 0.287371 data_time: 0.029689 memory: 11131 loss_kpt: 0.000693 acc_pose: 0.837456 loss: 0.000693 2022/10/27 13:42:33 - mmengine - INFO - Epoch(train) [32][300/586] lr: 5.000000e-04 eta: 7:55:34 time: 0.285451 data_time: 0.029236 memory: 11131 loss_kpt: 0.000700 acc_pose: 0.840079 loss: 0.000700 2022/10/27 13:42:47 - mmengine - INFO - Epoch(train) [32][350/586] lr: 5.000000e-04 eta: 7:55:24 time: 0.285998 data_time: 0.030257 memory: 11131 loss_kpt: 0.000675 acc_pose: 0.829000 loss: 0.000675 2022/10/27 13:43:02 - mmengine - INFO - Epoch(train) [32][400/586] lr: 5.000000e-04 eta: 7:55:15 time: 0.289491 data_time: 0.030613 memory: 11131 loss_kpt: 0.000675 acc_pose: 0.737589 loss: 0.000675 2022/10/27 13:43:17 - mmengine - INFO - Epoch(train) [32][450/586] lr: 5.000000e-04 eta: 7:55:07 time: 0.291414 data_time: 0.027879 memory: 11131 loss_kpt: 0.000681 acc_pose: 0.805477 loss: 0.000681 2022/10/27 13:43:31 - mmengine - INFO - Epoch(train) [32][500/586] lr: 5.000000e-04 eta: 7:54:57 time: 0.286768 data_time: 0.033566 memory: 11131 loss_kpt: 0.000676 acc_pose: 0.783663 loss: 0.000676 2022/10/27 13:43:45 - mmengine - INFO - Epoch(train) [32][550/586] lr: 5.000000e-04 eta: 7:54:47 time: 0.287831 data_time: 0.028664 memory: 11131 loss_kpt: 0.000682 acc_pose: 0.794015 loss: 0.000682 2022/10/27 13:43:56 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:44:10 - mmengine - INFO - Epoch(train) [33][50/586] lr: 5.000000e-04 eta: 7:53:35 time: 0.292859 data_time: 0.038869 memory: 11131 loss_kpt: 0.000689 acc_pose: 0.777811 loss: 0.000689 2022/10/27 13:44:25 - mmengine - INFO - Epoch(train) [33][100/586] lr: 5.000000e-04 eta: 7:53:27 time: 0.293720 data_time: 0.029854 memory: 11131 loss_kpt: 0.000671 acc_pose: 0.853951 loss: 0.000671 2022/10/27 13:44:39 - mmengine - INFO - Epoch(train) [33][150/586] lr: 5.000000e-04 eta: 7:53:18 time: 0.288196 data_time: 0.029683 memory: 11131 loss_kpt: 0.000653 acc_pose: 0.810262 loss: 0.000653 2022/10/27 13:44:54 - mmengine - INFO - Epoch(train) [33][200/586] lr: 5.000000e-04 eta: 7:53:08 time: 0.288413 data_time: 0.027226 memory: 11131 loss_kpt: 0.000676 acc_pose: 0.826915 loss: 0.000676 2022/10/27 13:45:07 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:45:08 - mmengine - INFO - Epoch(train) [33][250/586] lr: 5.000000e-04 eta: 7:52:58 time: 0.283936 data_time: 0.028392 memory: 11131 loss_kpt: 0.000680 acc_pose: 0.808191 loss: 0.000680 2022/10/27 13:45:22 - mmengine - INFO - Epoch(train) [33][300/586] lr: 5.000000e-04 eta: 7:52:47 time: 0.284103 data_time: 0.028774 memory: 11131 loss_kpt: 0.000673 acc_pose: 0.800355 loss: 0.000673 2022/10/27 13:45:37 - mmengine - INFO - Epoch(train) [33][350/586] lr: 5.000000e-04 eta: 7:52:40 time: 0.294832 data_time: 0.032337 memory: 11131 loss_kpt: 0.000678 acc_pose: 0.766861 loss: 0.000678 2022/10/27 13:45:51 - mmengine - INFO - Epoch(train) [33][400/586] lr: 5.000000e-04 eta: 7:52:30 time: 0.287281 data_time: 0.028233 memory: 11131 loss_kpt: 0.000666 acc_pose: 0.811247 loss: 0.000666 2022/10/27 13:46:06 - mmengine - INFO - Epoch(train) [33][450/586] lr: 5.000000e-04 eta: 7:52:21 time: 0.290123 data_time: 0.029018 memory: 11131 loss_kpt: 0.000697 acc_pose: 0.779896 loss: 0.000697 2022/10/27 13:46:20 - mmengine - INFO - Epoch(train) [33][500/586] lr: 5.000000e-04 eta: 7:52:11 time: 0.285445 data_time: 0.027852 memory: 11131 loss_kpt: 0.000679 acc_pose: 0.735637 loss: 0.000679 2022/10/27 13:46:34 - mmengine - INFO - Epoch(train) [33][550/586] lr: 5.000000e-04 eta: 7:52:00 time: 0.284796 data_time: 0.028147 memory: 11131 loss_kpt: 0.000659 acc_pose: 0.780045 loss: 0.000659 2022/10/27 13:46:45 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:47:00 - mmengine - INFO - Epoch(train) [34][50/586] lr: 5.000000e-04 eta: 7:50:51 time: 0.297410 data_time: 0.040096 memory: 11131 loss_kpt: 0.000679 acc_pose: 0.834325 loss: 0.000679 2022/10/27 13:47:14 - mmengine - INFO - Epoch(train) [34][100/586] lr: 5.000000e-04 eta: 7:50:41 time: 0.286969 data_time: 0.032765 memory: 11131 loss_kpt: 0.000655 acc_pose: 0.774705 loss: 0.000655 2022/10/27 13:47:28 - mmengine - INFO - Epoch(train) [34][150/586] lr: 5.000000e-04 eta: 7:50:30 time: 0.281580 data_time: 0.029342 memory: 11131 loss_kpt: 0.000656 acc_pose: 0.863249 loss: 0.000656 2022/10/27 13:47:43 - mmengine - INFO - Epoch(train) [34][200/586] lr: 5.000000e-04 eta: 7:50:20 time: 0.288929 data_time: 0.030319 memory: 11131 loss_kpt: 0.000689 acc_pose: 0.714863 loss: 0.000689 2022/10/27 13:47:57 - mmengine - INFO - Epoch(train) [34][250/586] lr: 5.000000e-04 eta: 7:50:12 time: 0.290628 data_time: 0.033325 memory: 11131 loss_kpt: 0.000644 acc_pose: 0.811721 loss: 0.000644 2022/10/27 13:48:11 - mmengine - INFO - Epoch(train) [34][300/586] lr: 5.000000e-04 eta: 7:50:02 time: 0.286746 data_time: 0.028203 memory: 11131 loss_kpt: 0.000684 acc_pose: 0.858307 loss: 0.000684 2022/10/27 13:48:26 - mmengine - INFO - Epoch(train) [34][350/586] lr: 5.000000e-04 eta: 7:49:52 time: 0.289368 data_time: 0.029914 memory: 11131 loss_kpt: 0.000680 acc_pose: 0.760588 loss: 0.000680 2022/10/27 13:48:40 - mmengine - INFO - Epoch(train) [34][400/586] lr: 5.000000e-04 eta: 7:49:43 time: 0.287637 data_time: 0.026743 memory: 11131 loss_kpt: 0.000668 acc_pose: 0.831624 loss: 0.000668 2022/10/27 13:48:55 - mmengine - INFO - Epoch(train) [34][450/586] lr: 5.000000e-04 eta: 7:49:34 time: 0.290670 data_time: 0.031681 memory: 11131 loss_kpt: 0.000670 acc_pose: 0.765246 loss: 0.000670 2022/10/27 13:49:09 - mmengine - INFO - Epoch(train) [34][500/586] lr: 5.000000e-04 eta: 7:49:24 time: 0.287735 data_time: 0.029109 memory: 11131 loss_kpt: 0.000648 acc_pose: 0.822097 loss: 0.000648 2022/10/27 13:49:24 - mmengine - INFO - Epoch(train) [34][550/586] lr: 5.000000e-04 eta: 7:49:14 time: 0.285316 data_time: 0.027783 memory: 11131 loss_kpt: 0.000677 acc_pose: 0.779278 loss: 0.000677 2022/10/27 13:49:34 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:49:49 - mmengine - INFO - Epoch(train) [35][50/586] lr: 5.000000e-04 eta: 7:48:06 time: 0.299000 data_time: 0.039890 memory: 11131 loss_kpt: 0.000693 acc_pose: 0.829467 loss: 0.000693 2022/10/27 13:49:56 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:50:03 - mmengine - INFO - Epoch(train) [35][100/586] lr: 5.000000e-04 eta: 7:47:59 time: 0.296150 data_time: 0.029364 memory: 11131 loss_kpt: 0.000664 acc_pose: 0.823960 loss: 0.000664 2022/10/27 13:50:18 - mmengine - INFO - Epoch(train) [35][150/586] lr: 5.000000e-04 eta: 7:47:49 time: 0.288096 data_time: 0.029993 memory: 11131 loss_kpt: 0.000690 acc_pose: 0.811387 loss: 0.000690 2022/10/27 13:50:32 - mmengine - INFO - Epoch(train) [35][200/586] lr: 5.000000e-04 eta: 7:47:38 time: 0.284535 data_time: 0.027122 memory: 11131 loss_kpt: 0.000676 acc_pose: 0.880050 loss: 0.000676 2022/10/27 13:50:46 - mmengine - INFO - Epoch(train) [35][250/586] lr: 5.000000e-04 eta: 7:47:28 time: 0.285625 data_time: 0.030156 memory: 11131 loss_kpt: 0.000662 acc_pose: 0.866159 loss: 0.000662 2022/10/27 13:51:01 - mmengine - INFO - Epoch(train) [35][300/586] lr: 5.000000e-04 eta: 7:47:19 time: 0.290986 data_time: 0.027930 memory: 11131 loss_kpt: 0.000681 acc_pose: 0.773186 loss: 0.000681 2022/10/27 13:51:15 - mmengine - INFO - Epoch(train) [35][350/586] lr: 5.000000e-04 eta: 7:47:11 time: 0.292843 data_time: 0.033647 memory: 11131 loss_kpt: 0.000670 acc_pose: 0.781111 loss: 0.000670 2022/10/27 13:51:30 - mmengine - INFO - Epoch(train) [35][400/586] lr: 5.000000e-04 eta: 7:47:00 time: 0.286157 data_time: 0.029278 memory: 11131 loss_kpt: 0.000661 acc_pose: 0.784500 loss: 0.000661 2022/10/27 13:51:44 - mmengine - INFO - Epoch(train) [35][450/586] lr: 5.000000e-04 eta: 7:46:51 time: 0.288431 data_time: 0.029751 memory: 11131 loss_kpt: 0.000672 acc_pose: 0.780134 loss: 0.000672 2022/10/27 13:51:59 - mmengine - INFO - Epoch(train) [35][500/586] lr: 5.000000e-04 eta: 7:46:41 time: 0.287901 data_time: 0.029203 memory: 11131 loss_kpt: 0.000667 acc_pose: 0.846870 loss: 0.000667 2022/10/27 13:52:13 - mmengine - INFO - Epoch(train) [35][550/586] lr: 5.000000e-04 eta: 7:46:33 time: 0.294590 data_time: 0.034581 memory: 11131 loss_kpt: 0.000669 acc_pose: 0.850164 loss: 0.000669 2022/10/27 13:52:23 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:52:38 - mmengine - INFO - Epoch(train) [36][50/586] lr: 5.000000e-04 eta: 7:45:27 time: 0.298709 data_time: 0.037683 memory: 11131 loss_kpt: 0.000667 acc_pose: 0.858812 loss: 0.000667 2022/10/27 13:52:53 - mmengine - INFO - Epoch(train) [36][100/586] lr: 5.000000e-04 eta: 7:45:17 time: 0.290126 data_time: 0.031387 memory: 11131 loss_kpt: 0.000644 acc_pose: 0.786663 loss: 0.000644 2022/10/27 13:53:07 - mmengine - INFO - Epoch(train) [36][150/586] lr: 5.000000e-04 eta: 7:45:06 time: 0.283185 data_time: 0.031258 memory: 11131 loss_kpt: 0.000666 acc_pose: 0.872215 loss: 0.000666 2022/10/27 13:53:22 - mmengine - INFO - Epoch(train) [36][200/586] lr: 5.000000e-04 eta: 7:44:59 time: 0.298557 data_time: 0.029679 memory: 11131 loss_kpt: 0.000664 acc_pose: 0.887296 loss: 0.000664 2022/10/27 13:53:37 - mmengine - INFO - Epoch(train) [36][250/586] lr: 5.000000e-04 eta: 7:44:50 time: 0.289451 data_time: 0.027786 memory: 11131 loss_kpt: 0.000673 acc_pose: 0.808162 loss: 0.000673 2022/10/27 13:53:51 - mmengine - INFO - Epoch(train) [36][300/586] lr: 5.000000e-04 eta: 7:44:39 time: 0.285811 data_time: 0.030191 memory: 11131 loss_kpt: 0.000671 acc_pose: 0.760345 loss: 0.000671 2022/10/27 13:54:05 - mmengine - INFO - Epoch(train) [36][350/586] lr: 5.000000e-04 eta: 7:44:29 time: 0.286268 data_time: 0.028594 memory: 11131 loss_kpt: 0.000677 acc_pose: 0.857253 loss: 0.000677 2022/10/27 13:54:19 - mmengine - INFO - Epoch(train) [36][400/586] lr: 5.000000e-04 eta: 7:44:19 time: 0.286916 data_time: 0.027324 memory: 11131 loss_kpt: 0.000675 acc_pose: 0.756559 loss: 0.000675 2022/10/27 13:54:34 - mmengine - INFO - Epoch(train) [36][450/586] lr: 5.000000e-04 eta: 7:44:10 time: 0.292659 data_time: 0.029358 memory: 11131 loss_kpt: 0.000691 acc_pose: 0.866956 loss: 0.000691 2022/10/27 13:54:46 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:54:48 - mmengine - INFO - Epoch(train) [36][500/586] lr: 5.000000e-04 eta: 7:44:00 time: 0.285270 data_time: 0.027559 memory: 11131 loss_kpt: 0.000675 acc_pose: 0.847393 loss: 0.000675 2022/10/27 13:55:03 - mmengine - INFO - Epoch(train) [36][550/586] lr: 5.000000e-04 eta: 7:43:50 time: 0.288182 data_time: 0.030478 memory: 11131 loss_kpt: 0.000669 acc_pose: 0.877402 loss: 0.000669 2022/10/27 13:55:13 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:55:28 - mmengine - INFO - Epoch(train) [37][50/586] lr: 5.000000e-04 eta: 7:42:44 time: 0.294593 data_time: 0.037718 memory: 11131 loss_kpt: 0.000655 acc_pose: 0.723008 loss: 0.000655 2022/10/27 13:55:43 - mmengine - INFO - Epoch(train) [37][100/586] lr: 5.000000e-04 eta: 7:42:37 time: 0.299991 data_time: 0.036379 memory: 11131 loss_kpt: 0.000671 acc_pose: 0.727615 loss: 0.000671 2022/10/27 13:55:57 - mmengine - INFO - Epoch(train) [37][150/586] lr: 5.000000e-04 eta: 7:42:28 time: 0.289517 data_time: 0.031197 memory: 11131 loss_kpt: 0.000667 acc_pose: 0.811498 loss: 0.000667 2022/10/27 13:56:12 - mmengine - INFO - Epoch(train) [37][200/586] lr: 5.000000e-04 eta: 7:42:17 time: 0.286840 data_time: 0.033355 memory: 11131 loss_kpt: 0.000663 acc_pose: 0.822570 loss: 0.000663 2022/10/27 13:56:26 - mmengine - INFO - Epoch(train) [37][250/586] lr: 5.000000e-04 eta: 7:42:06 time: 0.282006 data_time: 0.029923 memory: 11131 loss_kpt: 0.000655 acc_pose: 0.818282 loss: 0.000655 2022/10/27 13:56:40 - mmengine - INFO - Epoch(train) [37][300/586] lr: 5.000000e-04 eta: 7:41:56 time: 0.287563 data_time: 0.028096 memory: 11131 loss_kpt: 0.000667 acc_pose: 0.864282 loss: 0.000667 2022/10/27 13:56:55 - mmengine - INFO - Epoch(train) [37][350/586] lr: 5.000000e-04 eta: 7:41:48 time: 0.295771 data_time: 0.032446 memory: 11131 loss_kpt: 0.000668 acc_pose: 0.817226 loss: 0.000668 2022/10/27 13:57:09 - mmengine - INFO - Epoch(train) [37][400/586] lr: 5.000000e-04 eta: 7:41:37 time: 0.286764 data_time: 0.030410 memory: 11131 loss_kpt: 0.000694 acc_pose: 0.768971 loss: 0.000694 2022/10/27 13:57:23 - mmengine - INFO - Epoch(train) [37][450/586] lr: 5.000000e-04 eta: 7:41:27 time: 0.284530 data_time: 0.032406 memory: 11131 loss_kpt: 0.000668 acc_pose: 0.705781 loss: 0.000668 2022/10/27 13:57:38 - mmengine - INFO - Epoch(train) [37][500/586] lr: 5.000000e-04 eta: 7:41:17 time: 0.290823 data_time: 0.028680 memory: 11131 loss_kpt: 0.000687 acc_pose: 0.785700 loss: 0.000687 2022/10/27 13:57:52 - mmengine - INFO - Epoch(train) [37][550/586] lr: 5.000000e-04 eta: 7:41:07 time: 0.288139 data_time: 0.033641 memory: 11131 loss_kpt: 0.000679 acc_pose: 0.784529 loss: 0.000679 2022/10/27 13:58:03 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:58:18 - mmengine - INFO - Epoch(train) [38][50/586] lr: 5.000000e-04 eta: 7:40:05 time: 0.302540 data_time: 0.044771 memory: 11131 loss_kpt: 0.000652 acc_pose: 0.809891 loss: 0.000652 2022/10/27 13:58:32 - mmengine - INFO - Epoch(train) [38][100/586] lr: 5.000000e-04 eta: 7:39:55 time: 0.288794 data_time: 0.029191 memory: 11131 loss_kpt: 0.000659 acc_pose: 0.797091 loss: 0.000659 2022/10/27 13:58:47 - mmengine - INFO - Epoch(train) [38][150/586] lr: 5.000000e-04 eta: 7:39:44 time: 0.283283 data_time: 0.030595 memory: 11131 loss_kpt: 0.000672 acc_pose: 0.865488 loss: 0.000672 2022/10/27 13:59:01 - mmengine - INFO - Epoch(train) [38][200/586] lr: 5.000000e-04 eta: 7:39:34 time: 0.287996 data_time: 0.031895 memory: 11131 loss_kpt: 0.000647 acc_pose: 0.801879 loss: 0.000647 2022/10/27 13:59:16 - mmengine - INFO - Epoch(train) [38][250/586] lr: 5.000000e-04 eta: 7:39:26 time: 0.299084 data_time: 0.030587 memory: 11131 loss_kpt: 0.000661 acc_pose: 0.859420 loss: 0.000661 2022/10/27 13:59:30 - mmengine - INFO - Epoch(train) [38][300/586] lr: 5.000000e-04 eta: 7:39:15 time: 0.283946 data_time: 0.027699 memory: 11131 loss_kpt: 0.000664 acc_pose: 0.825026 loss: 0.000664 2022/10/27 13:59:35 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 13:59:44 - mmengine - INFO - Epoch(train) [38][350/586] lr: 5.000000e-04 eta: 7:39:04 time: 0.283113 data_time: 0.029703 memory: 11131 loss_kpt: 0.000656 acc_pose: 0.827919 loss: 0.000656 2022/10/27 13:59:58 - mmengine - INFO - Epoch(train) [38][400/586] lr: 5.000000e-04 eta: 7:38:53 time: 0.283812 data_time: 0.029203 memory: 11131 loss_kpt: 0.000670 acc_pose: 0.815045 loss: 0.000670 2022/10/27 14:00:13 - mmengine - INFO - Epoch(train) [38][450/586] lr: 5.000000e-04 eta: 7:38:45 time: 0.295406 data_time: 0.029192 memory: 11131 loss_kpt: 0.000675 acc_pose: 0.844447 loss: 0.000675 2022/10/27 14:00:28 - mmengine - INFO - Epoch(train) [38][500/586] lr: 5.000000e-04 eta: 7:38:35 time: 0.289631 data_time: 0.029774 memory: 11131 loss_kpt: 0.000684 acc_pose: 0.812199 loss: 0.000684 2022/10/27 14:00:42 - mmengine - INFO - Epoch(train) [38][550/586] lr: 5.000000e-04 eta: 7:38:24 time: 0.286178 data_time: 0.030846 memory: 11131 loss_kpt: 0.000660 acc_pose: 0.785266 loss: 0.000660 2022/10/27 14:00:52 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:01:07 - mmengine - INFO - Epoch(train) [39][50/586] lr: 5.000000e-04 eta: 7:37:22 time: 0.296520 data_time: 0.038558 memory: 11131 loss_kpt: 0.000651 acc_pose: 0.831762 loss: 0.000651 2022/10/27 14:01:22 - mmengine - INFO - Epoch(train) [39][100/586] lr: 5.000000e-04 eta: 7:37:13 time: 0.292961 data_time: 0.030187 memory: 11131 loss_kpt: 0.000657 acc_pose: 0.783941 loss: 0.000657 2022/10/27 14:01:36 - mmengine - INFO - Epoch(train) [39][150/586] lr: 5.000000e-04 eta: 7:37:03 time: 0.288010 data_time: 0.030271 memory: 11131 loss_kpt: 0.000686 acc_pose: 0.769901 loss: 0.000686 2022/10/27 14:01:50 - mmengine - INFO - Epoch(train) [39][200/586] lr: 5.000000e-04 eta: 7:36:53 time: 0.288377 data_time: 0.027714 memory: 11131 loss_kpt: 0.000650 acc_pose: 0.821981 loss: 0.000650 2022/10/27 14:02:05 - mmengine - INFO - Epoch(train) [39][250/586] lr: 5.000000e-04 eta: 7:36:42 time: 0.285715 data_time: 0.029152 memory: 11131 loss_kpt: 0.000647 acc_pose: 0.796519 loss: 0.000647 2022/10/27 14:02:19 - mmengine - INFO - Epoch(train) [39][300/586] lr: 5.000000e-04 eta: 7:36:31 time: 0.283825 data_time: 0.030361 memory: 11131 loss_kpt: 0.000647 acc_pose: 0.803441 loss: 0.000647 2022/10/27 14:02:34 - mmengine - INFO - Epoch(train) [39][350/586] lr: 5.000000e-04 eta: 7:36:22 time: 0.295291 data_time: 0.031909 memory: 11131 loss_kpt: 0.000655 acc_pose: 0.810856 loss: 0.000655 2022/10/27 14:02:48 - mmengine - INFO - Epoch(train) [39][400/586] lr: 5.000000e-04 eta: 7:36:12 time: 0.288152 data_time: 0.030193 memory: 11131 loss_kpt: 0.000638 acc_pose: 0.844900 loss: 0.000638 2022/10/27 14:03:02 - mmengine - INFO - Epoch(train) [39][450/586] lr: 5.000000e-04 eta: 7:36:00 time: 0.280843 data_time: 0.029400 memory: 11131 loss_kpt: 0.000658 acc_pose: 0.820000 loss: 0.000658 2022/10/27 14:03:16 - mmengine - INFO - Epoch(train) [39][500/586] lr: 5.000000e-04 eta: 7:35:50 time: 0.287053 data_time: 0.031524 memory: 11131 loss_kpt: 0.000666 acc_pose: 0.828874 loss: 0.000666 2022/10/27 14:03:31 - mmengine - INFO - Epoch(train) [39][550/586] lr: 5.000000e-04 eta: 7:35:40 time: 0.289035 data_time: 0.033278 memory: 11131 loss_kpt: 0.000658 acc_pose: 0.829477 loss: 0.000658 2022/10/27 14:03:41 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:03:56 - mmengine - INFO - Epoch(train) [40][50/586] lr: 5.000000e-04 eta: 7:34:39 time: 0.298966 data_time: 0.041466 memory: 11131 loss_kpt: 0.000658 acc_pose: 0.896799 loss: 0.000658 2022/10/27 14:04:11 - mmengine - INFO - Epoch(train) [40][100/586] lr: 5.000000e-04 eta: 7:34:28 time: 0.285572 data_time: 0.028526 memory: 11131 loss_kpt: 0.000634 acc_pose: 0.859650 loss: 0.000634 2022/10/27 14:04:24 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:04:25 - mmengine - INFO - Epoch(train) [40][150/586] lr: 5.000000e-04 eta: 7:34:16 time: 0.280997 data_time: 0.028157 memory: 11131 loss_kpt: 0.000665 acc_pose: 0.772065 loss: 0.000665 2022/10/27 14:04:39 - mmengine - INFO - Epoch(train) [40][200/586] lr: 5.000000e-04 eta: 7:34:06 time: 0.287708 data_time: 0.031345 memory: 11131 loss_kpt: 0.000664 acc_pose: 0.838527 loss: 0.000664 2022/10/27 14:04:54 - mmengine - INFO - Epoch(train) [40][250/586] lr: 5.000000e-04 eta: 7:33:57 time: 0.291929 data_time: 0.026945 memory: 11131 loss_kpt: 0.000671 acc_pose: 0.822022 loss: 0.000671 2022/10/27 14:05:08 - mmengine - INFO - Epoch(train) [40][300/586] lr: 5.000000e-04 eta: 7:33:46 time: 0.287973 data_time: 0.027982 memory: 11131 loss_kpt: 0.000651 acc_pose: 0.793486 loss: 0.000651 2022/10/27 14:05:22 - mmengine - INFO - Epoch(train) [40][350/586] lr: 5.000000e-04 eta: 7:33:36 time: 0.285252 data_time: 0.032254 memory: 11131 loss_kpt: 0.000667 acc_pose: 0.818149 loss: 0.000667 2022/10/27 14:05:37 - mmengine - INFO - Epoch(train) [40][400/586] lr: 5.000000e-04 eta: 7:33:25 time: 0.284719 data_time: 0.028831 memory: 11131 loss_kpt: 0.000654 acc_pose: 0.864610 loss: 0.000654 2022/10/27 14:05:51 - mmengine - INFO - Epoch(train) [40][450/586] lr: 5.000000e-04 eta: 7:33:14 time: 0.285053 data_time: 0.029246 memory: 11131 loss_kpt: 0.000658 acc_pose: 0.755084 loss: 0.000658 2022/10/27 14:06:05 - mmengine - INFO - Epoch(train) [40][500/586] lr: 5.000000e-04 eta: 7:33:04 time: 0.293233 data_time: 0.026694 memory: 11131 loss_kpt: 0.000665 acc_pose: 0.826004 loss: 0.000665 2022/10/27 14:06:20 - mmengine - INFO - Epoch(train) [40][550/586] lr: 5.000000e-04 eta: 7:32:53 time: 0.284208 data_time: 0.029436 memory: 11131 loss_kpt: 0.000663 acc_pose: 0.808677 loss: 0.000663 2022/10/27 14:06:30 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:06:30 - mmengine - INFO - Saving checkpoint at 40 epochs 2022/10/27 14:06:41 - mmengine - INFO - Epoch(val) [40][50/407] eta: 0:00:50 time: 0.141720 data_time: 0.022462 memory: 11131 2022/10/27 14:06:48 - mmengine - INFO - Epoch(val) [40][100/407] eta: 0:00:43 time: 0.142534 data_time: 0.022385 memory: 1836 2022/10/27 14:06:55 - mmengine - INFO - Epoch(val) [40][150/407] eta: 0:00:35 time: 0.138549 data_time: 0.017919 memory: 1836 2022/10/27 14:07:01 - mmengine - INFO - Epoch(val) [40][200/407] eta: 0:00:27 time: 0.131650 data_time: 0.012135 memory: 1836 2022/10/27 14:07:08 - mmengine - INFO - Epoch(val) [40][250/407] eta: 0:00:21 time: 0.136622 data_time: 0.014854 memory: 1836 2022/10/27 14:07:15 - mmengine - INFO - Epoch(val) [40][300/407] eta: 0:00:14 time: 0.131952 data_time: 0.012095 memory: 1836 2022/10/27 14:07:22 - mmengine - INFO - Epoch(val) [40][350/407] eta: 0:00:08 time: 0.140446 data_time: 0.021364 memory: 1836 2022/10/27 14:07:28 - mmengine - INFO - Epoch(val) [40][400/407] eta: 0:00:00 time: 0.129865 data_time: 0.013744 memory: 1836 2022/10/27 14:08:15 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 14:08:32 - mmengine - INFO - Epoch(val) [40][407/407] coco/AP: 0.718481 coco/AP .5: 0.890969 coco/AP .75: 0.789081 coco/AP (M): 0.675648 coco/AP (L): 0.791344 coco/AR: 0.770765 coco/AR .5: 0.928526 coco/AR .75: 0.833281 coco/AR (M): 0.724392 coco/AR (L): 0.837607 2022/10/27 14:08:32 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_30.pth is removed 2022/10/27 14:08:34 - mmengine - INFO - The best checkpoint with 0.7185 coco/AP at 40 epoch is saved to best_coco/AP_epoch_40.pth. 2022/10/27 14:08:49 - mmengine - INFO - Epoch(train) [41][50/586] lr: 5.000000e-04 eta: 7:31:53 time: 0.293622 data_time: 0.036779 memory: 11131 loss_kpt: 0.000636 acc_pose: 0.791012 loss: 0.000636 2022/10/27 14:09:03 - mmengine - INFO - Epoch(train) [41][100/586] lr: 5.000000e-04 eta: 7:31:42 time: 0.285476 data_time: 0.028166 memory: 11131 loss_kpt: 0.000643 acc_pose: 0.821110 loss: 0.000643 2022/10/27 14:09:18 - mmengine - INFO - Epoch(train) [41][150/586] lr: 5.000000e-04 eta: 7:31:32 time: 0.291008 data_time: 0.028045 memory: 11131 loss_kpt: 0.000667 acc_pose: 0.862859 loss: 0.000667 2022/10/27 14:09:32 - mmengine - INFO - Epoch(train) [41][200/586] lr: 5.000000e-04 eta: 7:31:21 time: 0.283071 data_time: 0.029319 memory: 11131 loss_kpt: 0.000648 acc_pose: 0.762137 loss: 0.000648 2022/10/27 14:09:46 - mmengine - INFO - Epoch(train) [41][250/586] lr: 5.000000e-04 eta: 7:31:10 time: 0.288513 data_time: 0.026839 memory: 11131 loss_kpt: 0.000649 acc_pose: 0.821586 loss: 0.000649 2022/10/27 14:10:01 - mmengine - INFO - Epoch(train) [41][300/586] lr: 5.000000e-04 eta: 7:31:00 time: 0.286658 data_time: 0.027977 memory: 11131 loss_kpt: 0.000659 acc_pose: 0.852039 loss: 0.000659 2022/10/27 14:10:15 - mmengine - INFO - Epoch(train) [41][350/586] lr: 5.000000e-04 eta: 7:30:51 time: 0.293591 data_time: 0.029318 memory: 11131 loss_kpt: 0.000676 acc_pose: 0.755344 loss: 0.000676 2022/10/27 14:10:30 - mmengine - INFO - Epoch(train) [41][400/586] lr: 5.000000e-04 eta: 7:30:40 time: 0.286365 data_time: 0.029230 memory: 11131 loss_kpt: 0.000669 acc_pose: 0.807394 loss: 0.000669 2022/10/27 14:10:44 - mmengine - INFO - Epoch(train) [41][450/586] lr: 5.000000e-04 eta: 7:30:29 time: 0.287804 data_time: 0.027929 memory: 11131 loss_kpt: 0.000650 acc_pose: 0.839418 loss: 0.000650 2022/10/27 14:10:58 - mmengine - INFO - Epoch(train) [41][500/586] lr: 5.000000e-04 eta: 7:30:19 time: 0.286709 data_time: 0.027463 memory: 11131 loss_kpt: 0.000671 acc_pose: 0.817918 loss: 0.000671 2022/10/27 14:11:13 - mmengine - INFO - Epoch(train) [41][550/586] lr: 5.000000e-04 eta: 7:30:07 time: 0.284064 data_time: 0.028095 memory: 11131 loss_kpt: 0.000688 acc_pose: 0.814181 loss: 0.000688 2022/10/27 14:11:16 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:11:23 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:11:38 - mmengine - INFO - Epoch(train) [42][50/586] lr: 5.000000e-04 eta: 7:29:09 time: 0.298319 data_time: 0.041351 memory: 11131 loss_kpt: 0.000651 acc_pose: 0.785233 loss: 0.000651 2022/10/27 14:11:52 - mmengine - INFO - Epoch(train) [42][100/586] lr: 5.000000e-04 eta: 7:28:59 time: 0.288837 data_time: 0.035861 memory: 11131 loss_kpt: 0.000662 acc_pose: 0.837320 loss: 0.000662 2022/10/27 14:12:07 - mmengine - INFO - Epoch(train) [42][150/586] lr: 5.000000e-04 eta: 7:28:47 time: 0.283415 data_time: 0.028629 memory: 11131 loss_kpt: 0.000657 acc_pose: 0.855930 loss: 0.000657 2022/10/27 14:12:21 - mmengine - INFO - Epoch(train) [42][200/586] lr: 5.000000e-04 eta: 7:28:36 time: 0.284639 data_time: 0.028592 memory: 11131 loss_kpt: 0.000625 acc_pose: 0.813077 loss: 0.000625 2022/10/27 14:12:35 - mmengine - INFO - Epoch(train) [42][250/586] lr: 5.000000e-04 eta: 7:28:26 time: 0.290859 data_time: 0.029338 memory: 11131 loss_kpt: 0.000660 acc_pose: 0.813903 loss: 0.000660 2022/10/27 14:12:50 - mmengine - INFO - Epoch(train) [42][300/586] lr: 5.000000e-04 eta: 7:28:15 time: 0.285319 data_time: 0.030394 memory: 11131 loss_kpt: 0.000655 acc_pose: 0.873924 loss: 0.000655 2022/10/27 14:13:04 - mmengine - INFO - Epoch(train) [42][350/586] lr: 5.000000e-04 eta: 7:28:05 time: 0.288862 data_time: 0.032097 memory: 11131 loss_kpt: 0.000652 acc_pose: 0.845448 loss: 0.000652 2022/10/27 14:13:18 - mmengine - INFO - Epoch(train) [42][400/586] lr: 5.000000e-04 eta: 7:27:54 time: 0.284595 data_time: 0.027330 memory: 11131 loss_kpt: 0.000646 acc_pose: 0.786224 loss: 0.000646 2022/10/27 14:13:33 - mmengine - INFO - Epoch(train) [42][450/586] lr: 5.000000e-04 eta: 7:27:43 time: 0.286033 data_time: 0.030453 memory: 11131 loss_kpt: 0.000632 acc_pose: 0.842666 loss: 0.000632 2022/10/27 14:13:47 - mmengine - INFO - Epoch(train) [42][500/586] lr: 5.000000e-04 eta: 7:27:33 time: 0.289179 data_time: 0.030552 memory: 11131 loss_kpt: 0.000679 acc_pose: 0.770315 loss: 0.000679 2022/10/27 14:14:02 - mmengine - INFO - Epoch(train) [42][550/586] lr: 5.000000e-04 eta: 7:27:23 time: 0.290450 data_time: 0.030280 memory: 11131 loss_kpt: 0.000653 acc_pose: 0.845765 loss: 0.000653 2022/10/27 14:14:12 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:14:27 - mmengine - INFO - Epoch(train) [43][50/586] lr: 5.000000e-04 eta: 7:26:25 time: 0.295676 data_time: 0.039837 memory: 11131 loss_kpt: 0.000649 acc_pose: 0.805702 loss: 0.000649 2022/10/27 14:14:41 - mmengine - INFO - Epoch(train) [43][100/586] lr: 5.000000e-04 eta: 7:26:14 time: 0.284286 data_time: 0.029506 memory: 11131 loss_kpt: 0.000629 acc_pose: 0.865524 loss: 0.000629 2022/10/27 14:14:55 - mmengine - INFO - Epoch(train) [43][150/586] lr: 5.000000e-04 eta: 7:26:03 time: 0.288829 data_time: 0.027981 memory: 11131 loss_kpt: 0.000654 acc_pose: 0.759590 loss: 0.000654 2022/10/27 14:15:10 - mmengine - INFO - Epoch(train) [43][200/586] lr: 5.000000e-04 eta: 7:25:52 time: 0.284140 data_time: 0.031107 memory: 11131 loss_kpt: 0.000658 acc_pose: 0.778314 loss: 0.000658 2022/10/27 14:15:24 - mmengine - INFO - Epoch(train) [43][250/586] lr: 5.000000e-04 eta: 7:25:42 time: 0.291386 data_time: 0.032084 memory: 11131 loss_kpt: 0.000643 acc_pose: 0.831882 loss: 0.000643 2022/10/27 14:15:38 - mmengine - INFO - Epoch(train) [43][300/586] lr: 5.000000e-04 eta: 7:25:31 time: 0.284716 data_time: 0.030747 memory: 11131 loss_kpt: 0.000659 acc_pose: 0.795245 loss: 0.000659 2022/10/27 14:15:53 - mmengine - INFO - Epoch(train) [43][350/586] lr: 5.000000e-04 eta: 7:25:21 time: 0.291467 data_time: 0.026793 memory: 11131 loss_kpt: 0.000662 acc_pose: 0.847621 loss: 0.000662 2022/10/27 14:16:04 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:16:07 - mmengine - INFO - Epoch(train) [43][400/586] lr: 5.000000e-04 eta: 7:25:10 time: 0.285676 data_time: 0.028341 memory: 11131 loss_kpt: 0.000667 acc_pose: 0.784848 loss: 0.000667 2022/10/27 14:16:22 - mmengine - INFO - Epoch(train) [43][450/586] lr: 5.000000e-04 eta: 7:25:00 time: 0.290435 data_time: 0.027344 memory: 11131 loss_kpt: 0.000650 acc_pose: 0.851182 loss: 0.000650 2022/10/27 14:16:36 - mmengine - INFO - Epoch(train) [43][500/586] lr: 5.000000e-04 eta: 7:24:50 time: 0.288502 data_time: 0.031711 memory: 11131 loss_kpt: 0.000635 acc_pose: 0.786499 loss: 0.000635 2022/10/27 14:16:50 - mmengine - INFO - Epoch(train) [43][550/586] lr: 5.000000e-04 eta: 7:24:38 time: 0.285306 data_time: 0.028356 memory: 11131 loss_kpt: 0.000645 acc_pose: 0.812631 loss: 0.000645 2022/10/27 14:17:01 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:17:16 - mmengine - INFO - Epoch(train) [44][50/586] lr: 5.000000e-04 eta: 7:23:42 time: 0.298075 data_time: 0.040570 memory: 11131 loss_kpt: 0.000650 acc_pose: 0.859664 loss: 0.000650 2022/10/27 14:17:30 - mmengine - INFO - Epoch(train) [44][100/586] lr: 5.000000e-04 eta: 7:23:32 time: 0.289565 data_time: 0.031316 memory: 11131 loss_kpt: 0.000648 acc_pose: 0.733642 loss: 0.000648 2022/10/27 14:17:45 - mmengine - INFO - Epoch(train) [44][150/586] lr: 5.000000e-04 eta: 7:23:21 time: 0.286930 data_time: 0.027576 memory: 11131 loss_kpt: 0.000635 acc_pose: 0.787762 loss: 0.000635 2022/10/27 14:17:59 - mmengine - INFO - Epoch(train) [44][200/586] lr: 5.000000e-04 eta: 7:23:09 time: 0.283713 data_time: 0.027898 memory: 11131 loss_kpt: 0.000644 acc_pose: 0.807409 loss: 0.000644 2022/10/27 14:18:13 - mmengine - INFO - Epoch(train) [44][250/586] lr: 5.000000e-04 eta: 7:22:59 time: 0.289135 data_time: 0.028334 memory: 11131 loss_kpt: 0.000656 acc_pose: 0.854200 loss: 0.000656 2022/10/27 14:18:27 - mmengine - INFO - Epoch(train) [44][300/586] lr: 5.000000e-04 eta: 7:22:48 time: 0.283391 data_time: 0.027549 memory: 11131 loss_kpt: 0.000641 acc_pose: 0.852592 loss: 0.000641 2022/10/27 14:18:42 - mmengine - INFO - Epoch(train) [44][350/586] lr: 5.000000e-04 eta: 7:22:37 time: 0.286467 data_time: 0.027835 memory: 11131 loss_kpt: 0.000636 acc_pose: 0.841018 loss: 0.000636 2022/10/27 14:18:56 - mmengine - INFO - Epoch(train) [44][400/586] lr: 5.000000e-04 eta: 7:22:26 time: 0.287531 data_time: 0.028823 memory: 11131 loss_kpt: 0.000641 acc_pose: 0.819972 loss: 0.000641 2022/10/27 14:19:10 - mmengine - INFO - Epoch(train) [44][450/586] lr: 5.000000e-04 eta: 7:22:15 time: 0.285141 data_time: 0.026829 memory: 11131 loss_kpt: 0.000660 acc_pose: 0.805868 loss: 0.000660 2022/10/27 14:19:25 - mmengine - INFO - Epoch(train) [44][500/586] lr: 5.000000e-04 eta: 7:22:05 time: 0.291139 data_time: 0.029385 memory: 11131 loss_kpt: 0.000645 acc_pose: 0.849752 loss: 0.000645 2022/10/27 14:19:39 - mmengine - INFO - Epoch(train) [44][550/586] lr: 5.000000e-04 eta: 7:21:54 time: 0.286269 data_time: 0.028584 memory: 11131 loss_kpt: 0.000650 acc_pose: 0.791956 loss: 0.000650 2022/10/27 14:19:50 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:20:04 - mmengine - INFO - Epoch(train) [45][50/586] lr: 5.000000e-04 eta: 7:20:58 time: 0.295484 data_time: 0.037349 memory: 11131 loss_kpt: 0.000644 acc_pose: 0.799640 loss: 0.000644 2022/10/27 14:20:19 - mmengine - INFO - Epoch(train) [45][100/586] lr: 5.000000e-04 eta: 7:20:47 time: 0.287451 data_time: 0.029790 memory: 11131 loss_kpt: 0.000645 acc_pose: 0.822799 loss: 0.000645 2022/10/27 14:20:33 - mmengine - INFO - Epoch(train) [45][150/586] lr: 5.000000e-04 eta: 7:20:37 time: 0.289535 data_time: 0.027376 memory: 11131 loss_kpt: 0.000634 acc_pose: 0.821398 loss: 0.000634 2022/10/27 14:20:47 - mmengine - INFO - Epoch(train) [45][200/586] lr: 5.000000e-04 eta: 7:20:25 time: 0.282465 data_time: 0.026863 memory: 11131 loss_kpt: 0.000628 acc_pose: 0.845446 loss: 0.000628 2022/10/27 14:20:52 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:21:02 - mmengine - INFO - Epoch(train) [45][250/586] lr: 5.000000e-04 eta: 7:20:15 time: 0.291139 data_time: 0.033862 memory: 11131 loss_kpt: 0.000650 acc_pose: 0.865779 loss: 0.000650 2022/10/27 14:21:16 - mmengine - INFO - Epoch(train) [45][300/586] lr: 5.000000e-04 eta: 7:20:03 time: 0.283634 data_time: 0.027438 memory: 11131 loss_kpt: 0.000642 acc_pose: 0.886727 loss: 0.000642 2022/10/27 14:21:30 - mmengine - INFO - Epoch(train) [45][350/586] lr: 5.000000e-04 eta: 7:19:52 time: 0.286929 data_time: 0.029729 memory: 11131 loss_kpt: 0.000615 acc_pose: 0.664121 loss: 0.000615 2022/10/27 14:21:45 - mmengine - INFO - Epoch(train) [45][400/586] lr: 5.000000e-04 eta: 7:19:42 time: 0.288047 data_time: 0.027163 memory: 11131 loss_kpt: 0.000649 acc_pose: 0.798169 loss: 0.000649 2022/10/27 14:21:59 - mmengine - INFO - Epoch(train) [45][450/586] lr: 5.000000e-04 eta: 7:19:30 time: 0.284198 data_time: 0.028761 memory: 11131 loss_kpt: 0.000647 acc_pose: 0.795388 loss: 0.000647 2022/10/27 14:22:14 - mmengine - INFO - Epoch(train) [45][500/586] lr: 5.000000e-04 eta: 7:19:20 time: 0.289776 data_time: 0.032486 memory: 11131 loss_kpt: 0.000642 acc_pose: 0.791488 loss: 0.000642 2022/10/27 14:22:28 - mmengine - INFO - Epoch(train) [45][550/586] lr: 5.000000e-04 eta: 7:19:10 time: 0.290210 data_time: 0.032817 memory: 11131 loss_kpt: 0.000651 acc_pose: 0.754343 loss: 0.000651 2022/10/27 14:22:38 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:22:53 - mmengine - INFO - Epoch(train) [46][50/586] lr: 5.000000e-04 eta: 7:18:15 time: 0.297478 data_time: 0.037548 memory: 11131 loss_kpt: 0.000634 acc_pose: 0.821021 loss: 0.000634 2022/10/27 14:23:08 - mmengine - INFO - Epoch(train) [46][100/586] lr: 5.000000e-04 eta: 7:18:04 time: 0.286940 data_time: 0.026968 memory: 11131 loss_kpt: 0.000632 acc_pose: 0.827764 loss: 0.000632 2022/10/27 14:23:22 - mmengine - INFO - Epoch(train) [46][150/586] lr: 5.000000e-04 eta: 7:17:54 time: 0.291117 data_time: 0.028620 memory: 11131 loss_kpt: 0.000651 acc_pose: 0.836414 loss: 0.000651 2022/10/27 14:23:36 - mmengine - INFO - Epoch(train) [46][200/586] lr: 5.000000e-04 eta: 7:17:42 time: 0.284880 data_time: 0.029503 memory: 11131 loss_kpt: 0.000621 acc_pose: 0.820588 loss: 0.000621 2022/10/27 14:23:51 - mmengine - INFO - Epoch(train) [46][250/586] lr: 5.000000e-04 eta: 7:17:32 time: 0.287446 data_time: 0.026956 memory: 11131 loss_kpt: 0.000645 acc_pose: 0.835444 loss: 0.000645 2022/10/27 14:24:05 - mmengine - INFO - Epoch(train) [46][300/586] lr: 5.000000e-04 eta: 7:17:20 time: 0.285435 data_time: 0.029545 memory: 11131 loss_kpt: 0.000624 acc_pose: 0.774449 loss: 0.000624 2022/10/27 14:24:20 - mmengine - INFO - Epoch(train) [46][350/586] lr: 5.000000e-04 eta: 7:17:10 time: 0.291649 data_time: 0.035759 memory: 11131 loss_kpt: 0.000632 acc_pose: 0.899011 loss: 0.000632 2022/10/27 14:24:34 - mmengine - INFO - Epoch(train) [46][400/586] lr: 5.000000e-04 eta: 7:17:00 time: 0.289882 data_time: 0.027714 memory: 11131 loss_kpt: 0.000651 acc_pose: 0.835793 loss: 0.000651 2022/10/27 14:24:48 - mmengine - INFO - Epoch(train) [46][450/586] lr: 5.000000e-04 eta: 7:16:49 time: 0.286016 data_time: 0.031768 memory: 11131 loss_kpt: 0.000650 acc_pose: 0.782799 loss: 0.000650 2022/10/27 14:25:03 - mmengine - INFO - Epoch(train) [46][500/586] lr: 5.000000e-04 eta: 7:16:39 time: 0.292949 data_time: 0.028943 memory: 11131 loss_kpt: 0.000654 acc_pose: 0.729945 loss: 0.000654 2022/10/27 14:25:17 - mmengine - INFO - Epoch(train) [46][550/586] lr: 5.000000e-04 eta: 7:16:27 time: 0.283385 data_time: 0.029112 memory: 11131 loss_kpt: 0.000648 acc_pose: 0.844668 loss: 0.000648 2022/10/27 14:25:28 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:25:41 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:25:42 - mmengine - INFO - Epoch(train) [47][50/586] lr: 5.000000e-04 eta: 7:15:33 time: 0.297240 data_time: 0.036809 memory: 11131 loss_kpt: 0.000654 acc_pose: 0.840172 loss: 0.000654 2022/10/27 14:25:57 - mmengine - INFO - Epoch(train) [47][100/586] lr: 5.000000e-04 eta: 7:15:22 time: 0.285155 data_time: 0.027944 memory: 11131 loss_kpt: 0.000630 acc_pose: 0.847871 loss: 0.000630 2022/10/27 14:26:11 - mmengine - INFO - Epoch(train) [47][150/586] lr: 5.000000e-04 eta: 7:15:12 time: 0.290366 data_time: 0.029405 memory: 11131 loss_kpt: 0.000638 acc_pose: 0.840625 loss: 0.000638 2022/10/27 14:26:25 - mmengine - INFO - Epoch(train) [47][200/586] lr: 5.000000e-04 eta: 7:15:00 time: 0.281439 data_time: 0.030287 memory: 11131 loss_kpt: 0.000632 acc_pose: 0.841010 loss: 0.000632 2022/10/27 14:26:40 - mmengine - INFO - Epoch(train) [47][250/586] lr: 5.000000e-04 eta: 7:14:49 time: 0.290003 data_time: 0.032587 memory: 11131 loss_kpt: 0.000637 acc_pose: 0.852483 loss: 0.000637 2022/10/27 14:26:54 - mmengine - INFO - Epoch(train) [47][300/586] lr: 5.000000e-04 eta: 7:14:39 time: 0.289965 data_time: 0.032406 memory: 11131 loss_kpt: 0.000633 acc_pose: 0.866315 loss: 0.000633 2022/10/27 14:27:09 - mmengine - INFO - Epoch(train) [47][350/586] lr: 5.000000e-04 eta: 7:14:27 time: 0.284888 data_time: 0.030474 memory: 11131 loss_kpt: 0.000655 acc_pose: 0.856007 loss: 0.000655 2022/10/27 14:27:23 - mmengine - INFO - Epoch(train) [47][400/586] lr: 5.000000e-04 eta: 7:14:17 time: 0.292127 data_time: 0.029345 memory: 11131 loss_kpt: 0.000640 acc_pose: 0.813803 loss: 0.000640 2022/10/27 14:27:38 - mmengine - INFO - Epoch(train) [47][450/586] lr: 5.000000e-04 eta: 7:14:06 time: 0.288978 data_time: 0.032796 memory: 11131 loss_kpt: 0.000659 acc_pose: 0.735662 loss: 0.000659 2022/10/27 14:27:52 - mmengine - INFO - Epoch(train) [47][500/586] lr: 5.000000e-04 eta: 7:13:56 time: 0.288143 data_time: 0.033214 memory: 11131 loss_kpt: 0.000632 acc_pose: 0.796939 loss: 0.000632 2022/10/27 14:28:06 - mmengine - INFO - Epoch(train) [47][550/586] lr: 5.000000e-04 eta: 7:13:45 time: 0.287426 data_time: 0.033179 memory: 11131 loss_kpt: 0.000636 acc_pose: 0.808705 loss: 0.000636 2022/10/27 14:28:17 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:28:32 - mmengine - INFO - Epoch(train) [48][50/586] lr: 5.000000e-04 eta: 7:12:53 time: 0.302818 data_time: 0.045546 memory: 11131 loss_kpt: 0.000639 acc_pose: 0.825750 loss: 0.000639 2022/10/27 14:28:46 - mmengine - INFO - Epoch(train) [48][100/586] lr: 5.000000e-04 eta: 7:12:42 time: 0.289774 data_time: 0.037931 memory: 11131 loss_kpt: 0.000644 acc_pose: 0.824960 loss: 0.000644 2022/10/27 14:29:01 - mmengine - INFO - Epoch(train) [48][150/586] lr: 5.000000e-04 eta: 7:12:31 time: 0.285248 data_time: 0.030369 memory: 11131 loss_kpt: 0.000640 acc_pose: 0.823652 loss: 0.000640 2022/10/27 14:29:15 - mmengine - INFO - Epoch(train) [48][200/586] lr: 5.000000e-04 eta: 7:12:20 time: 0.289528 data_time: 0.035536 memory: 11131 loss_kpt: 0.000639 acc_pose: 0.777715 loss: 0.000639 2022/10/27 14:29:29 - mmengine - INFO - Epoch(train) [48][250/586] lr: 5.000000e-04 eta: 7:12:09 time: 0.287450 data_time: 0.031361 memory: 11131 loss_kpt: 0.000644 acc_pose: 0.877810 loss: 0.000644 2022/10/27 14:29:44 - mmengine - INFO - Epoch(train) [48][300/586] lr: 5.000000e-04 eta: 7:11:58 time: 0.287270 data_time: 0.030268 memory: 11131 loss_kpt: 0.000651 acc_pose: 0.843287 loss: 0.000651 2022/10/27 14:29:58 - mmengine - INFO - Epoch(train) [48][350/586] lr: 5.000000e-04 eta: 7:11:48 time: 0.290754 data_time: 0.034705 memory: 11131 loss_kpt: 0.000640 acc_pose: 0.783732 loss: 0.000640 2022/10/27 14:30:13 - mmengine - INFO - Epoch(train) [48][400/586] lr: 5.000000e-04 eta: 7:11:37 time: 0.288030 data_time: 0.032767 memory: 11131 loss_kpt: 0.000637 acc_pose: 0.816982 loss: 0.000637 2022/10/27 14:30:27 - mmengine - INFO - Epoch(train) [48][450/586] lr: 5.000000e-04 eta: 7:11:25 time: 0.282982 data_time: 0.029664 memory: 11131 loss_kpt: 0.000648 acc_pose: 0.823273 loss: 0.000648 2022/10/27 14:30:29 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:30:42 - mmengine - INFO - Epoch(train) [48][500/586] lr: 5.000000e-04 eta: 7:11:15 time: 0.294888 data_time: 0.036090 memory: 11131 loss_kpt: 0.000649 acc_pose: 0.866092 loss: 0.000649 2022/10/27 14:30:56 - mmengine - INFO - Epoch(train) [48][550/586] lr: 5.000000e-04 eta: 7:11:03 time: 0.283105 data_time: 0.030628 memory: 11131 loss_kpt: 0.000650 acc_pose: 0.837362 loss: 0.000650 2022/10/27 14:31:06 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:31:21 - mmengine - INFO - Epoch(train) [49][50/586] lr: 5.000000e-04 eta: 7:10:11 time: 0.297263 data_time: 0.039243 memory: 11131 loss_kpt: 0.000651 acc_pose: 0.900287 loss: 0.000651 2022/10/27 14:31:35 - mmengine - INFO - Epoch(train) [49][100/586] lr: 5.000000e-04 eta: 7:10:00 time: 0.284630 data_time: 0.031641 memory: 11131 loss_kpt: 0.000663 acc_pose: 0.774097 loss: 0.000663 2022/10/27 14:31:50 - mmengine - INFO - Epoch(train) [49][150/586] lr: 5.000000e-04 eta: 7:09:49 time: 0.289567 data_time: 0.031906 memory: 11131 loss_kpt: 0.000633 acc_pose: 0.783958 loss: 0.000633 2022/10/27 14:32:04 - mmengine - INFO - Epoch(train) [49][200/586] lr: 5.000000e-04 eta: 7:09:38 time: 0.285758 data_time: 0.029973 memory: 11131 loss_kpt: 0.000644 acc_pose: 0.879780 loss: 0.000644 2022/10/27 14:32:19 - mmengine - INFO - Epoch(train) [49][250/586] lr: 5.000000e-04 eta: 7:09:27 time: 0.289566 data_time: 0.036687 memory: 11131 loss_kpt: 0.000628 acc_pose: 0.868401 loss: 0.000628 2022/10/27 14:32:33 - mmengine - INFO - Epoch(train) [49][300/586] lr: 5.000000e-04 eta: 7:09:16 time: 0.288034 data_time: 0.031035 memory: 11131 loss_kpt: 0.000631 acc_pose: 0.756960 loss: 0.000631 2022/10/27 14:32:47 - mmengine - INFO - Epoch(train) [49][350/586] lr: 5.000000e-04 eta: 7:09:05 time: 0.287160 data_time: 0.034192 memory: 11131 loss_kpt: 0.000611 acc_pose: 0.815489 loss: 0.000611 2022/10/27 14:33:02 - mmengine - INFO - Epoch(train) [49][400/586] lr: 5.000000e-04 eta: 7:08:54 time: 0.291340 data_time: 0.032960 memory: 11131 loss_kpt: 0.000633 acc_pose: 0.829886 loss: 0.000633 2022/10/27 14:33:16 - mmengine - INFO - Epoch(train) [49][450/586] lr: 5.000000e-04 eta: 7:08:43 time: 0.287000 data_time: 0.033334 memory: 11131 loss_kpt: 0.000637 acc_pose: 0.850121 loss: 0.000637 2022/10/27 14:33:31 - mmengine - INFO - Epoch(train) [49][500/586] lr: 5.000000e-04 eta: 7:08:33 time: 0.292185 data_time: 0.033266 memory: 11131 loss_kpt: 0.000660 acc_pose: 0.773697 loss: 0.000660 2022/10/27 14:33:45 - mmengine - INFO - Epoch(train) [49][550/586] lr: 5.000000e-04 eta: 7:08:22 time: 0.287383 data_time: 0.030882 memory: 11131 loss_kpt: 0.000653 acc_pose: 0.774579 loss: 0.000653 2022/10/27 14:33:55 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:34:10 - mmengine - INFO - Epoch(train) [50][50/586] lr: 5.000000e-04 eta: 7:07:31 time: 0.299440 data_time: 0.042310 memory: 11131 loss_kpt: 0.000625 acc_pose: 0.851207 loss: 0.000625 2022/10/27 14:34:25 - mmengine - INFO - Epoch(train) [50][100/586] lr: 5.000000e-04 eta: 7:07:19 time: 0.287064 data_time: 0.035802 memory: 11131 loss_kpt: 0.000620 acc_pose: 0.860219 loss: 0.000620 2022/10/27 14:34:39 - mmengine - INFO - Epoch(train) [50][150/586] lr: 5.000000e-04 eta: 7:07:08 time: 0.287425 data_time: 0.029448 memory: 11131 loss_kpt: 0.000625 acc_pose: 0.801462 loss: 0.000625 2022/10/27 14:34:53 - mmengine - INFO - Epoch(train) [50][200/586] lr: 5.000000e-04 eta: 7:06:57 time: 0.284128 data_time: 0.028557 memory: 11131 loss_kpt: 0.000617 acc_pose: 0.776527 loss: 0.000617 2022/10/27 14:35:08 - mmengine - INFO - Epoch(train) [50][250/586] lr: 5.000000e-04 eta: 7:06:47 time: 0.293048 data_time: 0.033710 memory: 11131 loss_kpt: 0.000625 acc_pose: 0.795867 loss: 0.000625 2022/10/27 14:35:18 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:35:22 - mmengine - INFO - Epoch(train) [50][300/586] lr: 5.000000e-04 eta: 7:06:36 time: 0.288281 data_time: 0.029647 memory: 11131 loss_kpt: 0.000643 acc_pose: 0.844498 loss: 0.000643 2022/10/27 14:35:37 - mmengine - INFO - Epoch(train) [50][350/586] lr: 5.000000e-04 eta: 7:06:24 time: 0.284270 data_time: 0.030720 memory: 11131 loss_kpt: 0.000646 acc_pose: 0.836335 loss: 0.000646 2022/10/27 14:35:51 - mmengine - INFO - Epoch(train) [50][400/586] lr: 5.000000e-04 eta: 7:06:13 time: 0.291148 data_time: 0.032688 memory: 11131 loss_kpt: 0.000656 acc_pose: 0.787834 loss: 0.000656 2022/10/27 14:36:06 - mmengine - INFO - Epoch(train) [50][450/586] lr: 5.000000e-04 eta: 7:06:02 time: 0.286454 data_time: 0.027205 memory: 11131 loss_kpt: 0.000651 acc_pose: 0.856100 loss: 0.000651 2022/10/27 14:36:20 - mmengine - INFO - Epoch(train) [50][500/586] lr: 5.000000e-04 eta: 7:05:51 time: 0.288930 data_time: 0.031876 memory: 11131 loss_kpt: 0.000625 acc_pose: 0.852775 loss: 0.000625 2022/10/27 14:36:34 - mmengine - INFO - Epoch(train) [50][550/586] lr: 5.000000e-04 eta: 7:05:40 time: 0.286275 data_time: 0.028193 memory: 11131 loss_kpt: 0.000642 acc_pose: 0.742867 loss: 0.000642 2022/10/27 14:36:45 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:36:45 - mmengine - INFO - Saving checkpoint at 50 epochs 2022/10/27 14:36:55 - mmengine - INFO - Epoch(val) [50][50/407] eta: 0:00:49 time: 0.139211 data_time: 0.018597 memory: 11131 2022/10/27 14:37:02 - mmengine - INFO - Epoch(val) [50][100/407] eta: 0:00:42 time: 0.137261 data_time: 0.017618 memory: 1836 2022/10/27 14:37:09 - mmengine - INFO - Epoch(val) [50][150/407] eta: 0:00:35 time: 0.139621 data_time: 0.015940 memory: 1836 2022/10/27 14:37:16 - mmengine - INFO - Epoch(val) [50][200/407] eta: 0:00:27 time: 0.133647 data_time: 0.013978 memory: 1836 2022/10/27 14:37:23 - mmengine - INFO - Epoch(val) [50][250/407] eta: 0:00:22 time: 0.141792 data_time: 0.020220 memory: 1836 2022/10/27 14:37:30 - mmengine - INFO - Epoch(val) [50][300/407] eta: 0:00:14 time: 0.135531 data_time: 0.015409 memory: 1836 2022/10/27 14:37:36 - mmengine - INFO - Epoch(val) [50][350/407] eta: 0:00:07 time: 0.132253 data_time: 0.012474 memory: 1836 2022/10/27 14:37:43 - mmengine - INFO - Epoch(val) [50][400/407] eta: 0:00:00 time: 0.132655 data_time: 0.015597 memory: 1836 2022/10/27 14:38:29 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 14:38:46 - mmengine - INFO - Epoch(val) [50][407/407] coco/AP: 0.721238 coco/AP .5: 0.893194 coco/AP .75: 0.788343 coco/AP (M): 0.679793 coco/AP (L): 0.793684 coco/AR: 0.774449 coco/AR .5: 0.930888 coco/AR .75: 0.835170 coco/AR (M): 0.728489 coco/AR (L): 0.840282 2022/10/27 14:38:46 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_40.pth is removed 2022/10/27 14:38:49 - mmengine - INFO - The best checkpoint with 0.7212 coco/AP at 50 epoch is saved to best_coco/AP_epoch_50.pth. 2022/10/27 14:39:03 - mmengine - INFO - Epoch(train) [51][50/586] lr: 5.000000e-04 eta: 7:04:48 time: 0.294032 data_time: 0.036682 memory: 11131 loss_kpt: 0.000634 acc_pose: 0.828916 loss: 0.000634 2022/10/27 14:39:18 - mmengine - INFO - Epoch(train) [51][100/586] lr: 5.000000e-04 eta: 7:04:38 time: 0.288666 data_time: 0.027016 memory: 11131 loss_kpt: 0.000641 acc_pose: 0.812982 loss: 0.000641 2022/10/27 14:39:32 - mmengine - INFO - Epoch(train) [51][150/586] lr: 5.000000e-04 eta: 7:04:26 time: 0.286427 data_time: 0.029103 memory: 11131 loss_kpt: 0.000620 acc_pose: 0.831089 loss: 0.000620 2022/10/27 14:39:46 - mmengine - INFO - Epoch(train) [51][200/586] lr: 5.000000e-04 eta: 7:04:14 time: 0.283482 data_time: 0.027747 memory: 11131 loss_kpt: 0.000626 acc_pose: 0.858018 loss: 0.000626 2022/10/27 14:40:00 - mmengine - INFO - Epoch(train) [51][250/586] lr: 5.000000e-04 eta: 7:04:03 time: 0.284306 data_time: 0.027365 memory: 11131 loss_kpt: 0.000633 acc_pose: 0.864024 loss: 0.000633 2022/10/27 14:40:15 - mmengine - INFO - Epoch(train) [51][300/586] lr: 5.000000e-04 eta: 7:03:52 time: 0.287401 data_time: 0.029700 memory: 11131 loss_kpt: 0.000637 acc_pose: 0.835786 loss: 0.000637 2022/10/27 14:40:29 - mmengine - INFO - Epoch(train) [51][350/586] lr: 5.000000e-04 eta: 7:03:41 time: 0.290314 data_time: 0.028266 memory: 11131 loss_kpt: 0.000656 acc_pose: 0.818985 loss: 0.000656 2022/10/27 14:40:44 - mmengine - INFO - Epoch(train) [51][400/586] lr: 5.000000e-04 eta: 7:03:30 time: 0.290264 data_time: 0.031728 memory: 11131 loss_kpt: 0.000610 acc_pose: 0.785693 loss: 0.000610 2022/10/27 14:40:58 - mmengine - INFO - Epoch(train) [51][450/586] lr: 5.000000e-04 eta: 7:03:18 time: 0.284751 data_time: 0.027948 memory: 11131 loss_kpt: 0.000650 acc_pose: 0.864862 loss: 0.000650 2022/10/27 14:41:13 - mmengine - INFO - Epoch(train) [51][500/586] lr: 5.000000e-04 eta: 7:03:08 time: 0.291372 data_time: 0.032810 memory: 11131 loss_kpt: 0.000621 acc_pose: 0.856411 loss: 0.000621 2022/10/27 14:41:27 - mmengine - INFO - Epoch(train) [51][550/586] lr: 5.000000e-04 eta: 7:02:56 time: 0.284657 data_time: 0.027546 memory: 11131 loss_kpt: 0.000623 acc_pose: 0.758133 loss: 0.000623 2022/10/27 14:41:37 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:41:52 - mmengine - INFO - Epoch(train) [52][50/586] lr: 5.000000e-04 eta: 7:02:07 time: 0.303321 data_time: 0.041552 memory: 11131 loss_kpt: 0.000638 acc_pose: 0.773655 loss: 0.000638 2022/10/27 14:42:06 - mmengine - INFO - Epoch(train) [52][100/586] lr: 5.000000e-04 eta: 7:01:55 time: 0.280782 data_time: 0.029882 memory: 11131 loss_kpt: 0.000634 acc_pose: 0.801626 loss: 0.000634 2022/10/27 14:42:10 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:42:20 - mmengine - INFO - Epoch(train) [52][150/586] lr: 5.000000e-04 eta: 7:01:43 time: 0.286088 data_time: 0.031513 memory: 11131 loss_kpt: 0.000632 acc_pose: 0.825925 loss: 0.000632 2022/10/27 14:42:35 - mmengine - INFO - Epoch(train) [52][200/586] lr: 5.000000e-04 eta: 7:01:33 time: 0.290723 data_time: 0.030174 memory: 11131 loss_kpt: 0.000626 acc_pose: 0.776855 loss: 0.000626 2022/10/27 14:42:49 - mmengine - INFO - Epoch(train) [52][250/586] lr: 5.000000e-04 eta: 7:01:21 time: 0.285580 data_time: 0.028145 memory: 11131 loss_kpt: 0.000638 acc_pose: 0.822136 loss: 0.000638 2022/10/27 14:43:04 - mmengine - INFO - Epoch(train) [52][300/586] lr: 5.000000e-04 eta: 7:01:10 time: 0.290223 data_time: 0.027631 memory: 11131 loss_kpt: 0.000651 acc_pose: 0.806861 loss: 0.000651 2022/10/27 14:43:18 - mmengine - INFO - Epoch(train) [52][350/586] lr: 5.000000e-04 eta: 7:00:59 time: 0.283566 data_time: 0.032425 memory: 11131 loss_kpt: 0.000630 acc_pose: 0.761875 loss: 0.000630 2022/10/27 14:43:33 - mmengine - INFO - Epoch(train) [52][400/586] lr: 5.000000e-04 eta: 7:00:48 time: 0.293304 data_time: 0.032495 memory: 11131 loss_kpt: 0.000627 acc_pose: 0.812954 loss: 0.000627 2022/10/27 14:43:47 - mmengine - INFO - Epoch(train) [52][450/586] lr: 5.000000e-04 eta: 7:00:37 time: 0.287568 data_time: 0.029960 memory: 11131 loss_kpt: 0.000649 acc_pose: 0.800328 loss: 0.000649 2022/10/27 14:44:01 - mmengine - INFO - Epoch(train) [52][500/586] lr: 5.000000e-04 eta: 7:00:25 time: 0.285568 data_time: 0.027990 memory: 11131 loss_kpt: 0.000626 acc_pose: 0.767582 loss: 0.000626 2022/10/27 14:44:16 - mmengine - INFO - Epoch(train) [52][550/586] lr: 5.000000e-04 eta: 7:00:15 time: 0.292005 data_time: 0.029275 memory: 11131 loss_kpt: 0.000630 acc_pose: 0.819605 loss: 0.000630 2022/10/27 14:44:26 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:44:41 - mmengine - INFO - Epoch(train) [53][50/586] lr: 5.000000e-04 eta: 6:59:26 time: 0.302576 data_time: 0.043195 memory: 11131 loss_kpt: 0.000626 acc_pose: 0.804665 loss: 0.000626 2022/10/27 14:44:55 - mmengine - INFO - Epoch(train) [53][100/586] lr: 5.000000e-04 eta: 6:59:15 time: 0.285449 data_time: 0.027805 memory: 11131 loss_kpt: 0.000619 acc_pose: 0.851137 loss: 0.000619 2022/10/27 14:45:10 - mmengine - INFO - Epoch(train) [53][150/586] lr: 5.000000e-04 eta: 6:59:03 time: 0.285976 data_time: 0.027646 memory: 11131 loss_kpt: 0.000658 acc_pose: 0.771294 loss: 0.000658 2022/10/27 14:45:24 - mmengine - INFO - Epoch(train) [53][200/586] lr: 5.000000e-04 eta: 6:58:52 time: 0.288768 data_time: 0.027329 memory: 11131 loss_kpt: 0.000631 acc_pose: 0.842333 loss: 0.000631 2022/10/27 14:45:38 - mmengine - INFO - Epoch(train) [53][250/586] lr: 5.000000e-04 eta: 6:58:41 time: 0.287839 data_time: 0.031628 memory: 11131 loss_kpt: 0.000644 acc_pose: 0.788841 loss: 0.000644 2022/10/27 14:45:53 - mmengine - INFO - Epoch(train) [53][300/586] lr: 5.000000e-04 eta: 6:58:30 time: 0.288168 data_time: 0.029622 memory: 11131 loss_kpt: 0.000650 acc_pose: 0.795041 loss: 0.000650 2022/10/27 14:46:07 - mmengine - INFO - Epoch(train) [53][350/586] lr: 5.000000e-04 eta: 6:58:18 time: 0.287203 data_time: 0.026540 memory: 11131 loss_kpt: 0.000641 acc_pose: 0.829378 loss: 0.000641 2022/10/27 14:46:22 - mmengine - INFO - Epoch(train) [53][400/586] lr: 5.000000e-04 eta: 6:58:07 time: 0.289282 data_time: 0.030577 memory: 11131 loss_kpt: 0.000635 acc_pose: 0.846691 loss: 0.000635 2022/10/27 14:46:36 - mmengine - INFO - Epoch(train) [53][450/586] lr: 5.000000e-04 eta: 6:57:56 time: 0.285310 data_time: 0.029378 memory: 11131 loss_kpt: 0.000624 acc_pose: 0.772622 loss: 0.000624 2022/10/27 14:46:51 - mmengine - INFO - Epoch(train) [53][500/586] lr: 5.000000e-04 eta: 6:57:45 time: 0.290601 data_time: 0.033008 memory: 11131 loss_kpt: 0.000629 acc_pose: 0.835466 loss: 0.000629 2022/10/27 14:46:59 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:47:05 - mmengine - INFO - Epoch(train) [53][550/586] lr: 5.000000e-04 eta: 6:57:33 time: 0.284766 data_time: 0.027218 memory: 11131 loss_kpt: 0.000654 acc_pose: 0.780611 loss: 0.000654 2022/10/27 14:47:15 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:47:30 - mmengine - INFO - Epoch(train) [54][50/586] lr: 5.000000e-04 eta: 6:56:45 time: 0.302807 data_time: 0.037599 memory: 11131 loss_kpt: 0.000640 acc_pose: 0.830660 loss: 0.000640 2022/10/27 14:47:45 - mmengine - INFO - Epoch(train) [54][100/586] lr: 5.000000e-04 eta: 6:56:34 time: 0.285004 data_time: 0.029886 memory: 11131 loss_kpt: 0.000632 acc_pose: 0.784031 loss: 0.000632 2022/10/27 14:47:59 - mmengine - INFO - Epoch(train) [54][150/586] lr: 5.000000e-04 eta: 6:56:22 time: 0.287323 data_time: 0.027384 memory: 11131 loss_kpt: 0.000612 acc_pose: 0.877075 loss: 0.000612 2022/10/27 14:48:13 - mmengine - INFO - Epoch(train) [54][200/586] lr: 5.000000e-04 eta: 6:56:10 time: 0.283583 data_time: 0.029819 memory: 11131 loss_kpt: 0.000621 acc_pose: 0.759574 loss: 0.000621 2022/10/27 14:48:28 - mmengine - INFO - Epoch(train) [54][250/586] lr: 5.000000e-04 eta: 6:55:59 time: 0.290930 data_time: 0.033023 memory: 11131 loss_kpt: 0.000648 acc_pose: 0.913861 loss: 0.000648 2022/10/27 14:48:42 - mmengine - INFO - Epoch(train) [54][300/586] lr: 5.000000e-04 eta: 6:55:48 time: 0.288592 data_time: 0.027840 memory: 11131 loss_kpt: 0.000635 acc_pose: 0.879016 loss: 0.000635 2022/10/27 14:48:56 - mmengine - INFO - Epoch(train) [54][350/586] lr: 5.000000e-04 eta: 6:55:36 time: 0.283525 data_time: 0.029180 memory: 11131 loss_kpt: 0.000623 acc_pose: 0.817181 loss: 0.000623 2022/10/27 14:49:11 - mmengine - INFO - Epoch(train) [54][400/586] lr: 5.000000e-04 eta: 6:55:26 time: 0.294107 data_time: 0.031899 memory: 11131 loss_kpt: 0.000625 acc_pose: 0.906572 loss: 0.000625 2022/10/27 14:49:25 - mmengine - INFO - Epoch(train) [54][450/586] lr: 5.000000e-04 eta: 6:55:15 time: 0.290369 data_time: 0.027531 memory: 11131 loss_kpt: 0.000623 acc_pose: 0.855198 loss: 0.000623 2022/10/27 14:49:40 - mmengine - INFO - Epoch(train) [54][500/586] lr: 5.000000e-04 eta: 6:55:03 time: 0.284167 data_time: 0.028930 memory: 11131 loss_kpt: 0.000633 acc_pose: 0.815876 loss: 0.000633 2022/10/27 14:49:54 - mmengine - INFO - Epoch(train) [54][550/586] lr: 5.000000e-04 eta: 6:54:52 time: 0.288507 data_time: 0.028064 memory: 11131 loss_kpt: 0.000647 acc_pose: 0.821608 loss: 0.000647 2022/10/27 14:50:04 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:50:19 - mmengine - INFO - Epoch(train) [55][50/586] lr: 5.000000e-04 eta: 6:54:05 time: 0.302541 data_time: 0.040086 memory: 11131 loss_kpt: 0.000619 acc_pose: 0.819504 loss: 0.000619 2022/10/27 14:50:34 - mmengine - INFO - Epoch(train) [55][100/586] lr: 5.000000e-04 eta: 6:53:53 time: 0.288890 data_time: 0.032813 memory: 11131 loss_kpt: 0.000634 acc_pose: 0.852953 loss: 0.000634 2022/10/27 14:50:48 - mmengine - INFO - Epoch(train) [55][150/586] lr: 5.000000e-04 eta: 6:53:42 time: 0.287496 data_time: 0.028376 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.832450 loss: 0.000607 2022/10/27 14:51:02 - mmengine - INFO - Epoch(train) [55][200/586] lr: 5.000000e-04 eta: 6:53:30 time: 0.285582 data_time: 0.029832 memory: 11131 loss_kpt: 0.000614 acc_pose: 0.798969 loss: 0.000614 2022/10/27 14:51:16 - mmengine - INFO - Epoch(train) [55][250/586] lr: 5.000000e-04 eta: 6:53:18 time: 0.281453 data_time: 0.028840 memory: 11131 loss_kpt: 0.000636 acc_pose: 0.838754 loss: 0.000636 2022/10/27 14:51:31 - mmengine - INFO - Epoch(train) [55][300/586] lr: 5.000000e-04 eta: 6:53:07 time: 0.291948 data_time: 0.031940 memory: 11131 loss_kpt: 0.000638 acc_pose: 0.833528 loss: 0.000638 2022/10/27 14:51:45 - mmengine - INFO - Epoch(train) [55][350/586] lr: 5.000000e-04 eta: 6:52:56 time: 0.287621 data_time: 0.030350 memory: 11131 loss_kpt: 0.000609 acc_pose: 0.847538 loss: 0.000609 2022/10/27 14:51:47 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:52:00 - mmengine - INFO - Epoch(train) [55][400/586] lr: 5.000000e-04 eta: 6:52:45 time: 0.287933 data_time: 0.026961 memory: 11131 loss_kpt: 0.000632 acc_pose: 0.800235 loss: 0.000632 2022/10/27 14:52:14 - mmengine - INFO - Epoch(train) [55][450/586] lr: 5.000000e-04 eta: 6:52:33 time: 0.285323 data_time: 0.028116 memory: 11131 loss_kpt: 0.000630 acc_pose: 0.885358 loss: 0.000630 2022/10/27 14:52:28 - mmengine - INFO - Epoch(train) [55][500/586] lr: 5.000000e-04 eta: 6:52:21 time: 0.285371 data_time: 0.029661 memory: 11131 loss_kpt: 0.000652 acc_pose: 0.821387 loss: 0.000652 2022/10/27 14:52:43 - mmengine - INFO - Epoch(train) [55][550/586] lr: 5.000000e-04 eta: 6:52:10 time: 0.286528 data_time: 0.027798 memory: 11131 loss_kpt: 0.000633 acc_pose: 0.835047 loss: 0.000633 2022/10/27 14:52:53 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:53:08 - mmengine - INFO - Epoch(train) [56][50/586] lr: 5.000000e-04 eta: 6:51:22 time: 0.296849 data_time: 0.039230 memory: 11131 loss_kpt: 0.000629 acc_pose: 0.793417 loss: 0.000629 2022/10/27 14:53:22 - mmengine - INFO - Epoch(train) [56][100/586] lr: 5.000000e-04 eta: 6:51:11 time: 0.285719 data_time: 0.028038 memory: 11131 loss_kpt: 0.000612 acc_pose: 0.792421 loss: 0.000612 2022/10/27 14:53:36 - mmengine - INFO - Epoch(train) [56][150/586] lr: 5.000000e-04 eta: 6:50:59 time: 0.284649 data_time: 0.032952 memory: 11131 loss_kpt: 0.000631 acc_pose: 0.795549 loss: 0.000631 2022/10/27 14:53:51 - mmengine - INFO - Epoch(train) [56][200/586] lr: 5.000000e-04 eta: 6:50:47 time: 0.286540 data_time: 0.029688 memory: 11131 loss_kpt: 0.000624 acc_pose: 0.769818 loss: 0.000624 2022/10/27 14:54:05 - mmengine - INFO - Epoch(train) [56][250/586] lr: 5.000000e-04 eta: 6:50:36 time: 0.287838 data_time: 0.029382 memory: 11131 loss_kpt: 0.000622 acc_pose: 0.897155 loss: 0.000622 2022/10/27 14:54:19 - mmengine - INFO - Epoch(train) [56][300/586] lr: 5.000000e-04 eta: 6:50:24 time: 0.287944 data_time: 0.028635 memory: 11131 loss_kpt: 0.000626 acc_pose: 0.847264 loss: 0.000626 2022/10/27 14:54:34 - mmengine - INFO - Epoch(train) [56][350/586] lr: 5.000000e-04 eta: 6:50:13 time: 0.286099 data_time: 0.027431 memory: 11131 loss_kpt: 0.000630 acc_pose: 0.775442 loss: 0.000630 2022/10/27 14:54:48 - mmengine - INFO - Epoch(train) [56][400/586] lr: 5.000000e-04 eta: 6:50:02 time: 0.290082 data_time: 0.035164 memory: 11131 loss_kpt: 0.000631 acc_pose: 0.828127 loss: 0.000631 2022/10/27 14:55:03 - mmengine - INFO - Epoch(train) [56][450/586] lr: 5.000000e-04 eta: 6:49:50 time: 0.285423 data_time: 0.027732 memory: 11131 loss_kpt: 0.000632 acc_pose: 0.844353 loss: 0.000632 2022/10/27 14:55:17 - mmengine - INFO - Epoch(train) [56][500/586] lr: 5.000000e-04 eta: 6:49:38 time: 0.287834 data_time: 0.028427 memory: 11131 loss_kpt: 0.000643 acc_pose: 0.834597 loss: 0.000643 2022/10/27 14:55:32 - mmengine - INFO - Epoch(train) [56][550/586] lr: 5.000000e-04 eta: 6:49:28 time: 0.293472 data_time: 0.027172 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.806001 loss: 0.000602 2022/10/27 14:55:42 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:55:57 - mmengine - INFO - Epoch(train) [57][50/586] lr: 5.000000e-04 eta: 6:48:41 time: 0.299783 data_time: 0.042001 memory: 11131 loss_kpt: 0.000642 acc_pose: 0.848765 loss: 0.000642 2022/10/27 14:56:11 - mmengine - INFO - Epoch(train) [57][100/586] lr: 5.000000e-04 eta: 6:48:29 time: 0.283815 data_time: 0.029447 memory: 11131 loss_kpt: 0.000606 acc_pose: 0.854472 loss: 0.000606 2022/10/27 14:56:25 - mmengine - INFO - Epoch(train) [57][150/586] lr: 5.000000e-04 eta: 6:48:18 time: 0.289820 data_time: 0.027259 memory: 11131 loss_kpt: 0.000621 acc_pose: 0.803974 loss: 0.000621 2022/10/27 14:56:35 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:56:40 - mmengine - INFO - Epoch(train) [57][200/586] lr: 5.000000e-04 eta: 6:48:07 time: 0.286903 data_time: 0.029926 memory: 11131 loss_kpt: 0.000626 acc_pose: 0.838660 loss: 0.000626 2022/10/27 14:56:54 - mmengine - INFO - Epoch(train) [57][250/586] lr: 5.000000e-04 eta: 6:47:55 time: 0.283138 data_time: 0.030737 memory: 11131 loss_kpt: 0.000605 acc_pose: 0.899605 loss: 0.000605 2022/10/27 14:57:08 - mmengine - INFO - Epoch(train) [57][300/586] lr: 5.000000e-04 eta: 6:47:43 time: 0.289604 data_time: 0.027523 memory: 11131 loss_kpt: 0.000598 acc_pose: 0.816180 loss: 0.000598 2022/10/27 14:57:23 - mmengine - INFO - Epoch(train) [57][350/586] lr: 5.000000e-04 eta: 6:47:32 time: 0.288059 data_time: 0.028092 memory: 11131 loss_kpt: 0.000616 acc_pose: 0.869101 loss: 0.000616 2022/10/27 14:57:37 - mmengine - INFO - Epoch(train) [57][400/586] lr: 5.000000e-04 eta: 6:47:21 time: 0.288374 data_time: 0.032918 memory: 11131 loss_kpt: 0.000621 acc_pose: 0.861564 loss: 0.000621 2022/10/27 14:57:52 - mmengine - INFO - Epoch(train) [57][450/586] lr: 5.000000e-04 eta: 6:47:09 time: 0.287751 data_time: 0.028590 memory: 11131 loss_kpt: 0.000622 acc_pose: 0.807445 loss: 0.000622 2022/10/27 14:58:06 - mmengine - INFO - Epoch(train) [57][500/586] lr: 5.000000e-04 eta: 6:46:57 time: 0.284792 data_time: 0.033945 memory: 11131 loss_kpt: 0.000636 acc_pose: 0.819469 loss: 0.000636 2022/10/27 14:58:20 - mmengine - INFO - Epoch(train) [57][550/586] lr: 5.000000e-04 eta: 6:46:46 time: 0.291201 data_time: 0.030641 memory: 11131 loss_kpt: 0.000614 acc_pose: 0.856547 loss: 0.000614 2022/10/27 14:58:31 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 14:58:46 - mmengine - INFO - Epoch(train) [58][50/586] lr: 5.000000e-04 eta: 6:46:00 time: 0.301075 data_time: 0.036046 memory: 11131 loss_kpt: 0.000608 acc_pose: 0.844508 loss: 0.000608 2022/10/27 14:59:00 - mmengine - INFO - Epoch(train) [58][100/586] lr: 5.000000e-04 eta: 6:45:48 time: 0.282600 data_time: 0.026849 memory: 11131 loss_kpt: 0.000611 acc_pose: 0.799894 loss: 0.000611 2022/10/27 14:59:14 - mmengine - INFO - Epoch(train) [58][150/586] lr: 5.000000e-04 eta: 6:45:37 time: 0.288306 data_time: 0.033379 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.825508 loss: 0.000600 2022/10/27 14:59:29 - mmengine - INFO - Epoch(train) [58][200/586] lr: 5.000000e-04 eta: 6:45:25 time: 0.287796 data_time: 0.031674 memory: 11131 loss_kpt: 0.000597 acc_pose: 0.812970 loss: 0.000597 2022/10/27 14:59:43 - mmengine - INFO - Epoch(train) [58][250/586] lr: 5.000000e-04 eta: 6:45:14 time: 0.288283 data_time: 0.027669 memory: 11131 loss_kpt: 0.000645 acc_pose: 0.783299 loss: 0.000645 2022/10/27 14:59:57 - mmengine - INFO - Epoch(train) [58][300/586] lr: 5.000000e-04 eta: 6:45:02 time: 0.287586 data_time: 0.031531 memory: 11131 loss_kpt: 0.000624 acc_pose: 0.741560 loss: 0.000624 2022/10/27 15:00:12 - mmengine - INFO - Epoch(train) [58][350/586] lr: 5.000000e-04 eta: 6:44:51 time: 0.285902 data_time: 0.028924 memory: 11131 loss_kpt: 0.000639 acc_pose: 0.799358 loss: 0.000639 2022/10/27 15:00:26 - mmengine - INFO - Epoch(train) [58][400/586] lr: 5.000000e-04 eta: 6:44:39 time: 0.286436 data_time: 0.030468 memory: 11131 loss_kpt: 0.000595 acc_pose: 0.786614 loss: 0.000595 2022/10/27 15:00:40 - mmengine - INFO - Epoch(train) [58][450/586] lr: 5.000000e-04 eta: 6:44:27 time: 0.286963 data_time: 0.026647 memory: 11131 loss_kpt: 0.000616 acc_pose: 0.830700 loss: 0.000616 2022/10/27 15:00:55 - mmengine - INFO - Epoch(train) [58][500/586] lr: 5.000000e-04 eta: 6:44:16 time: 0.287699 data_time: 0.027575 memory: 11131 loss_kpt: 0.000622 acc_pose: 0.800567 loss: 0.000622 2022/10/27 15:01:09 - mmengine - INFO - Epoch(train) [58][550/586] lr: 5.000000e-04 eta: 6:44:04 time: 0.289109 data_time: 0.029596 memory: 11131 loss_kpt: 0.000627 acc_pose: 0.910347 loss: 0.000627 2022/10/27 15:01:19 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:01:23 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:01:34 - mmengine - INFO - Epoch(train) [59][50/586] lr: 5.000000e-04 eta: 6:43:19 time: 0.296090 data_time: 0.038142 memory: 11131 loss_kpt: 0.000622 acc_pose: 0.814042 loss: 0.000622 2022/10/27 15:01:48 - mmengine - INFO - Epoch(train) [59][100/586] lr: 5.000000e-04 eta: 6:43:07 time: 0.286577 data_time: 0.028626 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.864085 loss: 0.000600 2022/10/27 15:02:03 - mmengine - INFO - Epoch(train) [59][150/586] lr: 5.000000e-04 eta: 6:42:55 time: 0.287167 data_time: 0.026673 memory: 11131 loss_kpt: 0.000644 acc_pose: 0.855183 loss: 0.000644 2022/10/27 15:02:17 - mmengine - INFO - Epoch(train) [59][200/586] lr: 5.000000e-04 eta: 6:42:44 time: 0.290485 data_time: 0.030516 memory: 11131 loss_kpt: 0.000630 acc_pose: 0.859793 loss: 0.000630 2022/10/27 15:02:32 - mmengine - INFO - Epoch(train) [59][250/586] lr: 5.000000e-04 eta: 6:42:32 time: 0.283519 data_time: 0.028028 memory: 11131 loss_kpt: 0.000630 acc_pose: 0.747931 loss: 0.000630 2022/10/27 15:02:46 - mmengine - INFO - Epoch(train) [59][300/586] lr: 5.000000e-04 eta: 6:42:20 time: 0.287083 data_time: 0.031889 memory: 11131 loss_kpt: 0.000624 acc_pose: 0.897241 loss: 0.000624 2022/10/27 15:03:00 - mmengine - INFO - Epoch(train) [59][350/586] lr: 5.000000e-04 eta: 6:42:08 time: 0.283603 data_time: 0.026826 memory: 11131 loss_kpt: 0.000626 acc_pose: 0.789157 loss: 0.000626 2022/10/27 15:03:15 - mmengine - INFO - Epoch(train) [59][400/586] lr: 5.000000e-04 eta: 6:41:57 time: 0.290992 data_time: 0.027654 memory: 11131 loss_kpt: 0.000606 acc_pose: 0.868134 loss: 0.000606 2022/10/27 15:03:29 - mmengine - INFO - Epoch(train) [59][450/586] lr: 5.000000e-04 eta: 6:41:45 time: 0.283527 data_time: 0.026500 memory: 11131 loss_kpt: 0.000611 acc_pose: 0.801451 loss: 0.000611 2022/10/27 15:03:43 - mmengine - INFO - Epoch(train) [59][500/586] lr: 5.000000e-04 eta: 6:41:34 time: 0.289567 data_time: 0.031763 memory: 11131 loss_kpt: 0.000629 acc_pose: 0.836850 loss: 0.000629 2022/10/27 15:03:58 - mmengine - INFO - Epoch(train) [59][550/586] lr: 5.000000e-04 eta: 6:41:22 time: 0.286664 data_time: 0.028902 memory: 11131 loss_kpt: 0.000631 acc_pose: 0.854481 loss: 0.000631 2022/10/27 15:04:08 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:04:23 - mmengine - INFO - Epoch(train) [60][50/586] lr: 5.000000e-04 eta: 6:40:38 time: 0.307721 data_time: 0.038790 memory: 11131 loss_kpt: 0.000626 acc_pose: 0.802621 loss: 0.000626 2022/10/27 15:04:37 - mmengine - INFO - Epoch(train) [60][100/586] lr: 5.000000e-04 eta: 6:40:26 time: 0.285164 data_time: 0.029886 memory: 11131 loss_kpt: 0.000608 acc_pose: 0.863042 loss: 0.000608 2022/10/27 15:04:52 - mmengine - INFO - Epoch(train) [60][150/586] lr: 5.000000e-04 eta: 6:40:15 time: 0.290670 data_time: 0.035396 memory: 11131 loss_kpt: 0.000609 acc_pose: 0.881036 loss: 0.000609 2022/10/27 15:05:06 - mmengine - INFO - Epoch(train) [60][200/586] lr: 5.000000e-04 eta: 6:40:03 time: 0.286490 data_time: 0.029526 memory: 11131 loss_kpt: 0.000627 acc_pose: 0.805306 loss: 0.000627 2022/10/27 15:05:21 - mmengine - INFO - Epoch(train) [60][250/586] lr: 5.000000e-04 eta: 6:39:52 time: 0.286739 data_time: 0.027151 memory: 11131 loss_kpt: 0.000619 acc_pose: 0.837920 loss: 0.000619 2022/10/27 15:05:35 - mmengine - INFO - Epoch(train) [60][300/586] lr: 5.000000e-04 eta: 6:39:40 time: 0.288959 data_time: 0.026726 memory: 11131 loss_kpt: 0.000626 acc_pose: 0.723214 loss: 0.000626 2022/10/27 15:05:49 - mmengine - INFO - Epoch(train) [60][350/586] lr: 5.000000e-04 eta: 6:39:28 time: 0.284814 data_time: 0.031122 memory: 11131 loss_kpt: 0.000613 acc_pose: 0.847431 loss: 0.000613 2022/10/27 15:06:04 - mmengine - INFO - Epoch(train) [60][400/586] lr: 5.000000e-04 eta: 6:39:17 time: 0.288982 data_time: 0.033491 memory: 11131 loss_kpt: 0.000612 acc_pose: 0.895284 loss: 0.000612 2022/10/27 15:06:11 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:06:18 - mmengine - INFO - Epoch(train) [60][450/586] lr: 5.000000e-04 eta: 6:39:05 time: 0.285177 data_time: 0.027485 memory: 11131 loss_kpt: 0.000606 acc_pose: 0.783750 loss: 0.000606 2022/10/27 15:06:33 - mmengine - INFO - Epoch(train) [60][500/586] lr: 5.000000e-04 eta: 6:38:53 time: 0.289272 data_time: 0.029209 memory: 11131 loss_kpt: 0.000609 acc_pose: 0.922210 loss: 0.000609 2022/10/27 15:06:47 - mmengine - INFO - Epoch(train) [60][550/586] lr: 5.000000e-04 eta: 6:38:42 time: 0.291011 data_time: 0.028609 memory: 11131 loss_kpt: 0.000618 acc_pose: 0.853824 loss: 0.000618 2022/10/27 15:06:57 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:06:57 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/10/27 15:07:08 - mmengine - INFO - Epoch(val) [60][50/407] eta: 0:00:50 time: 0.140290 data_time: 0.019915 memory: 11131 2022/10/27 15:07:16 - mmengine - INFO - Epoch(val) [60][100/407] eta: 0:00:50 time: 0.165778 data_time: 0.044889 memory: 1836 2022/10/27 15:07:23 - mmengine - INFO - Epoch(val) [60][150/407] eta: 0:00:34 time: 0.132706 data_time: 0.013374 memory: 1836 2022/10/27 15:07:30 - mmengine - INFO - Epoch(val) [60][200/407] eta: 0:00:27 time: 0.134939 data_time: 0.012807 memory: 1836 2022/10/27 15:07:36 - mmengine - INFO - Epoch(val) [60][250/407] eta: 0:00:21 time: 0.135417 data_time: 0.017403 memory: 1836 2022/10/27 15:07:43 - mmengine - INFO - Epoch(val) [60][300/407] eta: 0:00:14 time: 0.132307 data_time: 0.014342 memory: 1836 2022/10/27 15:07:50 - mmengine - INFO - Epoch(val) [60][350/407] eta: 0:00:07 time: 0.139941 data_time: 0.020885 memory: 1836 2022/10/27 15:07:56 - mmengine - INFO - Epoch(val) [60][400/407] eta: 0:00:00 time: 0.128645 data_time: 0.012375 memory: 1836 2022/10/27 15:08:43 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 15:09:01 - mmengine - INFO - Epoch(val) [60][407/407] coco/AP: 0.729140 coco/AP .5: 0.896049 coco/AP .75: 0.800697 coco/AP (M): 0.685498 coco/AP (L): 0.801519 coco/AR: 0.780384 coco/AR .5: 0.932305 coco/AR .75: 0.846033 coco/AR (M): 0.733789 coco/AR (L): 0.846674 2022/10/27 15:09:01 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_50.pth is removed 2022/10/27 15:09:03 - mmengine - INFO - The best checkpoint with 0.7291 coco/AP at 60 epoch is saved to best_coco/AP_epoch_60.pth. 2022/10/27 15:09:18 - mmengine - INFO - Epoch(train) [61][50/586] lr: 5.000000e-04 eta: 6:37:56 time: 0.289905 data_time: 0.036773 memory: 11131 loss_kpt: 0.000615 acc_pose: 0.880762 loss: 0.000615 2022/10/27 15:09:32 - mmengine - INFO - Epoch(train) [61][100/586] lr: 5.000000e-04 eta: 6:37:45 time: 0.287310 data_time: 0.028626 memory: 11131 loss_kpt: 0.000610 acc_pose: 0.798311 loss: 0.000610 2022/10/27 15:09:46 - mmengine - INFO - Epoch(train) [61][150/586] lr: 5.000000e-04 eta: 6:37:33 time: 0.286304 data_time: 0.029380 memory: 11131 loss_kpt: 0.000611 acc_pose: 0.853025 loss: 0.000611 2022/10/27 15:10:01 - mmengine - INFO - Epoch(train) [61][200/586] lr: 5.000000e-04 eta: 6:37:22 time: 0.290322 data_time: 0.032961 memory: 11131 loss_kpt: 0.000631 acc_pose: 0.837013 loss: 0.000631 2022/10/27 15:10:15 - mmengine - INFO - Epoch(train) [61][250/586] lr: 5.000000e-04 eta: 6:37:10 time: 0.284295 data_time: 0.027775 memory: 11131 loss_kpt: 0.000623 acc_pose: 0.821626 loss: 0.000623 2022/10/27 15:10:29 - mmengine - INFO - Epoch(train) [61][300/586] lr: 5.000000e-04 eta: 6:36:58 time: 0.288198 data_time: 0.031443 memory: 11131 loss_kpt: 0.000623 acc_pose: 0.774741 loss: 0.000623 2022/10/27 15:10:44 - mmengine - INFO - Epoch(train) [61][350/586] lr: 5.000000e-04 eta: 6:36:46 time: 0.282613 data_time: 0.027459 memory: 11131 loss_kpt: 0.000608 acc_pose: 0.917477 loss: 0.000608 2022/10/27 15:10:58 - mmengine - INFO - Epoch(train) [61][400/586] lr: 5.000000e-04 eta: 6:36:35 time: 0.294692 data_time: 0.029584 memory: 11131 loss_kpt: 0.000599 acc_pose: 0.896806 loss: 0.000599 2022/10/27 15:11:13 - mmengine - INFO - Epoch(train) [61][450/586] lr: 5.000000e-04 eta: 6:36:23 time: 0.286184 data_time: 0.030958 memory: 11131 loss_kpt: 0.000608 acc_pose: 0.845992 loss: 0.000608 2022/10/27 15:11:27 - mmengine - INFO - Epoch(train) [61][500/586] lr: 5.000000e-04 eta: 6:36:11 time: 0.283108 data_time: 0.028704 memory: 11131 loss_kpt: 0.000608 acc_pose: 0.830612 loss: 0.000608 2022/10/27 15:11:41 - mmengine - INFO - Epoch(train) [61][550/586] lr: 5.000000e-04 eta: 6:35:59 time: 0.286999 data_time: 0.026924 memory: 11131 loss_kpt: 0.000627 acc_pose: 0.754198 loss: 0.000627 2022/10/27 15:11:51 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:12:06 - mmengine - INFO - Epoch(train) [62][50/586] lr: 5.000000e-04 eta: 6:35:16 time: 0.302226 data_time: 0.034545 memory: 11131 loss_kpt: 0.000619 acc_pose: 0.887025 loss: 0.000619 2022/10/27 15:12:20 - mmengine - INFO - Epoch(train) [62][100/586] lr: 5.000000e-04 eta: 6:35:03 time: 0.283449 data_time: 0.031632 memory: 11131 loss_kpt: 0.000628 acc_pose: 0.775886 loss: 0.000628 2022/10/27 15:12:35 - mmengine - INFO - Epoch(train) [62][150/586] lr: 5.000000e-04 eta: 6:34:52 time: 0.285581 data_time: 0.026685 memory: 11131 loss_kpt: 0.000616 acc_pose: 0.868640 loss: 0.000616 2022/10/27 15:12:49 - mmengine - INFO - Epoch(train) [62][200/586] lr: 5.000000e-04 eta: 6:34:40 time: 0.290002 data_time: 0.030846 memory: 11131 loss_kpt: 0.000604 acc_pose: 0.888338 loss: 0.000604 2022/10/27 15:13:04 - mmengine - INFO - Epoch(train) [62][250/586] lr: 5.000000e-04 eta: 6:34:28 time: 0.286407 data_time: 0.030707 memory: 11131 loss_kpt: 0.000617 acc_pose: 0.811934 loss: 0.000617 2022/10/27 15:13:05 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:13:18 - mmengine - INFO - Epoch(train) [62][300/586] lr: 5.000000e-04 eta: 6:34:17 time: 0.292539 data_time: 0.028270 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.732759 loss: 0.000607 2022/10/27 15:13:33 - mmengine - INFO - Epoch(train) [62][350/586] lr: 5.000000e-04 eta: 6:34:06 time: 0.288256 data_time: 0.028721 memory: 11131 loss_kpt: 0.000628 acc_pose: 0.902077 loss: 0.000628 2022/10/27 15:13:47 - mmengine - INFO - Epoch(train) [62][400/586] lr: 5.000000e-04 eta: 6:33:54 time: 0.292061 data_time: 0.030921 memory: 11131 loss_kpt: 0.000621 acc_pose: 0.825235 loss: 0.000621 2022/10/27 15:14:02 - mmengine - INFO - Epoch(train) [62][450/586] lr: 5.000000e-04 eta: 6:33:43 time: 0.286941 data_time: 0.028548 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.714191 loss: 0.000607 2022/10/27 15:14:16 - mmengine - INFO - Epoch(train) [62][500/586] lr: 5.000000e-04 eta: 6:33:31 time: 0.286161 data_time: 0.028278 memory: 11131 loss_kpt: 0.000620 acc_pose: 0.908376 loss: 0.000620 2022/10/27 15:14:30 - mmengine - INFO - Epoch(train) [62][550/586] lr: 5.000000e-04 eta: 6:33:19 time: 0.288694 data_time: 0.032675 memory: 11131 loss_kpt: 0.000631 acc_pose: 0.829243 loss: 0.000631 2022/10/27 15:14:40 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:14:55 - mmengine - INFO - Epoch(train) [63][50/586] lr: 5.000000e-04 eta: 6:32:35 time: 0.294035 data_time: 0.039724 memory: 11131 loss_kpt: 0.000597 acc_pose: 0.836815 loss: 0.000597 2022/10/27 15:15:09 - mmengine - INFO - Epoch(train) [63][100/586] lr: 5.000000e-04 eta: 6:32:23 time: 0.283391 data_time: 0.027983 memory: 11131 loss_kpt: 0.000620 acc_pose: 0.809870 loss: 0.000620 2022/10/27 15:15:24 - mmengine - INFO - Epoch(train) [63][150/586] lr: 5.000000e-04 eta: 6:32:11 time: 0.286247 data_time: 0.028159 memory: 11131 loss_kpt: 0.000597 acc_pose: 0.783593 loss: 0.000597 2022/10/27 15:15:38 - mmengine - INFO - Epoch(train) [63][200/586] lr: 5.000000e-04 eta: 6:32:00 time: 0.291020 data_time: 0.033959 memory: 11131 loss_kpt: 0.000610 acc_pose: 0.881097 loss: 0.000610 2022/10/27 15:15:53 - mmengine - INFO - Epoch(train) [63][250/586] lr: 5.000000e-04 eta: 6:31:48 time: 0.290383 data_time: 0.028941 memory: 11131 loss_kpt: 0.000632 acc_pose: 0.834888 loss: 0.000632 2022/10/27 15:16:07 - mmengine - INFO - Epoch(train) [63][300/586] lr: 5.000000e-04 eta: 6:31:36 time: 0.284367 data_time: 0.027287 memory: 11131 loss_kpt: 0.000609 acc_pose: 0.833884 loss: 0.000609 2022/10/27 15:16:21 - mmengine - INFO - Epoch(train) [63][350/586] lr: 5.000000e-04 eta: 6:31:24 time: 0.284566 data_time: 0.028643 memory: 11131 loss_kpt: 0.000631 acc_pose: 0.821505 loss: 0.000631 2022/10/27 15:16:36 - mmengine - INFO - Epoch(train) [63][400/586] lr: 5.000000e-04 eta: 6:31:13 time: 0.294547 data_time: 0.027092 memory: 11131 loss_kpt: 0.000618 acc_pose: 0.795364 loss: 0.000618 2022/10/27 15:16:51 - mmengine - INFO - Epoch(train) [63][450/586] lr: 5.000000e-04 eta: 6:31:02 time: 0.293016 data_time: 0.029714 memory: 11131 loss_kpt: 0.000606 acc_pose: 0.791285 loss: 0.000606 2022/10/27 15:17:05 - mmengine - INFO - Epoch(train) [63][500/586] lr: 5.000000e-04 eta: 6:30:50 time: 0.284172 data_time: 0.027701 memory: 11131 loss_kpt: 0.000614 acc_pose: 0.802813 loss: 0.000614 2022/10/27 15:17:19 - mmengine - INFO - Epoch(train) [63][550/586] lr: 5.000000e-04 eta: 6:30:38 time: 0.286762 data_time: 0.029047 memory: 11131 loss_kpt: 0.000609 acc_pose: 0.861685 loss: 0.000609 2022/10/27 15:17:29 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:17:44 - mmengine - INFO - Epoch(train) [64][50/586] lr: 5.000000e-04 eta: 6:29:55 time: 0.301607 data_time: 0.041653 memory: 11131 loss_kpt: 0.000633 acc_pose: 0.834432 loss: 0.000633 2022/10/27 15:17:53 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:17:58 - mmengine - INFO - Epoch(train) [64][100/586] lr: 5.000000e-04 eta: 6:29:43 time: 0.285027 data_time: 0.030970 memory: 11131 loss_kpt: 0.000634 acc_pose: 0.848579 loss: 0.000634 2022/10/27 15:18:13 - mmengine - INFO - Epoch(train) [64][150/586] lr: 5.000000e-04 eta: 6:29:31 time: 0.284172 data_time: 0.028169 memory: 11131 loss_kpt: 0.000621 acc_pose: 0.846843 loss: 0.000621 2022/10/27 15:18:27 - mmengine - INFO - Epoch(train) [64][200/586] lr: 5.000000e-04 eta: 6:29:20 time: 0.289766 data_time: 0.030109 memory: 11131 loss_kpt: 0.000630 acc_pose: 0.776373 loss: 0.000630 2022/10/27 15:18:41 - mmengine - INFO - Epoch(train) [64][250/586] lr: 5.000000e-04 eta: 6:29:07 time: 0.283687 data_time: 0.028831 memory: 11131 loss_kpt: 0.000596 acc_pose: 0.820742 loss: 0.000596 2022/10/27 15:18:56 - mmengine - INFO - Epoch(train) [64][300/586] lr: 5.000000e-04 eta: 6:28:56 time: 0.295679 data_time: 0.037411 memory: 11131 loss_kpt: 0.000616 acc_pose: 0.751780 loss: 0.000616 2022/10/27 15:19:11 - mmengine - INFO - Epoch(train) [64][350/586] lr: 5.000000e-04 eta: 6:28:45 time: 0.291906 data_time: 0.028931 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.874823 loss: 0.000607 2022/10/27 15:19:25 - mmengine - INFO - Epoch(train) [64][400/586] lr: 5.000000e-04 eta: 6:28:34 time: 0.290624 data_time: 0.028917 memory: 11131 loss_kpt: 0.000599 acc_pose: 0.878893 loss: 0.000599 2022/10/27 15:19:40 - mmengine - INFO - Epoch(train) [64][450/586] lr: 5.000000e-04 eta: 6:28:22 time: 0.289837 data_time: 0.027671 memory: 11131 loss_kpt: 0.000610 acc_pose: 0.835799 loss: 0.000610 2022/10/27 15:19:54 - mmengine - INFO - Epoch(train) [64][500/586] lr: 5.000000e-04 eta: 6:28:10 time: 0.286121 data_time: 0.026525 memory: 11131 loss_kpt: 0.000623 acc_pose: 0.804817 loss: 0.000623 2022/10/27 15:20:09 - mmengine - INFO - Epoch(train) [64][550/586] lr: 5.000000e-04 eta: 6:27:59 time: 0.291376 data_time: 0.028119 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.801335 loss: 0.000600 2022/10/27 15:20:19 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:20:34 - mmengine - INFO - Epoch(train) [65][50/586] lr: 5.000000e-04 eta: 6:27:16 time: 0.293450 data_time: 0.040466 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.767229 loss: 0.000602 2022/10/27 15:20:48 - mmengine - INFO - Epoch(train) [65][100/586] lr: 5.000000e-04 eta: 6:27:04 time: 0.285365 data_time: 0.029889 memory: 11131 loss_kpt: 0.000615 acc_pose: 0.870405 loss: 0.000615 2022/10/27 15:21:02 - mmengine - INFO - Epoch(train) [65][150/586] lr: 5.000000e-04 eta: 6:26:52 time: 0.287526 data_time: 0.028954 memory: 11131 loss_kpt: 0.000617 acc_pose: 0.846261 loss: 0.000617 2022/10/27 15:21:17 - mmengine - INFO - Epoch(train) [65][200/586] lr: 5.000000e-04 eta: 6:26:40 time: 0.291375 data_time: 0.037420 memory: 11131 loss_kpt: 0.000628 acc_pose: 0.789464 loss: 0.000628 2022/10/27 15:21:31 - mmengine - INFO - Epoch(train) [65][250/586] lr: 5.000000e-04 eta: 6:26:29 time: 0.290288 data_time: 0.031150 memory: 11131 loss_kpt: 0.000631 acc_pose: 0.884610 loss: 0.000631 2022/10/27 15:21:46 - mmengine - INFO - Epoch(train) [65][300/586] lr: 5.000000e-04 eta: 6:26:17 time: 0.285508 data_time: 0.027086 memory: 11131 loss_kpt: 0.000617 acc_pose: 0.786322 loss: 0.000617 2022/10/27 15:22:00 - mmengine - INFO - Epoch(train) [65][350/586] lr: 5.000000e-04 eta: 6:26:05 time: 0.284836 data_time: 0.028291 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.868736 loss: 0.000607 2022/10/27 15:22:14 - mmengine - INFO - Epoch(train) [65][400/586] lr: 5.000000e-04 eta: 6:25:53 time: 0.290017 data_time: 0.027443 memory: 11131 loss_kpt: 0.000614 acc_pose: 0.789813 loss: 0.000614 2022/10/27 15:22:29 - mmengine - INFO - Epoch(train) [65][450/586] lr: 5.000000e-04 eta: 6:25:41 time: 0.287193 data_time: 0.029974 memory: 11131 loss_kpt: 0.000614 acc_pose: 0.822812 loss: 0.000614 2022/10/27 15:22:42 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:22:43 - mmengine - INFO - Epoch(train) [65][500/586] lr: 5.000000e-04 eta: 6:25:29 time: 0.285011 data_time: 0.029151 memory: 11131 loss_kpt: 0.000635 acc_pose: 0.776970 loss: 0.000635 2022/10/27 15:22:57 - mmengine - INFO - Epoch(train) [65][550/586] lr: 5.000000e-04 eta: 6:25:17 time: 0.285853 data_time: 0.027758 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.781989 loss: 0.000607 2022/10/27 15:23:07 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:23:22 - mmengine - INFO - Epoch(train) [66][50/586] lr: 5.000000e-04 eta: 6:24:35 time: 0.300023 data_time: 0.041077 memory: 11131 loss_kpt: 0.000612 acc_pose: 0.873878 loss: 0.000612 2022/10/27 15:23:37 - mmengine - INFO - Epoch(train) [66][100/586] lr: 5.000000e-04 eta: 6:24:24 time: 0.290587 data_time: 0.031513 memory: 11131 loss_kpt: 0.000613 acc_pose: 0.829323 loss: 0.000613 2022/10/27 15:23:51 - mmengine - INFO - Epoch(train) [66][150/586] lr: 5.000000e-04 eta: 6:24:12 time: 0.288256 data_time: 0.029252 memory: 11131 loss_kpt: 0.000612 acc_pose: 0.793483 loss: 0.000612 2022/10/27 15:24:05 - mmengine - INFO - Epoch(train) [66][200/586] lr: 5.000000e-04 eta: 6:23:59 time: 0.283371 data_time: 0.027289 memory: 11131 loss_kpt: 0.000611 acc_pose: 0.819988 loss: 0.000611 2022/10/27 15:24:20 - mmengine - INFO - Epoch(train) [66][250/586] lr: 5.000000e-04 eta: 6:23:48 time: 0.295086 data_time: 0.035396 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.826770 loss: 0.000600 2022/10/27 15:24:35 - mmengine - INFO - Epoch(train) [66][300/586] lr: 5.000000e-04 eta: 6:23:37 time: 0.291759 data_time: 0.031161 memory: 11131 loss_kpt: 0.000612 acc_pose: 0.770936 loss: 0.000612 2022/10/27 15:24:49 - mmengine - INFO - Epoch(train) [66][350/586] lr: 5.000000e-04 eta: 6:23:25 time: 0.287277 data_time: 0.028713 memory: 11131 loss_kpt: 0.000621 acc_pose: 0.786745 loss: 0.000621 2022/10/27 15:25:04 - mmengine - INFO - Epoch(train) [66][400/586] lr: 5.000000e-04 eta: 6:23:13 time: 0.287876 data_time: 0.028071 memory: 11131 loss_kpt: 0.000611 acc_pose: 0.861109 loss: 0.000611 2022/10/27 15:25:18 - mmengine - INFO - Epoch(train) [66][450/586] lr: 5.000000e-04 eta: 6:23:01 time: 0.286089 data_time: 0.029697 memory: 11131 loss_kpt: 0.000609 acc_pose: 0.829844 loss: 0.000609 2022/10/27 15:25:32 - mmengine - INFO - Epoch(train) [66][500/586] lr: 5.000000e-04 eta: 6:22:50 time: 0.288907 data_time: 0.028879 memory: 11131 loss_kpt: 0.000610 acc_pose: 0.799036 loss: 0.000610 2022/10/27 15:25:47 - mmengine - INFO - Epoch(train) [66][550/586] lr: 5.000000e-04 eta: 6:22:38 time: 0.291338 data_time: 0.029056 memory: 11131 loss_kpt: 0.000559 acc_pose: 0.835652 loss: 0.000559 2022/10/27 15:25:57 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:26:12 - mmengine - INFO - Epoch(train) [67][50/586] lr: 5.000000e-04 eta: 6:21:56 time: 0.300261 data_time: 0.038515 memory: 11131 loss_kpt: 0.000595 acc_pose: 0.830651 loss: 0.000595 2022/10/27 15:26:26 - mmengine - INFO - Epoch(train) [67][100/586] lr: 5.000000e-04 eta: 6:21:44 time: 0.281681 data_time: 0.027343 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.853540 loss: 0.000607 2022/10/27 15:26:40 - mmengine - INFO - Epoch(train) [67][150/586] lr: 5.000000e-04 eta: 6:21:32 time: 0.287949 data_time: 0.029787 memory: 11131 loss_kpt: 0.000628 acc_pose: 0.904691 loss: 0.000628 2022/10/27 15:26:55 - mmengine - INFO - Epoch(train) [67][200/586] lr: 5.000000e-04 eta: 6:21:21 time: 0.290917 data_time: 0.031910 memory: 11131 loss_kpt: 0.000594 acc_pose: 0.848054 loss: 0.000594 2022/10/27 15:27:09 - mmengine - INFO - Epoch(train) [67][250/586] lr: 5.000000e-04 eta: 6:21:08 time: 0.284491 data_time: 0.027685 memory: 11131 loss_kpt: 0.000623 acc_pose: 0.746918 loss: 0.000623 2022/10/27 15:27:24 - mmengine - INFO - Epoch(train) [67][300/586] lr: 5.000000e-04 eta: 6:20:57 time: 0.289775 data_time: 0.029768 memory: 11131 loss_kpt: 0.000595 acc_pose: 0.785468 loss: 0.000595 2022/10/27 15:27:31 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:27:38 - mmengine - INFO - Epoch(train) [67][350/586] lr: 5.000000e-04 eta: 6:20:45 time: 0.284529 data_time: 0.029595 memory: 11131 loss_kpt: 0.000617 acc_pose: 0.828336 loss: 0.000617 2022/10/27 15:27:53 - mmengine - INFO - Epoch(train) [67][400/586] lr: 5.000000e-04 eta: 6:20:33 time: 0.293519 data_time: 0.030370 memory: 11131 loss_kpt: 0.000603 acc_pose: 0.854491 loss: 0.000603 2022/10/27 15:28:07 - mmengine - INFO - Epoch(train) [67][450/586] lr: 5.000000e-04 eta: 6:20:21 time: 0.289172 data_time: 0.028448 memory: 11131 loss_kpt: 0.000615 acc_pose: 0.870972 loss: 0.000615 2022/10/27 15:28:21 - mmengine - INFO - Epoch(train) [67][500/586] lr: 5.000000e-04 eta: 6:20:09 time: 0.285625 data_time: 0.027996 memory: 11131 loss_kpt: 0.000617 acc_pose: 0.839771 loss: 0.000617 2022/10/27 15:28:36 - mmengine - INFO - Epoch(train) [67][550/586] lr: 5.000000e-04 eta: 6:19:57 time: 0.286118 data_time: 0.032068 memory: 11131 loss_kpt: 0.000614 acc_pose: 0.894072 loss: 0.000614 2022/10/27 15:28:46 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:29:01 - mmengine - INFO - Epoch(train) [68][50/586] lr: 5.000000e-04 eta: 6:19:16 time: 0.298640 data_time: 0.036547 memory: 11131 loss_kpt: 0.000612 acc_pose: 0.794090 loss: 0.000612 2022/10/27 15:29:15 - mmengine - INFO - Epoch(train) [68][100/586] lr: 5.000000e-04 eta: 6:19:04 time: 0.286104 data_time: 0.027843 memory: 11131 loss_kpt: 0.000635 acc_pose: 0.818537 loss: 0.000635 2022/10/27 15:29:29 - mmengine - INFO - Epoch(train) [68][150/586] lr: 5.000000e-04 eta: 6:18:52 time: 0.284304 data_time: 0.028836 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.799656 loss: 0.000586 2022/10/27 15:29:44 - mmengine - INFO - Epoch(train) [68][200/586] lr: 5.000000e-04 eta: 6:18:40 time: 0.286958 data_time: 0.028889 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.850343 loss: 0.000600 2022/10/27 15:29:58 - mmengine - INFO - Epoch(train) [68][250/586] lr: 5.000000e-04 eta: 6:18:28 time: 0.286328 data_time: 0.028568 memory: 11131 loss_kpt: 0.000594 acc_pose: 0.858711 loss: 0.000594 2022/10/27 15:30:13 - mmengine - INFO - Epoch(train) [68][300/586] lr: 5.000000e-04 eta: 6:18:16 time: 0.291154 data_time: 0.030898 memory: 11131 loss_kpt: 0.000608 acc_pose: 0.859610 loss: 0.000608 2022/10/27 15:30:27 - mmengine - INFO - Epoch(train) [68][350/586] lr: 5.000000e-04 eta: 6:18:04 time: 0.288511 data_time: 0.028030 memory: 11131 loss_kpt: 0.000629 acc_pose: 0.845919 loss: 0.000629 2022/10/27 15:30:41 - mmengine - INFO - Epoch(train) [68][400/586] lr: 5.000000e-04 eta: 6:17:52 time: 0.285027 data_time: 0.026659 memory: 11131 loss_kpt: 0.000596 acc_pose: 0.877496 loss: 0.000596 2022/10/27 15:30:56 - mmengine - INFO - Epoch(train) [68][450/586] lr: 5.000000e-04 eta: 6:17:40 time: 0.287188 data_time: 0.027378 memory: 11131 loss_kpt: 0.000619 acc_pose: 0.854842 loss: 0.000619 2022/10/27 15:31:10 - mmengine - INFO - Epoch(train) [68][500/586] lr: 5.000000e-04 eta: 6:17:28 time: 0.286169 data_time: 0.031639 memory: 11131 loss_kpt: 0.000606 acc_pose: 0.854104 loss: 0.000606 2022/10/27 15:31:24 - mmengine - INFO - Epoch(train) [68][550/586] lr: 5.000000e-04 eta: 6:17:16 time: 0.289946 data_time: 0.028042 memory: 11131 loss_kpt: 0.000620 acc_pose: 0.813358 loss: 0.000620 2022/10/27 15:31:35 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:31:50 - mmengine - INFO - Epoch(train) [69][50/586] lr: 5.000000e-04 eta: 6:16:36 time: 0.302272 data_time: 0.041922 memory: 11131 loss_kpt: 0.000617 acc_pose: 0.843670 loss: 0.000617 2022/10/27 15:32:04 - mmengine - INFO - Epoch(train) [69][100/586] lr: 5.000000e-04 eta: 6:16:23 time: 0.285598 data_time: 0.028164 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.885754 loss: 0.000590 2022/10/27 15:32:18 - mmengine - INFO - Epoch(train) [69][150/586] lr: 5.000000e-04 eta: 6:16:11 time: 0.285880 data_time: 0.030053 memory: 11131 loss_kpt: 0.000609 acc_pose: 0.795812 loss: 0.000609 2022/10/27 15:32:19 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:32:33 - mmengine - INFO - Epoch(train) [69][200/586] lr: 5.000000e-04 eta: 6:16:00 time: 0.290607 data_time: 0.033825 memory: 11131 loss_kpt: 0.000605 acc_pose: 0.801954 loss: 0.000605 2022/10/27 15:32:47 - mmengine - INFO - Epoch(train) [69][250/586] lr: 5.000000e-04 eta: 6:15:48 time: 0.287429 data_time: 0.028205 memory: 11131 loss_kpt: 0.000612 acc_pose: 0.875618 loss: 0.000612 2022/10/27 15:33:01 - mmengine - INFO - Epoch(train) [69][300/586] lr: 5.000000e-04 eta: 6:15:35 time: 0.284752 data_time: 0.027469 memory: 11131 loss_kpt: 0.000596 acc_pose: 0.788454 loss: 0.000596 2022/10/27 15:33:16 - mmengine - INFO - Epoch(train) [69][350/586] lr: 5.000000e-04 eta: 6:15:23 time: 0.286080 data_time: 0.031188 memory: 11131 loss_kpt: 0.000606 acc_pose: 0.857501 loss: 0.000606 2022/10/27 15:33:30 - mmengine - INFO - Epoch(train) [69][400/586] lr: 5.000000e-04 eta: 6:15:11 time: 0.287501 data_time: 0.028862 memory: 11131 loss_kpt: 0.000595 acc_pose: 0.877868 loss: 0.000595 2022/10/27 15:33:45 - mmengine - INFO - Epoch(train) [69][450/586] lr: 5.000000e-04 eta: 6:15:00 time: 0.293415 data_time: 0.030200 memory: 11131 loss_kpt: 0.000603 acc_pose: 0.748816 loss: 0.000603 2022/10/27 15:33:59 - mmengine - INFO - Epoch(train) [69][500/586] lr: 5.000000e-04 eta: 6:14:48 time: 0.284341 data_time: 0.029566 memory: 11131 loss_kpt: 0.000609 acc_pose: 0.808364 loss: 0.000609 2022/10/27 15:34:13 - mmengine - INFO - Epoch(train) [69][550/586] lr: 5.000000e-04 eta: 6:14:35 time: 0.285279 data_time: 0.027957 memory: 11131 loss_kpt: 0.000614 acc_pose: 0.874505 loss: 0.000614 2022/10/27 15:34:24 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:34:39 - mmengine - INFO - Epoch(train) [70][50/586] lr: 5.000000e-04 eta: 6:13:55 time: 0.302533 data_time: 0.045854 memory: 11131 loss_kpt: 0.000599 acc_pose: 0.768568 loss: 0.000599 2022/10/27 15:34:53 - mmengine - INFO - Epoch(train) [70][100/586] lr: 5.000000e-04 eta: 6:13:43 time: 0.286887 data_time: 0.030194 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.827463 loss: 0.000590 2022/10/27 15:35:07 - mmengine - INFO - Epoch(train) [70][150/586] lr: 5.000000e-04 eta: 6:13:31 time: 0.287753 data_time: 0.028979 memory: 11131 loss_kpt: 0.000605 acc_pose: 0.866600 loss: 0.000605 2022/10/27 15:35:22 - mmengine - INFO - Epoch(train) [70][200/586] lr: 5.000000e-04 eta: 6:13:19 time: 0.288226 data_time: 0.028775 memory: 11131 loss_kpt: 0.000610 acc_pose: 0.873362 loss: 0.000610 2022/10/27 15:35:36 - mmengine - INFO - Epoch(train) [70][250/586] lr: 5.000000e-04 eta: 6:13:08 time: 0.289787 data_time: 0.030725 memory: 11131 loss_kpt: 0.000603 acc_pose: 0.864068 loss: 0.000603 2022/10/27 15:35:51 - mmengine - INFO - Epoch(train) [70][300/586] lr: 5.000000e-04 eta: 6:12:56 time: 0.290337 data_time: 0.028110 memory: 11131 loss_kpt: 0.000618 acc_pose: 0.744637 loss: 0.000618 2022/10/27 15:36:06 - mmengine - INFO - Epoch(train) [70][350/586] lr: 5.000000e-04 eta: 6:12:44 time: 0.292126 data_time: 0.033696 memory: 11131 loss_kpt: 0.000601 acc_pose: 0.844536 loss: 0.000601 2022/10/27 15:36:20 - mmengine - INFO - Epoch(train) [70][400/586] lr: 5.000000e-04 eta: 6:12:32 time: 0.288804 data_time: 0.026965 memory: 11131 loss_kpt: 0.000614 acc_pose: 0.859440 loss: 0.000614 2022/10/27 15:36:34 - mmengine - INFO - Epoch(train) [70][450/586] lr: 5.000000e-04 eta: 6:12:20 time: 0.280900 data_time: 0.027677 memory: 11131 loss_kpt: 0.000625 acc_pose: 0.811582 loss: 0.000625 2022/10/27 15:36:48 - mmengine - INFO - Epoch(train) [70][500/586] lr: 5.000000e-04 eta: 6:12:08 time: 0.288245 data_time: 0.028123 memory: 11131 loss_kpt: 0.000623 acc_pose: 0.851307 loss: 0.000623 2022/10/27 15:37:03 - mmengine - INFO - Epoch(train) [70][550/586] lr: 5.000000e-04 eta: 6:11:56 time: 0.292542 data_time: 0.029455 memory: 11131 loss_kpt: 0.000614 acc_pose: 0.807634 loss: 0.000614 2022/10/27 15:37:08 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:37:13 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:37:13 - mmengine - INFO - Saving checkpoint at 70 epochs 2022/10/27 15:37:24 - mmengine - INFO - Epoch(val) [70][50/407] eta: 0:00:50 time: 0.141155 data_time: 0.021187 memory: 11131 2022/10/27 15:37:31 - mmengine - INFO - Epoch(val) [70][100/407] eta: 0:00:41 time: 0.136607 data_time: 0.016150 memory: 1836 2022/10/27 15:37:38 - mmengine - INFO - Epoch(val) [70][150/407] eta: 0:00:35 time: 0.137318 data_time: 0.017505 memory: 1836 2022/10/27 15:37:45 - mmengine - INFO - Epoch(val) [70][200/407] eta: 0:00:28 time: 0.137210 data_time: 0.018810 memory: 1836 2022/10/27 15:37:51 - mmengine - INFO - Epoch(val) [70][250/407] eta: 0:00:20 time: 0.133465 data_time: 0.012609 memory: 1836 2022/10/27 15:37:58 - mmengine - INFO - Epoch(val) [70][300/407] eta: 0:00:14 time: 0.135723 data_time: 0.014119 memory: 1836 2022/10/27 15:38:05 - mmengine - INFO - Epoch(val) [70][350/407] eta: 0:00:07 time: 0.138687 data_time: 0.019859 memory: 1836 2022/10/27 15:38:11 - mmengine - INFO - Epoch(val) [70][400/407] eta: 0:00:00 time: 0.126399 data_time: 0.011311 memory: 1836 2022/10/27 15:38:58 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 15:39:16 - mmengine - INFO - Epoch(val) [70][407/407] coco/AP: 0.733634 coco/AP .5: 0.898337 coco/AP .75: 0.803591 coco/AP (M): 0.690978 coco/AP (L): 0.807419 coco/AR: 0.784713 coco/AR .5: 0.934666 coco/AR .75: 0.847922 coco/AR (M): 0.737285 coco/AR (L): 0.852731 2022/10/27 15:39:16 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_60.pth is removed 2022/10/27 15:39:18 - mmengine - INFO - The best checkpoint with 0.7336 coco/AP at 70 epoch is saved to best_coco/AP_epoch_70.pth. 2022/10/27 15:39:33 - mmengine - INFO - Epoch(train) [71][50/586] lr: 5.000000e-04 eta: 6:11:16 time: 0.294331 data_time: 0.036029 memory: 11131 loss_kpt: 0.000606 acc_pose: 0.871166 loss: 0.000606 2022/10/27 15:39:47 - mmengine - INFO - Epoch(train) [71][100/586] lr: 5.000000e-04 eta: 6:11:04 time: 0.291526 data_time: 0.038257 memory: 11131 loss_kpt: 0.000599 acc_pose: 0.875724 loss: 0.000599 2022/10/27 15:40:02 - mmengine - INFO - Epoch(train) [71][150/586] lr: 5.000000e-04 eta: 6:10:52 time: 0.291111 data_time: 0.028464 memory: 11131 loss_kpt: 0.000591 acc_pose: 0.788425 loss: 0.000591 2022/10/27 15:40:16 - mmengine - INFO - Epoch(train) [71][200/586] lr: 5.000000e-04 eta: 6:10:40 time: 0.281142 data_time: 0.029930 memory: 11131 loss_kpt: 0.000604 acc_pose: 0.741851 loss: 0.000604 2022/10/27 15:40:31 - mmengine - INFO - Epoch(train) [71][250/586] lr: 5.000000e-04 eta: 6:10:28 time: 0.290825 data_time: 0.031969 memory: 11131 loss_kpt: 0.000594 acc_pose: 0.787095 loss: 0.000594 2022/10/27 15:40:45 - mmengine - INFO - Epoch(train) [71][300/586] lr: 5.000000e-04 eta: 6:10:16 time: 0.288407 data_time: 0.031278 memory: 11131 loss_kpt: 0.000624 acc_pose: 0.894303 loss: 0.000624 2022/10/27 15:40:59 - mmengine - INFO - Epoch(train) [71][350/586] lr: 5.000000e-04 eta: 6:10:04 time: 0.289267 data_time: 0.030264 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.850127 loss: 0.000607 2022/10/27 15:41:14 - mmengine - INFO - Epoch(train) [71][400/586] lr: 5.000000e-04 eta: 6:09:52 time: 0.287403 data_time: 0.026470 memory: 11131 loss_kpt: 0.000612 acc_pose: 0.848423 loss: 0.000612 2022/10/27 15:41:28 - mmengine - INFO - Epoch(train) [71][450/586] lr: 5.000000e-04 eta: 6:09:40 time: 0.287311 data_time: 0.030326 memory: 11131 loss_kpt: 0.000604 acc_pose: 0.828722 loss: 0.000604 2022/10/27 15:41:43 - mmengine - INFO - Epoch(train) [71][500/586] lr: 5.000000e-04 eta: 6:09:28 time: 0.287268 data_time: 0.032295 memory: 11131 loss_kpt: 0.000603 acc_pose: 0.834905 loss: 0.000603 2022/10/27 15:41:57 - mmengine - INFO - Epoch(train) [71][550/586] lr: 5.000000e-04 eta: 6:09:16 time: 0.289846 data_time: 0.032012 memory: 11131 loss_kpt: 0.000621 acc_pose: 0.809235 loss: 0.000621 2022/10/27 15:42:07 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:42:22 - mmengine - INFO - Epoch(train) [72][50/586] lr: 5.000000e-04 eta: 6:08:36 time: 0.297849 data_time: 0.035996 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.829716 loss: 0.000585 2022/10/27 15:42:37 - mmengine - INFO - Epoch(train) [72][100/586] lr: 5.000000e-04 eta: 6:08:24 time: 0.286969 data_time: 0.032977 memory: 11131 loss_kpt: 0.000579 acc_pose: 0.851559 loss: 0.000579 2022/10/27 15:42:51 - mmengine - INFO - Epoch(train) [72][150/586] lr: 5.000000e-04 eta: 6:08:12 time: 0.288215 data_time: 0.030754 memory: 11131 loss_kpt: 0.000599 acc_pose: 0.846296 loss: 0.000599 2022/10/27 15:43:05 - mmengine - INFO - Epoch(train) [72][200/586] lr: 5.000000e-04 eta: 6:08:00 time: 0.287962 data_time: 0.030291 memory: 11131 loss_kpt: 0.000576 acc_pose: 0.875611 loss: 0.000576 2022/10/27 15:43:20 - mmengine - INFO - Epoch(train) [72][250/586] lr: 5.000000e-04 eta: 6:07:49 time: 0.293231 data_time: 0.031597 memory: 11131 loss_kpt: 0.000598 acc_pose: 0.827131 loss: 0.000598 2022/10/27 15:43:34 - mmengine - INFO - Epoch(train) [72][300/586] lr: 5.000000e-04 eta: 6:07:36 time: 0.282246 data_time: 0.028854 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.829698 loss: 0.000600 2022/10/27 15:43:48 - mmengine - INFO - Epoch(train) [72][350/586] lr: 5.000000e-04 eta: 6:07:24 time: 0.287214 data_time: 0.029564 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.805667 loss: 0.000586 2022/10/27 15:44:01 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:44:03 - mmengine - INFO - Epoch(train) [72][400/586] lr: 5.000000e-04 eta: 6:07:12 time: 0.286833 data_time: 0.030573 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.872816 loss: 0.000569 2022/10/27 15:44:17 - mmengine - INFO - Epoch(train) [72][450/586] lr: 5.000000e-04 eta: 6:07:00 time: 0.292047 data_time: 0.033034 memory: 11131 loss_kpt: 0.000616 acc_pose: 0.868522 loss: 0.000616 2022/10/27 15:44:32 - mmengine - INFO - Epoch(train) [72][500/586] lr: 5.000000e-04 eta: 6:06:48 time: 0.291086 data_time: 0.029097 memory: 11131 loss_kpt: 0.000612 acc_pose: 0.803429 loss: 0.000612 2022/10/27 15:44:46 - mmengine - INFO - Epoch(train) [72][550/586] lr: 5.000000e-04 eta: 6:06:36 time: 0.283379 data_time: 0.029082 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.794457 loss: 0.000607 2022/10/27 15:44:56 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:45:12 - mmengine - INFO - Epoch(train) [73][50/586] lr: 5.000000e-04 eta: 6:05:57 time: 0.304001 data_time: 0.039666 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.847756 loss: 0.000602 2022/10/27 15:45:26 - mmengine - INFO - Epoch(train) [73][100/586] lr: 5.000000e-04 eta: 6:05:45 time: 0.290489 data_time: 0.028386 memory: 11131 loss_kpt: 0.000609 acc_pose: 0.873505 loss: 0.000609 2022/10/27 15:45:41 - mmengine - INFO - Epoch(train) [73][150/586] lr: 5.000000e-04 eta: 6:05:33 time: 0.288728 data_time: 0.029823 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.760191 loss: 0.000590 2022/10/27 15:45:55 - mmengine - INFO - Epoch(train) [73][200/586] lr: 5.000000e-04 eta: 6:05:21 time: 0.283413 data_time: 0.030588 memory: 11131 loss_kpt: 0.000608 acc_pose: 0.874744 loss: 0.000608 2022/10/27 15:46:09 - mmengine - INFO - Epoch(train) [73][250/586] lr: 5.000000e-04 eta: 6:05:09 time: 0.292627 data_time: 0.034161 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.825295 loss: 0.000600 2022/10/27 15:46:24 - mmengine - INFO - Epoch(train) [73][300/586] lr: 5.000000e-04 eta: 6:04:57 time: 0.289860 data_time: 0.034786 memory: 11131 loss_kpt: 0.000621 acc_pose: 0.760440 loss: 0.000621 2022/10/27 15:46:38 - mmengine - INFO - Epoch(train) [73][350/586] lr: 5.000000e-04 eta: 6:04:45 time: 0.284364 data_time: 0.026349 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.823981 loss: 0.000590 2022/10/27 15:46:53 - mmengine - INFO - Epoch(train) [73][400/586] lr: 5.000000e-04 eta: 6:04:33 time: 0.291939 data_time: 0.028871 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.866098 loss: 0.000592 2022/10/27 15:47:07 - mmengine - INFO - Epoch(train) [73][450/586] lr: 5.000000e-04 eta: 6:04:21 time: 0.285701 data_time: 0.027964 memory: 11131 loss_kpt: 0.000597 acc_pose: 0.830213 loss: 0.000597 2022/10/27 15:47:22 - mmengine - INFO - Epoch(train) [73][500/586] lr: 5.000000e-04 eta: 6:04:09 time: 0.291150 data_time: 0.029125 memory: 11131 loss_kpt: 0.000587 acc_pose: 0.858658 loss: 0.000587 2022/10/27 15:47:36 - mmengine - INFO - Epoch(train) [73][550/586] lr: 5.000000e-04 eta: 6:03:57 time: 0.288170 data_time: 0.033077 memory: 11131 loss_kpt: 0.000611 acc_pose: 0.800908 loss: 0.000611 2022/10/27 15:47:46 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:48:01 - mmengine - INFO - Epoch(train) [74][50/586] lr: 5.000000e-04 eta: 6:03:18 time: 0.298297 data_time: 0.035755 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.825683 loss: 0.000580 2022/10/27 15:48:15 - mmengine - INFO - Epoch(train) [74][100/586] lr: 5.000000e-04 eta: 6:03:05 time: 0.285542 data_time: 0.028102 memory: 11131 loss_kpt: 0.000597 acc_pose: 0.820105 loss: 0.000597 2022/10/27 15:48:30 - mmengine - INFO - Epoch(train) [74][150/586] lr: 5.000000e-04 eta: 6:02:54 time: 0.290962 data_time: 0.029485 memory: 11131 loss_kpt: 0.000574 acc_pose: 0.837712 loss: 0.000574 2022/10/27 15:48:45 - mmengine - INFO - Epoch(train) [74][200/586] lr: 5.000000e-04 eta: 6:02:42 time: 0.292148 data_time: 0.033110 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.825671 loss: 0.000602 2022/10/27 15:48:51 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:48:59 - mmengine - INFO - Epoch(train) [74][250/586] lr: 5.000000e-04 eta: 6:02:30 time: 0.288560 data_time: 0.030357 memory: 11131 loss_kpt: 0.000593 acc_pose: 0.833846 loss: 0.000593 2022/10/27 15:49:13 - mmengine - INFO - Epoch(train) [74][300/586] lr: 5.000000e-04 eta: 6:02:18 time: 0.285575 data_time: 0.029425 memory: 11131 loss_kpt: 0.000595 acc_pose: 0.863673 loss: 0.000595 2022/10/27 15:49:28 - mmengine - INFO - Epoch(train) [74][350/586] lr: 5.000000e-04 eta: 6:02:05 time: 0.287626 data_time: 0.027678 memory: 11131 loss_kpt: 0.000604 acc_pose: 0.831447 loss: 0.000604 2022/10/27 15:49:42 - mmengine - INFO - Epoch(train) [74][400/586] lr: 5.000000e-04 eta: 6:01:53 time: 0.282037 data_time: 0.027246 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.838443 loss: 0.000602 2022/10/27 15:49:56 - mmengine - INFO - Epoch(train) [74][450/586] lr: 5.000000e-04 eta: 6:01:41 time: 0.289221 data_time: 0.031444 memory: 11131 loss_kpt: 0.000598 acc_pose: 0.843948 loss: 0.000598 2022/10/27 15:50:11 - mmengine - INFO - Epoch(train) [74][500/586] lr: 5.000000e-04 eta: 6:01:29 time: 0.288875 data_time: 0.027311 memory: 11131 loss_kpt: 0.000595 acc_pose: 0.841454 loss: 0.000595 2022/10/27 15:50:25 - mmengine - INFO - Epoch(train) [74][550/586] lr: 5.000000e-04 eta: 6:01:16 time: 0.284782 data_time: 0.028489 memory: 11131 loss_kpt: 0.000611 acc_pose: 0.865079 loss: 0.000611 2022/10/27 15:50:35 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:50:50 - mmengine - INFO - Epoch(train) [75][50/586] lr: 5.000000e-04 eta: 6:00:37 time: 0.296729 data_time: 0.035417 memory: 11131 loss_kpt: 0.000605 acc_pose: 0.823606 loss: 0.000605 2022/10/27 15:51:04 - mmengine - INFO - Epoch(train) [75][100/586] lr: 5.000000e-04 eta: 6:00:25 time: 0.287271 data_time: 0.028196 memory: 11131 loss_kpt: 0.000597 acc_pose: 0.700053 loss: 0.000597 2022/10/27 15:51:19 - mmengine - INFO - Epoch(train) [75][150/586] lr: 5.000000e-04 eta: 6:00:13 time: 0.291802 data_time: 0.031606 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.844166 loss: 0.000600 2022/10/27 15:51:33 - mmengine - INFO - Epoch(train) [75][200/586] lr: 5.000000e-04 eta: 6:00:01 time: 0.287693 data_time: 0.031905 memory: 11131 loss_kpt: 0.000619 acc_pose: 0.869039 loss: 0.000619 2022/10/27 15:51:48 - mmengine - INFO - Epoch(train) [75][250/586] lr: 5.000000e-04 eta: 5:59:50 time: 0.292849 data_time: 0.032747 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.819358 loss: 0.000600 2022/10/27 15:52:02 - mmengine - INFO - Epoch(train) [75][300/586] lr: 5.000000e-04 eta: 5:59:37 time: 0.285177 data_time: 0.030774 memory: 11131 loss_kpt: 0.000603 acc_pose: 0.847283 loss: 0.000603 2022/10/27 15:52:17 - mmengine - INFO - Epoch(train) [75][350/586] lr: 5.000000e-04 eta: 5:59:25 time: 0.287324 data_time: 0.036902 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.879883 loss: 0.000584 2022/10/27 15:52:31 - mmengine - INFO - Epoch(train) [75][400/586] lr: 5.000000e-04 eta: 5:59:13 time: 0.292585 data_time: 0.028051 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.912663 loss: 0.000589 2022/10/27 15:52:45 - mmengine - INFO - Epoch(train) [75][450/586] lr: 5.000000e-04 eta: 5:59:01 time: 0.283789 data_time: 0.029305 memory: 11131 loss_kpt: 0.000617 acc_pose: 0.793508 loss: 0.000617 2022/10/27 15:53:00 - mmengine - INFO - Epoch(train) [75][500/586] lr: 5.000000e-04 eta: 5:58:49 time: 0.289956 data_time: 0.027304 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.798316 loss: 0.000586 2022/10/27 15:53:14 - mmengine - INFO - Epoch(train) [75][550/586] lr: 5.000000e-04 eta: 5:58:37 time: 0.287539 data_time: 0.030582 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.814962 loss: 0.000590 2022/10/27 15:53:25 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:53:39 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:53:39 - mmengine - INFO - Epoch(train) [76][50/586] lr: 5.000000e-04 eta: 5:57:58 time: 0.299387 data_time: 0.036337 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.835009 loss: 0.000590 2022/10/27 15:53:54 - mmengine - INFO - Epoch(train) [76][100/586] lr: 5.000000e-04 eta: 5:57:46 time: 0.282129 data_time: 0.027472 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.911107 loss: 0.000586 2022/10/27 15:54:08 - mmengine - INFO - Epoch(train) [76][150/586] lr: 5.000000e-04 eta: 5:57:33 time: 0.287501 data_time: 0.028221 memory: 11131 loss_kpt: 0.000595 acc_pose: 0.827659 loss: 0.000595 2022/10/27 15:54:22 - mmengine - INFO - Epoch(train) [76][200/586] lr: 5.000000e-04 eta: 5:57:21 time: 0.286003 data_time: 0.029585 memory: 11131 loss_kpt: 0.000595 acc_pose: 0.816228 loss: 0.000595 2022/10/27 15:54:37 - mmengine - INFO - Epoch(train) [76][250/586] lr: 5.000000e-04 eta: 5:57:09 time: 0.291894 data_time: 0.030154 memory: 11131 loss_kpt: 0.000612 acc_pose: 0.718460 loss: 0.000612 2022/10/27 15:54:51 - mmengine - INFO - Epoch(train) [76][300/586] lr: 5.000000e-04 eta: 5:56:57 time: 0.286502 data_time: 0.027421 memory: 11131 loss_kpt: 0.000609 acc_pose: 0.814095 loss: 0.000609 2022/10/27 15:55:05 - mmengine - INFO - Epoch(train) [76][350/586] lr: 5.000000e-04 eta: 5:56:45 time: 0.285342 data_time: 0.026626 memory: 11131 loss_kpt: 0.000599 acc_pose: 0.864289 loss: 0.000599 2022/10/27 15:55:20 - mmengine - INFO - Epoch(train) [76][400/586] lr: 5.000000e-04 eta: 5:56:33 time: 0.287580 data_time: 0.028001 memory: 11131 loss_kpt: 0.000616 acc_pose: 0.809310 loss: 0.000616 2022/10/27 15:55:34 - mmengine - INFO - Epoch(train) [76][450/586] lr: 5.000000e-04 eta: 5:56:20 time: 0.286270 data_time: 0.032128 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.800234 loss: 0.000602 2022/10/27 15:55:49 - mmengine - INFO - Epoch(train) [76][500/586] lr: 5.000000e-04 eta: 5:56:08 time: 0.287484 data_time: 0.027894 memory: 11131 loss_kpt: 0.000593 acc_pose: 0.787965 loss: 0.000593 2022/10/27 15:56:03 - mmengine - INFO - Epoch(train) [76][550/586] lr: 5.000000e-04 eta: 5:55:56 time: 0.284723 data_time: 0.027155 memory: 11131 loss_kpt: 0.000596 acc_pose: 0.830613 loss: 0.000596 2022/10/27 15:56:13 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:56:28 - mmengine - INFO - Epoch(train) [77][50/586] lr: 5.000000e-04 eta: 5:55:17 time: 0.296720 data_time: 0.038923 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.859633 loss: 0.000600 2022/10/27 15:56:42 - mmengine - INFO - Epoch(train) [77][100/586] lr: 5.000000e-04 eta: 5:55:05 time: 0.287519 data_time: 0.029032 memory: 11131 loss_kpt: 0.000604 acc_pose: 0.841445 loss: 0.000604 2022/10/27 15:56:56 - mmengine - INFO - Epoch(train) [77][150/586] lr: 5.000000e-04 eta: 5:54:53 time: 0.285369 data_time: 0.028461 memory: 11131 loss_kpt: 0.000594 acc_pose: 0.837066 loss: 0.000594 2022/10/27 15:57:11 - mmengine - INFO - Epoch(train) [77][200/586] lr: 5.000000e-04 eta: 5:54:40 time: 0.287864 data_time: 0.032176 memory: 11131 loss_kpt: 0.000603 acc_pose: 0.887905 loss: 0.000603 2022/10/27 15:57:25 - mmengine - INFO - Epoch(train) [77][250/586] lr: 5.000000e-04 eta: 5:54:29 time: 0.292560 data_time: 0.028448 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.851357 loss: 0.000585 2022/10/27 15:57:40 - mmengine - INFO - Epoch(train) [77][300/586] lr: 5.000000e-04 eta: 5:54:16 time: 0.285147 data_time: 0.029062 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.787647 loss: 0.000592 2022/10/27 15:57:54 - mmengine - INFO - Epoch(train) [77][350/586] lr: 5.000000e-04 eta: 5:54:04 time: 0.284825 data_time: 0.032125 memory: 11131 loss_kpt: 0.000591 acc_pose: 0.812739 loss: 0.000591 2022/10/27 15:58:09 - mmengine - INFO - Epoch(train) [77][400/586] lr: 5.000000e-04 eta: 5:53:52 time: 0.292871 data_time: 0.029247 memory: 11131 loss_kpt: 0.000605 acc_pose: 0.878281 loss: 0.000605 2022/10/27 15:58:23 - mmengine - INFO - Epoch(train) [77][450/586] lr: 5.000000e-04 eta: 5:53:40 time: 0.284882 data_time: 0.027522 memory: 11131 loss_kpt: 0.000610 acc_pose: 0.835512 loss: 0.000610 2022/10/27 15:58:27 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:58:37 - mmengine - INFO - Epoch(train) [77][500/586] lr: 5.000000e-04 eta: 5:53:28 time: 0.292591 data_time: 0.027692 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.787442 loss: 0.000607 2022/10/27 15:58:52 - mmengine - INFO - Epoch(train) [77][550/586] lr: 5.000000e-04 eta: 5:53:15 time: 0.285277 data_time: 0.028671 memory: 11131 loss_kpt: 0.000594 acc_pose: 0.854925 loss: 0.000594 2022/10/27 15:59:02 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 15:59:17 - mmengine - INFO - Epoch(train) [78][50/586] lr: 5.000000e-04 eta: 5:52:38 time: 0.299838 data_time: 0.037115 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.802153 loss: 0.000586 2022/10/27 15:59:31 - mmengine - INFO - Epoch(train) [78][100/586] lr: 5.000000e-04 eta: 5:52:25 time: 0.284119 data_time: 0.028216 memory: 11131 loss_kpt: 0.000614 acc_pose: 0.818848 loss: 0.000614 2022/10/27 15:59:46 - mmengine - INFO - Epoch(train) [78][150/586] lr: 5.000000e-04 eta: 5:52:13 time: 0.295261 data_time: 0.027751 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.838105 loss: 0.000592 2022/10/27 16:00:00 - mmengine - INFO - Epoch(train) [78][200/586] lr: 5.000000e-04 eta: 5:52:01 time: 0.285162 data_time: 0.030821 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.894856 loss: 0.000602 2022/10/27 16:00:15 - mmengine - INFO - Epoch(train) [78][250/586] lr: 5.000000e-04 eta: 5:51:49 time: 0.291119 data_time: 0.026975 memory: 11131 loss_kpt: 0.000591 acc_pose: 0.761583 loss: 0.000591 2022/10/27 16:00:29 - mmengine - INFO - Epoch(train) [78][300/586] lr: 5.000000e-04 eta: 5:51:37 time: 0.286989 data_time: 0.030574 memory: 11131 loss_kpt: 0.000599 acc_pose: 0.819574 loss: 0.000599 2022/10/27 16:00:43 - mmengine - INFO - Epoch(train) [78][350/586] lr: 5.000000e-04 eta: 5:51:24 time: 0.284634 data_time: 0.028734 memory: 11131 loss_kpt: 0.000606 acc_pose: 0.836942 loss: 0.000606 2022/10/27 16:00:58 - mmengine - INFO - Epoch(train) [78][400/586] lr: 5.000000e-04 eta: 5:51:12 time: 0.287182 data_time: 0.028399 memory: 11131 loss_kpt: 0.000605 acc_pose: 0.726067 loss: 0.000605 2022/10/27 16:01:12 - mmengine - INFO - Epoch(train) [78][450/586] lr: 5.000000e-04 eta: 5:51:00 time: 0.293953 data_time: 0.026564 memory: 11131 loss_kpt: 0.000605 acc_pose: 0.868792 loss: 0.000605 2022/10/27 16:01:27 - mmengine - INFO - Epoch(train) [78][500/586] lr: 5.000000e-04 eta: 5:50:48 time: 0.291435 data_time: 0.028389 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.866116 loss: 0.000586 2022/10/27 16:01:41 - mmengine - INFO - Epoch(train) [78][550/586] lr: 5.000000e-04 eta: 5:50:36 time: 0.284333 data_time: 0.026658 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.822224 loss: 0.000602 2022/10/27 16:01:51 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:02:06 - mmengine - INFO - Epoch(train) [79][50/586] lr: 5.000000e-04 eta: 5:49:58 time: 0.294112 data_time: 0.038040 memory: 11131 loss_kpt: 0.000598 acc_pose: 0.895340 loss: 0.000598 2022/10/27 16:02:21 - mmengine - INFO - Epoch(train) [79][100/586] lr: 5.000000e-04 eta: 5:49:46 time: 0.291231 data_time: 0.030793 memory: 11131 loss_kpt: 0.000587 acc_pose: 0.848908 loss: 0.000587 2022/10/27 16:02:35 - mmengine - INFO - Epoch(train) [79][150/586] lr: 5.000000e-04 eta: 5:49:34 time: 0.287607 data_time: 0.028783 memory: 11131 loss_kpt: 0.000603 acc_pose: 0.772875 loss: 0.000603 2022/10/27 16:02:49 - mmengine - INFO - Epoch(train) [79][200/586] lr: 5.000000e-04 eta: 5:49:22 time: 0.289570 data_time: 0.034279 memory: 11131 loss_kpt: 0.000577 acc_pose: 0.848165 loss: 0.000577 2022/10/27 16:03:04 - mmengine - INFO - Epoch(train) [79][250/586] lr: 5.000000e-04 eta: 5:49:10 time: 0.292969 data_time: 0.028762 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.856631 loss: 0.000592 2022/10/27 16:03:16 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:03:18 - mmengine - INFO - Epoch(train) [79][300/586] lr: 5.000000e-04 eta: 5:48:57 time: 0.283176 data_time: 0.027818 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.834273 loss: 0.000589 2022/10/27 16:03:33 - mmengine - INFO - Epoch(train) [79][350/586] lr: 5.000000e-04 eta: 5:48:45 time: 0.286713 data_time: 0.030751 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.843738 loss: 0.000589 2022/10/27 16:03:47 - mmengine - INFO - Epoch(train) [79][400/586] lr: 5.000000e-04 eta: 5:48:33 time: 0.291993 data_time: 0.028955 memory: 11131 loss_kpt: 0.000605 acc_pose: 0.814056 loss: 0.000605 2022/10/27 16:04:02 - mmengine - INFO - Epoch(train) [79][450/586] lr: 5.000000e-04 eta: 5:48:21 time: 0.287868 data_time: 0.028160 memory: 11131 loss_kpt: 0.000583 acc_pose: 0.799620 loss: 0.000583 2022/10/27 16:04:16 - mmengine - INFO - Epoch(train) [79][500/586] lr: 5.000000e-04 eta: 5:48:08 time: 0.284374 data_time: 0.028677 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.836675 loss: 0.000580 2022/10/27 16:04:30 - mmengine - INFO - Epoch(train) [79][550/586] lr: 5.000000e-04 eta: 5:47:56 time: 0.287306 data_time: 0.034469 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.793249 loss: 0.000600 2022/10/27 16:04:40 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:04:55 - mmengine - INFO - Epoch(train) [80][50/586] lr: 5.000000e-04 eta: 5:47:19 time: 0.300686 data_time: 0.040818 memory: 11131 loss_kpt: 0.000599 acc_pose: 0.847468 loss: 0.000599 2022/10/27 16:05:10 - mmengine - INFO - Epoch(train) [80][100/586] lr: 5.000000e-04 eta: 5:47:07 time: 0.288837 data_time: 0.031468 memory: 11131 loss_kpt: 0.000594 acc_pose: 0.828210 loss: 0.000594 2022/10/27 16:05:24 - mmengine - INFO - Epoch(train) [80][150/586] lr: 5.000000e-04 eta: 5:46:54 time: 0.287028 data_time: 0.028165 memory: 11131 loss_kpt: 0.000591 acc_pose: 0.868014 loss: 0.000591 2022/10/27 16:05:38 - mmengine - INFO - Epoch(train) [80][200/586] lr: 5.000000e-04 eta: 5:46:42 time: 0.283270 data_time: 0.029562 memory: 11131 loss_kpt: 0.000598 acc_pose: 0.824273 loss: 0.000598 2022/10/27 16:05:53 - mmengine - INFO - Epoch(train) [80][250/586] lr: 5.000000e-04 eta: 5:46:29 time: 0.289654 data_time: 0.028330 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.882542 loss: 0.000564 2022/10/27 16:06:07 - mmengine - INFO - Epoch(train) [80][300/586] lr: 5.000000e-04 eta: 5:46:17 time: 0.290921 data_time: 0.027850 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.861551 loss: 0.000600 2022/10/27 16:06:21 - mmengine - INFO - Epoch(train) [80][350/586] lr: 5.000000e-04 eta: 5:46:05 time: 0.284424 data_time: 0.029744 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.858146 loss: 0.000585 2022/10/27 16:06:36 - mmengine - INFO - Epoch(train) [80][400/586] lr: 5.000000e-04 eta: 5:45:53 time: 0.287047 data_time: 0.027070 memory: 11131 loss_kpt: 0.000593 acc_pose: 0.843972 loss: 0.000593 2022/10/27 16:06:50 - mmengine - INFO - Epoch(train) [80][450/586] lr: 5.000000e-04 eta: 5:45:40 time: 0.288538 data_time: 0.028229 memory: 11131 loss_kpt: 0.000596 acc_pose: 0.822675 loss: 0.000596 2022/10/27 16:07:04 - mmengine - INFO - Epoch(train) [80][500/586] lr: 5.000000e-04 eta: 5:45:28 time: 0.285759 data_time: 0.028637 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.803197 loss: 0.000584 2022/10/27 16:07:19 - mmengine - INFO - Epoch(train) [80][550/586] lr: 5.000000e-04 eta: 5:45:16 time: 0.288884 data_time: 0.029559 memory: 11131 loss_kpt: 0.000591 acc_pose: 0.813313 loss: 0.000591 2022/10/27 16:07:29 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:07:29 - mmengine - INFO - Saving checkpoint at 80 epochs 2022/10/27 16:07:40 - mmengine - INFO - Epoch(val) [80][50/407] eta: 0:00:53 time: 0.150924 data_time: 0.029428 memory: 11131 2022/10/27 16:07:47 - mmengine - INFO - Epoch(val) [80][100/407] eta: 0:00:42 time: 0.139654 data_time: 0.020644 memory: 1836 2022/10/27 16:07:54 - mmengine - INFO - Epoch(val) [80][150/407] eta: 0:00:36 time: 0.140529 data_time: 0.021246 memory: 1836 2022/10/27 16:08:02 - mmengine - INFO - Epoch(val) [80][200/407] eta: 0:00:29 time: 0.144536 data_time: 0.026325 memory: 1836 2022/10/27 16:08:08 - mmengine - INFO - Epoch(val) [80][250/407] eta: 0:00:20 time: 0.131922 data_time: 0.013560 memory: 1836 2022/10/27 16:08:16 - mmengine - INFO - Epoch(val) [80][300/407] eta: 0:00:15 time: 0.145159 data_time: 0.023531 memory: 1836 2022/10/27 16:08:23 - mmengine - INFO - Epoch(val) [80][350/407] eta: 0:00:07 time: 0.139377 data_time: 0.018630 memory: 1836 2022/10/27 16:08:29 - mmengine - INFO - Epoch(val) [80][400/407] eta: 0:00:00 time: 0.128662 data_time: 0.013417 memory: 1836 2022/10/27 16:09:14 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 16:09:32 - mmengine - INFO - Epoch(val) [80][407/407] coco/AP: 0.731745 coco/AP .5: 0.896846 coco/AP .75: 0.800725 coco/AP (M): 0.690566 coco/AP (L): 0.803507 coco/AR: 0.783659 coco/AR .5: 0.934351 coco/AR .75: 0.845246 coco/AR (M): 0.738842 coco/AR (L): 0.848049 2022/10/27 16:09:47 - mmengine - INFO - Epoch(train) [81][50/586] lr: 5.000000e-04 eta: 5:44:39 time: 0.301076 data_time: 0.040639 memory: 11131 loss_kpt: 0.000582 acc_pose: 0.773106 loss: 0.000582 2022/10/27 16:10:01 - mmengine - INFO - Epoch(train) [81][100/586] lr: 5.000000e-04 eta: 5:44:26 time: 0.286695 data_time: 0.029053 memory: 11131 loss_kpt: 0.000588 acc_pose: 0.816020 loss: 0.000588 2022/10/27 16:10:07 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:10:15 - mmengine - INFO - Epoch(train) [81][150/586] lr: 5.000000e-04 eta: 5:44:14 time: 0.289116 data_time: 0.031388 memory: 11131 loss_kpt: 0.000601 acc_pose: 0.850526 loss: 0.000601 2022/10/27 16:10:30 - mmengine - INFO - Epoch(train) [81][200/586] lr: 5.000000e-04 eta: 5:44:02 time: 0.283312 data_time: 0.027568 memory: 11131 loss_kpt: 0.000587 acc_pose: 0.751092 loss: 0.000587 2022/10/27 16:10:44 - mmengine - INFO - Epoch(train) [81][250/586] lr: 5.000000e-04 eta: 5:43:49 time: 0.287303 data_time: 0.032581 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.848673 loss: 0.000584 2022/10/27 16:10:58 - mmengine - INFO - Epoch(train) [81][300/586] lr: 5.000000e-04 eta: 5:43:37 time: 0.286598 data_time: 0.029598 memory: 11131 loss_kpt: 0.000593 acc_pose: 0.870755 loss: 0.000593 2022/10/27 16:11:13 - mmengine - INFO - Epoch(train) [81][350/586] lr: 5.000000e-04 eta: 5:43:25 time: 0.288423 data_time: 0.033468 memory: 11131 loss_kpt: 0.000610 acc_pose: 0.862396 loss: 0.000610 2022/10/27 16:11:27 - mmengine - INFO - Epoch(train) [81][400/586] lr: 5.000000e-04 eta: 5:43:12 time: 0.287617 data_time: 0.027295 memory: 11131 loss_kpt: 0.000588 acc_pose: 0.892965 loss: 0.000588 2022/10/27 16:11:41 - mmengine - INFO - Epoch(train) [81][450/586] lr: 5.000000e-04 eta: 5:43:00 time: 0.285120 data_time: 0.029925 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.793961 loss: 0.000602 2022/10/27 16:11:56 - mmengine - INFO - Epoch(train) [81][500/586] lr: 5.000000e-04 eta: 5:42:48 time: 0.291341 data_time: 0.027734 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.734442 loss: 0.000586 2022/10/27 16:12:10 - mmengine - INFO - Epoch(train) [81][550/586] lr: 5.000000e-04 eta: 5:42:35 time: 0.283553 data_time: 0.028133 memory: 11131 loss_kpt: 0.000588 acc_pose: 0.830987 loss: 0.000588 2022/10/27 16:12:20 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:12:35 - mmengine - INFO - Epoch(train) [82][50/586] lr: 5.000000e-04 eta: 5:41:58 time: 0.296366 data_time: 0.037412 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.799764 loss: 0.000586 2022/10/27 16:12:49 - mmengine - INFO - Epoch(train) [82][100/586] lr: 5.000000e-04 eta: 5:41:46 time: 0.283996 data_time: 0.028395 memory: 11131 loss_kpt: 0.000577 acc_pose: 0.886617 loss: 0.000577 2022/10/27 16:13:04 - mmengine - INFO - Epoch(train) [82][150/586] lr: 5.000000e-04 eta: 5:41:33 time: 0.285731 data_time: 0.027046 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.862024 loss: 0.000585 2022/10/27 16:13:18 - mmengine - INFO - Epoch(train) [82][200/586] lr: 5.000000e-04 eta: 5:41:21 time: 0.286083 data_time: 0.027895 memory: 11131 loss_kpt: 0.000575 acc_pose: 0.829071 loss: 0.000575 2022/10/27 16:13:33 - mmengine - INFO - Epoch(train) [82][250/586] lr: 5.000000e-04 eta: 5:41:09 time: 0.290907 data_time: 0.034161 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.797101 loss: 0.000590 2022/10/27 16:13:47 - mmengine - INFO - Epoch(train) [82][300/586] lr: 5.000000e-04 eta: 5:40:57 time: 0.292471 data_time: 0.027623 memory: 11131 loss_kpt: 0.000599 acc_pose: 0.922921 loss: 0.000599 2022/10/27 16:14:01 - mmengine - INFO - Epoch(train) [82][350/586] lr: 5.000000e-04 eta: 5:40:44 time: 0.281071 data_time: 0.028341 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.833166 loss: 0.000592 2022/10/27 16:14:16 - mmengine - INFO - Epoch(train) [82][400/586] lr: 5.000000e-04 eta: 5:40:32 time: 0.289859 data_time: 0.027990 memory: 11131 loss_kpt: 0.000593 acc_pose: 0.888248 loss: 0.000593 2022/10/27 16:14:30 - mmengine - INFO - Epoch(train) [82][450/586] lr: 5.000000e-04 eta: 5:40:20 time: 0.292685 data_time: 0.034484 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.872244 loss: 0.000589 2022/10/27 16:14:45 - mmengine - INFO - Epoch(train) [82][500/586] lr: 5.000000e-04 eta: 5:40:07 time: 0.286392 data_time: 0.029526 memory: 11131 loss_kpt: 0.000610 acc_pose: 0.823212 loss: 0.000610 2022/10/27 16:14:55 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:14:59 - mmengine - INFO - Epoch(train) [82][550/586] lr: 5.000000e-04 eta: 5:39:55 time: 0.291402 data_time: 0.030187 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.854327 loss: 0.000590 2022/10/27 16:15:09 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:15:25 - mmengine - INFO - Epoch(train) [83][50/586] lr: 5.000000e-04 eta: 5:39:19 time: 0.302344 data_time: 0.041249 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.844857 loss: 0.000562 2022/10/27 16:15:39 - mmengine - INFO - Epoch(train) [83][100/586] lr: 5.000000e-04 eta: 5:39:06 time: 0.283288 data_time: 0.031665 memory: 11131 loss_kpt: 0.000597 acc_pose: 0.885304 loss: 0.000597 2022/10/27 16:15:53 - mmengine - INFO - Epoch(train) [83][150/586] lr: 5.000000e-04 eta: 5:38:54 time: 0.288727 data_time: 0.027669 memory: 11131 loss_kpt: 0.000588 acc_pose: 0.913311 loss: 0.000588 2022/10/27 16:16:08 - mmengine - INFO - Epoch(train) [83][200/586] lr: 5.000000e-04 eta: 5:38:42 time: 0.289466 data_time: 0.031003 memory: 11131 loss_kpt: 0.000608 acc_pose: 0.820422 loss: 0.000608 2022/10/27 16:16:22 - mmengine - INFO - Epoch(train) [83][250/586] lr: 5.000000e-04 eta: 5:38:30 time: 0.287769 data_time: 0.030839 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.832457 loss: 0.000600 2022/10/27 16:16:36 - mmengine - INFO - Epoch(train) [83][300/586] lr: 5.000000e-04 eta: 5:38:17 time: 0.287295 data_time: 0.029962 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.827936 loss: 0.000589 2022/10/27 16:16:51 - mmengine - INFO - Epoch(train) [83][350/586] lr: 5.000000e-04 eta: 5:38:05 time: 0.288581 data_time: 0.035188 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.851001 loss: 0.000602 2022/10/27 16:17:05 - mmengine - INFO - Epoch(train) [83][400/586] lr: 5.000000e-04 eta: 5:37:53 time: 0.288534 data_time: 0.030917 memory: 11131 loss_kpt: 0.000600 acc_pose: 0.824508 loss: 0.000600 2022/10/27 16:17:19 - mmengine - INFO - Epoch(train) [83][450/586] lr: 5.000000e-04 eta: 5:37:40 time: 0.283470 data_time: 0.029312 memory: 11131 loss_kpt: 0.000579 acc_pose: 0.840321 loss: 0.000579 2022/10/27 16:17:34 - mmengine - INFO - Epoch(train) [83][500/586] lr: 5.000000e-04 eta: 5:37:28 time: 0.288036 data_time: 0.028560 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.868213 loss: 0.000580 2022/10/27 16:17:48 - mmengine - INFO - Epoch(train) [83][550/586] lr: 5.000000e-04 eta: 5:37:15 time: 0.283855 data_time: 0.030713 memory: 11131 loss_kpt: 0.000627 acc_pose: 0.867145 loss: 0.000627 2022/10/27 16:17:58 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:18:13 - mmengine - INFO - Epoch(train) [84][50/586] lr: 5.000000e-04 eta: 5:36:39 time: 0.298665 data_time: 0.038512 memory: 11131 loss_kpt: 0.000599 acc_pose: 0.796553 loss: 0.000599 2022/10/27 16:18:28 - mmengine - INFO - Epoch(train) [84][100/586] lr: 5.000000e-04 eta: 5:36:26 time: 0.283971 data_time: 0.031541 memory: 11131 loss_kpt: 0.000587 acc_pose: 0.859899 loss: 0.000587 2022/10/27 16:18:42 - mmengine - INFO - Epoch(train) [84][150/586] lr: 5.000000e-04 eta: 5:36:14 time: 0.292283 data_time: 0.029117 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.817270 loss: 0.000586 2022/10/27 16:18:56 - mmengine - INFO - Epoch(train) [84][200/586] lr: 5.000000e-04 eta: 5:36:02 time: 0.287285 data_time: 0.029472 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.852005 loss: 0.000586 2022/10/27 16:19:11 - mmengine - INFO - Epoch(train) [84][250/586] lr: 5.000000e-04 eta: 5:35:50 time: 0.294778 data_time: 0.035557 memory: 11131 loss_kpt: 0.000587 acc_pose: 0.828145 loss: 0.000587 2022/10/27 16:19:26 - mmengine - INFO - Epoch(train) [84][300/586] lr: 5.000000e-04 eta: 5:35:38 time: 0.292036 data_time: 0.027651 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.841139 loss: 0.000592 2022/10/27 16:19:40 - mmengine - INFO - Epoch(train) [84][350/586] lr: 5.000000e-04 eta: 5:35:25 time: 0.281663 data_time: 0.030182 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.876392 loss: 0.000580 2022/10/27 16:19:43 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:19:54 - mmengine - INFO - Epoch(train) [84][400/586] lr: 5.000000e-04 eta: 5:35:13 time: 0.288521 data_time: 0.027484 memory: 11131 loss_kpt: 0.000587 acc_pose: 0.797932 loss: 0.000587 2022/10/27 16:20:09 - mmengine - INFO - Epoch(train) [84][450/586] lr: 5.000000e-04 eta: 5:35:00 time: 0.284657 data_time: 0.029137 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.718480 loss: 0.000602 2022/10/27 16:20:23 - mmengine - INFO - Epoch(train) [84][500/586] lr: 5.000000e-04 eta: 5:34:48 time: 0.290556 data_time: 0.035898 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.825931 loss: 0.000586 2022/10/27 16:20:37 - mmengine - INFO - Epoch(train) [84][550/586] lr: 5.000000e-04 eta: 5:34:35 time: 0.286593 data_time: 0.029034 memory: 11131 loss_kpt: 0.000593 acc_pose: 0.881321 loss: 0.000593 2022/10/27 16:20:48 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:21:03 - mmengine - INFO - Epoch(train) [85][50/586] lr: 5.000000e-04 eta: 5:34:00 time: 0.308064 data_time: 0.042902 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.860189 loss: 0.000585 2022/10/27 16:21:17 - mmengine - INFO - Epoch(train) [85][100/586] lr: 5.000000e-04 eta: 5:33:48 time: 0.285735 data_time: 0.030335 memory: 11131 loss_kpt: 0.000594 acc_pose: 0.850360 loss: 0.000594 2022/10/27 16:21:32 - mmengine - INFO - Epoch(train) [85][150/586] lr: 5.000000e-04 eta: 5:33:35 time: 0.288683 data_time: 0.031834 memory: 11131 loss_kpt: 0.000593 acc_pose: 0.883247 loss: 0.000593 2022/10/27 16:21:46 - mmengine - INFO - Epoch(train) [85][200/586] lr: 5.000000e-04 eta: 5:33:23 time: 0.291505 data_time: 0.028613 memory: 11131 loss_kpt: 0.000581 acc_pose: 0.884073 loss: 0.000581 2022/10/27 16:22:00 - mmengine - INFO - Epoch(train) [85][250/586] lr: 5.000000e-04 eta: 5:33:10 time: 0.282421 data_time: 0.027901 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.763371 loss: 0.000563 2022/10/27 16:22:15 - mmengine - INFO - Epoch(train) [85][300/586] lr: 5.000000e-04 eta: 5:32:58 time: 0.290582 data_time: 0.028625 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.827985 loss: 0.000590 2022/10/27 16:22:29 - mmengine - INFO - Epoch(train) [85][350/586] lr: 5.000000e-04 eta: 5:32:46 time: 0.287277 data_time: 0.031886 memory: 11131 loss_kpt: 0.000591 acc_pose: 0.776279 loss: 0.000591 2022/10/27 16:22:44 - mmengine - INFO - Epoch(train) [85][400/586] lr: 5.000000e-04 eta: 5:32:33 time: 0.286533 data_time: 0.031448 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.870606 loss: 0.000589 2022/10/27 16:22:58 - mmengine - INFO - Epoch(train) [85][450/586] lr: 5.000000e-04 eta: 5:32:21 time: 0.286981 data_time: 0.028522 memory: 11131 loss_kpt: 0.000575 acc_pose: 0.853153 loss: 0.000575 2022/10/27 16:23:13 - mmengine - INFO - Epoch(train) [85][500/586] lr: 5.000000e-04 eta: 5:32:09 time: 0.292129 data_time: 0.028458 memory: 11131 loss_kpt: 0.000610 acc_pose: 0.790499 loss: 0.000610 2022/10/27 16:23:27 - mmengine - INFO - Epoch(train) [85][550/586] lr: 5.000000e-04 eta: 5:31:56 time: 0.285436 data_time: 0.027166 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.788151 loss: 0.000585 2022/10/27 16:23:37 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:23:52 - mmengine - INFO - Epoch(train) [86][50/586] lr: 5.000000e-04 eta: 5:31:20 time: 0.293594 data_time: 0.042316 memory: 11131 loss_kpt: 0.000578 acc_pose: 0.778537 loss: 0.000578 2022/10/27 16:24:06 - mmengine - INFO - Epoch(train) [86][100/586] lr: 5.000000e-04 eta: 5:31:08 time: 0.287544 data_time: 0.028170 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.844325 loss: 0.000584 2022/10/27 16:24:21 - mmengine - INFO - Epoch(train) [86][150/586] lr: 5.000000e-04 eta: 5:30:55 time: 0.290870 data_time: 0.029072 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.857821 loss: 0.000580 2022/10/27 16:24:32 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:24:35 - mmengine - INFO - Epoch(train) [86][200/586] lr: 5.000000e-04 eta: 5:30:43 time: 0.285278 data_time: 0.033416 memory: 11131 loss_kpt: 0.000587 acc_pose: 0.902608 loss: 0.000587 2022/10/27 16:24:49 - mmengine - INFO - Epoch(train) [86][250/586] lr: 5.000000e-04 eta: 5:30:30 time: 0.287975 data_time: 0.032777 memory: 11131 loss_kpt: 0.000614 acc_pose: 0.760079 loss: 0.000614 2022/10/27 16:25:04 - mmengine - INFO - Epoch(train) [86][300/586] lr: 5.000000e-04 eta: 5:30:18 time: 0.289906 data_time: 0.027591 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.876507 loss: 0.000589 2022/10/27 16:25:18 - mmengine - INFO - Epoch(train) [86][350/586] lr: 5.000000e-04 eta: 5:30:05 time: 0.282644 data_time: 0.029638 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.814448 loss: 0.000584 2022/10/27 16:25:33 - mmengine - INFO - Epoch(train) [86][400/586] lr: 5.000000e-04 eta: 5:29:53 time: 0.290293 data_time: 0.029562 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.853838 loss: 0.000589 2022/10/27 16:25:47 - mmengine - INFO - Epoch(train) [86][450/586] lr: 5.000000e-04 eta: 5:29:40 time: 0.282676 data_time: 0.027715 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.846465 loss: 0.000607 2022/10/27 16:26:01 - mmengine - INFO - Epoch(train) [86][500/586] lr: 5.000000e-04 eta: 5:29:28 time: 0.286973 data_time: 0.032107 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.861090 loss: 0.000585 2022/10/27 16:26:16 - mmengine - INFO - Epoch(train) [86][550/586] lr: 5.000000e-04 eta: 5:29:16 time: 0.291463 data_time: 0.028091 memory: 11131 loss_kpt: 0.000578 acc_pose: 0.819134 loss: 0.000578 2022/10/27 16:26:26 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:26:41 - mmengine - INFO - Epoch(train) [87][50/586] lr: 5.000000e-04 eta: 5:28:40 time: 0.301786 data_time: 0.035741 memory: 11131 loss_kpt: 0.000583 acc_pose: 0.831435 loss: 0.000583 2022/10/27 16:26:55 - mmengine - INFO - Epoch(train) [87][100/586] lr: 5.000000e-04 eta: 5:28:28 time: 0.283190 data_time: 0.029306 memory: 11131 loss_kpt: 0.000582 acc_pose: 0.864935 loss: 0.000582 2022/10/27 16:27:09 - mmengine - INFO - Epoch(train) [87][150/586] lr: 5.000000e-04 eta: 5:28:15 time: 0.290797 data_time: 0.036411 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.817542 loss: 0.000592 2022/10/27 16:27:24 - mmengine - INFO - Epoch(train) [87][200/586] lr: 5.000000e-04 eta: 5:28:03 time: 0.288710 data_time: 0.030787 memory: 11131 loss_kpt: 0.000601 acc_pose: 0.794731 loss: 0.000601 2022/10/27 16:27:38 - mmengine - INFO - Epoch(train) [87][250/586] lr: 5.000000e-04 eta: 5:27:51 time: 0.286143 data_time: 0.027098 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.873675 loss: 0.000589 2022/10/27 16:27:53 - mmengine - INFO - Epoch(train) [87][300/586] lr: 5.000000e-04 eta: 5:27:38 time: 0.286383 data_time: 0.026389 memory: 11131 loss_kpt: 0.000556 acc_pose: 0.862634 loss: 0.000556 2022/10/27 16:28:07 - mmengine - INFO - Epoch(train) [87][350/586] lr: 5.000000e-04 eta: 5:27:26 time: 0.289985 data_time: 0.027527 memory: 11131 loss_kpt: 0.000594 acc_pose: 0.791235 loss: 0.000594 2022/10/27 16:28:22 - mmengine - INFO - Epoch(train) [87][400/586] lr: 5.000000e-04 eta: 5:27:13 time: 0.288706 data_time: 0.027186 memory: 11131 loss_kpt: 0.000578 acc_pose: 0.808914 loss: 0.000578 2022/10/27 16:28:36 - mmengine - INFO - Epoch(train) [87][450/586] lr: 5.000000e-04 eta: 5:27:01 time: 0.284876 data_time: 0.027930 memory: 11131 loss_kpt: 0.000587 acc_pose: 0.803573 loss: 0.000587 2022/10/27 16:28:50 - mmengine - INFO - Epoch(train) [87][500/586] lr: 5.000000e-04 eta: 5:26:48 time: 0.287438 data_time: 0.027809 memory: 11131 loss_kpt: 0.000591 acc_pose: 0.808785 loss: 0.000591 2022/10/27 16:29:04 - mmengine - INFO - Epoch(train) [87][550/586] lr: 5.000000e-04 eta: 5:26:36 time: 0.286255 data_time: 0.031500 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.821933 loss: 0.000570 2022/10/27 16:29:15 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:29:21 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:29:30 - mmengine - INFO - Epoch(train) [88][50/586] lr: 5.000000e-04 eta: 5:26:01 time: 0.308866 data_time: 0.042412 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.836483 loss: 0.000568 2022/10/27 16:29:45 - mmengine - INFO - Epoch(train) [88][100/586] lr: 5.000000e-04 eta: 5:25:49 time: 0.287103 data_time: 0.029200 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.788866 loss: 0.000562 2022/10/27 16:29:59 - mmengine - INFO - Epoch(train) [88][150/586] lr: 5.000000e-04 eta: 5:25:36 time: 0.288530 data_time: 0.030018 memory: 11131 loss_kpt: 0.000582 acc_pose: 0.836484 loss: 0.000582 2022/10/27 16:30:13 - mmengine - INFO - Epoch(train) [88][200/586] lr: 5.000000e-04 eta: 5:25:24 time: 0.284175 data_time: 0.029023 memory: 11131 loss_kpt: 0.000593 acc_pose: 0.814538 loss: 0.000593 2022/10/27 16:30:28 - mmengine - INFO - Epoch(train) [88][250/586] lr: 5.000000e-04 eta: 5:25:11 time: 0.287864 data_time: 0.031665 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.919365 loss: 0.000592 2022/10/27 16:30:42 - mmengine - INFO - Epoch(train) [88][300/586] lr: 5.000000e-04 eta: 5:24:59 time: 0.286954 data_time: 0.030274 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.854092 loss: 0.000586 2022/10/27 16:30:56 - mmengine - INFO - Epoch(train) [88][350/586] lr: 5.000000e-04 eta: 5:24:46 time: 0.283503 data_time: 0.027637 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.910258 loss: 0.000584 2022/10/27 16:31:11 - mmengine - INFO - Epoch(train) [88][400/586] lr: 5.000000e-04 eta: 5:24:34 time: 0.292157 data_time: 0.027336 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.878276 loss: 0.000573 2022/10/27 16:31:25 - mmengine - INFO - Epoch(train) [88][450/586] lr: 5.000000e-04 eta: 5:24:21 time: 0.282245 data_time: 0.028404 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.816395 loss: 0.000551 2022/10/27 16:31:39 - mmengine - INFO - Epoch(train) [88][500/586] lr: 5.000000e-04 eta: 5:24:08 time: 0.287541 data_time: 0.028195 memory: 11131 loss_kpt: 0.000603 acc_pose: 0.767959 loss: 0.000603 2022/10/27 16:31:54 - mmengine - INFO - Epoch(train) [88][550/586] lr: 5.000000e-04 eta: 5:23:56 time: 0.290083 data_time: 0.029269 memory: 11131 loss_kpt: 0.000582 acc_pose: 0.837498 loss: 0.000582 2022/10/27 16:32:04 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:32:19 - mmengine - INFO - Epoch(train) [89][50/586] lr: 5.000000e-04 eta: 5:23:21 time: 0.301921 data_time: 0.036675 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.905166 loss: 0.000573 2022/10/27 16:32:33 - mmengine - INFO - Epoch(train) [89][100/586] lr: 5.000000e-04 eta: 5:23:08 time: 0.282503 data_time: 0.027508 memory: 11131 loss_kpt: 0.000571 acc_pose: 0.891632 loss: 0.000571 2022/10/27 16:32:48 - mmengine - INFO - Epoch(train) [89][150/586] lr: 5.000000e-04 eta: 5:22:56 time: 0.290429 data_time: 0.029375 memory: 11131 loss_kpt: 0.000591 acc_pose: 0.859630 loss: 0.000591 2022/10/27 16:33:03 - mmengine - INFO - Epoch(train) [89][200/586] lr: 5.000000e-04 eta: 5:22:44 time: 0.295434 data_time: 0.030045 memory: 11131 loss_kpt: 0.000566 acc_pose: 0.845374 loss: 0.000566 2022/10/27 16:33:17 - mmengine - INFO - Epoch(train) [89][250/586] lr: 5.000000e-04 eta: 5:22:31 time: 0.282632 data_time: 0.027515 memory: 11131 loss_kpt: 0.000586 acc_pose: 0.840909 loss: 0.000586 2022/10/27 16:33:31 - mmengine - INFO - Epoch(train) [89][300/586] lr: 5.000000e-04 eta: 5:22:19 time: 0.291954 data_time: 0.027473 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.896639 loss: 0.000580 2022/10/27 16:33:46 - mmengine - INFO - Epoch(train) [89][350/586] lr: 5.000000e-04 eta: 5:22:06 time: 0.283458 data_time: 0.027882 memory: 11131 loss_kpt: 0.000576 acc_pose: 0.862871 loss: 0.000576 2022/10/27 16:34:00 - mmengine - INFO - Epoch(train) [89][400/586] lr: 5.000000e-04 eta: 5:21:54 time: 0.292685 data_time: 0.032443 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.829269 loss: 0.000585 2022/10/27 16:34:09 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:34:14 - mmengine - INFO - Epoch(train) [89][450/586] lr: 5.000000e-04 eta: 5:21:42 time: 0.284692 data_time: 0.027331 memory: 11131 loss_kpt: 0.000602 acc_pose: 0.750443 loss: 0.000602 2022/10/27 16:34:29 - mmengine - INFO - Epoch(train) [89][500/586] lr: 5.000000e-04 eta: 5:21:29 time: 0.286005 data_time: 0.028256 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.803781 loss: 0.000570 2022/10/27 16:34:43 - mmengine - INFO - Epoch(train) [89][550/586] lr: 5.000000e-04 eta: 5:21:16 time: 0.285008 data_time: 0.027989 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.788958 loss: 0.000590 2022/10/27 16:34:53 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:35:08 - mmengine - INFO - Epoch(train) [90][50/586] lr: 5.000000e-04 eta: 5:20:42 time: 0.304922 data_time: 0.036889 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.866273 loss: 0.000570 2022/10/27 16:35:23 - mmengine - INFO - Epoch(train) [90][100/586] lr: 5.000000e-04 eta: 5:20:30 time: 0.292372 data_time: 0.027804 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.810502 loss: 0.000590 2022/10/27 16:35:37 - mmengine - INFO - Epoch(train) [90][150/586] lr: 5.000000e-04 eta: 5:20:17 time: 0.289069 data_time: 0.028574 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.843243 loss: 0.000592 2022/10/27 16:35:52 - mmengine - INFO - Epoch(train) [90][200/586] lr: 5.000000e-04 eta: 5:20:05 time: 0.286017 data_time: 0.030133 memory: 11131 loss_kpt: 0.000583 acc_pose: 0.876787 loss: 0.000583 2022/10/27 16:36:06 - mmengine - INFO - Epoch(train) [90][250/586] lr: 5.000000e-04 eta: 5:19:52 time: 0.285109 data_time: 0.030155 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.827433 loss: 0.000569 2022/10/27 16:36:20 - mmengine - INFO - Epoch(train) [90][300/586] lr: 5.000000e-04 eta: 5:19:40 time: 0.291636 data_time: 0.036846 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.867169 loss: 0.000589 2022/10/27 16:36:35 - mmengine - INFO - Epoch(train) [90][350/586] lr: 5.000000e-04 eta: 5:19:27 time: 0.285068 data_time: 0.027871 memory: 11131 loss_kpt: 0.000578 acc_pose: 0.909705 loss: 0.000578 2022/10/27 16:36:49 - mmengine - INFO - Epoch(train) [90][400/586] lr: 5.000000e-04 eta: 5:19:15 time: 0.288734 data_time: 0.027242 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.852263 loss: 0.000589 2022/10/27 16:37:03 - mmengine - INFO - Epoch(train) [90][450/586] lr: 5.000000e-04 eta: 5:19:02 time: 0.284849 data_time: 0.026704 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.817583 loss: 0.000580 2022/10/27 16:37:18 - mmengine - INFO - Epoch(train) [90][500/586] lr: 5.000000e-04 eta: 5:18:49 time: 0.286951 data_time: 0.031283 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.871450 loss: 0.000585 2022/10/27 16:37:32 - mmengine - INFO - Epoch(train) [90][550/586] lr: 5.000000e-04 eta: 5:18:37 time: 0.293538 data_time: 0.029422 memory: 11131 loss_kpt: 0.000588 acc_pose: 0.743606 loss: 0.000588 2022/10/27 16:37:42 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:37:42 - mmengine - INFO - Saving checkpoint at 90 epochs 2022/10/27 16:37:53 - mmengine - INFO - Epoch(val) [90][50/407] eta: 0:00:52 time: 0.148144 data_time: 0.024836 memory: 11131 2022/10/27 16:38:00 - mmengine - INFO - Epoch(val) [90][100/407] eta: 0:00:40 time: 0.131862 data_time: 0.012696 memory: 1836 2022/10/27 16:38:07 - mmengine - INFO - Epoch(val) [90][150/407] eta: 0:00:33 time: 0.132027 data_time: 0.011495 memory: 1836 2022/10/27 16:38:13 - mmengine - INFO - Epoch(val) [90][200/407] eta: 0:00:27 time: 0.134390 data_time: 0.014106 memory: 1836 2022/10/27 16:38:20 - mmengine - INFO - Epoch(val) [90][250/407] eta: 0:00:21 time: 0.134320 data_time: 0.013111 memory: 1836 2022/10/27 16:38:27 - mmengine - INFO - Epoch(val) [90][300/407] eta: 0:00:14 time: 0.140036 data_time: 0.021538 memory: 1836 2022/10/27 16:38:34 - mmengine - INFO - Epoch(val) [90][350/407] eta: 0:00:08 time: 0.149749 data_time: 0.030527 memory: 1836 2022/10/27 16:38:41 - mmengine - INFO - Epoch(val) [90][400/407] eta: 0:00:00 time: 0.132959 data_time: 0.016560 memory: 1836 2022/10/27 16:39:28 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 16:39:45 - mmengine - INFO - Epoch(val) [90][407/407] coco/AP: 0.736769 coco/AP .5: 0.899344 coco/AP .75: 0.803340 coco/AP (M): 0.694480 coco/AP (L): 0.809829 coco/AR: 0.788098 coco/AR .5: 0.935926 coco/AR .75: 0.848866 coco/AR (M): 0.741737 coco/AR (L): 0.854812 2022/10/27 16:39:45 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_70.pth is removed 2022/10/27 16:39:47 - mmengine - INFO - The best checkpoint with 0.7368 coco/AP at 90 epoch is saved to best_coco/AP_epoch_90.pth. 2022/10/27 16:40:02 - mmengine - INFO - Epoch(train) [91][50/586] lr: 5.000000e-04 eta: 5:18:02 time: 0.294165 data_time: 0.036260 memory: 11131 loss_kpt: 0.000571 acc_pose: 0.851321 loss: 0.000571 2022/10/27 16:40:16 - mmengine - INFO - Epoch(train) [91][100/586] lr: 5.000000e-04 eta: 5:17:50 time: 0.285750 data_time: 0.027502 memory: 11131 loss_kpt: 0.000574 acc_pose: 0.853644 loss: 0.000574 2022/10/27 16:40:31 - mmengine - INFO - Epoch(train) [91][150/586] lr: 5.000000e-04 eta: 5:17:37 time: 0.290645 data_time: 0.029933 memory: 11131 loss_kpt: 0.000587 acc_pose: 0.865936 loss: 0.000587 2022/10/27 16:40:45 - mmengine - INFO - Epoch(train) [91][200/586] lr: 5.000000e-04 eta: 5:17:25 time: 0.289690 data_time: 0.031246 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.858768 loss: 0.000590 2022/10/27 16:41:00 - mmengine - INFO - Epoch(train) [91][250/586] lr: 5.000000e-04 eta: 5:17:12 time: 0.284293 data_time: 0.027892 memory: 11131 loss_kpt: 0.000581 acc_pose: 0.798516 loss: 0.000581 2022/10/27 16:41:02 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:41:14 - mmengine - INFO - Epoch(train) [91][300/586] lr: 5.000000e-04 eta: 5:16:59 time: 0.282499 data_time: 0.027263 memory: 11131 loss_kpt: 0.000583 acc_pose: 0.862791 loss: 0.000583 2022/10/27 16:41:28 - mmengine - INFO - Epoch(train) [91][350/586] lr: 5.000000e-04 eta: 5:16:47 time: 0.287072 data_time: 0.030193 memory: 11131 loss_kpt: 0.000565 acc_pose: 0.879489 loss: 0.000565 2022/10/27 16:41:43 - mmengine - INFO - Epoch(train) [91][400/586] lr: 5.000000e-04 eta: 5:16:35 time: 0.291553 data_time: 0.032961 memory: 11131 loss_kpt: 0.000574 acc_pose: 0.879336 loss: 0.000574 2022/10/27 16:41:57 - mmengine - INFO - Epoch(train) [91][450/586] lr: 5.000000e-04 eta: 5:16:22 time: 0.290658 data_time: 0.027099 memory: 11131 loss_kpt: 0.000582 acc_pose: 0.844521 loss: 0.000582 2022/10/27 16:42:12 - mmengine - INFO - Epoch(train) [91][500/586] lr: 5.000000e-04 eta: 5:16:10 time: 0.286158 data_time: 0.027866 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.841485 loss: 0.000555 2022/10/27 16:42:26 - mmengine - INFO - Epoch(train) [91][550/586] lr: 5.000000e-04 eta: 5:15:57 time: 0.288637 data_time: 0.028398 memory: 11131 loss_kpt: 0.000577 acc_pose: 0.826948 loss: 0.000577 2022/10/27 16:42:36 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:42:51 - mmengine - INFO - Epoch(train) [92][50/586] lr: 5.000000e-04 eta: 5:15:23 time: 0.296477 data_time: 0.036304 memory: 11131 loss_kpt: 0.000582 acc_pose: 0.817039 loss: 0.000582 2022/10/27 16:43:06 - mmengine - INFO - Epoch(train) [92][100/586] lr: 5.000000e-04 eta: 5:15:10 time: 0.292241 data_time: 0.030656 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.848943 loss: 0.000590 2022/10/27 16:43:20 - mmengine - INFO - Epoch(train) [92][150/586] lr: 5.000000e-04 eta: 5:14:58 time: 0.287763 data_time: 0.029287 memory: 11131 loss_kpt: 0.000587 acc_pose: 0.799358 loss: 0.000587 2022/10/27 16:43:34 - mmengine - INFO - Epoch(train) [92][200/586] lr: 5.000000e-04 eta: 5:14:45 time: 0.287365 data_time: 0.029679 memory: 11131 loss_kpt: 0.000597 acc_pose: 0.828824 loss: 0.000597 2022/10/27 16:43:49 - mmengine - INFO - Epoch(train) [92][250/586] lr: 5.000000e-04 eta: 5:14:33 time: 0.288908 data_time: 0.028707 memory: 11131 loss_kpt: 0.000566 acc_pose: 0.862802 loss: 0.000566 2022/10/27 16:44:03 - mmengine - INFO - Epoch(train) [92][300/586] lr: 5.000000e-04 eta: 5:14:20 time: 0.288733 data_time: 0.030004 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.911993 loss: 0.000573 2022/10/27 16:44:18 - mmengine - INFO - Epoch(train) [92][350/586] lr: 5.000000e-04 eta: 5:14:08 time: 0.285605 data_time: 0.028284 memory: 11131 loss_kpt: 0.000607 acc_pose: 0.846858 loss: 0.000607 2022/10/27 16:44:32 - mmengine - INFO - Epoch(train) [92][400/586] lr: 5.000000e-04 eta: 5:13:55 time: 0.289029 data_time: 0.027437 memory: 11131 loss_kpt: 0.000587 acc_pose: 0.776169 loss: 0.000587 2022/10/27 16:44:46 - mmengine - INFO - Epoch(train) [92][450/586] lr: 5.000000e-04 eta: 5:13:43 time: 0.284809 data_time: 0.028476 memory: 11131 loss_kpt: 0.000572 acc_pose: 0.803689 loss: 0.000572 2022/10/27 16:45:01 - mmengine - INFO - Epoch(train) [92][500/586] lr: 5.000000e-04 eta: 5:13:30 time: 0.293452 data_time: 0.030923 memory: 11131 loss_kpt: 0.000571 acc_pose: 0.877184 loss: 0.000571 2022/10/27 16:45:15 - mmengine - INFO - Epoch(train) [92][550/586] lr: 5.000000e-04 eta: 5:13:18 time: 0.289205 data_time: 0.028523 memory: 11131 loss_kpt: 0.000579 acc_pose: 0.786352 loss: 0.000579 2022/10/27 16:45:25 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:45:40 - mmengine - INFO - Epoch(train) [93][50/586] lr: 5.000000e-04 eta: 5:12:44 time: 0.296577 data_time: 0.036430 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.771063 loss: 0.000585 2022/10/27 16:45:51 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:45:55 - mmengine - INFO - Epoch(train) [93][100/586] lr: 5.000000e-04 eta: 5:12:31 time: 0.285852 data_time: 0.028909 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.824244 loss: 0.000562 2022/10/27 16:46:09 - mmengine - INFO - Epoch(train) [93][150/586] lr: 5.000000e-04 eta: 5:12:19 time: 0.291205 data_time: 0.032614 memory: 11131 loss_kpt: 0.000579 acc_pose: 0.832370 loss: 0.000579 2022/10/27 16:46:24 - mmengine - INFO - Epoch(train) [93][200/586] lr: 5.000000e-04 eta: 5:12:06 time: 0.289091 data_time: 0.029320 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.869466 loss: 0.000573 2022/10/27 16:46:38 - mmengine - INFO - Epoch(train) [93][250/586] lr: 5.000000e-04 eta: 5:11:53 time: 0.283907 data_time: 0.029733 memory: 11131 loss_kpt: 0.000601 acc_pose: 0.807221 loss: 0.000601 2022/10/27 16:46:52 - mmengine - INFO - Epoch(train) [93][300/586] lr: 5.000000e-04 eta: 5:11:41 time: 0.286932 data_time: 0.029598 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.814195 loss: 0.000584 2022/10/27 16:47:07 - mmengine - INFO - Epoch(train) [93][350/586] lr: 5.000000e-04 eta: 5:11:28 time: 0.291390 data_time: 0.031398 memory: 11131 loss_kpt: 0.000595 acc_pose: 0.814646 loss: 0.000595 2022/10/27 16:47:21 - mmengine - INFO - Epoch(train) [93][400/586] lr: 5.000000e-04 eta: 5:11:16 time: 0.285708 data_time: 0.027914 memory: 11131 loss_kpt: 0.000572 acc_pose: 0.782985 loss: 0.000572 2022/10/27 16:47:35 - mmengine - INFO - Epoch(train) [93][450/586] lr: 5.000000e-04 eta: 5:11:03 time: 0.287963 data_time: 0.030588 memory: 11131 loss_kpt: 0.000577 acc_pose: 0.855936 loss: 0.000577 2022/10/27 16:47:50 - mmengine - INFO - Epoch(train) [93][500/586] lr: 5.000000e-04 eta: 5:10:51 time: 0.289076 data_time: 0.029581 memory: 11131 loss_kpt: 0.000579 acc_pose: 0.781539 loss: 0.000579 2022/10/27 16:48:04 - mmengine - INFO - Epoch(train) [93][550/586] lr: 5.000000e-04 eta: 5:10:38 time: 0.284520 data_time: 0.029398 memory: 11131 loss_kpt: 0.000579 acc_pose: 0.858192 loss: 0.000579 2022/10/27 16:48:14 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:48:29 - mmengine - INFO - Epoch(train) [94][50/586] lr: 5.000000e-04 eta: 5:10:04 time: 0.299192 data_time: 0.041698 memory: 11131 loss_kpt: 0.000572 acc_pose: 0.748076 loss: 0.000572 2022/10/27 16:48:44 - mmengine - INFO - Epoch(train) [94][100/586] lr: 5.000000e-04 eta: 5:09:51 time: 0.287821 data_time: 0.030433 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.871361 loss: 0.000580 2022/10/27 16:48:58 - mmengine - INFO - Epoch(train) [94][150/586] lr: 5.000000e-04 eta: 5:09:39 time: 0.287426 data_time: 0.030146 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.791308 loss: 0.000585 2022/10/27 16:49:12 - mmengine - INFO - Epoch(train) [94][200/586] lr: 5.000000e-04 eta: 5:09:26 time: 0.286582 data_time: 0.029588 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.889230 loss: 0.000592 2022/10/27 16:49:27 - mmengine - INFO - Epoch(train) [94][250/586] lr: 5.000000e-04 eta: 5:09:14 time: 0.286019 data_time: 0.028500 memory: 11131 loss_kpt: 0.000565 acc_pose: 0.900193 loss: 0.000565 2022/10/27 16:49:41 - mmengine - INFO - Epoch(train) [94][300/586] lr: 5.000000e-04 eta: 5:09:01 time: 0.291588 data_time: 0.029120 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.906462 loss: 0.000568 2022/10/27 16:49:55 - mmengine - INFO - Epoch(train) [94][350/586] lr: 5.000000e-04 eta: 5:08:48 time: 0.282799 data_time: 0.029270 memory: 11131 loss_kpt: 0.000583 acc_pose: 0.779254 loss: 0.000583 2022/10/27 16:50:10 - mmengine - INFO - Epoch(train) [94][400/586] lr: 5.000000e-04 eta: 5:08:36 time: 0.288285 data_time: 0.029641 memory: 11131 loss_kpt: 0.000595 acc_pose: 0.850044 loss: 0.000595 2022/10/27 16:50:24 - mmengine - INFO - Epoch(train) [94][450/586] lr: 5.000000e-04 eta: 5:08:23 time: 0.286518 data_time: 0.030334 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.835929 loss: 0.000568 2022/10/27 16:50:39 - mmengine - INFO - Epoch(train) [94][500/586] lr: 5.000000e-04 eta: 5:08:11 time: 0.296487 data_time: 0.031653 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.823171 loss: 0.000592 2022/10/27 16:50:39 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:50:53 - mmengine - INFO - Epoch(train) [94][550/586] lr: 5.000000e-04 eta: 5:07:58 time: 0.288480 data_time: 0.027596 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.845585 loss: 0.000561 2022/10/27 16:51:03 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:51:18 - mmengine - INFO - Epoch(train) [95][50/586] lr: 5.000000e-04 eta: 5:07:25 time: 0.300143 data_time: 0.041017 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.837889 loss: 0.000568 2022/10/27 16:51:33 - mmengine - INFO - Epoch(train) [95][100/586] lr: 5.000000e-04 eta: 5:07:12 time: 0.287354 data_time: 0.028711 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.766475 loss: 0.000568 2022/10/27 16:51:47 - mmengine - INFO - Epoch(train) [95][150/586] lr: 5.000000e-04 eta: 5:07:00 time: 0.289294 data_time: 0.034314 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.884457 loss: 0.000569 2022/10/27 16:52:02 - mmengine - INFO - Epoch(train) [95][200/586] lr: 5.000000e-04 eta: 5:06:47 time: 0.291875 data_time: 0.029136 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.847031 loss: 0.000590 2022/10/27 16:52:16 - mmengine - INFO - Epoch(train) [95][250/586] lr: 5.000000e-04 eta: 5:06:35 time: 0.288875 data_time: 0.030129 memory: 11131 loss_kpt: 0.000593 acc_pose: 0.832875 loss: 0.000593 2022/10/27 16:52:31 - mmengine - INFO - Epoch(train) [95][300/586] lr: 5.000000e-04 eta: 5:06:22 time: 0.286544 data_time: 0.030646 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.842481 loss: 0.000557 2022/10/27 16:52:45 - mmengine - INFO - Epoch(train) [95][350/586] lr: 5.000000e-04 eta: 5:06:09 time: 0.283364 data_time: 0.027701 memory: 11131 loss_kpt: 0.000577 acc_pose: 0.874695 loss: 0.000577 2022/10/27 16:52:59 - mmengine - INFO - Epoch(train) [95][400/586] lr: 5.000000e-04 eta: 5:05:57 time: 0.290094 data_time: 0.032364 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.844173 loss: 0.000573 2022/10/27 16:53:14 - mmengine - INFO - Epoch(train) [95][450/586] lr: 5.000000e-04 eta: 5:05:44 time: 0.285385 data_time: 0.026357 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.887977 loss: 0.000590 2022/10/27 16:53:28 - mmengine - INFO - Epoch(train) [95][500/586] lr: 5.000000e-04 eta: 5:05:32 time: 0.287666 data_time: 0.029853 memory: 11131 loss_kpt: 0.000574 acc_pose: 0.849668 loss: 0.000574 2022/10/27 16:53:42 - mmengine - INFO - Epoch(train) [95][550/586] lr: 5.000000e-04 eta: 5:05:19 time: 0.284579 data_time: 0.028284 memory: 11131 loss_kpt: 0.000582 acc_pose: 0.896924 loss: 0.000582 2022/10/27 16:53:52 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:54:07 - mmengine - INFO - Epoch(train) [96][50/586] lr: 5.000000e-04 eta: 5:04:45 time: 0.296567 data_time: 0.035925 memory: 11131 loss_kpt: 0.000571 acc_pose: 0.854576 loss: 0.000571 2022/10/27 16:54:21 - mmengine - INFO - Epoch(train) [96][100/586] lr: 5.000000e-04 eta: 5:04:32 time: 0.287904 data_time: 0.026506 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.815375 loss: 0.000562 2022/10/27 16:54:36 - mmengine - INFO - Epoch(train) [96][150/586] lr: 5.000000e-04 eta: 5:04:20 time: 0.289504 data_time: 0.030723 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.876122 loss: 0.000557 2022/10/27 16:54:50 - mmengine - INFO - Epoch(train) [96][200/586] lr: 5.000000e-04 eta: 5:04:07 time: 0.284497 data_time: 0.028156 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.881505 loss: 0.000584 2022/10/27 16:55:04 - mmengine - INFO - Epoch(train) [96][250/586] lr: 5.000000e-04 eta: 5:03:55 time: 0.287209 data_time: 0.033901 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.906475 loss: 0.000570 2022/10/27 16:55:19 - mmengine - INFO - Epoch(train) [96][300/586] lr: 5.000000e-04 eta: 5:03:42 time: 0.287151 data_time: 0.027161 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.875916 loss: 0.000561 2022/10/27 16:55:28 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:55:33 - mmengine - INFO - Epoch(train) [96][350/586] lr: 5.000000e-04 eta: 5:03:29 time: 0.292014 data_time: 0.029592 memory: 11131 loss_kpt: 0.000576 acc_pose: 0.810327 loss: 0.000576 2022/10/27 16:55:48 - mmengine - INFO - Epoch(train) [96][400/586] lr: 5.000000e-04 eta: 5:03:17 time: 0.288873 data_time: 0.027959 memory: 11131 loss_kpt: 0.000583 acc_pose: 0.907706 loss: 0.000583 2022/10/27 16:56:02 - mmengine - INFO - Epoch(train) [96][450/586] lr: 5.000000e-04 eta: 5:03:04 time: 0.284942 data_time: 0.026822 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.844974 loss: 0.000580 2022/10/27 16:56:16 - mmengine - INFO - Epoch(train) [96][500/586] lr: 5.000000e-04 eta: 5:02:51 time: 0.286903 data_time: 0.027148 memory: 11131 loss_kpt: 0.000583 acc_pose: 0.839238 loss: 0.000583 2022/10/27 16:56:31 - mmengine - INFO - Epoch(train) [96][550/586] lr: 5.000000e-04 eta: 5:02:39 time: 0.290261 data_time: 0.028864 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.848761 loss: 0.000584 2022/10/27 16:56:41 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:56:56 - mmengine - INFO - Epoch(train) [97][50/586] lr: 5.000000e-04 eta: 5:02:06 time: 0.302451 data_time: 0.039631 memory: 11131 loss_kpt: 0.000578 acc_pose: 0.802968 loss: 0.000578 2022/10/27 16:57:10 - mmengine - INFO - Epoch(train) [97][100/586] lr: 5.000000e-04 eta: 5:01:53 time: 0.285764 data_time: 0.031762 memory: 11131 loss_kpt: 0.000572 acc_pose: 0.789145 loss: 0.000572 2022/10/27 16:57:25 - mmengine - INFO - Epoch(train) [97][150/586] lr: 5.000000e-04 eta: 5:01:41 time: 0.288675 data_time: 0.027688 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.844966 loss: 0.000568 2022/10/27 16:57:39 - mmengine - INFO - Epoch(train) [97][200/586] lr: 5.000000e-04 eta: 5:01:28 time: 0.289168 data_time: 0.029015 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.838285 loss: 0.000558 2022/10/27 16:57:54 - mmengine - INFO - Epoch(train) [97][250/586] lr: 5.000000e-04 eta: 5:01:15 time: 0.288365 data_time: 0.027458 memory: 11131 loss_kpt: 0.000556 acc_pose: 0.811516 loss: 0.000556 2022/10/27 16:58:08 - mmengine - INFO - Epoch(train) [97][300/586] lr: 5.000000e-04 eta: 5:01:03 time: 0.290330 data_time: 0.028384 memory: 11131 loss_kpt: 0.000566 acc_pose: 0.870491 loss: 0.000566 2022/10/27 16:58:23 - mmengine - INFO - Epoch(train) [97][350/586] lr: 5.000000e-04 eta: 5:00:50 time: 0.286409 data_time: 0.026585 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.822583 loss: 0.000562 2022/10/27 16:58:37 - mmengine - INFO - Epoch(train) [97][400/586] lr: 5.000000e-04 eta: 5:00:38 time: 0.288474 data_time: 0.035356 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.882674 loss: 0.000562 2022/10/27 16:58:52 - mmengine - INFO - Epoch(train) [97][450/586] lr: 5.000000e-04 eta: 5:00:25 time: 0.291394 data_time: 0.027174 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.816331 loss: 0.000570 2022/10/27 16:59:06 - mmengine - INFO - Epoch(train) [97][500/586] lr: 5.000000e-04 eta: 5:00:13 time: 0.290749 data_time: 0.031996 memory: 11131 loss_kpt: 0.000581 acc_pose: 0.892043 loss: 0.000581 2022/10/27 16:59:20 - mmengine - INFO - Epoch(train) [97][550/586] lr: 5.000000e-04 eta: 5:00:00 time: 0.280937 data_time: 0.027653 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.835772 loss: 0.000551 2022/10/27 16:59:31 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 16:59:46 - mmengine - INFO - Epoch(train) [98][50/586] lr: 5.000000e-04 eta: 4:59:27 time: 0.300562 data_time: 0.041744 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.848486 loss: 0.000561 2022/10/27 17:00:00 - mmengine - INFO - Epoch(train) [98][100/586] lr: 5.000000e-04 eta: 4:59:14 time: 0.293401 data_time: 0.029082 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.847619 loss: 0.000562 2022/10/27 17:00:14 - mmengine - INFO - Epoch(train) [98][150/586] lr: 5.000000e-04 eta: 4:59:02 time: 0.284862 data_time: 0.031782 memory: 11131 loss_kpt: 0.000574 acc_pose: 0.843216 loss: 0.000574 2022/10/27 17:00:17 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:00:29 - mmengine - INFO - Epoch(train) [98][200/586] lr: 5.000000e-04 eta: 4:58:49 time: 0.286288 data_time: 0.029159 memory: 11131 loss_kpt: 0.000550 acc_pose: 0.916060 loss: 0.000550 2022/10/27 17:00:44 - mmengine - INFO - Epoch(train) [98][250/586] lr: 5.000000e-04 eta: 4:58:37 time: 0.294260 data_time: 0.028791 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.842903 loss: 0.000580 2022/10/27 17:00:58 - mmengine - INFO - Epoch(train) [98][300/586] lr: 5.000000e-04 eta: 4:58:24 time: 0.292564 data_time: 0.027412 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.814933 loss: 0.000568 2022/10/27 17:01:12 - mmengine - INFO - Epoch(train) [98][350/586] lr: 5.000000e-04 eta: 4:58:11 time: 0.286799 data_time: 0.031107 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.822732 loss: 0.000558 2022/10/27 17:01:27 - mmengine - INFO - Epoch(train) [98][400/586] lr: 5.000000e-04 eta: 4:57:59 time: 0.287798 data_time: 0.029635 memory: 11131 loss_kpt: 0.000572 acc_pose: 0.832942 loss: 0.000572 2022/10/27 17:01:41 - mmengine - INFO - Epoch(train) [98][450/586] lr: 5.000000e-04 eta: 4:57:46 time: 0.283808 data_time: 0.028587 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.856317 loss: 0.000584 2022/10/27 17:01:55 - mmengine - INFO - Epoch(train) [98][500/586] lr: 5.000000e-04 eta: 4:57:33 time: 0.286502 data_time: 0.027576 memory: 11131 loss_kpt: 0.000601 acc_pose: 0.890914 loss: 0.000601 2022/10/27 17:02:10 - mmengine - INFO - Epoch(train) [98][550/586] lr: 5.000000e-04 eta: 4:57:21 time: 0.295457 data_time: 0.028520 memory: 11131 loss_kpt: 0.000565 acc_pose: 0.828889 loss: 0.000565 2022/10/27 17:02:20 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:02:35 - mmengine - INFO - Epoch(train) [99][50/586] lr: 5.000000e-04 eta: 4:56:48 time: 0.301036 data_time: 0.036606 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.833771 loss: 0.000580 2022/10/27 17:02:50 - mmengine - INFO - Epoch(train) [99][100/586] lr: 5.000000e-04 eta: 4:56:35 time: 0.284312 data_time: 0.029472 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.888933 loss: 0.000558 2022/10/27 17:03:04 - mmengine - INFO - Epoch(train) [99][150/586] lr: 5.000000e-04 eta: 4:56:23 time: 0.286299 data_time: 0.029371 memory: 11131 loss_kpt: 0.000575 acc_pose: 0.722572 loss: 0.000575 2022/10/27 17:03:19 - mmengine - INFO - Epoch(train) [99][200/586] lr: 5.000000e-04 eta: 4:56:10 time: 0.290826 data_time: 0.031196 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.870099 loss: 0.000569 2022/10/27 17:03:33 - mmengine - INFO - Epoch(train) [99][250/586] lr: 5.000000e-04 eta: 4:55:57 time: 0.286205 data_time: 0.027710 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.853637 loss: 0.000584 2022/10/27 17:03:47 - mmengine - INFO - Epoch(train) [99][300/586] lr: 5.000000e-04 eta: 4:55:45 time: 0.292520 data_time: 0.030817 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.758276 loss: 0.000584 2022/10/27 17:04:02 - mmengine - INFO - Epoch(train) [99][350/586] lr: 5.000000e-04 eta: 4:55:32 time: 0.283506 data_time: 0.028183 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.915807 loss: 0.000568 2022/10/27 17:04:16 - mmengine - INFO - Epoch(train) [99][400/586] lr: 5.000000e-04 eta: 4:55:19 time: 0.285429 data_time: 0.027873 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.913605 loss: 0.000573 2022/10/27 17:04:30 - mmengine - INFO - Epoch(train) [99][450/586] lr: 5.000000e-04 eta: 4:55:07 time: 0.291308 data_time: 0.028188 memory: 11131 loss_kpt: 0.000590 acc_pose: 0.800586 loss: 0.000590 2022/10/27 17:04:45 - mmengine - INFO - Epoch(train) [99][500/586] lr: 5.000000e-04 eta: 4:54:54 time: 0.286362 data_time: 0.030728 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.812437 loss: 0.000551 2022/10/27 17:04:59 - mmengine - INFO - Epoch(train) [99][550/586] lr: 5.000000e-04 eta: 4:54:41 time: 0.286681 data_time: 0.028696 memory: 11131 loss_kpt: 0.000576 acc_pose: 0.794902 loss: 0.000576 2022/10/27 17:05:06 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:05:09 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:05:25 - mmengine - INFO - Epoch(train) [100][50/586] lr: 5.000000e-04 eta: 4:54:09 time: 0.302000 data_time: 0.043070 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.849605 loss: 0.000564 2022/10/27 17:05:39 - mmengine - INFO - Epoch(train) [100][100/586] lr: 5.000000e-04 eta: 4:53:56 time: 0.289514 data_time: 0.026905 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.864552 loss: 0.000564 2022/10/27 17:05:53 - mmengine - INFO - Epoch(train) [100][150/586] lr: 5.000000e-04 eta: 4:53:43 time: 0.285920 data_time: 0.029567 memory: 11131 loss_kpt: 0.000565 acc_pose: 0.812938 loss: 0.000565 2022/10/27 17:06:08 - mmengine - INFO - Epoch(train) [100][200/586] lr: 5.000000e-04 eta: 4:53:30 time: 0.285112 data_time: 0.028676 memory: 11131 loss_kpt: 0.000576 acc_pose: 0.800823 loss: 0.000576 2022/10/27 17:06:22 - mmengine - INFO - Epoch(train) [100][250/586] lr: 5.000000e-04 eta: 4:53:18 time: 0.288816 data_time: 0.029572 memory: 11131 loss_kpt: 0.000566 acc_pose: 0.873804 loss: 0.000566 2022/10/27 17:06:37 - mmengine - INFO - Epoch(train) [100][300/586] lr: 5.000000e-04 eta: 4:53:05 time: 0.292650 data_time: 0.032112 memory: 11131 loss_kpt: 0.000566 acc_pose: 0.884250 loss: 0.000566 2022/10/27 17:06:51 - mmengine - INFO - Epoch(train) [100][350/586] lr: 5.000000e-04 eta: 4:52:53 time: 0.285408 data_time: 0.028855 memory: 11131 loss_kpt: 0.000581 acc_pose: 0.874315 loss: 0.000581 2022/10/27 17:07:05 - mmengine - INFO - Epoch(train) [100][400/586] lr: 5.000000e-04 eta: 4:52:40 time: 0.287015 data_time: 0.030775 memory: 11131 loss_kpt: 0.000604 acc_pose: 0.862907 loss: 0.000604 2022/10/27 17:07:20 - mmengine - INFO - Epoch(train) [100][450/586] lr: 5.000000e-04 eta: 4:52:27 time: 0.285331 data_time: 0.029059 memory: 11131 loss_kpt: 0.000571 acc_pose: 0.869933 loss: 0.000571 2022/10/27 17:07:34 - mmengine - INFO - Epoch(train) [100][500/586] lr: 5.000000e-04 eta: 4:52:14 time: 0.285587 data_time: 0.029485 memory: 11131 loss_kpt: 0.000578 acc_pose: 0.830845 loss: 0.000578 2022/10/27 17:07:48 - mmengine - INFO - Epoch(train) [100][550/586] lr: 5.000000e-04 eta: 4:52:02 time: 0.291610 data_time: 0.031791 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.873565 loss: 0.000561 2022/10/27 17:07:59 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:07:59 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/10/27 17:08:09 - mmengine - INFO - Epoch(val) [100][50/407] eta: 0:00:50 time: 0.141268 data_time: 0.022970 memory: 11131 2022/10/27 17:08:16 - mmengine - INFO - Epoch(val) [100][100/407] eta: 0:00:41 time: 0.133761 data_time: 0.015205 memory: 1836 2022/10/27 17:08:23 - mmengine - INFO - Epoch(val) [100][150/407] eta: 0:00:35 time: 0.136930 data_time: 0.017640 memory: 1836 2022/10/27 17:08:30 - mmengine - INFO - Epoch(val) [100][200/407] eta: 0:00:27 time: 0.132453 data_time: 0.011914 memory: 1836 2022/10/27 17:08:37 - mmengine - INFO - Epoch(val) [100][250/407] eta: 0:00:22 time: 0.146123 data_time: 0.025797 memory: 1836 2022/10/27 17:08:44 - mmengine - INFO - Epoch(val) [100][300/407] eta: 0:00:14 time: 0.139392 data_time: 0.019399 memory: 1836 2022/10/27 17:08:51 - mmengine - INFO - Epoch(val) [100][350/407] eta: 0:00:07 time: 0.133570 data_time: 0.014211 memory: 1836 2022/10/27 17:08:57 - mmengine - INFO - Epoch(val) [100][400/407] eta: 0:00:00 time: 0.133802 data_time: 0.018499 memory: 1836 2022/10/27 17:09:44 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 17:10:02 - mmengine - INFO - Epoch(val) [100][407/407] coco/AP: 0.739558 coco/AP .5: 0.901186 coco/AP .75: 0.808358 coco/AP (M): 0.698001 coco/AP (L): 0.810361 coco/AR: 0.789673 coco/AR .5: 0.937343 coco/AR .75: 0.851228 coco/AR (M): 0.744387 coco/AR (L): 0.855295 2022/10/27 17:10:02 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_90.pth is removed 2022/10/27 17:10:04 - mmengine - INFO - The best checkpoint with 0.7396 coco/AP at 100 epoch is saved to best_coco/AP_epoch_100.pth. 2022/10/27 17:10:19 - mmengine - INFO - Epoch(train) [101][50/586] lr: 5.000000e-04 eta: 4:51:29 time: 0.297534 data_time: 0.040841 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.730929 loss: 0.000563 2022/10/27 17:10:33 - mmengine - INFO - Epoch(train) [101][100/586] lr: 5.000000e-04 eta: 4:51:16 time: 0.290515 data_time: 0.026827 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.856671 loss: 0.000573 2022/10/27 17:10:48 - mmengine - INFO - Epoch(train) [101][150/586] lr: 5.000000e-04 eta: 4:51:04 time: 0.287438 data_time: 0.027955 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.865487 loss: 0.000589 2022/10/27 17:11:02 - mmengine - INFO - Epoch(train) [101][200/586] lr: 5.000000e-04 eta: 4:50:51 time: 0.291009 data_time: 0.028856 memory: 11131 loss_kpt: 0.000572 acc_pose: 0.795977 loss: 0.000572 2022/10/27 17:11:16 - mmengine - INFO - Epoch(train) [101][250/586] lr: 5.000000e-04 eta: 4:50:38 time: 0.283914 data_time: 0.030519 memory: 11131 loss_kpt: 0.000553 acc_pose: 0.816109 loss: 0.000553 2022/10/27 17:11:31 - mmengine - INFO - Epoch(train) [101][300/586] lr: 5.000000e-04 eta: 4:50:26 time: 0.288798 data_time: 0.028427 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.837011 loss: 0.000569 2022/10/27 17:11:45 - mmengine - INFO - Epoch(train) [101][350/586] lr: 5.000000e-04 eta: 4:50:13 time: 0.288900 data_time: 0.029990 memory: 11131 loss_kpt: 0.000582 acc_pose: 0.850760 loss: 0.000582 2022/10/27 17:11:59 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:11:59 - mmengine - INFO - Epoch(train) [101][400/586] lr: 5.000000e-04 eta: 4:50:00 time: 0.282933 data_time: 0.028311 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.886255 loss: 0.000548 2022/10/27 17:12:14 - mmengine - INFO - Epoch(train) [101][450/586] lr: 5.000000e-04 eta: 4:49:47 time: 0.288821 data_time: 0.026997 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.893333 loss: 0.000562 2022/10/27 17:12:28 - mmengine - INFO - Epoch(train) [101][500/586] lr: 5.000000e-04 eta: 4:49:35 time: 0.289811 data_time: 0.028474 memory: 11131 loss_kpt: 0.000565 acc_pose: 0.880454 loss: 0.000565 2022/10/27 17:12:43 - mmengine - INFO - Epoch(train) [101][550/586] lr: 5.000000e-04 eta: 4:49:22 time: 0.289364 data_time: 0.031111 memory: 11131 loss_kpt: 0.000582 acc_pose: 0.920158 loss: 0.000582 2022/10/27 17:12:53 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:13:08 - mmengine - INFO - Epoch(train) [102][50/586] lr: 5.000000e-04 eta: 4:48:50 time: 0.296028 data_time: 0.036703 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.898844 loss: 0.000570 2022/10/27 17:13:22 - mmengine - INFO - Epoch(train) [102][100/586] lr: 5.000000e-04 eta: 4:48:37 time: 0.291835 data_time: 0.034541 memory: 11131 loss_kpt: 0.000579 acc_pose: 0.790011 loss: 0.000579 2022/10/27 17:13:36 - mmengine - INFO - Epoch(train) [102][150/586] lr: 5.000000e-04 eta: 4:48:24 time: 0.285093 data_time: 0.027578 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.846983 loss: 0.000564 2022/10/27 17:13:51 - mmengine - INFO - Epoch(train) [102][200/586] lr: 5.000000e-04 eta: 4:48:12 time: 0.294267 data_time: 0.035825 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.820742 loss: 0.000561 2022/10/27 17:14:05 - mmengine - INFO - Epoch(train) [102][250/586] lr: 5.000000e-04 eta: 4:47:59 time: 0.280509 data_time: 0.028936 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.895759 loss: 0.000569 2022/10/27 17:14:20 - mmengine - INFO - Epoch(train) [102][300/586] lr: 5.000000e-04 eta: 4:47:46 time: 0.291626 data_time: 0.027596 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.811363 loss: 0.000573 2022/10/27 17:14:34 - mmengine - INFO - Epoch(train) [102][350/586] lr: 5.000000e-04 eta: 4:47:33 time: 0.285301 data_time: 0.027865 memory: 11131 loss_kpt: 0.000565 acc_pose: 0.844886 loss: 0.000565 2022/10/27 17:14:48 - mmengine - INFO - Epoch(train) [102][400/586] lr: 5.000000e-04 eta: 4:47:21 time: 0.289299 data_time: 0.030158 memory: 11131 loss_kpt: 0.000582 acc_pose: 0.799696 loss: 0.000582 2022/10/27 17:15:03 - mmengine - INFO - Epoch(train) [102][450/586] lr: 5.000000e-04 eta: 4:47:08 time: 0.294373 data_time: 0.031751 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.862859 loss: 0.000568 2022/10/27 17:15:17 - mmengine - INFO - Epoch(train) [102][500/586] lr: 5.000000e-04 eta: 4:46:56 time: 0.284719 data_time: 0.027034 memory: 11131 loss_kpt: 0.000578 acc_pose: 0.891993 loss: 0.000578 2022/10/27 17:15:32 - mmengine - INFO - Epoch(train) [102][550/586] lr: 5.000000e-04 eta: 4:46:43 time: 0.291455 data_time: 0.031372 memory: 11131 loss_kpt: 0.000575 acc_pose: 0.834450 loss: 0.000575 2022/10/27 17:15:42 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:15:57 - mmengine - INFO - Epoch(train) [103][50/586] lr: 5.000000e-04 eta: 4:46:11 time: 0.298977 data_time: 0.040381 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.899470 loss: 0.000543 2022/10/27 17:16:12 - mmengine - INFO - Epoch(train) [103][100/586] lr: 5.000000e-04 eta: 4:45:58 time: 0.290076 data_time: 0.032028 memory: 11131 loss_kpt: 0.000584 acc_pose: 0.887401 loss: 0.000584 2022/10/27 17:16:26 - mmengine - INFO - Epoch(train) [103][150/586] lr: 5.000000e-04 eta: 4:45:45 time: 0.281613 data_time: 0.029716 memory: 11131 loss_kpt: 0.000577 acc_pose: 0.909712 loss: 0.000577 2022/10/27 17:16:40 - mmengine - INFO - Epoch(train) [103][200/586] lr: 5.000000e-04 eta: 4:45:33 time: 0.296022 data_time: 0.027259 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.839501 loss: 0.000562 2022/10/27 17:16:48 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:16:55 - mmengine - INFO - Epoch(train) [103][250/586] lr: 5.000000e-04 eta: 4:45:20 time: 0.284243 data_time: 0.030550 memory: 11131 loss_kpt: 0.000578 acc_pose: 0.859315 loss: 0.000578 2022/10/27 17:17:09 - mmengine - INFO - Epoch(train) [103][300/586] lr: 5.000000e-04 eta: 4:45:07 time: 0.290406 data_time: 0.035177 memory: 11131 loss_kpt: 0.000589 acc_pose: 0.878874 loss: 0.000589 2022/10/27 17:17:24 - mmengine - INFO - Epoch(train) [103][350/586] lr: 5.000000e-04 eta: 4:44:55 time: 0.288019 data_time: 0.028187 memory: 11131 loss_kpt: 0.000559 acc_pose: 0.867744 loss: 0.000559 2022/10/27 17:17:38 - mmengine - INFO - Epoch(train) [103][400/586] lr: 5.000000e-04 eta: 4:44:42 time: 0.286167 data_time: 0.027781 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.864252 loss: 0.000561 2022/10/27 17:17:52 - mmengine - INFO - Epoch(train) [103][450/586] lr: 5.000000e-04 eta: 4:44:29 time: 0.289402 data_time: 0.026563 memory: 11131 loss_kpt: 0.000572 acc_pose: 0.868835 loss: 0.000572 2022/10/27 17:18:06 - mmengine - INFO - Epoch(train) [103][500/586] lr: 5.000000e-04 eta: 4:44:16 time: 0.281396 data_time: 0.027952 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.850084 loss: 0.000580 2022/10/27 17:18:21 - mmengine - INFO - Epoch(train) [103][550/586] lr: 5.000000e-04 eta: 4:44:04 time: 0.294013 data_time: 0.027535 memory: 11131 loss_kpt: 0.000592 acc_pose: 0.857935 loss: 0.000592 2022/10/27 17:18:31 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:18:46 - mmengine - INFO - Epoch(train) [104][50/586] lr: 5.000000e-04 eta: 4:43:31 time: 0.297369 data_time: 0.037583 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.841318 loss: 0.000568 2022/10/27 17:19:00 - mmengine - INFO - Epoch(train) [104][100/586] lr: 5.000000e-04 eta: 4:43:19 time: 0.288850 data_time: 0.029211 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.801351 loss: 0.000569 2022/10/27 17:19:15 - mmengine - INFO - Epoch(train) [104][150/586] lr: 5.000000e-04 eta: 4:43:06 time: 0.284196 data_time: 0.030049 memory: 11131 loss_kpt: 0.000574 acc_pose: 0.801343 loss: 0.000574 2022/10/27 17:19:29 - mmengine - INFO - Epoch(train) [104][200/586] lr: 5.000000e-04 eta: 4:42:53 time: 0.293407 data_time: 0.035693 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.861078 loss: 0.000547 2022/10/27 17:19:43 - mmengine - INFO - Epoch(train) [104][250/586] lr: 5.000000e-04 eta: 4:42:40 time: 0.282358 data_time: 0.030693 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.895954 loss: 0.000564 2022/10/27 17:19:58 - mmengine - INFO - Epoch(train) [104][300/586] lr: 5.000000e-04 eta: 4:42:28 time: 0.293025 data_time: 0.028838 memory: 11131 loss_kpt: 0.000576 acc_pose: 0.849069 loss: 0.000576 2022/10/27 17:20:12 - mmengine - INFO - Epoch(train) [104][350/586] lr: 5.000000e-04 eta: 4:42:15 time: 0.285947 data_time: 0.029818 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.813089 loss: 0.000568 2022/10/27 17:20:27 - mmengine - INFO - Epoch(train) [104][400/586] lr: 5.000000e-04 eta: 4:42:02 time: 0.288908 data_time: 0.030755 memory: 11131 loss_kpt: 0.000576 acc_pose: 0.845674 loss: 0.000576 2022/10/27 17:20:41 - mmengine - INFO - Epoch(train) [104][450/586] lr: 5.000000e-04 eta: 4:41:50 time: 0.287969 data_time: 0.029701 memory: 11131 loss_kpt: 0.000571 acc_pose: 0.865853 loss: 0.000571 2022/10/27 17:20:55 - mmengine - INFO - Epoch(train) [104][500/586] lr: 5.000000e-04 eta: 4:41:37 time: 0.282884 data_time: 0.027760 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.846430 loss: 0.000573 2022/10/27 17:21:10 - mmengine - INFO - Epoch(train) [104][550/586] lr: 5.000000e-04 eta: 4:41:24 time: 0.293057 data_time: 0.027686 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.861828 loss: 0.000563 2022/10/27 17:21:20 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:21:35 - mmengine - INFO - Epoch(train) [105][50/586] lr: 5.000000e-04 eta: 4:40:52 time: 0.297959 data_time: 0.040342 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.843004 loss: 0.000547 2022/10/27 17:21:37 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:21:49 - mmengine - INFO - Epoch(train) [105][100/586] lr: 5.000000e-04 eta: 4:40:39 time: 0.288364 data_time: 0.034463 memory: 11131 loss_kpt: 0.000576 acc_pose: 0.899899 loss: 0.000576 2022/10/27 17:22:04 - mmengine - INFO - Epoch(train) [105][150/586] lr: 5.000000e-04 eta: 4:40:27 time: 0.285199 data_time: 0.028132 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.823533 loss: 0.000580 2022/10/27 17:22:18 - mmengine - INFO - Epoch(train) [105][200/586] lr: 5.000000e-04 eta: 4:40:14 time: 0.294777 data_time: 0.029137 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.828293 loss: 0.000569 2022/10/27 17:22:33 - mmengine - INFO - Epoch(train) [105][250/586] lr: 5.000000e-04 eta: 4:40:01 time: 0.283834 data_time: 0.032071 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.810376 loss: 0.000562 2022/10/27 17:22:47 - mmengine - INFO - Epoch(train) [105][300/586] lr: 5.000000e-04 eta: 4:39:49 time: 0.294296 data_time: 0.032311 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.798733 loss: 0.000564 2022/10/27 17:23:02 - mmengine - INFO - Epoch(train) [105][350/586] lr: 5.000000e-04 eta: 4:39:36 time: 0.284370 data_time: 0.027423 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.856137 loss: 0.000564 2022/10/27 17:23:16 - mmengine - INFO - Epoch(train) [105][400/586] lr: 5.000000e-04 eta: 4:39:23 time: 0.286641 data_time: 0.029321 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.766339 loss: 0.000570 2022/10/27 17:23:30 - mmengine - INFO - Epoch(train) [105][450/586] lr: 5.000000e-04 eta: 4:39:10 time: 0.285713 data_time: 0.026697 memory: 11131 loss_kpt: 0.000577 acc_pose: 0.837535 loss: 0.000577 2022/10/27 17:23:45 - mmengine - INFO - Epoch(train) [105][500/586] lr: 5.000000e-04 eta: 4:38:58 time: 0.292553 data_time: 0.030421 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.905335 loss: 0.000570 2022/10/27 17:23:59 - mmengine - INFO - Epoch(train) [105][550/586] lr: 5.000000e-04 eta: 4:38:45 time: 0.284233 data_time: 0.028048 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.814227 loss: 0.000562 2022/10/27 17:24:09 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:24:24 - mmengine - INFO - Epoch(train) [106][50/586] lr: 5.000000e-04 eta: 4:38:13 time: 0.297166 data_time: 0.036710 memory: 11131 loss_kpt: 0.000595 acc_pose: 0.786725 loss: 0.000595 2022/10/27 17:24:39 - mmengine - INFO - Epoch(train) [106][100/586] lr: 5.000000e-04 eta: 4:38:00 time: 0.291110 data_time: 0.031630 memory: 11131 loss_kpt: 0.000574 acc_pose: 0.857139 loss: 0.000574 2022/10/27 17:24:53 - mmengine - INFO - Epoch(train) [106][150/586] lr: 5.000000e-04 eta: 4:37:48 time: 0.290072 data_time: 0.028145 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.833977 loss: 0.000569 2022/10/27 17:25:07 - mmengine - INFO - Epoch(train) [106][200/586] lr: 5.000000e-04 eta: 4:37:35 time: 0.286155 data_time: 0.029160 memory: 11131 loss_kpt: 0.000559 acc_pose: 0.884948 loss: 0.000559 2022/10/27 17:25:22 - mmengine - INFO - Epoch(train) [106][250/586] lr: 5.000000e-04 eta: 4:37:22 time: 0.285901 data_time: 0.031686 memory: 11131 loss_kpt: 0.000560 acc_pose: 0.864257 loss: 0.000560 2022/10/27 17:25:36 - mmengine - INFO - Epoch(train) [106][300/586] lr: 5.000000e-04 eta: 4:37:09 time: 0.289220 data_time: 0.031485 memory: 11131 loss_kpt: 0.000571 acc_pose: 0.847745 loss: 0.000571 2022/10/27 17:25:51 - mmengine - INFO - Epoch(train) [106][350/586] lr: 5.000000e-04 eta: 4:36:56 time: 0.288065 data_time: 0.029049 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.890520 loss: 0.000558 2022/10/27 17:26:05 - mmengine - INFO - Epoch(train) [106][400/586] lr: 5.000000e-04 eta: 4:36:44 time: 0.287808 data_time: 0.028641 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.861431 loss: 0.000570 2022/10/27 17:26:19 - mmengine - INFO - Epoch(train) [106][450/586] lr: 5.000000e-04 eta: 4:36:31 time: 0.287540 data_time: 0.026970 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.833644 loss: 0.000573 2022/10/27 17:26:25 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:26:34 - mmengine - INFO - Epoch(train) [106][500/586] lr: 5.000000e-04 eta: 4:36:18 time: 0.282729 data_time: 0.028874 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.838014 loss: 0.000563 2022/10/27 17:26:48 - mmengine - INFO - Epoch(train) [106][550/586] lr: 5.000000e-04 eta: 4:36:05 time: 0.292926 data_time: 0.028505 memory: 11131 loss_kpt: 0.000567 acc_pose: 0.881367 loss: 0.000567 2022/10/27 17:26:58 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:27:13 - mmengine - INFO - Epoch(train) [107][50/586] lr: 5.000000e-04 eta: 4:35:33 time: 0.295377 data_time: 0.036349 memory: 11131 loss_kpt: 0.000560 acc_pose: 0.861070 loss: 0.000560 2022/10/27 17:27:28 - mmengine - INFO - Epoch(train) [107][100/586] lr: 5.000000e-04 eta: 4:35:21 time: 0.287770 data_time: 0.031919 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.868529 loss: 0.000573 2022/10/27 17:27:42 - mmengine - INFO - Epoch(train) [107][150/586] lr: 5.000000e-04 eta: 4:35:08 time: 0.284644 data_time: 0.027156 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.821937 loss: 0.000568 2022/10/27 17:27:57 - mmengine - INFO - Epoch(train) [107][200/586] lr: 5.000000e-04 eta: 4:34:55 time: 0.296295 data_time: 0.027941 memory: 11131 loss_kpt: 0.000565 acc_pose: 0.861088 loss: 0.000565 2022/10/27 17:28:11 - mmengine - INFO - Epoch(train) [107][250/586] lr: 5.000000e-04 eta: 4:34:42 time: 0.285563 data_time: 0.030043 memory: 11131 loss_kpt: 0.000572 acc_pose: 0.890154 loss: 0.000572 2022/10/27 17:28:26 - mmengine - INFO - Epoch(train) [107][300/586] lr: 5.000000e-04 eta: 4:34:30 time: 0.292849 data_time: 0.031725 memory: 11131 loss_kpt: 0.000553 acc_pose: 0.826721 loss: 0.000553 2022/10/27 17:28:40 - mmengine - INFO - Epoch(train) [107][350/586] lr: 5.000000e-04 eta: 4:34:17 time: 0.286471 data_time: 0.032727 memory: 11131 loss_kpt: 0.000567 acc_pose: 0.883673 loss: 0.000567 2022/10/27 17:28:54 - mmengine - INFO - Epoch(train) [107][400/586] lr: 5.000000e-04 eta: 4:34:04 time: 0.288938 data_time: 0.028089 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.891076 loss: 0.000557 2022/10/27 17:29:09 - mmengine - INFO - Epoch(train) [107][450/586] lr: 5.000000e-04 eta: 4:33:51 time: 0.285781 data_time: 0.028890 memory: 11131 loss_kpt: 0.000578 acc_pose: 0.892163 loss: 0.000578 2022/10/27 17:29:23 - mmengine - INFO - Epoch(train) [107][500/586] lr: 5.000000e-04 eta: 4:33:39 time: 0.286296 data_time: 0.028604 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.833514 loss: 0.000569 2022/10/27 17:29:38 - mmengine - INFO - Epoch(train) [107][550/586] lr: 5.000000e-04 eta: 4:33:26 time: 0.292200 data_time: 0.033699 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.885466 loss: 0.000557 2022/10/27 17:29:48 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:30:03 - mmengine - INFO - Epoch(train) [108][50/586] lr: 5.000000e-04 eta: 4:32:55 time: 0.302863 data_time: 0.039995 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.855012 loss: 0.000555 2022/10/27 17:30:17 - mmengine - INFO - Epoch(train) [108][100/586] lr: 5.000000e-04 eta: 4:32:42 time: 0.292027 data_time: 0.032519 memory: 11131 loss_kpt: 0.000553 acc_pose: 0.825642 loss: 0.000553 2022/10/27 17:30:32 - mmengine - INFO - Epoch(train) [108][150/586] lr: 5.000000e-04 eta: 4:32:29 time: 0.283933 data_time: 0.028095 memory: 11131 loss_kpt: 0.000566 acc_pose: 0.863608 loss: 0.000566 2022/10/27 17:30:46 - mmengine - INFO - Epoch(train) [108][200/586] lr: 5.000000e-04 eta: 4:32:16 time: 0.289351 data_time: 0.031884 memory: 11131 loss_kpt: 0.000565 acc_pose: 0.884875 loss: 0.000565 2022/10/27 17:31:00 - mmengine - INFO - Epoch(train) [108][250/586] lr: 5.000000e-04 eta: 4:32:03 time: 0.283168 data_time: 0.027672 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.871662 loss: 0.000551 2022/10/27 17:31:14 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:31:15 - mmengine - INFO - Epoch(train) [108][300/586] lr: 5.000000e-04 eta: 4:31:51 time: 0.289878 data_time: 0.028802 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.892609 loss: 0.000570 2022/10/27 17:31:29 - mmengine - INFO - Epoch(train) [108][350/586] lr: 5.000000e-04 eta: 4:31:38 time: 0.288216 data_time: 0.030435 memory: 11131 loss_kpt: 0.000576 acc_pose: 0.816275 loss: 0.000576 2022/10/27 17:31:44 - mmengine - INFO - Epoch(train) [108][400/586] lr: 5.000000e-04 eta: 4:31:25 time: 0.294606 data_time: 0.029920 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.784676 loss: 0.000570 2022/10/27 17:31:58 - mmengine - INFO - Epoch(train) [108][450/586] lr: 5.000000e-04 eta: 4:31:13 time: 0.288017 data_time: 0.028298 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.823929 loss: 0.000561 2022/10/27 17:32:13 - mmengine - INFO - Epoch(train) [108][500/586] lr: 5.000000e-04 eta: 4:31:00 time: 0.286134 data_time: 0.030014 memory: 11131 loss_kpt: 0.000559 acc_pose: 0.841498 loss: 0.000559 2022/10/27 17:32:27 - mmengine - INFO - Epoch(train) [108][550/586] lr: 5.000000e-04 eta: 4:30:47 time: 0.293137 data_time: 0.027637 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.881816 loss: 0.000564 2022/10/27 17:32:37 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:32:53 - mmengine - INFO - Epoch(train) [109][50/586] lr: 5.000000e-04 eta: 4:30:16 time: 0.302610 data_time: 0.040852 memory: 11131 loss_kpt: 0.000550 acc_pose: 0.802641 loss: 0.000550 2022/10/27 17:33:07 - mmengine - INFO - Epoch(train) [109][100/586] lr: 5.000000e-04 eta: 4:30:03 time: 0.288018 data_time: 0.031570 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.827261 loss: 0.000564 2022/10/27 17:33:21 - mmengine - INFO - Epoch(train) [109][150/586] lr: 5.000000e-04 eta: 4:29:50 time: 0.286057 data_time: 0.030362 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.842792 loss: 0.000563 2022/10/27 17:33:36 - mmengine - INFO - Epoch(train) [109][200/586] lr: 5.000000e-04 eta: 4:29:38 time: 0.293797 data_time: 0.027771 memory: 11131 loss_kpt: 0.000572 acc_pose: 0.847759 loss: 0.000572 2022/10/27 17:33:50 - mmengine - INFO - Epoch(train) [109][250/586] lr: 5.000000e-04 eta: 4:29:25 time: 0.285631 data_time: 0.029303 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.838674 loss: 0.000563 2022/10/27 17:34:05 - mmengine - INFO - Epoch(train) [109][300/586] lr: 5.000000e-04 eta: 4:29:12 time: 0.289122 data_time: 0.027617 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.870273 loss: 0.000569 2022/10/27 17:34:19 - mmengine - INFO - Epoch(train) [109][350/586] lr: 5.000000e-04 eta: 4:28:59 time: 0.286077 data_time: 0.027262 memory: 11131 loss_kpt: 0.000549 acc_pose: 0.857758 loss: 0.000549 2022/10/27 17:34:33 - mmengine - INFO - Epoch(train) [109][400/586] lr: 5.000000e-04 eta: 4:28:46 time: 0.284005 data_time: 0.028865 memory: 11131 loss_kpt: 0.000567 acc_pose: 0.883972 loss: 0.000567 2022/10/27 17:34:48 - mmengine - INFO - Epoch(train) [109][450/586] lr: 5.000000e-04 eta: 4:28:33 time: 0.284855 data_time: 0.026894 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.779168 loss: 0.000563 2022/10/27 17:35:02 - mmengine - INFO - Epoch(train) [109][500/586] lr: 5.000000e-04 eta: 4:28:20 time: 0.285786 data_time: 0.029622 memory: 11131 loss_kpt: 0.000574 acc_pose: 0.870365 loss: 0.000574 2022/10/27 17:35:16 - mmengine - INFO - Epoch(train) [109][550/586] lr: 5.000000e-04 eta: 4:28:08 time: 0.290311 data_time: 0.027710 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.872587 loss: 0.000563 2022/10/27 17:35:27 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:35:41 - mmengine - INFO - Epoch(train) [110][50/586] lr: 5.000000e-04 eta: 4:27:36 time: 0.297215 data_time: 0.036112 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.841909 loss: 0.000561 2022/10/27 17:35:56 - mmengine - INFO - Epoch(train) [110][100/586] lr: 5.000000e-04 eta: 4:27:24 time: 0.291397 data_time: 0.030892 memory: 11131 loss_kpt: 0.000575 acc_pose: 0.829466 loss: 0.000575 2022/10/27 17:36:03 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:36:10 - mmengine - INFO - Epoch(train) [110][150/586] lr: 5.000000e-04 eta: 4:27:11 time: 0.287741 data_time: 0.029250 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.848119 loss: 0.000561 2022/10/27 17:36:25 - mmengine - INFO - Epoch(train) [110][200/586] lr: 5.000000e-04 eta: 4:26:58 time: 0.290026 data_time: 0.032787 memory: 11131 loss_kpt: 0.000550 acc_pose: 0.829087 loss: 0.000550 2022/10/27 17:36:39 - mmengine - INFO - Epoch(train) [110][250/586] lr: 5.000000e-04 eta: 4:26:45 time: 0.284796 data_time: 0.029979 memory: 11131 loss_kpt: 0.000579 acc_pose: 0.902638 loss: 0.000579 2022/10/27 17:36:54 - mmengine - INFO - Epoch(train) [110][300/586] lr: 5.000000e-04 eta: 4:26:33 time: 0.292954 data_time: 0.027116 memory: 11131 loss_kpt: 0.000575 acc_pose: 0.847638 loss: 0.000575 2022/10/27 17:37:08 - mmengine - INFO - Epoch(train) [110][350/586] lr: 5.000000e-04 eta: 4:26:20 time: 0.285417 data_time: 0.031962 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.792053 loss: 0.000533 2022/10/27 17:37:23 - mmengine - INFO - Epoch(train) [110][400/586] lr: 5.000000e-04 eta: 4:26:07 time: 0.289122 data_time: 0.031627 memory: 11131 loss_kpt: 0.000560 acc_pose: 0.880740 loss: 0.000560 2022/10/27 17:37:37 - mmengine - INFO - Epoch(train) [110][450/586] lr: 5.000000e-04 eta: 4:25:54 time: 0.286928 data_time: 0.033745 memory: 11131 loss_kpt: 0.000572 acc_pose: 0.830756 loss: 0.000572 2022/10/27 17:37:51 - mmengine - INFO - Epoch(train) [110][500/586] lr: 5.000000e-04 eta: 4:25:41 time: 0.282871 data_time: 0.028261 memory: 11131 loss_kpt: 0.000571 acc_pose: 0.869255 loss: 0.000571 2022/10/27 17:38:06 - mmengine - INFO - Epoch(train) [110][550/586] lr: 5.000000e-04 eta: 4:25:28 time: 0.293636 data_time: 0.029009 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.813686 loss: 0.000564 2022/10/27 17:38:16 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:38:16 - mmengine - INFO - Saving checkpoint at 110 epochs 2022/10/27 17:38:27 - mmengine - INFO - Epoch(val) [110][50/407] eta: 0:00:53 time: 0.150385 data_time: 0.032421 memory: 11131 2022/10/27 17:38:34 - mmengine - INFO - Epoch(val) [110][100/407] eta: 0:00:41 time: 0.135442 data_time: 0.018611 memory: 1836 2022/10/27 17:38:41 - mmengine - INFO - Epoch(val) [110][150/407] eta: 0:00:34 time: 0.135687 data_time: 0.015133 memory: 1836 2022/10/27 17:38:48 - mmengine - INFO - Epoch(val) [110][200/407] eta: 0:00:28 time: 0.137221 data_time: 0.017561 memory: 1836 2022/10/27 17:38:55 - mmengine - INFO - Epoch(val) [110][250/407] eta: 0:00:21 time: 0.138665 data_time: 0.019482 memory: 1836 2022/10/27 17:39:01 - mmengine - INFO - Epoch(val) [110][300/407] eta: 0:00:14 time: 0.136327 data_time: 0.016363 memory: 1836 2022/10/27 17:39:08 - mmengine - INFO - Epoch(val) [110][350/407] eta: 0:00:07 time: 0.135889 data_time: 0.014018 memory: 1836 2022/10/27 17:39:14 - mmengine - INFO - Epoch(val) [110][400/407] eta: 0:00:00 time: 0.126935 data_time: 0.011639 memory: 1836 2022/10/27 17:40:01 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 17:40:19 - mmengine - INFO - Epoch(val) [110][407/407] coco/AP: 0.739102 coco/AP .5: 0.900320 coco/AP .75: 0.808013 coco/AP (M): 0.696631 coco/AP (L): 0.810265 coco/AR: 0.789641 coco/AR .5: 0.936241 coco/AR .75: 0.850913 coco/AR (M): 0.744469 coco/AR (L): 0.855147 2022/10/27 17:40:34 - mmengine - INFO - Epoch(train) [111][50/586] lr: 5.000000e-04 eta: 4:24:57 time: 0.303319 data_time: 0.037249 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.865988 loss: 0.000562 2022/10/27 17:40:49 - mmengine - INFO - Epoch(train) [111][100/586] lr: 5.000000e-04 eta: 4:24:45 time: 0.292034 data_time: 0.027991 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.833134 loss: 0.000552 2022/10/27 17:41:03 - mmengine - INFO - Epoch(train) [111][150/586] lr: 5.000000e-04 eta: 4:24:32 time: 0.289782 data_time: 0.027243 memory: 11131 loss_kpt: 0.000581 acc_pose: 0.938430 loss: 0.000581 2022/10/27 17:41:18 - mmengine - INFO - Epoch(train) [111][200/586] lr: 5.000000e-04 eta: 4:24:19 time: 0.290225 data_time: 0.030006 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.841619 loss: 0.000551 2022/10/27 17:41:32 - mmengine - INFO - Epoch(train) [111][250/586] lr: 5.000000e-04 eta: 4:24:06 time: 0.285670 data_time: 0.031609 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.834509 loss: 0.000551 2022/10/27 17:41:46 - mmengine - INFO - Epoch(train) [111][300/586] lr: 5.000000e-04 eta: 4:23:54 time: 0.288958 data_time: 0.032840 memory: 11131 loss_kpt: 0.000544 acc_pose: 0.830161 loss: 0.000544 2022/10/27 17:42:01 - mmengine - INFO - Epoch(train) [111][350/586] lr: 5.000000e-04 eta: 4:23:41 time: 0.283585 data_time: 0.028577 memory: 11131 loss_kpt: 0.000554 acc_pose: 0.866801 loss: 0.000554 2022/10/27 17:42:15 - mmengine - INFO - Epoch(train) [111][400/586] lr: 5.000000e-04 eta: 4:23:28 time: 0.287204 data_time: 0.028210 memory: 11131 loss_kpt: 0.000571 acc_pose: 0.931181 loss: 0.000571 2022/10/27 17:42:29 - mmengine - INFO - Epoch(train) [111][450/586] lr: 5.000000e-04 eta: 4:23:15 time: 0.286316 data_time: 0.027281 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.911063 loss: 0.000568 2022/10/27 17:42:44 - mmengine - INFO - Epoch(train) [111][500/586] lr: 5.000000e-04 eta: 4:23:02 time: 0.286828 data_time: 0.030048 memory: 11131 loss_kpt: 0.000573 acc_pose: 0.952320 loss: 0.000573 2022/10/27 17:42:55 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:42:58 - mmengine - INFO - Epoch(train) [111][550/586] lr: 5.000000e-04 eta: 4:22:49 time: 0.287604 data_time: 0.031781 memory: 11131 loss_kpt: 0.000574 acc_pose: 0.839077 loss: 0.000574 2022/10/27 17:43:08 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:43:23 - mmengine - INFO - Epoch(train) [112][50/586] lr: 5.000000e-04 eta: 4:22:18 time: 0.298731 data_time: 0.038029 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.818282 loss: 0.000555 2022/10/27 17:43:37 - mmengine - INFO - Epoch(train) [112][100/586] lr: 5.000000e-04 eta: 4:22:05 time: 0.287600 data_time: 0.028046 memory: 11131 loss_kpt: 0.000566 acc_pose: 0.847951 loss: 0.000566 2022/10/27 17:43:52 - mmengine - INFO - Epoch(train) [112][150/586] lr: 5.000000e-04 eta: 4:21:52 time: 0.285389 data_time: 0.026771 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.917364 loss: 0.000561 2022/10/27 17:44:06 - mmengine - INFO - Epoch(train) [112][200/586] lr: 5.000000e-04 eta: 4:21:40 time: 0.290232 data_time: 0.027314 memory: 11131 loss_kpt: 0.000554 acc_pose: 0.864577 loss: 0.000554 2022/10/27 17:44:21 - mmengine - INFO - Epoch(train) [112][250/586] lr: 5.000000e-04 eta: 4:21:27 time: 0.288269 data_time: 0.040727 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.879507 loss: 0.000538 2022/10/27 17:44:35 - mmengine - INFO - Epoch(train) [112][300/586] lr: 5.000000e-04 eta: 4:21:14 time: 0.294699 data_time: 0.028408 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.868769 loss: 0.000562 2022/10/27 17:44:49 - mmengine - INFO - Epoch(train) [112][350/586] lr: 5.000000e-04 eta: 4:21:01 time: 0.283390 data_time: 0.028784 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.855572 loss: 0.000557 2022/10/27 17:45:04 - mmengine - INFO - Epoch(train) [112][400/586] lr: 5.000000e-04 eta: 4:20:48 time: 0.287937 data_time: 0.028476 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.883762 loss: 0.000558 2022/10/27 17:45:18 - mmengine - INFO - Epoch(train) [112][450/586] lr: 5.000000e-04 eta: 4:20:35 time: 0.287857 data_time: 0.032340 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.880027 loss: 0.000568 2022/10/27 17:45:33 - mmengine - INFO - Epoch(train) [112][500/586] lr: 5.000000e-04 eta: 4:20:22 time: 0.284215 data_time: 0.028642 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.796228 loss: 0.000561 2022/10/27 17:45:47 - mmengine - INFO - Epoch(train) [112][550/586] lr: 5.000000e-04 eta: 4:20:10 time: 0.294959 data_time: 0.028878 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.917958 loss: 0.000564 2022/10/27 17:45:57 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:46:12 - mmengine - INFO - Epoch(train) [113][50/586] lr: 5.000000e-04 eta: 4:19:39 time: 0.300127 data_time: 0.038448 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.864128 loss: 0.000546 2022/10/27 17:46:27 - mmengine - INFO - Epoch(train) [113][100/586] lr: 5.000000e-04 eta: 4:19:26 time: 0.287753 data_time: 0.029086 memory: 11131 loss_kpt: 0.000560 acc_pose: 0.882437 loss: 0.000560 2022/10/27 17:46:41 - mmengine - INFO - Epoch(train) [113][150/586] lr: 5.000000e-04 eta: 4:19:13 time: 0.283451 data_time: 0.027544 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.802902 loss: 0.000555 2022/10/27 17:46:56 - mmengine - INFO - Epoch(train) [113][200/586] lr: 5.000000e-04 eta: 4:19:01 time: 0.297909 data_time: 0.031544 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.888167 loss: 0.000563 2022/10/27 17:47:10 - mmengine - INFO - Epoch(train) [113][250/586] lr: 5.000000e-04 eta: 4:18:48 time: 0.283331 data_time: 0.032781 memory: 11131 loss_kpt: 0.000577 acc_pose: 0.813335 loss: 0.000577 2022/10/27 17:47:24 - mmengine - INFO - Epoch(train) [113][300/586] lr: 5.000000e-04 eta: 4:18:35 time: 0.287417 data_time: 0.028478 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.874640 loss: 0.000580 2022/10/27 17:47:39 - mmengine - INFO - Epoch(train) [113][350/586] lr: 5.000000e-04 eta: 4:18:22 time: 0.289158 data_time: 0.032130 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.827026 loss: 0.000551 2022/10/27 17:47:44 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:47:53 - mmengine - INFO - Epoch(train) [113][400/586] lr: 5.000000e-04 eta: 4:18:09 time: 0.291344 data_time: 0.028872 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.835513 loss: 0.000563 2022/10/27 17:48:08 - mmengine - INFO - Epoch(train) [113][450/586] lr: 5.000000e-04 eta: 4:17:56 time: 0.287125 data_time: 0.028856 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.818648 loss: 0.000548 2022/10/27 17:48:22 - mmengine - INFO - Epoch(train) [113][500/586] lr: 5.000000e-04 eta: 4:17:44 time: 0.292313 data_time: 0.027878 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.824363 loss: 0.000569 2022/10/27 17:48:37 - mmengine - INFO - Epoch(train) [113][550/586] lr: 5.000000e-04 eta: 4:17:31 time: 0.291657 data_time: 0.033746 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.889347 loss: 0.000563 2022/10/27 17:48:47 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:49:02 - mmengine - INFO - Epoch(train) [114][50/586] lr: 5.000000e-04 eta: 4:17:01 time: 0.306067 data_time: 0.042118 memory: 11131 loss_kpt: 0.000580 acc_pose: 0.823346 loss: 0.000580 2022/10/27 17:49:17 - mmengine - INFO - Epoch(train) [114][100/586] lr: 5.000000e-04 eta: 4:16:48 time: 0.286890 data_time: 0.028980 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.797187 loss: 0.000555 2022/10/27 17:49:31 - mmengine - INFO - Epoch(train) [114][150/586] lr: 5.000000e-04 eta: 4:16:35 time: 0.287636 data_time: 0.032217 memory: 11131 loss_kpt: 0.000549 acc_pose: 0.873999 loss: 0.000549 2022/10/27 17:49:46 - mmengine - INFO - Epoch(train) [114][200/586] lr: 5.000000e-04 eta: 4:16:22 time: 0.290810 data_time: 0.035943 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.951407 loss: 0.000557 2022/10/27 17:50:00 - mmengine - INFO - Epoch(train) [114][250/586] lr: 5.000000e-04 eta: 4:16:09 time: 0.288525 data_time: 0.030141 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.894019 loss: 0.000557 2022/10/27 17:50:15 - mmengine - INFO - Epoch(train) [114][300/586] lr: 5.000000e-04 eta: 4:15:57 time: 0.292660 data_time: 0.027955 memory: 11131 loss_kpt: 0.000567 acc_pose: 0.802008 loss: 0.000567 2022/10/27 17:50:29 - mmengine - INFO - Epoch(train) [114][350/586] lr: 5.000000e-04 eta: 4:15:44 time: 0.288062 data_time: 0.028733 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.856617 loss: 0.000561 2022/10/27 17:50:43 - mmengine - INFO - Epoch(train) [114][400/586] lr: 5.000000e-04 eta: 4:15:31 time: 0.288011 data_time: 0.027913 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.838666 loss: 0.000555 2022/10/27 17:50:58 - mmengine - INFO - Epoch(train) [114][450/586] lr: 5.000000e-04 eta: 4:15:18 time: 0.290967 data_time: 0.032460 memory: 11131 loss_kpt: 0.000560 acc_pose: 0.816204 loss: 0.000560 2022/10/27 17:51:12 - mmengine - INFO - Epoch(train) [114][500/586] lr: 5.000000e-04 eta: 4:15:05 time: 0.280649 data_time: 0.027710 memory: 11131 loss_kpt: 0.000550 acc_pose: 0.843204 loss: 0.000550 2022/10/27 17:51:27 - mmengine - INFO - Epoch(train) [114][550/586] lr: 5.000000e-04 eta: 4:14:52 time: 0.294295 data_time: 0.027977 memory: 11131 loss_kpt: 0.000567 acc_pose: 0.878437 loss: 0.000567 2022/10/27 17:51:37 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:51:52 - mmengine - INFO - Epoch(train) [115][50/586] lr: 5.000000e-04 eta: 4:14:22 time: 0.299628 data_time: 0.039116 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.822648 loss: 0.000570 2022/10/27 17:52:06 - mmengine - INFO - Epoch(train) [115][100/586] lr: 5.000000e-04 eta: 4:14:09 time: 0.290364 data_time: 0.029738 memory: 11131 loss_kpt: 0.000549 acc_pose: 0.896454 loss: 0.000549 2022/10/27 17:52:20 - mmengine - INFO - Epoch(train) [115][150/586] lr: 5.000000e-04 eta: 4:13:56 time: 0.281461 data_time: 0.028742 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.800667 loss: 0.000555 2022/10/27 17:52:34 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:52:35 - mmengine - INFO - Epoch(train) [115][200/586] lr: 5.000000e-04 eta: 4:13:43 time: 0.291281 data_time: 0.028269 memory: 11131 loss_kpt: 0.000544 acc_pose: 0.894901 loss: 0.000544 2022/10/27 17:52:49 - mmengine - INFO - Epoch(train) [115][250/586] lr: 5.000000e-04 eta: 4:13:30 time: 0.286095 data_time: 0.030350 memory: 11131 loss_kpt: 0.000566 acc_pose: 0.864873 loss: 0.000566 2022/10/27 17:53:04 - mmengine - INFO - Epoch(train) [115][300/586] lr: 5.000000e-04 eta: 4:13:17 time: 0.287158 data_time: 0.027384 memory: 11131 loss_kpt: 0.000560 acc_pose: 0.867473 loss: 0.000560 2022/10/27 17:53:18 - mmengine - INFO - Epoch(train) [115][350/586] lr: 5.000000e-04 eta: 4:13:04 time: 0.286781 data_time: 0.028085 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.849245 loss: 0.000558 2022/10/27 17:53:33 - mmengine - INFO - Epoch(train) [115][400/586] lr: 5.000000e-04 eta: 4:12:51 time: 0.290253 data_time: 0.027660 memory: 11131 loss_kpt: 0.000567 acc_pose: 0.776203 loss: 0.000567 2022/10/27 17:53:47 - mmengine - INFO - Epoch(train) [115][450/586] lr: 5.000000e-04 eta: 4:12:39 time: 0.287691 data_time: 0.028361 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.859376 loss: 0.000563 2022/10/27 17:54:01 - mmengine - INFO - Epoch(train) [115][500/586] lr: 5.000000e-04 eta: 4:12:26 time: 0.285701 data_time: 0.028267 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.813046 loss: 0.000548 2022/10/27 17:54:16 - mmengine - INFO - Epoch(train) [115][550/586] lr: 5.000000e-04 eta: 4:12:13 time: 0.290222 data_time: 0.032719 memory: 11131 loss_kpt: 0.000575 acc_pose: 0.856289 loss: 0.000575 2022/10/27 17:54:26 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:54:41 - mmengine - INFO - Epoch(train) [116][50/586] lr: 5.000000e-04 eta: 4:11:42 time: 0.292605 data_time: 0.038344 memory: 11131 loss_kpt: 0.000565 acc_pose: 0.713036 loss: 0.000565 2022/10/27 17:54:55 - mmengine - INFO - Epoch(train) [116][100/586] lr: 5.000000e-04 eta: 4:11:29 time: 0.289330 data_time: 0.027958 memory: 11131 loss_kpt: 0.000564 acc_pose: 0.839277 loss: 0.000564 2022/10/27 17:55:09 - mmengine - INFO - Epoch(train) [116][150/586] lr: 5.000000e-04 eta: 4:11:16 time: 0.285042 data_time: 0.027661 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.877122 loss: 0.000551 2022/10/27 17:55:24 - mmengine - INFO - Epoch(train) [116][200/586] lr: 5.000000e-04 eta: 4:11:04 time: 0.292946 data_time: 0.031985 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.801437 loss: 0.000546 2022/10/27 17:55:38 - mmengine - INFO - Epoch(train) [116][250/586] lr: 5.000000e-04 eta: 4:10:51 time: 0.287956 data_time: 0.033162 memory: 11131 loss_kpt: 0.000544 acc_pose: 0.846289 loss: 0.000544 2022/10/27 17:55:53 - mmengine - INFO - Epoch(train) [116][300/586] lr: 5.000000e-04 eta: 4:10:38 time: 0.292778 data_time: 0.028023 memory: 11131 loss_kpt: 0.000575 acc_pose: 0.849191 loss: 0.000575 2022/10/27 17:56:07 - mmengine - INFO - Epoch(train) [116][350/586] lr: 5.000000e-04 eta: 4:10:25 time: 0.288172 data_time: 0.028377 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.909956 loss: 0.000557 2022/10/27 17:56:22 - mmengine - INFO - Epoch(train) [116][400/586] lr: 5.000000e-04 eta: 4:10:12 time: 0.285681 data_time: 0.027940 memory: 11131 loss_kpt: 0.000550 acc_pose: 0.862329 loss: 0.000550 2022/10/27 17:56:36 - mmengine - INFO - Epoch(train) [116][450/586] lr: 5.000000e-04 eta: 4:09:59 time: 0.293144 data_time: 0.026776 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.835096 loss: 0.000541 2022/10/27 17:56:50 - mmengine - INFO - Epoch(train) [116][500/586] lr: 5.000000e-04 eta: 4:09:46 time: 0.282041 data_time: 0.027441 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.918946 loss: 0.000562 2022/10/27 17:57:05 - mmengine - INFO - Epoch(train) [116][550/586] lr: 5.000000e-04 eta: 4:09:33 time: 0.289904 data_time: 0.027137 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.866617 loss: 0.000545 2022/10/27 17:57:15 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:57:22 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 17:57:30 - mmengine - INFO - Epoch(train) [117][50/586] lr: 5.000000e-04 eta: 4:09:03 time: 0.293134 data_time: 0.036911 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.853758 loss: 0.000562 2022/10/27 17:57:44 - mmengine - INFO - Epoch(train) [117][100/586] lr: 5.000000e-04 eta: 4:08:50 time: 0.293049 data_time: 0.031759 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.777905 loss: 0.000557 2022/10/27 17:57:59 - mmengine - INFO - Epoch(train) [117][150/586] lr: 5.000000e-04 eta: 4:08:37 time: 0.286354 data_time: 0.029228 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.875640 loss: 0.000555 2022/10/27 17:58:13 - mmengine - INFO - Epoch(train) [117][200/586] lr: 5.000000e-04 eta: 4:08:24 time: 0.290343 data_time: 0.030316 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.845812 loss: 0.000561 2022/10/27 17:58:28 - mmengine - INFO - Epoch(train) [117][250/586] lr: 5.000000e-04 eta: 4:08:11 time: 0.287256 data_time: 0.031189 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.806884 loss: 0.000542 2022/10/27 17:58:42 - mmengine - INFO - Epoch(train) [117][300/586] lr: 5.000000e-04 eta: 4:07:59 time: 0.287513 data_time: 0.026596 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.865014 loss: 0.000551 2022/10/27 17:58:56 - mmengine - INFO - Epoch(train) [117][350/586] lr: 5.000000e-04 eta: 4:07:46 time: 0.288511 data_time: 0.028409 memory: 11131 loss_kpt: 0.000576 acc_pose: 0.893397 loss: 0.000576 2022/10/27 17:59:11 - mmengine - INFO - Epoch(train) [117][400/586] lr: 5.000000e-04 eta: 4:07:33 time: 0.284417 data_time: 0.028158 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.891770 loss: 0.000558 2022/10/27 17:59:25 - mmengine - INFO - Epoch(train) [117][450/586] lr: 5.000000e-04 eta: 4:07:20 time: 0.294468 data_time: 0.028320 memory: 11131 loss_kpt: 0.000532 acc_pose: 0.828117 loss: 0.000532 2022/10/27 17:59:40 - mmengine - INFO - Epoch(train) [117][500/586] lr: 5.000000e-04 eta: 4:07:07 time: 0.283162 data_time: 0.028133 memory: 11131 loss_kpt: 0.000549 acc_pose: 0.904782 loss: 0.000549 2022/10/27 17:59:54 - mmengine - INFO - Epoch(train) [117][550/586] lr: 5.000000e-04 eta: 4:06:54 time: 0.292592 data_time: 0.030649 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.812655 loss: 0.000568 2022/10/27 18:00:04 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:00:19 - mmengine - INFO - Epoch(train) [118][50/586] lr: 5.000000e-04 eta: 4:06:24 time: 0.296658 data_time: 0.038500 memory: 11131 loss_kpt: 0.000554 acc_pose: 0.856676 loss: 0.000554 2022/10/27 18:00:34 - mmengine - INFO - Epoch(train) [118][100/586] lr: 5.000000e-04 eta: 4:06:11 time: 0.290173 data_time: 0.028186 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.892448 loss: 0.000535 2022/10/27 18:00:48 - mmengine - INFO - Epoch(train) [118][150/586] lr: 5.000000e-04 eta: 4:05:58 time: 0.284156 data_time: 0.027795 memory: 11131 loss_kpt: 0.000540 acc_pose: 0.856740 loss: 0.000540 2022/10/27 18:01:03 - mmengine - INFO - Epoch(train) [118][200/586] lr: 5.000000e-04 eta: 4:05:45 time: 0.296566 data_time: 0.028370 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.830337 loss: 0.000555 2022/10/27 18:01:17 - mmengine - INFO - Epoch(train) [118][250/586] lr: 5.000000e-04 eta: 4:05:32 time: 0.284239 data_time: 0.028578 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.869137 loss: 0.000547 2022/10/27 18:01:31 - mmengine - INFO - Epoch(train) [118][300/586] lr: 5.000000e-04 eta: 4:05:19 time: 0.287172 data_time: 0.028078 memory: 11131 loss_kpt: 0.000559 acc_pose: 0.872169 loss: 0.000559 2022/10/27 18:01:46 - mmengine - INFO - Epoch(train) [118][350/586] lr: 5.000000e-04 eta: 4:05:06 time: 0.289066 data_time: 0.028559 memory: 11131 loss_kpt: 0.000560 acc_pose: 0.839590 loss: 0.000560 2022/10/27 18:02:00 - mmengine - INFO - Epoch(train) [118][400/586] lr: 5.000000e-04 eta: 4:04:53 time: 0.286466 data_time: 0.028501 memory: 11131 loss_kpt: 0.000559 acc_pose: 0.912699 loss: 0.000559 2022/10/27 18:02:11 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:02:15 - mmengine - INFO - Epoch(train) [118][450/586] lr: 5.000000e-04 eta: 4:04:41 time: 0.294406 data_time: 0.030614 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.869126 loss: 0.000539 2022/10/27 18:02:29 - mmengine - INFO - Epoch(train) [118][500/586] lr: 5.000000e-04 eta: 4:04:28 time: 0.287200 data_time: 0.027788 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.808921 loss: 0.000533 2022/10/27 18:02:44 - mmengine - INFO - Epoch(train) [118][550/586] lr: 5.000000e-04 eta: 4:04:15 time: 0.287667 data_time: 0.028239 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.860564 loss: 0.000558 2022/10/27 18:02:54 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:03:08 - mmengine - INFO - Epoch(train) [119][50/586] lr: 5.000000e-04 eta: 4:03:45 time: 0.290513 data_time: 0.038700 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.833285 loss: 0.000548 2022/10/27 18:03:23 - mmengine - INFO - Epoch(train) [119][100/586] lr: 5.000000e-04 eta: 4:03:32 time: 0.291742 data_time: 0.031578 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.842631 loss: 0.000548 2022/10/27 18:03:37 - mmengine - INFO - Epoch(train) [119][150/586] lr: 5.000000e-04 eta: 4:03:19 time: 0.288873 data_time: 0.030819 memory: 11131 loss_kpt: 0.000540 acc_pose: 0.911295 loss: 0.000540 2022/10/27 18:03:52 - mmengine - INFO - Epoch(train) [119][200/586] lr: 5.000000e-04 eta: 4:03:06 time: 0.288172 data_time: 0.027191 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.886786 loss: 0.000563 2022/10/27 18:04:06 - mmengine - INFO - Epoch(train) [119][250/586] lr: 5.000000e-04 eta: 4:02:53 time: 0.285363 data_time: 0.028171 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.866654 loss: 0.000561 2022/10/27 18:04:21 - mmengine - INFO - Epoch(train) [119][300/586] lr: 5.000000e-04 eta: 4:02:40 time: 0.289702 data_time: 0.032068 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.891364 loss: 0.000548 2022/10/27 18:04:35 - mmengine - INFO - Epoch(train) [119][350/586] lr: 5.000000e-04 eta: 4:02:27 time: 0.288328 data_time: 0.027076 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.817194 loss: 0.000585 2022/10/27 18:04:49 - mmengine - INFO - Epoch(train) [119][400/586] lr: 5.000000e-04 eta: 4:02:14 time: 0.285913 data_time: 0.027157 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.787288 loss: 0.000555 2022/10/27 18:05:04 - mmengine - INFO - Epoch(train) [119][450/586] lr: 5.000000e-04 eta: 4:02:01 time: 0.289268 data_time: 0.028600 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.818869 loss: 0.000562 2022/10/27 18:05:18 - mmengine - INFO - Epoch(train) [119][500/586] lr: 5.000000e-04 eta: 4:01:48 time: 0.286145 data_time: 0.029148 memory: 11131 loss_kpt: 0.000577 acc_pose: 0.912055 loss: 0.000577 2022/10/27 18:05:32 - mmengine - INFO - Epoch(train) [119][550/586] lr: 5.000000e-04 eta: 4:01:35 time: 0.288162 data_time: 0.028395 memory: 11131 loss_kpt: 0.000568 acc_pose: 0.882668 loss: 0.000568 2022/10/27 18:05:43 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:05:58 - mmengine - INFO - Epoch(train) [120][50/586] lr: 5.000000e-04 eta: 4:01:05 time: 0.295269 data_time: 0.038973 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.885426 loss: 0.000561 2022/10/27 18:06:12 - mmengine - INFO - Epoch(train) [120][100/586] lr: 5.000000e-04 eta: 4:00:52 time: 0.289207 data_time: 0.027876 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.860395 loss: 0.000538 2022/10/27 18:06:26 - mmengine - INFO - Epoch(train) [120][150/586] lr: 5.000000e-04 eta: 4:00:39 time: 0.285228 data_time: 0.028152 memory: 11131 loss_kpt: 0.000550 acc_pose: 0.817790 loss: 0.000550 2022/10/27 18:06:41 - mmengine - INFO - Epoch(train) [120][200/586] lr: 5.000000e-04 eta: 4:00:27 time: 0.294129 data_time: 0.032764 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.907818 loss: 0.000558 2022/10/27 18:06:55 - mmengine - INFO - Epoch(train) [120][250/586] lr: 5.000000e-04 eta: 4:00:14 time: 0.287686 data_time: 0.028245 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.765560 loss: 0.000562 2022/10/27 18:07:00 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:07:10 - mmengine - INFO - Epoch(train) [120][300/586] lr: 5.000000e-04 eta: 4:00:01 time: 0.289104 data_time: 0.031623 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.831281 loss: 0.000557 2022/10/27 18:07:24 - mmengine - INFO - Epoch(train) [120][350/586] lr: 5.000000e-04 eta: 3:59:48 time: 0.289286 data_time: 0.027923 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.845051 loss: 0.000543 2022/10/27 18:07:39 - mmengine - INFO - Epoch(train) [120][400/586] lr: 5.000000e-04 eta: 3:59:35 time: 0.284534 data_time: 0.032160 memory: 11131 loss_kpt: 0.000550 acc_pose: 0.825255 loss: 0.000550 2022/10/27 18:07:53 - mmengine - INFO - Epoch(train) [120][450/586] lr: 5.000000e-04 eta: 3:59:22 time: 0.292488 data_time: 0.033437 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.873412 loss: 0.000563 2022/10/27 18:08:07 - mmengine - INFO - Epoch(train) [120][500/586] lr: 5.000000e-04 eta: 3:59:09 time: 0.284270 data_time: 0.027604 memory: 11131 loss_kpt: 0.000554 acc_pose: 0.851499 loss: 0.000554 2022/10/27 18:08:22 - mmengine - INFO - Epoch(train) [120][550/586] lr: 5.000000e-04 eta: 3:58:56 time: 0.287176 data_time: 0.029013 memory: 11131 loss_kpt: 0.000554 acc_pose: 0.828000 loss: 0.000554 2022/10/27 18:08:32 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:08:32 - mmengine - INFO - Saving checkpoint at 120 epochs 2022/10/27 18:08:43 - mmengine - INFO - Epoch(val) [120][50/407] eta: 0:00:51 time: 0.143816 data_time: 0.023515 memory: 11131 2022/10/27 18:08:50 - mmengine - INFO - Epoch(val) [120][100/407] eta: 0:00:41 time: 0.134128 data_time: 0.014977 memory: 1836 2022/10/27 18:08:56 - mmengine - INFO - Epoch(val) [120][150/407] eta: 0:00:33 time: 0.131938 data_time: 0.013189 memory: 1836 2022/10/27 18:09:03 - mmengine - INFO - Epoch(val) [120][200/407] eta: 0:00:28 time: 0.135560 data_time: 0.014700 memory: 1836 2022/10/27 18:09:10 - mmengine - INFO - Epoch(val) [120][250/407] eta: 0:00:21 time: 0.133801 data_time: 0.013510 memory: 1836 2022/10/27 18:09:17 - mmengine - INFO - Epoch(val) [120][300/407] eta: 0:00:14 time: 0.138402 data_time: 0.017509 memory: 1836 2022/10/27 18:09:23 - mmengine - INFO - Epoch(val) [120][350/407] eta: 0:00:07 time: 0.132140 data_time: 0.011115 memory: 1836 2022/10/27 18:09:30 - mmengine - INFO - Epoch(val) [120][400/407] eta: 0:00:00 time: 0.132752 data_time: 0.016340 memory: 1836 2022/10/27 18:10:18 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 18:10:35 - mmengine - INFO - Epoch(val) [120][407/407] coco/AP: 0.742179 coco/AP .5: 0.901501 coco/AP .75: 0.812290 coco/AP (M): 0.702179 coco/AP (L): 0.810935 coco/AR: 0.793624 coco/AR .5: 0.938917 coco/AR .75: 0.858627 coco/AR (M): 0.748784 coco/AR (L): 0.857897 2022/10/27 18:10:35 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_100.pth is removed 2022/10/27 18:10:37 - mmengine - INFO - The best checkpoint with 0.7422 coco/AP at 120 epoch is saved to best_coco/AP_epoch_120.pth. 2022/10/27 18:10:52 - mmengine - INFO - Epoch(train) [121][50/586] lr: 5.000000e-04 eta: 3:58:26 time: 0.289123 data_time: 0.035317 memory: 11131 loss_kpt: 0.000574 acc_pose: 0.792726 loss: 0.000574 2022/10/27 18:11:06 - mmengine - INFO - Epoch(train) [121][100/586] lr: 5.000000e-04 eta: 3:58:13 time: 0.288164 data_time: 0.027460 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.864404 loss: 0.000557 2022/10/27 18:11:21 - mmengine - INFO - Epoch(train) [121][150/586] lr: 5.000000e-04 eta: 3:58:00 time: 0.292002 data_time: 0.029246 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.881285 loss: 0.000558 2022/10/27 18:11:36 - mmengine - INFO - Epoch(train) [121][200/586] lr: 5.000000e-04 eta: 3:57:47 time: 0.292620 data_time: 0.030692 memory: 11131 loss_kpt: 0.000556 acc_pose: 0.871890 loss: 0.000556 2022/10/27 18:11:50 - mmengine - INFO - Epoch(train) [121][250/586] lr: 5.000000e-04 eta: 3:57:34 time: 0.288246 data_time: 0.028224 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.835930 loss: 0.000545 2022/10/27 18:12:04 - mmengine - INFO - Epoch(train) [121][300/586] lr: 5.000000e-04 eta: 3:57:21 time: 0.281116 data_time: 0.026703 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.886521 loss: 0.000541 2022/10/27 18:12:19 - mmengine - INFO - Epoch(train) [121][350/586] lr: 5.000000e-04 eta: 3:57:08 time: 0.290328 data_time: 0.030839 memory: 11131 loss_kpt: 0.000560 acc_pose: 0.827003 loss: 0.000560 2022/10/27 18:12:33 - mmengine - INFO - Epoch(train) [121][400/586] lr: 5.000000e-04 eta: 3:56:55 time: 0.293395 data_time: 0.028735 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.826189 loss: 0.000561 2022/10/27 18:12:48 - mmengine - INFO - Epoch(train) [121][450/586] lr: 5.000000e-04 eta: 3:56:42 time: 0.288846 data_time: 0.028053 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.902955 loss: 0.000570 2022/10/27 18:13:02 - mmengine - INFO - Epoch(train) [121][500/586] lr: 5.000000e-04 eta: 3:56:29 time: 0.285931 data_time: 0.027356 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.878141 loss: 0.000558 2022/10/27 18:13:16 - mmengine - INFO - Epoch(train) [121][550/586] lr: 5.000000e-04 eta: 3:56:16 time: 0.287801 data_time: 0.029935 memory: 11131 loss_kpt: 0.000576 acc_pose: 0.775660 loss: 0.000576 2022/10/27 18:13:27 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:13:42 - mmengine - INFO - Epoch(train) [122][50/586] lr: 5.000000e-04 eta: 3:55:47 time: 0.299422 data_time: 0.041117 memory: 11131 loss_kpt: 0.000562 acc_pose: 0.850392 loss: 0.000562 2022/10/27 18:13:54 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:13:56 - mmengine - INFO - Epoch(train) [122][100/586] lr: 5.000000e-04 eta: 3:55:34 time: 0.289531 data_time: 0.028319 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.927436 loss: 0.000563 2022/10/27 18:14:10 - mmengine - INFO - Epoch(train) [122][150/586] lr: 5.000000e-04 eta: 3:55:21 time: 0.285126 data_time: 0.028168 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.835998 loss: 0.000552 2022/10/27 18:14:25 - mmengine - INFO - Epoch(train) [122][200/586] lr: 5.000000e-04 eta: 3:55:08 time: 0.288637 data_time: 0.028063 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.836532 loss: 0.000557 2022/10/27 18:14:39 - mmengine - INFO - Epoch(train) [122][250/586] lr: 5.000000e-04 eta: 3:54:55 time: 0.284312 data_time: 0.028211 memory: 11131 loss_kpt: 0.000556 acc_pose: 0.810026 loss: 0.000556 2022/10/27 18:14:53 - mmengine - INFO - Epoch(train) [122][300/586] lr: 5.000000e-04 eta: 3:54:42 time: 0.287525 data_time: 0.029728 memory: 11131 loss_kpt: 0.000527 acc_pose: 0.851410 loss: 0.000527 2022/10/27 18:15:08 - mmengine - INFO - Epoch(train) [122][350/586] lr: 5.000000e-04 eta: 3:54:29 time: 0.292182 data_time: 0.030767 memory: 11131 loss_kpt: 0.000536 acc_pose: 0.881737 loss: 0.000536 2022/10/27 18:15:22 - mmengine - INFO - Epoch(train) [122][400/586] lr: 5.000000e-04 eta: 3:54:16 time: 0.284729 data_time: 0.027296 memory: 11131 loss_kpt: 0.000549 acc_pose: 0.830406 loss: 0.000549 2022/10/27 18:15:37 - mmengine - INFO - Epoch(train) [122][450/586] lr: 5.000000e-04 eta: 3:54:03 time: 0.288554 data_time: 0.026560 memory: 11131 loss_kpt: 0.000531 acc_pose: 0.889666 loss: 0.000531 2022/10/27 18:15:51 - mmengine - INFO - Epoch(train) [122][500/586] lr: 5.000000e-04 eta: 3:53:50 time: 0.286903 data_time: 0.027256 memory: 11131 loss_kpt: 0.000554 acc_pose: 0.771123 loss: 0.000554 2022/10/27 18:16:06 - mmengine - INFO - Epoch(train) [122][550/586] lr: 5.000000e-04 eta: 3:53:37 time: 0.295390 data_time: 0.028759 memory: 11131 loss_kpt: 0.000549 acc_pose: 0.855499 loss: 0.000549 2022/10/27 18:16:16 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:16:30 - mmengine - INFO - Epoch(train) [123][50/586] lr: 5.000000e-04 eta: 3:53:07 time: 0.290740 data_time: 0.039880 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.881599 loss: 0.000543 2022/10/27 18:16:45 - mmengine - INFO - Epoch(train) [123][100/586] lr: 5.000000e-04 eta: 3:52:55 time: 0.289239 data_time: 0.029967 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.867076 loss: 0.000547 2022/10/27 18:16:59 - mmengine - INFO - Epoch(train) [123][150/586] lr: 5.000000e-04 eta: 3:52:41 time: 0.283155 data_time: 0.027646 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.855402 loss: 0.000569 2022/10/27 18:17:14 - mmengine - INFO - Epoch(train) [123][200/586] lr: 5.000000e-04 eta: 3:52:29 time: 0.292945 data_time: 0.027410 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.890464 loss: 0.000552 2022/10/27 18:17:28 - mmengine - INFO - Epoch(train) [123][250/586] lr: 5.000000e-04 eta: 3:52:15 time: 0.284070 data_time: 0.026954 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.833427 loss: 0.000541 2022/10/27 18:17:42 - mmengine - INFO - Epoch(train) [123][300/586] lr: 5.000000e-04 eta: 3:52:02 time: 0.288989 data_time: 0.029349 memory: 11131 loss_kpt: 0.000570 acc_pose: 0.860677 loss: 0.000570 2022/10/27 18:17:57 - mmengine - INFO - Epoch(train) [123][350/586] lr: 5.000000e-04 eta: 3:51:50 time: 0.290768 data_time: 0.029443 memory: 11131 loss_kpt: 0.000553 acc_pose: 0.839488 loss: 0.000553 2022/10/27 18:18:11 - mmengine - INFO - Epoch(train) [123][400/586] lr: 5.000000e-04 eta: 3:51:37 time: 0.287183 data_time: 0.027603 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.879811 loss: 0.000547 2022/10/27 18:18:26 - mmengine - INFO - Epoch(train) [123][450/586] lr: 5.000000e-04 eta: 3:51:24 time: 0.286976 data_time: 0.028593 memory: 11131 loss_kpt: 0.000556 acc_pose: 0.882002 loss: 0.000556 2022/10/27 18:18:40 - mmengine - INFO - Epoch(train) [123][500/586] lr: 5.000000e-04 eta: 3:51:10 time: 0.285606 data_time: 0.029206 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.824488 loss: 0.000524 2022/10/27 18:18:42 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:18:54 - mmengine - INFO - Epoch(train) [123][550/586] lr: 5.000000e-04 eta: 3:50:57 time: 0.284572 data_time: 0.030054 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.787692 loss: 0.000548 2022/10/27 18:19:04 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:19:19 - mmengine - INFO - Epoch(train) [124][50/586] lr: 5.000000e-04 eta: 3:50:28 time: 0.296336 data_time: 0.039478 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.815556 loss: 0.000552 2022/10/27 18:19:34 - mmengine - INFO - Epoch(train) [124][100/586] lr: 5.000000e-04 eta: 3:50:15 time: 0.291462 data_time: 0.028956 memory: 11131 loss_kpt: 0.000560 acc_pose: 0.742960 loss: 0.000560 2022/10/27 18:19:48 - mmengine - INFO - Epoch(train) [124][150/586] lr: 5.000000e-04 eta: 3:50:02 time: 0.285797 data_time: 0.027825 memory: 11131 loss_kpt: 0.000536 acc_pose: 0.822063 loss: 0.000536 2022/10/27 18:20:03 - mmengine - INFO - Epoch(train) [124][200/586] lr: 5.000000e-04 eta: 3:49:49 time: 0.289710 data_time: 0.029653 memory: 11131 loss_kpt: 0.000556 acc_pose: 0.772916 loss: 0.000556 2022/10/27 18:20:17 - mmengine - INFO - Epoch(train) [124][250/586] lr: 5.000000e-04 eta: 3:49:36 time: 0.284545 data_time: 0.028513 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.890514 loss: 0.000545 2022/10/27 18:20:31 - mmengine - INFO - Epoch(train) [124][300/586] lr: 5.000000e-04 eta: 3:49:23 time: 0.288119 data_time: 0.028095 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.895867 loss: 0.000539 2022/10/27 18:20:46 - mmengine - INFO - Epoch(train) [124][350/586] lr: 5.000000e-04 eta: 3:49:10 time: 0.287391 data_time: 0.028844 memory: 11131 loss_kpt: 0.000574 acc_pose: 0.840713 loss: 0.000574 2022/10/27 18:21:00 - mmengine - INFO - Epoch(train) [124][400/586] lr: 5.000000e-04 eta: 3:48:57 time: 0.288798 data_time: 0.029670 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.785646 loss: 0.000539 2022/10/27 18:21:14 - mmengine - INFO - Epoch(train) [124][450/586] lr: 5.000000e-04 eta: 3:48:44 time: 0.285367 data_time: 0.028292 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.827737 loss: 0.000561 2022/10/27 18:21:29 - mmengine - INFO - Epoch(train) [124][500/586] lr: 5.000000e-04 eta: 3:48:31 time: 0.290630 data_time: 0.033653 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.864496 loss: 0.000552 2022/10/27 18:21:43 - mmengine - INFO - Epoch(train) [124][550/586] lr: 5.000000e-04 eta: 3:48:18 time: 0.289355 data_time: 0.029349 memory: 11131 loss_kpt: 0.000559 acc_pose: 0.891016 loss: 0.000559 2022/10/27 18:21:53 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:22:08 - mmengine - INFO - Epoch(train) [125][50/586] lr: 5.000000e-04 eta: 3:47:49 time: 0.294649 data_time: 0.036215 memory: 11131 loss_kpt: 0.000561 acc_pose: 0.855195 loss: 0.000561 2022/10/27 18:22:23 - mmengine - INFO - Epoch(train) [125][100/586] lr: 5.000000e-04 eta: 3:47:36 time: 0.288638 data_time: 0.027843 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.898890 loss: 0.000543 2022/10/27 18:22:37 - mmengine - INFO - Epoch(train) [125][150/586] lr: 5.000000e-04 eta: 3:47:23 time: 0.288594 data_time: 0.027650 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.821703 loss: 0.000546 2022/10/27 18:22:52 - mmengine - INFO - Epoch(train) [125][200/586] lr: 5.000000e-04 eta: 3:47:10 time: 0.291831 data_time: 0.028985 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.833111 loss: 0.000558 2022/10/27 18:23:06 - mmengine - INFO - Epoch(train) [125][250/586] lr: 5.000000e-04 eta: 3:46:57 time: 0.284701 data_time: 0.029641 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.929744 loss: 0.000535 2022/10/27 18:23:20 - mmengine - INFO - Epoch(train) [125][300/586] lr: 5.000000e-04 eta: 3:46:44 time: 0.286409 data_time: 0.029427 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.867076 loss: 0.000558 2022/10/27 18:23:31 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:23:35 - mmengine - INFO - Epoch(train) [125][350/586] lr: 5.000000e-04 eta: 3:46:30 time: 0.286957 data_time: 0.029089 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.882470 loss: 0.000538 2022/10/27 18:23:49 - mmengine - INFO - Epoch(train) [125][400/586] lr: 5.000000e-04 eta: 3:46:18 time: 0.290247 data_time: 0.034086 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.843831 loss: 0.000541 2022/10/27 18:24:03 - mmengine - INFO - Epoch(train) [125][450/586] lr: 5.000000e-04 eta: 3:46:05 time: 0.287603 data_time: 0.028223 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.883680 loss: 0.000555 2022/10/27 18:24:18 - mmengine - INFO - Epoch(train) [125][500/586] lr: 5.000000e-04 eta: 3:45:52 time: 0.289105 data_time: 0.027525 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.858727 loss: 0.000563 2022/10/27 18:24:32 - mmengine - INFO - Epoch(train) [125][550/586] lr: 5.000000e-04 eta: 3:45:38 time: 0.286116 data_time: 0.030729 memory: 11131 loss_kpt: 0.000585 acc_pose: 0.888059 loss: 0.000585 2022/10/27 18:24:42 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:24:57 - mmengine - INFO - Epoch(train) [126][50/586] lr: 5.000000e-04 eta: 3:45:09 time: 0.299628 data_time: 0.041428 memory: 11131 loss_kpt: 0.000540 acc_pose: 0.807708 loss: 0.000540 2022/10/27 18:25:12 - mmengine - INFO - Epoch(train) [126][100/586] lr: 5.000000e-04 eta: 3:44:57 time: 0.292338 data_time: 0.028799 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.842515 loss: 0.000557 2022/10/27 18:25:26 - mmengine - INFO - Epoch(train) [126][150/586] lr: 5.000000e-04 eta: 3:44:44 time: 0.289963 data_time: 0.032024 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.816687 loss: 0.000555 2022/10/27 18:25:41 - mmengine - INFO - Epoch(train) [126][200/586] lr: 5.000000e-04 eta: 3:44:31 time: 0.291277 data_time: 0.028349 memory: 11131 loss_kpt: 0.000550 acc_pose: 0.875622 loss: 0.000550 2022/10/27 18:25:55 - mmengine - INFO - Epoch(train) [126][250/586] lr: 5.000000e-04 eta: 3:44:18 time: 0.287727 data_time: 0.028361 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.826974 loss: 0.000541 2022/10/27 18:26:10 - mmengine - INFO - Epoch(train) [126][300/586] lr: 5.000000e-04 eta: 3:44:05 time: 0.287030 data_time: 0.028921 memory: 11131 loss_kpt: 0.000544 acc_pose: 0.869117 loss: 0.000544 2022/10/27 18:26:24 - mmengine - INFO - Epoch(train) [126][350/586] lr: 5.000000e-04 eta: 3:43:52 time: 0.289435 data_time: 0.028950 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.775429 loss: 0.000552 2022/10/27 18:26:38 - mmengine - INFO - Epoch(train) [126][400/586] lr: 5.000000e-04 eta: 3:43:38 time: 0.283440 data_time: 0.026896 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.829347 loss: 0.000552 2022/10/27 18:26:53 - mmengine - INFO - Epoch(train) [126][450/586] lr: 5.000000e-04 eta: 3:43:26 time: 0.292306 data_time: 0.029309 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.893955 loss: 0.000542 2022/10/27 18:27:08 - mmengine - INFO - Epoch(train) [126][500/586] lr: 5.000000e-04 eta: 3:43:13 time: 0.293762 data_time: 0.027857 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.880667 loss: 0.000546 2022/10/27 18:27:22 - mmengine - INFO - Epoch(train) [126][550/586] lr: 5.000000e-04 eta: 3:43:00 time: 0.289581 data_time: 0.028082 memory: 11131 loss_kpt: 0.000550 acc_pose: 0.778533 loss: 0.000550 2022/10/27 18:27:32 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:27:47 - mmengine - INFO - Epoch(train) [127][50/586] lr: 5.000000e-04 eta: 3:42:31 time: 0.294756 data_time: 0.037417 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.909356 loss: 0.000534 2022/10/27 18:28:02 - mmengine - INFO - Epoch(train) [127][100/586] lr: 5.000000e-04 eta: 3:42:18 time: 0.287481 data_time: 0.028876 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.834900 loss: 0.000543 2022/10/27 18:28:16 - mmengine - INFO - Epoch(train) [127][150/586] lr: 5.000000e-04 eta: 3:42:05 time: 0.287589 data_time: 0.031459 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.823701 loss: 0.000546 2022/10/27 18:28:20 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:28:31 - mmengine - INFO - Epoch(train) [127][200/586] lr: 5.000000e-04 eta: 3:41:52 time: 0.291832 data_time: 0.027391 memory: 11131 loss_kpt: 0.000556 acc_pose: 0.846978 loss: 0.000556 2022/10/27 18:28:45 - mmengine - INFO - Epoch(train) [127][250/586] lr: 5.000000e-04 eta: 3:41:38 time: 0.282162 data_time: 0.029209 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.811472 loss: 0.000552 2022/10/27 18:28:59 - mmengine - INFO - Epoch(train) [127][300/586] lr: 5.000000e-04 eta: 3:41:25 time: 0.286717 data_time: 0.027775 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.864844 loss: 0.000547 2022/10/27 18:29:14 - mmengine - INFO - Epoch(train) [127][350/586] lr: 5.000000e-04 eta: 3:41:12 time: 0.290834 data_time: 0.029169 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.847507 loss: 0.000563 2022/10/27 18:29:28 - mmengine - INFO - Epoch(train) [127][400/586] lr: 5.000000e-04 eta: 3:40:59 time: 0.286485 data_time: 0.028251 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.856680 loss: 0.000545 2022/10/27 18:29:42 - mmengine - INFO - Epoch(train) [127][450/586] lr: 5.000000e-04 eta: 3:40:46 time: 0.292335 data_time: 0.030130 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.850616 loss: 0.000535 2022/10/27 18:29:57 - mmengine - INFO - Epoch(train) [127][500/586] lr: 5.000000e-04 eta: 3:40:33 time: 0.285124 data_time: 0.028266 memory: 11131 loss_kpt: 0.000553 acc_pose: 0.771963 loss: 0.000553 2022/10/27 18:30:11 - mmengine - INFO - Epoch(train) [127][550/586] lr: 5.000000e-04 eta: 3:40:20 time: 0.290788 data_time: 0.027124 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.855525 loss: 0.000547 2022/10/27 18:30:21 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:30:36 - mmengine - INFO - Epoch(train) [128][50/586] lr: 5.000000e-04 eta: 3:39:51 time: 0.299447 data_time: 0.040438 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.808222 loss: 0.000547 2022/10/27 18:30:51 - mmengine - INFO - Epoch(train) [128][100/586] lr: 5.000000e-04 eta: 3:39:38 time: 0.289278 data_time: 0.027011 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.891904 loss: 0.000545 2022/10/27 18:31:05 - mmengine - INFO - Epoch(train) [128][150/586] lr: 5.000000e-04 eta: 3:39:25 time: 0.286335 data_time: 0.028993 memory: 11131 loss_kpt: 0.000553 acc_pose: 0.872881 loss: 0.000553 2022/10/27 18:31:20 - mmengine - INFO - Epoch(train) [128][200/586] lr: 5.000000e-04 eta: 3:39:12 time: 0.288997 data_time: 0.032537 memory: 11131 loss_kpt: 0.000550 acc_pose: 0.831848 loss: 0.000550 2022/10/27 18:31:34 - mmengine - INFO - Epoch(train) [128][250/586] lr: 5.000000e-04 eta: 3:38:59 time: 0.289570 data_time: 0.028950 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.830772 loss: 0.000541 2022/10/27 18:31:48 - mmengine - INFO - Epoch(train) [128][300/586] lr: 5.000000e-04 eta: 3:38:46 time: 0.285748 data_time: 0.031289 memory: 11131 loss_kpt: 0.000569 acc_pose: 0.858644 loss: 0.000569 2022/10/27 18:32:03 - mmengine - INFO - Epoch(train) [128][350/586] lr: 5.000000e-04 eta: 3:38:33 time: 0.284095 data_time: 0.031292 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.883874 loss: 0.000542 2022/10/27 18:32:17 - mmengine - INFO - Epoch(train) [128][400/586] lr: 5.000000e-04 eta: 3:38:20 time: 0.283765 data_time: 0.028194 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.808929 loss: 0.000551 2022/10/27 18:32:31 - mmengine - INFO - Epoch(train) [128][450/586] lr: 5.000000e-04 eta: 3:38:07 time: 0.287959 data_time: 0.028429 memory: 11131 loss_kpt: 0.000544 acc_pose: 0.816794 loss: 0.000544 2022/10/27 18:32:46 - mmengine - INFO - Epoch(train) [128][500/586] lr: 5.000000e-04 eta: 3:37:54 time: 0.292956 data_time: 0.032459 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.801751 loss: 0.000563 2022/10/27 18:33:00 - mmengine - INFO - Epoch(train) [128][550/586] lr: 5.000000e-04 eta: 3:37:41 time: 0.289602 data_time: 0.028081 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.865969 loss: 0.000541 2022/10/27 18:33:08 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:33:10 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:33:25 - mmengine - INFO - Epoch(train) [129][50/586] lr: 5.000000e-04 eta: 3:37:12 time: 0.299944 data_time: 0.036186 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.924900 loss: 0.000555 2022/10/27 18:33:40 - mmengine - INFO - Epoch(train) [129][100/586] lr: 5.000000e-04 eta: 3:36:59 time: 0.289351 data_time: 0.030017 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.844653 loss: 0.000558 2022/10/27 18:33:54 - mmengine - INFO - Epoch(train) [129][150/586] lr: 5.000000e-04 eta: 3:36:46 time: 0.288482 data_time: 0.033351 memory: 11131 loss_kpt: 0.000518 acc_pose: 0.850303 loss: 0.000518 2022/10/27 18:34:09 - mmengine - INFO - Epoch(train) [129][200/586] lr: 5.000000e-04 eta: 3:36:33 time: 0.291708 data_time: 0.031715 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.861722 loss: 0.000555 2022/10/27 18:34:23 - mmengine - INFO - Epoch(train) [129][250/586] lr: 5.000000e-04 eta: 3:36:20 time: 0.284894 data_time: 0.029303 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.844049 loss: 0.000552 2022/10/27 18:34:37 - mmengine - INFO - Epoch(train) [129][300/586] lr: 5.000000e-04 eta: 3:36:07 time: 0.284305 data_time: 0.028329 memory: 11131 loss_kpt: 0.000527 acc_pose: 0.787575 loss: 0.000527 2022/10/27 18:34:52 - mmengine - INFO - Epoch(train) [129][350/586] lr: 5.000000e-04 eta: 3:35:54 time: 0.286759 data_time: 0.026315 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.806580 loss: 0.000533 2022/10/27 18:35:06 - mmengine - INFO - Epoch(train) [129][400/586] lr: 5.000000e-04 eta: 3:35:41 time: 0.286911 data_time: 0.027978 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.843264 loss: 0.000548 2022/10/27 18:35:21 - mmengine - INFO - Epoch(train) [129][450/586] lr: 5.000000e-04 eta: 3:35:28 time: 0.292838 data_time: 0.031090 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.891573 loss: 0.000558 2022/10/27 18:35:35 - mmengine - INFO - Epoch(train) [129][500/586] lr: 5.000000e-04 eta: 3:35:15 time: 0.283881 data_time: 0.029826 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.831112 loss: 0.000545 2022/10/27 18:35:49 - mmengine - INFO - Epoch(train) [129][550/586] lr: 5.000000e-04 eta: 3:35:02 time: 0.290831 data_time: 0.029213 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.884604 loss: 0.000547 2022/10/27 18:36:00 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:36:15 - mmengine - INFO - Epoch(train) [130][50/586] lr: 5.000000e-04 eta: 3:34:33 time: 0.301590 data_time: 0.038126 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.868113 loss: 0.000542 2022/10/27 18:36:29 - mmengine - INFO - Epoch(train) [130][100/586] lr: 5.000000e-04 eta: 3:34:20 time: 0.290452 data_time: 0.029183 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.858766 loss: 0.000539 2022/10/27 18:36:44 - mmengine - INFO - Epoch(train) [130][150/586] lr: 5.000000e-04 eta: 3:34:07 time: 0.288110 data_time: 0.031449 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.905204 loss: 0.000545 2022/10/27 18:36:58 - mmengine - INFO - Epoch(train) [130][200/586] lr: 5.000000e-04 eta: 3:33:54 time: 0.286426 data_time: 0.028112 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.843081 loss: 0.000543 2022/10/27 18:37:12 - mmengine - INFO - Epoch(train) [130][250/586] lr: 5.000000e-04 eta: 3:33:41 time: 0.283904 data_time: 0.027589 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.845591 loss: 0.000542 2022/10/27 18:37:27 - mmengine - INFO - Epoch(train) [130][300/586] lr: 5.000000e-04 eta: 3:33:28 time: 0.288833 data_time: 0.027436 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.865817 loss: 0.000535 2022/10/27 18:37:41 - mmengine - INFO - Epoch(train) [130][350/586] lr: 5.000000e-04 eta: 3:33:15 time: 0.282365 data_time: 0.026779 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.857692 loss: 0.000535 2022/10/27 18:37:55 - mmengine - INFO - Epoch(train) [130][400/586] lr: 5.000000e-04 eta: 3:33:01 time: 0.283872 data_time: 0.028921 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.855303 loss: 0.000551 2022/10/27 18:37:57 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:38:09 - mmengine - INFO - Epoch(train) [130][450/586] lr: 5.000000e-04 eta: 3:32:48 time: 0.285788 data_time: 0.026812 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.888027 loss: 0.000542 2022/10/27 18:38:24 - mmengine - INFO - Epoch(train) [130][500/586] lr: 5.000000e-04 eta: 3:32:35 time: 0.287651 data_time: 0.030065 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.847305 loss: 0.000525 2022/10/27 18:38:38 - mmengine - INFO - Epoch(train) [130][550/586] lr: 5.000000e-04 eta: 3:32:22 time: 0.292050 data_time: 0.027008 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.861143 loss: 0.000539 2022/10/27 18:38:48 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:38:48 - mmengine - INFO - Saving checkpoint at 130 epochs 2022/10/27 18:38:59 - mmengine - INFO - Epoch(val) [130][50/407] eta: 0:00:51 time: 0.144339 data_time: 0.019887 memory: 11131 2022/10/27 18:39:06 - mmengine - INFO - Epoch(val) [130][100/407] eta: 0:00:40 time: 0.131845 data_time: 0.013068 memory: 1836 2022/10/27 18:39:12 - mmengine - INFO - Epoch(val) [130][150/407] eta: 0:00:34 time: 0.132681 data_time: 0.012697 memory: 1836 2022/10/27 18:39:19 - mmengine - INFO - Epoch(val) [130][200/407] eta: 0:00:27 time: 0.133737 data_time: 0.013215 memory: 1836 2022/10/27 18:39:26 - mmengine - INFO - Epoch(val) [130][250/407] eta: 0:00:20 time: 0.132064 data_time: 0.013522 memory: 1836 2022/10/27 18:39:33 - mmengine - INFO - Epoch(val) [130][300/407] eta: 0:00:14 time: 0.136092 data_time: 0.016030 memory: 1836 2022/10/27 18:39:40 - mmengine - INFO - Epoch(val) [130][350/407] eta: 0:00:08 time: 0.147761 data_time: 0.028325 memory: 1836 2022/10/27 18:39:46 - mmengine - INFO - Epoch(val) [130][400/407] eta: 0:00:00 time: 0.129625 data_time: 0.014425 memory: 1836 2022/10/27 18:40:33 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 18:40:50 - mmengine - INFO - Epoch(val) [130][407/407] coco/AP: 0.740783 coco/AP .5: 0.902266 coco/AP .75: 0.810893 coco/AP (M): 0.697693 coco/AP (L): 0.813838 coco/AR: 0.791121 coco/AR .5: 0.938917 coco/AR .75: 0.854062 coco/AR (M): 0.745315 coco/AR (L): 0.857674 2022/10/27 18:41:05 - mmengine - INFO - Epoch(train) [131][50/586] lr: 5.000000e-04 eta: 3:31:53 time: 0.294807 data_time: 0.039074 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.794710 loss: 0.000545 2022/10/27 18:41:19 - mmengine - INFO - Epoch(train) [131][100/586] lr: 5.000000e-04 eta: 3:31:40 time: 0.288163 data_time: 0.027569 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.842183 loss: 0.000542 2022/10/27 18:41:33 - mmengine - INFO - Epoch(train) [131][150/586] lr: 5.000000e-04 eta: 3:31:27 time: 0.284765 data_time: 0.027542 memory: 11131 loss_kpt: 0.000558 acc_pose: 0.845590 loss: 0.000558 2022/10/27 18:41:48 - mmengine - INFO - Epoch(train) [131][200/586] lr: 5.000000e-04 eta: 3:31:14 time: 0.290555 data_time: 0.027293 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.847751 loss: 0.000538 2022/10/27 18:42:02 - mmengine - INFO - Epoch(train) [131][250/586] lr: 5.000000e-04 eta: 3:31:01 time: 0.288466 data_time: 0.027792 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.841956 loss: 0.000548 2022/10/27 18:42:17 - mmengine - INFO - Epoch(train) [131][300/586] lr: 5.000000e-04 eta: 3:30:48 time: 0.284053 data_time: 0.026637 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.809674 loss: 0.000533 2022/10/27 18:42:31 - mmengine - INFO - Epoch(train) [131][350/586] lr: 5.000000e-04 eta: 3:30:35 time: 0.289182 data_time: 0.036833 memory: 11131 loss_kpt: 0.000559 acc_pose: 0.879788 loss: 0.000559 2022/10/27 18:42:45 - mmengine - INFO - Epoch(train) [131][400/586] lr: 5.000000e-04 eta: 3:30:22 time: 0.284810 data_time: 0.030471 memory: 11131 loss_kpt: 0.000540 acc_pose: 0.878392 loss: 0.000540 2022/10/27 18:43:00 - mmengine - INFO - Epoch(train) [131][450/586] lr: 5.000000e-04 eta: 3:30:09 time: 0.295135 data_time: 0.031176 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.875345 loss: 0.000538 2022/10/27 18:43:15 - mmengine - INFO - Epoch(train) [131][500/586] lr: 5.000000e-04 eta: 3:29:56 time: 0.289774 data_time: 0.026986 memory: 11131 loss_kpt: 0.000559 acc_pose: 0.903682 loss: 0.000559 2022/10/27 18:43:29 - mmengine - INFO - Epoch(train) [131][550/586] lr: 5.000000e-04 eta: 3:29:43 time: 0.285719 data_time: 0.029070 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.837751 loss: 0.000542 2022/10/27 18:43:39 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:43:54 - mmengine - INFO - Epoch(train) [132][50/586] lr: 5.000000e-04 eta: 3:29:14 time: 0.297777 data_time: 0.035957 memory: 11131 loss_kpt: 0.000527 acc_pose: 0.776954 loss: 0.000527 2022/10/27 18:44:09 - mmengine - INFO - Epoch(train) [132][100/586] lr: 5.000000e-04 eta: 3:29:01 time: 0.290949 data_time: 0.027654 memory: 11131 loss_kpt: 0.000549 acc_pose: 0.844576 loss: 0.000549 2022/10/27 18:44:23 - mmengine - INFO - Epoch(train) [132][150/586] lr: 5.000000e-04 eta: 3:28:48 time: 0.285677 data_time: 0.028141 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.859731 loss: 0.000557 2022/10/27 18:44:37 - mmengine - INFO - Epoch(train) [132][200/586] lr: 5.000000e-04 eta: 3:28:35 time: 0.282041 data_time: 0.026954 memory: 11131 loss_kpt: 0.000536 acc_pose: 0.908762 loss: 0.000536 2022/10/27 18:44:47 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:44:52 - mmengine - INFO - Epoch(train) [132][250/586] lr: 5.000000e-04 eta: 3:28:22 time: 0.290863 data_time: 0.034125 memory: 11131 loss_kpt: 0.000565 acc_pose: 0.848708 loss: 0.000565 2022/10/27 18:45:06 - mmengine - INFO - Epoch(train) [132][300/586] lr: 5.000000e-04 eta: 3:28:09 time: 0.287801 data_time: 0.027022 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.870530 loss: 0.000563 2022/10/27 18:45:20 - mmengine - INFO - Epoch(train) [132][350/586] lr: 5.000000e-04 eta: 3:27:56 time: 0.289056 data_time: 0.028428 memory: 11131 loss_kpt: 0.000550 acc_pose: 0.829814 loss: 0.000550 2022/10/27 18:45:35 - mmengine - INFO - Epoch(train) [132][400/586] lr: 5.000000e-04 eta: 3:27:43 time: 0.284980 data_time: 0.030410 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.864754 loss: 0.000539 2022/10/27 18:45:49 - mmengine - INFO - Epoch(train) [132][450/586] lr: 5.000000e-04 eta: 3:27:29 time: 0.287027 data_time: 0.028219 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.847691 loss: 0.000546 2022/10/27 18:46:03 - mmengine - INFO - Epoch(train) [132][500/586] lr: 5.000000e-04 eta: 3:27:16 time: 0.288275 data_time: 0.032368 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.893070 loss: 0.000543 2022/10/27 18:46:18 - mmengine - INFO - Epoch(train) [132][550/586] lr: 5.000000e-04 eta: 3:27:03 time: 0.288494 data_time: 0.030390 memory: 11131 loss_kpt: 0.000549 acc_pose: 0.856654 loss: 0.000549 2022/10/27 18:46:28 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:46:43 - mmengine - INFO - Epoch(train) [133][50/586] lr: 5.000000e-04 eta: 3:26:35 time: 0.297487 data_time: 0.035772 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.860951 loss: 0.000541 2022/10/27 18:46:57 - mmengine - INFO - Epoch(train) [133][100/586] lr: 5.000000e-04 eta: 3:26:22 time: 0.285225 data_time: 0.028193 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.865011 loss: 0.000547 2022/10/27 18:47:12 - mmengine - INFO - Epoch(train) [133][150/586] lr: 5.000000e-04 eta: 3:26:09 time: 0.293631 data_time: 0.034459 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.863903 loss: 0.000534 2022/10/27 18:47:26 - mmengine - INFO - Epoch(train) [133][200/586] lr: 5.000000e-04 eta: 3:25:56 time: 0.286788 data_time: 0.029890 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.887495 loss: 0.000545 2022/10/27 18:47:41 - mmengine - INFO - Epoch(train) [133][250/586] lr: 5.000000e-04 eta: 3:25:43 time: 0.286696 data_time: 0.029041 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.830814 loss: 0.000541 2022/10/27 18:47:55 - mmengine - INFO - Epoch(train) [133][300/586] lr: 5.000000e-04 eta: 3:25:30 time: 0.293448 data_time: 0.035708 memory: 11131 loss_kpt: 0.000536 acc_pose: 0.857679 loss: 0.000536 2022/10/27 18:48:10 - mmengine - INFO - Epoch(train) [133][350/586] lr: 5.000000e-04 eta: 3:25:17 time: 0.289582 data_time: 0.030439 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.842507 loss: 0.000557 2022/10/27 18:48:24 - mmengine - INFO - Epoch(train) [133][400/586] lr: 5.000000e-04 eta: 3:25:03 time: 0.287884 data_time: 0.032040 memory: 11131 loss_kpt: 0.000549 acc_pose: 0.747173 loss: 0.000549 2022/10/27 18:48:39 - mmengine - INFO - Epoch(train) [133][450/586] lr: 5.000000e-04 eta: 3:24:50 time: 0.290969 data_time: 0.030237 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.894666 loss: 0.000552 2022/10/27 18:48:53 - mmengine - INFO - Epoch(train) [133][500/586] lr: 5.000000e-04 eta: 3:24:37 time: 0.285685 data_time: 0.027941 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.890430 loss: 0.000552 2022/10/27 18:49:08 - mmengine - INFO - Epoch(train) [133][550/586] lr: 5.000000e-04 eta: 3:24:24 time: 0.285680 data_time: 0.026700 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.814437 loss: 0.000529 2022/10/27 18:49:18 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:49:33 - mmengine - INFO - Epoch(train) [134][50/586] lr: 5.000000e-04 eta: 3:23:56 time: 0.306337 data_time: 0.049746 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.842706 loss: 0.000543 2022/10/27 18:49:37 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:49:48 - mmengine - INFO - Epoch(train) [134][100/586] lr: 5.000000e-04 eta: 3:23:43 time: 0.291972 data_time: 0.028211 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.813895 loss: 0.000534 2022/10/27 18:50:02 - mmengine - INFO - Epoch(train) [134][150/586] lr: 5.000000e-04 eta: 3:23:30 time: 0.286060 data_time: 0.029832 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.904912 loss: 0.000541 2022/10/27 18:50:16 - mmengine - INFO - Epoch(train) [134][200/586] lr: 5.000000e-04 eta: 3:23:17 time: 0.284393 data_time: 0.027383 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.845789 loss: 0.000538 2022/10/27 18:50:31 - mmengine - INFO - Epoch(train) [134][250/586] lr: 5.000000e-04 eta: 3:23:04 time: 0.288307 data_time: 0.031406 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.878774 loss: 0.000547 2022/10/27 18:50:45 - mmengine - INFO - Epoch(train) [134][300/586] lr: 5.000000e-04 eta: 3:22:51 time: 0.289302 data_time: 0.028234 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.910699 loss: 0.000533 2022/10/27 18:51:00 - mmengine - INFO - Epoch(train) [134][350/586] lr: 5.000000e-04 eta: 3:22:38 time: 0.292490 data_time: 0.027450 memory: 11131 loss_kpt: 0.000527 acc_pose: 0.846656 loss: 0.000527 2022/10/27 18:51:14 - mmengine - INFO - Epoch(train) [134][400/586] lr: 5.000000e-04 eta: 3:22:25 time: 0.287593 data_time: 0.029230 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.827510 loss: 0.000546 2022/10/27 18:51:29 - mmengine - INFO - Epoch(train) [134][450/586] lr: 5.000000e-04 eta: 3:22:11 time: 0.287942 data_time: 0.033508 memory: 11131 loss_kpt: 0.000560 acc_pose: 0.856778 loss: 0.000560 2022/10/27 18:51:43 - mmengine - INFO - Epoch(train) [134][500/586] lr: 5.000000e-04 eta: 3:21:58 time: 0.287098 data_time: 0.031352 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.884989 loss: 0.000538 2022/10/27 18:51:57 - mmengine - INFO - Epoch(train) [134][550/586] lr: 5.000000e-04 eta: 3:21:45 time: 0.288734 data_time: 0.027813 memory: 11131 loss_kpt: 0.000532 acc_pose: 0.823451 loss: 0.000532 2022/10/27 18:52:08 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:52:22 - mmengine - INFO - Epoch(train) [135][50/586] lr: 5.000000e-04 eta: 3:21:17 time: 0.297311 data_time: 0.037509 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.860231 loss: 0.000525 2022/10/27 18:52:37 - mmengine - INFO - Epoch(train) [135][100/586] lr: 5.000000e-04 eta: 3:21:04 time: 0.289512 data_time: 0.029200 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.860549 loss: 0.000545 2022/10/27 18:52:51 - mmengine - INFO - Epoch(train) [135][150/586] lr: 5.000000e-04 eta: 3:20:51 time: 0.289631 data_time: 0.033066 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.888862 loss: 0.000535 2022/10/27 18:53:06 - mmengine - INFO - Epoch(train) [135][200/586] lr: 5.000000e-04 eta: 3:20:38 time: 0.288402 data_time: 0.028564 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.849821 loss: 0.000538 2022/10/27 18:53:20 - mmengine - INFO - Epoch(train) [135][250/586] lr: 5.000000e-04 eta: 3:20:25 time: 0.288215 data_time: 0.028700 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.834222 loss: 0.000533 2022/10/27 18:53:35 - mmengine - INFO - Epoch(train) [135][300/586] lr: 5.000000e-04 eta: 3:20:12 time: 0.286677 data_time: 0.028543 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.886267 loss: 0.000546 2022/10/27 18:53:49 - mmengine - INFO - Epoch(train) [135][350/586] lr: 5.000000e-04 eta: 3:19:58 time: 0.290101 data_time: 0.029586 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.921180 loss: 0.000524 2022/10/27 18:54:04 - mmengine - INFO - Epoch(train) [135][400/586] lr: 5.000000e-04 eta: 3:19:45 time: 0.287698 data_time: 0.029732 memory: 11131 loss_kpt: 0.000527 acc_pose: 0.869851 loss: 0.000527 2022/10/27 18:54:18 - mmengine - INFO - Epoch(train) [135][450/586] lr: 5.000000e-04 eta: 3:19:32 time: 0.291085 data_time: 0.027790 memory: 11131 loss_kpt: 0.000556 acc_pose: 0.831391 loss: 0.000556 2022/10/27 18:54:25 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:54:32 - mmengine - INFO - Epoch(train) [135][500/586] lr: 5.000000e-04 eta: 3:19:19 time: 0.288002 data_time: 0.028557 memory: 11131 loss_kpt: 0.000540 acc_pose: 0.874100 loss: 0.000540 2022/10/27 18:54:47 - mmengine - INFO - Epoch(train) [135][550/586] lr: 5.000000e-04 eta: 3:19:06 time: 0.287379 data_time: 0.027444 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.822977 loss: 0.000541 2022/10/27 18:54:57 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:55:12 - mmengine - INFO - Epoch(train) [136][50/586] lr: 5.000000e-04 eta: 3:18:38 time: 0.297090 data_time: 0.036770 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.901261 loss: 0.000523 2022/10/27 18:55:26 - mmengine - INFO - Epoch(train) [136][100/586] lr: 5.000000e-04 eta: 3:18:25 time: 0.285960 data_time: 0.028493 memory: 11131 loss_kpt: 0.000531 acc_pose: 0.832455 loss: 0.000531 2022/10/27 18:55:41 - mmengine - INFO - Epoch(train) [136][150/586] lr: 5.000000e-04 eta: 3:18:12 time: 0.291198 data_time: 0.029654 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.768908 loss: 0.000541 2022/10/27 18:55:55 - mmengine - INFO - Epoch(train) [136][200/586] lr: 5.000000e-04 eta: 3:17:59 time: 0.287661 data_time: 0.032379 memory: 11131 loss_kpt: 0.000532 acc_pose: 0.848302 loss: 0.000532 2022/10/27 18:56:09 - mmengine - INFO - Epoch(train) [136][250/586] lr: 5.000000e-04 eta: 3:17:45 time: 0.282839 data_time: 0.026859 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.835910 loss: 0.000542 2022/10/27 18:56:24 - mmengine - INFO - Epoch(train) [136][300/586] lr: 5.000000e-04 eta: 3:17:32 time: 0.291210 data_time: 0.027237 memory: 11131 loss_kpt: 0.000559 acc_pose: 0.856261 loss: 0.000559 2022/10/27 18:56:38 - mmengine - INFO - Epoch(train) [136][350/586] lr: 5.000000e-04 eta: 3:17:19 time: 0.287750 data_time: 0.028566 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.826400 loss: 0.000526 2022/10/27 18:56:53 - mmengine - INFO - Epoch(train) [136][400/586] lr: 5.000000e-04 eta: 3:17:06 time: 0.287323 data_time: 0.027297 memory: 11131 loss_kpt: 0.000549 acc_pose: 0.866316 loss: 0.000549 2022/10/27 18:57:07 - mmengine - INFO - Epoch(train) [136][450/586] lr: 5.000000e-04 eta: 3:16:53 time: 0.292556 data_time: 0.034269 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.853638 loss: 0.000543 2022/10/27 18:57:21 - mmengine - INFO - Epoch(train) [136][500/586] lr: 5.000000e-04 eta: 3:16:40 time: 0.284348 data_time: 0.029792 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.855618 loss: 0.000541 2022/10/27 18:57:36 - mmengine - INFO - Epoch(train) [136][550/586] lr: 5.000000e-04 eta: 3:16:27 time: 0.288284 data_time: 0.030754 memory: 11131 loss_kpt: 0.000537 acc_pose: 0.824660 loss: 0.000537 2022/10/27 18:57:46 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:58:01 - mmengine - INFO - Epoch(train) [137][50/586] lr: 5.000000e-04 eta: 3:15:59 time: 0.303185 data_time: 0.036225 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.868570 loss: 0.000524 2022/10/27 18:58:16 - mmengine - INFO - Epoch(train) [137][100/586] lr: 5.000000e-04 eta: 3:15:46 time: 0.287186 data_time: 0.026753 memory: 11131 loss_kpt: 0.000553 acc_pose: 0.784636 loss: 0.000553 2022/10/27 18:58:30 - mmengine - INFO - Epoch(train) [137][150/586] lr: 5.000000e-04 eta: 3:15:33 time: 0.285227 data_time: 0.031153 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.880209 loss: 0.000539 2022/10/27 18:58:44 - mmengine - INFO - Epoch(train) [137][200/586] lr: 5.000000e-04 eta: 3:15:19 time: 0.285905 data_time: 0.027338 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.853813 loss: 0.000542 2022/10/27 18:58:59 - mmengine - INFO - Epoch(train) [137][250/586] lr: 5.000000e-04 eta: 3:15:06 time: 0.290338 data_time: 0.027224 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.881407 loss: 0.000542 2022/10/27 18:59:13 - mmengine - INFO - Epoch(train) [137][300/586] lr: 5.000000e-04 eta: 3:14:53 time: 0.286319 data_time: 0.028031 memory: 11131 loss_kpt: 0.000530 acc_pose: 0.868878 loss: 0.000530 2022/10/27 18:59:14 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 18:59:28 - mmengine - INFO - Epoch(train) [137][350/586] lr: 5.000000e-04 eta: 3:14:40 time: 0.288580 data_time: 0.031401 memory: 11131 loss_kpt: 0.000563 acc_pose: 0.880407 loss: 0.000563 2022/10/27 18:59:42 - mmengine - INFO - Epoch(train) [137][400/586] lr: 5.000000e-04 eta: 3:14:27 time: 0.288782 data_time: 0.029791 memory: 11131 loss_kpt: 0.000553 acc_pose: 0.829385 loss: 0.000553 2022/10/27 18:59:56 - mmengine - INFO - Epoch(train) [137][450/586] lr: 5.000000e-04 eta: 3:14:14 time: 0.285539 data_time: 0.026956 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.829597 loss: 0.000551 2022/10/27 19:00:11 - mmengine - INFO - Epoch(train) [137][500/586] lr: 5.000000e-04 eta: 3:14:01 time: 0.290061 data_time: 0.030329 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.876705 loss: 0.000543 2022/10/27 19:00:25 - mmengine - INFO - Epoch(train) [137][550/586] lr: 5.000000e-04 eta: 3:13:47 time: 0.288379 data_time: 0.030346 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.808932 loss: 0.000526 2022/10/27 19:00:36 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:00:50 - mmengine - INFO - Epoch(train) [138][50/586] lr: 5.000000e-04 eta: 3:13:20 time: 0.298161 data_time: 0.039042 memory: 11131 loss_kpt: 0.000540 acc_pose: 0.807380 loss: 0.000540 2022/10/27 19:01:05 - mmengine - INFO - Epoch(train) [138][100/586] lr: 5.000000e-04 eta: 3:13:06 time: 0.285602 data_time: 0.029493 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.826192 loss: 0.000522 2022/10/27 19:01:19 - mmengine - INFO - Epoch(train) [138][150/586] lr: 5.000000e-04 eta: 3:12:53 time: 0.283687 data_time: 0.029031 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.829434 loss: 0.000534 2022/10/27 19:01:33 - mmengine - INFO - Epoch(train) [138][200/586] lr: 5.000000e-04 eta: 3:12:40 time: 0.289039 data_time: 0.032674 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.860510 loss: 0.000525 2022/10/27 19:01:48 - mmengine - INFO - Epoch(train) [138][250/586] lr: 5.000000e-04 eta: 3:12:27 time: 0.289203 data_time: 0.033346 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.811886 loss: 0.000534 2022/10/27 19:02:02 - mmengine - INFO - Epoch(train) [138][300/586] lr: 5.000000e-04 eta: 3:12:14 time: 0.290270 data_time: 0.028634 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.807689 loss: 0.000545 2022/10/27 19:02:17 - mmengine - INFO - Epoch(train) [138][350/586] lr: 5.000000e-04 eta: 3:12:01 time: 0.290478 data_time: 0.029147 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.814987 loss: 0.000548 2022/10/27 19:02:31 - mmengine - INFO - Epoch(train) [138][400/586] lr: 5.000000e-04 eta: 3:11:48 time: 0.288250 data_time: 0.028273 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.871272 loss: 0.000539 2022/10/27 19:02:46 - mmengine - INFO - Epoch(train) [138][450/586] lr: 5.000000e-04 eta: 3:11:35 time: 0.291031 data_time: 0.028357 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.869049 loss: 0.000534 2022/10/27 19:03:00 - mmengine - INFO - Epoch(train) [138][500/586] lr: 5.000000e-04 eta: 3:11:21 time: 0.289836 data_time: 0.028857 memory: 11131 loss_kpt: 0.000536 acc_pose: 0.798135 loss: 0.000536 2022/10/27 19:03:15 - mmengine - INFO - Epoch(train) [138][550/586] lr: 5.000000e-04 eta: 3:11:08 time: 0.285645 data_time: 0.030476 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.841124 loss: 0.000542 2022/10/27 19:03:25 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:03:41 - mmengine - INFO - Epoch(train) [139][50/586] lr: 5.000000e-04 eta: 3:10:41 time: 0.309910 data_time: 0.037323 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.870807 loss: 0.000546 2022/10/27 19:03:55 - mmengine - INFO - Epoch(train) [139][100/586] lr: 5.000000e-04 eta: 3:10:28 time: 0.290478 data_time: 0.035773 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.918661 loss: 0.000538 2022/10/27 19:04:04 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:04:09 - mmengine - INFO - Epoch(train) [139][150/586] lr: 5.000000e-04 eta: 3:10:15 time: 0.285967 data_time: 0.028597 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.830621 loss: 0.000542 2022/10/27 19:04:24 - mmengine - INFO - Epoch(train) [139][200/586] lr: 5.000000e-04 eta: 3:10:01 time: 0.284870 data_time: 0.029270 memory: 11131 loss_kpt: 0.000559 acc_pose: 0.887092 loss: 0.000559 2022/10/27 19:04:38 - mmengine - INFO - Epoch(train) [139][250/586] lr: 5.000000e-04 eta: 3:09:48 time: 0.286846 data_time: 0.027130 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.819307 loss: 0.000547 2022/10/27 19:04:52 - mmengine - INFO - Epoch(train) [139][300/586] lr: 5.000000e-04 eta: 3:09:35 time: 0.287455 data_time: 0.029299 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.848521 loss: 0.000543 2022/10/27 19:05:07 - mmengine - INFO - Epoch(train) [139][350/586] lr: 5.000000e-04 eta: 3:09:22 time: 0.290409 data_time: 0.033674 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.826420 loss: 0.000539 2022/10/27 19:05:21 - mmengine - INFO - Epoch(train) [139][400/586] lr: 5.000000e-04 eta: 3:09:09 time: 0.288556 data_time: 0.029589 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.806400 loss: 0.000526 2022/10/27 19:05:36 - mmengine - INFO - Epoch(train) [139][450/586] lr: 5.000000e-04 eta: 3:08:55 time: 0.284176 data_time: 0.027540 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.875456 loss: 0.000547 2022/10/27 19:05:50 - mmengine - INFO - Epoch(train) [139][500/586] lr: 5.000000e-04 eta: 3:08:42 time: 0.289444 data_time: 0.032393 memory: 11131 loss_kpt: 0.000571 acc_pose: 0.788746 loss: 0.000571 2022/10/27 19:06:04 - mmengine - INFO - Epoch(train) [139][550/586] lr: 5.000000e-04 eta: 3:08:29 time: 0.287110 data_time: 0.028587 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.852451 loss: 0.000541 2022/10/27 19:06:15 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:06:30 - mmengine - INFO - Epoch(train) [140][50/586] lr: 5.000000e-04 eta: 3:08:01 time: 0.295917 data_time: 0.038790 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.863394 loss: 0.000524 2022/10/27 19:06:44 - mmengine - INFO - Epoch(train) [140][100/586] lr: 5.000000e-04 eta: 3:07:48 time: 0.285268 data_time: 0.029531 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.860814 loss: 0.000548 2022/10/27 19:06:58 - mmengine - INFO - Epoch(train) [140][150/586] lr: 5.000000e-04 eta: 3:07:35 time: 0.292095 data_time: 0.032708 memory: 11131 loss_kpt: 0.000554 acc_pose: 0.872723 loss: 0.000554 2022/10/27 19:07:13 - mmengine - INFO - Epoch(train) [140][200/586] lr: 5.000000e-04 eta: 3:07:22 time: 0.287946 data_time: 0.029123 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.889838 loss: 0.000534 2022/10/27 19:07:27 - mmengine - INFO - Epoch(train) [140][250/586] lr: 5.000000e-04 eta: 3:07:09 time: 0.288748 data_time: 0.031803 memory: 11131 loss_kpt: 0.000537 acc_pose: 0.885379 loss: 0.000537 2022/10/27 19:07:42 - mmengine - INFO - Epoch(train) [140][300/586] lr: 5.000000e-04 eta: 3:06:56 time: 0.286789 data_time: 0.027687 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.864147 loss: 0.000545 2022/10/27 19:07:56 - mmengine - INFO - Epoch(train) [140][350/586] lr: 5.000000e-04 eta: 3:06:42 time: 0.286911 data_time: 0.029637 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.831640 loss: 0.000539 2022/10/27 19:08:11 - mmengine - INFO - Epoch(train) [140][400/586] lr: 5.000000e-04 eta: 3:06:29 time: 0.291687 data_time: 0.028227 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.820674 loss: 0.000541 2022/10/27 19:08:25 - mmengine - INFO - Epoch(train) [140][450/586] lr: 5.000000e-04 eta: 3:06:16 time: 0.287999 data_time: 0.028469 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.853151 loss: 0.000534 2022/10/27 19:08:40 - mmengine - INFO - Epoch(train) [140][500/586] lr: 5.000000e-04 eta: 3:06:03 time: 0.290475 data_time: 0.032131 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.831782 loss: 0.000538 2022/10/27 19:08:53 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:08:54 - mmengine - INFO - Epoch(train) [140][550/586] lr: 5.000000e-04 eta: 3:05:50 time: 0.285193 data_time: 0.028529 memory: 11131 loss_kpt: 0.000549 acc_pose: 0.884413 loss: 0.000549 2022/10/27 19:09:04 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:09:04 - mmengine - INFO - Saving checkpoint at 140 epochs 2022/10/27 19:09:15 - mmengine - INFO - Epoch(val) [140][50/407] eta: 0:00:52 time: 0.147278 data_time: 0.026625 memory: 11131 2022/10/27 19:09:22 - mmengine - INFO - Epoch(val) [140][100/407] eta: 0:00:43 time: 0.141143 data_time: 0.021376 memory: 1836 2022/10/27 19:09:29 - mmengine - INFO - Epoch(val) [140][150/407] eta: 0:00:34 time: 0.132302 data_time: 0.012339 memory: 1836 2022/10/27 19:09:36 - mmengine - INFO - Epoch(val) [140][200/407] eta: 0:00:29 time: 0.143270 data_time: 0.021770 memory: 1836 2022/10/27 19:09:43 - mmengine - INFO - Epoch(val) [140][250/407] eta: 0:00:21 time: 0.136860 data_time: 0.017367 memory: 1836 2022/10/27 19:09:49 - mmengine - INFO - Epoch(val) [140][300/407] eta: 0:00:14 time: 0.134758 data_time: 0.014963 memory: 1836 2022/10/27 19:09:56 - mmengine - INFO - Epoch(val) [140][350/407] eta: 0:00:07 time: 0.136306 data_time: 0.015722 memory: 1836 2022/10/27 19:10:03 - mmengine - INFO - Epoch(val) [140][400/407] eta: 0:00:00 time: 0.132044 data_time: 0.012099 memory: 1836 2022/10/27 19:10:50 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 19:11:07 - mmengine - INFO - Epoch(val) [140][407/407] coco/AP: 0.740039 coco/AP .5: 0.900479 coco/AP .75: 0.810511 coco/AP (M): 0.698216 coco/AP (L): 0.812617 coco/AR: 0.791215 coco/AR .5: 0.938130 coco/AR .75: 0.854849 coco/AR (M): 0.745561 coco/AR (L): 0.857637 2022/10/27 19:11:23 - mmengine - INFO - Epoch(train) [141][50/586] lr: 5.000000e-04 eta: 3:05:23 time: 0.305556 data_time: 0.042944 memory: 11131 loss_kpt: 0.000540 acc_pose: 0.868150 loss: 0.000540 2022/10/27 19:11:37 - mmengine - INFO - Epoch(train) [141][100/586] lr: 5.000000e-04 eta: 3:05:09 time: 0.282122 data_time: 0.027278 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.869803 loss: 0.000539 2022/10/27 19:11:51 - mmengine - INFO - Epoch(train) [141][150/586] lr: 5.000000e-04 eta: 3:04:56 time: 0.286273 data_time: 0.033786 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.850715 loss: 0.000541 2022/10/27 19:12:05 - mmengine - INFO - Epoch(train) [141][200/586] lr: 5.000000e-04 eta: 3:04:43 time: 0.289662 data_time: 0.028443 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.850773 loss: 0.000526 2022/10/27 19:12:20 - mmengine - INFO - Epoch(train) [141][250/586] lr: 5.000000e-04 eta: 3:04:30 time: 0.287373 data_time: 0.026496 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.816933 loss: 0.000514 2022/10/27 19:12:34 - mmengine - INFO - Epoch(train) [141][300/586] lr: 5.000000e-04 eta: 3:04:16 time: 0.285645 data_time: 0.026469 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.879001 loss: 0.000533 2022/10/27 19:12:48 - mmengine - INFO - Epoch(train) [141][350/586] lr: 5.000000e-04 eta: 3:04:03 time: 0.286112 data_time: 0.028382 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.863509 loss: 0.000539 2022/10/27 19:13:03 - mmengine - INFO - Epoch(train) [141][400/586] lr: 5.000000e-04 eta: 3:03:50 time: 0.289148 data_time: 0.026582 memory: 11131 loss_kpt: 0.000530 acc_pose: 0.868869 loss: 0.000530 2022/10/27 19:13:17 - mmengine - INFO - Epoch(train) [141][450/586] lr: 5.000000e-04 eta: 3:03:37 time: 0.285298 data_time: 0.027458 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.803075 loss: 0.000546 2022/10/27 19:13:32 - mmengine - INFO - Epoch(train) [141][500/586] lr: 5.000000e-04 eta: 3:03:24 time: 0.292501 data_time: 0.028398 memory: 11131 loss_kpt: 0.000530 acc_pose: 0.852742 loss: 0.000530 2022/10/27 19:13:46 - mmengine - INFO - Epoch(train) [141][550/586] lr: 5.000000e-04 eta: 3:03:11 time: 0.286382 data_time: 0.029821 memory: 11131 loss_kpt: 0.000540 acc_pose: 0.879470 loss: 0.000540 2022/10/27 19:13:56 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:14:12 - mmengine - INFO - Epoch(train) [142][50/586] lr: 5.000000e-04 eta: 3:02:43 time: 0.304159 data_time: 0.044256 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.828574 loss: 0.000542 2022/10/27 19:14:26 - mmengine - INFO - Epoch(train) [142][100/586] lr: 5.000000e-04 eta: 3:02:30 time: 0.280733 data_time: 0.028336 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.757140 loss: 0.000535 2022/10/27 19:14:40 - mmengine - INFO - Epoch(train) [142][150/586] lr: 5.000000e-04 eta: 3:02:17 time: 0.290734 data_time: 0.029275 memory: 11131 loss_kpt: 0.000537 acc_pose: 0.889849 loss: 0.000537 2022/10/27 19:14:54 - mmengine - INFO - Epoch(train) [142][200/586] lr: 5.000000e-04 eta: 3:02:04 time: 0.285844 data_time: 0.030462 memory: 11131 loss_kpt: 0.000527 acc_pose: 0.840568 loss: 0.000527 2022/10/27 19:15:09 - mmengine - INFO - Epoch(train) [142][250/586] lr: 5.000000e-04 eta: 3:01:50 time: 0.289466 data_time: 0.029900 memory: 11131 loss_kpt: 0.000544 acc_pose: 0.887469 loss: 0.000544 2022/10/27 19:15:23 - mmengine - INFO - Epoch(train) [142][300/586] lr: 5.000000e-04 eta: 3:01:37 time: 0.286721 data_time: 0.028446 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.853584 loss: 0.000535 2022/10/27 19:15:37 - mmengine - INFO - Epoch(train) [142][350/586] lr: 5.000000e-04 eta: 3:01:24 time: 0.283483 data_time: 0.029409 memory: 11131 loss_kpt: 0.000557 acc_pose: 0.833283 loss: 0.000557 2022/10/27 19:15:45 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:15:52 - mmengine - INFO - Epoch(train) [142][400/586] lr: 5.000000e-04 eta: 3:01:11 time: 0.291953 data_time: 0.028493 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.885310 loss: 0.000538 2022/10/27 19:16:06 - mmengine - INFO - Epoch(train) [142][450/586] lr: 5.000000e-04 eta: 3:00:58 time: 0.286390 data_time: 0.027949 memory: 11131 loss_kpt: 0.000544 acc_pose: 0.831244 loss: 0.000544 2022/10/27 19:16:21 - mmengine - INFO - Epoch(train) [142][500/586] lr: 5.000000e-04 eta: 3:00:44 time: 0.287694 data_time: 0.028133 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.872412 loss: 0.000526 2022/10/27 19:16:35 - mmengine - INFO - Epoch(train) [142][550/586] lr: 5.000000e-04 eta: 3:00:31 time: 0.287503 data_time: 0.027062 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.840208 loss: 0.000543 2022/10/27 19:16:45 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:17:01 - mmengine - INFO - Epoch(train) [143][50/586] lr: 5.000000e-04 eta: 3:00:04 time: 0.305086 data_time: 0.039086 memory: 11131 loss_kpt: 0.000517 acc_pose: 0.850773 loss: 0.000517 2022/10/27 19:17:15 - mmengine - INFO - Epoch(train) [143][100/586] lr: 5.000000e-04 eta: 2:59:51 time: 0.291628 data_time: 0.029947 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.833926 loss: 0.000541 2022/10/27 19:17:29 - mmengine - INFO - Epoch(train) [143][150/586] lr: 5.000000e-04 eta: 2:59:38 time: 0.285460 data_time: 0.030719 memory: 11131 loss_kpt: 0.000527 acc_pose: 0.847856 loss: 0.000527 2022/10/27 19:17:44 - mmengine - INFO - Epoch(train) [143][200/586] lr: 5.000000e-04 eta: 2:59:25 time: 0.292779 data_time: 0.028720 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.845104 loss: 0.000545 2022/10/27 19:17:58 - mmengine - INFO - Epoch(train) [143][250/586] lr: 5.000000e-04 eta: 2:59:11 time: 0.286733 data_time: 0.030295 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.867963 loss: 0.000547 2022/10/27 19:18:13 - mmengine - INFO - Epoch(train) [143][300/586] lr: 5.000000e-04 eta: 2:58:58 time: 0.288857 data_time: 0.027414 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.863238 loss: 0.000519 2022/10/27 19:18:27 - mmengine - INFO - Epoch(train) [143][350/586] lr: 5.000000e-04 eta: 2:58:45 time: 0.288319 data_time: 0.027362 memory: 11131 loss_kpt: 0.000530 acc_pose: 0.908250 loss: 0.000530 2022/10/27 19:18:42 - mmengine - INFO - Epoch(train) [143][400/586] lr: 5.000000e-04 eta: 2:58:32 time: 0.288395 data_time: 0.033451 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.877932 loss: 0.000546 2022/10/27 19:18:56 - mmengine - INFO - Epoch(train) [143][450/586] lr: 5.000000e-04 eta: 2:58:19 time: 0.284074 data_time: 0.029033 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.879279 loss: 0.000539 2022/10/27 19:19:11 - mmengine - INFO - Epoch(train) [143][500/586] lr: 5.000000e-04 eta: 2:58:06 time: 0.294840 data_time: 0.029104 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.889647 loss: 0.000533 2022/10/27 19:19:25 - mmengine - INFO - Epoch(train) [143][550/586] lr: 5.000000e-04 eta: 2:57:52 time: 0.287487 data_time: 0.029222 memory: 11131 loss_kpt: 0.000536 acc_pose: 0.832746 loss: 0.000536 2022/10/27 19:19:35 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:19:50 - mmengine - INFO - Epoch(train) [144][50/586] lr: 5.000000e-04 eta: 2:57:25 time: 0.299831 data_time: 0.039833 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.829300 loss: 0.000548 2022/10/27 19:20:05 - mmengine - INFO - Epoch(train) [144][100/586] lr: 5.000000e-04 eta: 2:57:12 time: 0.288070 data_time: 0.031757 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.903644 loss: 0.000539 2022/10/27 19:20:19 - mmengine - INFO - Epoch(train) [144][150/586] lr: 5.000000e-04 eta: 2:56:59 time: 0.291650 data_time: 0.030031 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.952196 loss: 0.000545 2022/10/27 19:20:34 - mmengine - INFO - Epoch(train) [144][200/586] lr: 5.000000e-04 eta: 2:56:46 time: 0.287748 data_time: 0.028862 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.846696 loss: 0.000538 2022/10/27 19:20:34 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:20:48 - mmengine - INFO - Epoch(train) [144][250/586] lr: 5.000000e-04 eta: 2:56:32 time: 0.289755 data_time: 0.027048 memory: 11131 loss_kpt: 0.000531 acc_pose: 0.894197 loss: 0.000531 2022/10/27 19:21:03 - mmengine - INFO - Epoch(train) [144][300/586] lr: 5.000000e-04 eta: 2:56:19 time: 0.291290 data_time: 0.027906 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.813734 loss: 0.000538 2022/10/27 19:21:17 - mmengine - INFO - Epoch(train) [144][350/586] lr: 5.000000e-04 eta: 2:56:06 time: 0.286344 data_time: 0.028461 memory: 11131 loss_kpt: 0.000537 acc_pose: 0.924910 loss: 0.000537 2022/10/27 19:21:32 - mmengine - INFO - Epoch(train) [144][400/586] lr: 5.000000e-04 eta: 2:55:53 time: 0.295916 data_time: 0.028085 memory: 11131 loss_kpt: 0.000528 acc_pose: 0.890076 loss: 0.000528 2022/10/27 19:21:46 - mmengine - INFO - Epoch(train) [144][450/586] lr: 5.000000e-04 eta: 2:55:40 time: 0.286473 data_time: 0.028085 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.830771 loss: 0.000543 2022/10/27 19:22:01 - mmengine - INFO - Epoch(train) [144][500/586] lr: 5.000000e-04 eta: 2:55:27 time: 0.288976 data_time: 0.029644 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.841888 loss: 0.000542 2022/10/27 19:22:15 - mmengine - INFO - Epoch(train) [144][550/586] lr: 5.000000e-04 eta: 2:55:13 time: 0.288662 data_time: 0.027083 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.862002 loss: 0.000529 2022/10/27 19:22:25 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:22:40 - mmengine - INFO - Epoch(train) [145][50/586] lr: 5.000000e-04 eta: 2:54:46 time: 0.301617 data_time: 0.036585 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.855494 loss: 0.000535 2022/10/27 19:22:54 - mmengine - INFO - Epoch(train) [145][100/586] lr: 5.000000e-04 eta: 2:54:33 time: 0.285768 data_time: 0.030039 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.837388 loss: 0.000535 2022/10/27 19:23:09 - mmengine - INFO - Epoch(train) [145][150/586] lr: 5.000000e-04 eta: 2:54:20 time: 0.289779 data_time: 0.031917 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.851022 loss: 0.000538 2022/10/27 19:23:23 - mmengine - INFO - Epoch(train) [145][200/586] lr: 5.000000e-04 eta: 2:54:07 time: 0.285978 data_time: 0.028107 memory: 11131 loss_kpt: 0.000536 acc_pose: 0.871508 loss: 0.000536 2022/10/27 19:23:38 - mmengine - INFO - Epoch(train) [145][250/586] lr: 5.000000e-04 eta: 2:53:53 time: 0.289625 data_time: 0.029738 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.786190 loss: 0.000548 2022/10/27 19:23:52 - mmengine - INFO - Epoch(train) [145][300/586] lr: 5.000000e-04 eta: 2:53:40 time: 0.289756 data_time: 0.027782 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.903800 loss: 0.000542 2022/10/27 19:24:07 - mmengine - INFO - Epoch(train) [145][350/586] lr: 5.000000e-04 eta: 2:53:27 time: 0.287726 data_time: 0.031813 memory: 11131 loss_kpt: 0.000528 acc_pose: 0.862574 loss: 0.000528 2022/10/27 19:24:21 - mmengine - INFO - Epoch(train) [145][400/586] lr: 5.000000e-04 eta: 2:53:14 time: 0.282953 data_time: 0.027752 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.873094 loss: 0.000524 2022/10/27 19:24:35 - mmengine - INFO - Epoch(train) [145][450/586] lr: 5.000000e-04 eta: 2:53:01 time: 0.291138 data_time: 0.027875 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.889949 loss: 0.000535 2022/10/27 19:24:50 - mmengine - INFO - Epoch(train) [145][500/586] lr: 5.000000e-04 eta: 2:52:48 time: 0.293318 data_time: 0.027640 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.851557 loss: 0.000526 2022/10/27 19:25:04 - mmengine - INFO - Epoch(train) [145][550/586] lr: 5.000000e-04 eta: 2:52:34 time: 0.282569 data_time: 0.027612 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.863844 loss: 0.000538 2022/10/27 19:25:14 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:25:24 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:25:29 - mmengine - INFO - Epoch(train) [146][50/586] lr: 5.000000e-04 eta: 2:52:07 time: 0.296821 data_time: 0.038960 memory: 11131 loss_kpt: 0.000530 acc_pose: 0.871479 loss: 0.000530 2022/10/27 19:25:44 - mmengine - INFO - Epoch(train) [146][100/586] lr: 5.000000e-04 eta: 2:51:54 time: 0.287526 data_time: 0.029357 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.822346 loss: 0.000522 2022/10/27 19:25:58 - mmengine - INFO - Epoch(train) [146][150/586] lr: 5.000000e-04 eta: 2:51:41 time: 0.294021 data_time: 0.026337 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.858968 loss: 0.000523 2022/10/27 19:26:12 - mmengine - INFO - Epoch(train) [146][200/586] lr: 5.000000e-04 eta: 2:51:27 time: 0.281723 data_time: 0.029269 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.850561 loss: 0.000529 2022/10/27 19:26:27 - mmengine - INFO - Epoch(train) [146][250/586] lr: 5.000000e-04 eta: 2:51:14 time: 0.288897 data_time: 0.029103 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.868440 loss: 0.000545 2022/10/27 19:26:41 - mmengine - INFO - Epoch(train) [146][300/586] lr: 5.000000e-04 eta: 2:51:01 time: 0.285593 data_time: 0.028098 memory: 11131 loss_kpt: 0.000532 acc_pose: 0.884007 loss: 0.000532 2022/10/27 19:26:55 - mmengine - INFO - Epoch(train) [146][350/586] lr: 5.000000e-04 eta: 2:50:48 time: 0.285559 data_time: 0.030084 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.875704 loss: 0.000542 2022/10/27 19:27:10 - mmengine - INFO - Epoch(train) [146][400/586] lr: 5.000000e-04 eta: 2:50:35 time: 0.293230 data_time: 0.027473 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.846373 loss: 0.000534 2022/10/27 19:27:24 - mmengine - INFO - Epoch(train) [146][450/586] lr: 5.000000e-04 eta: 2:50:21 time: 0.282434 data_time: 0.029917 memory: 11131 loss_kpt: 0.000560 acc_pose: 0.896835 loss: 0.000560 2022/10/27 19:27:39 - mmengine - INFO - Epoch(train) [146][500/586] lr: 5.000000e-04 eta: 2:50:08 time: 0.287679 data_time: 0.032221 memory: 11131 loss_kpt: 0.000515 acc_pose: 0.885351 loss: 0.000515 2022/10/27 19:27:53 - mmengine - INFO - Epoch(train) [146][550/586] lr: 5.000000e-04 eta: 2:49:55 time: 0.293303 data_time: 0.028359 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.863910 loss: 0.000522 2022/10/27 19:28:03 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:28:19 - mmengine - INFO - Epoch(train) [147][50/586] lr: 5.000000e-04 eta: 2:49:28 time: 0.310362 data_time: 0.039538 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.919882 loss: 0.000534 2022/10/27 19:28:33 - mmengine - INFO - Epoch(train) [147][100/586] lr: 5.000000e-04 eta: 2:49:15 time: 0.281816 data_time: 0.027083 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.799876 loss: 0.000526 2022/10/27 19:28:47 - mmengine - INFO - Epoch(train) [147][150/586] lr: 5.000000e-04 eta: 2:49:02 time: 0.288614 data_time: 0.033686 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.837454 loss: 0.000547 2022/10/27 19:29:02 - mmengine - INFO - Epoch(train) [147][200/586] lr: 5.000000e-04 eta: 2:48:48 time: 0.292722 data_time: 0.027513 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.878044 loss: 0.000541 2022/10/27 19:29:16 - mmengine - INFO - Epoch(train) [147][250/586] lr: 5.000000e-04 eta: 2:48:35 time: 0.285784 data_time: 0.027307 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.825538 loss: 0.000522 2022/10/27 19:29:31 - mmengine - INFO - Epoch(train) [147][300/586] lr: 5.000000e-04 eta: 2:48:22 time: 0.293374 data_time: 0.027744 memory: 11131 loss_kpt: 0.000537 acc_pose: 0.791687 loss: 0.000537 2022/10/27 19:29:45 - mmengine - INFO - Epoch(train) [147][350/586] lr: 5.000000e-04 eta: 2:48:09 time: 0.284951 data_time: 0.027696 memory: 11131 loss_kpt: 0.000520 acc_pose: 0.895022 loss: 0.000520 2022/10/27 19:30:00 - mmengine - INFO - Epoch(train) [147][400/586] lr: 5.000000e-04 eta: 2:47:56 time: 0.288738 data_time: 0.032448 memory: 11131 loss_kpt: 0.000552 acc_pose: 0.838345 loss: 0.000552 2022/10/27 19:30:13 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:30:15 - mmengine - INFO - Epoch(train) [147][450/586] lr: 5.000000e-04 eta: 2:47:43 time: 0.297410 data_time: 0.029809 memory: 11131 loss_kpt: 0.000537 acc_pose: 0.890909 loss: 0.000537 2022/10/27 19:30:29 - mmengine - INFO - Epoch(train) [147][500/586] lr: 5.000000e-04 eta: 2:47:29 time: 0.286466 data_time: 0.026595 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.873716 loss: 0.000526 2022/10/27 19:30:43 - mmengine - INFO - Epoch(train) [147][550/586] lr: 5.000000e-04 eta: 2:47:16 time: 0.289349 data_time: 0.028126 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.805519 loss: 0.000545 2022/10/27 19:30:54 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:31:09 - mmengine - INFO - Epoch(train) [148][50/586] lr: 5.000000e-04 eta: 2:46:49 time: 0.304229 data_time: 0.048271 memory: 11131 loss_kpt: 0.000515 acc_pose: 0.903692 loss: 0.000515 2022/10/27 19:31:23 - mmengine - INFO - Epoch(train) [148][100/586] lr: 5.000000e-04 eta: 2:46:36 time: 0.289499 data_time: 0.027844 memory: 11131 loss_kpt: 0.000517 acc_pose: 0.935008 loss: 0.000517 2022/10/27 19:31:38 - mmengine - INFO - Epoch(train) [148][150/586] lr: 5.000000e-04 eta: 2:46:23 time: 0.290104 data_time: 0.027995 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.871783 loss: 0.000529 2022/10/27 19:31:52 - mmengine - INFO - Epoch(train) [148][200/586] lr: 5.000000e-04 eta: 2:46:10 time: 0.285015 data_time: 0.027231 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.820810 loss: 0.000534 2022/10/27 19:32:07 - mmengine - INFO - Epoch(train) [148][250/586] lr: 5.000000e-04 eta: 2:45:56 time: 0.288689 data_time: 0.028451 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.880928 loss: 0.000543 2022/10/27 19:32:21 - mmengine - INFO - Epoch(train) [148][300/586] lr: 5.000000e-04 eta: 2:45:43 time: 0.286318 data_time: 0.027568 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.911538 loss: 0.000519 2022/10/27 19:32:35 - mmengine - INFO - Epoch(train) [148][350/586] lr: 5.000000e-04 eta: 2:45:30 time: 0.284207 data_time: 0.027297 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.914759 loss: 0.000541 2022/10/27 19:32:50 - mmengine - INFO - Epoch(train) [148][400/586] lr: 5.000000e-04 eta: 2:45:17 time: 0.292466 data_time: 0.027098 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.887575 loss: 0.000519 2022/10/27 19:33:04 - mmengine - INFO - Epoch(train) [148][450/586] lr: 5.000000e-04 eta: 2:45:03 time: 0.283025 data_time: 0.027316 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.838352 loss: 0.000523 2022/10/27 19:33:18 - mmengine - INFO - Epoch(train) [148][500/586] lr: 5.000000e-04 eta: 2:44:50 time: 0.290156 data_time: 0.028376 memory: 11131 loss_kpt: 0.000527 acc_pose: 0.890997 loss: 0.000527 2022/10/27 19:33:33 - mmengine - INFO - Epoch(train) [148][550/586] lr: 5.000000e-04 eta: 2:44:37 time: 0.291928 data_time: 0.026960 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.871249 loss: 0.000534 2022/10/27 19:33:43 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:33:58 - mmengine - INFO - Epoch(train) [149][50/586] lr: 5.000000e-04 eta: 2:44:10 time: 0.303483 data_time: 0.035474 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.882782 loss: 0.000519 2022/10/27 19:34:13 - mmengine - INFO - Epoch(train) [149][100/586] lr: 5.000000e-04 eta: 2:43:57 time: 0.284747 data_time: 0.029807 memory: 11131 loss_kpt: 0.000516 acc_pose: 0.887800 loss: 0.000516 2022/10/27 19:34:27 - mmengine - INFO - Epoch(train) [149][150/586] lr: 5.000000e-04 eta: 2:43:44 time: 0.288992 data_time: 0.032463 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.878287 loss: 0.000548 2022/10/27 19:34:41 - mmengine - INFO - Epoch(train) [149][200/586] lr: 5.000000e-04 eta: 2:43:31 time: 0.288106 data_time: 0.028737 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.831439 loss: 0.000525 2022/10/27 19:34:56 - mmengine - INFO - Epoch(train) [149][250/586] lr: 5.000000e-04 eta: 2:43:17 time: 0.284085 data_time: 0.028051 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.820881 loss: 0.000541 2022/10/27 19:35:02 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:35:10 - mmengine - INFO - Epoch(train) [149][300/586] lr: 5.000000e-04 eta: 2:43:04 time: 0.292783 data_time: 0.028063 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.842183 loss: 0.000535 2022/10/27 19:35:24 - mmengine - INFO - Epoch(train) [149][350/586] lr: 5.000000e-04 eta: 2:42:51 time: 0.281929 data_time: 0.026801 memory: 11131 loss_kpt: 0.000527 acc_pose: 0.820933 loss: 0.000527 2022/10/27 19:35:39 - mmengine - INFO - Epoch(train) [149][400/586] lr: 5.000000e-04 eta: 2:42:37 time: 0.286884 data_time: 0.032946 memory: 11131 loss_kpt: 0.000531 acc_pose: 0.871690 loss: 0.000531 2022/10/27 19:35:53 - mmengine - INFO - Epoch(train) [149][450/586] lr: 5.000000e-04 eta: 2:42:24 time: 0.290676 data_time: 0.029966 memory: 11131 loss_kpt: 0.000544 acc_pose: 0.801418 loss: 0.000544 2022/10/27 19:36:07 - mmengine - INFO - Epoch(train) [149][500/586] lr: 5.000000e-04 eta: 2:42:11 time: 0.284000 data_time: 0.029764 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.851059 loss: 0.000523 2022/10/27 19:36:22 - mmengine - INFO - Epoch(train) [149][550/586] lr: 5.000000e-04 eta: 2:41:58 time: 0.289052 data_time: 0.030392 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.852101 loss: 0.000529 2022/10/27 19:36:32 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:36:47 - mmengine - INFO - Epoch(train) [150][50/586] lr: 5.000000e-04 eta: 2:41:31 time: 0.300020 data_time: 0.043636 memory: 11131 loss_kpt: 0.000547 acc_pose: 0.852166 loss: 0.000547 2022/10/27 19:37:02 - mmengine - INFO - Epoch(train) [150][100/586] lr: 5.000000e-04 eta: 2:41:18 time: 0.292083 data_time: 0.030419 memory: 11131 loss_kpt: 0.000536 acc_pose: 0.906322 loss: 0.000536 2022/10/27 19:37:16 - mmengine - INFO - Epoch(train) [150][150/586] lr: 5.000000e-04 eta: 2:41:04 time: 0.284952 data_time: 0.027240 memory: 11131 loss_kpt: 0.000509 acc_pose: 0.877155 loss: 0.000509 2022/10/27 19:37:30 - mmengine - INFO - Epoch(train) [150][200/586] lr: 5.000000e-04 eta: 2:40:51 time: 0.290270 data_time: 0.028892 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.864413 loss: 0.000533 2022/10/27 19:37:45 - mmengine - INFO - Epoch(train) [150][250/586] lr: 5.000000e-04 eta: 2:40:38 time: 0.288155 data_time: 0.030354 memory: 11131 loss_kpt: 0.000532 acc_pose: 0.914056 loss: 0.000532 2022/10/27 19:37:59 - mmengine - INFO - Epoch(train) [150][300/586] lr: 5.000000e-04 eta: 2:40:25 time: 0.284459 data_time: 0.028295 memory: 11131 loss_kpt: 0.000531 acc_pose: 0.866508 loss: 0.000531 2022/10/27 19:38:13 - mmengine - INFO - Epoch(train) [150][350/586] lr: 5.000000e-04 eta: 2:40:11 time: 0.284395 data_time: 0.027617 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.857948 loss: 0.000538 2022/10/27 19:38:28 - mmengine - INFO - Epoch(train) [150][400/586] lr: 5.000000e-04 eta: 2:39:58 time: 0.295548 data_time: 0.028801 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.871586 loss: 0.000529 2022/10/27 19:38:43 - mmengine - INFO - Epoch(train) [150][450/586] lr: 5.000000e-04 eta: 2:39:45 time: 0.288400 data_time: 0.028763 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.771942 loss: 0.000545 2022/10/27 19:38:57 - mmengine - INFO - Epoch(train) [150][500/586] lr: 5.000000e-04 eta: 2:39:32 time: 0.292688 data_time: 0.031844 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.854332 loss: 0.000539 2022/10/27 19:39:11 - mmengine - INFO - Epoch(train) [150][550/586] lr: 5.000000e-04 eta: 2:39:19 time: 0.286378 data_time: 0.028470 memory: 11131 loss_kpt: 0.000540 acc_pose: 0.782339 loss: 0.000540 2022/10/27 19:39:22 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:39:22 - mmengine - INFO - Saving checkpoint at 150 epochs 2022/10/27 19:39:32 - mmengine - INFO - Epoch(val) [150][50/407] eta: 0:00:50 time: 0.142616 data_time: 0.022530 memory: 11131 2022/10/27 19:39:40 - mmengine - INFO - Epoch(val) [150][100/407] eta: 0:00:44 time: 0.145223 data_time: 0.023992 memory: 1836 2022/10/27 19:39:47 - mmengine - INFO - Epoch(val) [150][150/407] eta: 0:00:35 time: 0.137364 data_time: 0.016891 memory: 1836 2022/10/27 19:39:54 - mmengine - INFO - Epoch(val) [150][200/407] eta: 0:00:28 time: 0.138701 data_time: 0.018791 memory: 1836 2022/10/27 19:40:01 - mmengine - INFO - Epoch(val) [150][250/407] eta: 0:00:22 time: 0.140889 data_time: 0.020906 memory: 1836 2022/10/27 19:40:07 - mmengine - INFO - Epoch(val) [150][300/407] eta: 0:00:14 time: 0.136408 data_time: 0.016823 memory: 1836 2022/10/27 19:40:15 - mmengine - INFO - Epoch(val) [150][350/407] eta: 0:00:08 time: 0.147967 data_time: 0.027280 memory: 1836 2022/10/27 19:40:21 - mmengine - INFO - Epoch(val) [150][400/407] eta: 0:00:00 time: 0.126501 data_time: 0.011174 memory: 1836 2022/10/27 19:41:08 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 19:41:25 - mmengine - INFO - Epoch(val) [150][407/407] coco/AP: 0.741585 coco/AP .5: 0.900224 coco/AP .75: 0.811504 coco/AP (M): 0.697879 coco/AP (L): 0.816509 coco/AR: 0.793105 coco/AR .5: 0.938287 coco/AR .75: 0.855479 coco/AR (M): 0.744742 coco/AR (L): 0.861613 2022/10/27 19:41:40 - mmengine - INFO - Epoch(train) [151][50/586] lr: 5.000000e-04 eta: 2:38:52 time: 0.301259 data_time: 0.037637 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.879451 loss: 0.000529 2022/10/27 19:41:54 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:41:54 - mmengine - INFO - Epoch(train) [151][100/586] lr: 5.000000e-04 eta: 2:38:39 time: 0.288147 data_time: 0.027882 memory: 11131 loss_kpt: 0.000509 acc_pose: 0.831302 loss: 0.000509 2022/10/27 19:42:09 - mmengine - INFO - Epoch(train) [151][150/586] lr: 5.000000e-04 eta: 2:38:25 time: 0.285203 data_time: 0.028152 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.808127 loss: 0.000522 2022/10/27 19:42:23 - mmengine - INFO - Epoch(train) [151][200/586] lr: 5.000000e-04 eta: 2:38:12 time: 0.291843 data_time: 0.034575 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.875166 loss: 0.000541 2022/10/27 19:42:37 - mmengine - INFO - Epoch(train) [151][250/586] lr: 5.000000e-04 eta: 2:37:59 time: 0.281631 data_time: 0.027105 memory: 11131 loss_kpt: 0.000510 acc_pose: 0.907047 loss: 0.000510 2022/10/27 19:42:52 - mmengine - INFO - Epoch(train) [151][300/586] lr: 5.000000e-04 eta: 2:37:46 time: 0.291156 data_time: 0.027821 memory: 11131 loss_kpt: 0.000520 acc_pose: 0.856654 loss: 0.000520 2022/10/27 19:43:06 - mmengine - INFO - Epoch(train) [151][350/586] lr: 5.000000e-04 eta: 2:37:32 time: 0.286562 data_time: 0.029492 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.904895 loss: 0.000525 2022/10/27 19:43:21 - mmengine - INFO - Epoch(train) [151][400/586] lr: 5.000000e-04 eta: 2:37:19 time: 0.284759 data_time: 0.028424 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.862540 loss: 0.000539 2022/10/27 19:43:35 - mmengine - INFO - Epoch(train) [151][450/586] lr: 5.000000e-04 eta: 2:37:06 time: 0.291053 data_time: 0.027825 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.897665 loss: 0.000523 2022/10/27 19:43:49 - mmengine - INFO - Epoch(train) [151][500/586] lr: 5.000000e-04 eta: 2:36:53 time: 0.284666 data_time: 0.027231 memory: 11131 loss_kpt: 0.000532 acc_pose: 0.815198 loss: 0.000532 2022/10/27 19:44:04 - mmengine - INFO - Epoch(train) [151][550/586] lr: 5.000000e-04 eta: 2:36:39 time: 0.290560 data_time: 0.027659 memory: 11131 loss_kpt: 0.000545 acc_pose: 0.887938 loss: 0.000545 2022/10/27 19:44:14 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:44:29 - mmengine - INFO - Epoch(train) [152][50/586] lr: 5.000000e-04 eta: 2:36:13 time: 0.295627 data_time: 0.036871 memory: 11131 loss_kpt: 0.000537 acc_pose: 0.848467 loss: 0.000537 2022/10/27 19:44:43 - mmengine - INFO - Epoch(train) [152][100/586] lr: 5.000000e-04 eta: 2:36:00 time: 0.292780 data_time: 0.027538 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.876313 loss: 0.000524 2022/10/27 19:44:58 - mmengine - INFO - Epoch(train) [152][150/586] lr: 5.000000e-04 eta: 2:35:46 time: 0.285985 data_time: 0.030304 memory: 11131 loss_kpt: 0.000509 acc_pose: 0.885005 loss: 0.000509 2022/10/27 19:45:12 - mmengine - INFO - Epoch(train) [152][200/586] lr: 5.000000e-04 eta: 2:35:33 time: 0.293409 data_time: 0.026823 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.875946 loss: 0.000523 2022/10/27 19:45:27 - mmengine - INFO - Epoch(train) [152][250/586] lr: 5.000000e-04 eta: 2:35:20 time: 0.284645 data_time: 0.029614 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.878780 loss: 0.000538 2022/10/27 19:45:41 - mmengine - INFO - Epoch(train) [152][300/586] lr: 5.000000e-04 eta: 2:35:06 time: 0.287114 data_time: 0.026625 memory: 11131 loss_kpt: 0.000555 acc_pose: 0.896192 loss: 0.000555 2022/10/27 19:45:55 - mmengine - INFO - Epoch(train) [152][350/586] lr: 5.000000e-04 eta: 2:34:53 time: 0.288236 data_time: 0.028644 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.840516 loss: 0.000541 2022/10/27 19:46:10 - mmengine - INFO - Epoch(train) [152][400/586] lr: 5.000000e-04 eta: 2:34:40 time: 0.288492 data_time: 0.029413 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.892558 loss: 0.000514 2022/10/27 19:46:24 - mmengine - INFO - Epoch(train) [152][450/586] lr: 5.000000e-04 eta: 2:34:27 time: 0.286560 data_time: 0.029029 memory: 11131 loss_kpt: 0.000512 acc_pose: 0.914270 loss: 0.000512 2022/10/27 19:46:39 - mmengine - INFO - Epoch(train) [152][500/586] lr: 5.000000e-04 eta: 2:34:13 time: 0.287381 data_time: 0.029663 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.881485 loss: 0.000522 2022/10/27 19:46:42 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:46:53 - mmengine - INFO - Epoch(train) [152][550/586] lr: 5.000000e-04 eta: 2:34:00 time: 0.289928 data_time: 0.031153 memory: 11131 loss_kpt: 0.000530 acc_pose: 0.840578 loss: 0.000530 2022/10/27 19:47:03 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:47:18 - mmengine - INFO - Epoch(train) [153][50/586] lr: 5.000000e-04 eta: 2:33:34 time: 0.303472 data_time: 0.042242 memory: 11131 loss_kpt: 0.000527 acc_pose: 0.761029 loss: 0.000527 2022/10/27 19:47:32 - mmengine - INFO - Epoch(train) [153][100/586] lr: 5.000000e-04 eta: 2:33:20 time: 0.284148 data_time: 0.026667 memory: 11131 loss_kpt: 0.000510 acc_pose: 0.881853 loss: 0.000510 2022/10/27 19:47:47 - mmengine - INFO - Epoch(train) [153][150/586] lr: 5.000000e-04 eta: 2:33:07 time: 0.283805 data_time: 0.029523 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.897090 loss: 0.000539 2022/10/27 19:48:01 - mmengine - INFO - Epoch(train) [153][200/586] lr: 5.000000e-04 eta: 2:32:54 time: 0.292161 data_time: 0.034550 memory: 11131 loss_kpt: 0.000517 acc_pose: 0.940896 loss: 0.000517 2022/10/27 19:48:15 - mmengine - INFO - Epoch(train) [153][250/586] lr: 5.000000e-04 eta: 2:32:40 time: 0.280773 data_time: 0.028720 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.901123 loss: 0.000526 2022/10/27 19:48:30 - mmengine - INFO - Epoch(train) [153][300/586] lr: 5.000000e-04 eta: 2:32:27 time: 0.294415 data_time: 0.029929 memory: 11131 loss_kpt: 0.000520 acc_pose: 0.803811 loss: 0.000520 2022/10/27 19:48:44 - mmengine - INFO - Epoch(train) [153][350/586] lr: 5.000000e-04 eta: 2:32:14 time: 0.284187 data_time: 0.027521 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.824623 loss: 0.000534 2022/10/27 19:48:59 - mmengine - INFO - Epoch(train) [153][400/586] lr: 5.000000e-04 eta: 2:32:01 time: 0.285652 data_time: 0.028406 memory: 11131 loss_kpt: 0.000509 acc_pose: 0.875162 loss: 0.000509 2022/10/27 19:49:13 - mmengine - INFO - Epoch(train) [153][450/586] lr: 5.000000e-04 eta: 2:31:47 time: 0.291362 data_time: 0.031878 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.823293 loss: 0.000543 2022/10/27 19:49:28 - mmengine - INFO - Epoch(train) [153][500/586] lr: 5.000000e-04 eta: 2:31:34 time: 0.288349 data_time: 0.032796 memory: 11131 loss_kpt: 0.000546 acc_pose: 0.869218 loss: 0.000546 2022/10/27 19:49:42 - mmengine - INFO - Epoch(train) [153][550/586] lr: 5.000000e-04 eta: 2:31:21 time: 0.294081 data_time: 0.029734 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.900746 loss: 0.000526 2022/10/27 19:49:52 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:50:07 - mmengine - INFO - Epoch(train) [154][50/586] lr: 5.000000e-04 eta: 2:30:54 time: 0.296664 data_time: 0.038499 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.837657 loss: 0.000524 2022/10/27 19:50:22 - mmengine - INFO - Epoch(train) [154][100/586] lr: 5.000000e-04 eta: 2:30:41 time: 0.292506 data_time: 0.031797 memory: 11131 loss_kpt: 0.000513 acc_pose: 0.909272 loss: 0.000513 2022/10/27 19:50:36 - mmengine - INFO - Epoch(train) [154][150/586] lr: 5.000000e-04 eta: 2:30:28 time: 0.285370 data_time: 0.027127 memory: 11131 loss_kpt: 0.000537 acc_pose: 0.744393 loss: 0.000537 2022/10/27 19:50:51 - mmengine - INFO - Epoch(train) [154][200/586] lr: 5.000000e-04 eta: 2:30:15 time: 0.293060 data_time: 0.029921 memory: 11131 loss_kpt: 0.000503 acc_pose: 0.898998 loss: 0.000503 2022/10/27 19:51:05 - mmengine - INFO - Epoch(train) [154][250/586] lr: 5.000000e-04 eta: 2:30:02 time: 0.289726 data_time: 0.030964 memory: 11131 loss_kpt: 0.000520 acc_pose: 0.880555 loss: 0.000520 2022/10/27 19:51:20 - mmengine - INFO - Epoch(train) [154][300/586] lr: 5.000000e-04 eta: 2:29:48 time: 0.286064 data_time: 0.029082 memory: 11131 loss_kpt: 0.000540 acc_pose: 0.792693 loss: 0.000540 2022/10/27 19:51:32 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:51:34 - mmengine - INFO - Epoch(train) [154][350/586] lr: 5.000000e-04 eta: 2:29:35 time: 0.287097 data_time: 0.031206 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.886621 loss: 0.000539 2022/10/27 19:51:49 - mmengine - INFO - Epoch(train) [154][400/586] lr: 5.000000e-04 eta: 2:29:22 time: 0.292577 data_time: 0.028235 memory: 11131 loss_kpt: 0.000553 acc_pose: 0.867987 loss: 0.000553 2022/10/27 19:52:03 - mmengine - INFO - Epoch(train) [154][450/586] lr: 5.000000e-04 eta: 2:29:08 time: 0.284427 data_time: 0.028928 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.872196 loss: 0.000523 2022/10/27 19:52:17 - mmengine - INFO - Epoch(train) [154][500/586] lr: 5.000000e-04 eta: 2:28:55 time: 0.284660 data_time: 0.030162 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.831065 loss: 0.000523 2022/10/27 19:52:32 - mmengine - INFO - Epoch(train) [154][550/586] lr: 5.000000e-04 eta: 2:28:42 time: 0.291682 data_time: 0.026557 memory: 11131 loss_kpt: 0.000537 acc_pose: 0.874388 loss: 0.000537 2022/10/27 19:52:42 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:52:57 - mmengine - INFO - Epoch(train) [155][50/586] lr: 5.000000e-04 eta: 2:28:15 time: 0.299414 data_time: 0.038199 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.937149 loss: 0.000524 2022/10/27 19:53:11 - mmengine - INFO - Epoch(train) [155][100/586] lr: 5.000000e-04 eta: 2:28:02 time: 0.284915 data_time: 0.028241 memory: 11131 loss_kpt: 0.000530 acc_pose: 0.871070 loss: 0.000530 2022/10/27 19:53:25 - mmengine - INFO - Epoch(train) [155][150/586] lr: 5.000000e-04 eta: 2:27:49 time: 0.287835 data_time: 0.032616 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.852434 loss: 0.000519 2022/10/27 19:53:40 - mmengine - INFO - Epoch(train) [155][200/586] lr: 5.000000e-04 eta: 2:27:36 time: 0.287241 data_time: 0.030945 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.902853 loss: 0.000525 2022/10/27 19:53:54 - mmengine - INFO - Epoch(train) [155][250/586] lr: 5.000000e-04 eta: 2:27:22 time: 0.284630 data_time: 0.027181 memory: 11131 loss_kpt: 0.000536 acc_pose: 0.798953 loss: 0.000536 2022/10/27 19:54:09 - mmengine - INFO - Epoch(train) [155][300/586] lr: 5.000000e-04 eta: 2:27:09 time: 0.292176 data_time: 0.029819 memory: 11131 loss_kpt: 0.000521 acc_pose: 0.889693 loss: 0.000521 2022/10/27 19:54:23 - mmengine - INFO - Epoch(train) [155][350/586] lr: 5.000000e-04 eta: 2:26:56 time: 0.290575 data_time: 0.029430 memory: 11131 loss_kpt: 0.000537 acc_pose: 0.826774 loss: 0.000537 2022/10/27 19:54:37 - mmengine - INFO - Epoch(train) [155][400/586] lr: 5.000000e-04 eta: 2:26:42 time: 0.285159 data_time: 0.027930 memory: 11131 loss_kpt: 0.000521 acc_pose: 0.816573 loss: 0.000521 2022/10/27 19:54:52 - mmengine - INFO - Epoch(train) [155][450/586] lr: 5.000000e-04 eta: 2:26:29 time: 0.295254 data_time: 0.031939 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.842193 loss: 0.000541 2022/10/27 19:55:06 - mmengine - INFO - Epoch(train) [155][500/586] lr: 5.000000e-04 eta: 2:26:16 time: 0.283504 data_time: 0.028948 memory: 11131 loss_kpt: 0.000517 acc_pose: 0.858401 loss: 0.000517 2022/10/27 19:55:21 - mmengine - INFO - Epoch(train) [155][550/586] lr: 5.000000e-04 eta: 2:26:03 time: 0.297270 data_time: 0.028912 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.837496 loss: 0.000526 2022/10/27 19:55:31 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:55:47 - mmengine - INFO - Epoch(train) [156][50/586] lr: 5.000000e-04 eta: 2:25:37 time: 0.303996 data_time: 0.036834 memory: 11131 loss_kpt: 0.000520 acc_pose: 0.827573 loss: 0.000520 2022/10/27 19:56:01 - mmengine - INFO - Epoch(train) [156][100/586] lr: 5.000000e-04 eta: 2:25:23 time: 0.287672 data_time: 0.029248 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.786429 loss: 0.000522 2022/10/27 19:56:15 - mmengine - INFO - Epoch(train) [156][150/586] lr: 5.000000e-04 eta: 2:25:10 time: 0.284051 data_time: 0.027756 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.814814 loss: 0.000514 2022/10/27 19:56:22 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:56:30 - mmengine - INFO - Epoch(train) [156][200/586] lr: 5.000000e-04 eta: 2:24:57 time: 0.302012 data_time: 0.028145 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.853739 loss: 0.000524 2022/10/27 19:56:45 - mmengine - INFO - Epoch(train) [156][250/586] lr: 5.000000e-04 eta: 2:24:44 time: 0.287860 data_time: 0.030424 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.901362 loss: 0.000514 2022/10/27 19:56:59 - mmengine - INFO - Epoch(train) [156][300/586] lr: 5.000000e-04 eta: 2:24:30 time: 0.288137 data_time: 0.028733 memory: 11131 loss_kpt: 0.000518 acc_pose: 0.849504 loss: 0.000518 2022/10/27 19:57:13 - mmengine - INFO - Epoch(train) [156][350/586] lr: 5.000000e-04 eta: 2:24:17 time: 0.285533 data_time: 0.028158 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.873831 loss: 0.000533 2022/10/27 19:57:28 - mmengine - INFO - Epoch(train) [156][400/586] lr: 5.000000e-04 eta: 2:24:04 time: 0.287431 data_time: 0.030381 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.885648 loss: 0.000524 2022/10/27 19:57:42 - mmengine - INFO - Epoch(train) [156][450/586] lr: 5.000000e-04 eta: 2:23:50 time: 0.291517 data_time: 0.026788 memory: 11131 loss_kpt: 0.000532 acc_pose: 0.906598 loss: 0.000532 2022/10/27 19:57:57 - mmengine - INFO - Epoch(train) [156][500/586] lr: 5.000000e-04 eta: 2:23:37 time: 0.287126 data_time: 0.029090 memory: 11131 loss_kpt: 0.000518 acc_pose: 0.889569 loss: 0.000518 2022/10/27 19:58:11 - mmengine - INFO - Epoch(train) [156][550/586] lr: 5.000000e-04 eta: 2:23:24 time: 0.292280 data_time: 0.031916 memory: 11131 loss_kpt: 0.000516 acc_pose: 0.874548 loss: 0.000516 2022/10/27 19:58:22 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 19:58:36 - mmengine - INFO - Epoch(train) [157][50/586] lr: 5.000000e-04 eta: 2:22:58 time: 0.297566 data_time: 0.042002 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.768813 loss: 0.000543 2022/10/27 19:58:51 - mmengine - INFO - Epoch(train) [157][100/586] lr: 5.000000e-04 eta: 2:22:44 time: 0.296684 data_time: 0.028429 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.888461 loss: 0.000522 2022/10/27 19:59:06 - mmengine - INFO - Epoch(train) [157][150/586] lr: 5.000000e-04 eta: 2:22:31 time: 0.289955 data_time: 0.031126 memory: 11131 loss_kpt: 0.000543 acc_pose: 0.886811 loss: 0.000543 2022/10/27 19:59:20 - mmengine - INFO - Epoch(train) [157][200/586] lr: 5.000000e-04 eta: 2:22:18 time: 0.290555 data_time: 0.033898 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.869426 loss: 0.000525 2022/10/27 19:59:35 - mmengine - INFO - Epoch(train) [157][250/586] lr: 5.000000e-04 eta: 2:22:05 time: 0.287509 data_time: 0.027002 memory: 11131 loss_kpt: 0.000513 acc_pose: 0.870652 loss: 0.000513 2022/10/27 19:59:50 - mmengine - INFO - Epoch(train) [157][300/586] lr: 5.000000e-04 eta: 2:21:52 time: 0.297387 data_time: 0.035593 memory: 11131 loss_kpt: 0.000528 acc_pose: 0.854618 loss: 0.000528 2022/10/27 20:00:04 - mmengine - INFO - Epoch(train) [157][350/586] lr: 5.000000e-04 eta: 2:21:38 time: 0.285109 data_time: 0.027599 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.857447 loss: 0.000529 2022/10/27 20:00:18 - mmengine - INFO - Epoch(train) [157][400/586] lr: 5.000000e-04 eta: 2:21:25 time: 0.287556 data_time: 0.027030 memory: 11131 loss_kpt: 0.000521 acc_pose: 0.922028 loss: 0.000521 2022/10/27 20:00:33 - mmengine - INFO - Epoch(train) [157][450/586] lr: 5.000000e-04 eta: 2:21:12 time: 0.288018 data_time: 0.028752 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.914116 loss: 0.000525 2022/10/27 20:00:47 - mmengine - INFO - Epoch(train) [157][500/586] lr: 5.000000e-04 eta: 2:20:58 time: 0.284966 data_time: 0.028607 memory: 11131 loss_kpt: 0.000531 acc_pose: 0.862652 loss: 0.000531 2022/10/27 20:01:01 - mmengine - INFO - Epoch(train) [157][550/586] lr: 5.000000e-04 eta: 2:20:45 time: 0.285697 data_time: 0.027234 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.759016 loss: 0.000539 2022/10/27 20:01:11 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:01:11 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:01:26 - mmengine - INFO - Epoch(train) [158][50/586] lr: 5.000000e-04 eta: 2:20:19 time: 0.301454 data_time: 0.040954 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.849121 loss: 0.000522 2022/10/27 20:01:41 - mmengine - INFO - Epoch(train) [158][100/586] lr: 5.000000e-04 eta: 2:20:05 time: 0.287831 data_time: 0.031573 memory: 11131 loss_kpt: 0.000517 acc_pose: 0.823615 loss: 0.000517 2022/10/27 20:01:55 - mmengine - INFO - Epoch(train) [158][150/586] lr: 5.000000e-04 eta: 2:19:52 time: 0.288613 data_time: 0.028482 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.851592 loss: 0.000539 2022/10/27 20:02:10 - mmengine - INFO - Epoch(train) [158][200/586] lr: 5.000000e-04 eta: 2:19:39 time: 0.296210 data_time: 0.028925 memory: 11131 loss_kpt: 0.000536 acc_pose: 0.768307 loss: 0.000536 2022/10/27 20:02:24 - mmengine - INFO - Epoch(train) [158][250/586] lr: 5.000000e-04 eta: 2:19:26 time: 0.281726 data_time: 0.029667 memory: 11131 loss_kpt: 0.000537 acc_pose: 0.911457 loss: 0.000537 2022/10/27 20:02:39 - mmengine - INFO - Epoch(train) [158][300/586] lr: 5.000000e-04 eta: 2:19:12 time: 0.290020 data_time: 0.027918 memory: 11131 loss_kpt: 0.000528 acc_pose: 0.854368 loss: 0.000528 2022/10/27 20:02:53 - mmengine - INFO - Epoch(train) [158][350/586] lr: 5.000000e-04 eta: 2:18:59 time: 0.286916 data_time: 0.029785 memory: 11131 loss_kpt: 0.000528 acc_pose: 0.865889 loss: 0.000528 2022/10/27 20:03:07 - mmengine - INFO - Epoch(train) [158][400/586] lr: 5.000000e-04 eta: 2:18:46 time: 0.288296 data_time: 0.027005 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.888380 loss: 0.000522 2022/10/27 20:03:22 - mmengine - INFO - Epoch(train) [158][450/586] lr: 5.000000e-04 eta: 2:18:32 time: 0.292554 data_time: 0.026579 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.876364 loss: 0.000542 2022/10/27 20:03:36 - mmengine - INFO - Epoch(train) [158][500/586] lr: 5.000000e-04 eta: 2:18:19 time: 0.287705 data_time: 0.029207 memory: 11131 loss_kpt: 0.000531 acc_pose: 0.815110 loss: 0.000531 2022/10/27 20:03:51 - mmengine - INFO - Epoch(train) [158][550/586] lr: 5.000000e-04 eta: 2:18:06 time: 0.289458 data_time: 0.033925 memory: 11131 loss_kpt: 0.000513 acc_pose: 0.850163 loss: 0.000513 2022/10/27 20:04:01 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:04:16 - mmengine - INFO - Epoch(train) [159][50/586] lr: 5.000000e-04 eta: 2:17:40 time: 0.297514 data_time: 0.038000 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.877518 loss: 0.000523 2022/10/27 20:04:31 - mmengine - INFO - Epoch(train) [159][100/586] lr: 5.000000e-04 eta: 2:17:26 time: 0.294880 data_time: 0.028042 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.892809 loss: 0.000533 2022/10/27 20:04:45 - mmengine - INFO - Epoch(train) [159][150/586] lr: 5.000000e-04 eta: 2:17:13 time: 0.285805 data_time: 0.030449 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.879617 loss: 0.000525 2022/10/27 20:04:59 - mmengine - INFO - Epoch(train) [159][200/586] lr: 5.000000e-04 eta: 2:17:00 time: 0.288768 data_time: 0.027576 memory: 11131 loss_kpt: 0.000528 acc_pose: 0.854897 loss: 0.000528 2022/10/27 20:05:14 - mmengine - INFO - Epoch(train) [159][250/586] lr: 5.000000e-04 eta: 2:16:46 time: 0.285735 data_time: 0.029486 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.805068 loss: 0.000539 2022/10/27 20:05:28 - mmengine - INFO - Epoch(train) [159][300/586] lr: 5.000000e-04 eta: 2:16:33 time: 0.288919 data_time: 0.027028 memory: 11131 loss_kpt: 0.000518 acc_pose: 0.839073 loss: 0.000518 2022/10/27 20:05:42 - mmengine - INFO - Epoch(train) [159][350/586] lr: 5.000000e-04 eta: 2:16:20 time: 0.285807 data_time: 0.027177 memory: 11131 loss_kpt: 0.000518 acc_pose: 0.851100 loss: 0.000518 2022/10/27 20:05:57 - mmengine - INFO - Epoch(train) [159][400/586] lr: 5.000000e-04 eta: 2:16:07 time: 0.286972 data_time: 0.028154 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.863741 loss: 0.000538 2022/10/27 20:06:00 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:06:11 - mmengine - INFO - Epoch(train) [159][450/586] lr: 5.000000e-04 eta: 2:15:53 time: 0.287423 data_time: 0.031022 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.891518 loss: 0.000529 2022/10/27 20:06:25 - mmengine - INFO - Epoch(train) [159][500/586] lr: 5.000000e-04 eta: 2:15:40 time: 0.285944 data_time: 0.029717 memory: 11131 loss_kpt: 0.000515 acc_pose: 0.852148 loss: 0.000515 2022/10/27 20:06:40 - mmengine - INFO - Epoch(train) [159][550/586] lr: 5.000000e-04 eta: 2:15:27 time: 0.287488 data_time: 0.028092 memory: 11131 loss_kpt: 0.000542 acc_pose: 0.875523 loss: 0.000542 2022/10/27 20:06:50 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:07:05 - mmengine - INFO - Epoch(train) [160][50/586] lr: 5.000000e-04 eta: 2:15:00 time: 0.295557 data_time: 0.036895 memory: 11131 loss_kpt: 0.000513 acc_pose: 0.861368 loss: 0.000513 2022/10/27 20:07:19 - mmengine - INFO - Epoch(train) [160][100/586] lr: 5.000000e-04 eta: 2:14:47 time: 0.289258 data_time: 0.033790 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.895231 loss: 0.000519 2022/10/27 20:07:34 - mmengine - INFO - Epoch(train) [160][150/586] lr: 5.000000e-04 eta: 2:14:34 time: 0.284253 data_time: 0.029617 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.888062 loss: 0.000534 2022/10/27 20:07:48 - mmengine - INFO - Epoch(train) [160][200/586] lr: 5.000000e-04 eta: 2:14:20 time: 0.289108 data_time: 0.027260 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.864443 loss: 0.000526 2022/10/27 20:08:03 - mmengine - INFO - Epoch(train) [160][250/586] lr: 5.000000e-04 eta: 2:14:07 time: 0.291458 data_time: 0.029787 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.883598 loss: 0.000529 2022/10/27 20:08:17 - mmengine - INFO - Epoch(train) [160][300/586] lr: 5.000000e-04 eta: 2:13:54 time: 0.285872 data_time: 0.030408 memory: 11131 loss_kpt: 0.000521 acc_pose: 0.929456 loss: 0.000521 2022/10/27 20:08:31 - mmengine - INFO - Epoch(train) [160][350/586] lr: 5.000000e-04 eta: 2:13:41 time: 0.291650 data_time: 0.031891 memory: 11131 loss_kpt: 0.000548 acc_pose: 0.899611 loss: 0.000548 2022/10/27 20:08:46 - mmengine - INFO - Epoch(train) [160][400/586] lr: 5.000000e-04 eta: 2:13:27 time: 0.292011 data_time: 0.029164 memory: 11131 loss_kpt: 0.000518 acc_pose: 0.810277 loss: 0.000518 2022/10/27 20:09:01 - mmengine - INFO - Epoch(train) [160][450/586] lr: 5.000000e-04 eta: 2:13:14 time: 0.290888 data_time: 0.027961 memory: 11131 loss_kpt: 0.000530 acc_pose: 0.881976 loss: 0.000530 2022/10/27 20:09:15 - mmengine - INFO - Epoch(train) [160][500/586] lr: 5.000000e-04 eta: 2:13:01 time: 0.287368 data_time: 0.026705 memory: 11131 loss_kpt: 0.000518 acc_pose: 0.855160 loss: 0.000518 2022/10/27 20:09:30 - mmengine - INFO - Epoch(train) [160][550/586] lr: 5.000000e-04 eta: 2:12:47 time: 0.291356 data_time: 0.029895 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.864489 loss: 0.000534 2022/10/27 20:09:40 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:09:40 - mmengine - INFO - Saving checkpoint at 160 epochs 2022/10/27 20:09:51 - mmengine - INFO - Epoch(val) [160][50/407] eta: 0:00:51 time: 0.144778 data_time: 0.023801 memory: 11131 2022/10/27 20:09:58 - mmengine - INFO - Epoch(val) [160][100/407] eta: 0:00:42 time: 0.139912 data_time: 0.017223 memory: 1836 2022/10/27 20:10:05 - mmengine - INFO - Epoch(val) [160][150/407] eta: 0:00:35 time: 0.137583 data_time: 0.016259 memory: 1836 2022/10/27 20:10:11 - mmengine - INFO - Epoch(val) [160][200/407] eta: 0:00:28 time: 0.135402 data_time: 0.013932 memory: 1836 2022/10/27 20:10:18 - mmengine - INFO - Epoch(val) [160][250/407] eta: 0:00:20 time: 0.131766 data_time: 0.012016 memory: 1836 2022/10/27 20:10:25 - mmengine - INFO - Epoch(val) [160][300/407] eta: 0:00:14 time: 0.135683 data_time: 0.015885 memory: 1836 2022/10/27 20:10:32 - mmengine - INFO - Epoch(val) [160][350/407] eta: 0:00:08 time: 0.145831 data_time: 0.025787 memory: 1836 2022/10/27 20:10:39 - mmengine - INFO - Epoch(val) [160][400/407] eta: 0:00:00 time: 0.136991 data_time: 0.021862 memory: 1836 2022/10/27 20:11:26 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 20:11:43 - mmengine - INFO - Epoch(val) [160][407/407] coco/AP: 0.739742 coco/AP .5: 0.900938 coco/AP .75: 0.808630 coco/AP (M): 0.698505 coco/AP (L): 0.810884 coco/AR: 0.790475 coco/AR .5: 0.937343 coco/AR .75: 0.852015 coco/AR (M): 0.745015 coco/AR (L): 0.856150 2022/10/27 20:11:58 - mmengine - INFO - Epoch(train) [161][50/586] lr: 5.000000e-04 eta: 2:12:21 time: 0.296604 data_time: 0.041132 memory: 11131 loss_kpt: 0.000503 acc_pose: 0.953397 loss: 0.000503 2022/10/27 20:12:12 - mmengine - INFO - Epoch(train) [161][100/586] lr: 5.000000e-04 eta: 2:12:08 time: 0.292130 data_time: 0.028288 memory: 11131 loss_kpt: 0.000505 acc_pose: 0.932732 loss: 0.000505 2022/10/27 20:12:27 - mmengine - INFO - Epoch(train) [161][150/586] lr: 5.000000e-04 eta: 2:11:55 time: 0.285540 data_time: 0.029372 memory: 11131 loss_kpt: 0.000509 acc_pose: 0.907119 loss: 0.000509 2022/10/27 20:12:41 - mmengine - INFO - Epoch(train) [161][200/586] lr: 5.000000e-04 eta: 2:11:42 time: 0.288363 data_time: 0.029937 memory: 11131 loss_kpt: 0.000511 acc_pose: 0.855639 loss: 0.000511 2022/10/27 20:12:53 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:12:55 - mmengine - INFO - Epoch(train) [161][250/586] lr: 5.000000e-04 eta: 2:11:28 time: 0.285587 data_time: 0.027899 memory: 11131 loss_kpt: 0.000513 acc_pose: 0.901038 loss: 0.000513 2022/10/27 20:13:10 - mmengine - INFO - Epoch(train) [161][300/586] lr: 5.000000e-04 eta: 2:11:15 time: 0.288816 data_time: 0.030629 memory: 11131 loss_kpt: 0.000512 acc_pose: 0.895498 loss: 0.000512 2022/10/27 20:13:24 - mmengine - INFO - Epoch(train) [161][350/586] lr: 5.000000e-04 eta: 2:11:02 time: 0.292482 data_time: 0.028490 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.897793 loss: 0.000514 2022/10/27 20:13:39 - mmengine - INFO - Epoch(train) [161][400/586] lr: 5.000000e-04 eta: 2:10:48 time: 0.289278 data_time: 0.027907 memory: 11131 loss_kpt: 0.000533 acc_pose: 0.871697 loss: 0.000533 2022/10/27 20:13:53 - mmengine - INFO - Epoch(train) [161][450/586] lr: 5.000000e-04 eta: 2:10:35 time: 0.285687 data_time: 0.030725 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.840168 loss: 0.000519 2022/10/27 20:14:07 - mmengine - INFO - Epoch(train) [161][500/586] lr: 5.000000e-04 eta: 2:10:22 time: 0.284990 data_time: 0.029273 memory: 11131 loss_kpt: 0.000518 acc_pose: 0.842062 loss: 0.000518 2022/10/27 20:14:22 - mmengine - INFO - Epoch(train) [161][550/586] lr: 5.000000e-04 eta: 2:10:08 time: 0.289444 data_time: 0.028263 memory: 11131 loss_kpt: 0.000516 acc_pose: 0.856989 loss: 0.000516 2022/10/27 20:14:32 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:14:47 - mmengine - INFO - Epoch(train) [162][50/586] lr: 5.000000e-04 eta: 2:09:42 time: 0.300382 data_time: 0.040378 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.847622 loss: 0.000526 2022/10/27 20:15:02 - mmengine - INFO - Epoch(train) [162][100/586] lr: 5.000000e-04 eta: 2:09:29 time: 0.288502 data_time: 0.027499 memory: 11131 loss_kpt: 0.000512 acc_pose: 0.852972 loss: 0.000512 2022/10/27 20:15:16 - mmengine - INFO - Epoch(train) [162][150/586] lr: 5.000000e-04 eta: 2:09:16 time: 0.285709 data_time: 0.027654 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.902954 loss: 0.000514 2022/10/27 20:15:30 - mmengine - INFO - Epoch(train) [162][200/586] lr: 5.000000e-04 eta: 2:09:02 time: 0.290066 data_time: 0.027904 memory: 11131 loss_kpt: 0.000517 acc_pose: 0.890142 loss: 0.000517 2022/10/27 20:15:45 - mmengine - INFO - Epoch(train) [162][250/586] lr: 5.000000e-04 eta: 2:08:49 time: 0.290448 data_time: 0.030482 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.868817 loss: 0.000524 2022/10/27 20:15:59 - mmengine - INFO - Epoch(train) [162][300/586] lr: 5.000000e-04 eta: 2:08:36 time: 0.283918 data_time: 0.027887 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.868947 loss: 0.000525 2022/10/27 20:16:14 - mmengine - INFO - Epoch(train) [162][350/586] lr: 5.000000e-04 eta: 2:08:22 time: 0.287461 data_time: 0.028346 memory: 11131 loss_kpt: 0.000511 acc_pose: 0.902827 loss: 0.000511 2022/10/27 20:16:28 - mmengine - INFO - Epoch(train) [162][400/586] lr: 5.000000e-04 eta: 2:08:09 time: 0.285839 data_time: 0.027425 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.883773 loss: 0.000514 2022/10/27 20:16:42 - mmengine - INFO - Epoch(train) [162][450/586] lr: 5.000000e-04 eta: 2:07:56 time: 0.286987 data_time: 0.026693 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.837252 loss: 0.000525 2022/10/27 20:16:57 - mmengine - INFO - Epoch(train) [162][500/586] lr: 5.000000e-04 eta: 2:07:42 time: 0.291524 data_time: 0.027234 memory: 11131 loss_kpt: 0.000532 acc_pose: 0.872412 loss: 0.000532 2022/10/27 20:17:11 - mmengine - INFO - Epoch(train) [162][550/586] lr: 5.000000e-04 eta: 2:07:29 time: 0.289300 data_time: 0.028988 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.845866 loss: 0.000524 2022/10/27 20:17:21 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:17:36 - mmengine - INFO - Epoch(train) [163][50/586] lr: 5.000000e-04 eta: 2:07:03 time: 0.296514 data_time: 0.036498 memory: 11131 loss_kpt: 0.000520 acc_pose: 0.886030 loss: 0.000520 2022/10/27 20:17:41 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:17:51 - mmengine - INFO - Epoch(train) [163][100/586] lr: 5.000000e-04 eta: 2:06:50 time: 0.289099 data_time: 0.029124 memory: 11131 loss_kpt: 0.000505 acc_pose: 0.898910 loss: 0.000505 2022/10/27 20:18:05 - mmengine - INFO - Epoch(train) [163][150/586] lr: 5.000000e-04 eta: 2:06:37 time: 0.291834 data_time: 0.027425 memory: 11131 loss_kpt: 0.000521 acc_pose: 0.812265 loss: 0.000521 2022/10/27 20:18:20 - mmengine - INFO - Epoch(train) [163][200/586] lr: 5.000000e-04 eta: 2:06:23 time: 0.288490 data_time: 0.030357 memory: 11131 loss_kpt: 0.000513 acc_pose: 0.863991 loss: 0.000513 2022/10/27 20:18:34 - mmengine - INFO - Epoch(train) [163][250/586] lr: 5.000000e-04 eta: 2:06:10 time: 0.283953 data_time: 0.028023 memory: 11131 loss_kpt: 0.000539 acc_pose: 0.820360 loss: 0.000539 2022/10/27 20:18:48 - mmengine - INFO - Epoch(train) [163][300/586] lr: 5.000000e-04 eta: 2:05:56 time: 0.284030 data_time: 0.027803 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.878231 loss: 0.000522 2022/10/27 20:19:02 - mmengine - INFO - Epoch(train) [163][350/586] lr: 5.000000e-04 eta: 2:05:43 time: 0.287311 data_time: 0.027703 memory: 11131 loss_kpt: 0.000541 acc_pose: 0.870279 loss: 0.000541 2022/10/27 20:19:17 - mmengine - INFO - Epoch(train) [163][400/586] lr: 5.000000e-04 eta: 2:05:30 time: 0.292001 data_time: 0.028961 memory: 11131 loss_kpt: 0.000512 acc_pose: 0.888436 loss: 0.000512 2022/10/27 20:19:31 - mmengine - INFO - Epoch(train) [163][450/586] lr: 5.000000e-04 eta: 2:05:16 time: 0.280154 data_time: 0.027781 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.851153 loss: 0.000523 2022/10/27 20:19:45 - mmengine - INFO - Epoch(train) [163][500/586] lr: 5.000000e-04 eta: 2:05:03 time: 0.286839 data_time: 0.027757 memory: 11131 loss_kpt: 0.000507 acc_pose: 0.865110 loss: 0.000507 2022/10/27 20:20:00 - mmengine - INFO - Epoch(train) [163][550/586] lr: 5.000000e-04 eta: 2:04:50 time: 0.288863 data_time: 0.029897 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.874081 loss: 0.000535 2022/10/27 20:20:10 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:20:25 - mmengine - INFO - Epoch(train) [164][50/586] lr: 5.000000e-04 eta: 2:04:24 time: 0.299943 data_time: 0.040205 memory: 11131 loss_kpt: 0.000525 acc_pose: 0.867188 loss: 0.000525 2022/10/27 20:20:39 - mmengine - INFO - Epoch(train) [164][100/586] lr: 5.000000e-04 eta: 2:04:11 time: 0.285084 data_time: 0.027649 memory: 11131 loss_kpt: 0.000521 acc_pose: 0.891379 loss: 0.000521 2022/10/27 20:20:54 - mmengine - INFO - Epoch(train) [164][150/586] lr: 5.000000e-04 eta: 2:03:57 time: 0.286558 data_time: 0.029620 memory: 11131 loss_kpt: 0.000515 acc_pose: 0.867464 loss: 0.000515 2022/10/27 20:21:08 - mmengine - INFO - Epoch(train) [164][200/586] lr: 5.000000e-04 eta: 2:03:44 time: 0.293154 data_time: 0.028034 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.823050 loss: 0.000524 2022/10/27 20:21:23 - mmengine - INFO - Epoch(train) [164][250/586] lr: 5.000000e-04 eta: 2:03:31 time: 0.292725 data_time: 0.031849 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.905060 loss: 0.000526 2022/10/27 20:21:37 - mmengine - INFO - Epoch(train) [164][300/586] lr: 5.000000e-04 eta: 2:03:17 time: 0.284487 data_time: 0.028714 memory: 11131 loss_kpt: 0.000505 acc_pose: 0.851604 loss: 0.000505 2022/10/27 20:21:52 - mmengine - INFO - Epoch(train) [164][350/586] lr: 5.000000e-04 eta: 2:03:04 time: 0.286749 data_time: 0.027425 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.889063 loss: 0.000522 2022/10/27 20:22:06 - mmengine - INFO - Epoch(train) [164][400/586] lr: 5.000000e-04 eta: 2:02:50 time: 0.286047 data_time: 0.030221 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.857445 loss: 0.000519 2022/10/27 20:22:20 - mmengine - INFO - Epoch(train) [164][450/586] lr: 5.000000e-04 eta: 2:02:37 time: 0.285681 data_time: 0.029459 memory: 11131 loss_kpt: 0.000512 acc_pose: 0.871080 loss: 0.000512 2022/10/27 20:22:29 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:22:35 - mmengine - INFO - Epoch(train) [164][500/586] lr: 5.000000e-04 eta: 2:02:24 time: 0.291457 data_time: 0.029314 memory: 11131 loss_kpt: 0.000522 acc_pose: 0.879654 loss: 0.000522 2022/10/27 20:22:49 - mmengine - INFO - Epoch(train) [164][550/586] lr: 5.000000e-04 eta: 2:02:10 time: 0.288117 data_time: 0.030154 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.838335 loss: 0.000519 2022/10/27 20:22:59 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:23:14 - mmengine - INFO - Epoch(train) [165][50/586] lr: 5.000000e-04 eta: 2:01:45 time: 0.299924 data_time: 0.035596 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.875114 loss: 0.000514 2022/10/27 20:23:29 - mmengine - INFO - Epoch(train) [165][100/586] lr: 5.000000e-04 eta: 2:01:31 time: 0.286938 data_time: 0.029027 memory: 11131 loss_kpt: 0.000510 acc_pose: 0.819567 loss: 0.000510 2022/10/27 20:23:43 - mmengine - INFO - Epoch(train) [165][150/586] lr: 5.000000e-04 eta: 2:01:18 time: 0.291164 data_time: 0.031336 memory: 11131 loss_kpt: 0.000510 acc_pose: 0.882920 loss: 0.000510 2022/10/27 20:23:57 - mmengine - INFO - Epoch(train) [165][200/586] lr: 5.000000e-04 eta: 2:01:05 time: 0.286595 data_time: 0.029842 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.838788 loss: 0.000514 2022/10/27 20:24:12 - mmengine - INFO - Epoch(train) [165][250/586] lr: 5.000000e-04 eta: 2:00:51 time: 0.286386 data_time: 0.030149 memory: 11131 loss_kpt: 0.000517 acc_pose: 0.893194 loss: 0.000517 2022/10/27 20:24:26 - mmengine - INFO - Epoch(train) [165][300/586] lr: 5.000000e-04 eta: 2:00:38 time: 0.287866 data_time: 0.029846 memory: 11131 loss_kpt: 0.000518 acc_pose: 0.826686 loss: 0.000518 2022/10/27 20:24:41 - mmengine - INFO - Epoch(train) [165][350/586] lr: 5.000000e-04 eta: 2:00:25 time: 0.291383 data_time: 0.027712 memory: 11131 loss_kpt: 0.000521 acc_pose: 0.877366 loss: 0.000521 2022/10/27 20:24:55 - mmengine - INFO - Epoch(train) [165][400/586] lr: 5.000000e-04 eta: 2:00:11 time: 0.288149 data_time: 0.032625 memory: 11131 loss_kpt: 0.000531 acc_pose: 0.848589 loss: 0.000531 2022/10/27 20:25:09 - mmengine - INFO - Epoch(train) [165][450/586] lr: 5.000000e-04 eta: 1:59:58 time: 0.284599 data_time: 0.027193 memory: 11131 loss_kpt: 0.000510 acc_pose: 0.886335 loss: 0.000510 2022/10/27 20:25:24 - mmengine - INFO - Epoch(train) [165][500/586] lr: 5.000000e-04 eta: 1:59:45 time: 0.286753 data_time: 0.029419 memory: 11131 loss_kpt: 0.000512 acc_pose: 0.828280 loss: 0.000512 2022/10/27 20:25:38 - mmengine - INFO - Epoch(train) [165][550/586] lr: 5.000000e-04 eta: 1:59:31 time: 0.288653 data_time: 0.029389 memory: 11131 loss_kpt: 0.000511 acc_pose: 0.844096 loss: 0.000511 2022/10/27 20:25:49 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:26:03 - mmengine - INFO - Epoch(train) [166][50/586] lr: 5.000000e-04 eta: 1:59:06 time: 0.296841 data_time: 0.040283 memory: 11131 loss_kpt: 0.000521 acc_pose: 0.911083 loss: 0.000521 2022/10/27 20:26:18 - mmengine - INFO - Epoch(train) [166][100/586] lr: 5.000000e-04 eta: 1:58:52 time: 0.288015 data_time: 0.030323 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.889510 loss: 0.000526 2022/10/27 20:26:32 - mmengine - INFO - Epoch(train) [166][150/586] lr: 5.000000e-04 eta: 1:58:39 time: 0.288482 data_time: 0.028794 memory: 11131 loss_kpt: 0.000510 acc_pose: 0.816153 loss: 0.000510 2022/10/27 20:26:47 - mmengine - INFO - Epoch(train) [166][200/586] lr: 5.000000e-04 eta: 1:58:25 time: 0.287421 data_time: 0.027827 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.866872 loss: 0.000526 2022/10/27 20:27:01 - mmengine - INFO - Epoch(train) [166][250/586] lr: 5.000000e-04 eta: 1:58:12 time: 0.294201 data_time: 0.028446 memory: 11131 loss_kpt: 0.000551 acc_pose: 0.875958 loss: 0.000551 2022/10/27 20:27:16 - mmengine - INFO - Epoch(train) [166][300/586] lr: 5.000000e-04 eta: 1:57:59 time: 0.285024 data_time: 0.028996 memory: 11131 loss_kpt: 0.000527 acc_pose: 0.878914 loss: 0.000527 2022/10/27 20:27:18 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:27:30 - mmengine - INFO - Epoch(train) [166][350/586] lr: 5.000000e-04 eta: 1:57:45 time: 0.282244 data_time: 0.028726 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.925506 loss: 0.000529 2022/10/27 20:27:44 - mmengine - INFO - Epoch(train) [166][400/586] lr: 5.000000e-04 eta: 1:57:32 time: 0.287876 data_time: 0.026697 memory: 11131 loss_kpt: 0.000513 acc_pose: 0.839291 loss: 0.000513 2022/10/27 20:27:59 - mmengine - INFO - Epoch(train) [166][450/586] lr: 5.000000e-04 eta: 1:57:19 time: 0.287260 data_time: 0.027311 memory: 11131 loss_kpt: 0.000511 acc_pose: 0.880928 loss: 0.000511 2022/10/27 20:28:13 - mmengine - INFO - Epoch(train) [166][500/586] lr: 5.000000e-04 eta: 1:57:05 time: 0.291991 data_time: 0.028502 memory: 11131 loss_kpt: 0.000509 acc_pose: 0.896711 loss: 0.000509 2022/10/27 20:28:28 - mmengine - INFO - Epoch(train) [166][550/586] lr: 5.000000e-04 eta: 1:56:52 time: 0.287600 data_time: 0.028254 memory: 11131 loss_kpt: 0.000505 acc_pose: 0.836972 loss: 0.000505 2022/10/27 20:28:38 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:28:52 - mmengine - INFO - Epoch(train) [167][50/586] lr: 5.000000e-04 eta: 1:56:26 time: 0.297149 data_time: 0.039716 memory: 11131 loss_kpt: 0.000511 acc_pose: 0.895346 loss: 0.000511 2022/10/27 20:29:07 - mmengine - INFO - Epoch(train) [167][100/586] lr: 5.000000e-04 eta: 1:56:13 time: 0.290897 data_time: 0.027221 memory: 11131 loss_kpt: 0.000528 acc_pose: 0.875192 loss: 0.000528 2022/10/27 20:29:22 - mmengine - INFO - Epoch(train) [167][150/586] lr: 5.000000e-04 eta: 1:56:00 time: 0.290588 data_time: 0.026814 memory: 11131 loss_kpt: 0.000538 acc_pose: 0.805977 loss: 0.000538 2022/10/27 20:29:36 - mmengine - INFO - Epoch(train) [167][200/586] lr: 5.000000e-04 eta: 1:55:46 time: 0.287665 data_time: 0.027420 memory: 11131 loss_kpt: 0.000517 acc_pose: 0.863298 loss: 0.000517 2022/10/27 20:29:50 - mmengine - INFO - Epoch(train) [167][250/586] lr: 5.000000e-04 eta: 1:55:33 time: 0.283456 data_time: 0.027510 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.890423 loss: 0.000526 2022/10/27 20:30:05 - mmengine - INFO - Epoch(train) [167][300/586] lr: 5.000000e-04 eta: 1:55:20 time: 0.290939 data_time: 0.033338 memory: 11131 loss_kpt: 0.000507 acc_pose: 0.884637 loss: 0.000507 2022/10/27 20:30:19 - mmengine - INFO - Epoch(train) [167][350/586] lr: 5.000000e-04 eta: 1:55:06 time: 0.295636 data_time: 0.035848 memory: 11131 loss_kpt: 0.000511 acc_pose: 0.834520 loss: 0.000511 2022/10/27 20:30:34 - mmengine - INFO - Epoch(train) [167][400/586] lr: 5.000000e-04 eta: 1:54:53 time: 0.291159 data_time: 0.027978 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.905751 loss: 0.000519 2022/10/27 20:30:48 - mmengine - INFO - Epoch(train) [167][450/586] lr: 5.000000e-04 eta: 1:54:40 time: 0.286772 data_time: 0.030404 memory: 11131 loss_kpt: 0.000515 acc_pose: 0.877394 loss: 0.000515 2022/10/27 20:31:03 - mmengine - INFO - Epoch(train) [167][500/586] lr: 5.000000e-04 eta: 1:54:26 time: 0.285887 data_time: 0.030228 memory: 11131 loss_kpt: 0.000540 acc_pose: 0.861120 loss: 0.000540 2022/10/27 20:31:17 - mmengine - INFO - Epoch(train) [167][550/586] lr: 5.000000e-04 eta: 1:54:13 time: 0.293194 data_time: 0.028472 memory: 11131 loss_kpt: 0.000518 acc_pose: 0.885237 loss: 0.000518 2022/10/27 20:31:28 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:31:43 - mmengine - INFO - Epoch(train) [168][50/586] lr: 5.000000e-04 eta: 1:53:47 time: 0.297233 data_time: 0.036714 memory: 11131 loss_kpt: 0.000518 acc_pose: 0.840064 loss: 0.000518 2022/10/27 20:31:57 - mmengine - INFO - Epoch(train) [168][100/586] lr: 5.000000e-04 eta: 1:53:34 time: 0.287151 data_time: 0.030202 memory: 11131 loss_kpt: 0.000534 acc_pose: 0.784890 loss: 0.000534 2022/10/27 20:32:08 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:32:11 - mmengine - INFO - Epoch(train) [168][150/586] lr: 5.000000e-04 eta: 1:53:21 time: 0.285151 data_time: 0.028857 memory: 11131 loss_kpt: 0.000505 acc_pose: 0.894289 loss: 0.000505 2022/10/27 20:32:26 - mmengine - INFO - Epoch(train) [168][200/586] lr: 5.000000e-04 eta: 1:53:07 time: 0.284460 data_time: 0.029464 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.868742 loss: 0.000519 2022/10/27 20:32:40 - mmengine - INFO - Epoch(train) [168][250/586] lr: 5.000000e-04 eta: 1:52:54 time: 0.293846 data_time: 0.031153 memory: 11131 loss_kpt: 0.000506 acc_pose: 0.811654 loss: 0.000506 2022/10/27 20:32:54 - mmengine - INFO - Epoch(train) [168][300/586] lr: 5.000000e-04 eta: 1:52:41 time: 0.282427 data_time: 0.030521 memory: 11131 loss_kpt: 0.000524 acc_pose: 0.883542 loss: 0.000524 2022/10/27 20:33:09 - mmengine - INFO - Epoch(train) [168][350/586] lr: 5.000000e-04 eta: 1:52:27 time: 0.287265 data_time: 0.030096 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.934742 loss: 0.000523 2022/10/27 20:33:23 - mmengine - INFO - Epoch(train) [168][400/586] lr: 5.000000e-04 eta: 1:52:14 time: 0.286454 data_time: 0.029282 memory: 11131 loss_kpt: 0.000510 acc_pose: 0.882243 loss: 0.000510 2022/10/27 20:33:38 - mmengine - INFO - Epoch(train) [168][450/586] lr: 5.000000e-04 eta: 1:52:00 time: 0.291355 data_time: 0.030590 memory: 11131 loss_kpt: 0.000515 acc_pose: 0.841716 loss: 0.000515 2022/10/27 20:33:52 - mmengine - INFO - Epoch(train) [168][500/586] lr: 5.000000e-04 eta: 1:51:47 time: 0.294735 data_time: 0.031827 memory: 11131 loss_kpt: 0.000510 acc_pose: 0.854338 loss: 0.000510 2022/10/27 20:34:07 - mmengine - INFO - Epoch(train) [168][550/586] lr: 5.000000e-04 eta: 1:51:34 time: 0.293651 data_time: 0.029663 memory: 11131 loss_kpt: 0.000507 acc_pose: 0.839321 loss: 0.000507 2022/10/27 20:34:17 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:34:32 - mmengine - INFO - Epoch(train) [169][50/586] lr: 5.000000e-04 eta: 1:51:08 time: 0.296738 data_time: 0.038423 memory: 11131 loss_kpt: 0.000509 acc_pose: 0.902266 loss: 0.000509 2022/10/27 20:34:47 - mmengine - INFO - Epoch(train) [169][100/586] lr: 5.000000e-04 eta: 1:50:55 time: 0.293004 data_time: 0.028241 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.867882 loss: 0.000514 2022/10/27 20:35:01 - mmengine - INFO - Epoch(train) [169][150/586] lr: 5.000000e-04 eta: 1:50:42 time: 0.292900 data_time: 0.028268 memory: 11131 loss_kpt: 0.000520 acc_pose: 0.900766 loss: 0.000520 2022/10/27 20:35:15 - mmengine - INFO - Epoch(train) [169][200/586] lr: 5.000000e-04 eta: 1:50:28 time: 0.284654 data_time: 0.030002 memory: 11131 loss_kpt: 0.000490 acc_pose: 0.858803 loss: 0.000490 2022/10/27 20:35:30 - mmengine - INFO - Epoch(train) [169][250/586] lr: 5.000000e-04 eta: 1:50:15 time: 0.286060 data_time: 0.027051 memory: 11131 loss_kpt: 0.000513 acc_pose: 0.874824 loss: 0.000513 2022/10/27 20:35:44 - mmengine - INFO - Epoch(train) [169][300/586] lr: 5.000000e-04 eta: 1:50:02 time: 0.286917 data_time: 0.026837 memory: 11131 loss_kpt: 0.000517 acc_pose: 0.856296 loss: 0.000517 2022/10/27 20:35:59 - mmengine - INFO - Epoch(train) [169][350/586] lr: 5.000000e-04 eta: 1:49:48 time: 0.289191 data_time: 0.032565 memory: 11131 loss_kpt: 0.000517 acc_pose: 0.892604 loss: 0.000517 2022/10/27 20:36:13 - mmengine - INFO - Epoch(train) [169][400/586] lr: 5.000000e-04 eta: 1:49:35 time: 0.286569 data_time: 0.027528 memory: 11131 loss_kpt: 0.000532 acc_pose: 0.828659 loss: 0.000532 2022/10/27 20:36:27 - mmengine - INFO - Epoch(train) [169][450/586] lr: 5.000000e-04 eta: 1:49:21 time: 0.285870 data_time: 0.028252 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.908875 loss: 0.000514 2022/10/27 20:36:42 - mmengine - INFO - Epoch(train) [169][500/586] lr: 5.000000e-04 eta: 1:49:08 time: 0.291344 data_time: 0.030155 memory: 11131 loss_kpt: 0.000526 acc_pose: 0.843691 loss: 0.000526 2022/10/27 20:36:56 - mmengine - INFO - Epoch(train) [169][550/586] lr: 5.000000e-04 eta: 1:48:55 time: 0.283670 data_time: 0.027709 memory: 11131 loss_kpt: 0.000529 acc_pose: 0.825223 loss: 0.000529 2022/10/27 20:36:57 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:37:07 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:37:22 - mmengine - INFO - Epoch(train) [170][50/586] lr: 5.000000e-04 eta: 1:48:29 time: 0.301107 data_time: 0.035349 memory: 11131 loss_kpt: 0.000513 acc_pose: 0.791512 loss: 0.000513 2022/10/27 20:37:36 - mmengine - INFO - Epoch(train) [170][100/586] lr: 5.000000e-04 eta: 1:48:16 time: 0.288330 data_time: 0.027645 memory: 11131 loss_kpt: 0.000511 acc_pose: 0.770584 loss: 0.000511 2022/10/27 20:37:51 - mmengine - INFO - Epoch(train) [170][150/586] lr: 5.000000e-04 eta: 1:48:03 time: 0.292809 data_time: 0.030595 memory: 11131 loss_kpt: 0.000535 acc_pose: 0.863158 loss: 0.000535 2022/10/27 20:38:05 - mmengine - INFO - Epoch(train) [170][200/586] lr: 5.000000e-04 eta: 1:47:49 time: 0.285748 data_time: 0.029493 memory: 11131 loss_kpt: 0.000520 acc_pose: 0.874569 loss: 0.000520 2022/10/27 20:38:20 - mmengine - INFO - Epoch(train) [170][250/586] lr: 5.000000e-04 eta: 1:47:36 time: 0.291425 data_time: 0.031475 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.877748 loss: 0.000523 2022/10/27 20:38:34 - mmengine - INFO - Epoch(train) [170][300/586] lr: 5.000000e-04 eta: 1:47:22 time: 0.287885 data_time: 0.031408 memory: 11131 loss_kpt: 0.000512 acc_pose: 0.863164 loss: 0.000512 2022/10/27 20:38:48 - mmengine - INFO - Epoch(train) [170][350/586] lr: 5.000000e-04 eta: 1:47:09 time: 0.288808 data_time: 0.028854 memory: 11131 loss_kpt: 0.000532 acc_pose: 0.839627 loss: 0.000532 2022/10/27 20:39:03 - mmengine - INFO - Epoch(train) [170][400/586] lr: 5.000000e-04 eta: 1:46:56 time: 0.286011 data_time: 0.027732 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.896059 loss: 0.000519 2022/10/27 20:39:17 - mmengine - INFO - Epoch(train) [170][450/586] lr: 5.000000e-04 eta: 1:46:42 time: 0.287691 data_time: 0.028286 memory: 11131 loss_kpt: 0.000523 acc_pose: 0.905850 loss: 0.000523 2022/10/27 20:39:32 - mmengine - INFO - Epoch(train) [170][500/586] lr: 5.000000e-04 eta: 1:46:29 time: 0.289607 data_time: 0.032731 memory: 11131 loss_kpt: 0.000504 acc_pose: 0.903371 loss: 0.000504 2022/10/27 20:39:46 - mmengine - INFO - Epoch(train) [170][550/586] lr: 5.000000e-04 eta: 1:46:15 time: 0.287158 data_time: 0.029251 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.833791 loss: 0.000514 2022/10/27 20:39:56 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:39:56 - mmengine - INFO - Saving checkpoint at 170 epochs 2022/10/27 20:40:07 - mmengine - INFO - Epoch(val) [170][50/407] eta: 0:00:51 time: 0.143064 data_time: 0.021547 memory: 11131 2022/10/27 20:40:14 - mmengine - INFO - Epoch(val) [170][100/407] eta: 0:00:41 time: 0.134070 data_time: 0.014115 memory: 1836 2022/10/27 20:40:21 - mmengine - INFO - Epoch(val) [170][150/407] eta: 0:00:34 time: 0.135476 data_time: 0.013472 memory: 1836 2022/10/27 20:40:27 - mmengine - INFO - Epoch(val) [170][200/407] eta: 0:00:27 time: 0.133223 data_time: 0.012849 memory: 1836 2022/10/27 20:40:34 - mmengine - INFO - Epoch(val) [170][250/407] eta: 0:00:21 time: 0.138278 data_time: 0.018954 memory: 1836 2022/10/27 20:40:41 - mmengine - INFO - Epoch(val) [170][300/407] eta: 0:00:14 time: 0.135315 data_time: 0.015267 memory: 1836 2022/10/27 20:40:48 - mmengine - INFO - Epoch(val) [170][350/407] eta: 0:00:07 time: 0.136730 data_time: 0.018073 memory: 1836 2022/10/27 20:40:54 - mmengine - INFO - Epoch(val) [170][400/407] eta: 0:00:00 time: 0.128440 data_time: 0.014386 memory: 1836 2022/10/27 20:41:41 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 20:41:58 - mmengine - INFO - Epoch(val) [170][407/407] coco/AP: 0.738869 coco/AP .5: 0.900892 coco/AP .75: 0.805643 coco/AP (M): 0.696994 coco/AP (L): 0.811771 coco/AR: 0.789405 coco/AR .5: 0.937500 coco/AR .75: 0.849339 coco/AR (M): 0.743786 coco/AR (L): 0.855110 2022/10/27 20:42:13 - mmengine - INFO - Epoch(train) [171][50/586] lr: 5.000000e-05 eta: 1:45:50 time: 0.293573 data_time: 0.036593 memory: 11131 loss_kpt: 0.000510 acc_pose: 0.894078 loss: 0.000510 2022/10/27 20:42:28 - mmengine - INFO - Epoch(train) [171][100/586] lr: 5.000000e-05 eta: 1:45:37 time: 0.293508 data_time: 0.030701 memory: 11131 loss_kpt: 0.000519 acc_pose: 0.864716 loss: 0.000519 2022/10/27 20:42:42 - mmengine - INFO - Epoch(train) [171][150/586] lr: 5.000000e-05 eta: 1:45:23 time: 0.292543 data_time: 0.029563 memory: 11131 loss_kpt: 0.000494 acc_pose: 0.872282 loss: 0.000494 2022/10/27 20:42:57 - mmengine - INFO - Epoch(train) [171][200/586] lr: 5.000000e-05 eta: 1:45:10 time: 0.287917 data_time: 0.029377 memory: 11131 loss_kpt: 0.000517 acc_pose: 0.914791 loss: 0.000517 2022/10/27 20:43:11 - mmengine - INFO - Epoch(train) [171][250/586] lr: 5.000000e-05 eta: 1:44:57 time: 0.284440 data_time: 0.031659 memory: 11131 loss_kpt: 0.000511 acc_pose: 0.888173 loss: 0.000511 2022/10/27 20:43:25 - mmengine - INFO - Epoch(train) [171][300/586] lr: 5.000000e-05 eta: 1:44:43 time: 0.284536 data_time: 0.026681 memory: 11131 loss_kpt: 0.000504 acc_pose: 0.839428 loss: 0.000504 2022/10/27 20:43:40 - mmengine - INFO - Epoch(train) [171][350/586] lr: 5.000000e-05 eta: 1:44:30 time: 0.292331 data_time: 0.028375 memory: 11131 loss_kpt: 0.000499 acc_pose: 0.891032 loss: 0.000499 2022/10/27 20:43:49 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:43:54 - mmengine - INFO - Epoch(train) [171][400/586] lr: 5.000000e-05 eta: 1:44:16 time: 0.289591 data_time: 0.027588 memory: 11131 loss_kpt: 0.000483 acc_pose: 0.929112 loss: 0.000483 2022/10/27 20:44:08 - mmengine - INFO - Epoch(train) [171][450/586] lr: 5.000000e-05 eta: 1:44:03 time: 0.284982 data_time: 0.027679 memory: 11131 loss_kpt: 0.000497 acc_pose: 0.898076 loss: 0.000497 2022/10/27 20:44:23 - mmengine - INFO - Epoch(train) [171][500/586] lr: 5.000000e-05 eta: 1:43:50 time: 0.284948 data_time: 0.034217 memory: 11131 loss_kpt: 0.000486 acc_pose: 0.858018 loss: 0.000486 2022/10/27 20:44:37 - mmengine - INFO - Epoch(train) [171][550/586] lr: 5.000000e-05 eta: 1:43:36 time: 0.286798 data_time: 0.026928 memory: 11131 loss_kpt: 0.000490 acc_pose: 0.843602 loss: 0.000490 2022/10/27 20:44:47 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:45:02 - mmengine - INFO - Epoch(train) [172][50/586] lr: 5.000000e-05 eta: 1:43:11 time: 0.298593 data_time: 0.035607 memory: 11131 loss_kpt: 0.000491 acc_pose: 0.928427 loss: 0.000491 2022/10/27 20:45:17 - mmengine - INFO - Epoch(train) [172][100/586] lr: 5.000000e-05 eta: 1:42:58 time: 0.288019 data_time: 0.028543 memory: 11131 loss_kpt: 0.000498 acc_pose: 0.894895 loss: 0.000498 2022/10/27 20:45:31 - mmengine - INFO - Epoch(train) [172][150/586] lr: 5.000000e-05 eta: 1:42:44 time: 0.285527 data_time: 0.028917 memory: 11131 loss_kpt: 0.000498 acc_pose: 0.882487 loss: 0.000498 2022/10/27 20:45:46 - mmengine - INFO - Epoch(train) [172][200/586] lr: 5.000000e-05 eta: 1:42:31 time: 0.287740 data_time: 0.027870 memory: 11131 loss_kpt: 0.000485 acc_pose: 0.931186 loss: 0.000485 2022/10/27 20:46:00 - mmengine - INFO - Epoch(train) [172][250/586] lr: 5.000000e-05 eta: 1:42:17 time: 0.296250 data_time: 0.030918 memory: 11131 loss_kpt: 0.000490 acc_pose: 0.907903 loss: 0.000490 2022/10/27 20:46:15 - mmengine - INFO - Epoch(train) [172][300/586] lr: 5.000000e-05 eta: 1:42:04 time: 0.286343 data_time: 0.026888 memory: 11131 loss_kpt: 0.000486 acc_pose: 0.882689 loss: 0.000486 2022/10/27 20:46:29 - mmengine - INFO - Epoch(train) [172][350/586] lr: 5.000000e-05 eta: 1:41:51 time: 0.286038 data_time: 0.028536 memory: 11131 loss_kpt: 0.000499 acc_pose: 0.865991 loss: 0.000499 2022/10/27 20:46:44 - mmengine - INFO - Epoch(train) [172][400/586] lr: 5.000000e-05 eta: 1:41:37 time: 0.292456 data_time: 0.031349 memory: 11131 loss_kpt: 0.000485 acc_pose: 0.862942 loss: 0.000485 2022/10/27 20:46:58 - mmengine - INFO - Epoch(train) [172][450/586] lr: 5.000000e-05 eta: 1:41:24 time: 0.285607 data_time: 0.027257 memory: 11131 loss_kpt: 0.000502 acc_pose: 0.934674 loss: 0.000502 2022/10/27 20:47:13 - mmengine - INFO - Epoch(train) [172][500/586] lr: 5.000000e-05 eta: 1:41:11 time: 0.294636 data_time: 0.029140 memory: 11131 loss_kpt: 0.000484 acc_pose: 0.922246 loss: 0.000484 2022/10/27 20:47:27 - mmengine - INFO - Epoch(train) [172][550/586] lr: 5.000000e-05 eta: 1:40:57 time: 0.287630 data_time: 0.027000 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.858911 loss: 0.000476 2022/10/27 20:47:37 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:47:52 - mmengine - INFO - Epoch(train) [173][50/586] lr: 5.000000e-05 eta: 1:40:32 time: 0.295226 data_time: 0.036492 memory: 11131 loss_kpt: 0.000485 acc_pose: 0.939944 loss: 0.000485 2022/10/27 20:48:06 - mmengine - INFO - Epoch(train) [173][100/586] lr: 5.000000e-05 eta: 1:40:19 time: 0.289525 data_time: 0.031115 memory: 11131 loss_kpt: 0.000500 acc_pose: 0.885712 loss: 0.000500 2022/10/27 20:48:21 - mmengine - INFO - Epoch(train) [173][150/586] lr: 5.000000e-05 eta: 1:40:05 time: 0.295137 data_time: 0.027640 memory: 11131 loss_kpt: 0.000477 acc_pose: 0.891579 loss: 0.000477 2022/10/27 20:48:36 - mmengine - INFO - Epoch(train) [173][200/586] lr: 5.000000e-05 eta: 1:39:52 time: 0.287244 data_time: 0.031948 memory: 11131 loss_kpt: 0.000493 acc_pose: 0.867885 loss: 0.000493 2022/10/27 20:48:38 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:48:50 - mmengine - INFO - Epoch(train) [173][250/586] lr: 5.000000e-05 eta: 1:39:38 time: 0.284764 data_time: 0.028613 memory: 11131 loss_kpt: 0.000484 acc_pose: 0.899271 loss: 0.000484 2022/10/27 20:49:04 - mmengine - INFO - Epoch(train) [173][300/586] lr: 5.000000e-05 eta: 1:39:25 time: 0.287034 data_time: 0.028884 memory: 11131 loss_kpt: 0.000491 acc_pose: 0.879119 loss: 0.000491 2022/10/27 20:49:19 - mmengine - INFO - Epoch(train) [173][350/586] lr: 5.000000e-05 eta: 1:39:12 time: 0.290871 data_time: 0.027921 memory: 11131 loss_kpt: 0.000514 acc_pose: 0.898084 loss: 0.000514 2022/10/27 20:49:33 - mmengine - INFO - Epoch(train) [173][400/586] lr: 5.000000e-05 eta: 1:38:58 time: 0.291687 data_time: 0.030505 memory: 11131 loss_kpt: 0.000482 acc_pose: 0.869105 loss: 0.000482 2022/10/27 20:49:48 - mmengine - INFO - Epoch(train) [173][450/586] lr: 5.000000e-05 eta: 1:38:45 time: 0.287364 data_time: 0.030022 memory: 11131 loss_kpt: 0.000475 acc_pose: 0.900833 loss: 0.000475 2022/10/27 20:50:02 - mmengine - INFO - Epoch(train) [173][500/586] lr: 5.000000e-05 eta: 1:38:31 time: 0.285197 data_time: 0.029681 memory: 11131 loss_kpt: 0.000503 acc_pose: 0.875362 loss: 0.000503 2022/10/27 20:50:16 - mmengine - INFO - Epoch(train) [173][550/586] lr: 5.000000e-05 eta: 1:38:18 time: 0.287938 data_time: 0.027800 memory: 11131 loss_kpt: 0.000479 acc_pose: 0.874830 loss: 0.000479 2022/10/27 20:50:27 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:50:42 - mmengine - INFO - Epoch(train) [174][50/586] lr: 5.000000e-05 eta: 1:37:53 time: 0.298558 data_time: 0.037225 memory: 11131 loss_kpt: 0.000496 acc_pose: 0.909229 loss: 0.000496 2022/10/27 20:50:56 - mmengine - INFO - Epoch(train) [174][100/586] lr: 5.000000e-05 eta: 1:37:39 time: 0.285336 data_time: 0.027662 memory: 11131 loss_kpt: 0.000487 acc_pose: 0.875689 loss: 0.000487 2022/10/27 20:51:10 - mmengine - INFO - Epoch(train) [174][150/586] lr: 5.000000e-05 eta: 1:37:26 time: 0.287659 data_time: 0.032456 memory: 11131 loss_kpt: 0.000475 acc_pose: 0.814563 loss: 0.000475 2022/10/27 20:51:25 - mmengine - INFO - Epoch(train) [174][200/586] lr: 5.000000e-05 eta: 1:37:13 time: 0.290030 data_time: 0.029958 memory: 11131 loss_kpt: 0.000482 acc_pose: 0.824269 loss: 0.000482 2022/10/27 20:51:39 - mmengine - INFO - Epoch(train) [174][250/586] lr: 5.000000e-05 eta: 1:36:59 time: 0.289811 data_time: 0.027010 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.866867 loss: 0.000471 2022/10/27 20:51:54 - mmengine - INFO - Epoch(train) [174][300/586] lr: 5.000000e-05 eta: 1:36:46 time: 0.292969 data_time: 0.028205 memory: 11131 loss_kpt: 0.000477 acc_pose: 0.851480 loss: 0.000477 2022/10/27 20:52:08 - mmengine - INFO - Epoch(train) [174][350/586] lr: 5.000000e-05 eta: 1:36:32 time: 0.283053 data_time: 0.027529 memory: 11131 loss_kpt: 0.000480 acc_pose: 0.918146 loss: 0.000480 2022/10/27 20:52:23 - mmengine - INFO - Epoch(train) [174][400/586] lr: 5.000000e-05 eta: 1:36:19 time: 0.291134 data_time: 0.028580 memory: 11131 loss_kpt: 0.000483 acc_pose: 0.912706 loss: 0.000483 2022/10/27 20:52:37 - mmengine - INFO - Epoch(train) [174][450/586] lr: 5.000000e-05 eta: 1:36:06 time: 0.287027 data_time: 0.031234 memory: 11131 loss_kpt: 0.000483 acc_pose: 0.882572 loss: 0.000483 2022/10/27 20:52:52 - mmengine - INFO - Epoch(train) [174][500/586] lr: 5.000000e-05 eta: 1:35:52 time: 0.291536 data_time: 0.027366 memory: 11131 loss_kpt: 0.000483 acc_pose: 0.931049 loss: 0.000483 2022/10/27 20:53:06 - mmengine - INFO - Epoch(train) [174][550/586] lr: 5.000000e-05 eta: 1:35:39 time: 0.288827 data_time: 0.027617 memory: 11131 loss_kpt: 0.000489 acc_pose: 0.873247 loss: 0.000489 2022/10/27 20:53:16 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:53:27 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:53:31 - mmengine - INFO - Epoch(train) [175][50/586] lr: 5.000000e-05 eta: 1:35:14 time: 0.297919 data_time: 0.036788 memory: 11131 loss_kpt: 0.000482 acc_pose: 0.867410 loss: 0.000482 2022/10/27 20:53:45 - mmengine - INFO - Epoch(train) [175][100/586] lr: 5.000000e-05 eta: 1:35:00 time: 0.288056 data_time: 0.030266 memory: 11131 loss_kpt: 0.000502 acc_pose: 0.922418 loss: 0.000502 2022/10/27 20:54:00 - mmengine - INFO - Epoch(train) [175][150/586] lr: 5.000000e-05 eta: 1:34:47 time: 0.289450 data_time: 0.027908 memory: 11131 loss_kpt: 0.000477 acc_pose: 0.919400 loss: 0.000477 2022/10/27 20:54:14 - mmengine - INFO - Epoch(train) [175][200/586] lr: 5.000000e-05 eta: 1:34:34 time: 0.294210 data_time: 0.030411 memory: 11131 loss_kpt: 0.000487 acc_pose: 0.864658 loss: 0.000487 2022/10/27 20:54:29 - mmengine - INFO - Epoch(train) [175][250/586] lr: 5.000000e-05 eta: 1:34:20 time: 0.286332 data_time: 0.035586 memory: 11131 loss_kpt: 0.000482 acc_pose: 0.870925 loss: 0.000482 2022/10/27 20:54:43 - mmengine - INFO - Epoch(train) [175][300/586] lr: 5.000000e-05 eta: 1:34:07 time: 0.285842 data_time: 0.030811 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.865671 loss: 0.000471 2022/10/27 20:54:58 - mmengine - INFO - Epoch(train) [175][350/586] lr: 5.000000e-05 eta: 1:33:53 time: 0.292874 data_time: 0.027187 memory: 11131 loss_kpt: 0.000480 acc_pose: 0.920605 loss: 0.000480 2022/10/27 20:55:12 - mmengine - INFO - Epoch(train) [175][400/586] lr: 5.000000e-05 eta: 1:33:40 time: 0.292215 data_time: 0.027629 memory: 11131 loss_kpt: 0.000485 acc_pose: 0.887900 loss: 0.000485 2022/10/27 20:55:27 - mmengine - INFO - Epoch(train) [175][450/586] lr: 5.000000e-05 eta: 1:33:27 time: 0.286749 data_time: 0.027616 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.876052 loss: 0.000459 2022/10/27 20:55:41 - mmengine - INFO - Epoch(train) [175][500/586] lr: 5.000000e-05 eta: 1:33:13 time: 0.285250 data_time: 0.026853 memory: 11131 loss_kpt: 0.000485 acc_pose: 0.916297 loss: 0.000485 2022/10/27 20:55:55 - mmengine - INFO - Epoch(train) [175][550/586] lr: 5.000000e-05 eta: 1:33:00 time: 0.289881 data_time: 0.031037 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.896129 loss: 0.000464 2022/10/27 20:56:06 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:56:21 - mmengine - INFO - Epoch(train) [176][50/586] lr: 5.000000e-05 eta: 1:32:35 time: 0.303034 data_time: 0.036731 memory: 11131 loss_kpt: 0.000481 acc_pose: 0.887480 loss: 0.000481 2022/10/27 20:56:35 - mmengine - INFO - Epoch(train) [176][100/586] lr: 5.000000e-05 eta: 1:32:21 time: 0.284566 data_time: 0.028000 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.909245 loss: 0.000468 2022/10/27 20:56:49 - mmengine - INFO - Epoch(train) [176][150/586] lr: 5.000000e-05 eta: 1:32:08 time: 0.287525 data_time: 0.028143 memory: 11131 loss_kpt: 0.000472 acc_pose: 0.885653 loss: 0.000472 2022/10/27 20:57:04 - mmengine - INFO - Epoch(train) [176][200/586] lr: 5.000000e-05 eta: 1:31:54 time: 0.288707 data_time: 0.027990 memory: 11131 loss_kpt: 0.000497 acc_pose: 0.794865 loss: 0.000497 2022/10/27 20:57:18 - mmengine - INFO - Epoch(train) [176][250/586] lr: 5.000000e-05 eta: 1:31:41 time: 0.289647 data_time: 0.027185 memory: 11131 loss_kpt: 0.000481 acc_pose: 0.956519 loss: 0.000481 2022/10/27 20:57:33 - mmengine - INFO - Epoch(train) [176][300/586] lr: 5.000000e-05 eta: 1:31:28 time: 0.291194 data_time: 0.027293 memory: 11131 loss_kpt: 0.000478 acc_pose: 0.894276 loss: 0.000478 2022/10/27 20:57:47 - mmengine - INFO - Epoch(train) [176][350/586] lr: 5.000000e-05 eta: 1:31:14 time: 0.284054 data_time: 0.029045 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.844589 loss: 0.000462 2022/10/27 20:58:02 - mmengine - INFO - Epoch(train) [176][400/586] lr: 5.000000e-05 eta: 1:31:01 time: 0.288246 data_time: 0.034868 memory: 11131 loss_kpt: 0.000490 acc_pose: 0.903608 loss: 0.000490 2022/10/27 20:58:16 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:58:16 - mmengine - INFO - Epoch(train) [176][450/586] lr: 5.000000e-05 eta: 1:30:47 time: 0.287130 data_time: 0.029192 memory: 11131 loss_kpt: 0.000485 acc_pose: 0.875071 loss: 0.000485 2022/10/27 20:58:30 - mmengine - INFO - Epoch(train) [176][500/586] lr: 5.000000e-05 eta: 1:30:34 time: 0.289138 data_time: 0.027931 memory: 11131 loss_kpt: 0.000477 acc_pose: 0.842854 loss: 0.000477 2022/10/27 20:58:45 - mmengine - INFO - Epoch(train) [176][550/586] lr: 5.000000e-05 eta: 1:30:21 time: 0.294145 data_time: 0.027007 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.896943 loss: 0.000466 2022/10/27 20:58:55 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 20:59:10 - mmengine - INFO - Epoch(train) [177][50/586] lr: 5.000000e-05 eta: 1:29:56 time: 0.295311 data_time: 0.042450 memory: 11131 loss_kpt: 0.000486 acc_pose: 0.833341 loss: 0.000486 2022/10/27 20:59:24 - mmengine - INFO - Epoch(train) [177][100/586] lr: 5.000000e-05 eta: 1:29:42 time: 0.288672 data_time: 0.028197 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.878838 loss: 0.000471 2022/10/27 20:59:39 - mmengine - INFO - Epoch(train) [177][150/586] lr: 5.000000e-05 eta: 1:29:29 time: 0.292020 data_time: 0.027911 memory: 11131 loss_kpt: 0.000480 acc_pose: 0.876480 loss: 0.000480 2022/10/27 20:59:53 - mmengine - INFO - Epoch(train) [177][200/586] lr: 5.000000e-05 eta: 1:29:15 time: 0.291547 data_time: 0.029714 memory: 11131 loss_kpt: 0.000490 acc_pose: 0.873086 loss: 0.000490 2022/10/27 21:00:08 - mmengine - INFO - Epoch(train) [177][250/586] lr: 5.000000e-05 eta: 1:29:02 time: 0.284901 data_time: 0.028129 memory: 11131 loss_kpt: 0.000481 acc_pose: 0.863837 loss: 0.000481 2022/10/27 21:00:22 - mmengine - INFO - Epoch(train) [177][300/586] lr: 5.000000e-05 eta: 1:28:49 time: 0.287428 data_time: 0.029477 memory: 11131 loss_kpt: 0.000455 acc_pose: 0.917014 loss: 0.000455 2022/10/27 21:00:37 - mmengine - INFO - Epoch(train) [177][350/586] lr: 5.000000e-05 eta: 1:28:35 time: 0.291803 data_time: 0.033268 memory: 11131 loss_kpt: 0.000473 acc_pose: 0.908305 loss: 0.000473 2022/10/27 21:00:51 - mmengine - INFO - Epoch(train) [177][400/586] lr: 5.000000e-05 eta: 1:28:22 time: 0.292491 data_time: 0.030191 memory: 11131 loss_kpt: 0.000472 acc_pose: 0.911776 loss: 0.000472 2022/10/27 21:01:06 - mmengine - INFO - Epoch(train) [177][450/586] lr: 5.000000e-05 eta: 1:28:08 time: 0.289132 data_time: 0.031788 memory: 11131 loss_kpt: 0.000467 acc_pose: 0.932069 loss: 0.000467 2022/10/27 21:01:20 - mmengine - INFO - Epoch(train) [177][500/586] lr: 5.000000e-05 eta: 1:27:55 time: 0.288701 data_time: 0.033152 memory: 11131 loss_kpt: 0.000488 acc_pose: 0.882774 loss: 0.000488 2022/10/27 21:01:34 - mmengine - INFO - Epoch(train) [177][550/586] lr: 5.000000e-05 eta: 1:27:42 time: 0.284753 data_time: 0.029055 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.869840 loss: 0.000469 2022/10/27 21:01:45 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:02:00 - mmengine - INFO - Epoch(train) [178][50/586] lr: 5.000000e-05 eta: 1:27:17 time: 0.300522 data_time: 0.040669 memory: 11131 loss_kpt: 0.000467 acc_pose: 0.926369 loss: 0.000467 2022/10/27 21:02:14 - mmengine - INFO - Epoch(train) [178][100/586] lr: 5.000000e-05 eta: 1:27:03 time: 0.284630 data_time: 0.029775 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.903878 loss: 0.000464 2022/10/27 21:02:29 - mmengine - INFO - Epoch(train) [178][150/586] lr: 5.000000e-05 eta: 1:26:50 time: 0.288463 data_time: 0.031188 memory: 11131 loss_kpt: 0.000486 acc_pose: 0.884050 loss: 0.000486 2022/10/27 21:02:43 - mmengine - INFO - Epoch(train) [178][200/586] lr: 5.000000e-05 eta: 1:26:36 time: 0.286567 data_time: 0.029878 memory: 11131 loss_kpt: 0.000490 acc_pose: 0.909095 loss: 0.000490 2022/10/27 21:02:58 - mmengine - INFO - Epoch(train) [178][250/586] lr: 5.000000e-05 eta: 1:26:23 time: 0.294214 data_time: 0.032284 memory: 11131 loss_kpt: 0.000472 acc_pose: 0.909165 loss: 0.000472 2022/10/27 21:03:06 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:03:12 - mmengine - INFO - Epoch(train) [178][300/586] lr: 5.000000e-05 eta: 1:26:10 time: 0.291845 data_time: 0.027775 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.850441 loss: 0.000462 2022/10/27 21:03:27 - mmengine - INFO - Epoch(train) [178][350/586] lr: 5.000000e-05 eta: 1:25:56 time: 0.285843 data_time: 0.027822 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.882840 loss: 0.000463 2022/10/27 21:03:41 - mmengine - INFO - Epoch(train) [178][400/586] lr: 5.000000e-05 eta: 1:25:43 time: 0.289504 data_time: 0.031851 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.874620 loss: 0.000466 2022/10/27 21:03:55 - mmengine - INFO - Epoch(train) [178][450/586] lr: 5.000000e-05 eta: 1:25:29 time: 0.285118 data_time: 0.029142 memory: 11131 loss_kpt: 0.000498 acc_pose: 0.873857 loss: 0.000498 2022/10/27 21:04:10 - mmengine - INFO - Epoch(train) [178][500/586] lr: 5.000000e-05 eta: 1:25:16 time: 0.289291 data_time: 0.029513 memory: 11131 loss_kpt: 0.000489 acc_pose: 0.900653 loss: 0.000489 2022/10/27 21:04:24 - mmengine - INFO - Epoch(train) [178][550/586] lr: 5.000000e-05 eta: 1:25:02 time: 0.292215 data_time: 0.027850 memory: 11131 loss_kpt: 0.000474 acc_pose: 0.880431 loss: 0.000474 2022/10/27 21:04:34 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:04:49 - mmengine - INFO - Epoch(train) [179][50/586] lr: 5.000000e-05 eta: 1:24:38 time: 0.298065 data_time: 0.038470 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.847081 loss: 0.000466 2022/10/27 21:05:04 - mmengine - INFO - Epoch(train) [179][100/586] lr: 5.000000e-05 eta: 1:24:24 time: 0.285756 data_time: 0.028778 memory: 11131 loss_kpt: 0.000481 acc_pose: 0.887703 loss: 0.000481 2022/10/27 21:05:18 - mmengine - INFO - Epoch(train) [179][150/586] lr: 5.000000e-05 eta: 1:24:11 time: 0.288247 data_time: 0.027156 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.819855 loss: 0.000471 2022/10/27 21:05:33 - mmengine - INFO - Epoch(train) [179][200/586] lr: 5.000000e-05 eta: 1:23:57 time: 0.293101 data_time: 0.029092 memory: 11131 loss_kpt: 0.000477 acc_pose: 0.892348 loss: 0.000477 2022/10/27 21:05:47 - mmengine - INFO - Epoch(train) [179][250/586] lr: 5.000000e-05 eta: 1:23:44 time: 0.286513 data_time: 0.029600 memory: 11131 loss_kpt: 0.000483 acc_pose: 0.870793 loss: 0.000483 2022/10/27 21:06:01 - mmengine - INFO - Epoch(train) [179][300/586] lr: 5.000000e-05 eta: 1:23:30 time: 0.285136 data_time: 0.029308 memory: 11131 loss_kpt: 0.000479 acc_pose: 0.950450 loss: 0.000479 2022/10/27 21:06:16 - mmengine - INFO - Epoch(train) [179][350/586] lr: 5.000000e-05 eta: 1:23:17 time: 0.289510 data_time: 0.030306 memory: 11131 loss_kpt: 0.000486 acc_pose: 0.857466 loss: 0.000486 2022/10/27 21:06:30 - mmengine - INFO - Epoch(train) [179][400/586] lr: 5.000000e-05 eta: 1:23:03 time: 0.283222 data_time: 0.026706 memory: 11131 loss_kpt: 0.000486 acc_pose: 0.872648 loss: 0.000486 2022/10/27 21:06:45 - mmengine - INFO - Epoch(train) [179][450/586] lr: 5.000000e-05 eta: 1:22:50 time: 0.290152 data_time: 0.028464 memory: 11131 loss_kpt: 0.000490 acc_pose: 0.893371 loss: 0.000490 2022/10/27 21:06:59 - mmengine - INFO - Epoch(train) [179][500/586] lr: 5.000000e-05 eta: 1:22:37 time: 0.288797 data_time: 0.031272 memory: 11131 loss_kpt: 0.000491 acc_pose: 0.893207 loss: 0.000491 2022/10/27 21:07:13 - mmengine - INFO - Epoch(train) [179][550/586] lr: 5.000000e-05 eta: 1:22:23 time: 0.287553 data_time: 0.030750 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.829913 loss: 0.000463 2022/10/27 21:07:24 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:07:38 - mmengine - INFO - Epoch(train) [180][50/586] lr: 5.000000e-05 eta: 1:21:58 time: 0.295949 data_time: 0.037166 memory: 11131 loss_kpt: 0.000456 acc_pose: 0.866817 loss: 0.000456 2022/10/27 21:07:53 - mmengine - INFO - Epoch(train) [180][100/586] lr: 5.000000e-05 eta: 1:21:45 time: 0.294085 data_time: 0.032790 memory: 11131 loss_kpt: 0.000484 acc_pose: 0.905709 loss: 0.000484 2022/10/27 21:07:55 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:08:07 - mmengine - INFO - Epoch(train) [180][150/586] lr: 5.000000e-05 eta: 1:21:32 time: 0.286165 data_time: 0.035111 memory: 11131 loss_kpt: 0.000488 acc_pose: 0.839184 loss: 0.000488 2022/10/27 21:08:22 - mmengine - INFO - Epoch(train) [180][200/586] lr: 5.000000e-05 eta: 1:21:18 time: 0.288226 data_time: 0.029114 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.847275 loss: 0.000463 2022/10/27 21:08:36 - mmengine - INFO - Epoch(train) [180][250/586] lr: 5.000000e-05 eta: 1:21:05 time: 0.288959 data_time: 0.033149 memory: 11131 loss_kpt: 0.000467 acc_pose: 0.871847 loss: 0.000467 2022/10/27 21:08:51 - mmengine - INFO - Epoch(train) [180][300/586] lr: 5.000000e-05 eta: 1:20:51 time: 0.291524 data_time: 0.028405 memory: 11131 loss_kpt: 0.000454 acc_pose: 0.906452 loss: 0.000454 2022/10/27 21:09:06 - mmengine - INFO - Epoch(train) [180][350/586] lr: 5.000000e-05 eta: 1:20:38 time: 0.292761 data_time: 0.036972 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.904165 loss: 0.000471 2022/10/27 21:09:20 - mmengine - INFO - Epoch(train) [180][400/586] lr: 5.000000e-05 eta: 1:20:24 time: 0.282645 data_time: 0.029300 memory: 11131 loss_kpt: 0.000472 acc_pose: 0.919015 loss: 0.000472 2022/10/27 21:09:34 - mmengine - INFO - Epoch(train) [180][450/586] lr: 5.000000e-05 eta: 1:20:11 time: 0.289701 data_time: 0.029801 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.892867 loss: 0.000458 2022/10/27 21:09:48 - mmengine - INFO - Epoch(train) [180][500/586] lr: 5.000000e-05 eta: 1:19:57 time: 0.285070 data_time: 0.029295 memory: 11131 loss_kpt: 0.000484 acc_pose: 0.879621 loss: 0.000484 2022/10/27 21:10:03 - mmengine - INFO - Epoch(train) [180][550/586] lr: 5.000000e-05 eta: 1:19:44 time: 0.296170 data_time: 0.027925 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.855291 loss: 0.000466 2022/10/27 21:10:13 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:10:13 - mmengine - INFO - Saving checkpoint at 180 epochs 2022/10/27 21:10:24 - mmengine - INFO - Epoch(val) [180][50/407] eta: 0:00:51 time: 0.142948 data_time: 0.023446 memory: 11131 2022/10/27 21:10:31 - mmengine - INFO - Epoch(val) [180][100/407] eta: 0:00:42 time: 0.138755 data_time: 0.019693 memory: 1836 2022/10/27 21:10:38 - mmengine - INFO - Epoch(val) [180][150/407] eta: 0:00:35 time: 0.139880 data_time: 0.016023 memory: 1836 2022/10/27 21:10:45 - mmengine - INFO - Epoch(val) [180][200/407] eta: 0:00:27 time: 0.131522 data_time: 0.012989 memory: 1836 2022/10/27 21:10:52 - mmengine - INFO - Epoch(val) [180][250/407] eta: 0:00:23 time: 0.150520 data_time: 0.030750 memory: 1836 2022/10/27 21:10:59 - mmengine - INFO - Epoch(val) [180][300/407] eta: 0:00:15 time: 0.140925 data_time: 0.021034 memory: 1836 2022/10/27 21:11:07 - mmengine - INFO - Epoch(val) [180][350/407] eta: 0:00:08 time: 0.147418 data_time: 0.027084 memory: 1836 2022/10/27 21:11:13 - mmengine - INFO - Epoch(val) [180][400/407] eta: 0:00:00 time: 0.128174 data_time: 0.012873 memory: 1836 2022/10/27 21:12:00 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 21:12:17 - mmengine - INFO - Epoch(val) [180][407/407] coco/AP: 0.746906 coco/AP .5: 0.904823 coco/AP .75: 0.814898 coco/AP (M): 0.706074 coco/AP (L): 0.818767 coco/AR: 0.797229 coco/AR .5: 0.940334 coco/AR .75: 0.859099 coco/AR (M): 0.751243 coco/AR (L): 0.864326 2022/10/27 21:12:17 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_120.pth is removed 2022/10/27 21:12:19 - mmengine - INFO - The best checkpoint with 0.7469 coco/AP at 180 epoch is saved to best_coco/AP_epoch_180.pth. 2022/10/27 21:12:34 - mmengine - INFO - Epoch(train) [181][50/586] lr: 5.000000e-05 eta: 1:19:19 time: 0.291210 data_time: 0.035171 memory: 11131 loss_kpt: 0.000487 acc_pose: 0.865335 loss: 0.000487 2022/10/27 21:12:48 - mmengine - INFO - Epoch(train) [181][100/586] lr: 5.000000e-05 eta: 1:19:06 time: 0.287371 data_time: 0.030073 memory: 11131 loss_kpt: 0.000479 acc_pose: 0.899651 loss: 0.000479 2022/10/27 21:13:03 - mmengine - INFO - Epoch(train) [181][150/586] lr: 5.000000e-05 eta: 1:18:52 time: 0.289608 data_time: 0.028327 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.924844 loss: 0.000470 2022/10/27 21:13:18 - mmengine - INFO - Epoch(train) [181][200/586] lr: 5.000000e-05 eta: 1:18:39 time: 0.296346 data_time: 0.027382 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.874215 loss: 0.000468 2022/10/27 21:13:32 - mmengine - INFO - Epoch(train) [181][250/586] lr: 5.000000e-05 eta: 1:18:26 time: 0.288217 data_time: 0.036964 memory: 11131 loss_kpt: 0.000454 acc_pose: 0.879666 loss: 0.000454 2022/10/27 21:13:46 - mmengine - INFO - Epoch(train) [181][300/586] lr: 5.000000e-05 eta: 1:18:12 time: 0.286745 data_time: 0.031557 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.836012 loss: 0.000469 2022/10/27 21:14:01 - mmengine - INFO - Epoch(train) [181][350/586] lr: 5.000000e-05 eta: 1:17:59 time: 0.291835 data_time: 0.027763 memory: 11131 loss_kpt: 0.000467 acc_pose: 0.911808 loss: 0.000467 2022/10/27 21:14:15 - mmengine - INFO - Epoch(train) [181][400/586] lr: 5.000000e-05 eta: 1:17:45 time: 0.285984 data_time: 0.027215 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.861017 loss: 0.000471 2022/10/27 21:14:30 - mmengine - INFO - Epoch(train) [181][450/586] lr: 5.000000e-05 eta: 1:17:32 time: 0.289269 data_time: 0.028890 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.909789 loss: 0.000470 2022/10/27 21:14:44 - mmengine - INFO - Epoch(train) [181][500/586] lr: 5.000000e-05 eta: 1:17:18 time: 0.285744 data_time: 0.029257 memory: 11131 loss_kpt: 0.000487 acc_pose: 0.882487 loss: 0.000487 2022/10/27 21:14:50 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:14:58 - mmengine - INFO - Epoch(train) [181][550/586] lr: 5.000000e-05 eta: 1:17:05 time: 0.289382 data_time: 0.028581 memory: 11131 loss_kpt: 0.000485 acc_pose: 0.918675 loss: 0.000485 2022/10/27 21:15:09 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:15:24 - mmengine - INFO - Epoch(train) [182][50/586] lr: 5.000000e-05 eta: 1:16:40 time: 0.300233 data_time: 0.037269 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.952133 loss: 0.000470 2022/10/27 21:15:38 - mmengine - INFO - Epoch(train) [182][100/586] lr: 5.000000e-05 eta: 1:16:27 time: 0.286270 data_time: 0.029256 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.884482 loss: 0.000459 2022/10/27 21:15:52 - mmengine - INFO - Epoch(train) [182][150/586] lr: 5.000000e-05 eta: 1:16:13 time: 0.287662 data_time: 0.033287 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.812554 loss: 0.000459 2022/10/27 21:16:07 - mmengine - INFO - Epoch(train) [182][200/586] lr: 5.000000e-05 eta: 1:16:00 time: 0.290241 data_time: 0.029904 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.882562 loss: 0.000476 2022/10/27 21:16:21 - mmengine - INFO - Epoch(train) [182][250/586] lr: 5.000000e-05 eta: 1:15:46 time: 0.283633 data_time: 0.028398 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.877135 loss: 0.000476 2022/10/27 21:16:35 - mmengine - INFO - Epoch(train) [182][300/586] lr: 5.000000e-05 eta: 1:15:33 time: 0.287850 data_time: 0.028743 memory: 11131 loss_kpt: 0.000472 acc_pose: 0.865385 loss: 0.000472 2022/10/27 21:16:50 - mmengine - INFO - Epoch(train) [182][350/586] lr: 5.000000e-05 eta: 1:15:20 time: 0.288925 data_time: 0.027527 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.902722 loss: 0.000469 2022/10/27 21:17:04 - mmengine - INFO - Epoch(train) [182][400/586] lr: 5.000000e-05 eta: 1:15:06 time: 0.288462 data_time: 0.030929 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.849265 loss: 0.000468 2022/10/27 21:17:19 - mmengine - INFO - Epoch(train) [182][450/586] lr: 5.000000e-05 eta: 1:14:53 time: 0.286779 data_time: 0.027554 memory: 11131 loss_kpt: 0.000485 acc_pose: 0.842013 loss: 0.000485 2022/10/27 21:17:33 - mmengine - INFO - Epoch(train) [182][500/586] lr: 5.000000e-05 eta: 1:14:39 time: 0.289174 data_time: 0.031486 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.831851 loss: 0.000469 2022/10/27 21:17:48 - mmengine - INFO - Epoch(train) [182][550/586] lr: 5.000000e-05 eta: 1:14:26 time: 0.291760 data_time: 0.028451 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.862730 loss: 0.000461 2022/10/27 21:17:58 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:18:13 - mmengine - INFO - Epoch(train) [183][50/586] lr: 5.000000e-05 eta: 1:14:01 time: 0.298684 data_time: 0.045836 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.930366 loss: 0.000469 2022/10/27 21:18:27 - mmengine - INFO - Epoch(train) [183][100/586] lr: 5.000000e-05 eta: 1:13:48 time: 0.289426 data_time: 0.028437 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.904428 loss: 0.000464 2022/10/27 21:18:42 - mmengine - INFO - Epoch(train) [183][150/586] lr: 5.000000e-05 eta: 1:13:34 time: 0.288255 data_time: 0.028146 memory: 11131 loss_kpt: 0.000475 acc_pose: 0.955583 loss: 0.000475 2022/10/27 21:18:56 - mmengine - INFO - Epoch(train) [183][200/586] lr: 5.000000e-05 eta: 1:13:21 time: 0.291002 data_time: 0.029598 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.866003 loss: 0.000459 2022/10/27 21:19:10 - mmengine - INFO - Epoch(train) [183][250/586] lr: 5.000000e-05 eta: 1:13:07 time: 0.284891 data_time: 0.032231 memory: 11131 loss_kpt: 0.000484 acc_pose: 0.903606 loss: 0.000484 2022/10/27 21:19:25 - mmengine - INFO - Epoch(train) [183][300/586] lr: 5.000000e-05 eta: 1:12:54 time: 0.286642 data_time: 0.029281 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.840546 loss: 0.000468 2022/10/27 21:19:39 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:19:39 - mmengine - INFO - Epoch(train) [183][350/586] lr: 5.000000e-05 eta: 1:12:40 time: 0.289238 data_time: 0.028627 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.902565 loss: 0.000469 2022/10/27 21:19:54 - mmengine - INFO - Epoch(train) [183][400/586] lr: 5.000000e-05 eta: 1:12:27 time: 0.289145 data_time: 0.029053 memory: 11131 loss_kpt: 0.000479 acc_pose: 0.891978 loss: 0.000479 2022/10/27 21:20:08 - mmengine - INFO - Epoch(train) [183][450/586] lr: 5.000000e-05 eta: 1:12:14 time: 0.291293 data_time: 0.030844 memory: 11131 loss_kpt: 0.000496 acc_pose: 0.917424 loss: 0.000496 2022/10/27 21:20:23 - mmengine - INFO - Epoch(train) [183][500/586] lr: 5.000000e-05 eta: 1:12:00 time: 0.285160 data_time: 0.028617 memory: 11131 loss_kpt: 0.000478 acc_pose: 0.903774 loss: 0.000478 2022/10/27 21:20:37 - mmengine - INFO - Epoch(train) [183][550/586] lr: 5.000000e-05 eta: 1:11:47 time: 0.285123 data_time: 0.028218 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.906313 loss: 0.000458 2022/10/27 21:20:47 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:21:02 - mmengine - INFO - Epoch(train) [184][50/586] lr: 5.000000e-05 eta: 1:11:22 time: 0.299053 data_time: 0.040089 memory: 11131 loss_kpt: 0.000472 acc_pose: 0.926708 loss: 0.000472 2022/10/27 21:21:17 - mmengine - INFO - Epoch(train) [184][100/586] lr: 5.000000e-05 eta: 1:11:09 time: 0.293664 data_time: 0.029804 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.862596 loss: 0.000466 2022/10/27 21:21:31 - mmengine - INFO - Epoch(train) [184][150/586] lr: 5.000000e-05 eta: 1:10:55 time: 0.287131 data_time: 0.031739 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.899773 loss: 0.000471 2022/10/27 21:21:45 - mmengine - INFO - Epoch(train) [184][200/586] lr: 5.000000e-05 eta: 1:10:42 time: 0.287133 data_time: 0.026819 memory: 11131 loss_kpt: 0.000477 acc_pose: 0.923551 loss: 0.000477 2022/10/27 21:22:00 - mmengine - INFO - Epoch(train) [184][250/586] lr: 5.000000e-05 eta: 1:10:28 time: 0.289762 data_time: 0.030456 memory: 11131 loss_kpt: 0.000479 acc_pose: 0.874676 loss: 0.000479 2022/10/27 21:22:15 - mmengine - INFO - Epoch(train) [184][300/586] lr: 5.000000e-05 eta: 1:10:15 time: 0.291358 data_time: 0.030528 memory: 11131 loss_kpt: 0.000478 acc_pose: 0.895012 loss: 0.000478 2022/10/27 21:22:29 - mmengine - INFO - Epoch(train) [184][350/586] lr: 5.000000e-05 eta: 1:10:01 time: 0.288510 data_time: 0.027775 memory: 11131 loss_kpt: 0.000482 acc_pose: 0.903051 loss: 0.000482 2022/10/27 21:22:43 - mmengine - INFO - Epoch(train) [184][400/586] lr: 5.000000e-05 eta: 1:09:48 time: 0.288384 data_time: 0.028319 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.887777 loss: 0.000463 2022/10/27 21:22:58 - mmengine - INFO - Epoch(train) [184][450/586] lr: 5.000000e-05 eta: 1:09:34 time: 0.291603 data_time: 0.031769 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.868207 loss: 0.000459 2022/10/27 21:23:12 - mmengine - INFO - Epoch(train) [184][500/586] lr: 5.000000e-05 eta: 1:09:21 time: 0.288317 data_time: 0.029759 memory: 11131 loss_kpt: 0.000467 acc_pose: 0.865278 loss: 0.000467 2022/10/27 21:23:27 - mmengine - INFO - Epoch(train) [184][550/586] lr: 5.000000e-05 eta: 1:09:07 time: 0.289703 data_time: 0.031017 memory: 11131 loss_kpt: 0.000473 acc_pose: 0.903198 loss: 0.000473 2022/10/27 21:23:37 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:23:52 - mmengine - INFO - Epoch(train) [185][50/586] lr: 5.000000e-05 eta: 1:08:43 time: 0.297318 data_time: 0.038270 memory: 11131 loss_kpt: 0.000449 acc_pose: 0.895149 loss: 0.000449 2022/10/27 21:24:07 - mmengine - INFO - Epoch(train) [185][100/586] lr: 5.000000e-05 eta: 1:08:29 time: 0.288654 data_time: 0.029402 memory: 11131 loss_kpt: 0.000472 acc_pose: 0.873201 loss: 0.000472 2022/10/27 21:24:21 - mmengine - INFO - Epoch(train) [185][150/586] lr: 5.000000e-05 eta: 1:08:16 time: 0.290406 data_time: 0.030089 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.879666 loss: 0.000470 2022/10/27 21:24:29 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:24:36 - mmengine - INFO - Epoch(train) [185][200/586] lr: 5.000000e-05 eta: 1:08:03 time: 0.295604 data_time: 0.032474 memory: 11131 loss_kpt: 0.000456 acc_pose: 0.849557 loss: 0.000456 2022/10/27 21:24:50 - mmengine - INFO - Epoch(train) [185][250/586] lr: 5.000000e-05 eta: 1:07:49 time: 0.285136 data_time: 0.028294 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.913534 loss: 0.000471 2022/10/27 21:25:04 - mmengine - INFO - Epoch(train) [185][300/586] lr: 5.000000e-05 eta: 1:07:36 time: 0.284774 data_time: 0.028908 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.917823 loss: 0.000476 2022/10/27 21:25:19 - mmengine - INFO - Epoch(train) [185][350/586] lr: 5.000000e-05 eta: 1:07:22 time: 0.291634 data_time: 0.031335 memory: 11131 loss_kpt: 0.000452 acc_pose: 0.888691 loss: 0.000452 2022/10/27 21:25:33 - mmengine - INFO - Epoch(train) [185][400/586] lr: 5.000000e-05 eta: 1:07:09 time: 0.288772 data_time: 0.033635 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.883319 loss: 0.000466 2022/10/27 21:25:48 - mmengine - INFO - Epoch(train) [185][450/586] lr: 5.000000e-05 eta: 1:06:55 time: 0.291687 data_time: 0.030569 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.904660 loss: 0.000462 2022/10/27 21:26:02 - mmengine - INFO - Epoch(train) [185][500/586] lr: 5.000000e-05 eta: 1:06:42 time: 0.284962 data_time: 0.027147 memory: 11131 loss_kpt: 0.000481 acc_pose: 0.864219 loss: 0.000481 2022/10/27 21:26:17 - mmengine - INFO - Epoch(train) [185][550/586] lr: 5.000000e-05 eta: 1:06:28 time: 0.288072 data_time: 0.029992 memory: 11131 loss_kpt: 0.000487 acc_pose: 0.885074 loss: 0.000487 2022/10/27 21:26:27 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:26:42 - mmengine - INFO - Epoch(train) [186][50/586] lr: 5.000000e-05 eta: 1:06:04 time: 0.295980 data_time: 0.039047 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.889470 loss: 0.000459 2022/10/27 21:26:56 - mmengine - INFO - Epoch(train) [186][100/586] lr: 5.000000e-05 eta: 1:05:50 time: 0.293942 data_time: 0.028626 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.901096 loss: 0.000476 2022/10/27 21:27:11 - mmengine - INFO - Epoch(train) [186][150/586] lr: 5.000000e-05 eta: 1:05:37 time: 0.285439 data_time: 0.031176 memory: 11131 loss_kpt: 0.000483 acc_pose: 0.889357 loss: 0.000483 2022/10/27 21:27:25 - mmengine - INFO - Epoch(train) [186][200/586] lr: 5.000000e-05 eta: 1:05:23 time: 0.290297 data_time: 0.028887 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.921272 loss: 0.000463 2022/10/27 21:27:40 - mmengine - INFO - Epoch(train) [186][250/586] lr: 5.000000e-05 eta: 1:05:10 time: 0.286407 data_time: 0.029677 memory: 11131 loss_kpt: 0.000465 acc_pose: 0.880338 loss: 0.000465 2022/10/27 21:27:54 - mmengine - INFO - Epoch(train) [186][300/586] lr: 5.000000e-05 eta: 1:04:57 time: 0.288742 data_time: 0.030130 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.924291 loss: 0.000471 2022/10/27 21:28:08 - mmengine - INFO - Epoch(train) [186][350/586] lr: 5.000000e-05 eta: 1:04:43 time: 0.288138 data_time: 0.029399 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.901668 loss: 0.000463 2022/10/27 21:28:23 - mmengine - INFO - Epoch(train) [186][400/586] lr: 5.000000e-05 eta: 1:04:30 time: 0.286961 data_time: 0.035852 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.923996 loss: 0.000463 2022/10/27 21:28:37 - mmengine - INFO - Epoch(train) [186][450/586] lr: 5.000000e-05 eta: 1:04:16 time: 0.293267 data_time: 0.029782 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.871102 loss: 0.000457 2022/10/27 21:28:52 - mmengine - INFO - Epoch(train) [186][500/586] lr: 5.000000e-05 eta: 1:04:03 time: 0.284721 data_time: 0.026954 memory: 11131 loss_kpt: 0.000475 acc_pose: 0.874895 loss: 0.000475 2022/10/27 21:29:06 - mmengine - INFO - Epoch(train) [186][550/586] lr: 5.000000e-05 eta: 1:03:49 time: 0.288436 data_time: 0.029726 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.923433 loss: 0.000470 2022/10/27 21:29:16 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:29:18 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:29:31 - mmengine - INFO - Epoch(train) [187][50/586] lr: 5.000000e-05 eta: 1:03:25 time: 0.297302 data_time: 0.041714 memory: 11131 loss_kpt: 0.000486 acc_pose: 0.894697 loss: 0.000486 2022/10/27 21:29:46 - mmengine - INFO - Epoch(train) [187][100/586] lr: 5.000000e-05 eta: 1:03:11 time: 0.290162 data_time: 0.028554 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.913973 loss: 0.000466 2022/10/27 21:30:00 - mmengine - INFO - Epoch(train) [187][150/586] lr: 5.000000e-05 eta: 1:02:58 time: 0.284077 data_time: 0.027207 memory: 11131 loss_kpt: 0.000475 acc_pose: 0.891022 loss: 0.000475 2022/10/27 21:30:15 - mmengine - INFO - Epoch(train) [187][200/586] lr: 5.000000e-05 eta: 1:02:44 time: 0.291168 data_time: 0.030288 memory: 11131 loss_kpt: 0.000494 acc_pose: 0.897663 loss: 0.000494 2022/10/27 21:30:29 - mmengine - INFO - Epoch(train) [187][250/586] lr: 5.000000e-05 eta: 1:02:31 time: 0.292377 data_time: 0.034152 memory: 11131 loss_kpt: 0.000474 acc_pose: 0.854624 loss: 0.000474 2022/10/27 21:30:44 - mmengine - INFO - Epoch(train) [187][300/586] lr: 5.000000e-05 eta: 1:02:17 time: 0.285151 data_time: 0.029461 memory: 11131 loss_kpt: 0.000488 acc_pose: 0.835646 loss: 0.000488 2022/10/27 21:30:58 - mmengine - INFO - Epoch(train) [187][350/586] lr: 5.000000e-05 eta: 1:02:04 time: 0.288429 data_time: 0.027862 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.913249 loss: 0.000476 2022/10/27 21:31:12 - mmengine - INFO - Epoch(train) [187][400/586] lr: 5.000000e-05 eta: 1:01:50 time: 0.284441 data_time: 0.027242 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.906082 loss: 0.000469 2022/10/27 21:31:27 - mmengine - INFO - Epoch(train) [187][450/586] lr: 5.000000e-05 eta: 1:01:37 time: 0.289003 data_time: 0.031899 memory: 11131 loss_kpt: 0.000478 acc_pose: 0.880729 loss: 0.000478 2022/10/27 21:31:41 - mmengine - INFO - Epoch(train) [187][500/586] lr: 5.000000e-05 eta: 1:01:23 time: 0.290944 data_time: 0.029826 memory: 11131 loss_kpt: 0.000455 acc_pose: 0.868958 loss: 0.000455 2022/10/27 21:31:56 - mmengine - INFO - Epoch(train) [187][550/586] lr: 5.000000e-05 eta: 1:01:10 time: 0.286416 data_time: 0.030014 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.910178 loss: 0.000461 2022/10/27 21:32:06 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:32:21 - mmengine - INFO - Epoch(train) [188][50/586] lr: 5.000000e-05 eta: 1:00:46 time: 0.301465 data_time: 0.038568 memory: 11131 loss_kpt: 0.000453 acc_pose: 0.891410 loss: 0.000453 2022/10/27 21:32:35 - mmengine - INFO - Epoch(train) [188][100/586] lr: 5.000000e-05 eta: 1:00:32 time: 0.290008 data_time: 0.028848 memory: 11131 loss_kpt: 0.000483 acc_pose: 0.948109 loss: 0.000483 2022/10/27 21:32:50 - mmengine - INFO - Epoch(train) [188][150/586] lr: 5.000000e-05 eta: 1:00:19 time: 0.292844 data_time: 0.032404 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.855224 loss: 0.000476 2022/10/27 21:33:04 - mmengine - INFO - Epoch(train) [188][200/586] lr: 5.000000e-05 eta: 1:00:05 time: 0.287171 data_time: 0.031613 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.854578 loss: 0.000466 2022/10/27 21:33:19 - mmengine - INFO - Epoch(train) [188][250/586] lr: 5.000000e-05 eta: 0:59:52 time: 0.290524 data_time: 0.028048 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.915924 loss: 0.000458 2022/10/27 21:33:33 - mmengine - INFO - Epoch(train) [188][300/586] lr: 5.000000e-05 eta: 0:59:38 time: 0.286297 data_time: 0.030940 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.901984 loss: 0.000468 2022/10/27 21:33:48 - mmengine - INFO - Epoch(train) [188][350/586] lr: 5.000000e-05 eta: 0:59:25 time: 0.292007 data_time: 0.028767 memory: 11131 loss_kpt: 0.000486 acc_pose: 0.863543 loss: 0.000486 2022/10/27 21:34:02 - mmengine - INFO - Epoch(train) [188][400/586] lr: 5.000000e-05 eta: 0:59:11 time: 0.287352 data_time: 0.035395 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.909446 loss: 0.000461 2022/10/27 21:34:07 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:34:17 - mmengine - INFO - Epoch(train) [188][450/586] lr: 5.000000e-05 eta: 0:58:58 time: 0.288364 data_time: 0.027908 memory: 11131 loss_kpt: 0.000477 acc_pose: 0.914784 loss: 0.000477 2022/10/27 21:34:31 - mmengine - INFO - Epoch(train) [188][500/586] lr: 5.000000e-05 eta: 0:58:44 time: 0.285637 data_time: 0.027944 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.870675 loss: 0.000466 2022/10/27 21:34:46 - mmengine - INFO - Epoch(train) [188][550/586] lr: 5.000000e-05 eta: 0:58:31 time: 0.293352 data_time: 0.029812 memory: 11131 loss_kpt: 0.000467 acc_pose: 0.819923 loss: 0.000467 2022/10/27 21:34:56 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:35:11 - mmengine - INFO - Epoch(train) [189][50/586] lr: 5.000000e-05 eta: 0:58:07 time: 0.295829 data_time: 0.041825 memory: 11131 loss_kpt: 0.000467 acc_pose: 0.888988 loss: 0.000467 2022/10/27 21:35:25 - mmengine - INFO - Epoch(train) [189][100/586] lr: 5.000000e-05 eta: 0:57:53 time: 0.292448 data_time: 0.027089 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.886473 loss: 0.000457 2022/10/27 21:35:40 - mmengine - INFO - Epoch(train) [189][150/586] lr: 5.000000e-05 eta: 0:57:40 time: 0.286361 data_time: 0.032328 memory: 11131 loss_kpt: 0.000453 acc_pose: 0.907599 loss: 0.000453 2022/10/27 21:35:54 - mmengine - INFO - Epoch(train) [189][200/586] lr: 5.000000e-05 eta: 0:57:26 time: 0.292695 data_time: 0.030274 memory: 11131 loss_kpt: 0.000453 acc_pose: 0.847476 loss: 0.000453 2022/10/27 21:36:09 - mmengine - INFO - Epoch(train) [189][250/586] lr: 5.000000e-05 eta: 0:57:13 time: 0.290937 data_time: 0.039526 memory: 11131 loss_kpt: 0.000486 acc_pose: 0.905371 loss: 0.000486 2022/10/27 21:36:23 - mmengine - INFO - Epoch(train) [189][300/586] lr: 5.000000e-05 eta: 0:56:59 time: 0.282429 data_time: 0.030375 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.883336 loss: 0.000462 2022/10/27 21:36:38 - mmengine - INFO - Epoch(train) [189][350/586] lr: 5.000000e-05 eta: 0:56:46 time: 0.291311 data_time: 0.028220 memory: 11131 loss_kpt: 0.000474 acc_pose: 0.893271 loss: 0.000474 2022/10/27 21:36:52 - mmengine - INFO - Epoch(train) [189][400/586] lr: 5.000000e-05 eta: 0:56:32 time: 0.282661 data_time: 0.029803 memory: 11131 loss_kpt: 0.000473 acc_pose: 0.888079 loss: 0.000473 2022/10/27 21:37:07 - mmengine - INFO - Epoch(train) [189][450/586] lr: 5.000000e-05 eta: 0:56:19 time: 0.295925 data_time: 0.028688 memory: 11131 loss_kpt: 0.000456 acc_pose: 0.855630 loss: 0.000456 2022/10/27 21:37:21 - mmengine - INFO - Epoch(train) [189][500/586] lr: 5.000000e-05 eta: 0:56:05 time: 0.289934 data_time: 0.033807 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.888338 loss: 0.000470 2022/10/27 21:37:36 - mmengine - INFO - Epoch(train) [189][550/586] lr: 5.000000e-05 eta: 0:55:52 time: 0.290390 data_time: 0.031972 memory: 11131 loss_kpt: 0.000473 acc_pose: 0.862822 loss: 0.000473 2022/10/27 21:37:46 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:38:01 - mmengine - INFO - Epoch(train) [190][50/586] lr: 5.000000e-05 eta: 0:55:27 time: 0.294108 data_time: 0.039170 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.866897 loss: 0.000457 2022/10/27 21:38:15 - mmengine - INFO - Epoch(train) [190][100/586] lr: 5.000000e-05 eta: 0:55:14 time: 0.290602 data_time: 0.028667 memory: 11131 loss_kpt: 0.000452 acc_pose: 0.873386 loss: 0.000452 2022/10/27 21:38:30 - mmengine - INFO - Epoch(train) [190][150/586] lr: 5.000000e-05 eta: 0:55:00 time: 0.288350 data_time: 0.035107 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.877379 loss: 0.000468 2022/10/27 21:38:44 - mmengine - INFO - Epoch(train) [190][200/586] lr: 5.000000e-05 eta: 0:54:47 time: 0.286736 data_time: 0.030375 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.918426 loss: 0.000468 2022/10/27 21:38:57 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:38:59 - mmengine - INFO - Epoch(train) [190][250/586] lr: 5.000000e-05 eta: 0:54:34 time: 0.291779 data_time: 0.031541 memory: 11131 loss_kpt: 0.000480 acc_pose: 0.860039 loss: 0.000480 2022/10/27 21:39:13 - mmengine - INFO - Epoch(train) [190][300/586] lr: 5.000000e-05 eta: 0:54:20 time: 0.291338 data_time: 0.034606 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.926541 loss: 0.000469 2022/10/27 21:39:28 - mmengine - INFO - Epoch(train) [190][350/586] lr: 5.000000e-05 eta: 0:54:07 time: 0.294989 data_time: 0.029220 memory: 11131 loss_kpt: 0.000472 acc_pose: 0.917866 loss: 0.000472 2022/10/27 21:39:42 - mmengine - INFO - Epoch(train) [190][400/586] lr: 5.000000e-05 eta: 0:53:53 time: 0.281315 data_time: 0.028752 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.942722 loss: 0.000457 2022/10/27 21:39:56 - mmengine - INFO - Epoch(train) [190][450/586] lr: 5.000000e-05 eta: 0:53:40 time: 0.286711 data_time: 0.027458 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.894339 loss: 0.000457 2022/10/27 21:40:11 - mmengine - INFO - Epoch(train) [190][500/586] lr: 5.000000e-05 eta: 0:53:26 time: 0.288256 data_time: 0.031244 memory: 11131 loss_kpt: 0.000460 acc_pose: 0.875392 loss: 0.000460 2022/10/27 21:40:25 - mmengine - INFO - Epoch(train) [190][550/586] lr: 5.000000e-05 eta: 0:53:13 time: 0.293759 data_time: 0.029487 memory: 11131 loss_kpt: 0.000477 acc_pose: 0.883283 loss: 0.000477 2022/10/27 21:40:36 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:40:36 - mmengine - INFO - Saving checkpoint at 190 epochs 2022/10/27 21:40:47 - mmengine - INFO - Epoch(val) [190][50/407] eta: 0:00:50 time: 0.140139 data_time: 0.020526 memory: 11131 2022/10/27 21:40:54 - mmengine - INFO - Epoch(val) [190][100/407] eta: 0:00:42 time: 0.137161 data_time: 0.016202 memory: 1836 2022/10/27 21:41:01 - mmengine - INFO - Epoch(val) [190][150/407] eta: 0:00:35 time: 0.138068 data_time: 0.019659 memory: 1836 2022/10/27 21:41:07 - mmengine - INFO - Epoch(val) [190][200/407] eta: 0:00:27 time: 0.135170 data_time: 0.014135 memory: 1836 2022/10/27 21:41:14 - mmengine - INFO - Epoch(val) [190][250/407] eta: 0:00:21 time: 0.136110 data_time: 0.015665 memory: 1836 2022/10/27 21:41:21 - mmengine - INFO - Epoch(val) [190][300/407] eta: 0:00:14 time: 0.133261 data_time: 0.014409 memory: 1836 2022/10/27 21:41:28 - mmengine - INFO - Epoch(val) [190][350/407] eta: 0:00:07 time: 0.136553 data_time: 0.016575 memory: 1836 2022/10/27 21:41:34 - mmengine - INFO - Epoch(val) [190][400/407] eta: 0:00:00 time: 0.133222 data_time: 0.018466 memory: 1836 2022/10/27 21:42:21 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 21:42:38 - mmengine - INFO - Epoch(val) [190][407/407] coco/AP: 0.747489 coco/AP .5: 0.905625 coco/AP .75: 0.817713 coco/AP (M): 0.705052 coco/AP (L): 0.820349 coco/AR: 0.798142 coco/AR .5: 0.941593 coco/AR .75: 0.860674 coco/AR (M): 0.751052 coco/AR (L): 0.866184 2022/10/27 21:42:38 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_180.pth is removed 2022/10/27 21:42:40 - mmengine - INFO - The best checkpoint with 0.7475 coco/AP at 190 epoch is saved to best_coco/AP_epoch_190.pth. 2022/10/27 21:42:55 - mmengine - INFO - Epoch(train) [191][50/586] lr: 5.000000e-05 eta: 0:52:48 time: 0.291115 data_time: 0.035491 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.887849 loss: 0.000470 2022/10/27 21:43:09 - mmengine - INFO - Epoch(train) [191][100/586] lr: 5.000000e-05 eta: 0:52:35 time: 0.285674 data_time: 0.026767 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.904961 loss: 0.000469 2022/10/27 21:43:24 - mmengine - INFO - Epoch(train) [191][150/586] lr: 5.000000e-05 eta: 0:52:21 time: 0.300712 data_time: 0.032342 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.898442 loss: 0.000468 2022/10/27 21:43:39 - mmengine - INFO - Epoch(train) [191][200/586] lr: 5.000000e-05 eta: 0:52:08 time: 0.291701 data_time: 0.031650 memory: 11131 loss_kpt: 0.000473 acc_pose: 0.883139 loss: 0.000473 2022/10/27 21:43:53 - mmengine - INFO - Epoch(train) [191][250/586] lr: 5.000000e-05 eta: 0:51:54 time: 0.286196 data_time: 0.033045 memory: 11131 loss_kpt: 0.000473 acc_pose: 0.878549 loss: 0.000473 2022/10/27 21:44:07 - mmengine - INFO - Epoch(train) [191][300/586] lr: 5.000000e-05 eta: 0:51:41 time: 0.283372 data_time: 0.032066 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.905561 loss: 0.000462 2022/10/27 21:44:22 - mmengine - INFO - Epoch(train) [191][350/586] lr: 5.000000e-05 eta: 0:51:27 time: 0.294538 data_time: 0.028487 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.835751 loss: 0.000468 2022/10/27 21:44:36 - mmengine - INFO - Epoch(train) [191][400/586] lr: 5.000000e-05 eta: 0:51:14 time: 0.284027 data_time: 0.028318 memory: 11131 loss_kpt: 0.000472 acc_pose: 0.911892 loss: 0.000472 2022/10/27 21:44:51 - mmengine - INFO - Epoch(train) [191][450/586] lr: 5.000000e-05 eta: 0:51:00 time: 0.289457 data_time: 0.029200 memory: 11131 loss_kpt: 0.000472 acc_pose: 0.857727 loss: 0.000472 2022/10/27 21:45:05 - mmengine - INFO - Epoch(train) [191][500/586] lr: 5.000000e-05 eta: 0:50:47 time: 0.283929 data_time: 0.027517 memory: 11131 loss_kpt: 0.000499 acc_pose: 0.900246 loss: 0.000499 2022/10/27 21:45:19 - mmengine - INFO - Epoch(train) [191][550/586] lr: 5.000000e-05 eta: 0:50:33 time: 0.289468 data_time: 0.026937 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.869127 loss: 0.000462 2022/10/27 21:45:29 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:45:44 - mmengine - INFO - Epoch(train) [192][50/586] lr: 5.000000e-05 eta: 0:50:09 time: 0.293882 data_time: 0.036532 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.927152 loss: 0.000457 2022/10/27 21:45:51 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:45:59 - mmengine - INFO - Epoch(train) [192][100/586] lr: 5.000000e-05 eta: 0:49:56 time: 0.293494 data_time: 0.027816 memory: 11131 loss_kpt: 0.000465 acc_pose: 0.846947 loss: 0.000465 2022/10/27 21:46:13 - mmengine - INFO - Epoch(train) [192][150/586] lr: 5.000000e-05 eta: 0:49:42 time: 0.287704 data_time: 0.030053 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.923912 loss: 0.000469 2022/10/27 21:46:28 - mmengine - INFO - Epoch(train) [192][200/586] lr: 5.000000e-05 eta: 0:49:29 time: 0.287488 data_time: 0.028502 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.889201 loss: 0.000459 2022/10/27 21:46:42 - mmengine - INFO - Epoch(train) [192][250/586] lr: 5.000000e-05 eta: 0:49:15 time: 0.293863 data_time: 0.029957 memory: 11131 loss_kpt: 0.000480 acc_pose: 0.919171 loss: 0.000480 2022/10/27 21:46:57 - mmengine - INFO - Epoch(train) [192][300/586] lr: 5.000000e-05 eta: 0:49:02 time: 0.290601 data_time: 0.029024 memory: 11131 loss_kpt: 0.000467 acc_pose: 0.827516 loss: 0.000467 2022/10/27 21:47:11 - mmengine - INFO - Epoch(train) [192][350/586] lr: 5.000000e-05 eta: 0:48:48 time: 0.288522 data_time: 0.029930 memory: 11131 loss_kpt: 0.000483 acc_pose: 0.877576 loss: 0.000483 2022/10/27 21:47:25 - mmengine - INFO - Epoch(train) [192][400/586] lr: 5.000000e-05 eta: 0:48:35 time: 0.283426 data_time: 0.027104 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.869777 loss: 0.000464 2022/10/27 21:47:40 - mmengine - INFO - Epoch(train) [192][450/586] lr: 5.000000e-05 eta: 0:48:21 time: 0.290461 data_time: 0.028111 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.818952 loss: 0.000470 2022/10/27 21:47:55 - mmengine - INFO - Epoch(train) [192][500/586] lr: 5.000000e-05 eta: 0:48:08 time: 0.295049 data_time: 0.027976 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.845708 loss: 0.000462 2022/10/27 21:48:09 - mmengine - INFO - Epoch(train) [192][550/586] lr: 5.000000e-05 eta: 0:47:54 time: 0.291118 data_time: 0.028858 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.898373 loss: 0.000471 2022/10/27 21:48:20 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:48:34 - mmengine - INFO - Epoch(train) [193][50/586] lr: 5.000000e-05 eta: 0:47:30 time: 0.298255 data_time: 0.037277 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.923682 loss: 0.000476 2022/10/27 21:48:49 - mmengine - INFO - Epoch(train) [193][100/586] lr: 5.000000e-05 eta: 0:47:17 time: 0.287668 data_time: 0.029780 memory: 11131 loss_kpt: 0.000465 acc_pose: 0.874929 loss: 0.000465 2022/10/27 21:49:04 - mmengine - INFO - Epoch(train) [193][150/586] lr: 5.000000e-05 eta: 0:47:03 time: 0.292749 data_time: 0.030933 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.771663 loss: 0.000466 2022/10/27 21:49:18 - mmengine - INFO - Epoch(train) [193][200/586] lr: 5.000000e-05 eta: 0:46:50 time: 0.286334 data_time: 0.027445 memory: 11131 loss_kpt: 0.000460 acc_pose: 0.914339 loss: 0.000460 2022/10/27 21:49:32 - mmengine - INFO - Epoch(train) [193][250/586] lr: 5.000000e-05 eta: 0:46:36 time: 0.286832 data_time: 0.029127 memory: 11131 loss_kpt: 0.000460 acc_pose: 0.895359 loss: 0.000460 2022/10/27 21:49:47 - mmengine - INFO - Epoch(train) [193][300/586] lr: 5.000000e-05 eta: 0:46:23 time: 0.291002 data_time: 0.028930 memory: 11131 loss_kpt: 0.000460 acc_pose: 0.869082 loss: 0.000460 2022/10/27 21:50:01 - mmengine - INFO - Epoch(train) [193][350/586] lr: 5.000000e-05 eta: 0:46:09 time: 0.291931 data_time: 0.032809 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.881194 loss: 0.000471 2022/10/27 21:50:16 - mmengine - INFO - Epoch(train) [193][400/586] lr: 5.000000e-05 eta: 0:45:56 time: 0.287648 data_time: 0.027120 memory: 11131 loss_kpt: 0.000455 acc_pose: 0.910914 loss: 0.000455 2022/10/27 21:50:30 - mmengine - INFO - Epoch(train) [193][450/586] lr: 5.000000e-05 eta: 0:45:42 time: 0.292085 data_time: 0.027176 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.846648 loss: 0.000466 2022/10/27 21:50:41 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:50:45 - mmengine - INFO - Epoch(train) [193][500/586] lr: 5.000000e-05 eta: 0:45:29 time: 0.284216 data_time: 0.028303 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.920750 loss: 0.000470 2022/10/27 21:50:59 - mmengine - INFO - Epoch(train) [193][550/586] lr: 5.000000e-05 eta: 0:45:15 time: 0.285513 data_time: 0.027733 memory: 11131 loss_kpt: 0.000456 acc_pose: 0.897505 loss: 0.000456 2022/10/27 21:51:09 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:51:24 - mmengine - INFO - Epoch(train) [194][50/586] lr: 5.000000e-05 eta: 0:44:51 time: 0.307157 data_time: 0.043142 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.922048 loss: 0.000462 2022/10/27 21:51:39 - mmengine - INFO - Epoch(train) [194][100/586] lr: 5.000000e-05 eta: 0:44:38 time: 0.291277 data_time: 0.029265 memory: 11131 loss_kpt: 0.000475 acc_pose: 0.903064 loss: 0.000475 2022/10/27 21:51:53 - mmengine - INFO - Epoch(train) [194][150/586] lr: 5.000000e-05 eta: 0:44:24 time: 0.286804 data_time: 0.028857 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.874784 loss: 0.000457 2022/10/27 21:52:08 - mmengine - INFO - Epoch(train) [194][200/586] lr: 5.000000e-05 eta: 0:44:11 time: 0.291181 data_time: 0.031818 memory: 11131 loss_kpt: 0.000467 acc_pose: 0.856488 loss: 0.000467 2022/10/27 21:52:23 - mmengine - INFO - Epoch(train) [194][250/586] lr: 5.000000e-05 eta: 0:43:57 time: 0.291907 data_time: 0.028673 memory: 11131 loss_kpt: 0.000479 acc_pose: 0.954534 loss: 0.000479 2022/10/27 21:52:37 - mmengine - INFO - Epoch(train) [194][300/586] lr: 5.000000e-05 eta: 0:43:44 time: 0.285520 data_time: 0.028090 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.892168 loss: 0.000458 2022/10/27 21:52:52 - mmengine - INFO - Epoch(train) [194][350/586] lr: 5.000000e-05 eta: 0:43:30 time: 0.293397 data_time: 0.033325 memory: 11131 loss_kpt: 0.000481 acc_pose: 0.907269 loss: 0.000481 2022/10/27 21:53:06 - mmengine - INFO - Epoch(train) [194][400/586] lr: 5.000000e-05 eta: 0:43:17 time: 0.282330 data_time: 0.027248 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.888024 loss: 0.000463 2022/10/27 21:53:20 - mmengine - INFO - Epoch(train) [194][450/586] lr: 5.000000e-05 eta: 0:43:03 time: 0.288766 data_time: 0.028621 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.896259 loss: 0.000457 2022/10/27 21:53:35 - mmengine - INFO - Epoch(train) [194][500/586] lr: 5.000000e-05 eta: 0:42:50 time: 0.295552 data_time: 0.034040 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.920534 loss: 0.000463 2022/10/27 21:53:49 - mmengine - INFO - Epoch(train) [194][550/586] lr: 5.000000e-05 eta: 0:42:36 time: 0.281950 data_time: 0.030262 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.882755 loss: 0.000461 2022/10/27 21:53:59 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:54:14 - mmengine - INFO - Epoch(train) [195][50/586] lr: 5.000000e-05 eta: 0:42:12 time: 0.302163 data_time: 0.043302 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.905364 loss: 0.000463 2022/10/27 21:54:29 - mmengine - INFO - Epoch(train) [195][100/586] lr: 5.000000e-05 eta: 0:41:58 time: 0.286705 data_time: 0.027635 memory: 11131 loss_kpt: 0.000475 acc_pose: 0.895191 loss: 0.000475 2022/10/27 21:54:43 - mmengine - INFO - Epoch(train) [195][150/586] lr: 5.000000e-05 eta: 0:41:45 time: 0.291629 data_time: 0.031881 memory: 11131 loss_kpt: 0.000450 acc_pose: 0.910011 loss: 0.000450 2022/10/27 21:54:58 - mmengine - INFO - Epoch(train) [195][200/586] lr: 5.000000e-05 eta: 0:41:31 time: 0.290050 data_time: 0.031667 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.837593 loss: 0.000471 2022/10/27 21:55:12 - mmengine - INFO - Epoch(train) [195][250/586] lr: 5.000000e-05 eta: 0:41:18 time: 0.288612 data_time: 0.029390 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.912056 loss: 0.000458 2022/10/27 21:55:27 - mmengine - INFO - Epoch(train) [195][300/586] lr: 5.000000e-05 eta: 0:41:04 time: 0.283617 data_time: 0.027018 memory: 11131 loss_kpt: 0.000474 acc_pose: 0.848300 loss: 0.000474 2022/10/27 21:55:31 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:55:41 - mmengine - INFO - Epoch(train) [195][350/586] lr: 5.000000e-05 eta: 0:40:51 time: 0.287267 data_time: 0.026454 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.915707 loss: 0.000476 2022/10/27 21:55:56 - mmengine - INFO - Epoch(train) [195][400/586] lr: 5.000000e-05 eta: 0:40:37 time: 0.293695 data_time: 0.033914 memory: 11131 loss_kpt: 0.000465 acc_pose: 0.911297 loss: 0.000465 2022/10/27 21:56:10 - mmengine - INFO - Epoch(train) [195][450/586] lr: 5.000000e-05 eta: 0:40:24 time: 0.293444 data_time: 0.028322 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.924088 loss: 0.000458 2022/10/27 21:56:24 - mmengine - INFO - Epoch(train) [195][500/586] lr: 5.000000e-05 eta: 0:40:10 time: 0.284161 data_time: 0.028308 memory: 11131 loss_kpt: 0.000485 acc_pose: 0.915464 loss: 0.000485 2022/10/27 21:56:39 - mmengine - INFO - Epoch(train) [195][550/586] lr: 5.000000e-05 eta: 0:39:57 time: 0.287536 data_time: 0.030131 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.850751 loss: 0.000466 2022/10/27 21:56:49 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:57:04 - mmengine - INFO - Epoch(train) [196][50/586] lr: 5.000000e-05 eta: 0:39:33 time: 0.305363 data_time: 0.043501 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.867363 loss: 0.000457 2022/10/27 21:57:19 - mmengine - INFO - Epoch(train) [196][100/586] lr: 5.000000e-05 eta: 0:39:19 time: 0.290394 data_time: 0.030674 memory: 11131 loss_kpt: 0.000450 acc_pose: 0.870291 loss: 0.000450 2022/10/27 21:57:33 - mmengine - INFO - Epoch(train) [196][150/586] lr: 5.000000e-05 eta: 0:39:06 time: 0.285865 data_time: 0.027517 memory: 11131 loss_kpt: 0.000452 acc_pose: 0.864060 loss: 0.000452 2022/10/27 21:57:48 - mmengine - INFO - Epoch(train) [196][200/586] lr: 5.000000e-05 eta: 0:38:52 time: 0.288924 data_time: 0.033258 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.894812 loss: 0.000459 2022/10/27 21:58:02 - mmengine - INFO - Epoch(train) [196][250/586] lr: 5.000000e-05 eta: 0:38:39 time: 0.288119 data_time: 0.027445 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.844639 loss: 0.000466 2022/10/27 21:58:17 - mmengine - INFO - Epoch(train) [196][300/586] lr: 5.000000e-05 eta: 0:38:25 time: 0.288451 data_time: 0.029665 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.895036 loss: 0.000461 2022/10/27 21:58:31 - mmengine - INFO - Epoch(train) [196][350/586] lr: 5.000000e-05 eta: 0:38:12 time: 0.286330 data_time: 0.028691 memory: 11131 loss_kpt: 0.000482 acc_pose: 0.914322 loss: 0.000482 2022/10/27 21:58:45 - mmengine - INFO - Epoch(train) [196][400/586] lr: 5.000000e-05 eta: 0:37:58 time: 0.285437 data_time: 0.031109 memory: 11131 loss_kpt: 0.000452 acc_pose: 0.910809 loss: 0.000452 2022/10/27 21:58:59 - mmengine - INFO - Epoch(train) [196][450/586] lr: 5.000000e-05 eta: 0:37:45 time: 0.284860 data_time: 0.028303 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.914926 loss: 0.000476 2022/10/27 21:59:14 - mmengine - INFO - Epoch(train) [196][500/586] lr: 5.000000e-05 eta: 0:37:31 time: 0.291981 data_time: 0.033251 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.880177 loss: 0.000470 2022/10/27 21:59:28 - mmengine - INFO - Epoch(train) [196][550/586] lr: 5.000000e-05 eta: 0:37:18 time: 0.287306 data_time: 0.030385 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.901312 loss: 0.000466 2022/10/27 21:59:39 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 21:59:54 - mmengine - INFO - Epoch(train) [197][50/586] lr: 5.000000e-05 eta: 0:36:54 time: 0.294599 data_time: 0.039123 memory: 11131 loss_kpt: 0.000450 acc_pose: 0.884816 loss: 0.000450 2022/10/27 22:00:08 - mmengine - INFO - Epoch(train) [197][100/586] lr: 5.000000e-05 eta: 0:36:40 time: 0.290161 data_time: 0.029792 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.908489 loss: 0.000464 2022/10/27 22:00:21 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:00:23 - mmengine - INFO - Epoch(train) [197][150/586] lr: 5.000000e-05 eta: 0:36:27 time: 0.293343 data_time: 0.032835 memory: 11131 loss_kpt: 0.000473 acc_pose: 0.916234 loss: 0.000473 2022/10/27 22:00:37 - mmengine - INFO - Epoch(train) [197][200/586] lr: 5.000000e-05 eta: 0:36:13 time: 0.283736 data_time: 0.027324 memory: 11131 loss_kpt: 0.000465 acc_pose: 0.948133 loss: 0.000465 2022/10/27 22:00:51 - mmengine - INFO - Epoch(train) [197][250/586] lr: 5.000000e-05 eta: 0:36:00 time: 0.288911 data_time: 0.031853 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.903882 loss: 0.000469 2022/10/27 22:01:06 - mmengine - INFO - Epoch(train) [197][300/586] lr: 5.000000e-05 eta: 0:35:46 time: 0.284224 data_time: 0.028618 memory: 11131 loss_kpt: 0.000465 acc_pose: 0.892584 loss: 0.000465 2022/10/27 22:01:20 - mmengine - INFO - Epoch(train) [197][350/586] lr: 5.000000e-05 eta: 0:35:33 time: 0.287154 data_time: 0.027651 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.911187 loss: 0.000464 2022/10/27 22:01:35 - mmengine - INFO - Epoch(train) [197][400/586] lr: 5.000000e-05 eta: 0:35:19 time: 0.293966 data_time: 0.029665 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.915487 loss: 0.000466 2022/10/27 22:01:49 - mmengine - INFO - Epoch(train) [197][450/586] lr: 5.000000e-05 eta: 0:35:06 time: 0.285415 data_time: 0.029245 memory: 11131 loss_kpt: 0.000450 acc_pose: 0.847863 loss: 0.000450 2022/10/27 22:02:03 - mmengine - INFO - Epoch(train) [197][500/586] lr: 5.000000e-05 eta: 0:34:52 time: 0.289311 data_time: 0.029383 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.899703 loss: 0.000464 2022/10/27 22:02:18 - mmengine - INFO - Epoch(train) [197][550/586] lr: 5.000000e-05 eta: 0:34:39 time: 0.284900 data_time: 0.028487 memory: 11131 loss_kpt: 0.000475 acc_pose: 0.902572 loss: 0.000475 2022/10/27 22:02:28 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:02:43 - mmengine - INFO - Epoch(train) [198][50/586] lr: 5.000000e-05 eta: 0:34:15 time: 0.303652 data_time: 0.040074 memory: 11131 loss_kpt: 0.000435 acc_pose: 0.937588 loss: 0.000435 2022/10/27 22:02:58 - mmengine - INFO - Epoch(train) [198][100/586] lr: 5.000000e-05 eta: 0:34:01 time: 0.295148 data_time: 0.027195 memory: 11131 loss_kpt: 0.000460 acc_pose: 0.913617 loss: 0.000460 2022/10/27 22:03:12 - mmengine - INFO - Epoch(train) [198][150/586] lr: 5.000000e-05 eta: 0:33:48 time: 0.285651 data_time: 0.030121 memory: 11131 loss_kpt: 0.000454 acc_pose: 0.878211 loss: 0.000454 2022/10/27 22:03:26 - mmengine - INFO - Epoch(train) [198][200/586] lr: 5.000000e-05 eta: 0:33:34 time: 0.283953 data_time: 0.030652 memory: 11131 loss_kpt: 0.000474 acc_pose: 0.916660 loss: 0.000474 2022/10/27 22:03:41 - mmengine - INFO - Epoch(train) [198][250/586] lr: 5.000000e-05 eta: 0:33:21 time: 0.293137 data_time: 0.033464 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.865033 loss: 0.000471 2022/10/27 22:03:55 - mmengine - INFO - Epoch(train) [198][300/586] lr: 5.000000e-05 eta: 0:33:07 time: 0.283323 data_time: 0.027410 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.875064 loss: 0.000463 2022/10/27 22:04:10 - mmengine - INFO - Epoch(train) [198][350/586] lr: 5.000000e-05 eta: 0:32:53 time: 0.291988 data_time: 0.029643 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.891001 loss: 0.000466 2022/10/27 22:04:24 - mmengine - INFO - Epoch(train) [198][400/586] lr: 5.000000e-05 eta: 0:32:40 time: 0.282364 data_time: 0.031211 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.923111 loss: 0.000466 2022/10/27 22:04:38 - mmengine - INFO - Epoch(train) [198][450/586] lr: 5.000000e-05 eta: 0:32:26 time: 0.288591 data_time: 0.028517 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.893583 loss: 0.000476 2022/10/27 22:04:53 - mmengine - INFO - Epoch(train) [198][500/586] lr: 5.000000e-05 eta: 0:32:13 time: 0.294315 data_time: 0.032868 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.858278 loss: 0.000461 2022/10/27 22:05:07 - mmengine - INFO - Epoch(train) [198][550/586] lr: 5.000000e-05 eta: 0:31:59 time: 0.287107 data_time: 0.028786 memory: 11131 loss_kpt: 0.000475 acc_pose: 0.872670 loss: 0.000475 2022/10/27 22:05:10 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:05:18 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:05:33 - mmengine - INFO - Epoch(train) [199][50/586] lr: 5.000000e-05 eta: 0:31:36 time: 0.298912 data_time: 0.038929 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.958676 loss: 0.000469 2022/10/27 22:05:47 - mmengine - INFO - Epoch(train) [199][100/586] lr: 5.000000e-05 eta: 0:31:22 time: 0.288511 data_time: 0.031391 memory: 11131 loss_kpt: 0.000448 acc_pose: 0.881534 loss: 0.000448 2022/10/27 22:06:02 - mmengine - INFO - Epoch(train) [199][150/586] lr: 5.000000e-05 eta: 0:31:08 time: 0.289595 data_time: 0.034043 memory: 11131 loss_kpt: 0.000474 acc_pose: 0.889332 loss: 0.000474 2022/10/27 22:06:16 - mmengine - INFO - Epoch(train) [199][200/586] lr: 5.000000e-05 eta: 0:30:55 time: 0.287447 data_time: 0.030233 memory: 11131 loss_kpt: 0.000450 acc_pose: 0.853397 loss: 0.000450 2022/10/27 22:06:31 - mmengine - INFO - Epoch(train) [199][250/586] lr: 5.000000e-05 eta: 0:30:41 time: 0.293624 data_time: 0.029633 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.823861 loss: 0.000464 2022/10/27 22:06:45 - mmengine - INFO - Epoch(train) [199][300/586] lr: 5.000000e-05 eta: 0:30:28 time: 0.289074 data_time: 0.030052 memory: 11131 loss_kpt: 0.000473 acc_pose: 0.892916 loss: 0.000473 2022/10/27 22:06:59 - mmengine - INFO - Epoch(train) [199][350/586] lr: 5.000000e-05 eta: 0:30:14 time: 0.284291 data_time: 0.027226 memory: 11131 loss_kpt: 0.000455 acc_pose: 0.943661 loss: 0.000455 2022/10/27 22:07:14 - mmengine - INFO - Epoch(train) [199][400/586] lr: 5.000000e-05 eta: 0:30:01 time: 0.295391 data_time: 0.030430 memory: 11131 loss_kpt: 0.000448 acc_pose: 0.859765 loss: 0.000448 2022/10/27 22:07:29 - mmengine - INFO - Epoch(train) [199][450/586] lr: 5.000000e-05 eta: 0:29:47 time: 0.287019 data_time: 0.027983 memory: 11131 loss_kpt: 0.000454 acc_pose: 0.868027 loss: 0.000454 2022/10/27 22:07:43 - mmengine - INFO - Epoch(train) [199][500/586] lr: 5.000000e-05 eta: 0:29:34 time: 0.287897 data_time: 0.027921 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.947079 loss: 0.000457 2022/10/27 22:07:57 - mmengine - INFO - Epoch(train) [199][550/586] lr: 5.000000e-05 eta: 0:29:20 time: 0.284534 data_time: 0.032123 memory: 11131 loss_kpt: 0.000449 acc_pose: 0.845156 loss: 0.000449 2022/10/27 22:08:08 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:08:23 - mmengine - INFO - Epoch(train) [200][50/586] lr: 5.000000e-05 eta: 0:28:56 time: 0.302179 data_time: 0.035616 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.861229 loss: 0.000470 2022/10/27 22:08:37 - mmengine - INFO - Epoch(train) [200][100/586] lr: 5.000000e-05 eta: 0:28:43 time: 0.286259 data_time: 0.028635 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.852027 loss: 0.000461 2022/10/27 22:08:52 - mmengine - INFO - Epoch(train) [200][150/586] lr: 5.000000e-05 eta: 0:28:29 time: 0.288434 data_time: 0.029443 memory: 11131 loss_kpt: 0.000453 acc_pose: 0.892673 loss: 0.000453 2022/10/27 22:09:06 - mmengine - INFO - Epoch(train) [200][200/586] lr: 5.000000e-05 eta: 0:28:16 time: 0.285199 data_time: 0.028831 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.891501 loss: 0.000463 2022/10/27 22:09:20 - mmengine - INFO - Epoch(train) [200][250/586] lr: 5.000000e-05 eta: 0:28:02 time: 0.290657 data_time: 0.034495 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.890697 loss: 0.000461 2022/10/27 22:09:35 - mmengine - INFO - Epoch(train) [200][300/586] lr: 5.000000e-05 eta: 0:27:49 time: 0.287945 data_time: 0.027411 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.897567 loss: 0.000459 2022/10/27 22:09:49 - mmengine - INFO - Epoch(train) [200][350/586] lr: 5.000000e-05 eta: 0:27:35 time: 0.287902 data_time: 0.027410 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.882562 loss: 0.000464 2022/10/27 22:10:00 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:10:04 - mmengine - INFO - Epoch(train) [200][400/586] lr: 5.000000e-05 eta: 0:27:22 time: 0.285750 data_time: 0.027740 memory: 11131 loss_kpt: 0.000454 acc_pose: 0.877278 loss: 0.000454 2022/10/27 22:10:18 - mmengine - INFO - Epoch(train) [200][450/586] lr: 5.000000e-05 eta: 0:27:08 time: 0.286654 data_time: 0.029555 memory: 11131 loss_kpt: 0.000474 acc_pose: 0.877167 loss: 0.000474 2022/10/27 22:10:33 - mmengine - INFO - Epoch(train) [200][500/586] lr: 5.000000e-05 eta: 0:26:55 time: 0.293062 data_time: 0.027828 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.877748 loss: 0.000466 2022/10/27 22:10:47 - mmengine - INFO - Epoch(train) [200][550/586] lr: 5.000000e-05 eta: 0:26:41 time: 0.285901 data_time: 0.028629 memory: 11131 loss_kpt: 0.000460 acc_pose: 0.890342 loss: 0.000460 2022/10/27 22:10:57 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:10:57 - mmengine - INFO - Saving checkpoint at 200 epochs 2022/10/27 22:11:08 - mmengine - INFO - Epoch(val) [200][50/407] eta: 0:00:50 time: 0.142001 data_time: 0.021483 memory: 11131 2022/10/27 22:11:15 - mmengine - INFO - Epoch(val) [200][100/407] eta: 0:00:41 time: 0.134141 data_time: 0.014674 memory: 1836 2022/10/27 22:11:22 - mmengine - INFO - Epoch(val) [200][150/407] eta: 0:00:35 time: 0.138613 data_time: 0.020066 memory: 1836 2022/10/27 22:11:28 - mmengine - INFO - Epoch(val) [200][200/407] eta: 0:00:27 time: 0.134205 data_time: 0.016012 memory: 1836 2022/10/27 22:11:35 - mmengine - INFO - Epoch(val) [200][250/407] eta: 0:00:21 time: 0.139770 data_time: 0.019006 memory: 1836 2022/10/27 22:11:43 - mmengine - INFO - Epoch(val) [200][300/407] eta: 0:00:15 time: 0.143079 data_time: 0.023273 memory: 1836 2022/10/27 22:11:50 - mmengine - INFO - Epoch(val) [200][350/407] eta: 0:00:08 time: 0.140366 data_time: 0.020618 memory: 1836 2022/10/27 22:11:56 - mmengine - INFO - Epoch(val) [200][400/407] eta: 0:00:00 time: 0.127758 data_time: 0.012980 memory: 1836 2022/10/27 22:12:42 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 22:13:00 - mmengine - INFO - Epoch(val) [200][407/407] coco/AP: 0.747273 coco/AP .5: 0.905165 coco/AP .75: 0.815547 coco/AP (M): 0.705293 coco/AP (L): 0.820578 coco/AR: 0.798567 coco/AR .5: 0.940649 coco/AR .75: 0.860359 coco/AR (M): 0.751844 coco/AR (L): 0.866109 2022/10/27 22:13:15 - mmengine - INFO - Epoch(train) [201][50/586] lr: 5.000000e-06 eta: 0:26:17 time: 0.297332 data_time: 0.036080 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.906439 loss: 0.000462 2022/10/27 22:13:29 - mmengine - INFO - Epoch(train) [201][100/586] lr: 5.000000e-06 eta: 0:26:04 time: 0.288860 data_time: 0.028495 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.891220 loss: 0.000464 2022/10/27 22:13:44 - mmengine - INFO - Epoch(train) [201][150/586] lr: 5.000000e-06 eta: 0:25:50 time: 0.295337 data_time: 0.032729 memory: 11131 loss_kpt: 0.000453 acc_pose: 0.868526 loss: 0.000453 2022/10/27 22:13:59 - mmengine - INFO - Epoch(train) [201][200/586] lr: 5.000000e-06 eta: 0:25:37 time: 0.294569 data_time: 0.028736 memory: 11131 loss_kpt: 0.000453 acc_pose: 0.849119 loss: 0.000453 2022/10/27 22:14:13 - mmengine - INFO - Epoch(train) [201][250/586] lr: 5.000000e-06 eta: 0:25:23 time: 0.287400 data_time: 0.028989 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.835173 loss: 0.000458 2022/10/27 22:14:28 - mmengine - INFO - Epoch(train) [201][300/586] lr: 5.000000e-06 eta: 0:25:10 time: 0.284730 data_time: 0.029293 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.857299 loss: 0.000459 2022/10/27 22:14:42 - mmengine - INFO - Epoch(train) [201][350/586] lr: 5.000000e-06 eta: 0:24:56 time: 0.295254 data_time: 0.027398 memory: 11131 loss_kpt: 0.000467 acc_pose: 0.857500 loss: 0.000467 2022/10/27 22:14:57 - mmengine - INFO - Epoch(train) [201][400/586] lr: 5.000000e-06 eta: 0:24:42 time: 0.285996 data_time: 0.027122 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.884479 loss: 0.000458 2022/10/27 22:15:11 - mmengine - INFO - Epoch(train) [201][450/586] lr: 5.000000e-06 eta: 0:24:29 time: 0.290876 data_time: 0.027514 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.869583 loss: 0.000469 2022/10/27 22:15:25 - mmengine - INFO - Epoch(train) [201][500/586] lr: 5.000000e-06 eta: 0:24:15 time: 0.284956 data_time: 0.030244 memory: 11131 loss_kpt: 0.000454 acc_pose: 0.884102 loss: 0.000454 2022/10/27 22:15:40 - mmengine - INFO - Epoch(train) [201][550/586] lr: 5.000000e-06 eta: 0:24:02 time: 0.291183 data_time: 0.029600 memory: 11131 loss_kpt: 0.000475 acc_pose: 0.902294 loss: 0.000475 2022/10/27 22:15:50 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:16:05 - mmengine - INFO - Epoch(train) [202][50/586] lr: 5.000000e-06 eta: 0:23:38 time: 0.294554 data_time: 0.037774 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.884616 loss: 0.000458 2022/10/27 22:16:20 - mmengine - INFO - Epoch(train) [202][100/586] lr: 5.000000e-06 eta: 0:23:25 time: 0.292232 data_time: 0.028368 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.827699 loss: 0.000461 2022/10/27 22:16:34 - mmengine - INFO - Epoch(train) [202][150/586] lr: 5.000000e-06 eta: 0:23:11 time: 0.284607 data_time: 0.028348 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.923123 loss: 0.000459 2022/10/27 22:16:48 - mmengine - INFO - Epoch(train) [202][200/586] lr: 5.000000e-06 eta: 0:22:57 time: 0.284123 data_time: 0.030506 memory: 11131 loss_kpt: 0.000465 acc_pose: 0.868482 loss: 0.000465 2022/10/27 22:16:52 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:17:03 - mmengine - INFO - Epoch(train) [202][250/586] lr: 5.000000e-06 eta: 0:22:44 time: 0.291602 data_time: 0.031641 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.920413 loss: 0.000468 2022/10/27 22:17:17 - mmengine - INFO - Epoch(train) [202][300/586] lr: 5.000000e-06 eta: 0:22:30 time: 0.284982 data_time: 0.029598 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.893966 loss: 0.000461 2022/10/27 22:17:31 - mmengine - INFO - Epoch(train) [202][350/586] lr: 5.000000e-06 eta: 0:22:17 time: 0.290531 data_time: 0.033333 memory: 11131 loss_kpt: 0.000452 acc_pose: 0.894404 loss: 0.000452 2022/10/27 22:17:46 - mmengine - INFO - Epoch(train) [202][400/586] lr: 5.000000e-06 eta: 0:22:03 time: 0.281990 data_time: 0.028447 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.922275 loss: 0.000463 2022/10/27 22:18:00 - mmengine - INFO - Epoch(train) [202][450/586] lr: 5.000000e-06 eta: 0:21:50 time: 0.295931 data_time: 0.027796 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.888466 loss: 0.000476 2022/10/27 22:18:15 - mmengine - INFO - Epoch(train) [202][500/586] lr: 5.000000e-06 eta: 0:21:36 time: 0.290235 data_time: 0.029711 memory: 11131 loss_kpt: 0.000465 acc_pose: 0.876242 loss: 0.000465 2022/10/27 22:18:29 - mmengine - INFO - Epoch(train) [202][550/586] lr: 5.000000e-06 eta: 0:21:23 time: 0.287517 data_time: 0.028071 memory: 11131 loss_kpt: 0.000447 acc_pose: 0.903973 loss: 0.000447 2022/10/27 22:18:39 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:18:54 - mmengine - INFO - Epoch(train) [203][50/586] lr: 5.000000e-06 eta: 0:20:59 time: 0.291799 data_time: 0.038093 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.886791 loss: 0.000458 2022/10/27 22:19:09 - mmengine - INFO - Epoch(train) [203][100/586] lr: 5.000000e-06 eta: 0:20:45 time: 0.294629 data_time: 0.029662 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.810165 loss: 0.000457 2022/10/27 22:19:23 - mmengine - INFO - Epoch(train) [203][150/586] lr: 5.000000e-06 eta: 0:20:32 time: 0.288378 data_time: 0.028889 memory: 11131 loss_kpt: 0.000452 acc_pose: 0.915717 loss: 0.000452 2022/10/27 22:19:38 - mmengine - INFO - Epoch(train) [203][200/586] lr: 5.000000e-06 eta: 0:20:18 time: 0.292643 data_time: 0.033709 memory: 11131 loss_kpt: 0.000451 acc_pose: 0.903990 loss: 0.000451 2022/10/27 22:19:52 - mmengine - INFO - Epoch(train) [203][250/586] lr: 5.000000e-06 eta: 0:20:05 time: 0.284282 data_time: 0.028054 memory: 11131 loss_kpt: 0.000460 acc_pose: 0.896679 loss: 0.000460 2022/10/27 22:20:06 - mmengine - INFO - Epoch(train) [203][300/586] lr: 5.000000e-06 eta: 0:19:51 time: 0.283865 data_time: 0.027185 memory: 11131 loss_kpt: 0.000477 acc_pose: 0.842625 loss: 0.000477 2022/10/27 22:20:21 - mmengine - INFO - Epoch(train) [203][350/586] lr: 5.000000e-06 eta: 0:19:38 time: 0.290728 data_time: 0.030839 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.797110 loss: 0.000471 2022/10/27 22:20:35 - mmengine - INFO - Epoch(train) [203][400/586] lr: 5.000000e-06 eta: 0:19:24 time: 0.287633 data_time: 0.032852 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.835240 loss: 0.000458 2022/10/27 22:20:50 - mmengine - INFO - Epoch(train) [203][450/586] lr: 5.000000e-06 eta: 0:19:11 time: 0.293094 data_time: 0.029906 memory: 11131 loss_kpt: 0.000465 acc_pose: 0.916659 loss: 0.000465 2022/10/27 22:21:04 - mmengine - INFO - Epoch(train) [203][500/586] lr: 5.000000e-06 eta: 0:18:57 time: 0.286744 data_time: 0.029278 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.838952 loss: 0.000468 2022/10/27 22:21:19 - mmengine - INFO - Epoch(train) [203][550/586] lr: 5.000000e-06 eta: 0:18:44 time: 0.287810 data_time: 0.027481 memory: 11131 loss_kpt: 0.000456 acc_pose: 0.918934 loss: 0.000456 2022/10/27 22:21:29 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:21:41 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:21:44 - mmengine - INFO - Epoch(train) [204][50/586] lr: 5.000000e-06 eta: 0:18:20 time: 0.297065 data_time: 0.038070 memory: 11131 loss_kpt: 0.000453 acc_pose: 0.866914 loss: 0.000453 2022/10/27 22:21:58 - mmengine - INFO - Epoch(train) [204][100/586] lr: 5.000000e-06 eta: 0:18:06 time: 0.291720 data_time: 0.033075 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.891195 loss: 0.000457 2022/10/27 22:22:13 - mmengine - INFO - Epoch(train) [204][150/586] lr: 5.000000e-06 eta: 0:17:53 time: 0.289488 data_time: 0.027807 memory: 11131 loss_kpt: 0.000476 acc_pose: 0.890356 loss: 0.000476 2022/10/27 22:22:27 - mmengine - INFO - Epoch(train) [204][200/586] lr: 5.000000e-06 eta: 0:17:39 time: 0.287891 data_time: 0.030686 memory: 11131 loss_kpt: 0.000449 acc_pose: 0.898438 loss: 0.000449 2022/10/27 22:22:42 - mmengine - INFO - Epoch(train) [204][250/586] lr: 5.000000e-06 eta: 0:17:26 time: 0.291878 data_time: 0.029291 memory: 11131 loss_kpt: 0.000449 acc_pose: 0.852729 loss: 0.000449 2022/10/27 22:22:56 - mmengine - INFO - Epoch(train) [204][300/586] lr: 5.000000e-06 eta: 0:17:12 time: 0.283245 data_time: 0.030499 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.936773 loss: 0.000462 2022/10/27 22:23:11 - mmengine - INFO - Epoch(train) [204][350/586] lr: 5.000000e-06 eta: 0:16:59 time: 0.294628 data_time: 0.029646 memory: 11131 loss_kpt: 0.000460 acc_pose: 0.914060 loss: 0.000460 2022/10/27 22:23:25 - mmengine - INFO - Epoch(train) [204][400/586] lr: 5.000000e-06 eta: 0:16:45 time: 0.284542 data_time: 0.027613 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.893422 loss: 0.000463 2022/10/27 22:23:39 - mmengine - INFO - Epoch(train) [204][450/586] lr: 5.000000e-06 eta: 0:16:31 time: 0.285231 data_time: 0.026943 memory: 11131 loss_kpt: 0.000452 acc_pose: 0.922153 loss: 0.000452 2022/10/27 22:23:54 - mmengine - INFO - Epoch(train) [204][500/586] lr: 5.000000e-06 eta: 0:16:18 time: 0.293007 data_time: 0.028707 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.893112 loss: 0.000461 2022/10/27 22:24:08 - mmengine - INFO - Epoch(train) [204][550/586] lr: 5.000000e-06 eta: 0:16:04 time: 0.287853 data_time: 0.028456 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.901860 loss: 0.000463 2022/10/27 22:24:19 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:24:33 - mmengine - INFO - Epoch(train) [205][50/586] lr: 5.000000e-06 eta: 0:15:41 time: 0.294248 data_time: 0.034589 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.906842 loss: 0.000461 2022/10/27 22:24:48 - mmengine - INFO - Epoch(train) [205][100/586] lr: 5.000000e-06 eta: 0:15:27 time: 0.288294 data_time: 0.028497 memory: 11131 loss_kpt: 0.000450 acc_pose: 0.941627 loss: 0.000450 2022/10/27 22:25:02 - mmengine - INFO - Epoch(train) [205][150/586] lr: 5.000000e-06 eta: 0:15:14 time: 0.289916 data_time: 0.028454 memory: 11131 loss_kpt: 0.000461 acc_pose: 0.883724 loss: 0.000461 2022/10/27 22:25:17 - mmengine - INFO - Epoch(train) [205][200/586] lr: 5.000000e-06 eta: 0:15:00 time: 0.293152 data_time: 0.027462 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.879210 loss: 0.000462 2022/10/27 22:25:31 - mmengine - INFO - Epoch(train) [205][250/586] lr: 5.000000e-06 eta: 0:14:47 time: 0.285679 data_time: 0.029563 memory: 11131 loss_kpt: 0.000455 acc_pose: 0.886781 loss: 0.000455 2022/10/27 22:25:46 - mmengine - INFO - Epoch(train) [205][300/586] lr: 5.000000e-06 eta: 0:14:33 time: 0.287924 data_time: 0.027825 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.899922 loss: 0.000463 2022/10/27 22:26:00 - mmengine - INFO - Epoch(train) [205][350/586] lr: 5.000000e-06 eta: 0:14:19 time: 0.286640 data_time: 0.027916 memory: 11131 loss_kpt: 0.000456 acc_pose: 0.916973 loss: 0.000456 2022/10/27 22:26:15 - mmengine - INFO - Epoch(train) [205][400/586] lr: 5.000000e-06 eta: 0:14:06 time: 0.288279 data_time: 0.027301 memory: 11131 loss_kpt: 0.000469 acc_pose: 0.853794 loss: 0.000469 2022/10/27 22:26:29 - mmengine - INFO - Epoch(train) [205][450/586] lr: 5.000000e-06 eta: 0:13:52 time: 0.288552 data_time: 0.033673 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.893258 loss: 0.000462 2022/10/27 22:26:31 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:26:43 - mmengine - INFO - Epoch(train) [205][500/586] lr: 5.000000e-06 eta: 0:13:39 time: 0.289749 data_time: 0.032440 memory: 11131 loss_kpt: 0.000453 acc_pose: 0.912773 loss: 0.000453 2022/10/27 22:26:58 - mmengine - INFO - Epoch(train) [205][550/586] lr: 5.000000e-06 eta: 0:13:25 time: 0.286356 data_time: 0.029956 memory: 11131 loss_kpt: 0.000451 acc_pose: 0.864632 loss: 0.000451 2022/10/27 22:27:08 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:27:23 - mmengine - INFO - Epoch(train) [206][50/586] lr: 5.000000e-06 eta: 0:13:02 time: 0.297037 data_time: 0.035562 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.886241 loss: 0.000466 2022/10/27 22:27:38 - mmengine - INFO - Epoch(train) [206][100/586] lr: 5.000000e-06 eta: 0:12:48 time: 0.289066 data_time: 0.027563 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.913444 loss: 0.000464 2022/10/27 22:27:52 - mmengine - INFO - Epoch(train) [206][150/586] lr: 5.000000e-06 eta: 0:12:34 time: 0.286327 data_time: 0.028698 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.882652 loss: 0.000462 2022/10/27 22:28:06 - mmengine - INFO - Epoch(train) [206][200/586] lr: 5.000000e-06 eta: 0:12:21 time: 0.287079 data_time: 0.030409 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.905530 loss: 0.000463 2022/10/27 22:28:21 - mmengine - INFO - Epoch(train) [206][250/586] lr: 5.000000e-06 eta: 0:12:07 time: 0.287880 data_time: 0.028891 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.869276 loss: 0.000466 2022/10/27 22:28:35 - mmengine - INFO - Epoch(train) [206][300/586] lr: 5.000000e-06 eta: 0:11:54 time: 0.295515 data_time: 0.032322 memory: 11131 loss_kpt: 0.000452 acc_pose: 0.872463 loss: 0.000452 2022/10/27 22:28:50 - mmengine - INFO - Epoch(train) [206][350/586] lr: 5.000000e-06 eta: 0:11:40 time: 0.289278 data_time: 0.029133 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.900200 loss: 0.000462 2022/10/27 22:29:04 - mmengine - INFO - Epoch(train) [206][400/586] lr: 5.000000e-06 eta: 0:11:27 time: 0.282490 data_time: 0.030211 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.936603 loss: 0.000471 2022/10/27 22:29:18 - mmengine - INFO - Epoch(train) [206][450/586] lr: 5.000000e-06 eta: 0:11:13 time: 0.282688 data_time: 0.029075 memory: 11131 loss_kpt: 0.000459 acc_pose: 0.881244 loss: 0.000459 2022/10/27 22:29:33 - mmengine - INFO - Epoch(train) [206][500/586] lr: 5.000000e-06 eta: 0:11:00 time: 0.298153 data_time: 0.029426 memory: 11131 loss_kpt: 0.000451 acc_pose: 0.891895 loss: 0.000451 2022/10/27 22:29:48 - mmengine - INFO - Epoch(train) [206][550/586] lr: 5.000000e-06 eta: 0:10:46 time: 0.291243 data_time: 0.031384 memory: 11131 loss_kpt: 0.000465 acc_pose: 0.956195 loss: 0.000465 2022/10/27 22:29:58 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:30:12 - mmengine - INFO - Epoch(train) [207][50/586] lr: 5.000000e-06 eta: 0:10:22 time: 0.294409 data_time: 0.037319 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.946604 loss: 0.000470 2022/10/27 22:30:27 - mmengine - INFO - Epoch(train) [207][100/586] lr: 5.000000e-06 eta: 0:10:09 time: 0.292044 data_time: 0.026945 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.904361 loss: 0.000458 2022/10/27 22:30:42 - mmengine - INFO - Epoch(train) [207][150/586] lr: 5.000000e-06 eta: 0:09:55 time: 0.289240 data_time: 0.029327 memory: 11131 loss_kpt: 0.000455 acc_pose: 0.870981 loss: 0.000455 2022/10/27 22:30:56 - mmengine - INFO - Epoch(train) [207][200/586] lr: 5.000000e-06 eta: 0:09:42 time: 0.290313 data_time: 0.032572 memory: 11131 loss_kpt: 0.000453 acc_pose: 0.874015 loss: 0.000453 2022/10/27 22:31:10 - mmengine - INFO - Epoch(train) [207][250/586] lr: 5.000000e-06 eta: 0:09:28 time: 0.284873 data_time: 0.027057 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.859189 loss: 0.000471 2022/10/27 22:31:20 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:31:25 - mmengine - INFO - Epoch(train) [207][300/586] lr: 5.000000e-06 eta: 0:09:15 time: 0.289527 data_time: 0.029841 memory: 11131 loss_kpt: 0.000454 acc_pose: 0.897328 loss: 0.000454 2022/10/27 22:31:39 - mmengine - INFO - Epoch(train) [207][350/586] lr: 5.000000e-06 eta: 0:09:01 time: 0.287948 data_time: 0.032346 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.858850 loss: 0.000462 2022/10/27 22:31:54 - mmengine - INFO - Epoch(train) [207][400/586] lr: 5.000000e-06 eta: 0:08:48 time: 0.285274 data_time: 0.028255 memory: 11131 loss_kpt: 0.000465 acc_pose: 0.887410 loss: 0.000465 2022/10/27 22:32:08 - mmengine - INFO - Epoch(train) [207][450/586] lr: 5.000000e-06 eta: 0:08:34 time: 0.290243 data_time: 0.028305 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.893641 loss: 0.000464 2022/10/27 22:32:22 - mmengine - INFO - Epoch(train) [207][500/586] lr: 5.000000e-06 eta: 0:08:20 time: 0.284853 data_time: 0.030879 memory: 11131 loss_kpt: 0.000468 acc_pose: 0.893743 loss: 0.000468 2022/10/27 22:32:37 - mmengine - INFO - Epoch(train) [207][550/586] lr: 5.000000e-06 eta: 0:08:07 time: 0.285131 data_time: 0.028015 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.887983 loss: 0.000466 2022/10/27 22:32:47 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:33:02 - mmengine - INFO - Epoch(train) [208][50/586] lr: 5.000000e-06 eta: 0:07:43 time: 0.300308 data_time: 0.036842 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.919068 loss: 0.000466 2022/10/27 22:33:16 - mmengine - INFO - Epoch(train) [208][100/586] lr: 5.000000e-06 eta: 0:07:30 time: 0.291508 data_time: 0.030984 memory: 11131 loss_kpt: 0.000446 acc_pose: 0.902663 loss: 0.000446 2022/10/27 22:33:31 - mmengine - INFO - Epoch(train) [208][150/586] lr: 5.000000e-06 eta: 0:07:16 time: 0.285178 data_time: 0.029725 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.880795 loss: 0.000471 2022/10/27 22:33:45 - mmengine - INFO - Epoch(train) [208][200/586] lr: 5.000000e-06 eta: 0:07:03 time: 0.288291 data_time: 0.032792 memory: 11131 loss_kpt: 0.000464 acc_pose: 0.905755 loss: 0.000464 2022/10/27 22:34:00 - mmengine - INFO - Epoch(train) [208][250/586] lr: 5.000000e-06 eta: 0:06:49 time: 0.291807 data_time: 0.029302 memory: 11131 loss_kpt: 0.000456 acc_pose: 0.857482 loss: 0.000456 2022/10/27 22:34:14 - mmengine - INFO - Epoch(train) [208][300/586] lr: 5.000000e-06 eta: 0:06:35 time: 0.291562 data_time: 0.033330 memory: 11131 loss_kpt: 0.000453 acc_pose: 0.889487 loss: 0.000453 2022/10/27 22:34:29 - mmengine - INFO - Epoch(train) [208][350/586] lr: 5.000000e-06 eta: 0:06:22 time: 0.291364 data_time: 0.033661 memory: 11131 loss_kpt: 0.000449 acc_pose: 0.891123 loss: 0.000449 2022/10/27 22:34:43 - mmengine - INFO - Epoch(train) [208][400/586] lr: 5.000000e-06 eta: 0:06:08 time: 0.287914 data_time: 0.027885 memory: 11131 loss_kpt: 0.000451 acc_pose: 0.952410 loss: 0.000451 2022/10/27 22:34:57 - mmengine - INFO - Epoch(train) [208][450/586] lr: 5.000000e-06 eta: 0:05:55 time: 0.285426 data_time: 0.029474 memory: 11131 loss_kpt: 0.000477 acc_pose: 0.890300 loss: 0.000477 2022/10/27 22:35:12 - mmengine - INFO - Epoch(train) [208][500/586] lr: 5.000000e-06 eta: 0:05:41 time: 0.295816 data_time: 0.036116 memory: 11131 loss_kpt: 0.000450 acc_pose: 0.889251 loss: 0.000450 2022/10/27 22:35:27 - mmengine - INFO - Epoch(train) [208][550/586] lr: 5.000000e-06 eta: 0:05:28 time: 0.292813 data_time: 0.031343 memory: 11131 loss_kpt: 0.000444 acc_pose: 0.940448 loss: 0.000444 2022/10/27 22:35:37 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:35:52 - mmengine - INFO - Epoch(train) [209][50/586] lr: 5.000000e-06 eta: 0:05:04 time: 0.293902 data_time: 0.037266 memory: 11131 loss_kpt: 0.000447 acc_pose: 0.885483 loss: 0.000447 2022/10/27 22:36:06 - mmengine - INFO - Epoch(train) [209][100/586] lr: 5.000000e-06 eta: 0:04:51 time: 0.285713 data_time: 0.027571 memory: 11131 loss_kpt: 0.000442 acc_pose: 0.870012 loss: 0.000442 2022/10/27 22:36:09 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:36:21 - mmengine - INFO - Epoch(train) [209][150/586] lr: 5.000000e-06 eta: 0:04:37 time: 0.294446 data_time: 0.026788 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.922349 loss: 0.000457 2022/10/27 22:36:36 - mmengine - INFO - Epoch(train) [209][200/586] lr: 5.000000e-06 eta: 0:04:23 time: 0.294368 data_time: 0.032785 memory: 11131 loss_kpt: 0.000455 acc_pose: 0.849640 loss: 0.000455 2022/10/27 22:36:50 - mmengine - INFO - Epoch(train) [209][250/586] lr: 5.000000e-06 eta: 0:04:10 time: 0.289280 data_time: 0.028263 memory: 11131 loss_kpt: 0.000447 acc_pose: 0.922890 loss: 0.000447 2022/10/27 22:37:04 - mmengine - INFO - Epoch(train) [209][300/586] lr: 5.000000e-06 eta: 0:03:56 time: 0.288313 data_time: 0.027880 memory: 11131 loss_kpt: 0.000457 acc_pose: 0.883169 loss: 0.000457 2022/10/27 22:37:19 - mmengine - INFO - Epoch(train) [209][350/586] lr: 5.000000e-06 eta: 0:03:43 time: 0.287032 data_time: 0.028582 memory: 11131 loss_kpt: 0.000455 acc_pose: 0.861894 loss: 0.000455 2022/10/27 22:37:33 - mmengine - INFO - Epoch(train) [209][400/586] lr: 5.000000e-06 eta: 0:03:29 time: 0.292237 data_time: 0.026843 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.914063 loss: 0.000458 2022/10/27 22:37:48 - mmengine - INFO - Epoch(train) [209][450/586] lr: 5.000000e-06 eta: 0:03:16 time: 0.291422 data_time: 0.029967 memory: 11131 loss_kpt: 0.000474 acc_pose: 0.855985 loss: 0.000474 2022/10/27 22:38:02 - mmengine - INFO - Epoch(train) [209][500/586] lr: 5.000000e-06 eta: 0:03:02 time: 0.287156 data_time: 0.032221 memory: 11131 loss_kpt: 0.000452 acc_pose: 0.934588 loss: 0.000452 2022/10/27 22:38:17 - mmengine - INFO - Epoch(train) [209][550/586] lr: 5.000000e-06 eta: 0:02:48 time: 0.285410 data_time: 0.028434 memory: 11131 loss_kpt: 0.000467 acc_pose: 0.867519 loss: 0.000467 2022/10/27 22:38:27 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:38:42 - mmengine - INFO - Epoch(train) [210][50/586] lr: 5.000000e-06 eta: 0:02:25 time: 0.303840 data_time: 0.036365 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.835440 loss: 0.000462 2022/10/27 22:38:57 - mmengine - INFO - Epoch(train) [210][100/586] lr: 5.000000e-06 eta: 0:02:11 time: 0.291557 data_time: 0.028276 memory: 11131 loss_kpt: 0.000470 acc_pose: 0.885990 loss: 0.000470 2022/10/27 22:39:11 - mmengine - INFO - Epoch(train) [210][150/586] lr: 5.000000e-06 eta: 0:01:58 time: 0.288302 data_time: 0.029822 memory: 11131 loss_kpt: 0.000466 acc_pose: 0.879079 loss: 0.000466 2022/10/27 22:39:25 - mmengine - INFO - Epoch(train) [210][200/586] lr: 5.000000e-06 eta: 0:01:44 time: 0.285438 data_time: 0.027465 memory: 11131 loss_kpt: 0.000452 acc_pose: 0.896359 loss: 0.000452 2022/10/27 22:39:40 - mmengine - INFO - Epoch(train) [210][250/586] lr: 5.000000e-06 eta: 0:01:31 time: 0.293302 data_time: 0.027244 memory: 11131 loss_kpt: 0.000471 acc_pose: 0.924898 loss: 0.000471 2022/10/27 22:39:55 - mmengine - INFO - Epoch(train) [210][300/586] lr: 5.000000e-06 eta: 0:01:17 time: 0.292806 data_time: 0.031891 memory: 11131 loss_kpt: 0.000448 acc_pose: 0.867146 loss: 0.000448 2022/10/27 22:40:09 - mmengine - INFO - Epoch(train) [210][350/586] lr: 5.000000e-06 eta: 0:01:04 time: 0.285505 data_time: 0.028431 memory: 11131 loss_kpt: 0.000451 acc_pose: 0.879200 loss: 0.000451 2022/10/27 22:40:23 - mmengine - INFO - Epoch(train) [210][400/586] lr: 5.000000e-06 eta: 0:00:50 time: 0.285466 data_time: 0.028062 memory: 11131 loss_kpt: 0.000458 acc_pose: 0.907205 loss: 0.000458 2022/10/27 22:40:38 - mmengine - INFO - Epoch(train) [210][450/586] lr: 5.000000e-06 eta: 0:00:36 time: 0.290181 data_time: 0.028790 memory: 11131 loss_kpt: 0.000462 acc_pose: 0.867752 loss: 0.000462 2022/10/27 22:40:53 - mmengine - INFO - Epoch(train) [210][500/586] lr: 5.000000e-06 eta: 0:00:23 time: 0.298629 data_time: 0.029941 memory: 11131 loss_kpt: 0.000463 acc_pose: 0.911065 loss: 0.000463 2022/10/27 22:41:00 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:41:07 - mmengine - INFO - Epoch(train) [210][550/586] lr: 5.000000e-06 eta: 0:00:09 time: 0.287406 data_time: 0.033612 memory: 11131 loss_kpt: 0.000449 acc_pose: 0.877573 loss: 0.000449 2022/10/27 22:41:17 - mmengine - INFO - Exp name: td-hm_resnetv1d101_8xb32-210e_coco-384x288_20221027_120558 2022/10/27 22:41:17 - mmengine - INFO - Saving checkpoint at 210 epochs 2022/10/27 22:41:29 - mmengine - INFO - Epoch(val) [210][50/407] eta: 0:00:55 time: 0.156238 data_time: 0.038032 memory: 11131 2022/10/27 22:41:36 - mmengine - INFO - Epoch(val) [210][100/407] eta: 0:00:45 time: 0.147736 data_time: 0.028289 memory: 1836 2022/10/27 22:41:43 - mmengine - INFO - Epoch(val) [210][150/407] eta: 0:00:33 time: 0.131950 data_time: 0.011805 memory: 1836 2022/10/27 22:41:50 - mmengine - INFO - Epoch(val) [210][200/407] eta: 0:00:29 time: 0.143466 data_time: 0.023383 memory: 1836 2022/10/27 22:41:57 - mmengine - INFO - Epoch(val) [210][250/407] eta: 0:00:21 time: 0.137397 data_time: 0.017929 memory: 1836 2022/10/27 22:42:04 - mmengine - INFO - Epoch(val) [210][300/407] eta: 0:00:14 time: 0.134371 data_time: 0.014165 memory: 1836 2022/10/27 22:42:11 - mmengine - INFO - Epoch(val) [210][350/407] eta: 0:00:08 time: 0.142201 data_time: 0.023859 memory: 1836 2022/10/27 22:42:17 - mmengine - INFO - Epoch(val) [210][400/407] eta: 0:00:00 time: 0.126909 data_time: 0.012563 memory: 1836 2022/10/27 22:43:04 - mmengine - INFO - Evaluating CocoMetric... 2022/10/27 22:43:21 - mmengine - INFO - Epoch(val) [210][407/407] coco/AP: 0.748367 coco/AP .5: 0.905660 coco/AP .75: 0.817310 coco/AP (M): 0.705923 coco/AP (L): 0.821867 coco/AR: 0.798300 coco/AR .5: 0.940963 coco/AR .75: 0.860359 coco/AR (M): 0.751297 coco/AR (L): 0.866146 2022/10/27 22:43:21 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221027/resnetv1d101_384/best_coco/AP_epoch_190.pth is removed 2022/10/27 22:43:23 - mmengine - INFO - The best checkpoint with 0.7484 coco/AP at 210 epoch is saved to best_coco/AP_epoch_210.pth.