2022/10/20 10:02:44 - 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: 718181046 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 ------------------------------------------------------------ 2022/10/20 10:02:45 - 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=512) codec = dict( type='MSRAHeatmap', input_size=(192, 256), heatmap_size=(48, 64), sigma=2) 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=152, init_cfg=dict(type='Pretrained', checkpoint='mmcls://resnet152_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=(192, 256), heatmap_size=(48, 64), sigma=2)), 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=(192, 256)), dict( type='GenerateTarget', target_type='heatmap', encoder=dict( type='MSRAHeatmap', input_size=(192, 256), heatmap_size=(48, 64), sigma=2)), 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=(192, 256)), 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=(192, 256)), dict( type='GenerateTarget', target_type='heatmap', encoder=dict( type='MSRAHeatmap', input_size=(192, 256), heatmap_size=(48, 64), sigma=2)), 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=(192, 256)), 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=(192, 256)), 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/20221020/resnetv1d152_256/' 2022/10/20 10:03:27 - 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. 2022/10/20 10:03:27 - 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. 2022/10/20 10:03:27 - 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. 2022/10/20 10:03:27 - 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. 2022/10/20 10:03:27 - 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. 2022/10/20 10:03:27 - 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. 2022/10/20 10:03:27 - 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. 2022/10/20 10:03:27 - 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. 2022/10/20 10:03:31 - 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. 2022/10/20 10:03:33 - 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. 2022/10/20 10:04:00 - 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. 2022/10/20 10:04:00 - 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://resnet152_v1d backbone.stem.0.bn.weight - torch.Size([32]): PretrainedInit: load from mmcls://resnet152_v1d backbone.stem.0.bn.bias - torch.Size([32]): PretrainedInit: load from mmcls://resnet152_v1d backbone.stem.1.conv.weight - torch.Size([32, 32, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.stem.1.bn.weight - torch.Size([32]): PretrainedInit: load from mmcls://resnet152_v1d backbone.stem.1.bn.bias - torch.Size([32]): PretrainedInit: load from mmcls://resnet152_v1d backbone.stem.2.conv.weight - torch.Size([64, 32, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.stem.2.bn.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.stem.2.bn.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.conv1.weight - torch.Size([64, 64, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.bn1.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.bn1.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.bn2.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.bn2.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.bn3.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.bn3.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.downsample.0.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.downsample.1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.0.downsample.1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.1.conv1.weight - torch.Size([64, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.1.bn1.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.1.bn1.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.1.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.1.bn2.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.1.bn2.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.1.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.1.bn3.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.1.bn3.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.2.conv1.weight - torch.Size([64, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.2.bn1.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.2.bn1.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.2.conv2.weight - torch.Size([64, 64, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.2.bn2.weight - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.2.bn2.bias - torch.Size([64]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.2.conv3.weight - torch.Size([256, 64, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.2.bn3.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer1.2.bn3.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.conv1.weight - torch.Size([128, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.downsample.1.weight - torch.Size([512, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.downsample.2.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.0.downsample.2.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.1.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.1.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.1.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.1.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.1.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.1.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.1.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.1.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.1.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.2.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.2.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.2.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.2.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.2.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.2.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.2.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.2.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.2.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.3.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.3.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.3.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.3.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.3.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.3.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.3.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.3.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.3.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.4.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.4.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.4.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.4.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.4.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.4.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.4.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.4.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.4.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.5.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.5.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.5.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.5.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.5.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.5.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.5.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.5.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.5.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.6.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.6.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.6.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.6.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.6.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.6.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.6.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.6.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.6.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.7.conv1.weight - torch.Size([128, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.7.bn1.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.7.bn1.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.7.conv2.weight - torch.Size([128, 128, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.7.bn2.weight - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.7.bn2.bias - torch.Size([128]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.7.conv3.weight - torch.Size([512, 128, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.7.bn3.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer2.7.bn3.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.conv1.weight - torch.Size([256, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.downsample.1.weight - torch.Size([1024, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.downsample.2.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.0.downsample.2.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.1.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.1.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.1.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.1.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.1.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.1.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.1.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.1.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.1.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.2.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.2.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.2.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.2.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.2.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.2.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.2.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.2.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.2.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.3.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.3.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.3.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.3.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.3.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.3.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.3.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.3.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.3.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.4.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.4.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.4.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.4.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.4.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.4.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.4.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.4.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.4.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.5.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.5.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.5.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.5.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.5.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.5.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.5.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.5.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.5.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.6.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.6.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.6.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.6.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.6.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.6.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.6.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.6.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.6.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.7.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.7.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.7.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.7.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.7.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.7.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.7.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.7.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.7.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.8.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.8.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.8.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.8.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.8.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.8.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.8.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.8.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.8.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.9.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.9.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.9.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.9.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.9.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.9.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.9.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.9.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.9.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.10.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.10.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.10.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.10.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.10.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.10.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.10.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.10.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.10.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.11.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.11.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.11.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.11.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.11.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.11.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.11.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.11.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.11.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.12.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.12.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.12.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.12.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.12.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.12.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.12.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.12.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.12.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.13.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.13.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.13.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.13.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.13.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.13.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.13.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.13.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.13.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.14.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.14.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.14.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.14.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.14.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.14.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.14.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.14.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.14.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.15.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.15.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.15.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.15.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.15.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.15.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.15.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.15.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.15.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.16.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.16.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.16.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.16.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.16.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.16.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.16.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.16.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.16.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.17.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.17.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.17.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.17.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.17.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.17.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.17.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.17.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.17.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.18.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.18.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.18.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.18.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.18.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.18.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.18.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.18.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.18.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.19.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.19.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.19.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.19.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.19.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.19.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.19.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.19.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.19.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.20.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.20.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.20.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.20.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.20.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.20.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.20.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.20.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.20.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.21.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.21.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.21.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.21.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.21.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.21.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.21.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.21.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.21.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.22.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.22.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.22.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.22.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.22.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.22.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.22.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.22.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.22.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.23.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.23.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.23.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.23.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.23.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.23.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.23.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.23.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.23.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.24.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.24.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.24.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.24.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.24.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.24.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.24.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.24.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.24.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.25.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.25.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.25.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.25.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.25.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.25.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.25.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.25.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.25.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.26.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.26.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.26.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.26.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.26.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.26.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.26.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.26.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.26.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.27.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.27.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.27.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.27.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.27.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.27.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.27.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.27.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.27.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.28.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.28.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.28.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.28.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.28.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.28.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.28.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.28.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.28.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.29.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.29.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.29.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.29.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.29.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.29.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.29.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.29.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.29.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.30.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.30.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.30.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.30.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.30.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.30.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.30.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.30.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.30.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.31.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.31.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.31.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.31.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.31.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.31.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.31.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.31.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.31.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.32.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.32.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.32.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.32.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.32.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.32.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.32.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.32.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.32.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.33.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.33.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.33.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.33.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.33.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.33.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.33.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.33.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.33.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.34.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.34.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.34.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.34.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.34.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.34.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.34.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.34.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.34.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.35.conv1.weight - torch.Size([256, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.35.bn1.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.35.bn1.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.35.conv2.weight - torch.Size([256, 256, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.35.bn2.weight - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.35.bn2.bias - torch.Size([256]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.35.conv3.weight - torch.Size([1024, 256, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.35.bn3.weight - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer3.35.bn3.bias - torch.Size([1024]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.conv1.weight - torch.Size([512, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.bn1.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.bn1.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.bn2.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.bn2.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.bn3.weight - torch.Size([2048]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.bn3.bias - torch.Size([2048]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.downsample.1.weight - torch.Size([2048, 1024, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.downsample.2.weight - torch.Size([2048]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.0.downsample.2.bias - torch.Size([2048]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.1.conv1.weight - torch.Size([512, 2048, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.1.bn1.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.1.bn1.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.1.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.1.bn2.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.1.bn2.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.1.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.1.bn3.weight - torch.Size([2048]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.1.bn3.bias - torch.Size([2048]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.2.conv1.weight - torch.Size([512, 2048, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.2.bn1.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.2.bn1.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.2.conv2.weight - torch.Size([512, 512, 3, 3]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.2.bn2.weight - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.2.bn2.bias - torch.Size([512]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.2.conv3.weight - torch.Size([2048, 512, 1, 1]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.2.bn3.weight - torch.Size([2048]): PretrainedInit: load from mmcls://resnet152_v1d backbone.layer4.2.bn3.bias - torch.Size([2048]): PretrainedInit: load from mmcls://resnet152_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 2022/10/20 10:04:00 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256 by HardDiskBackend. 2022/10/20 10:04:19 - mmengine - INFO - Epoch(train) [1][50/586] lr: 4.954910e-05 eta: 12:40:54 time: 0.371145 data_time: 0.104987 memory: 7326 loss_kpt: 0.002168 acc_pose: 0.200357 loss: 0.002168 2022/10/20 10:04:30 - mmengine - INFO - Epoch(train) [1][100/586] lr: 9.959920e-05 eta: 10:17:07 time: 0.231127 data_time: 0.026522 memory: 7326 loss_kpt: 0.001789 acc_pose: 0.419944 loss: 0.001789 2022/10/20 10:04:41 - mmengine - INFO - Epoch(train) [1][150/586] lr: 1.496493e-04 eta: 9:21:06 time: 0.219465 data_time: 0.024833 memory: 7326 loss_kpt: 0.001540 acc_pose: 0.552513 loss: 0.001540 2022/10/20 10:04:53 - mmengine - INFO - Epoch(train) [1][200/586] lr: 1.996994e-04 eta: 8:59:39 time: 0.232455 data_time: 0.025026 memory: 7326 loss_kpt: 0.001389 acc_pose: 0.565341 loss: 0.001389 2022/10/20 10:05:05 - mmengine - INFO - Epoch(train) [1][250/586] lr: 2.497495e-04 eta: 8:53:21 time: 0.248712 data_time: 0.028858 memory: 7326 loss_kpt: 0.001316 acc_pose: 0.559109 loss: 0.001316 2022/10/20 10:05:16 - mmengine - INFO - Epoch(train) [1][300/586] lr: 2.997996e-04 eta: 8:39:36 time: 0.220868 data_time: 0.023031 memory: 7326 loss_kpt: 0.001266 acc_pose: 0.520646 loss: 0.001266 2022/10/20 10:05:28 - mmengine - INFO - Epoch(train) [1][350/586] lr: 3.498497e-04 eta: 8:35:35 time: 0.240938 data_time: 0.028045 memory: 7326 loss_kpt: 0.001246 acc_pose: 0.486523 loss: 0.001246 2022/10/20 10:05:39 - mmengine - INFO - Epoch(train) [1][400/586] lr: 3.998998e-04 eta: 8:27:09 time: 0.219935 data_time: 0.026356 memory: 7326 loss_kpt: 0.001223 acc_pose: 0.596971 loss: 0.001223 2022/10/20 10:05:50 - mmengine - INFO - Epoch(train) [1][450/586] lr: 4.499499e-04 eta: 8:20:17 time: 0.218713 data_time: 0.026054 memory: 7326 loss_kpt: 0.001232 acc_pose: 0.539639 loss: 0.001232 2022/10/20 10:06:01 - mmengine - INFO - Epoch(train) [1][500/586] lr: 5.000000e-04 eta: 8:13:59 time: 0.215006 data_time: 0.021917 memory: 7326 loss_kpt: 0.001205 acc_pose: 0.628354 loss: 0.001205 2022/10/20 10:06:13 - mmengine - INFO - Epoch(train) [1][550/586] lr: 5.000000e-04 eta: 8:12:00 time: 0.232254 data_time: 0.024471 memory: 7326 loss_kpt: 0.001196 acc_pose: 0.610557 loss: 0.001196 2022/10/20 10:06:20 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:06:32 - mmengine - INFO - Epoch(train) [2][50/586] lr: 5.000000e-04 eta: 7:41:27 time: 0.226183 data_time: 0.030445 memory: 7326 loss_kpt: 0.001200 acc_pose: 0.575150 loss: 0.001200 2022/10/20 10:06:43 - mmengine - INFO - Epoch(train) [2][100/586] lr: 5.000000e-04 eta: 7:40:04 time: 0.218066 data_time: 0.022643 memory: 7326 loss_kpt: 0.001148 acc_pose: 0.598486 loss: 0.001148 2022/10/20 10:06:54 - mmengine - INFO - Epoch(train) [2][150/586] lr: 5.000000e-04 eta: 7:38:37 time: 0.216433 data_time: 0.025743 memory: 7326 loss_kpt: 0.001097 acc_pose: 0.678015 loss: 0.001097 2022/10/20 10:07:06 - mmengine - INFO - Epoch(train) [2][200/586] lr: 5.000000e-04 eta: 7:40:59 time: 0.244746 data_time: 0.032226 memory: 7326 loss_kpt: 0.001089 acc_pose: 0.600901 loss: 0.001089 2022/10/20 10:07:17 - mmengine - INFO - Epoch(train) [2][250/586] lr: 5.000000e-04 eta: 7:41:11 time: 0.229382 data_time: 0.024301 memory: 7326 loss_kpt: 0.001078 acc_pose: 0.651258 loss: 0.001078 2022/10/20 10:07:28 - mmengine - INFO - Epoch(train) [2][300/586] lr: 5.000000e-04 eta: 7:40:51 time: 0.225101 data_time: 0.023217 memory: 7326 loss_kpt: 0.001092 acc_pose: 0.664331 loss: 0.001092 2022/10/20 10:07:39 - mmengine - INFO - Epoch(train) [2][350/586] lr: 5.000000e-04 eta: 7:39:32 time: 0.216043 data_time: 0.023401 memory: 7326 loss_kpt: 0.001099 acc_pose: 0.625413 loss: 0.001099 2022/10/20 10:07:54 - mmengine - INFO - Epoch(train) [2][400/586] lr: 5.000000e-04 eta: 7:46:54 time: 0.298979 data_time: 0.038684 memory: 7326 loss_kpt: 0.001082 acc_pose: 0.706601 loss: 0.001082 2022/10/20 10:07:58 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:08:07 - mmengine - INFO - Epoch(train) [2][450/586] lr: 5.000000e-04 eta: 7:48:45 time: 0.250163 data_time: 0.032493 memory: 7326 loss_kpt: 0.001063 acc_pose: 0.736169 loss: 0.001063 2022/10/20 10:08:18 - mmengine - INFO - Epoch(train) [2][500/586] lr: 5.000000e-04 eta: 7:47:27 time: 0.218733 data_time: 0.025932 memory: 7326 loss_kpt: 0.001038 acc_pose: 0.680331 loss: 0.001038 2022/10/20 10:08:29 - mmengine - INFO - Epoch(train) [2][550/586] lr: 5.000000e-04 eta: 7:46:25 time: 0.220577 data_time: 0.022846 memory: 7326 loss_kpt: 0.001044 acc_pose: 0.693123 loss: 0.001044 2022/10/20 10:08:37 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:08:51 - mmengine - INFO - Epoch(train) [3][50/586] lr: 5.000000e-04 eta: 7:36:42 time: 0.281708 data_time: 0.030925 memory: 7326 loss_kpt: 0.001063 acc_pose: 0.696874 loss: 0.001063 2022/10/20 10:09:02 - mmengine - INFO - Epoch(train) [3][100/586] lr: 5.000000e-04 eta: 7:37:11 time: 0.233342 data_time: 0.024033 memory: 7326 loss_kpt: 0.001021 acc_pose: 0.652355 loss: 0.001021 2022/10/20 10:09:13 - mmengine - INFO - Epoch(train) [3][150/586] lr: 5.000000e-04 eta: 7:36:06 time: 0.213560 data_time: 0.024816 memory: 7326 loss_kpt: 0.001000 acc_pose: 0.663214 loss: 0.001000 2022/10/20 10:09:24 - mmengine - INFO - Epoch(train) [3][200/586] lr: 5.000000e-04 eta: 7:35:31 time: 0.219564 data_time: 0.022438 memory: 7326 loss_kpt: 0.000977 acc_pose: 0.746107 loss: 0.000977 2022/10/20 10:09:35 - mmengine - INFO - Epoch(train) [3][250/586] lr: 5.000000e-04 eta: 7:35:01 time: 0.220021 data_time: 0.026214 memory: 7326 loss_kpt: 0.000985 acc_pose: 0.689862 loss: 0.000985 2022/10/20 10:09:47 - mmengine - INFO - Epoch(train) [3][300/586] lr: 5.000000e-04 eta: 7:36:29 time: 0.248542 data_time: 0.031352 memory: 7326 loss_kpt: 0.001038 acc_pose: 0.689147 loss: 0.001038 2022/10/20 10:09:59 - mmengine - INFO - Epoch(train) [3][350/586] lr: 5.000000e-04 eta: 7:36:47 time: 0.232522 data_time: 0.024959 memory: 7326 loss_kpt: 0.001010 acc_pose: 0.682256 loss: 0.001010 2022/10/20 10:10:10 - mmengine - INFO - Epoch(train) [3][400/586] lr: 5.000000e-04 eta: 7:36:05 time: 0.217758 data_time: 0.022885 memory: 7326 loss_kpt: 0.000999 acc_pose: 0.673346 loss: 0.000999 2022/10/20 10:10:21 - mmengine - INFO - Epoch(train) [3][450/586] lr: 5.000000e-04 eta: 7:35:18 time: 0.215524 data_time: 0.024552 memory: 7326 loss_kpt: 0.000991 acc_pose: 0.767282 loss: 0.000991 2022/10/20 10:10:32 - mmengine - INFO - Epoch(train) [3][500/586] lr: 5.000000e-04 eta: 7:34:51 time: 0.220707 data_time: 0.023783 memory: 7326 loss_kpt: 0.001034 acc_pose: 0.704094 loss: 0.001034 2022/10/20 10:10:44 - mmengine - INFO - Epoch(train) [3][550/586] lr: 5.000000e-04 eta: 7:35:27 time: 0.238253 data_time: 0.026961 memory: 7326 loss_kpt: 0.000980 acc_pose: 0.686420 loss: 0.000980 2022/10/20 10:10:51 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:11:03 - mmengine - INFO - Epoch(train) [4][50/586] lr: 5.000000e-04 eta: 7:26:08 time: 0.226516 data_time: 0.031371 memory: 7326 loss_kpt: 0.000990 acc_pose: 0.682177 loss: 0.000990 2022/10/20 10:11:14 - mmengine - INFO - Epoch(train) [4][100/586] lr: 5.000000e-04 eta: 7:25:48 time: 0.218065 data_time: 0.022652 memory: 7326 loss_kpt: 0.000971 acc_pose: 0.680223 loss: 0.000971 2022/10/20 10:11:25 - mmengine - INFO - Epoch(train) [4][150/586] lr: 5.000000e-04 eta: 7:25:33 time: 0.219441 data_time: 0.020885 memory: 7326 loss_kpt: 0.000970 acc_pose: 0.686785 loss: 0.000970 2022/10/20 10:11:36 - mmengine - INFO - Epoch(train) [4][200/586] lr: 5.000000e-04 eta: 7:26:12 time: 0.236608 data_time: 0.031884 memory: 7326 loss_kpt: 0.000984 acc_pose: 0.648254 loss: 0.000984 2022/10/20 10:11:46 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:11:47 - mmengine - INFO - Epoch(train) [4][250/586] lr: 5.000000e-04 eta: 7:25:58 time: 0.220166 data_time: 0.023846 memory: 7326 loss_kpt: 0.000955 acc_pose: 0.780488 loss: 0.000955 2022/10/20 10:11:59 - mmengine - INFO - Epoch(train) [4][300/586] lr: 5.000000e-04 eta: 7:25:58 time: 0.224990 data_time: 0.028469 memory: 7326 loss_kpt: 0.000966 acc_pose: 0.743345 loss: 0.000966 2022/10/20 10:12:10 - mmengine - INFO - Epoch(train) [4][350/586] lr: 5.000000e-04 eta: 7:26:25 time: 0.234394 data_time: 0.024713 memory: 7326 loss_kpt: 0.000950 acc_pose: 0.733897 loss: 0.000950 2022/10/20 10:12:25 - mmengine - INFO - Epoch(train) [4][400/586] lr: 5.000000e-04 eta: 7:29:09 time: 0.283882 data_time: 0.036001 memory: 7326 loss_kpt: 0.000954 acc_pose: 0.782722 loss: 0.000954 2022/10/20 10:12:38 - mmengine - INFO - Epoch(train) [4][450/586] lr: 5.000000e-04 eta: 7:31:04 time: 0.269112 data_time: 0.036816 memory: 7326 loss_kpt: 0.000937 acc_pose: 0.683388 loss: 0.000937 2022/10/20 10:12:49 - mmengine - INFO - Epoch(train) [4][500/586] lr: 5.000000e-04 eta: 7:30:54 time: 0.224258 data_time: 0.024378 memory: 7326 loss_kpt: 0.000969 acc_pose: 0.739328 loss: 0.000969 2022/10/20 10:13:07 - mmengine - INFO - Epoch(train) [4][550/586] lr: 5.000000e-04 eta: 7:36:50 time: 0.364220 data_time: 0.121879 memory: 7326 loss_kpt: 0.000944 acc_pose: 0.714346 loss: 0.000944 2022/10/20 10:13:15 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:13:27 - mmengine - INFO - Epoch(train) [5][50/586] lr: 5.000000e-04 eta: 7:30:05 time: 0.237431 data_time: 0.034564 memory: 7326 loss_kpt: 0.000952 acc_pose: 0.650544 loss: 0.000952 2022/10/20 10:13:38 - mmengine - INFO - Epoch(train) [5][100/586] lr: 5.000000e-04 eta: 7:29:46 time: 0.220938 data_time: 0.022908 memory: 7326 loss_kpt: 0.000897 acc_pose: 0.743657 loss: 0.000897 2022/10/20 10:13:49 - mmengine - INFO - Epoch(train) [5][150/586] lr: 5.000000e-04 eta: 7:29:13 time: 0.214641 data_time: 0.024460 memory: 7326 loss_kpt: 0.000953 acc_pose: 0.631844 loss: 0.000953 2022/10/20 10:14:00 - mmengine - INFO - Epoch(train) [5][200/586] lr: 5.000000e-04 eta: 7:29:06 time: 0.225279 data_time: 0.031305 memory: 7326 loss_kpt: 0.000932 acc_pose: 0.699442 loss: 0.000932 2022/10/20 10:14:12 - mmengine - INFO - Epoch(train) [5][250/586] lr: 5.000000e-04 eta: 7:29:02 time: 0.226638 data_time: 0.021813 memory: 7326 loss_kpt: 0.000913 acc_pose: 0.610644 loss: 0.000913 2022/10/20 10:14:24 - mmengine - INFO - Epoch(train) [5][300/586] lr: 5.000000e-04 eta: 7:29:22 time: 0.237385 data_time: 0.028979 memory: 7326 loss_kpt: 0.000907 acc_pose: 0.698717 loss: 0.000907 2022/10/20 10:14:35 - mmengine - INFO - Epoch(train) [5][350/586] lr: 5.000000e-04 eta: 7:29:11 time: 0.223981 data_time: 0.022542 memory: 7326 loss_kpt: 0.000935 acc_pose: 0.649323 loss: 0.000935 2022/10/20 10:14:46 - mmengine - INFO - Epoch(train) [5][400/586] lr: 5.000000e-04 eta: 7:29:16 time: 0.231359 data_time: 0.022187 memory: 7326 loss_kpt: 0.000920 acc_pose: 0.680059 loss: 0.000920 2022/10/20 10:14:57 - mmengine - INFO - Epoch(train) [5][450/586] lr: 5.000000e-04 eta: 7:28:55 time: 0.219193 data_time: 0.021858 memory: 7326 loss_kpt: 0.000910 acc_pose: 0.786420 loss: 0.000910 2022/10/20 10:15:09 - mmengine - INFO - Epoch(train) [5][500/586] lr: 5.000000e-04 eta: 7:29:13 time: 0.238087 data_time: 0.023078 memory: 7326 loss_kpt: 0.000926 acc_pose: 0.714916 loss: 0.000926 2022/10/20 10:15:21 - mmengine - INFO - Epoch(train) [5][550/586] lr: 5.000000e-04 eta: 7:29:10 time: 0.228098 data_time: 0.024536 memory: 7326 loss_kpt: 0.000918 acc_pose: 0.722940 loss: 0.000918 2022/10/20 10:15:28 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:15:40 - mmengine - INFO - Epoch(train) [6][50/586] lr: 5.000000e-04 eta: 7:23:31 time: 0.227217 data_time: 0.034182 memory: 7326 loss_kpt: 0.000901 acc_pose: 0.778261 loss: 0.000901 2022/10/20 10:15:44 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:15:50 - mmengine - INFO - Epoch(train) [6][100/586] lr: 5.000000e-04 eta: 7:23:07 time: 0.214837 data_time: 0.022677 memory: 7326 loss_kpt: 0.000907 acc_pose: 0.668354 loss: 0.000907 2022/10/20 10:16:02 - mmengine - INFO - Epoch(train) [6][150/586] lr: 5.000000e-04 eta: 7:23:07 time: 0.227225 data_time: 0.021774 memory: 7326 loss_kpt: 0.000872 acc_pose: 0.734611 loss: 0.000872 2022/10/20 10:16:13 - mmengine - INFO - Epoch(train) [6][200/586] lr: 5.000000e-04 eta: 7:23:13 time: 0.230661 data_time: 0.025661 memory: 7326 loss_kpt: 0.000918 acc_pose: 0.737305 loss: 0.000918 2022/10/20 10:16:24 - mmengine - INFO - Epoch(train) [6][250/586] lr: 5.000000e-04 eta: 7:22:59 time: 0.220240 data_time: 0.026994 memory: 7326 loss_kpt: 0.000887 acc_pose: 0.746891 loss: 0.000887 2022/10/20 10:16:35 - mmengine - INFO - Epoch(train) [6][300/586] lr: 5.000000e-04 eta: 7:22:50 time: 0.222664 data_time: 0.026722 memory: 7326 loss_kpt: 0.000905 acc_pose: 0.705219 loss: 0.000905 2022/10/20 10:16:48 - mmengine - INFO - Epoch(train) [6][350/586] lr: 5.000000e-04 eta: 7:23:20 time: 0.244059 data_time: 0.045487 memory: 7326 loss_kpt: 0.000904 acc_pose: 0.714713 loss: 0.000904 2022/10/20 10:17:02 - mmengine - INFO - Epoch(train) [6][400/586] lr: 5.000000e-04 eta: 7:25:09 time: 0.289262 data_time: 0.026478 memory: 7326 loss_kpt: 0.000910 acc_pose: 0.645236 loss: 0.000910 2022/10/20 10:17:14 - mmengine - INFO - Epoch(train) [6][450/586] lr: 5.000000e-04 eta: 7:25:38 time: 0.245573 data_time: 0.029255 memory: 7326 loss_kpt: 0.000898 acc_pose: 0.722190 loss: 0.000898 2022/10/20 10:17:26 - mmengine - INFO - Epoch(train) [6][500/586] lr: 5.000000e-04 eta: 7:25:27 time: 0.223615 data_time: 0.023099 memory: 7326 loss_kpt: 0.000891 acc_pose: 0.707831 loss: 0.000891 2022/10/20 10:17:37 - mmengine - INFO - Epoch(train) [6][550/586] lr: 5.000000e-04 eta: 7:25:17 time: 0.223835 data_time: 0.023815 memory: 7326 loss_kpt: 0.000908 acc_pose: 0.743578 loss: 0.000908 2022/10/20 10:17:45 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:17:57 - mmengine - INFO - Epoch(train) [7][50/586] lr: 5.000000e-04 eta: 7:20:53 time: 0.238374 data_time: 0.031490 memory: 7326 loss_kpt: 0.000870 acc_pose: 0.688080 loss: 0.000870 2022/10/20 10:18:08 - mmengine - INFO - Epoch(train) [7][100/586] lr: 5.000000e-04 eta: 7:20:34 time: 0.216611 data_time: 0.023047 memory: 7326 loss_kpt: 0.000911 acc_pose: 0.732575 loss: 0.000911 2022/10/20 10:18:18 - mmengine - INFO - Epoch(train) [7][150/586] lr: 5.000000e-04 eta: 7:20:14 time: 0.216046 data_time: 0.023393 memory: 7326 loss_kpt: 0.000885 acc_pose: 0.718605 loss: 0.000885 2022/10/20 10:18:29 - mmengine - INFO - Epoch(train) [7][200/586] lr: 5.000000e-04 eta: 7:19:58 time: 0.217889 data_time: 0.023313 memory: 7326 loss_kpt: 0.000897 acc_pose: 0.660697 loss: 0.000897 2022/10/20 10:18:41 - mmengine - INFO - Epoch(train) [7][250/586] lr: 5.000000e-04 eta: 7:20:02 time: 0.230487 data_time: 0.023839 memory: 7326 loss_kpt: 0.000880 acc_pose: 0.703009 loss: 0.000880 2022/10/20 10:18:53 - mmengine - INFO - Epoch(train) [7][300/586] lr: 5.000000e-04 eta: 7:20:08 time: 0.232373 data_time: 0.027799 memory: 7326 loss_kpt: 0.000875 acc_pose: 0.767140 loss: 0.000875 2022/10/20 10:19:04 - mmengine - INFO - Epoch(train) [7][350/586] lr: 5.000000e-04 eta: 7:20:02 time: 0.224629 data_time: 0.024580 memory: 7326 loss_kpt: 0.000876 acc_pose: 0.782764 loss: 0.000876 2022/10/20 10:19:15 - mmengine - INFO - Epoch(train) [7][400/586] lr: 5.000000e-04 eta: 7:19:59 time: 0.226858 data_time: 0.023710 memory: 7326 loss_kpt: 0.000885 acc_pose: 0.753393 loss: 0.000885 2022/10/20 10:19:27 - mmengine - INFO - Epoch(train) [7][450/586] lr: 5.000000e-04 eta: 7:20:00 time: 0.229842 data_time: 0.023122 memory: 7326 loss_kpt: 0.000897 acc_pose: 0.670089 loss: 0.000897 2022/10/20 10:19:35 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:19:38 - mmengine - INFO - Epoch(train) [7][500/586] lr: 5.000000e-04 eta: 7:20:07 time: 0.233925 data_time: 0.023406 memory: 7326 loss_kpt: 0.000864 acc_pose: 0.711931 loss: 0.000864 2022/10/20 10:19:50 - mmengine - INFO - Epoch(train) [7][550/586] lr: 5.000000e-04 eta: 7:20:00 time: 0.224489 data_time: 0.023097 memory: 7326 loss_kpt: 0.000865 acc_pose: 0.794576 loss: 0.000865 2022/10/20 10:19:57 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:20:09 - mmengine - INFO - Epoch(train) [8][50/586] lr: 5.000000e-04 eta: 7:15:59 time: 0.226588 data_time: 0.032926 memory: 7326 loss_kpt: 0.000857 acc_pose: 0.814063 loss: 0.000857 2022/10/20 10:20:20 - mmengine - INFO - Epoch(train) [8][100/586] lr: 5.000000e-04 eta: 7:15:53 time: 0.223804 data_time: 0.021630 memory: 7326 loss_kpt: 0.000860 acc_pose: 0.748741 loss: 0.000860 2022/10/20 10:20:31 - mmengine - INFO - Epoch(train) [8][150/586] lr: 5.000000e-04 eta: 7:15:54 time: 0.228467 data_time: 0.022840 memory: 7326 loss_kpt: 0.000873 acc_pose: 0.607403 loss: 0.000873 2022/10/20 10:20:42 - mmengine - INFO - Epoch(train) [8][200/586] lr: 5.000000e-04 eta: 7:15:38 time: 0.216254 data_time: 0.022266 memory: 7326 loss_kpt: 0.000839 acc_pose: 0.741547 loss: 0.000839 2022/10/20 10:20:53 - mmengine - INFO - Epoch(train) [8][250/586] lr: 5.000000e-04 eta: 7:15:29 time: 0.221575 data_time: 0.028395 memory: 7326 loss_kpt: 0.000870 acc_pose: 0.802751 loss: 0.000870 2022/10/20 10:21:05 - mmengine - INFO - Epoch(train) [8][300/586] lr: 5.000000e-04 eta: 7:15:25 time: 0.225262 data_time: 0.023773 memory: 7326 loss_kpt: 0.000863 acc_pose: 0.840205 loss: 0.000863 2022/10/20 10:21:16 - mmengine - INFO - Epoch(train) [8][350/586] lr: 5.000000e-04 eta: 7:15:37 time: 0.237503 data_time: 0.030870 memory: 7326 loss_kpt: 0.000860 acc_pose: 0.645043 loss: 0.000860 2022/10/20 10:21:29 - mmengine - INFO - Epoch(train) [8][400/586] lr: 5.000000e-04 eta: 7:16:16 time: 0.258324 data_time: 0.029154 memory: 7326 loss_kpt: 0.000893 acc_pose: 0.784517 loss: 0.000893 2022/10/20 10:21:41 - mmengine - INFO - Epoch(train) [8][450/586] lr: 5.000000e-04 eta: 7:16:20 time: 0.232589 data_time: 0.031730 memory: 7326 loss_kpt: 0.000884 acc_pose: 0.737070 loss: 0.000884 2022/10/20 10:21:52 - mmengine - INFO - Epoch(train) [8][500/586] lr: 5.000000e-04 eta: 7:16:16 time: 0.226199 data_time: 0.024318 memory: 7326 loss_kpt: 0.000854 acc_pose: 0.767530 loss: 0.000854 2022/10/20 10:22:04 - mmengine - INFO - Epoch(train) [8][550/586] lr: 5.000000e-04 eta: 7:16:11 time: 0.226312 data_time: 0.022669 memory: 7326 loss_kpt: 0.000843 acc_pose: 0.733166 loss: 0.000843 2022/10/20 10:22:12 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:22:23 - mmengine - INFO - Epoch(train) [9][50/586] lr: 5.000000e-04 eta: 7:12:42 time: 0.227358 data_time: 0.028086 memory: 7326 loss_kpt: 0.000870 acc_pose: 0.766902 loss: 0.000870 2022/10/20 10:22:34 - mmengine - INFO - Epoch(train) [9][100/586] lr: 5.000000e-04 eta: 7:12:33 time: 0.221343 data_time: 0.023883 memory: 7326 loss_kpt: 0.000856 acc_pose: 0.760534 loss: 0.000856 2022/10/20 10:22:45 - mmengine - INFO - Epoch(train) [9][150/586] lr: 5.000000e-04 eta: 7:12:22 time: 0.218998 data_time: 0.021493 memory: 7326 loss_kpt: 0.000848 acc_pose: 0.796447 loss: 0.000848 2022/10/20 10:22:57 - mmengine - INFO - Epoch(train) [9][200/586] lr: 5.000000e-04 eta: 7:12:16 time: 0.223658 data_time: 0.026231 memory: 7326 loss_kpt: 0.000831 acc_pose: 0.694698 loss: 0.000831 2022/10/20 10:23:08 - mmengine - INFO - Epoch(train) [9][250/586] lr: 5.000000e-04 eta: 7:12:24 time: 0.235274 data_time: 0.024171 memory: 7326 loss_kpt: 0.000865 acc_pose: 0.685690 loss: 0.000865 2022/10/20 10:23:19 - mmengine - INFO - Epoch(train) [9][300/586] lr: 5.000000e-04 eta: 7:12:11 time: 0.218512 data_time: 0.027354 memory: 7326 loss_kpt: 0.000851 acc_pose: 0.775749 loss: 0.000851 2022/10/20 10:23:22 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:23:30 - mmengine - INFO - Epoch(train) [9][350/586] lr: 5.000000e-04 eta: 7:11:55 time: 0.215145 data_time: 0.022297 memory: 7326 loss_kpt: 0.000830 acc_pose: 0.726578 loss: 0.000830 2022/10/20 10:23:42 - mmengine - INFO - Epoch(train) [9][400/586] lr: 5.000000e-04 eta: 7:11:55 time: 0.229199 data_time: 0.029496 memory: 7326 loss_kpt: 0.000838 acc_pose: 0.751519 loss: 0.000838 2022/10/20 10:23:53 - mmengine - INFO - Epoch(train) [9][450/586] lr: 5.000000e-04 eta: 7:11:52 time: 0.226463 data_time: 0.030296 memory: 7326 loss_kpt: 0.000854 acc_pose: 0.739593 loss: 0.000854 2022/10/20 10:24:04 - mmengine - INFO - Epoch(train) [9][500/586] lr: 5.000000e-04 eta: 7:11:53 time: 0.230601 data_time: 0.022785 memory: 7326 loss_kpt: 0.000851 acc_pose: 0.645850 loss: 0.000851 2022/10/20 10:24:15 - mmengine - INFO - Epoch(train) [9][550/586] lr: 5.000000e-04 eta: 7:11:44 time: 0.221223 data_time: 0.021544 memory: 7326 loss_kpt: 0.000838 acc_pose: 0.771763 loss: 0.000838 2022/10/20 10:24:23 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:24:35 - mmengine - INFO - Epoch(train) [10][50/586] lr: 5.000000e-04 eta: 7:08:40 time: 0.229326 data_time: 0.029490 memory: 7326 loss_kpt: 0.000863 acc_pose: 0.769484 loss: 0.000863 2022/10/20 10:24:46 - mmengine - INFO - Epoch(train) [10][100/586] lr: 5.000000e-04 eta: 7:08:38 time: 0.226079 data_time: 0.029027 memory: 7326 loss_kpt: 0.000861 acc_pose: 0.765779 loss: 0.000861 2022/10/20 10:24:58 - mmengine - INFO - Epoch(train) [10][150/586] lr: 5.000000e-04 eta: 7:08:36 time: 0.226557 data_time: 0.024502 memory: 7326 loss_kpt: 0.000846 acc_pose: 0.815964 loss: 0.000846 2022/10/20 10:25:08 - mmengine - INFO - Epoch(train) [10][200/586] lr: 5.000000e-04 eta: 7:08:24 time: 0.217913 data_time: 0.022241 memory: 7326 loss_kpt: 0.000846 acc_pose: 0.718043 loss: 0.000846 2022/10/20 10:25:19 - mmengine - INFO - Epoch(train) [10][250/586] lr: 5.000000e-04 eta: 7:08:14 time: 0.219575 data_time: 0.023658 memory: 7326 loss_kpt: 0.000835 acc_pose: 0.818828 loss: 0.000835 2022/10/20 10:25:31 - mmengine - INFO - Epoch(train) [10][300/586] lr: 5.000000e-04 eta: 7:08:14 time: 0.228875 data_time: 0.033820 memory: 7326 loss_kpt: 0.000831 acc_pose: 0.753801 loss: 0.000831 2022/10/20 10:25:43 - mmengine - INFO - Epoch(train) [10][350/586] lr: 5.000000e-04 eta: 7:08:21 time: 0.235878 data_time: 0.024074 memory: 7326 loss_kpt: 0.000842 acc_pose: 0.690036 loss: 0.000842 2022/10/20 10:25:56 - mmengine - INFO - Epoch(train) [10][400/586] lr: 5.000000e-04 eta: 7:09:09 time: 0.276150 data_time: 0.047966 memory: 7326 loss_kpt: 0.000835 acc_pose: 0.742751 loss: 0.000835 2022/10/20 10:26:09 - mmengine - INFO - Epoch(train) [10][450/586] lr: 5.000000e-04 eta: 7:09:34 time: 0.254137 data_time: 0.033420 memory: 7326 loss_kpt: 0.000823 acc_pose: 0.698598 loss: 0.000823 2022/10/20 10:26:21 - mmengine - INFO - Epoch(train) [10][500/586] lr: 5.000000e-04 eta: 7:09:34 time: 0.230658 data_time: 0.027162 memory: 7326 loss_kpt: 0.000824 acc_pose: 0.681105 loss: 0.000824 2022/10/20 10:26:32 - mmengine - INFO - Epoch(train) [10][550/586] lr: 5.000000e-04 eta: 7:09:31 time: 0.227659 data_time: 0.024148 memory: 7326 loss_kpt: 0.000838 acc_pose: 0.782099 loss: 0.000838 2022/10/20 10:26:40 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:26:40 - mmengine - INFO - Saving checkpoint at 10 epochs 2022/10/20 10:27:04 - mmengine - INFO - Epoch(val) [10][50/407] eta: 0:02:18 time: 0.388776 data_time: 0.307782 memory: 7326 2022/10/20 10:27:09 - mmengine - INFO - Epoch(val) [10][100/407] eta: 0:00:35 time: 0.116350 data_time: 0.035152 memory: 1680 2022/10/20 10:27:15 - mmengine - INFO - Epoch(val) [10][150/407] eta: 0:00:29 time: 0.116012 data_time: 0.035079 memory: 1680 2022/10/20 10:27:21 - mmengine - INFO - Epoch(val) [10][200/407] eta: 0:00:25 time: 0.120929 data_time: 0.042749 memory: 1680 2022/10/20 10:27:27 - mmengine - INFO - Epoch(val) [10][250/407] eta: 0:00:17 time: 0.113104 data_time: 0.033778 memory: 1680 2022/10/20 10:27:33 - mmengine - INFO - Epoch(val) [10][300/407] eta: 0:00:12 time: 0.117496 data_time: 0.037690 memory: 1680 2022/10/20 10:27:39 - mmengine - INFO - Epoch(val) [10][350/407] eta: 0:00:06 time: 0.117044 data_time: 0.038179 memory: 1680 2022/10/20 10:27:45 - mmengine - INFO - Epoch(val) [10][400/407] eta: 0:00:00 time: 0.121043 data_time: 0.043819 memory: 1680 2022/10/20 10:28:18 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 10:28:31 - mmengine - INFO - Epoch(val) [10][407/407] coco/AP: 0.638360 coco/AP .5: 0.862104 coco/AP .75: 0.714445 coco/AP (M): 0.603237 coco/AP (L): 0.705743 coco/AR: 0.703133 coco/AR .5: 0.907903 coco/AR .75: 0.773929 coco/AR (M): 0.658099 coco/AR (L): 0.767261 2022/10/20 10:28:37 - mmengine - INFO - The best checkpoint with 0.6384 coco/AP at 10 epoch is saved to best_coco/AP_epoch_10.pth. 2022/10/20 10:28:48 - mmengine - INFO - Epoch(train) [11][50/586] lr: 5.000000e-04 eta: 7:06:43 time: 0.227825 data_time: 0.030179 memory: 7326 loss_kpt: 0.000843 acc_pose: 0.776089 loss: 0.000843 2022/10/20 10:28:59 - mmengine - INFO - Epoch(train) [11][100/586] lr: 5.000000e-04 eta: 7:06:39 time: 0.225095 data_time: 0.026082 memory: 7326 loss_kpt: 0.000837 acc_pose: 0.803774 loss: 0.000837 2022/10/20 10:29:09 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:29:11 - mmengine - INFO - Epoch(train) [11][150/586] lr: 5.000000e-04 eta: 7:06:39 time: 0.230169 data_time: 0.024577 memory: 7326 loss_kpt: 0.000824 acc_pose: 0.717610 loss: 0.000824 2022/10/20 10:29:23 - mmengine - INFO - Epoch(train) [11][200/586] lr: 5.000000e-04 eta: 7:06:40 time: 0.231337 data_time: 0.023640 memory: 7326 loss_kpt: 0.000827 acc_pose: 0.815900 loss: 0.000827 2022/10/20 10:29:34 - mmengine - INFO - Epoch(train) [11][250/586] lr: 5.000000e-04 eta: 7:06:37 time: 0.226666 data_time: 0.021446 memory: 7326 loss_kpt: 0.000820 acc_pose: 0.765132 loss: 0.000820 2022/10/20 10:29:45 - mmengine - INFO - Epoch(train) [11][300/586] lr: 5.000000e-04 eta: 7:06:30 time: 0.223600 data_time: 0.026130 memory: 7326 loss_kpt: 0.000836 acc_pose: 0.695787 loss: 0.000836 2022/10/20 10:29:56 - mmengine - INFO - Epoch(train) [11][350/586] lr: 5.000000e-04 eta: 7:06:24 time: 0.224028 data_time: 0.024755 memory: 7326 loss_kpt: 0.000840 acc_pose: 0.763699 loss: 0.000840 2022/10/20 10:30:08 - mmengine - INFO - Epoch(train) [11][400/586] lr: 5.000000e-04 eta: 7:06:21 time: 0.227100 data_time: 0.024250 memory: 7326 loss_kpt: 0.000825 acc_pose: 0.726030 loss: 0.000825 2022/10/20 10:30:21 - mmengine - INFO - Epoch(train) [11][450/586] lr: 5.000000e-04 eta: 7:06:46 time: 0.257958 data_time: 0.023378 memory: 7326 loss_kpt: 0.000837 acc_pose: 0.670723 loss: 0.000837 2022/10/20 10:30:34 - mmengine - INFO - Epoch(train) [11][500/586] lr: 5.000000e-04 eta: 7:07:27 time: 0.276053 data_time: 0.035682 memory: 7326 loss_kpt: 0.000827 acc_pose: 0.774693 loss: 0.000827 2022/10/20 10:30:46 - mmengine - INFO - Epoch(train) [11][550/586] lr: 5.000000e-04 eta: 7:07:24 time: 0.228499 data_time: 0.026985 memory: 7326 loss_kpt: 0.000824 acc_pose: 0.792716 loss: 0.000824 2022/10/20 10:30:54 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:31:14 - mmengine - INFO - Epoch(train) [12][50/586] lr: 5.000000e-04 eta: 7:07:24 time: 0.398928 data_time: 0.062552 memory: 7326 loss_kpt: 0.000809 acc_pose: 0.807543 loss: 0.000809 2022/10/20 10:31:26 - mmengine - INFO - Epoch(train) [12][100/586] lr: 5.000000e-04 eta: 7:07:26 time: 0.235016 data_time: 0.022587 memory: 7326 loss_kpt: 0.000790 acc_pose: 0.784909 loss: 0.000790 2022/10/20 10:31:37 - mmengine - INFO - Epoch(train) [12][150/586] lr: 5.000000e-04 eta: 7:07:18 time: 0.223329 data_time: 0.023076 memory: 7326 loss_kpt: 0.000811 acc_pose: 0.790711 loss: 0.000811 2022/10/20 10:31:48 - mmengine - INFO - Epoch(train) [12][200/586] lr: 5.000000e-04 eta: 7:07:10 time: 0.224132 data_time: 0.025258 memory: 7326 loss_kpt: 0.000837 acc_pose: 0.840747 loss: 0.000837 2022/10/20 10:31:59 - mmengine - INFO - Epoch(train) [12][250/586] lr: 5.000000e-04 eta: 7:07:01 time: 0.221414 data_time: 0.025043 memory: 7326 loss_kpt: 0.000823 acc_pose: 0.746934 loss: 0.000823 2022/10/20 10:32:11 - mmengine - INFO - Epoch(train) [12][300/586] lr: 5.000000e-04 eta: 7:07:00 time: 0.232804 data_time: 0.024068 memory: 7326 loss_kpt: 0.000802 acc_pose: 0.765992 loss: 0.000802 2022/10/20 10:32:22 - mmengine - INFO - Epoch(train) [12][350/586] lr: 5.000000e-04 eta: 7:06:54 time: 0.225815 data_time: 0.028299 memory: 7326 loss_kpt: 0.000847 acc_pose: 0.833958 loss: 0.000847 2022/10/20 10:32:33 - mmengine - INFO - Epoch(train) [12][400/586] lr: 5.000000e-04 eta: 7:06:46 time: 0.224046 data_time: 0.026665 memory: 7326 loss_kpt: 0.000818 acc_pose: 0.729343 loss: 0.000818 2022/10/20 10:32:44 - mmengine - INFO - Epoch(train) [12][450/586] lr: 5.000000e-04 eta: 7:06:31 time: 0.215378 data_time: 0.021754 memory: 7326 loss_kpt: 0.000807 acc_pose: 0.766292 loss: 0.000807 2022/10/20 10:32:55 - mmengine - INFO - Epoch(train) [12][500/586] lr: 5.000000e-04 eta: 7:06:23 time: 0.223687 data_time: 0.026324 memory: 7326 loss_kpt: 0.000799 acc_pose: 0.842155 loss: 0.000799 2022/10/20 10:33:07 - mmengine - INFO - Epoch(train) [12][550/586] lr: 5.000000e-04 eta: 7:06:24 time: 0.235425 data_time: 0.024505 memory: 7326 loss_kpt: 0.000810 acc_pose: 0.752257 loss: 0.000810 2022/10/20 10:33:08 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:33:15 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:33:27 - mmengine - INFO - Epoch(train) [13][50/586] lr: 5.000000e-04 eta: 7:04:05 time: 0.231730 data_time: 0.034187 memory: 7326 loss_kpt: 0.000808 acc_pose: 0.732806 loss: 0.000808 2022/10/20 10:33:38 - mmengine - INFO - Epoch(train) [13][100/586] lr: 5.000000e-04 eta: 7:04:02 time: 0.229044 data_time: 0.022922 memory: 7326 loss_kpt: 0.000799 acc_pose: 0.807381 loss: 0.000799 2022/10/20 10:33:49 - mmengine - INFO - Epoch(train) [13][150/586] lr: 5.000000e-04 eta: 7:03:59 time: 0.229212 data_time: 0.025418 memory: 7326 loss_kpt: 0.000812 acc_pose: 0.753840 loss: 0.000812 2022/10/20 10:34:01 - mmengine - INFO - Epoch(train) [13][200/586] lr: 5.000000e-04 eta: 7:04:00 time: 0.234675 data_time: 0.025106 memory: 7326 loss_kpt: 0.000809 acc_pose: 0.751777 loss: 0.000809 2022/10/20 10:34:12 - mmengine - INFO - Epoch(train) [13][250/586] lr: 5.000000e-04 eta: 7:03:49 time: 0.220344 data_time: 0.024609 memory: 7326 loss_kpt: 0.000802 acc_pose: 0.663447 loss: 0.000802 2022/10/20 10:34:23 - mmengine - INFO - Epoch(train) [13][300/586] lr: 5.000000e-04 eta: 7:03:43 time: 0.225155 data_time: 0.023390 memory: 7326 loss_kpt: 0.000826 acc_pose: 0.740663 loss: 0.000826 2022/10/20 10:34:35 - mmengine - INFO - Epoch(train) [13][350/586] lr: 5.000000e-04 eta: 7:03:34 time: 0.222962 data_time: 0.027784 memory: 7326 loss_kpt: 0.000802 acc_pose: 0.716967 loss: 0.000802 2022/10/20 10:34:46 - mmengine - INFO - Epoch(train) [13][400/586] lr: 5.000000e-04 eta: 7:03:26 time: 0.222709 data_time: 0.025591 memory: 7326 loss_kpt: 0.000813 acc_pose: 0.732591 loss: 0.000813 2022/10/20 10:34:59 - mmengine - INFO - Epoch(train) [13][450/586] lr: 5.000000e-04 eta: 7:03:51 time: 0.266532 data_time: 0.038025 memory: 7326 loss_kpt: 0.000790 acc_pose: 0.760594 loss: 0.000790 2022/10/20 10:35:11 - mmengine - INFO - Epoch(train) [13][500/586] lr: 5.000000e-04 eta: 7:03:56 time: 0.240993 data_time: 0.025185 memory: 7326 loss_kpt: 0.000799 acc_pose: 0.751042 loss: 0.000799 2022/10/20 10:35:23 - mmengine - INFO - Epoch(train) [13][550/586] lr: 5.000000e-04 eta: 7:03:50 time: 0.227409 data_time: 0.033522 memory: 7326 loss_kpt: 0.000799 acc_pose: 0.701740 loss: 0.000799 2022/10/20 10:35:30 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:35:43 - mmengine - INFO - Epoch(train) [14][50/586] lr: 5.000000e-04 eta: 7:01:48 time: 0.241019 data_time: 0.031063 memory: 7326 loss_kpt: 0.000817 acc_pose: 0.762207 loss: 0.000817 2022/10/20 10:35:54 - mmengine - INFO - Epoch(train) [14][100/586] lr: 5.000000e-04 eta: 7:01:39 time: 0.222588 data_time: 0.023546 memory: 7326 loss_kpt: 0.000820 acc_pose: 0.819745 loss: 0.000820 2022/10/20 10:36:05 - mmengine - INFO - Epoch(train) [14][150/586] lr: 5.000000e-04 eta: 7:01:34 time: 0.227719 data_time: 0.029137 memory: 7326 loss_kpt: 0.000801 acc_pose: 0.781492 loss: 0.000801 2022/10/20 10:36:17 - mmengine - INFO - Epoch(train) [14][200/586] lr: 5.000000e-04 eta: 7:01:31 time: 0.229982 data_time: 0.022151 memory: 7326 loss_kpt: 0.000803 acc_pose: 0.597932 loss: 0.000803 2022/10/20 10:36:28 - mmengine - INFO - Epoch(train) [14][250/586] lr: 5.000000e-04 eta: 7:01:23 time: 0.223834 data_time: 0.021921 memory: 7326 loss_kpt: 0.000805 acc_pose: 0.720266 loss: 0.000805 2022/10/20 10:36:39 - mmengine - INFO - Epoch(train) [14][300/586] lr: 5.000000e-04 eta: 7:01:17 time: 0.225942 data_time: 0.022802 memory: 7326 loss_kpt: 0.000803 acc_pose: 0.813711 loss: 0.000803 2022/10/20 10:36:50 - mmengine - INFO - Epoch(train) [14][350/586] lr: 5.000000e-04 eta: 7:01:08 time: 0.221761 data_time: 0.025854 memory: 7326 loss_kpt: 0.000799 acc_pose: 0.771562 loss: 0.000799 2022/10/20 10:36:58 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:37:02 - mmengine - INFO - Epoch(train) [14][400/586] lr: 5.000000e-04 eta: 7:01:03 time: 0.228027 data_time: 0.026306 memory: 7326 loss_kpt: 0.000811 acc_pose: 0.766898 loss: 0.000811 2022/10/20 10:37:13 - mmengine - INFO - Epoch(train) [14][450/586] lr: 5.000000e-04 eta: 7:00:58 time: 0.227434 data_time: 0.025758 memory: 7326 loss_kpt: 0.000787 acc_pose: 0.715843 loss: 0.000787 2022/10/20 10:37:24 - mmengine - INFO - Epoch(train) [14][500/586] lr: 5.000000e-04 eta: 7:00:47 time: 0.220748 data_time: 0.026479 memory: 7326 loss_kpt: 0.000794 acc_pose: 0.714986 loss: 0.000794 2022/10/20 10:37:36 - mmengine - INFO - Epoch(train) [14][550/586] lr: 5.000000e-04 eta: 7:00:45 time: 0.231865 data_time: 0.023699 memory: 7326 loss_kpt: 0.000795 acc_pose: 0.751011 loss: 0.000795 2022/10/20 10:37:43 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:37:55 - mmengine - INFO - Epoch(train) [15][50/586] lr: 5.000000e-04 eta: 6:58:47 time: 0.235191 data_time: 0.033448 memory: 7326 loss_kpt: 0.000788 acc_pose: 0.777560 loss: 0.000788 2022/10/20 10:38:06 - mmengine - INFO - Epoch(train) [15][100/586] lr: 5.000000e-04 eta: 6:58:36 time: 0.218900 data_time: 0.024469 memory: 7326 loss_kpt: 0.000810 acc_pose: 0.779532 loss: 0.000810 2022/10/20 10:38:17 - mmengine - INFO - Epoch(train) [15][150/586] lr: 5.000000e-04 eta: 6:58:29 time: 0.224218 data_time: 0.026835 memory: 7326 loss_kpt: 0.000787 acc_pose: 0.787993 loss: 0.000787 2022/10/20 10:38:29 - mmengine - INFO - Epoch(train) [15][200/586] lr: 5.000000e-04 eta: 6:58:29 time: 0.235972 data_time: 0.023245 memory: 7326 loss_kpt: 0.000777 acc_pose: 0.775118 loss: 0.000777 2022/10/20 10:38:40 - mmengine - INFO - Epoch(train) [15][250/586] lr: 5.000000e-04 eta: 6:58:23 time: 0.225922 data_time: 0.026907 memory: 7326 loss_kpt: 0.000793 acc_pose: 0.729450 loss: 0.000793 2022/10/20 10:38:52 - mmengine - INFO - Epoch(train) [15][300/586] lr: 5.000000e-04 eta: 6:58:13 time: 0.220589 data_time: 0.022801 memory: 7326 loss_kpt: 0.000795 acc_pose: 0.730289 loss: 0.000795 2022/10/20 10:39:03 - mmengine - INFO - Epoch(train) [15][350/586] lr: 5.000000e-04 eta: 6:58:05 time: 0.222913 data_time: 0.022960 memory: 7326 loss_kpt: 0.000799 acc_pose: 0.752763 loss: 0.000799 2022/10/20 10:39:14 - mmengine - INFO - Epoch(train) [15][400/586] lr: 5.000000e-04 eta: 6:58:01 time: 0.230376 data_time: 0.023560 memory: 7326 loss_kpt: 0.000807 acc_pose: 0.776666 loss: 0.000807 2022/10/20 10:39:25 - mmengine - INFO - Epoch(train) [15][450/586] lr: 5.000000e-04 eta: 6:57:52 time: 0.221835 data_time: 0.022092 memory: 7326 loss_kpt: 0.000775 acc_pose: 0.735618 loss: 0.000775 2022/10/20 10:39:37 - mmengine - INFO - Epoch(train) [15][500/586] lr: 5.000000e-04 eta: 6:57:48 time: 0.230343 data_time: 0.032313 memory: 7326 loss_kpt: 0.000820 acc_pose: 0.807312 loss: 0.000820 2022/10/20 10:39:48 - mmengine - INFO - Epoch(train) [15][550/586] lr: 5.000000e-04 eta: 6:57:39 time: 0.221324 data_time: 0.023797 memory: 7326 loss_kpt: 0.000799 acc_pose: 0.811870 loss: 0.000799 2022/10/20 10:39:56 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:40:08 - mmengine - INFO - Epoch(train) [16][50/586] lr: 5.000000e-04 eta: 6:55:50 time: 0.238228 data_time: 0.035656 memory: 7326 loss_kpt: 0.000800 acc_pose: 0.727585 loss: 0.000800 2022/10/20 10:40:19 - mmengine - INFO - Epoch(train) [16][100/586] lr: 5.000000e-04 eta: 6:55:43 time: 0.224425 data_time: 0.027158 memory: 7326 loss_kpt: 0.000807 acc_pose: 0.788412 loss: 0.000807 2022/10/20 10:40:31 - mmengine - INFO - Epoch(train) [16][150/586] lr: 5.000000e-04 eta: 6:55:40 time: 0.230606 data_time: 0.023681 memory: 7326 loss_kpt: 0.000790 acc_pose: 0.707741 loss: 0.000790 2022/10/20 10:40:42 - mmengine - INFO - Epoch(train) [16][200/586] lr: 5.000000e-04 eta: 6:55:36 time: 0.229632 data_time: 0.021844 memory: 7326 loss_kpt: 0.000789 acc_pose: 0.784591 loss: 0.000789 2022/10/20 10:40:44 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:40:53 - mmengine - INFO - Epoch(train) [16][250/586] lr: 5.000000e-04 eta: 6:55:29 time: 0.224252 data_time: 0.023316 memory: 7326 loss_kpt: 0.000791 acc_pose: 0.744824 loss: 0.000791 2022/10/20 10:41:05 - mmengine - INFO - Epoch(train) [16][300/586] lr: 5.000000e-04 eta: 6:55:23 time: 0.227333 data_time: 0.024144 memory: 7326 loss_kpt: 0.000809 acc_pose: 0.805689 loss: 0.000809 2022/10/20 10:41:16 - mmengine - INFO - Epoch(train) [16][350/586] lr: 5.000000e-04 eta: 6:55:18 time: 0.227724 data_time: 0.030242 memory: 7326 loss_kpt: 0.000788 acc_pose: 0.794682 loss: 0.000788 2022/10/20 10:41:27 - mmengine - INFO - Epoch(train) [16][400/586] lr: 5.000000e-04 eta: 6:55:07 time: 0.218382 data_time: 0.022372 memory: 7326 loss_kpt: 0.000789 acc_pose: 0.710104 loss: 0.000789 2022/10/20 10:41:38 - mmengine - INFO - Epoch(train) [16][450/586] lr: 5.000000e-04 eta: 6:54:57 time: 0.221013 data_time: 0.023410 memory: 7326 loss_kpt: 0.000774 acc_pose: 0.764365 loss: 0.000774 2022/10/20 10:41:49 - mmengine - INFO - Epoch(train) [16][500/586] lr: 5.000000e-04 eta: 6:54:50 time: 0.225222 data_time: 0.026200 memory: 7326 loss_kpt: 0.000787 acc_pose: 0.800088 loss: 0.000787 2022/10/20 10:42:00 - mmengine - INFO - Epoch(train) [16][550/586] lr: 5.000000e-04 eta: 6:54:42 time: 0.223550 data_time: 0.023194 memory: 7326 loss_kpt: 0.000772 acc_pose: 0.729688 loss: 0.000772 2022/10/20 10:42:08 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:42:20 - mmengine - INFO - Epoch(train) [17][50/586] lr: 5.000000e-04 eta: 6:52:56 time: 0.231957 data_time: 0.033781 memory: 7326 loss_kpt: 0.000781 acc_pose: 0.737461 loss: 0.000781 2022/10/20 10:42:31 - mmengine - INFO - Epoch(train) [17][100/586] lr: 5.000000e-04 eta: 6:52:50 time: 0.226094 data_time: 0.024708 memory: 7326 loss_kpt: 0.000764 acc_pose: 0.771724 loss: 0.000764 2022/10/20 10:42:43 - mmengine - INFO - Epoch(train) [17][150/586] lr: 5.000000e-04 eta: 6:52:45 time: 0.227156 data_time: 0.024541 memory: 7326 loss_kpt: 0.000765 acc_pose: 0.771130 loss: 0.000765 2022/10/20 10:42:54 - mmengine - INFO - Epoch(train) [17][200/586] lr: 5.000000e-04 eta: 6:52:41 time: 0.229842 data_time: 0.023722 memory: 7326 loss_kpt: 0.000794 acc_pose: 0.761093 loss: 0.000794 2022/10/20 10:43:05 - mmengine - INFO - Epoch(train) [17][250/586] lr: 5.000000e-04 eta: 6:52:34 time: 0.224717 data_time: 0.029627 memory: 7326 loss_kpt: 0.000802 acc_pose: 0.833012 loss: 0.000802 2022/10/20 10:43:16 - mmengine - INFO - Epoch(train) [17][300/586] lr: 5.000000e-04 eta: 6:52:25 time: 0.221210 data_time: 0.023579 memory: 7326 loss_kpt: 0.000779 acc_pose: 0.758974 loss: 0.000779 2022/10/20 10:43:28 - mmengine - INFO - Epoch(train) [17][350/586] lr: 5.000000e-04 eta: 6:52:15 time: 0.220764 data_time: 0.025004 memory: 7326 loss_kpt: 0.000775 acc_pose: 0.772060 loss: 0.000775 2022/10/20 10:43:39 - mmengine - INFO - Epoch(train) [17][400/586] lr: 5.000000e-04 eta: 6:52:11 time: 0.229823 data_time: 0.023877 memory: 7326 loss_kpt: 0.000776 acc_pose: 0.774142 loss: 0.000776 2022/10/20 10:43:50 - mmengine - INFO - Epoch(train) [17][450/586] lr: 5.000000e-04 eta: 6:52:03 time: 0.222722 data_time: 0.022407 memory: 7326 loss_kpt: 0.000763 acc_pose: 0.803669 loss: 0.000763 2022/10/20 10:44:01 - mmengine - INFO - Epoch(train) [17][500/586] lr: 5.000000e-04 eta: 6:51:55 time: 0.223226 data_time: 0.027115 memory: 7326 loss_kpt: 0.000770 acc_pose: 0.794004 loss: 0.000770 2022/10/20 10:44:12 - mmengine - INFO - Epoch(train) [17][550/586] lr: 5.000000e-04 eta: 6:51:46 time: 0.222489 data_time: 0.026374 memory: 7326 loss_kpt: 0.000786 acc_pose: 0.815039 loss: 0.000786 2022/10/20 10:44:20 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:44:29 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:44:32 - mmengine - INFO - Epoch(train) [18][50/586] lr: 5.000000e-04 eta: 6:50:11 time: 0.240303 data_time: 0.032660 memory: 7326 loss_kpt: 0.000773 acc_pose: 0.751983 loss: 0.000773 2022/10/20 10:44:44 - mmengine - INFO - Epoch(train) [18][100/586] lr: 5.000000e-04 eta: 6:50:06 time: 0.229271 data_time: 0.029042 memory: 7326 loss_kpt: 0.000773 acc_pose: 0.815742 loss: 0.000773 2022/10/20 10:44:55 - mmengine - INFO - Epoch(train) [18][150/586] lr: 5.000000e-04 eta: 6:49:57 time: 0.219902 data_time: 0.025405 memory: 7326 loss_kpt: 0.000755 acc_pose: 0.716006 loss: 0.000755 2022/10/20 10:45:06 - mmengine - INFO - Epoch(train) [18][200/586] lr: 5.000000e-04 eta: 6:49:53 time: 0.230879 data_time: 0.023429 memory: 7326 loss_kpt: 0.000783 acc_pose: 0.799849 loss: 0.000783 2022/10/20 10:45:18 - mmengine - INFO - Epoch(train) [18][250/586] lr: 5.000000e-04 eta: 6:49:48 time: 0.227988 data_time: 0.024247 memory: 7326 loss_kpt: 0.000766 acc_pose: 0.786619 loss: 0.000766 2022/10/20 10:45:29 - mmengine - INFO - Epoch(train) [18][300/586] lr: 5.000000e-04 eta: 6:49:41 time: 0.225363 data_time: 0.023758 memory: 7326 loss_kpt: 0.000755 acc_pose: 0.795089 loss: 0.000755 2022/10/20 10:45:41 - mmengine - INFO - Epoch(train) [18][350/586] lr: 5.000000e-04 eta: 6:49:38 time: 0.231541 data_time: 0.024862 memory: 7326 loss_kpt: 0.000758 acc_pose: 0.782605 loss: 0.000758 2022/10/20 10:45:51 - mmengine - INFO - Epoch(train) [18][400/586] lr: 5.000000e-04 eta: 6:49:25 time: 0.215564 data_time: 0.023370 memory: 7326 loss_kpt: 0.000772 acc_pose: 0.724547 loss: 0.000772 2022/10/20 10:46:02 - mmengine - INFO - Epoch(train) [18][450/586] lr: 5.000000e-04 eta: 6:49:17 time: 0.222330 data_time: 0.027006 memory: 7326 loss_kpt: 0.000760 acc_pose: 0.745902 loss: 0.000760 2022/10/20 10:46:14 - mmengine - INFO - Epoch(train) [18][500/586] lr: 5.000000e-04 eta: 6:49:09 time: 0.222849 data_time: 0.028636 memory: 7326 loss_kpt: 0.000777 acc_pose: 0.792604 loss: 0.000777 2022/10/20 10:46:25 - mmengine - INFO - Epoch(train) [18][550/586] lr: 5.000000e-04 eta: 6:49:03 time: 0.227284 data_time: 0.026492 memory: 7326 loss_kpt: 0.000768 acc_pose: 0.778566 loss: 0.000768 2022/10/20 10:46:33 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:46:44 - mmengine - INFO - Epoch(train) [19][50/586] lr: 5.000000e-04 eta: 6:47:23 time: 0.222162 data_time: 0.028065 memory: 7326 loss_kpt: 0.000782 acc_pose: 0.840546 loss: 0.000782 2022/10/20 10:46:55 - mmengine - INFO - Epoch(train) [19][100/586] lr: 5.000000e-04 eta: 6:47:14 time: 0.220549 data_time: 0.023636 memory: 7326 loss_kpt: 0.000753 acc_pose: 0.762182 loss: 0.000753 2022/10/20 10:47:07 - mmengine - INFO - Epoch(train) [19][150/586] lr: 5.000000e-04 eta: 6:47:07 time: 0.225358 data_time: 0.026517 memory: 7326 loss_kpt: 0.000773 acc_pose: 0.834057 loss: 0.000773 2022/10/20 10:47:18 - mmengine - INFO - Epoch(train) [19][200/586] lr: 5.000000e-04 eta: 6:47:05 time: 0.234415 data_time: 0.022730 memory: 7326 loss_kpt: 0.000765 acc_pose: 0.770413 loss: 0.000765 2022/10/20 10:47:30 - mmengine - INFO - Epoch(train) [19][250/586] lr: 5.000000e-04 eta: 6:47:01 time: 0.231424 data_time: 0.022963 memory: 7326 loss_kpt: 0.000770 acc_pose: 0.775996 loss: 0.000770 2022/10/20 10:47:41 - mmengine - INFO - Epoch(train) [19][300/586] lr: 5.000000e-04 eta: 6:46:52 time: 0.221413 data_time: 0.024996 memory: 7326 loss_kpt: 0.000760 acc_pose: 0.768486 loss: 0.000760 2022/10/20 10:47:52 - mmengine - INFO - Epoch(train) [19][350/586] lr: 5.000000e-04 eta: 6:46:43 time: 0.221320 data_time: 0.024636 memory: 7326 loss_kpt: 0.000751 acc_pose: 0.836980 loss: 0.000751 2022/10/20 10:48:03 - mmengine - INFO - Epoch(train) [19][400/586] lr: 5.000000e-04 eta: 6:46:37 time: 0.226356 data_time: 0.023532 memory: 7326 loss_kpt: 0.000724 acc_pose: 0.713628 loss: 0.000724 2022/10/20 10:48:15 - mmengine - INFO - Epoch(train) [19][450/586] lr: 5.000000e-04 eta: 6:46:31 time: 0.227789 data_time: 0.027178 memory: 7326 loss_kpt: 0.000779 acc_pose: 0.781127 loss: 0.000779 2022/10/20 10:48:15 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:48:26 - mmengine - INFO - Epoch(train) [19][500/586] lr: 5.000000e-04 eta: 6:46:22 time: 0.221557 data_time: 0.023417 memory: 7326 loss_kpt: 0.000743 acc_pose: 0.848116 loss: 0.000743 2022/10/20 10:48:37 - mmengine - INFO - Epoch(train) [19][550/586] lr: 5.000000e-04 eta: 6:46:15 time: 0.224573 data_time: 0.026863 memory: 7326 loss_kpt: 0.000750 acc_pose: 0.824408 loss: 0.000750 2022/10/20 10:48:45 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:48:56 - mmengine - INFO - Epoch(train) [20][50/586] lr: 5.000000e-04 eta: 6:44:44 time: 0.229237 data_time: 0.033087 memory: 7326 loss_kpt: 0.000772 acc_pose: 0.780781 loss: 0.000772 2022/10/20 10:49:08 - mmengine - INFO - Epoch(train) [20][100/586] lr: 5.000000e-04 eta: 6:44:43 time: 0.238217 data_time: 0.024990 memory: 7326 loss_kpt: 0.000754 acc_pose: 0.808285 loss: 0.000754 2022/10/20 10:49:20 - mmengine - INFO - Epoch(train) [20][150/586] lr: 5.000000e-04 eta: 6:44:38 time: 0.228566 data_time: 0.027714 memory: 7326 loss_kpt: 0.000746 acc_pose: 0.819331 loss: 0.000746 2022/10/20 10:49:31 - mmengine - INFO - Epoch(train) [20][200/586] lr: 5.000000e-04 eta: 6:44:34 time: 0.229949 data_time: 0.025278 memory: 7326 loss_kpt: 0.000771 acc_pose: 0.843251 loss: 0.000771 2022/10/20 10:49:43 - mmengine - INFO - Epoch(train) [20][250/586] lr: 5.000000e-04 eta: 6:44:29 time: 0.230648 data_time: 0.024801 memory: 7326 loss_kpt: 0.000755 acc_pose: 0.667672 loss: 0.000755 2022/10/20 10:49:54 - mmengine - INFO - Epoch(train) [20][300/586] lr: 5.000000e-04 eta: 6:44:22 time: 0.225680 data_time: 0.026099 memory: 7326 loss_kpt: 0.000762 acc_pose: 0.806657 loss: 0.000762 2022/10/20 10:50:05 - mmengine - INFO - Epoch(train) [20][350/586] lr: 5.000000e-04 eta: 6:44:15 time: 0.224946 data_time: 0.024156 memory: 7326 loss_kpt: 0.000759 acc_pose: 0.803799 loss: 0.000759 2022/10/20 10:50:16 - mmengine - INFO - Epoch(train) [20][400/586] lr: 5.000000e-04 eta: 6:44:07 time: 0.222289 data_time: 0.023319 memory: 7326 loss_kpt: 0.000767 acc_pose: 0.853084 loss: 0.000767 2022/10/20 10:50:28 - mmengine - INFO - Epoch(train) [20][450/586] lr: 5.000000e-04 eta: 6:44:00 time: 0.226643 data_time: 0.023394 memory: 7326 loss_kpt: 0.000790 acc_pose: 0.822337 loss: 0.000790 2022/10/20 10:50:39 - mmengine - INFO - Epoch(train) [20][500/586] lr: 5.000000e-04 eta: 6:43:53 time: 0.225051 data_time: 0.023971 memory: 7326 loss_kpt: 0.000757 acc_pose: 0.703816 loss: 0.000757 2022/10/20 10:50:50 - mmengine - INFO - Epoch(train) [20][550/586] lr: 5.000000e-04 eta: 6:43:48 time: 0.229933 data_time: 0.024839 memory: 7326 loss_kpt: 0.000745 acc_pose: 0.836616 loss: 0.000745 2022/10/20 10:50:59 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:50:59 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/10/20 10:51:08 - mmengine - INFO - Epoch(val) [20][50/407] eta: 0:00:43 time: 0.121594 data_time: 0.033577 memory: 7326 2022/10/20 10:51:14 - mmengine - INFO - Epoch(val) [20][100/407] eta: 0:00:35 time: 0.117070 data_time: 0.037394 memory: 1680 2022/10/20 10:51:20 - mmengine - INFO - Epoch(val) [20][150/407] eta: 0:00:29 time: 0.113430 data_time: 0.031815 memory: 1680 2022/10/20 10:51:25 - mmengine - INFO - Epoch(val) [20][200/407] eta: 0:00:23 time: 0.111670 data_time: 0.031273 memory: 1680 2022/10/20 10:51:31 - mmengine - INFO - Epoch(val) [20][250/407] eta: 0:00:18 time: 0.116613 data_time: 0.036968 memory: 1680 2022/10/20 10:51:37 - mmengine - INFO - Epoch(val) [20][300/407] eta: 0:00:12 time: 0.118866 data_time: 0.040382 memory: 1680 2022/10/20 10:51:43 - mmengine - INFO - Epoch(val) [20][350/407] eta: 0:00:06 time: 0.119885 data_time: 0.042036 memory: 1680 2022/10/20 10:51:48 - mmengine - INFO - Epoch(val) [20][400/407] eta: 0:00:00 time: 0.100504 data_time: 0.024137 memory: 1680 2022/10/20 10:52:21 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 10:52:34 - mmengine - INFO - Epoch(val) [20][407/407] coco/AP: 0.678698 coco/AP .5: 0.882368 coco/AP .75: 0.755866 coco/AP (M): 0.643793 coco/AP (L): 0.743972 coco/AR: 0.738728 coco/AR .5: 0.922702 coco/AR .75: 0.807777 coco/AR (M): 0.695630 coco/AR (L): 0.800409 2022/10/20 10:52:34 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_10.pth is removed 2022/10/20 10:52:36 - mmengine - INFO - The best checkpoint with 0.6787 coco/AP at 20 epoch is saved to best_coco/AP_epoch_20.pth. 2022/10/20 10:52:47 - mmengine - INFO - Epoch(train) [21][50/586] lr: 5.000000e-04 eta: 6:42:17 time: 0.219981 data_time: 0.028639 memory: 7326 loss_kpt: 0.000766 acc_pose: 0.796142 loss: 0.000766 2022/10/20 10:52:59 - mmengine - INFO - Epoch(train) [21][100/586] lr: 5.000000e-04 eta: 6:42:09 time: 0.223209 data_time: 0.023189 memory: 7326 loss_kpt: 0.000756 acc_pose: 0.779655 loss: 0.000756 2022/10/20 10:53:10 - mmengine - INFO - Epoch(train) [21][150/586] lr: 5.000000e-04 eta: 6:42:05 time: 0.232689 data_time: 0.027708 memory: 7326 loss_kpt: 0.000754 acc_pose: 0.793498 loss: 0.000754 2022/10/20 10:53:22 - mmengine - INFO - Epoch(train) [21][200/586] lr: 5.000000e-04 eta: 6:42:01 time: 0.231145 data_time: 0.027768 memory: 7326 loss_kpt: 0.000762 acc_pose: 0.766383 loss: 0.000762 2022/10/20 10:53:33 - mmengine - INFO - Epoch(train) [21][250/586] lr: 5.000000e-04 eta: 6:41:56 time: 0.230163 data_time: 0.024549 memory: 7326 loss_kpt: 0.000747 acc_pose: 0.839922 loss: 0.000747 2022/10/20 10:53:40 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:53:44 - mmengine - INFO - Epoch(train) [21][300/586] lr: 5.000000e-04 eta: 6:41:48 time: 0.222764 data_time: 0.023192 memory: 7326 loss_kpt: 0.000763 acc_pose: 0.824593 loss: 0.000763 2022/10/20 10:53:55 - mmengine - INFO - Epoch(train) [21][350/586] lr: 5.000000e-04 eta: 6:41:38 time: 0.219398 data_time: 0.023282 memory: 7326 loss_kpt: 0.000751 acc_pose: 0.812748 loss: 0.000751 2022/10/20 10:54:07 - mmengine - INFO - Epoch(train) [21][400/586] lr: 5.000000e-04 eta: 6:41:35 time: 0.234800 data_time: 0.026480 memory: 7326 loss_kpt: 0.000786 acc_pose: 0.802867 loss: 0.000786 2022/10/20 10:54:18 - mmengine - INFO - Epoch(train) [21][450/586] lr: 5.000000e-04 eta: 6:41:27 time: 0.222994 data_time: 0.024022 memory: 7326 loss_kpt: 0.000751 acc_pose: 0.826177 loss: 0.000751 2022/10/20 10:54:29 - mmengine - INFO - Epoch(train) [21][500/586] lr: 5.000000e-04 eta: 6:41:19 time: 0.223297 data_time: 0.022100 memory: 7326 loss_kpt: 0.000770 acc_pose: 0.771406 loss: 0.000770 2022/10/20 10:54:41 - mmengine - INFO - Epoch(train) [21][550/586] lr: 5.000000e-04 eta: 6:41:11 time: 0.222648 data_time: 0.022944 memory: 7326 loss_kpt: 0.000752 acc_pose: 0.797430 loss: 0.000752 2022/10/20 10:54:49 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:55:00 - mmengine - INFO - Epoch(train) [22][50/586] lr: 5.000000e-04 eta: 6:39:50 time: 0.235836 data_time: 0.033269 memory: 7326 loss_kpt: 0.000748 acc_pose: 0.751874 loss: 0.000748 2022/10/20 10:55:12 - mmengine - INFO - Epoch(train) [22][100/586] lr: 5.000000e-04 eta: 6:39:46 time: 0.230495 data_time: 0.029515 memory: 7326 loss_kpt: 0.000746 acc_pose: 0.882621 loss: 0.000746 2022/10/20 10:55:23 - mmengine - INFO - Epoch(train) [22][150/586] lr: 5.000000e-04 eta: 6:39:37 time: 0.222425 data_time: 0.022960 memory: 7326 loss_kpt: 0.000749 acc_pose: 0.824625 loss: 0.000749 2022/10/20 10:55:34 - mmengine - INFO - Epoch(train) [22][200/586] lr: 5.000000e-04 eta: 6:39:31 time: 0.227184 data_time: 0.027975 memory: 7326 loss_kpt: 0.000774 acc_pose: 0.758335 loss: 0.000774 2022/10/20 10:55:45 - mmengine - INFO - Epoch(train) [22][250/586] lr: 5.000000e-04 eta: 6:39:22 time: 0.221122 data_time: 0.022354 memory: 7326 loss_kpt: 0.000731 acc_pose: 0.866143 loss: 0.000731 2022/10/20 10:55:57 - mmengine - INFO - Epoch(train) [22][300/586] lr: 5.000000e-04 eta: 6:39:17 time: 0.229383 data_time: 0.023549 memory: 7326 loss_kpt: 0.000730 acc_pose: 0.784791 loss: 0.000730 2022/10/20 10:56:08 - mmengine - INFO - Epoch(train) [22][350/586] lr: 5.000000e-04 eta: 6:39:12 time: 0.230214 data_time: 0.028878 memory: 7326 loss_kpt: 0.000738 acc_pose: 0.760910 loss: 0.000738 2022/10/20 10:56:20 - mmengine - INFO - Epoch(train) [22][400/586] lr: 5.000000e-04 eta: 6:39:05 time: 0.227205 data_time: 0.024244 memory: 7326 loss_kpt: 0.000758 acc_pose: 0.729423 loss: 0.000758 2022/10/20 10:56:31 - mmengine - INFO - Epoch(train) [22][450/586] lr: 5.000000e-04 eta: 6:38:57 time: 0.222539 data_time: 0.025328 memory: 7326 loss_kpt: 0.000748 acc_pose: 0.806782 loss: 0.000748 2022/10/20 10:56:42 - mmengine - INFO - Epoch(train) [22][500/586] lr: 5.000000e-04 eta: 6:38:48 time: 0.221793 data_time: 0.025357 memory: 7326 loss_kpt: 0.000761 acc_pose: 0.756695 loss: 0.000761 2022/10/20 10:56:53 - mmengine - INFO - Epoch(train) [22][550/586] lr: 5.000000e-04 eta: 6:38:41 time: 0.226140 data_time: 0.026908 memory: 7326 loss_kpt: 0.000744 acc_pose: 0.797815 loss: 0.000744 2022/10/20 10:57:01 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:57:13 - mmengine - INFO - Epoch(train) [23][50/586] lr: 5.000000e-04 eta: 6:37:23 time: 0.232600 data_time: 0.035010 memory: 7326 loss_kpt: 0.000761 acc_pose: 0.779818 loss: 0.000761 2022/10/20 10:57:24 - mmengine - INFO - Epoch(train) [23][100/586] lr: 5.000000e-04 eta: 6:37:12 time: 0.216965 data_time: 0.025116 memory: 7326 loss_kpt: 0.000751 acc_pose: 0.797055 loss: 0.000751 2022/10/20 10:57:26 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:57:35 - mmengine - INFO - Epoch(train) [23][150/586] lr: 5.000000e-04 eta: 6:37:05 time: 0.226530 data_time: 0.025579 memory: 7326 loss_kpt: 0.000726 acc_pose: 0.686009 loss: 0.000726 2022/10/20 10:57:47 - mmengine - INFO - Epoch(train) [23][200/586] lr: 5.000000e-04 eta: 6:36:59 time: 0.227613 data_time: 0.023235 memory: 7326 loss_kpt: 0.000734 acc_pose: 0.817332 loss: 0.000734 2022/10/20 10:57:58 - mmengine - INFO - Epoch(train) [23][250/586] lr: 5.000000e-04 eta: 6:36:51 time: 0.224117 data_time: 0.023328 memory: 7326 loss_kpt: 0.000762 acc_pose: 0.796340 loss: 0.000762 2022/10/20 10:58:09 - mmengine - INFO - Epoch(train) [23][300/586] lr: 5.000000e-04 eta: 6:36:46 time: 0.230845 data_time: 0.023867 memory: 7326 loss_kpt: 0.000758 acc_pose: 0.725380 loss: 0.000758 2022/10/20 10:58:21 - mmengine - INFO - Epoch(train) [23][350/586] lr: 5.000000e-04 eta: 6:36:39 time: 0.225210 data_time: 0.025630 memory: 7326 loss_kpt: 0.000760 acc_pose: 0.726663 loss: 0.000760 2022/10/20 10:58:32 - mmengine - INFO - Epoch(train) [23][400/586] lr: 5.000000e-04 eta: 6:36:32 time: 0.226220 data_time: 0.023339 memory: 7326 loss_kpt: 0.000721 acc_pose: 0.835348 loss: 0.000721 2022/10/20 10:58:43 - mmengine - INFO - Epoch(train) [23][450/586] lr: 5.000000e-04 eta: 6:36:28 time: 0.231533 data_time: 0.027018 memory: 7326 loss_kpt: 0.000755 acc_pose: 0.782877 loss: 0.000755 2022/10/20 10:58:55 - mmengine - INFO - Epoch(train) [23][500/586] lr: 5.000000e-04 eta: 6:36:19 time: 0.222336 data_time: 0.024025 memory: 7326 loss_kpt: 0.000755 acc_pose: 0.797158 loss: 0.000755 2022/10/20 10:59:06 - mmengine - INFO - Epoch(train) [23][550/586] lr: 5.000000e-04 eta: 6:36:09 time: 0.219593 data_time: 0.021687 memory: 7326 loss_kpt: 0.000736 acc_pose: 0.782803 loss: 0.000736 2022/10/20 10:59:13 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 10:59:25 - mmengine - INFO - Epoch(train) [24][50/586] lr: 5.000000e-04 eta: 6:34:54 time: 0.233162 data_time: 0.030856 memory: 7326 loss_kpt: 0.000750 acc_pose: 0.832547 loss: 0.000750 2022/10/20 10:59:37 - mmengine - INFO - Epoch(train) [24][100/586] lr: 5.000000e-04 eta: 6:34:49 time: 0.230535 data_time: 0.029122 memory: 7326 loss_kpt: 0.000745 acc_pose: 0.820998 loss: 0.000745 2022/10/20 10:59:47 - mmengine - INFO - Epoch(train) [24][150/586] lr: 5.000000e-04 eta: 6:34:39 time: 0.219285 data_time: 0.024946 memory: 7326 loss_kpt: 0.000733 acc_pose: 0.818479 loss: 0.000733 2022/10/20 10:59:59 - mmengine - INFO - Epoch(train) [24][200/586] lr: 5.000000e-04 eta: 6:34:30 time: 0.221053 data_time: 0.021530 memory: 7326 loss_kpt: 0.000727 acc_pose: 0.797608 loss: 0.000727 2022/10/20 11:00:10 - mmengine - INFO - Epoch(train) [24][250/586] lr: 5.000000e-04 eta: 6:34:23 time: 0.226021 data_time: 0.022440 memory: 7326 loss_kpt: 0.000735 acc_pose: 0.777405 loss: 0.000735 2022/10/20 11:00:21 - mmengine - INFO - Epoch(train) [24][300/586] lr: 5.000000e-04 eta: 6:34:18 time: 0.229319 data_time: 0.026466 memory: 7326 loss_kpt: 0.000720 acc_pose: 0.796380 loss: 0.000720 2022/10/20 11:00:33 - mmengine - INFO - Epoch(train) [24][350/586] lr: 5.000000e-04 eta: 6:34:12 time: 0.230677 data_time: 0.029433 memory: 7326 loss_kpt: 0.000749 acc_pose: 0.789028 loss: 0.000749 2022/10/20 11:00:44 - mmengine - INFO - Epoch(train) [24][400/586] lr: 5.000000e-04 eta: 6:34:05 time: 0.226089 data_time: 0.023384 memory: 7326 loss_kpt: 0.000740 acc_pose: 0.742687 loss: 0.000740 2022/10/20 11:00:55 - mmengine - INFO - Epoch(train) [24][450/586] lr: 5.000000e-04 eta: 6:33:56 time: 0.219284 data_time: 0.023611 memory: 7326 loss_kpt: 0.000762 acc_pose: 0.776992 loss: 0.000762 2022/10/20 11:01:06 - mmengine - INFO - Epoch(train) [24][500/586] lr: 5.000000e-04 eta: 6:33:47 time: 0.222342 data_time: 0.022923 memory: 7326 loss_kpt: 0.000735 acc_pose: 0.729204 loss: 0.000735 2022/10/20 11:01:11 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:01:18 - mmengine - INFO - Epoch(train) [24][550/586] lr: 5.000000e-04 eta: 6:33:41 time: 0.230278 data_time: 0.027831 memory: 7326 loss_kpt: 0.000736 acc_pose: 0.737134 loss: 0.000736 2022/10/20 11:01:26 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:01:37 - mmengine - INFO - Epoch(train) [25][50/586] lr: 5.000000e-04 eta: 6:32:27 time: 0.227423 data_time: 0.030065 memory: 7326 loss_kpt: 0.000741 acc_pose: 0.778488 loss: 0.000741 2022/10/20 11:01:48 - mmengine - INFO - Epoch(train) [25][100/586] lr: 5.000000e-04 eta: 6:32:17 time: 0.219538 data_time: 0.027150 memory: 7326 loss_kpt: 0.000720 acc_pose: 0.805118 loss: 0.000720 2022/10/20 11:02:00 - mmengine - INFO - Epoch(train) [25][150/586] lr: 5.000000e-04 eta: 6:32:11 time: 0.228748 data_time: 0.026611 memory: 7326 loss_kpt: 0.000756 acc_pose: 0.794931 loss: 0.000756 2022/10/20 11:02:11 - mmengine - INFO - Epoch(train) [25][200/586] lr: 5.000000e-04 eta: 6:32:02 time: 0.220223 data_time: 0.022451 memory: 7326 loss_kpt: 0.000750 acc_pose: 0.822480 loss: 0.000750 2022/10/20 11:02:22 - mmengine - INFO - Epoch(train) [25][250/586] lr: 5.000000e-04 eta: 6:31:57 time: 0.230756 data_time: 0.022307 memory: 7326 loss_kpt: 0.000734 acc_pose: 0.810090 loss: 0.000734 2022/10/20 11:02:34 - mmengine - INFO - Epoch(train) [25][300/586] lr: 5.000000e-04 eta: 6:31:49 time: 0.224413 data_time: 0.025068 memory: 7326 loss_kpt: 0.000738 acc_pose: 0.854331 loss: 0.000738 2022/10/20 11:02:45 - mmengine - INFO - Epoch(train) [25][350/586] lr: 5.000000e-04 eta: 6:31:40 time: 0.220617 data_time: 0.022923 memory: 7326 loss_kpt: 0.000740 acc_pose: 0.806284 loss: 0.000740 2022/10/20 11:02:56 - mmengine - INFO - Epoch(train) [25][400/586] lr: 5.000000e-04 eta: 6:31:34 time: 0.230770 data_time: 0.022934 memory: 7326 loss_kpt: 0.000743 acc_pose: 0.759800 loss: 0.000743 2022/10/20 11:03:08 - mmengine - INFO - Epoch(train) [25][450/586] lr: 5.000000e-04 eta: 6:31:29 time: 0.230368 data_time: 0.029000 memory: 7326 loss_kpt: 0.000733 acc_pose: 0.807639 loss: 0.000733 2022/10/20 11:03:19 - mmengine - INFO - Epoch(train) [25][500/586] lr: 5.000000e-04 eta: 6:31:19 time: 0.219906 data_time: 0.025034 memory: 7326 loss_kpt: 0.000724 acc_pose: 0.803745 loss: 0.000724 2022/10/20 11:03:30 - mmengine - INFO - Epoch(train) [25][550/586] lr: 5.000000e-04 eta: 6:31:11 time: 0.224191 data_time: 0.024501 memory: 7326 loss_kpt: 0.000757 acc_pose: 0.803248 loss: 0.000757 2022/10/20 11:03:38 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:03:49 - mmengine - INFO - Epoch(train) [26][50/586] lr: 5.000000e-04 eta: 6:30:00 time: 0.230333 data_time: 0.029325 memory: 7326 loss_kpt: 0.000739 acc_pose: 0.723408 loss: 0.000739 2022/10/20 11:04:01 - mmengine - INFO - Epoch(train) [26][100/586] lr: 5.000000e-04 eta: 6:29:56 time: 0.231871 data_time: 0.027449 memory: 7326 loss_kpt: 0.000709 acc_pose: 0.846893 loss: 0.000709 2022/10/20 11:04:12 - mmengine - INFO - Epoch(train) [26][150/586] lr: 5.000000e-04 eta: 6:29:49 time: 0.228752 data_time: 0.031603 memory: 7326 loss_kpt: 0.000715 acc_pose: 0.845761 loss: 0.000715 2022/10/20 11:04:23 - mmengine - INFO - Epoch(train) [26][200/586] lr: 5.000000e-04 eta: 6:29:41 time: 0.223199 data_time: 0.022379 memory: 7326 loss_kpt: 0.000712 acc_pose: 0.874904 loss: 0.000712 2022/10/20 11:04:35 - mmengine - INFO - Epoch(train) [26][250/586] lr: 5.000000e-04 eta: 6:29:35 time: 0.228982 data_time: 0.024344 memory: 7326 loss_kpt: 0.000733 acc_pose: 0.843693 loss: 0.000733 2022/10/20 11:04:46 - mmengine - INFO - Epoch(train) [26][300/586] lr: 5.000000e-04 eta: 6:29:26 time: 0.220816 data_time: 0.022022 memory: 7326 loss_kpt: 0.000744 acc_pose: 0.742194 loss: 0.000744 2022/10/20 11:04:58 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:04:58 - mmengine - INFO - Epoch(train) [26][350/586] lr: 5.000000e-04 eta: 6:29:20 time: 0.230422 data_time: 0.021921 memory: 7326 loss_kpt: 0.000742 acc_pose: 0.814633 loss: 0.000742 2022/10/20 11:05:09 - mmengine - INFO - Epoch(train) [26][400/586] lr: 5.000000e-04 eta: 6:29:12 time: 0.223913 data_time: 0.022817 memory: 7326 loss_kpt: 0.000740 acc_pose: 0.832664 loss: 0.000740 2022/10/20 11:05:20 - mmengine - INFO - Epoch(train) [26][450/586] lr: 5.000000e-04 eta: 6:29:03 time: 0.220096 data_time: 0.022155 memory: 7326 loss_kpt: 0.000740 acc_pose: 0.767370 loss: 0.000740 2022/10/20 11:05:31 - mmengine - INFO - Epoch(train) [26][500/586] lr: 5.000000e-04 eta: 6:28:56 time: 0.226844 data_time: 0.023545 memory: 7326 loss_kpt: 0.000717 acc_pose: 0.808266 loss: 0.000717 2022/10/20 11:05:43 - mmengine - INFO - Epoch(train) [26][550/586] lr: 5.000000e-04 eta: 6:28:50 time: 0.231436 data_time: 0.024497 memory: 7326 loss_kpt: 0.000737 acc_pose: 0.792441 loss: 0.000737 2022/10/20 11:05:51 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:06:02 - mmengine - INFO - Epoch(train) [27][50/586] lr: 5.000000e-04 eta: 6:27:43 time: 0.232655 data_time: 0.031259 memory: 7326 loss_kpt: 0.000728 acc_pose: 0.854528 loss: 0.000728 2022/10/20 11:06:13 - mmengine - INFO - Epoch(train) [27][100/586] lr: 5.000000e-04 eta: 6:27:35 time: 0.223975 data_time: 0.025905 memory: 7326 loss_kpt: 0.000754 acc_pose: 0.775184 loss: 0.000754 2022/10/20 11:06:25 - mmengine - INFO - Epoch(train) [27][150/586] lr: 5.000000e-04 eta: 6:27:26 time: 0.223200 data_time: 0.027215 memory: 7326 loss_kpt: 0.000757 acc_pose: 0.808505 loss: 0.000757 2022/10/20 11:06:36 - mmengine - INFO - Epoch(train) [27][200/586] lr: 5.000000e-04 eta: 6:27:24 time: 0.238704 data_time: 0.026601 memory: 7326 loss_kpt: 0.000725 acc_pose: 0.784645 loss: 0.000725 2022/10/20 11:06:48 - mmengine - INFO - Epoch(train) [27][250/586] lr: 5.000000e-04 eta: 6:27:16 time: 0.224581 data_time: 0.023199 memory: 7326 loss_kpt: 0.000720 acc_pose: 0.752513 loss: 0.000720 2022/10/20 11:06:59 - mmengine - INFO - Epoch(train) [27][300/586] lr: 5.000000e-04 eta: 6:27:07 time: 0.222241 data_time: 0.023325 memory: 7326 loss_kpt: 0.000745 acc_pose: 0.806464 loss: 0.000745 2022/10/20 11:07:10 - mmengine - INFO - Epoch(train) [27][350/586] lr: 5.000000e-04 eta: 6:26:58 time: 0.219381 data_time: 0.022841 memory: 7326 loss_kpt: 0.000729 acc_pose: 0.826220 loss: 0.000729 2022/10/20 11:07:21 - mmengine - INFO - Epoch(train) [27][400/586] lr: 5.000000e-04 eta: 6:26:49 time: 0.222125 data_time: 0.023646 memory: 7326 loss_kpt: 0.000715 acc_pose: 0.819078 loss: 0.000715 2022/10/20 11:07:33 - mmengine - INFO - Epoch(train) [27][450/586] lr: 5.000000e-04 eta: 6:26:45 time: 0.235799 data_time: 0.027431 memory: 7326 loss_kpt: 0.000764 acc_pose: 0.787752 loss: 0.000764 2022/10/20 11:07:44 - mmengine - INFO - Epoch(train) [27][500/586] lr: 5.000000e-04 eta: 6:26:38 time: 0.229079 data_time: 0.023300 memory: 7326 loss_kpt: 0.000714 acc_pose: 0.814881 loss: 0.000714 2022/10/20 11:07:55 - mmengine - INFO - Epoch(train) [27][550/586] lr: 5.000000e-04 eta: 6:26:29 time: 0.221809 data_time: 0.023835 memory: 7326 loss_kpt: 0.000706 acc_pose: 0.846781 loss: 0.000706 2022/10/20 11:08:03 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:08:15 - mmengine - INFO - Epoch(train) [28][50/586] lr: 5.000000e-04 eta: 6:25:24 time: 0.233495 data_time: 0.032167 memory: 7326 loss_kpt: 0.000728 acc_pose: 0.831215 loss: 0.000728 2022/10/20 11:08:27 - mmengine - INFO - Epoch(train) [28][100/586] lr: 5.000000e-04 eta: 6:25:20 time: 0.235266 data_time: 0.026752 memory: 7326 loss_kpt: 0.000716 acc_pose: 0.757874 loss: 0.000716 2022/10/20 11:08:38 - mmengine - INFO - Epoch(train) [28][150/586] lr: 5.000000e-04 eta: 6:25:10 time: 0.218925 data_time: 0.027367 memory: 7326 loss_kpt: 0.000710 acc_pose: 0.841181 loss: 0.000710 2022/10/20 11:08:44 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:08:49 - mmengine - INFO - Epoch(train) [28][200/586] lr: 5.000000e-04 eta: 6:25:03 time: 0.226049 data_time: 0.022290 memory: 7326 loss_kpt: 0.000718 acc_pose: 0.765536 loss: 0.000718 2022/10/20 11:09:00 - mmengine - INFO - Epoch(train) [28][250/586] lr: 5.000000e-04 eta: 6:24:55 time: 0.224331 data_time: 0.023615 memory: 7326 loss_kpt: 0.000715 acc_pose: 0.838459 loss: 0.000715 2022/10/20 11:09:11 - mmengine - INFO - Epoch(train) [28][300/586] lr: 5.000000e-04 eta: 6:24:48 time: 0.226249 data_time: 0.021795 memory: 7326 loss_kpt: 0.000727 acc_pose: 0.785988 loss: 0.000727 2022/10/20 11:09:23 - mmengine - INFO - Epoch(train) [28][350/586] lr: 5.000000e-04 eta: 6:24:40 time: 0.226869 data_time: 0.023204 memory: 7326 loss_kpt: 0.000743 acc_pose: 0.787080 loss: 0.000743 2022/10/20 11:09:34 - mmengine - INFO - Epoch(train) [28][400/586] lr: 5.000000e-04 eta: 6:24:32 time: 0.223415 data_time: 0.025167 memory: 7326 loss_kpt: 0.000721 acc_pose: 0.753320 loss: 0.000721 2022/10/20 11:09:45 - mmengine - INFO - Epoch(train) [28][450/586] lr: 5.000000e-04 eta: 6:24:24 time: 0.223449 data_time: 0.022259 memory: 7326 loss_kpt: 0.000724 acc_pose: 0.824817 loss: 0.000724 2022/10/20 11:09:56 - mmengine - INFO - Epoch(train) [28][500/586] lr: 5.000000e-04 eta: 6:24:16 time: 0.226857 data_time: 0.022603 memory: 7326 loss_kpt: 0.000725 acc_pose: 0.803022 loss: 0.000725 2022/10/20 11:10:08 - mmengine - INFO - Epoch(train) [28][550/586] lr: 5.000000e-04 eta: 6:24:12 time: 0.235907 data_time: 0.026637 memory: 7326 loss_kpt: 0.000723 acc_pose: 0.821797 loss: 0.000723 2022/10/20 11:10:16 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:10:28 - mmengine - INFO - Epoch(train) [29][50/586] lr: 5.000000e-04 eta: 6:23:07 time: 0.227697 data_time: 0.031175 memory: 7326 loss_kpt: 0.000716 acc_pose: 0.800866 loss: 0.000716 2022/10/20 11:10:39 - mmengine - INFO - Epoch(train) [29][100/586] lr: 5.000000e-04 eta: 6:22:59 time: 0.226008 data_time: 0.023656 memory: 7326 loss_kpt: 0.000719 acc_pose: 0.827066 loss: 0.000719 2022/10/20 11:10:50 - mmengine - INFO - Epoch(train) [29][150/586] lr: 5.000000e-04 eta: 6:22:51 time: 0.221580 data_time: 0.025154 memory: 7326 loss_kpt: 0.000711 acc_pose: 0.811069 loss: 0.000711 2022/10/20 11:11:01 - mmengine - INFO - Epoch(train) [29][200/586] lr: 5.000000e-04 eta: 6:22:43 time: 0.226798 data_time: 0.027845 memory: 7326 loss_kpt: 0.000723 acc_pose: 0.737651 loss: 0.000723 2022/10/20 11:11:13 - mmengine - INFO - Epoch(train) [29][250/586] lr: 5.000000e-04 eta: 6:22:36 time: 0.227327 data_time: 0.031051 memory: 7326 loss_kpt: 0.000710 acc_pose: 0.747217 loss: 0.000710 2022/10/20 11:11:24 - mmengine - INFO - Epoch(train) [29][300/586] lr: 5.000000e-04 eta: 6:22:29 time: 0.225114 data_time: 0.024572 memory: 7326 loss_kpt: 0.000724 acc_pose: 0.807216 loss: 0.000724 2022/10/20 11:11:35 - mmengine - INFO - Epoch(train) [29][350/586] lr: 5.000000e-04 eta: 6:22:21 time: 0.226933 data_time: 0.023792 memory: 7326 loss_kpt: 0.000744 acc_pose: 0.773144 loss: 0.000744 2022/10/20 11:11:46 - mmengine - INFO - Epoch(train) [29][400/586] lr: 5.000000e-04 eta: 6:22:13 time: 0.224662 data_time: 0.024629 memory: 7326 loss_kpt: 0.000718 acc_pose: 0.804148 loss: 0.000718 2022/10/20 11:11:58 - mmengine - INFO - Epoch(train) [29][450/586] lr: 5.000000e-04 eta: 6:22:07 time: 0.229780 data_time: 0.021963 memory: 7326 loss_kpt: 0.000752 acc_pose: 0.868387 loss: 0.000752 2022/10/20 11:12:09 - mmengine - INFO - Epoch(train) [29][500/586] lr: 5.000000e-04 eta: 6:21:58 time: 0.223381 data_time: 0.026508 memory: 7326 loss_kpt: 0.000736 acc_pose: 0.808867 loss: 0.000736 2022/10/20 11:12:20 - mmengine - INFO - Epoch(train) [29][550/586] lr: 5.000000e-04 eta: 6:21:51 time: 0.226480 data_time: 0.023002 memory: 7326 loss_kpt: 0.000697 acc_pose: 0.757830 loss: 0.000697 2022/10/20 11:12:28 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:12:30 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:12:40 - mmengine - INFO - Epoch(train) [30][50/586] lr: 5.000000e-04 eta: 6:20:49 time: 0.230666 data_time: 0.036485 memory: 7326 loss_kpt: 0.000705 acc_pose: 0.818074 loss: 0.000705 2022/10/20 11:12:52 - mmengine - INFO - Epoch(train) [30][100/586] lr: 5.000000e-04 eta: 6:20:43 time: 0.231357 data_time: 0.024305 memory: 7326 loss_kpt: 0.000703 acc_pose: 0.795511 loss: 0.000703 2022/10/20 11:13:03 - mmengine - INFO - Epoch(train) [30][150/586] lr: 5.000000e-04 eta: 6:20:34 time: 0.221348 data_time: 0.024128 memory: 7326 loss_kpt: 0.000724 acc_pose: 0.783884 loss: 0.000724 2022/10/20 11:13:14 - mmengine - INFO - Epoch(train) [30][200/586] lr: 5.000000e-04 eta: 6:20:26 time: 0.225447 data_time: 0.027980 memory: 7326 loss_kpt: 0.000730 acc_pose: 0.823974 loss: 0.000730 2022/10/20 11:13:25 - mmengine - INFO - Epoch(train) [30][250/586] lr: 5.000000e-04 eta: 6:20:19 time: 0.228463 data_time: 0.023934 memory: 7326 loss_kpt: 0.000719 acc_pose: 0.805308 loss: 0.000719 2022/10/20 11:13:37 - mmengine - INFO - Epoch(train) [30][300/586] lr: 5.000000e-04 eta: 6:20:14 time: 0.233580 data_time: 0.032562 memory: 7326 loss_kpt: 0.000727 acc_pose: 0.830192 loss: 0.000727 2022/10/20 11:13:49 - mmengine - INFO - Epoch(train) [30][350/586] lr: 5.000000e-04 eta: 6:20:09 time: 0.235781 data_time: 0.021988 memory: 7326 loss_kpt: 0.000714 acc_pose: 0.766726 loss: 0.000714 2022/10/20 11:14:00 - mmengine - INFO - Epoch(train) [30][400/586] lr: 5.000000e-04 eta: 6:20:00 time: 0.220753 data_time: 0.024424 memory: 7326 loss_kpt: 0.000717 acc_pose: 0.725513 loss: 0.000717 2022/10/20 11:14:11 - mmengine - INFO - Epoch(train) [30][450/586] lr: 5.000000e-04 eta: 6:19:52 time: 0.224737 data_time: 0.022621 memory: 7326 loss_kpt: 0.000714 acc_pose: 0.798927 loss: 0.000714 2022/10/20 11:14:22 - mmengine - INFO - Epoch(train) [30][500/586] lr: 5.000000e-04 eta: 6:19:42 time: 0.219311 data_time: 0.025700 memory: 7326 loss_kpt: 0.000715 acc_pose: 0.778922 loss: 0.000715 2022/10/20 11:14:34 - mmengine - INFO - Epoch(train) [30][550/586] lr: 5.000000e-04 eta: 6:19:37 time: 0.233858 data_time: 0.028359 memory: 7326 loss_kpt: 0.000711 acc_pose: 0.726368 loss: 0.000711 2022/10/20 11:14:42 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:14:42 - mmengine - INFO - Saving checkpoint at 30 epochs 2022/10/20 11:14:52 - mmengine - INFO - Epoch(val) [30][50/407] eta: 0:00:42 time: 0.118733 data_time: 0.038338 memory: 7326 2022/10/20 11:14:57 - mmengine - INFO - Epoch(val) [30][100/407] eta: 0:00:34 time: 0.112495 data_time: 0.031507 memory: 1680 2022/10/20 11:15:03 - mmengine - INFO - Epoch(val) [30][150/407] eta: 0:00:31 time: 0.123568 data_time: 0.044021 memory: 1680 2022/10/20 11:15:09 - mmengine - INFO - Epoch(val) [30][200/407] eta: 0:00:23 time: 0.112459 data_time: 0.028192 memory: 1680 2022/10/20 11:15:15 - mmengine - INFO - Epoch(val) [30][250/407] eta: 0:00:19 time: 0.121605 data_time: 0.040842 memory: 1680 2022/10/20 11:15:21 - mmengine - INFO - Epoch(val) [30][300/407] eta: 0:00:12 time: 0.117995 data_time: 0.038309 memory: 1680 2022/10/20 11:15:27 - mmengine - INFO - Epoch(val) [30][350/407] eta: 0:00:06 time: 0.114389 data_time: 0.036149 memory: 1680 2022/10/20 11:15:32 - mmengine - INFO - Epoch(val) [30][400/407] eta: 0:00:00 time: 0.102524 data_time: 0.026320 memory: 1680 2022/10/20 11:16:05 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 11:16:17 - mmengine - INFO - Epoch(val) [30][407/407] coco/AP: 0.690213 coco/AP .5: 0.885473 coco/AP .75: 0.770454 coco/AP (M): 0.651816 coco/AP (L): 0.758743 coco/AR: 0.748111 coco/AR .5: 0.923646 coco/AR .75: 0.820214 coco/AR (M): 0.703769 coco/AR (L): 0.811631 2022/10/20 11:16:18 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_20.pth is removed 2022/10/20 11:16:20 - mmengine - INFO - The best checkpoint with 0.6902 coco/AP at 30 epoch is saved to best_coco/AP_epoch_30.pth. 2022/10/20 11:16:31 - mmengine - INFO - Epoch(train) [31][50/586] lr: 5.000000e-04 eta: 6:18:34 time: 0.224264 data_time: 0.032170 memory: 7326 loss_kpt: 0.000707 acc_pose: 0.831136 loss: 0.000707 2022/10/20 11:16:42 - mmengine - INFO - Epoch(train) [31][100/586] lr: 5.000000e-04 eta: 6:18:26 time: 0.223425 data_time: 0.027720 memory: 7326 loss_kpt: 0.000710 acc_pose: 0.760779 loss: 0.000710 2022/10/20 11:16:54 - mmengine - INFO - Epoch(train) [31][150/586] lr: 5.000000e-04 eta: 6:18:20 time: 0.230950 data_time: 0.024345 memory: 7326 loss_kpt: 0.000716 acc_pose: 0.737076 loss: 0.000716 2022/10/20 11:17:05 - mmengine - INFO - Epoch(train) [31][200/586] lr: 5.000000e-04 eta: 6:18:12 time: 0.225464 data_time: 0.027656 memory: 7326 loss_kpt: 0.000716 acc_pose: 0.800934 loss: 0.000716 2022/10/20 11:17:16 - mmengine - INFO - Epoch(train) [31][250/586] lr: 5.000000e-04 eta: 6:18:03 time: 0.221455 data_time: 0.023791 memory: 7326 loss_kpt: 0.000723 acc_pose: 0.733549 loss: 0.000723 2022/10/20 11:17:27 - mmengine - INFO - Epoch(train) [31][300/586] lr: 5.000000e-04 eta: 6:17:56 time: 0.229150 data_time: 0.024748 memory: 7326 loss_kpt: 0.000718 acc_pose: 0.847796 loss: 0.000718 2022/10/20 11:17:39 - mmengine - INFO - Epoch(train) [31][350/586] lr: 5.000000e-04 eta: 6:17:50 time: 0.230363 data_time: 0.023860 memory: 7326 loss_kpt: 0.000712 acc_pose: 0.827583 loss: 0.000712 2022/10/20 11:17:50 - mmengine - INFO - Epoch(train) [31][400/586] lr: 5.000000e-04 eta: 6:17:40 time: 0.221128 data_time: 0.026537 memory: 7326 loss_kpt: 0.000717 acc_pose: 0.823610 loss: 0.000717 2022/10/20 11:17:55 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:18:01 - mmengine - INFO - Epoch(train) [31][450/586] lr: 5.000000e-04 eta: 6:17:34 time: 0.229274 data_time: 0.022356 memory: 7326 loss_kpt: 0.000704 acc_pose: 0.788415 loss: 0.000704 2022/10/20 11:18:13 - mmengine - INFO - Epoch(train) [31][500/586] lr: 5.000000e-04 eta: 6:17:26 time: 0.226250 data_time: 0.022389 memory: 7326 loss_kpt: 0.000728 acc_pose: 0.830606 loss: 0.000728 2022/10/20 11:18:24 - mmengine - INFO - Epoch(train) [31][550/586] lr: 5.000000e-04 eta: 6:17:17 time: 0.223129 data_time: 0.024643 memory: 7326 loss_kpt: 0.000741 acc_pose: 0.849583 loss: 0.000741 2022/10/20 11:18:32 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:18:43 - mmengine - INFO - Epoch(train) [32][50/586] lr: 5.000000e-04 eta: 6:16:18 time: 0.228314 data_time: 0.032316 memory: 7326 loss_kpt: 0.000711 acc_pose: 0.767299 loss: 0.000711 2022/10/20 11:18:55 - mmengine - INFO - Epoch(train) [32][100/586] lr: 5.000000e-04 eta: 6:16:12 time: 0.234059 data_time: 0.026088 memory: 7326 loss_kpt: 0.000712 acc_pose: 0.747701 loss: 0.000712 2022/10/20 11:19:07 - mmengine - INFO - Epoch(train) [32][150/586] lr: 5.000000e-04 eta: 6:16:05 time: 0.228986 data_time: 0.026989 memory: 7326 loss_kpt: 0.000707 acc_pose: 0.809932 loss: 0.000707 2022/10/20 11:19:18 - mmengine - INFO - Epoch(train) [32][200/586] lr: 5.000000e-04 eta: 6:15:58 time: 0.227958 data_time: 0.026711 memory: 7326 loss_kpt: 0.000697 acc_pose: 0.802104 loss: 0.000697 2022/10/20 11:19:29 - mmengine - INFO - Epoch(train) [32][250/586] lr: 5.000000e-04 eta: 6:15:50 time: 0.224297 data_time: 0.026027 memory: 7326 loss_kpt: 0.000705 acc_pose: 0.834514 loss: 0.000705 2022/10/20 11:19:41 - mmengine - INFO - Epoch(train) [32][300/586] lr: 5.000000e-04 eta: 6:15:42 time: 0.227064 data_time: 0.028932 memory: 7326 loss_kpt: 0.000696 acc_pose: 0.850845 loss: 0.000696 2022/10/20 11:19:52 - mmengine - INFO - Epoch(train) [32][350/586] lr: 5.000000e-04 eta: 6:15:36 time: 0.231345 data_time: 0.025305 memory: 7326 loss_kpt: 0.000703 acc_pose: 0.845258 loss: 0.000703 2022/10/20 11:20:03 - mmengine - INFO - Epoch(train) [32][400/586] lr: 5.000000e-04 eta: 6:15:27 time: 0.220241 data_time: 0.024710 memory: 7326 loss_kpt: 0.000687 acc_pose: 0.693010 loss: 0.000687 2022/10/20 11:20:15 - mmengine - INFO - Epoch(train) [32][450/586] lr: 5.000000e-04 eta: 6:15:20 time: 0.229735 data_time: 0.027103 memory: 7326 loss_kpt: 0.000705 acc_pose: 0.786062 loss: 0.000705 2022/10/20 11:20:26 - mmengine - INFO - Epoch(train) [32][500/586] lr: 5.000000e-04 eta: 6:15:10 time: 0.219998 data_time: 0.023802 memory: 7326 loss_kpt: 0.000724 acc_pose: 0.807300 loss: 0.000724 2022/10/20 11:20:37 - mmengine - INFO - Epoch(train) [32][550/586] lr: 5.000000e-04 eta: 6:15:03 time: 0.227502 data_time: 0.028049 memory: 7326 loss_kpt: 0.000704 acc_pose: 0.719731 loss: 0.000704 2022/10/20 11:20:45 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:20:57 - mmengine - INFO - Epoch(train) [33][50/586] lr: 5.000000e-04 eta: 6:14:06 time: 0.232191 data_time: 0.036332 memory: 7326 loss_kpt: 0.000732 acc_pose: 0.725616 loss: 0.000732 2022/10/20 11:21:08 - mmengine - INFO - Epoch(train) [33][100/586] lr: 5.000000e-04 eta: 6:13:59 time: 0.229502 data_time: 0.024839 memory: 7326 loss_kpt: 0.000711 acc_pose: 0.711745 loss: 0.000711 2022/10/20 11:21:20 - mmengine - INFO - Epoch(train) [33][150/586] lr: 5.000000e-04 eta: 6:13:51 time: 0.226756 data_time: 0.028923 memory: 7326 loss_kpt: 0.000701 acc_pose: 0.731967 loss: 0.000701 2022/10/20 11:21:31 - mmengine - INFO - Epoch(train) [33][200/586] lr: 5.000000e-04 eta: 6:13:43 time: 0.224960 data_time: 0.025295 memory: 7326 loss_kpt: 0.000742 acc_pose: 0.758967 loss: 0.000742 2022/10/20 11:21:42 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:21:42 - mmengine - INFO - Epoch(train) [33][250/586] lr: 5.000000e-04 eta: 6:13:34 time: 0.222867 data_time: 0.023233 memory: 7326 loss_kpt: 0.000715 acc_pose: 0.794574 loss: 0.000715 2022/10/20 11:21:53 - mmengine - INFO - Epoch(train) [33][300/586] lr: 5.000000e-04 eta: 6:13:26 time: 0.224280 data_time: 0.025906 memory: 7326 loss_kpt: 0.000703 acc_pose: 0.775228 loss: 0.000703 2022/10/20 11:22:05 - mmengine - INFO - Epoch(train) [33][350/586] lr: 5.000000e-04 eta: 6:13:19 time: 0.229428 data_time: 0.023184 memory: 7326 loss_kpt: 0.000684 acc_pose: 0.786629 loss: 0.000684 2022/10/20 11:22:16 - mmengine - INFO - Epoch(train) [33][400/586] lr: 5.000000e-04 eta: 6:13:10 time: 0.222899 data_time: 0.032883 memory: 7326 loss_kpt: 0.000691 acc_pose: 0.852213 loss: 0.000691 2022/10/20 11:22:27 - mmengine - INFO - Epoch(train) [33][450/586] lr: 5.000000e-04 eta: 6:13:02 time: 0.223622 data_time: 0.024600 memory: 7326 loss_kpt: 0.000710 acc_pose: 0.856138 loss: 0.000710 2022/10/20 11:22:39 - mmengine - INFO - Epoch(train) [33][500/586] lr: 5.000000e-04 eta: 6:12:54 time: 0.228238 data_time: 0.023489 memory: 7326 loss_kpt: 0.000733 acc_pose: 0.781511 loss: 0.000733 2022/10/20 11:22:50 - mmengine - INFO - Epoch(train) [33][550/586] lr: 5.000000e-04 eta: 6:12:47 time: 0.227595 data_time: 0.025017 memory: 7326 loss_kpt: 0.000717 acc_pose: 0.833935 loss: 0.000717 2022/10/20 11:22:58 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:23:10 - mmengine - INFO - Epoch(train) [34][50/586] lr: 5.000000e-04 eta: 6:11:52 time: 0.234763 data_time: 0.031587 memory: 7326 loss_kpt: 0.000722 acc_pose: 0.667624 loss: 0.000722 2022/10/20 11:23:21 - mmengine - INFO - Epoch(train) [34][100/586] lr: 5.000000e-04 eta: 6:11:45 time: 0.228491 data_time: 0.026539 memory: 7326 loss_kpt: 0.000723 acc_pose: 0.803975 loss: 0.000723 2022/10/20 11:23:33 - mmengine - INFO - Epoch(train) [34][150/586] lr: 5.000000e-04 eta: 6:11:37 time: 0.226156 data_time: 0.026462 memory: 7326 loss_kpt: 0.000697 acc_pose: 0.797498 loss: 0.000697 2022/10/20 11:23:44 - mmengine - INFO - Epoch(train) [34][200/586] lr: 5.000000e-04 eta: 6:11:28 time: 0.221913 data_time: 0.021619 memory: 7326 loss_kpt: 0.000711 acc_pose: 0.848041 loss: 0.000711 2022/10/20 11:23:55 - mmengine - INFO - Epoch(train) [34][250/586] lr: 5.000000e-04 eta: 6:11:21 time: 0.228987 data_time: 0.022729 memory: 7326 loss_kpt: 0.000740 acc_pose: 0.771973 loss: 0.000740 2022/10/20 11:24:07 - mmengine - INFO - Epoch(train) [34][300/586] lr: 5.000000e-04 eta: 6:11:13 time: 0.227647 data_time: 0.027268 memory: 7326 loss_kpt: 0.000718 acc_pose: 0.838037 loss: 0.000718 2022/10/20 11:24:18 - mmengine - INFO - Epoch(train) [34][350/586] lr: 5.000000e-04 eta: 6:11:06 time: 0.229305 data_time: 0.029477 memory: 7326 loss_kpt: 0.000719 acc_pose: 0.736313 loss: 0.000719 2022/10/20 11:24:29 - mmengine - INFO - Epoch(train) [34][400/586] lr: 5.000000e-04 eta: 6:10:56 time: 0.219497 data_time: 0.023544 memory: 7326 loss_kpt: 0.000697 acc_pose: 0.855806 loss: 0.000697 2022/10/20 11:24:41 - mmengine - INFO - Epoch(train) [34][450/586] lr: 5.000000e-04 eta: 6:10:50 time: 0.231380 data_time: 0.024828 memory: 7326 loss_kpt: 0.000720 acc_pose: 0.788037 loss: 0.000720 2022/10/20 11:24:51 - mmengine - INFO - Epoch(train) [34][500/586] lr: 5.000000e-04 eta: 6:10:40 time: 0.217618 data_time: 0.023935 memory: 7326 loss_kpt: 0.000677 acc_pose: 0.837093 loss: 0.000677 2022/10/20 11:25:03 - mmengine - INFO - Epoch(train) [34][550/586] lr: 5.000000e-04 eta: 6:10:33 time: 0.231434 data_time: 0.024006 memory: 7326 loss_kpt: 0.000706 acc_pose: 0.788895 loss: 0.000706 2022/10/20 11:25:11 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:25:22 - mmengine - INFO - Epoch(train) [35][50/586] lr: 5.000000e-04 eta: 6:09:37 time: 0.226311 data_time: 0.032951 memory: 7326 loss_kpt: 0.000713 acc_pose: 0.804720 loss: 0.000713 2022/10/20 11:25:28 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:25:34 - mmengine - INFO - Epoch(train) [35][100/586] lr: 5.000000e-04 eta: 6:09:30 time: 0.230527 data_time: 0.027482 memory: 7326 loss_kpt: 0.000697 acc_pose: 0.785361 loss: 0.000697 2022/10/20 11:25:45 - mmengine - INFO - Epoch(train) [35][150/586] lr: 5.000000e-04 eta: 6:09:21 time: 0.220552 data_time: 0.026115 memory: 7326 loss_kpt: 0.000694 acc_pose: 0.765427 loss: 0.000694 2022/10/20 11:25:56 - mmengine - INFO - Epoch(train) [35][200/586] lr: 5.000000e-04 eta: 6:09:13 time: 0.227555 data_time: 0.025890 memory: 7326 loss_kpt: 0.000712 acc_pose: 0.866243 loss: 0.000712 2022/10/20 11:26:07 - mmengine - INFO - Epoch(train) [35][250/586] lr: 5.000000e-04 eta: 6:09:05 time: 0.224267 data_time: 0.025142 memory: 7326 loss_kpt: 0.000705 acc_pose: 0.843669 loss: 0.000705 2022/10/20 11:26:19 - mmengine - INFO - Epoch(train) [35][300/586] lr: 5.000000e-04 eta: 6:08:57 time: 0.224750 data_time: 0.025312 memory: 7326 loss_kpt: 0.000706 acc_pose: 0.774022 loss: 0.000706 2022/10/20 11:26:30 - mmengine - INFO - Epoch(train) [35][350/586] lr: 5.000000e-04 eta: 6:08:50 time: 0.230064 data_time: 0.026329 memory: 7326 loss_kpt: 0.000679 acc_pose: 0.750908 loss: 0.000679 2022/10/20 11:26:42 - mmengine - INFO - Epoch(train) [35][400/586] lr: 5.000000e-04 eta: 6:08:42 time: 0.228657 data_time: 0.021659 memory: 7326 loss_kpt: 0.000708 acc_pose: 0.809457 loss: 0.000708 2022/10/20 11:26:53 - mmengine - INFO - Epoch(train) [35][450/586] lr: 5.000000e-04 eta: 6:08:34 time: 0.226462 data_time: 0.024685 memory: 7326 loss_kpt: 0.000710 acc_pose: 0.823383 loss: 0.000710 2022/10/20 11:27:04 - mmengine - INFO - Epoch(train) [35][500/586] lr: 5.000000e-04 eta: 6:08:26 time: 0.225228 data_time: 0.023088 memory: 7326 loss_kpt: 0.000691 acc_pose: 0.785396 loss: 0.000691 2022/10/20 11:27:16 - mmengine - INFO - Epoch(train) [35][550/586] lr: 5.000000e-04 eta: 6:08:18 time: 0.224965 data_time: 0.023273 memory: 7326 loss_kpt: 0.000709 acc_pose: 0.852208 loss: 0.000709 2022/10/20 11:27:23 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:27:35 - mmengine - INFO - Epoch(train) [36][50/586] lr: 5.000000e-04 eta: 6:07:25 time: 0.234334 data_time: 0.037631 memory: 7326 loss_kpt: 0.000706 acc_pose: 0.765511 loss: 0.000706 2022/10/20 11:27:47 - mmengine - INFO - Epoch(train) [36][100/586] lr: 5.000000e-04 eta: 6:07:19 time: 0.233346 data_time: 0.026592 memory: 7326 loss_kpt: 0.000721 acc_pose: 0.736023 loss: 0.000721 2022/10/20 11:27:58 - mmengine - INFO - Epoch(train) [36][150/586] lr: 5.000000e-04 eta: 6:07:11 time: 0.225285 data_time: 0.025674 memory: 7326 loss_kpt: 0.000684 acc_pose: 0.812010 loss: 0.000684 2022/10/20 11:28:09 - mmengine - INFO - Epoch(train) [36][200/586] lr: 5.000000e-04 eta: 6:07:03 time: 0.226345 data_time: 0.024368 memory: 7326 loss_kpt: 0.000714 acc_pose: 0.786146 loss: 0.000714 2022/10/20 11:28:21 - mmengine - INFO - Epoch(train) [36][250/586] lr: 5.000000e-04 eta: 6:06:54 time: 0.223872 data_time: 0.023897 memory: 7326 loss_kpt: 0.000720 acc_pose: 0.706071 loss: 0.000720 2022/10/20 11:28:32 - mmengine - INFO - Epoch(train) [36][300/586] lr: 5.000000e-04 eta: 6:06:46 time: 0.225441 data_time: 0.025786 memory: 7326 loss_kpt: 0.000684 acc_pose: 0.772703 loss: 0.000684 2022/10/20 11:28:44 - mmengine - INFO - Epoch(train) [36][350/586] lr: 5.000000e-04 eta: 6:06:40 time: 0.235617 data_time: 0.022440 memory: 7326 loss_kpt: 0.000700 acc_pose: 0.802371 loss: 0.000700 2022/10/20 11:28:55 - mmengine - INFO - Epoch(train) [36][400/586] lr: 5.000000e-04 eta: 6:06:31 time: 0.222428 data_time: 0.025081 memory: 7326 loss_kpt: 0.000695 acc_pose: 0.743024 loss: 0.000695 2022/10/20 11:29:06 - mmengine - INFO - Epoch(train) [36][450/586] lr: 5.000000e-04 eta: 6:06:23 time: 0.225964 data_time: 0.023350 memory: 7326 loss_kpt: 0.000699 acc_pose: 0.802718 loss: 0.000699 2022/10/20 11:29:15 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:29:17 - mmengine - INFO - Epoch(train) [36][500/586] lr: 5.000000e-04 eta: 6:06:14 time: 0.221629 data_time: 0.026654 memory: 7326 loss_kpt: 0.000701 acc_pose: 0.871882 loss: 0.000701 2022/10/20 11:29:29 - mmengine - INFO - Epoch(train) [36][550/586] lr: 5.000000e-04 eta: 6:06:06 time: 0.228104 data_time: 0.023765 memory: 7326 loss_kpt: 0.000718 acc_pose: 0.821614 loss: 0.000718 2022/10/20 11:29:37 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:29:48 - mmengine - INFO - Epoch(train) [37][50/586] lr: 5.000000e-04 eta: 6:05:13 time: 0.227870 data_time: 0.033057 memory: 7326 loss_kpt: 0.000726 acc_pose: 0.844358 loss: 0.000726 2022/10/20 11:30:00 - mmengine - INFO - Epoch(train) [37][100/586] lr: 5.000000e-04 eta: 6:05:06 time: 0.229846 data_time: 0.028126 memory: 7326 loss_kpt: 0.000696 acc_pose: 0.749555 loss: 0.000696 2022/10/20 11:30:11 - mmengine - INFO - Epoch(train) [37][150/586] lr: 5.000000e-04 eta: 6:04:56 time: 0.217083 data_time: 0.023338 memory: 7326 loss_kpt: 0.000705 acc_pose: 0.806395 loss: 0.000705 2022/10/20 11:30:22 - mmengine - INFO - Epoch(train) [37][200/586] lr: 5.000000e-04 eta: 6:04:48 time: 0.227541 data_time: 0.027667 memory: 7326 loss_kpt: 0.000685 acc_pose: 0.835493 loss: 0.000685 2022/10/20 11:30:33 - mmengine - INFO - Epoch(train) [37][250/586] lr: 5.000000e-04 eta: 6:04:40 time: 0.226262 data_time: 0.026309 memory: 7326 loss_kpt: 0.000698 acc_pose: 0.791657 loss: 0.000698 2022/10/20 11:30:45 - mmengine - INFO - Epoch(train) [37][300/586] lr: 5.000000e-04 eta: 6:04:32 time: 0.228749 data_time: 0.032468 memory: 7326 loss_kpt: 0.000697 acc_pose: 0.792336 loss: 0.000697 2022/10/20 11:30:56 - mmengine - INFO - Epoch(train) [37][350/586] lr: 5.000000e-04 eta: 6:04:25 time: 0.232040 data_time: 0.023945 memory: 7326 loss_kpt: 0.000702 acc_pose: 0.767072 loss: 0.000702 2022/10/20 11:31:08 - mmengine - INFO - Epoch(train) [37][400/586] lr: 5.000000e-04 eta: 6:04:19 time: 0.231990 data_time: 0.030836 memory: 7326 loss_kpt: 0.000701 acc_pose: 0.828569 loss: 0.000701 2022/10/20 11:31:19 - mmengine - INFO - Epoch(train) [37][450/586] lr: 5.000000e-04 eta: 6:04:11 time: 0.227091 data_time: 0.026696 memory: 7326 loss_kpt: 0.000719 acc_pose: 0.821124 loss: 0.000719 2022/10/20 11:31:30 - mmengine - INFO - Epoch(train) [37][500/586] lr: 5.000000e-04 eta: 6:04:01 time: 0.218425 data_time: 0.026413 memory: 7326 loss_kpt: 0.000681 acc_pose: 0.754889 loss: 0.000681 2022/10/20 11:31:42 - mmengine - INFO - Epoch(train) [37][550/586] lr: 5.000000e-04 eta: 6:03:53 time: 0.227058 data_time: 0.026198 memory: 7326 loss_kpt: 0.000689 acc_pose: 0.779671 loss: 0.000689 2022/10/20 11:31:49 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:32:01 - mmengine - INFO - Epoch(train) [38][50/586] lr: 5.000000e-04 eta: 6:03:02 time: 0.233523 data_time: 0.038244 memory: 7326 loss_kpt: 0.000688 acc_pose: 0.817400 loss: 0.000688 2022/10/20 11:32:13 - mmengine - INFO - Epoch(train) [38][100/586] lr: 5.000000e-04 eta: 6:02:55 time: 0.230981 data_time: 0.023690 memory: 7326 loss_kpt: 0.000688 acc_pose: 0.789703 loss: 0.000688 2022/10/20 11:32:24 - mmengine - INFO - Epoch(train) [38][150/586] lr: 5.000000e-04 eta: 6:02:47 time: 0.224783 data_time: 0.026773 memory: 7326 loss_kpt: 0.000697 acc_pose: 0.782640 loss: 0.000697 2022/10/20 11:32:36 - mmengine - INFO - Epoch(train) [38][200/586] lr: 5.000000e-04 eta: 6:02:40 time: 0.232974 data_time: 0.023393 memory: 7326 loss_kpt: 0.000703 acc_pose: 0.823788 loss: 0.000703 2022/10/20 11:32:46 - mmengine - INFO - Epoch(train) [38][250/586] lr: 5.000000e-04 eta: 6:02:30 time: 0.217380 data_time: 0.022572 memory: 7326 loss_kpt: 0.000711 acc_pose: 0.822924 loss: 0.000711 2022/10/20 11:32:58 - mmengine - INFO - Epoch(train) [38][300/586] lr: 5.000000e-04 eta: 6:02:23 time: 0.233242 data_time: 0.024645 memory: 7326 loss_kpt: 0.000698 acc_pose: 0.718057 loss: 0.000698 2022/10/20 11:33:02 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:33:09 - mmengine - INFO - Epoch(train) [38][350/586] lr: 5.000000e-04 eta: 6:02:16 time: 0.227805 data_time: 0.024881 memory: 7326 loss_kpt: 0.000690 acc_pose: 0.886215 loss: 0.000690 2022/10/20 11:33:21 - mmengine - INFO - Epoch(train) [38][400/586] lr: 5.000000e-04 eta: 6:02:06 time: 0.220349 data_time: 0.022892 memory: 7326 loss_kpt: 0.000695 acc_pose: 0.777683 loss: 0.000695 2022/10/20 11:33:32 - mmengine - INFO - Epoch(train) [38][450/586] lr: 5.000000e-04 eta: 6:01:58 time: 0.225368 data_time: 0.024500 memory: 7326 loss_kpt: 0.000680 acc_pose: 0.805505 loss: 0.000680 2022/10/20 11:33:43 - mmengine - INFO - Epoch(train) [38][500/586] lr: 5.000000e-04 eta: 6:01:49 time: 0.223671 data_time: 0.024790 memory: 7326 loss_kpt: 0.000707 acc_pose: 0.776401 loss: 0.000707 2022/10/20 11:33:54 - mmengine - INFO - Epoch(train) [38][550/586] lr: 5.000000e-04 eta: 6:01:39 time: 0.221924 data_time: 0.029074 memory: 7326 loss_kpt: 0.000699 acc_pose: 0.819225 loss: 0.000699 2022/10/20 11:34:02 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:34:14 - mmengine - INFO - Epoch(train) [39][50/586] lr: 5.000000e-04 eta: 6:00:50 time: 0.231041 data_time: 0.029398 memory: 7326 loss_kpt: 0.000700 acc_pose: 0.827815 loss: 0.000700 2022/10/20 11:34:25 - mmengine - INFO - Epoch(train) [39][100/586] lr: 5.000000e-04 eta: 6:00:42 time: 0.227306 data_time: 0.022417 memory: 7326 loss_kpt: 0.000688 acc_pose: 0.797363 loss: 0.000688 2022/10/20 11:34:36 - mmengine - INFO - Epoch(train) [39][150/586] lr: 5.000000e-04 eta: 6:00:32 time: 0.221421 data_time: 0.027043 memory: 7326 loss_kpt: 0.000680 acc_pose: 0.842745 loss: 0.000680 2022/10/20 11:34:47 - mmengine - INFO - Epoch(train) [39][200/586] lr: 5.000000e-04 eta: 6:00:24 time: 0.225222 data_time: 0.024392 memory: 7326 loss_kpt: 0.000685 acc_pose: 0.798356 loss: 0.000685 2022/10/20 11:34:59 - mmengine - INFO - Epoch(train) [39][250/586] lr: 5.000000e-04 eta: 6:00:17 time: 0.234691 data_time: 0.028923 memory: 7326 loss_kpt: 0.000713 acc_pose: 0.774413 loss: 0.000713 2022/10/20 11:35:11 - mmengine - INFO - Epoch(train) [39][300/586] lr: 5.000000e-04 eta: 6:00:10 time: 0.228353 data_time: 0.023610 memory: 7326 loss_kpt: 0.000673 acc_pose: 0.815100 loss: 0.000673 2022/10/20 11:35:22 - mmengine - INFO - Epoch(train) [39][350/586] lr: 5.000000e-04 eta: 6:00:02 time: 0.229065 data_time: 0.023776 memory: 7326 loss_kpt: 0.000702 acc_pose: 0.803284 loss: 0.000702 2022/10/20 11:35:33 - mmengine - INFO - Epoch(train) [39][400/586] lr: 5.000000e-04 eta: 5:59:53 time: 0.223581 data_time: 0.029210 memory: 7326 loss_kpt: 0.000706 acc_pose: 0.806233 loss: 0.000706 2022/10/20 11:35:45 - mmengine - INFO - Epoch(train) [39][450/586] lr: 5.000000e-04 eta: 5:59:45 time: 0.225283 data_time: 0.024296 memory: 7326 loss_kpt: 0.000692 acc_pose: 0.878002 loss: 0.000692 2022/10/20 11:35:55 - mmengine - INFO - Epoch(train) [39][500/586] lr: 5.000000e-04 eta: 5:59:34 time: 0.217137 data_time: 0.024492 memory: 7326 loss_kpt: 0.000691 acc_pose: 0.819395 loss: 0.000691 2022/10/20 11:36:07 - mmengine - INFO - Epoch(train) [39][550/586] lr: 5.000000e-04 eta: 5:59:26 time: 0.227886 data_time: 0.023173 memory: 7326 loss_kpt: 0.000699 acc_pose: 0.771213 loss: 0.000699 2022/10/20 11:36:14 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:36:26 - mmengine - INFO - Epoch(train) [40][50/586] lr: 5.000000e-04 eta: 5:58:39 time: 0.236016 data_time: 0.032647 memory: 7326 loss_kpt: 0.000675 acc_pose: 0.813418 loss: 0.000675 2022/10/20 11:36:37 - mmengine - INFO - Epoch(train) [40][100/586] lr: 5.000000e-04 eta: 5:58:30 time: 0.222336 data_time: 0.022970 memory: 7326 loss_kpt: 0.000686 acc_pose: 0.846245 loss: 0.000686 2022/10/20 11:36:48 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:36:49 - mmengine - INFO - Epoch(train) [40][150/586] lr: 5.000000e-04 eta: 5:58:21 time: 0.224186 data_time: 0.025829 memory: 7326 loss_kpt: 0.000707 acc_pose: 0.795008 loss: 0.000707 2022/10/20 11:37:00 - mmengine - INFO - Epoch(train) [40][200/586] lr: 5.000000e-04 eta: 5:58:13 time: 0.230591 data_time: 0.031626 memory: 7326 loss_kpt: 0.000682 acc_pose: 0.783304 loss: 0.000682 2022/10/20 11:37:11 - mmengine - INFO - Epoch(train) [40][250/586] lr: 5.000000e-04 eta: 5:58:05 time: 0.224533 data_time: 0.023770 memory: 7326 loss_kpt: 0.000687 acc_pose: 0.805346 loss: 0.000687 2022/10/20 11:37:23 - mmengine - INFO - Epoch(train) [40][300/586] lr: 5.000000e-04 eta: 5:57:57 time: 0.228662 data_time: 0.031284 memory: 7326 loss_kpt: 0.000695 acc_pose: 0.794714 loss: 0.000695 2022/10/20 11:37:34 - mmengine - INFO - Epoch(train) [40][350/586] lr: 5.000000e-04 eta: 5:57:49 time: 0.228773 data_time: 0.024489 memory: 7326 loss_kpt: 0.000696 acc_pose: 0.856664 loss: 0.000696 2022/10/20 11:37:45 - mmengine - INFO - Epoch(train) [40][400/586] lr: 5.000000e-04 eta: 5:57:39 time: 0.219342 data_time: 0.024701 memory: 7326 loss_kpt: 0.000691 acc_pose: 0.701967 loss: 0.000691 2022/10/20 11:37:57 - mmengine - INFO - Epoch(train) [40][450/586] lr: 5.000000e-04 eta: 5:57:31 time: 0.227007 data_time: 0.023533 memory: 7326 loss_kpt: 0.000694 acc_pose: 0.767100 loss: 0.000694 2022/10/20 11:38:08 - mmengine - INFO - Epoch(train) [40][500/586] lr: 5.000000e-04 eta: 5:57:22 time: 0.221899 data_time: 0.025592 memory: 7326 loss_kpt: 0.000685 acc_pose: 0.826182 loss: 0.000685 2022/10/20 11:38:19 - mmengine - INFO - Epoch(train) [40][550/586] lr: 5.000000e-04 eta: 5:57:14 time: 0.228131 data_time: 0.026019 memory: 7326 loss_kpt: 0.000702 acc_pose: 0.825472 loss: 0.000702 2022/10/20 11:38:27 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:38:27 - mmengine - INFO - Saving checkpoint at 40 epochs 2022/10/20 11:38:37 - mmengine - INFO - Epoch(val) [40][50/407] eta: 0:00:41 time: 0.117620 data_time: 0.036860 memory: 7326 2022/10/20 11:38:43 - mmengine - INFO - Epoch(val) [40][100/407] eta: 0:00:35 time: 0.116923 data_time: 0.034036 memory: 1680 2022/10/20 11:38:49 - mmengine - INFO - Epoch(val) [40][150/407] eta: 0:00:30 time: 0.117400 data_time: 0.036360 memory: 1680 2022/10/20 11:38:55 - mmengine - INFO - Epoch(val) [40][200/407] eta: 0:00:23 time: 0.114447 data_time: 0.034067 memory: 1680 2022/10/20 11:39:01 - mmengine - INFO - Epoch(val) [40][250/407] eta: 0:00:18 time: 0.117958 data_time: 0.037299 memory: 1680 2022/10/20 11:39:07 - mmengine - INFO - Epoch(val) [40][300/407] eta: 0:00:12 time: 0.118740 data_time: 0.038173 memory: 1680 2022/10/20 11:39:12 - mmengine - INFO - Epoch(val) [40][350/407] eta: 0:00:06 time: 0.114231 data_time: 0.035193 memory: 1680 2022/10/20 11:39:18 - mmengine - INFO - Epoch(val) [40][400/407] eta: 0:00:00 time: 0.107027 data_time: 0.029626 memory: 1680 2022/10/20 11:39:51 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 11:40:04 - mmengine - INFO - Epoch(val) [40][407/407] coco/AP: 0.703075 coco/AP .5: 0.892503 coco/AP .75: 0.784210 coco/AP (M): 0.667294 coco/AP (L): 0.767346 coco/AR: 0.759776 coco/AR .5: 0.930101 coco/AR .75: 0.831392 coco/AR (M): 0.717318 coco/AR (L): 0.820513 2022/10/20 11:40:04 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_30.pth is removed 2022/10/20 11:40:06 - mmengine - INFO - The best checkpoint with 0.7031 coco/AP at 40 epoch is saved to best_coco/AP_epoch_40.pth. 2022/10/20 11:40:18 - mmengine - INFO - Epoch(train) [41][50/586] lr: 5.000000e-04 eta: 5:56:27 time: 0.234644 data_time: 0.031182 memory: 7326 loss_kpt: 0.000678 acc_pose: 0.823083 loss: 0.000678 2022/10/20 11:40:29 - mmengine - INFO - Epoch(train) [41][100/586] lr: 5.000000e-04 eta: 5:56:19 time: 0.228903 data_time: 0.023978 memory: 7326 loss_kpt: 0.000690 acc_pose: 0.812920 loss: 0.000690 2022/10/20 11:40:41 - mmengine - INFO - Epoch(train) [41][150/586] lr: 5.000000e-04 eta: 5:56:10 time: 0.222740 data_time: 0.025308 memory: 7326 loss_kpt: 0.000682 acc_pose: 0.870282 loss: 0.000682 2022/10/20 11:40:52 - mmengine - INFO - Epoch(train) [41][200/586] lr: 5.000000e-04 eta: 5:56:03 time: 0.231903 data_time: 0.030257 memory: 7326 loss_kpt: 0.000677 acc_pose: 0.770346 loss: 0.000677 2022/10/20 11:41:03 - mmengine - INFO - Epoch(train) [41][250/586] lr: 5.000000e-04 eta: 5:55:54 time: 0.225421 data_time: 0.023832 memory: 7326 loss_kpt: 0.000676 acc_pose: 0.791611 loss: 0.000676 2022/10/20 11:41:15 - mmengine - INFO - Epoch(train) [41][300/586] lr: 5.000000e-04 eta: 5:55:47 time: 0.232495 data_time: 0.026513 memory: 7326 loss_kpt: 0.000666 acc_pose: 0.770986 loss: 0.000666 2022/10/20 11:41:26 - mmengine - INFO - Epoch(train) [41][350/586] lr: 5.000000e-04 eta: 5:55:39 time: 0.229149 data_time: 0.023986 memory: 7326 loss_kpt: 0.000684 acc_pose: 0.838313 loss: 0.000684 2022/10/20 11:41:38 - mmengine - INFO - Epoch(train) [41][400/586] lr: 5.000000e-04 eta: 5:55:31 time: 0.225870 data_time: 0.026225 memory: 7326 loss_kpt: 0.000696 acc_pose: 0.810658 loss: 0.000696 2022/10/20 11:41:49 - mmengine - INFO - Epoch(train) [41][450/586] lr: 5.000000e-04 eta: 5:55:23 time: 0.226180 data_time: 0.029589 memory: 7326 loss_kpt: 0.000701 acc_pose: 0.744282 loss: 0.000701 2022/10/20 11:42:00 - mmengine - INFO - Epoch(train) [41][500/586] lr: 5.000000e-04 eta: 5:55:14 time: 0.225198 data_time: 0.024336 memory: 7326 loss_kpt: 0.000690 acc_pose: 0.838411 loss: 0.000690 2022/10/20 11:42:12 - mmengine - INFO - Epoch(train) [41][550/586] lr: 5.000000e-04 eta: 5:55:05 time: 0.226264 data_time: 0.025391 memory: 7326 loss_kpt: 0.000687 acc_pose: 0.842120 loss: 0.000687 2022/10/20 11:42:14 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:42:20 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:42:31 - mmengine - INFO - Epoch(train) [42][50/586] lr: 5.000000e-04 eta: 5:54:20 time: 0.237296 data_time: 0.031810 memory: 7326 loss_kpt: 0.000674 acc_pose: 0.846833 loss: 0.000674 2022/10/20 11:42:43 - mmengine - INFO - Epoch(train) [42][100/586] lr: 5.000000e-04 eta: 5:54:12 time: 0.229299 data_time: 0.025659 memory: 7326 loss_kpt: 0.000691 acc_pose: 0.754789 loss: 0.000691 2022/10/20 11:42:54 - mmengine - INFO - Epoch(train) [42][150/586] lr: 5.000000e-04 eta: 5:54:03 time: 0.222471 data_time: 0.024894 memory: 7326 loss_kpt: 0.000662 acc_pose: 0.822298 loss: 0.000662 2022/10/20 11:43:05 - mmengine - INFO - Epoch(train) [42][200/586] lr: 5.000000e-04 eta: 5:53:54 time: 0.224959 data_time: 0.024182 memory: 7326 loss_kpt: 0.000671 acc_pose: 0.835819 loss: 0.000671 2022/10/20 11:43:17 - mmengine - INFO - Epoch(train) [42][250/586] lr: 5.000000e-04 eta: 5:53:45 time: 0.225310 data_time: 0.028501 memory: 7326 loss_kpt: 0.000677 acc_pose: 0.792430 loss: 0.000677 2022/10/20 11:43:28 - mmengine - INFO - Epoch(train) [42][300/586] lr: 5.000000e-04 eta: 5:53:38 time: 0.232521 data_time: 0.028835 memory: 7326 loss_kpt: 0.000687 acc_pose: 0.852776 loss: 0.000687 2022/10/20 11:43:39 - mmengine - INFO - Epoch(train) [42][350/586] lr: 5.000000e-04 eta: 5:53:29 time: 0.224367 data_time: 0.025698 memory: 7326 loss_kpt: 0.000685 acc_pose: 0.719191 loss: 0.000685 2022/10/20 11:43:51 - mmengine - INFO - Epoch(train) [42][400/586] lr: 5.000000e-04 eta: 5:53:21 time: 0.226441 data_time: 0.025480 memory: 7326 loss_kpt: 0.000691 acc_pose: 0.820223 loss: 0.000691 2022/10/20 11:44:02 - mmengine - INFO - Epoch(train) [42][450/586] lr: 5.000000e-04 eta: 5:53:13 time: 0.227970 data_time: 0.026192 memory: 7326 loss_kpt: 0.000674 acc_pose: 0.869756 loss: 0.000674 2022/10/20 11:44:13 - mmengine - INFO - Epoch(train) [42][500/586] lr: 5.000000e-04 eta: 5:53:03 time: 0.220655 data_time: 0.025513 memory: 7326 loss_kpt: 0.000677 acc_pose: 0.759037 loss: 0.000677 2022/10/20 11:44:25 - mmengine - INFO - Epoch(train) [42][550/586] lr: 5.000000e-04 eta: 5:52:56 time: 0.232822 data_time: 0.029871 memory: 7326 loss_kpt: 0.000687 acc_pose: 0.804610 loss: 0.000687 2022/10/20 11:44:33 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:44:44 - mmengine - INFO - Epoch(train) [43][50/586] lr: 5.000000e-04 eta: 5:52:09 time: 0.227856 data_time: 0.031734 memory: 7326 loss_kpt: 0.000687 acc_pose: 0.747189 loss: 0.000687 2022/10/20 11:44:56 - mmengine - INFO - Epoch(train) [43][100/586] lr: 5.000000e-04 eta: 5:52:01 time: 0.227693 data_time: 0.025889 memory: 7326 loss_kpt: 0.000700 acc_pose: 0.772553 loss: 0.000700 2022/10/20 11:45:07 - mmengine - INFO - Epoch(train) [43][150/586] lr: 5.000000e-04 eta: 5:51:52 time: 0.222598 data_time: 0.025053 memory: 7326 loss_kpt: 0.000676 acc_pose: 0.793369 loss: 0.000676 2022/10/20 11:45:18 - mmengine - INFO - Epoch(train) [43][200/586] lr: 5.000000e-04 eta: 5:51:43 time: 0.223862 data_time: 0.028651 memory: 7326 loss_kpt: 0.000694 acc_pose: 0.850729 loss: 0.000694 2022/10/20 11:45:29 - mmengine - INFO - Epoch(train) [43][250/586] lr: 5.000000e-04 eta: 5:51:35 time: 0.229729 data_time: 0.023895 memory: 7326 loss_kpt: 0.000657 acc_pose: 0.820675 loss: 0.000657 2022/10/20 11:45:41 - mmengine - INFO - Epoch(train) [43][300/586] lr: 5.000000e-04 eta: 5:51:27 time: 0.227302 data_time: 0.023773 memory: 7326 loss_kpt: 0.000693 acc_pose: 0.774553 loss: 0.000693 2022/10/20 11:45:52 - mmengine - INFO - Epoch(train) [43][350/586] lr: 5.000000e-04 eta: 5:51:19 time: 0.227808 data_time: 0.027744 memory: 7326 loss_kpt: 0.000687 acc_pose: 0.860397 loss: 0.000687 2022/10/20 11:46:01 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:46:03 - mmengine - INFO - Epoch(train) [43][400/586] lr: 5.000000e-04 eta: 5:51:10 time: 0.223134 data_time: 0.025512 memory: 7326 loss_kpt: 0.000695 acc_pose: 0.877415 loss: 0.000695 2022/10/20 11:46:15 - mmengine - INFO - Epoch(train) [43][450/586] lr: 5.000000e-04 eta: 5:51:03 time: 0.234300 data_time: 0.025784 memory: 7326 loss_kpt: 0.000671 acc_pose: 0.754799 loss: 0.000671 2022/10/20 11:46:26 - mmengine - INFO - Epoch(train) [43][500/586] lr: 5.000000e-04 eta: 5:50:52 time: 0.217547 data_time: 0.024270 memory: 7326 loss_kpt: 0.000668 acc_pose: 0.829467 loss: 0.000668 2022/10/20 11:46:37 - mmengine - INFO - Epoch(train) [43][550/586] lr: 5.000000e-04 eta: 5:50:45 time: 0.229430 data_time: 0.025421 memory: 7326 loss_kpt: 0.000693 acc_pose: 0.758726 loss: 0.000693 2022/10/20 11:46:45 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:46:57 - mmengine - INFO - Epoch(train) [44][50/586] lr: 5.000000e-04 eta: 5:49:59 time: 0.232015 data_time: 0.033232 memory: 7326 loss_kpt: 0.000683 acc_pose: 0.772990 loss: 0.000683 2022/10/20 11:47:08 - mmengine - INFO - Epoch(train) [44][100/586] lr: 5.000000e-04 eta: 5:49:51 time: 0.228483 data_time: 0.027707 memory: 7326 loss_kpt: 0.000689 acc_pose: 0.762929 loss: 0.000689 2022/10/20 11:47:19 - mmengine - INFO - Epoch(train) [44][150/586] lr: 5.000000e-04 eta: 5:49:41 time: 0.218669 data_time: 0.025342 memory: 7326 loss_kpt: 0.000682 acc_pose: 0.854452 loss: 0.000682 2022/10/20 11:47:31 - mmengine - INFO - Epoch(train) [44][200/586] lr: 5.000000e-04 eta: 5:49:34 time: 0.230859 data_time: 0.026521 memory: 7326 loss_kpt: 0.000682 acc_pose: 0.794207 loss: 0.000682 2022/10/20 11:47:42 - mmengine - INFO - Epoch(train) [44][250/586] lr: 5.000000e-04 eta: 5:49:24 time: 0.221753 data_time: 0.024634 memory: 7326 loss_kpt: 0.000685 acc_pose: 0.796518 loss: 0.000685 2022/10/20 11:47:54 - mmengine - INFO - Epoch(train) [44][300/586] lr: 5.000000e-04 eta: 5:49:16 time: 0.229445 data_time: 0.027365 memory: 7326 loss_kpt: 0.000671 acc_pose: 0.732231 loss: 0.000671 2022/10/20 11:48:05 - mmengine - INFO - Epoch(train) [44][350/586] lr: 5.000000e-04 eta: 5:49:08 time: 0.228741 data_time: 0.029070 memory: 7326 loss_kpt: 0.000698 acc_pose: 0.822429 loss: 0.000698 2022/10/20 11:48:16 - mmengine - INFO - Epoch(train) [44][400/586] lr: 5.000000e-04 eta: 5:49:00 time: 0.229022 data_time: 0.026308 memory: 7326 loss_kpt: 0.000696 acc_pose: 0.816318 loss: 0.000696 2022/10/20 11:48:28 - mmengine - INFO - Epoch(train) [44][450/586] lr: 5.000000e-04 eta: 5:48:52 time: 0.230019 data_time: 0.025852 memory: 7326 loss_kpt: 0.000684 acc_pose: 0.799631 loss: 0.000684 2022/10/20 11:48:39 - mmengine - INFO - Epoch(train) [44][500/586] lr: 5.000000e-04 eta: 5:48:42 time: 0.217672 data_time: 0.025809 memory: 7326 loss_kpt: 0.000700 acc_pose: 0.805886 loss: 0.000700 2022/10/20 11:48:50 - mmengine - INFO - Epoch(train) [44][550/586] lr: 5.000000e-04 eta: 5:48:34 time: 0.228087 data_time: 0.029513 memory: 7326 loss_kpt: 0.000683 acc_pose: 0.763424 loss: 0.000683 2022/10/20 11:48:58 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:49:10 - mmengine - INFO - Epoch(train) [45][50/586] lr: 5.000000e-04 eta: 5:47:49 time: 0.226885 data_time: 0.032520 memory: 7326 loss_kpt: 0.000676 acc_pose: 0.783770 loss: 0.000676 2022/10/20 11:49:21 - mmengine - INFO - Epoch(train) [45][100/586] lr: 5.000000e-04 eta: 5:47:39 time: 0.223384 data_time: 0.024810 memory: 7326 loss_kpt: 0.000684 acc_pose: 0.810095 loss: 0.000684 2022/10/20 11:49:32 - mmengine - INFO - Epoch(train) [45][150/586] lr: 5.000000e-04 eta: 5:47:30 time: 0.221278 data_time: 0.024439 memory: 7326 loss_kpt: 0.000680 acc_pose: 0.854317 loss: 0.000680 2022/10/20 11:49:44 - mmengine - INFO - Epoch(train) [45][200/586] lr: 5.000000e-04 eta: 5:47:22 time: 0.228340 data_time: 0.025300 memory: 7326 loss_kpt: 0.000676 acc_pose: 0.831108 loss: 0.000676 2022/10/20 11:49:47 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:49:55 - mmengine - INFO - Epoch(train) [45][250/586] lr: 5.000000e-04 eta: 5:47:13 time: 0.223595 data_time: 0.025728 memory: 7326 loss_kpt: 0.000658 acc_pose: 0.878624 loss: 0.000658 2022/10/20 11:50:06 - mmengine - INFO - Epoch(train) [45][300/586] lr: 5.000000e-04 eta: 5:47:03 time: 0.222837 data_time: 0.026176 memory: 7326 loss_kpt: 0.000680 acc_pose: 0.729354 loss: 0.000680 2022/10/20 11:50:17 - mmengine - INFO - Epoch(train) [45][350/586] lr: 5.000000e-04 eta: 5:46:56 time: 0.230272 data_time: 0.027086 memory: 7326 loss_kpt: 0.000685 acc_pose: 0.778398 loss: 0.000685 2022/10/20 11:50:29 - mmengine - INFO - Epoch(train) [45][400/586] lr: 5.000000e-04 eta: 5:46:47 time: 0.225090 data_time: 0.026395 memory: 7326 loss_kpt: 0.000689 acc_pose: 0.806579 loss: 0.000689 2022/10/20 11:50:40 - mmengine - INFO - Epoch(train) [45][450/586] lr: 5.000000e-04 eta: 5:46:39 time: 0.228977 data_time: 0.023979 memory: 7326 loss_kpt: 0.000660 acc_pose: 0.802376 loss: 0.000660 2022/10/20 11:50:51 - mmengine - INFO - Epoch(train) [45][500/586] lr: 5.000000e-04 eta: 5:46:30 time: 0.223504 data_time: 0.025624 memory: 7326 loss_kpt: 0.000678 acc_pose: 0.843752 loss: 0.000678 2022/10/20 11:51:03 - mmengine - INFO - Epoch(train) [45][550/586] lr: 5.000000e-04 eta: 5:46:21 time: 0.225360 data_time: 0.025014 memory: 7326 loss_kpt: 0.000695 acc_pose: 0.796414 loss: 0.000695 2022/10/20 11:51:10 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:51:22 - mmengine - INFO - Epoch(train) [46][50/586] lr: 5.000000e-04 eta: 5:45:38 time: 0.238210 data_time: 0.032604 memory: 7326 loss_kpt: 0.000679 acc_pose: 0.822868 loss: 0.000679 2022/10/20 11:51:34 - mmengine - INFO - Epoch(train) [46][100/586] lr: 5.000000e-04 eta: 5:45:30 time: 0.226065 data_time: 0.025016 memory: 7326 loss_kpt: 0.000681 acc_pose: 0.803409 loss: 0.000681 2022/10/20 11:51:45 - mmengine - INFO - Epoch(train) [46][150/586] lr: 5.000000e-04 eta: 5:45:20 time: 0.223713 data_time: 0.025755 memory: 7326 loss_kpt: 0.000672 acc_pose: 0.837150 loss: 0.000672 2022/10/20 11:51:56 - mmengine - INFO - Epoch(train) [46][200/586] lr: 5.000000e-04 eta: 5:45:11 time: 0.223832 data_time: 0.023732 memory: 7326 loss_kpt: 0.000664 acc_pose: 0.779965 loss: 0.000664 2022/10/20 11:52:07 - mmengine - INFO - Epoch(train) [46][250/586] lr: 5.000000e-04 eta: 5:45:02 time: 0.221455 data_time: 0.025828 memory: 7326 loss_kpt: 0.000648 acc_pose: 0.846252 loss: 0.000648 2022/10/20 11:52:19 - mmengine - INFO - Epoch(train) [46][300/586] lr: 5.000000e-04 eta: 5:44:54 time: 0.231456 data_time: 0.031757 memory: 7326 loss_kpt: 0.000679 acc_pose: 0.797895 loss: 0.000679 2022/10/20 11:52:30 - mmengine - INFO - Epoch(train) [46][350/586] lr: 5.000000e-04 eta: 5:44:45 time: 0.222868 data_time: 0.025034 memory: 7326 loss_kpt: 0.000700 acc_pose: 0.803788 loss: 0.000700 2022/10/20 11:52:41 - mmengine - INFO - Epoch(train) [46][400/586] lr: 5.000000e-04 eta: 5:44:37 time: 0.229940 data_time: 0.023162 memory: 7326 loss_kpt: 0.000675 acc_pose: 0.736009 loss: 0.000675 2022/10/20 11:52:53 - mmengine - INFO - Epoch(train) [46][450/586] lr: 5.000000e-04 eta: 5:44:29 time: 0.231764 data_time: 0.028356 memory: 7326 loss_kpt: 0.000688 acc_pose: 0.895939 loss: 0.000688 2022/10/20 11:53:04 - mmengine - INFO - Epoch(train) [46][500/586] lr: 5.000000e-04 eta: 5:44:19 time: 0.218040 data_time: 0.025888 memory: 7326 loss_kpt: 0.000660 acc_pose: 0.852014 loss: 0.000660 2022/10/20 11:53:15 - mmengine - INFO - Epoch(train) [46][550/586] lr: 5.000000e-04 eta: 5:44:11 time: 0.230677 data_time: 0.024104 memory: 7326 loss_kpt: 0.000690 acc_pose: 0.807942 loss: 0.000690 2022/10/20 11:53:23 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:53:34 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:53:35 - mmengine - INFO - Epoch(train) [47][50/586] lr: 5.000000e-04 eta: 5:43:29 time: 0.235267 data_time: 0.032487 memory: 7326 loss_kpt: 0.000658 acc_pose: 0.780229 loss: 0.000658 2022/10/20 11:53:46 - mmengine - INFO - Epoch(train) [47][100/586] lr: 5.000000e-04 eta: 5:43:20 time: 0.224798 data_time: 0.024254 memory: 7326 loss_kpt: 0.000678 acc_pose: 0.804884 loss: 0.000678 2022/10/20 11:53:57 - mmengine - INFO - Epoch(train) [47][150/586] lr: 5.000000e-04 eta: 5:43:11 time: 0.223511 data_time: 0.025675 memory: 7326 loss_kpt: 0.000681 acc_pose: 0.838971 loss: 0.000681 2022/10/20 11:54:09 - mmengine - INFO - Epoch(train) [47][200/586] lr: 5.000000e-04 eta: 5:43:03 time: 0.229574 data_time: 0.023206 memory: 7326 loss_kpt: 0.000667 acc_pose: 0.766739 loss: 0.000667 2022/10/20 11:54:20 - mmengine - INFO - Epoch(train) [47][250/586] lr: 5.000000e-04 eta: 5:42:54 time: 0.227225 data_time: 0.028449 memory: 7326 loss_kpt: 0.000660 acc_pose: 0.763237 loss: 0.000660 2022/10/20 11:54:31 - mmengine - INFO - Epoch(train) [47][300/586] lr: 5.000000e-04 eta: 5:42:45 time: 0.224675 data_time: 0.024831 memory: 7326 loss_kpt: 0.000686 acc_pose: 0.760416 loss: 0.000686 2022/10/20 11:54:42 - mmengine - INFO - Epoch(train) [47][350/586] lr: 5.000000e-04 eta: 5:42:35 time: 0.217749 data_time: 0.022695 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.856419 loss: 0.000642 2022/10/20 11:54:54 - mmengine - INFO - Epoch(train) [47][400/586] lr: 5.000000e-04 eta: 5:42:26 time: 0.226862 data_time: 0.026897 memory: 7326 loss_kpt: 0.000653 acc_pose: 0.755767 loss: 0.000653 2022/10/20 11:55:05 - mmengine - INFO - Epoch(train) [47][450/586] lr: 5.000000e-04 eta: 5:42:19 time: 0.233783 data_time: 0.028517 memory: 7326 loss_kpt: 0.000686 acc_pose: 0.833607 loss: 0.000686 2022/10/20 11:55:17 - mmengine - INFO - Epoch(train) [47][500/586] lr: 5.000000e-04 eta: 5:42:10 time: 0.223323 data_time: 0.024091 memory: 7326 loss_kpt: 0.000685 acc_pose: 0.823637 loss: 0.000685 2022/10/20 11:55:28 - mmengine - INFO - Epoch(train) [47][550/586] lr: 5.000000e-04 eta: 5:42:02 time: 0.231631 data_time: 0.023941 memory: 7326 loss_kpt: 0.000669 acc_pose: 0.819199 loss: 0.000669 2022/10/20 11:55:36 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:55:48 - mmengine - INFO - Epoch(train) [48][50/586] lr: 5.000000e-04 eta: 5:41:20 time: 0.231876 data_time: 0.033697 memory: 7326 loss_kpt: 0.000648 acc_pose: 0.849430 loss: 0.000648 2022/10/20 11:55:59 - mmengine - INFO - Epoch(train) [48][100/586] lr: 5.000000e-04 eta: 5:41:11 time: 0.226681 data_time: 0.023685 memory: 7326 loss_kpt: 0.000665 acc_pose: 0.862224 loss: 0.000665 2022/10/20 11:56:10 - mmengine - INFO - Epoch(train) [48][150/586] lr: 5.000000e-04 eta: 5:41:02 time: 0.224967 data_time: 0.023001 memory: 7326 loss_kpt: 0.000677 acc_pose: 0.820555 loss: 0.000677 2022/10/20 11:56:22 - mmengine - INFO - Epoch(train) [48][200/586] lr: 5.000000e-04 eta: 5:40:54 time: 0.228701 data_time: 0.025652 memory: 7326 loss_kpt: 0.000683 acc_pose: 0.738807 loss: 0.000683 2022/10/20 11:56:33 - mmengine - INFO - Epoch(train) [48][250/586] lr: 5.000000e-04 eta: 5:40:44 time: 0.221507 data_time: 0.027590 memory: 7326 loss_kpt: 0.000672 acc_pose: 0.817244 loss: 0.000672 2022/10/20 11:56:44 - mmengine - INFO - Epoch(train) [48][300/586] lr: 5.000000e-04 eta: 5:40:36 time: 0.225971 data_time: 0.026889 memory: 7326 loss_kpt: 0.000669 acc_pose: 0.765642 loss: 0.000669 2022/10/20 11:56:55 - mmengine - INFO - Epoch(train) [48][350/586] lr: 5.000000e-04 eta: 5:40:26 time: 0.220070 data_time: 0.026247 memory: 7326 loss_kpt: 0.000677 acc_pose: 0.784425 loss: 0.000677 2022/10/20 11:57:06 - mmengine - INFO - Epoch(train) [48][400/586] lr: 5.000000e-04 eta: 5:40:17 time: 0.227546 data_time: 0.024173 memory: 7326 loss_kpt: 0.000670 acc_pose: 0.844841 loss: 0.000670 2022/10/20 11:57:18 - mmengine - INFO - Epoch(train) [48][450/586] lr: 5.000000e-04 eta: 5:40:09 time: 0.229487 data_time: 0.025757 memory: 7326 loss_kpt: 0.000662 acc_pose: 0.870256 loss: 0.000662 2022/10/20 11:57:20 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:57:29 - mmengine - INFO - Epoch(train) [48][500/586] lr: 5.000000e-04 eta: 5:39:59 time: 0.220761 data_time: 0.023960 memory: 7326 loss_kpt: 0.000676 acc_pose: 0.826687 loss: 0.000676 2022/10/20 11:57:40 - mmengine - INFO - Epoch(train) [48][550/586] lr: 5.000000e-04 eta: 5:39:51 time: 0.226135 data_time: 0.027745 memory: 7326 loss_kpt: 0.000677 acc_pose: 0.803054 loss: 0.000677 2022/10/20 11:57:48 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 11:58:00 - mmengine - INFO - Epoch(train) [49][50/586] lr: 5.000000e-04 eta: 5:39:09 time: 0.234794 data_time: 0.032592 memory: 7326 loss_kpt: 0.000666 acc_pose: 0.779107 loss: 0.000666 2022/10/20 11:58:11 - mmengine - INFO - Epoch(train) [49][100/586] lr: 5.000000e-04 eta: 5:39:02 time: 0.231427 data_time: 0.024340 memory: 7326 loss_kpt: 0.000693 acc_pose: 0.731338 loss: 0.000693 2022/10/20 11:58:22 - mmengine - INFO - Epoch(train) [49][150/586] lr: 5.000000e-04 eta: 5:38:51 time: 0.218244 data_time: 0.024117 memory: 7326 loss_kpt: 0.000673 acc_pose: 0.834017 loss: 0.000673 2022/10/20 11:58:34 - mmengine - INFO - Epoch(train) [49][200/586] lr: 5.000000e-04 eta: 5:38:43 time: 0.228088 data_time: 0.027613 memory: 7326 loss_kpt: 0.000661 acc_pose: 0.805950 loss: 0.000661 2022/10/20 11:58:45 - mmengine - INFO - Epoch(train) [49][250/586] lr: 5.000000e-04 eta: 5:38:33 time: 0.221454 data_time: 0.024794 memory: 7326 loss_kpt: 0.000670 acc_pose: 0.819788 loss: 0.000670 2022/10/20 11:58:56 - mmengine - INFO - Epoch(train) [49][300/586] lr: 5.000000e-04 eta: 5:38:24 time: 0.225100 data_time: 0.024528 memory: 7326 loss_kpt: 0.000667 acc_pose: 0.796833 loss: 0.000667 2022/10/20 11:59:07 - mmengine - INFO - Epoch(train) [49][350/586] lr: 5.000000e-04 eta: 5:38:15 time: 0.221539 data_time: 0.025384 memory: 7326 loss_kpt: 0.000661 acc_pose: 0.788239 loss: 0.000661 2022/10/20 11:59:18 - mmengine - INFO - Epoch(train) [49][400/586] lr: 5.000000e-04 eta: 5:38:06 time: 0.225024 data_time: 0.024769 memory: 7326 loss_kpt: 0.000664 acc_pose: 0.831493 loss: 0.000664 2022/10/20 11:59:30 - mmengine - INFO - Epoch(train) [49][450/586] lr: 5.000000e-04 eta: 5:37:58 time: 0.232428 data_time: 0.025411 memory: 7326 loss_kpt: 0.000681 acc_pose: 0.794064 loss: 0.000681 2022/10/20 11:59:41 - mmengine - INFO - Epoch(train) [49][500/586] lr: 5.000000e-04 eta: 5:37:48 time: 0.221347 data_time: 0.026340 memory: 7326 loss_kpt: 0.000682 acc_pose: 0.879888 loss: 0.000682 2022/10/20 11:59:53 - mmengine - INFO - Epoch(train) [49][550/586] lr: 5.000000e-04 eta: 5:37:40 time: 0.230070 data_time: 0.024740 memory: 7326 loss_kpt: 0.000678 acc_pose: 0.790841 loss: 0.000678 2022/10/20 12:00:00 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:00:12 - mmengine - INFO - Epoch(train) [50][50/586] lr: 5.000000e-04 eta: 5:36:59 time: 0.230495 data_time: 0.032479 memory: 7326 loss_kpt: 0.000662 acc_pose: 0.790400 loss: 0.000662 2022/10/20 12:00:24 - mmengine - INFO - Epoch(train) [50][100/586] lr: 5.000000e-04 eta: 5:36:52 time: 0.234467 data_time: 0.027216 memory: 7326 loss_kpt: 0.000644 acc_pose: 0.839179 loss: 0.000644 2022/10/20 12:00:35 - mmengine - INFO - Epoch(train) [50][150/586] lr: 5.000000e-04 eta: 5:36:42 time: 0.223726 data_time: 0.023053 memory: 7326 loss_kpt: 0.000686 acc_pose: 0.865843 loss: 0.000686 2022/10/20 12:00:46 - mmengine - INFO - Epoch(train) [50][200/586] lr: 5.000000e-04 eta: 5:36:34 time: 0.229568 data_time: 0.024151 memory: 7326 loss_kpt: 0.000660 acc_pose: 0.843330 loss: 0.000660 2022/10/20 12:00:57 - mmengine - INFO - Epoch(train) [50][250/586] lr: 5.000000e-04 eta: 5:36:25 time: 0.222201 data_time: 0.028400 memory: 7326 loss_kpt: 0.000661 acc_pose: 0.817854 loss: 0.000661 2022/10/20 12:01:05 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:01:09 - mmengine - INFO - Epoch(train) [50][300/586] lr: 5.000000e-04 eta: 5:36:16 time: 0.224522 data_time: 0.023411 memory: 7326 loss_kpt: 0.000660 acc_pose: 0.830713 loss: 0.000660 2022/10/20 12:01:20 - mmengine - INFO - Epoch(train) [50][350/586] lr: 5.000000e-04 eta: 5:36:07 time: 0.225504 data_time: 0.024445 memory: 7326 loss_kpt: 0.000661 acc_pose: 0.847210 loss: 0.000661 2022/10/20 12:01:31 - mmengine - INFO - Epoch(train) [50][400/586] lr: 5.000000e-04 eta: 5:35:58 time: 0.230535 data_time: 0.028702 memory: 7326 loss_kpt: 0.000675 acc_pose: 0.785471 loss: 0.000675 2022/10/20 12:01:43 - mmengine - INFO - Epoch(train) [50][450/586] lr: 5.000000e-04 eta: 5:35:50 time: 0.228192 data_time: 0.021929 memory: 7326 loss_kpt: 0.000654 acc_pose: 0.857725 loss: 0.000654 2022/10/20 12:01:54 - mmengine - INFO - Epoch(train) [50][500/586] lr: 5.000000e-04 eta: 5:35:41 time: 0.227679 data_time: 0.024040 memory: 7326 loss_kpt: 0.000674 acc_pose: 0.848312 loss: 0.000674 2022/10/20 12:02:06 - mmengine - INFO - Epoch(train) [50][550/586] lr: 5.000000e-04 eta: 5:35:33 time: 0.228856 data_time: 0.028299 memory: 7326 loss_kpt: 0.000682 acc_pose: 0.817279 loss: 0.000682 2022/10/20 12:02:14 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:02:14 - mmengine - INFO - Saving checkpoint at 50 epochs 2022/10/20 12:02:24 - mmengine - INFO - Epoch(val) [50][50/407] eta: 0:00:46 time: 0.129657 data_time: 0.042598 memory: 7326 2022/10/20 12:02:30 - mmengine - INFO - Epoch(val) [50][100/407] eta: 0:00:35 time: 0.115142 data_time: 0.032503 memory: 1680 2022/10/20 12:02:36 - mmengine - INFO - Epoch(val) [50][150/407] eta: 0:00:30 time: 0.116914 data_time: 0.034671 memory: 1680 2022/10/20 12:02:41 - mmengine - INFO - Epoch(val) [50][200/407] eta: 0:00:23 time: 0.114062 data_time: 0.031657 memory: 1680 2022/10/20 12:02:48 - mmengine - INFO - Epoch(val) [50][250/407] eta: 0:00:19 time: 0.122169 data_time: 0.041003 memory: 1680 2022/10/20 12:02:53 - mmengine - INFO - Epoch(val) [50][300/407] eta: 0:00:11 time: 0.111053 data_time: 0.027957 memory: 1680 2022/10/20 12:02:59 - mmengine - INFO - Epoch(val) [50][350/407] eta: 0:00:06 time: 0.119766 data_time: 0.039761 memory: 1680 2022/10/20 12:03:04 - mmengine - INFO - Epoch(val) [50][400/407] eta: 0:00:00 time: 0.100379 data_time: 0.023106 memory: 1680 2022/10/20 12:03:37 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 12:03:50 - mmengine - INFO - Epoch(val) [50][407/407] coco/AP: 0.709625 coco/AP .5: 0.892977 coco/AP .75: 0.789573 coco/AP (M): 0.669862 coco/AP (L): 0.779274 coco/AR: 0.765428 coco/AR .5: 0.930101 coco/AR .75: 0.835800 coco/AR (M): 0.720186 coco/AR (L): 0.831401 2022/10/20 12:03:50 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_40.pth is removed 2022/10/20 12:03:52 - mmengine - INFO - The best checkpoint with 0.7096 coco/AP at 50 epoch is saved to best_coco/AP_epoch_50.pth. 2022/10/20 12:04:04 - mmengine - INFO - Epoch(train) [51][50/586] lr: 5.000000e-04 eta: 5:34:53 time: 0.235156 data_time: 0.031331 memory: 7326 loss_kpt: 0.000678 acc_pose: 0.762146 loss: 0.000678 2022/10/20 12:04:15 - mmengine - INFO - Epoch(train) [51][100/586] lr: 5.000000e-04 eta: 5:34:44 time: 0.226965 data_time: 0.024919 memory: 7326 loss_kpt: 0.000656 acc_pose: 0.856320 loss: 0.000656 2022/10/20 12:04:27 - mmengine - INFO - Epoch(train) [51][150/586] lr: 5.000000e-04 eta: 5:34:37 time: 0.234069 data_time: 0.024359 memory: 7326 loss_kpt: 0.000662 acc_pose: 0.779906 loss: 0.000662 2022/10/20 12:04:38 - mmengine - INFO - Epoch(train) [51][200/586] lr: 5.000000e-04 eta: 5:34:27 time: 0.221610 data_time: 0.028557 memory: 7326 loss_kpt: 0.000671 acc_pose: 0.775262 loss: 0.000671 2022/10/20 12:04:49 - mmengine - INFO - Epoch(train) [51][250/586] lr: 5.000000e-04 eta: 5:34:18 time: 0.225200 data_time: 0.024363 memory: 7326 loss_kpt: 0.000689 acc_pose: 0.840206 loss: 0.000689 2022/10/20 12:05:01 - mmengine - INFO - Epoch(train) [51][300/586] lr: 5.000000e-04 eta: 5:34:11 time: 0.235304 data_time: 0.024967 memory: 7326 loss_kpt: 0.000661 acc_pose: 0.821946 loss: 0.000661 2022/10/20 12:05:12 - mmengine - INFO - Epoch(train) [51][350/586] lr: 5.000000e-04 eta: 5:34:00 time: 0.217034 data_time: 0.023003 memory: 7326 loss_kpt: 0.000651 acc_pose: 0.854870 loss: 0.000651 2022/10/20 12:05:23 - mmengine - INFO - Epoch(train) [51][400/586] lr: 5.000000e-04 eta: 5:33:51 time: 0.224389 data_time: 0.027974 memory: 7326 loss_kpt: 0.000656 acc_pose: 0.696275 loss: 0.000656 2022/10/20 12:05:34 - mmengine - INFO - Epoch(train) [51][450/586] lr: 5.000000e-04 eta: 5:33:41 time: 0.221494 data_time: 0.024505 memory: 7326 loss_kpt: 0.000660 acc_pose: 0.744709 loss: 0.000660 2022/10/20 12:05:46 - mmengine - INFO - Epoch(train) [51][500/586] lr: 5.000000e-04 eta: 5:33:34 time: 0.232431 data_time: 0.025700 memory: 7326 loss_kpt: 0.000669 acc_pose: 0.863414 loss: 0.000669 2022/10/20 12:05:57 - mmengine - INFO - Epoch(train) [51][550/586] lr: 5.000000e-04 eta: 5:33:25 time: 0.227951 data_time: 0.022971 memory: 7326 loss_kpt: 0.000652 acc_pose: 0.821520 loss: 0.000652 2022/10/20 12:06:05 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:06:17 - mmengine - INFO - Epoch(train) [52][50/586] lr: 5.000000e-04 eta: 5:32:45 time: 0.233599 data_time: 0.033508 memory: 7326 loss_kpt: 0.000680 acc_pose: 0.832100 loss: 0.000680 2022/10/20 12:06:28 - mmengine - INFO - Epoch(train) [52][100/586] lr: 5.000000e-04 eta: 5:32:37 time: 0.227559 data_time: 0.030177 memory: 7326 loss_kpt: 0.000640 acc_pose: 0.810167 loss: 0.000640 2022/10/20 12:06:31 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:06:39 - mmengine - INFO - Epoch(train) [52][150/586] lr: 5.000000e-04 eta: 5:32:28 time: 0.226245 data_time: 0.023675 memory: 7326 loss_kpt: 0.000654 acc_pose: 0.804226 loss: 0.000654 2022/10/20 12:06:51 - mmengine - INFO - Epoch(train) [52][200/586] lr: 5.000000e-04 eta: 5:32:19 time: 0.229495 data_time: 0.022379 memory: 7326 loss_kpt: 0.000681 acc_pose: 0.853870 loss: 0.000681 2022/10/20 12:07:02 - mmengine - INFO - Epoch(train) [52][250/586] lr: 5.000000e-04 eta: 5:32:11 time: 0.228895 data_time: 0.026247 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.789349 loss: 0.000642 2022/10/20 12:07:14 - mmengine - INFO - Epoch(train) [52][300/586] lr: 5.000000e-04 eta: 5:32:02 time: 0.225328 data_time: 0.025230 memory: 7326 loss_kpt: 0.000669 acc_pose: 0.757393 loss: 0.000669 2022/10/20 12:07:25 - mmengine - INFO - Epoch(train) [52][350/586] lr: 5.000000e-04 eta: 5:31:52 time: 0.222481 data_time: 0.024391 memory: 7326 loss_kpt: 0.000690 acc_pose: 0.752934 loss: 0.000690 2022/10/20 12:07:37 - mmengine - INFO - Epoch(train) [52][400/586] lr: 5.000000e-04 eta: 5:31:45 time: 0.239219 data_time: 0.027344 memory: 7326 loss_kpt: 0.000661 acc_pose: 0.874045 loss: 0.000661 2022/10/20 12:07:48 - mmengine - INFO - Epoch(train) [52][450/586] lr: 5.000000e-04 eta: 5:31:36 time: 0.221914 data_time: 0.024477 memory: 7326 loss_kpt: 0.000652 acc_pose: 0.783106 loss: 0.000652 2022/10/20 12:07:59 - mmengine - INFO - Epoch(train) [52][500/586] lr: 5.000000e-04 eta: 5:31:27 time: 0.225095 data_time: 0.024828 memory: 7326 loss_kpt: 0.000658 acc_pose: 0.784579 loss: 0.000658 2022/10/20 12:08:10 - mmengine - INFO - Epoch(train) [52][550/586] lr: 5.000000e-04 eta: 5:31:18 time: 0.225654 data_time: 0.028351 memory: 7326 loss_kpt: 0.000666 acc_pose: 0.797752 loss: 0.000666 2022/10/20 12:08:19 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:08:31 - mmengine - INFO - Epoch(train) [53][50/586] lr: 5.000000e-04 eta: 5:30:40 time: 0.241784 data_time: 0.033013 memory: 7326 loss_kpt: 0.000664 acc_pose: 0.855976 loss: 0.000664 2022/10/20 12:08:42 - mmengine - INFO - Epoch(train) [53][100/586] lr: 5.000000e-04 eta: 5:30:31 time: 0.226352 data_time: 0.023689 memory: 7326 loss_kpt: 0.000670 acc_pose: 0.752086 loss: 0.000670 2022/10/20 12:08:53 - mmengine - INFO - Epoch(train) [53][150/586] lr: 5.000000e-04 eta: 5:30:22 time: 0.224002 data_time: 0.025590 memory: 7326 loss_kpt: 0.000687 acc_pose: 0.858446 loss: 0.000687 2022/10/20 12:09:04 - mmengine - INFO - Epoch(train) [53][200/586] lr: 5.000000e-04 eta: 5:30:12 time: 0.220551 data_time: 0.026612 memory: 7326 loss_kpt: 0.000671 acc_pose: 0.778164 loss: 0.000671 2022/10/20 12:09:15 - mmengine - INFO - Epoch(train) [53][250/586] lr: 5.000000e-04 eta: 5:30:02 time: 0.223590 data_time: 0.023887 memory: 7326 loss_kpt: 0.000674 acc_pose: 0.840817 loss: 0.000674 2022/10/20 12:09:27 - mmengine - INFO - Epoch(train) [53][300/586] lr: 5.000000e-04 eta: 5:29:54 time: 0.232212 data_time: 0.024083 memory: 7326 loss_kpt: 0.000652 acc_pose: 0.879874 loss: 0.000652 2022/10/20 12:09:38 - mmengine - INFO - Epoch(train) [53][350/586] lr: 5.000000e-04 eta: 5:29:45 time: 0.221976 data_time: 0.024929 memory: 7326 loss_kpt: 0.000655 acc_pose: 0.831071 loss: 0.000655 2022/10/20 12:09:49 - mmengine - INFO - Epoch(train) [53][400/586] lr: 5.000000e-04 eta: 5:29:35 time: 0.221839 data_time: 0.026218 memory: 7326 loss_kpt: 0.000683 acc_pose: 0.814756 loss: 0.000683 2022/10/20 12:10:01 - mmengine - INFO - Epoch(train) [53][450/586] lr: 5.000000e-04 eta: 5:29:27 time: 0.229611 data_time: 0.025185 memory: 7326 loss_kpt: 0.000668 acc_pose: 0.802041 loss: 0.000668 2022/10/20 12:10:12 - mmengine - INFO - Epoch(train) [53][500/586] lr: 5.000000e-04 eta: 5:29:19 time: 0.231771 data_time: 0.023302 memory: 7326 loss_kpt: 0.000666 acc_pose: 0.838208 loss: 0.000666 2022/10/20 12:10:19 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:10:24 - mmengine - INFO - Epoch(train) [53][550/586] lr: 5.000000e-04 eta: 5:29:10 time: 0.226954 data_time: 0.024278 memory: 7326 loss_kpt: 0.000651 acc_pose: 0.756037 loss: 0.000651 2022/10/20 12:10:31 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:10:43 - mmengine - INFO - Epoch(train) [54][50/586] lr: 5.000000e-04 eta: 5:28:31 time: 0.231348 data_time: 0.030470 memory: 7326 loss_kpt: 0.000667 acc_pose: 0.831649 loss: 0.000667 2022/10/20 12:10:54 - mmengine - INFO - Epoch(train) [54][100/586] lr: 5.000000e-04 eta: 5:28:21 time: 0.222500 data_time: 0.028017 memory: 7326 loss_kpt: 0.000653 acc_pose: 0.858505 loss: 0.000653 2022/10/20 12:11:06 - mmengine - INFO - Epoch(train) [54][150/586] lr: 5.000000e-04 eta: 5:28:13 time: 0.233078 data_time: 0.025666 memory: 7326 loss_kpt: 0.000685 acc_pose: 0.782034 loss: 0.000685 2022/10/20 12:11:17 - mmengine - INFO - Epoch(train) [54][200/586] lr: 5.000000e-04 eta: 5:28:05 time: 0.228081 data_time: 0.026212 memory: 7326 loss_kpt: 0.000665 acc_pose: 0.888986 loss: 0.000665 2022/10/20 12:11:28 - mmengine - INFO - Epoch(train) [54][250/586] lr: 5.000000e-04 eta: 5:27:55 time: 0.220055 data_time: 0.023972 memory: 7326 loss_kpt: 0.000652 acc_pose: 0.804474 loss: 0.000652 2022/10/20 12:11:40 - mmengine - INFO - Epoch(train) [54][300/586] lr: 5.000000e-04 eta: 5:27:46 time: 0.226120 data_time: 0.026237 memory: 7326 loss_kpt: 0.000653 acc_pose: 0.746825 loss: 0.000653 2022/10/20 12:11:50 - mmengine - INFO - Epoch(train) [54][350/586] lr: 5.000000e-04 eta: 5:27:36 time: 0.218846 data_time: 0.025063 memory: 7326 loss_kpt: 0.000668 acc_pose: 0.760967 loss: 0.000668 2022/10/20 12:12:02 - mmengine - INFO - Epoch(train) [54][400/586] lr: 5.000000e-04 eta: 5:27:27 time: 0.229436 data_time: 0.023633 memory: 7326 loss_kpt: 0.000682 acc_pose: 0.876412 loss: 0.000682 2022/10/20 12:12:13 - mmengine - INFO - Epoch(train) [54][450/586] lr: 5.000000e-04 eta: 5:27:19 time: 0.229335 data_time: 0.026108 memory: 7326 loss_kpt: 0.000675 acc_pose: 0.798990 loss: 0.000675 2022/10/20 12:12:25 - mmengine - INFO - Epoch(train) [54][500/586] lr: 5.000000e-04 eta: 5:27:09 time: 0.221395 data_time: 0.025712 memory: 7326 loss_kpt: 0.000668 acc_pose: 0.825998 loss: 0.000668 2022/10/20 12:12:36 - mmengine - INFO - Epoch(train) [54][550/586] lr: 5.000000e-04 eta: 5:27:00 time: 0.228843 data_time: 0.025381 memory: 7326 loss_kpt: 0.000655 acc_pose: 0.794636 loss: 0.000655 2022/10/20 12:12:44 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:12:56 - mmengine - INFO - Epoch(train) [55][50/586] lr: 5.000000e-04 eta: 5:26:23 time: 0.236434 data_time: 0.030976 memory: 7326 loss_kpt: 0.000656 acc_pose: 0.897921 loss: 0.000656 2022/10/20 12:13:07 - mmengine - INFO - Epoch(train) [55][100/586] lr: 5.000000e-04 eta: 5:26:14 time: 0.231872 data_time: 0.023642 memory: 7326 loss_kpt: 0.000666 acc_pose: 0.826199 loss: 0.000666 2022/10/20 12:13:18 - mmengine - INFO - Epoch(train) [55][150/586] lr: 5.000000e-04 eta: 5:26:05 time: 0.222583 data_time: 0.024555 memory: 7326 loss_kpt: 0.000659 acc_pose: 0.819520 loss: 0.000659 2022/10/20 12:13:30 - mmengine - INFO - Epoch(train) [55][200/586] lr: 5.000000e-04 eta: 5:25:56 time: 0.227191 data_time: 0.026174 memory: 7326 loss_kpt: 0.000654 acc_pose: 0.781858 loss: 0.000654 2022/10/20 12:13:41 - mmengine - INFO - Epoch(train) [55][250/586] lr: 5.000000e-04 eta: 5:25:47 time: 0.229046 data_time: 0.026700 memory: 7326 loss_kpt: 0.000637 acc_pose: 0.826698 loss: 0.000637 2022/10/20 12:13:52 - mmengine - INFO - Epoch(train) [55][300/586] lr: 5.000000e-04 eta: 5:25:38 time: 0.225564 data_time: 0.024054 memory: 7326 loss_kpt: 0.000655 acc_pose: 0.826669 loss: 0.000655 2022/10/20 12:14:03 - mmengine - INFO - Epoch(train) [55][350/586] lr: 5.000000e-04 eta: 5:25:28 time: 0.217587 data_time: 0.023853 memory: 7326 loss_kpt: 0.000661 acc_pose: 0.881248 loss: 0.000661 2022/10/20 12:14:05 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:14:15 - mmengine - INFO - Epoch(train) [55][400/586] lr: 5.000000e-04 eta: 5:25:19 time: 0.227030 data_time: 0.022912 memory: 7326 loss_kpt: 0.000674 acc_pose: 0.845324 loss: 0.000674 2022/10/20 12:14:26 - mmengine - INFO - Epoch(train) [55][450/586] lr: 5.000000e-04 eta: 5:25:09 time: 0.222923 data_time: 0.025722 memory: 7326 loss_kpt: 0.000670 acc_pose: 0.777631 loss: 0.000670 2022/10/20 12:14:37 - mmengine - INFO - Epoch(train) [55][500/586] lr: 5.000000e-04 eta: 5:25:01 time: 0.228591 data_time: 0.027194 memory: 7326 loss_kpt: 0.000655 acc_pose: 0.867741 loss: 0.000655 2022/10/20 12:14:49 - mmengine - INFO - Epoch(train) [55][550/586] lr: 5.000000e-04 eta: 5:24:51 time: 0.224362 data_time: 0.025925 memory: 7326 loss_kpt: 0.000653 acc_pose: 0.780754 loss: 0.000653 2022/10/20 12:14:57 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:15:09 - mmengine - INFO - Epoch(train) [56][50/586] lr: 5.000000e-04 eta: 5:24:14 time: 0.236066 data_time: 0.031716 memory: 7326 loss_kpt: 0.000646 acc_pose: 0.825478 loss: 0.000646 2022/10/20 12:15:20 - mmengine - INFO - Epoch(train) [56][100/586] lr: 5.000000e-04 eta: 5:24:04 time: 0.219552 data_time: 0.024003 memory: 7326 loss_kpt: 0.000662 acc_pose: 0.792002 loss: 0.000662 2022/10/20 12:15:31 - mmengine - INFO - Epoch(train) [56][150/586] lr: 5.000000e-04 eta: 5:23:55 time: 0.227451 data_time: 0.024153 memory: 7326 loss_kpt: 0.000639 acc_pose: 0.894804 loss: 0.000639 2022/10/20 12:15:42 - mmengine - INFO - Epoch(train) [56][200/586] lr: 5.000000e-04 eta: 5:23:46 time: 0.223907 data_time: 0.027563 memory: 7326 loss_kpt: 0.000644 acc_pose: 0.809370 loss: 0.000644 2022/10/20 12:15:53 - mmengine - INFO - Epoch(train) [56][250/586] lr: 5.000000e-04 eta: 5:23:37 time: 0.226637 data_time: 0.027235 memory: 7326 loss_kpt: 0.000655 acc_pose: 0.872555 loss: 0.000655 2022/10/20 12:16:05 - mmengine - INFO - Epoch(train) [56][300/586] lr: 5.000000e-04 eta: 5:23:28 time: 0.228895 data_time: 0.028440 memory: 7326 loss_kpt: 0.000645 acc_pose: 0.886059 loss: 0.000645 2022/10/20 12:16:16 - mmengine - INFO - Epoch(train) [56][350/586] lr: 5.000000e-04 eta: 5:23:19 time: 0.226783 data_time: 0.023046 memory: 7326 loss_kpt: 0.000633 acc_pose: 0.774968 loss: 0.000633 2022/10/20 12:16:28 - mmengine - INFO - Epoch(train) [56][400/586] lr: 5.000000e-04 eta: 5:23:11 time: 0.231202 data_time: 0.023657 memory: 7326 loss_kpt: 0.000660 acc_pose: 0.881085 loss: 0.000660 2022/10/20 12:16:39 - mmengine - INFO - Epoch(train) [56][450/586] lr: 5.000000e-04 eta: 5:23:01 time: 0.222822 data_time: 0.022349 memory: 7326 loss_kpt: 0.000657 acc_pose: 0.852057 loss: 0.000657 2022/10/20 12:16:50 - mmengine - INFO - Epoch(train) [56][500/586] lr: 5.000000e-04 eta: 5:22:52 time: 0.225367 data_time: 0.027764 memory: 7326 loss_kpt: 0.000659 acc_pose: 0.821774 loss: 0.000659 2022/10/20 12:17:01 - mmengine - INFO - Epoch(train) [56][550/586] lr: 5.000000e-04 eta: 5:22:42 time: 0.219052 data_time: 0.025121 memory: 7326 loss_kpt: 0.000650 acc_pose: 0.823237 loss: 0.000650 2022/10/20 12:17:10 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:17:22 - mmengine - INFO - Epoch(train) [57][50/586] lr: 5.000000e-04 eta: 5:22:06 time: 0.240922 data_time: 0.032631 memory: 7326 loss_kpt: 0.000648 acc_pose: 0.808067 loss: 0.000648 2022/10/20 12:17:33 - mmengine - INFO - Epoch(train) [57][100/586] lr: 5.000000e-04 eta: 5:21:56 time: 0.220285 data_time: 0.023374 memory: 7326 loss_kpt: 0.000643 acc_pose: 0.744594 loss: 0.000643 2022/10/20 12:17:44 - mmengine - INFO - Epoch(train) [57][150/586] lr: 5.000000e-04 eta: 5:21:46 time: 0.220182 data_time: 0.027958 memory: 7326 loss_kpt: 0.000653 acc_pose: 0.783005 loss: 0.000653 2022/10/20 12:17:51 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:17:55 - mmengine - INFO - Epoch(train) [57][200/586] lr: 5.000000e-04 eta: 5:21:37 time: 0.226302 data_time: 0.024065 memory: 7326 loss_kpt: 0.000646 acc_pose: 0.780962 loss: 0.000646 2022/10/20 12:18:07 - mmengine - INFO - Epoch(train) [57][250/586] lr: 5.000000e-04 eta: 5:21:29 time: 0.233862 data_time: 0.026318 memory: 7326 loss_kpt: 0.000663 acc_pose: 0.802309 loss: 0.000663 2022/10/20 12:18:18 - mmengine - INFO - Epoch(train) [57][300/586] lr: 5.000000e-04 eta: 5:21:20 time: 0.229126 data_time: 0.025499 memory: 7326 loss_kpt: 0.000648 acc_pose: 0.863619 loss: 0.000648 2022/10/20 12:18:29 - mmengine - INFO - Epoch(train) [57][350/586] lr: 5.000000e-04 eta: 5:21:10 time: 0.220045 data_time: 0.024361 memory: 7326 loss_kpt: 0.000665 acc_pose: 0.783927 loss: 0.000665 2022/10/20 12:18:41 - mmengine - INFO - Epoch(train) [57][400/586] lr: 5.000000e-04 eta: 5:21:01 time: 0.225389 data_time: 0.027822 memory: 7326 loss_kpt: 0.000638 acc_pose: 0.846441 loss: 0.000638 2022/10/20 12:18:52 - mmengine - INFO - Epoch(train) [57][450/586] lr: 5.000000e-04 eta: 5:20:52 time: 0.227546 data_time: 0.025129 memory: 7326 loss_kpt: 0.000640 acc_pose: 0.824570 loss: 0.000640 2022/10/20 12:19:03 - mmengine - INFO - Epoch(train) [57][500/586] lr: 5.000000e-04 eta: 5:20:43 time: 0.223602 data_time: 0.024633 memory: 7326 loss_kpt: 0.000660 acc_pose: 0.877185 loss: 0.000660 2022/10/20 12:19:14 - mmengine - INFO - Epoch(train) [57][550/586] lr: 5.000000e-04 eta: 5:20:33 time: 0.223916 data_time: 0.024205 memory: 7326 loss_kpt: 0.000664 acc_pose: 0.806106 loss: 0.000664 2022/10/20 12:19:22 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:19:34 - mmengine - INFO - Epoch(train) [58][50/586] lr: 5.000000e-04 eta: 5:19:57 time: 0.236946 data_time: 0.031700 memory: 7326 loss_kpt: 0.000665 acc_pose: 0.734469 loss: 0.000665 2022/10/20 12:19:46 - mmengine - INFO - Epoch(train) [58][100/586] lr: 5.000000e-04 eta: 5:19:49 time: 0.233486 data_time: 0.023800 memory: 7326 loss_kpt: 0.000663 acc_pose: 0.766916 loss: 0.000663 2022/10/20 12:19:57 - mmengine - INFO - Epoch(train) [58][150/586] lr: 5.000000e-04 eta: 5:19:40 time: 0.228650 data_time: 0.024762 memory: 7326 loss_kpt: 0.000666 acc_pose: 0.836910 loss: 0.000666 2022/10/20 12:20:08 - mmengine - INFO - Epoch(train) [58][200/586] lr: 5.000000e-04 eta: 5:19:31 time: 0.223227 data_time: 0.024729 memory: 7326 loss_kpt: 0.000644 acc_pose: 0.845442 loss: 0.000644 2022/10/20 12:20:20 - mmengine - INFO - Epoch(train) [58][250/586] lr: 5.000000e-04 eta: 5:19:22 time: 0.226180 data_time: 0.026102 memory: 7326 loss_kpt: 0.000668 acc_pose: 0.790008 loss: 0.000668 2022/10/20 12:20:31 - mmengine - INFO - Epoch(train) [58][300/586] lr: 5.000000e-04 eta: 5:19:12 time: 0.220872 data_time: 0.026238 memory: 7326 loss_kpt: 0.000662 acc_pose: 0.805184 loss: 0.000662 2022/10/20 12:20:42 - mmengine - INFO - Epoch(train) [58][350/586] lr: 5.000000e-04 eta: 5:19:02 time: 0.224427 data_time: 0.026410 memory: 7326 loss_kpt: 0.000635 acc_pose: 0.807058 loss: 0.000635 2022/10/20 12:20:54 - mmengine - INFO - Epoch(train) [58][400/586] lr: 5.000000e-04 eta: 5:18:55 time: 0.235831 data_time: 0.024877 memory: 7326 loss_kpt: 0.000640 acc_pose: 0.809978 loss: 0.000640 2022/10/20 12:21:05 - mmengine - INFO - Epoch(train) [58][450/586] lr: 5.000000e-04 eta: 5:18:44 time: 0.217686 data_time: 0.024673 memory: 7326 loss_kpt: 0.000644 acc_pose: 0.771043 loss: 0.000644 2022/10/20 12:21:16 - mmengine - INFO - Epoch(train) [58][500/586] lr: 5.000000e-04 eta: 5:18:35 time: 0.221587 data_time: 0.022447 memory: 7326 loss_kpt: 0.000659 acc_pose: 0.834357 loss: 0.000659 2022/10/20 12:21:27 - mmengine - INFO - Epoch(train) [58][550/586] lr: 5.000000e-04 eta: 5:18:25 time: 0.226435 data_time: 0.025659 memory: 7326 loss_kpt: 0.000620 acc_pose: 0.828429 loss: 0.000620 2022/10/20 12:21:35 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:21:38 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:21:47 - mmengine - INFO - Epoch(train) [59][50/586] lr: 5.000000e-04 eta: 5:17:50 time: 0.240814 data_time: 0.036409 memory: 7326 loss_kpt: 0.000658 acc_pose: 0.920455 loss: 0.000658 2022/10/20 12:21:59 - mmengine - INFO - Epoch(train) [59][100/586] lr: 5.000000e-04 eta: 5:17:42 time: 0.230807 data_time: 0.026729 memory: 7326 loss_kpt: 0.000682 acc_pose: 0.784712 loss: 0.000682 2022/10/20 12:22:10 - mmengine - INFO - Epoch(train) [59][150/586] lr: 5.000000e-04 eta: 5:17:32 time: 0.221553 data_time: 0.024562 memory: 7326 loss_kpt: 0.000661 acc_pose: 0.871483 loss: 0.000661 2022/10/20 12:22:21 - mmengine - INFO - Epoch(train) [59][200/586] lr: 5.000000e-04 eta: 5:17:22 time: 0.221393 data_time: 0.024903 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.793365 loss: 0.000636 2022/10/20 12:22:32 - mmengine - INFO - Epoch(train) [59][250/586] lr: 5.000000e-04 eta: 5:17:12 time: 0.221298 data_time: 0.022568 memory: 7326 loss_kpt: 0.000633 acc_pose: 0.795990 loss: 0.000633 2022/10/20 12:22:43 - mmengine - INFO - Epoch(train) [59][300/586] lr: 5.000000e-04 eta: 5:17:04 time: 0.229290 data_time: 0.022633 memory: 7326 loss_kpt: 0.000653 acc_pose: 0.845954 loss: 0.000653 2022/10/20 12:22:55 - mmengine - INFO - Epoch(train) [59][350/586] lr: 5.000000e-04 eta: 5:16:55 time: 0.228564 data_time: 0.027316 memory: 7326 loss_kpt: 0.000652 acc_pose: 0.789310 loss: 0.000652 2022/10/20 12:23:06 - mmengine - INFO - Epoch(train) [59][400/586] lr: 5.000000e-04 eta: 5:16:45 time: 0.225641 data_time: 0.027039 memory: 7326 loss_kpt: 0.000661 acc_pose: 0.852835 loss: 0.000661 2022/10/20 12:23:17 - mmengine - INFO - Epoch(train) [59][450/586] lr: 5.000000e-04 eta: 5:16:36 time: 0.226822 data_time: 0.023821 memory: 7326 loss_kpt: 0.000654 acc_pose: 0.809356 loss: 0.000654 2022/10/20 12:23:29 - mmengine - INFO - Epoch(train) [59][500/586] lr: 5.000000e-04 eta: 5:16:27 time: 0.225484 data_time: 0.024576 memory: 7326 loss_kpt: 0.000652 acc_pose: 0.812241 loss: 0.000652 2022/10/20 12:23:40 - mmengine - INFO - Epoch(train) [59][550/586] lr: 5.000000e-04 eta: 5:16:17 time: 0.222937 data_time: 0.028785 memory: 7326 loss_kpt: 0.000658 acc_pose: 0.815745 loss: 0.000658 2022/10/20 12:23:48 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:23:59 - mmengine - INFO - Epoch(train) [60][50/586] lr: 5.000000e-04 eta: 5:15:42 time: 0.233829 data_time: 0.032383 memory: 7326 loss_kpt: 0.000661 acc_pose: 0.814427 loss: 0.000661 2022/10/20 12:24:10 - mmengine - INFO - Epoch(train) [60][100/586] lr: 5.000000e-04 eta: 5:15:32 time: 0.221331 data_time: 0.022541 memory: 7326 loss_kpt: 0.000659 acc_pose: 0.846830 loss: 0.000659 2022/10/20 12:24:22 - mmengine - INFO - Epoch(train) [60][150/586] lr: 5.000000e-04 eta: 5:15:24 time: 0.232719 data_time: 0.025365 memory: 7326 loss_kpt: 0.000652 acc_pose: 0.830330 loss: 0.000652 2022/10/20 12:24:33 - mmengine - INFO - Epoch(train) [60][200/586] lr: 5.000000e-04 eta: 5:15:14 time: 0.222724 data_time: 0.023087 memory: 7326 loss_kpt: 0.000646 acc_pose: 0.797118 loss: 0.000646 2022/10/20 12:24:45 - mmengine - INFO - Epoch(train) [60][250/586] lr: 5.000000e-04 eta: 5:15:05 time: 0.228253 data_time: 0.029201 memory: 7326 loss_kpt: 0.000647 acc_pose: 0.849610 loss: 0.000647 2022/10/20 12:24:56 - mmengine - INFO - Epoch(train) [60][300/586] lr: 5.000000e-04 eta: 5:14:56 time: 0.226714 data_time: 0.027608 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.808176 loss: 0.000641 2022/10/20 12:25:07 - mmengine - INFO - Epoch(train) [60][350/586] lr: 5.000000e-04 eta: 5:14:47 time: 0.225411 data_time: 0.024793 memory: 7326 loss_kpt: 0.000651 acc_pose: 0.822949 loss: 0.000651 2022/10/20 12:25:19 - mmengine - INFO - Epoch(train) [60][400/586] lr: 5.000000e-04 eta: 5:14:38 time: 0.233092 data_time: 0.026826 memory: 7326 loss_kpt: 0.000655 acc_pose: 0.855276 loss: 0.000655 2022/10/20 12:25:25 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:25:30 - mmengine - INFO - Epoch(train) [60][450/586] lr: 5.000000e-04 eta: 5:14:28 time: 0.221500 data_time: 0.029174 memory: 7326 loss_kpt: 0.000637 acc_pose: 0.826611 loss: 0.000637 2022/10/20 12:25:41 - mmengine - INFO - Epoch(train) [60][500/586] lr: 5.000000e-04 eta: 5:14:18 time: 0.217748 data_time: 0.025488 memory: 7326 loss_kpt: 0.000662 acc_pose: 0.827860 loss: 0.000662 2022/10/20 12:25:52 - mmengine - INFO - Epoch(train) [60][550/586] lr: 5.000000e-04 eta: 5:14:09 time: 0.223663 data_time: 0.025986 memory: 7326 loss_kpt: 0.000646 acc_pose: 0.800401 loss: 0.000646 2022/10/20 12:26:00 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:26:00 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/10/20 12:26:11 - mmengine - INFO - Epoch(val) [60][50/407] eta: 0:00:46 time: 0.129724 data_time: 0.045984 memory: 7326 2022/10/20 12:26:17 - mmengine - INFO - Epoch(val) [60][100/407] eta: 0:00:36 time: 0.117495 data_time: 0.035360 memory: 1680 2022/10/20 12:26:23 - mmengine - INFO - Epoch(val) [60][150/407] eta: 0:00:28 time: 0.111320 data_time: 0.027398 memory: 1680 2022/10/20 12:26:29 - mmengine - INFO - Epoch(val) [60][200/407] eta: 0:00:24 time: 0.120486 data_time: 0.038296 memory: 1680 2022/10/20 12:26:34 - mmengine - INFO - Epoch(val) [60][250/407] eta: 0:00:18 time: 0.116678 data_time: 0.033839 memory: 1680 2022/10/20 12:26:40 - mmengine - INFO - Epoch(val) [60][300/407] eta: 0:00:12 time: 0.119981 data_time: 0.036740 memory: 1680 2022/10/20 12:26:47 - mmengine - INFO - Epoch(val) [60][350/407] eta: 0:00:06 time: 0.120302 data_time: 0.038681 memory: 1680 2022/10/20 12:26:51 - mmengine - INFO - Epoch(val) [60][400/407] eta: 0:00:00 time: 0.095519 data_time: 0.020236 memory: 1680 2022/10/20 12:27:24 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 12:27:37 - mmengine - INFO - Epoch(val) [60][407/407] coco/AP: 0.716793 coco/AP .5: 0.897757 coco/AP .75: 0.797077 coco/AP (M): 0.679925 coco/AP (L): 0.782027 coco/AR: 0.772040 coco/AR .5: 0.933564 coco/AR .75: 0.843199 coco/AR (M): 0.729309 coco/AR (L): 0.833742 2022/10/20 12:27:37 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_50.pth is removed 2022/10/20 12:27:39 - mmengine - INFO - The best checkpoint with 0.7168 coco/AP at 60 epoch is saved to best_coco/AP_epoch_60.pth. 2022/10/20 12:27:51 - mmengine - INFO - Epoch(train) [61][50/586] lr: 5.000000e-04 eta: 5:13:34 time: 0.237583 data_time: 0.031108 memory: 7326 loss_kpt: 0.000651 acc_pose: 0.795631 loss: 0.000651 2022/10/20 12:28:02 - mmengine - INFO - Epoch(train) [61][100/586] lr: 5.000000e-04 eta: 5:13:24 time: 0.222644 data_time: 0.023827 memory: 7326 loss_kpt: 0.000638 acc_pose: 0.830303 loss: 0.000638 2022/10/20 12:28:14 - mmengine - INFO - Epoch(train) [61][150/586] lr: 5.000000e-04 eta: 5:13:14 time: 0.222532 data_time: 0.023438 memory: 7326 loss_kpt: 0.000645 acc_pose: 0.818283 loss: 0.000645 2022/10/20 12:28:26 - mmengine - INFO - Epoch(train) [61][200/586] lr: 5.000000e-04 eta: 5:13:07 time: 0.240832 data_time: 0.023174 memory: 7326 loss_kpt: 0.000650 acc_pose: 0.853579 loss: 0.000650 2022/10/20 12:28:37 - mmengine - INFO - Epoch(train) [61][250/586] lr: 5.000000e-04 eta: 5:12:58 time: 0.225967 data_time: 0.028674 memory: 7326 loss_kpt: 0.000661 acc_pose: 0.818488 loss: 0.000661 2022/10/20 12:28:48 - mmengine - INFO - Epoch(train) [61][300/586] lr: 5.000000e-04 eta: 5:12:49 time: 0.230763 data_time: 0.024813 memory: 7326 loss_kpt: 0.000663 acc_pose: 0.830547 loss: 0.000663 2022/10/20 12:29:00 - mmengine - INFO - Epoch(train) [61][350/586] lr: 5.000000e-04 eta: 5:12:40 time: 0.224714 data_time: 0.027215 memory: 7326 loss_kpt: 0.000638 acc_pose: 0.802223 loss: 0.000638 2022/10/20 12:29:11 - mmengine - INFO - Epoch(train) [61][400/586] lr: 5.000000e-04 eta: 5:12:31 time: 0.231999 data_time: 0.025817 memory: 7326 loss_kpt: 0.000646 acc_pose: 0.733160 loss: 0.000646 2022/10/20 12:29:23 - mmengine - INFO - Epoch(train) [61][450/586] lr: 5.000000e-04 eta: 5:12:22 time: 0.227942 data_time: 0.024801 memory: 7326 loss_kpt: 0.000674 acc_pose: 0.803438 loss: 0.000674 2022/10/20 12:29:34 - mmengine - INFO - Epoch(train) [61][500/586] lr: 5.000000e-04 eta: 5:12:12 time: 0.220348 data_time: 0.024584 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.805183 loss: 0.000622 2022/10/20 12:29:45 - mmengine - INFO - Epoch(train) [61][550/586] lr: 5.000000e-04 eta: 5:12:03 time: 0.228223 data_time: 0.024877 memory: 7326 loss_kpt: 0.000662 acc_pose: 0.860830 loss: 0.000662 2022/10/20 12:29:53 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:30:05 - mmengine - INFO - Epoch(train) [62][50/586] lr: 5.000000e-04 eta: 5:11:28 time: 0.234181 data_time: 0.033141 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.880053 loss: 0.000641 2022/10/20 12:30:16 - mmengine - INFO - Epoch(train) [62][100/586] lr: 5.000000e-04 eta: 5:11:19 time: 0.225507 data_time: 0.024580 memory: 7326 loss_kpt: 0.000657 acc_pose: 0.866246 loss: 0.000657 2022/10/20 12:30:28 - mmengine - INFO - Epoch(train) [62][150/586] lr: 5.000000e-04 eta: 5:11:10 time: 0.232584 data_time: 0.027937 memory: 7326 loss_kpt: 0.000647 acc_pose: 0.779262 loss: 0.000647 2022/10/20 12:30:39 - mmengine - INFO - Epoch(train) [62][200/586] lr: 5.000000e-04 eta: 5:11:02 time: 0.229183 data_time: 0.030111 memory: 7326 loss_kpt: 0.000634 acc_pose: 0.814840 loss: 0.000634 2022/10/20 12:30:50 - mmengine - INFO - Epoch(train) [62][250/586] lr: 5.000000e-04 eta: 5:10:52 time: 0.221720 data_time: 0.026183 memory: 7326 loss_kpt: 0.000645 acc_pose: 0.802377 loss: 0.000645 2022/10/20 12:30:51 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:31:02 - mmengine - INFO - Epoch(train) [62][300/586] lr: 5.000000e-04 eta: 5:10:43 time: 0.229012 data_time: 0.025894 memory: 7326 loss_kpt: 0.000643 acc_pose: 0.864756 loss: 0.000643 2022/10/20 12:31:13 - mmengine - INFO - Epoch(train) [62][350/586] lr: 5.000000e-04 eta: 5:10:34 time: 0.231568 data_time: 0.032616 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.841959 loss: 0.000642 2022/10/20 12:31:25 - mmengine - INFO - Epoch(train) [62][400/586] lr: 5.000000e-04 eta: 5:10:25 time: 0.229248 data_time: 0.025435 memory: 7326 loss_kpt: 0.000639 acc_pose: 0.845575 loss: 0.000639 2022/10/20 12:31:36 - mmengine - INFO - Epoch(train) [62][450/586] lr: 5.000000e-04 eta: 5:10:15 time: 0.219556 data_time: 0.024270 memory: 7326 loss_kpt: 0.000652 acc_pose: 0.821864 loss: 0.000652 2022/10/20 12:31:47 - mmengine - INFO - Epoch(train) [62][500/586] lr: 5.000000e-04 eta: 5:10:06 time: 0.229664 data_time: 0.028628 memory: 7326 loss_kpt: 0.000637 acc_pose: 0.848020 loss: 0.000637 2022/10/20 12:31:59 - mmengine - INFO - Epoch(train) [62][550/586] lr: 5.000000e-04 eta: 5:09:57 time: 0.225216 data_time: 0.027273 memory: 7326 loss_kpt: 0.000653 acc_pose: 0.777322 loss: 0.000653 2022/10/20 12:32:06 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:32:19 - mmengine - INFO - Epoch(train) [63][50/586] lr: 5.000000e-04 eta: 5:09:24 time: 0.247236 data_time: 0.036271 memory: 7326 loss_kpt: 0.000634 acc_pose: 0.851171 loss: 0.000634 2022/10/20 12:32:30 - mmengine - INFO - Epoch(train) [63][100/586] lr: 5.000000e-04 eta: 5:09:14 time: 0.223017 data_time: 0.023997 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.850511 loss: 0.000642 2022/10/20 12:32:41 - mmengine - INFO - Epoch(train) [63][150/586] lr: 5.000000e-04 eta: 5:09:05 time: 0.224772 data_time: 0.023391 memory: 7326 loss_kpt: 0.000638 acc_pose: 0.791542 loss: 0.000638 2022/10/20 12:32:53 - mmengine - INFO - Epoch(train) [63][200/586] lr: 5.000000e-04 eta: 5:08:56 time: 0.227920 data_time: 0.024616 memory: 7326 loss_kpt: 0.000638 acc_pose: 0.854947 loss: 0.000638 2022/10/20 12:33:04 - mmengine - INFO - Epoch(train) [63][250/586] lr: 5.000000e-04 eta: 5:08:46 time: 0.224129 data_time: 0.026228 memory: 7326 loss_kpt: 0.000655 acc_pose: 0.774146 loss: 0.000655 2022/10/20 12:33:16 - mmengine - INFO - Epoch(train) [63][300/586] lr: 5.000000e-04 eta: 5:08:38 time: 0.234346 data_time: 0.029258 memory: 7326 loss_kpt: 0.000635 acc_pose: 0.795355 loss: 0.000635 2022/10/20 12:33:27 - mmengine - INFO - Epoch(train) [63][350/586] lr: 5.000000e-04 eta: 5:08:28 time: 0.217990 data_time: 0.024082 memory: 7326 loss_kpt: 0.000639 acc_pose: 0.810818 loss: 0.000639 2022/10/20 12:33:38 - mmengine - INFO - Epoch(train) [63][400/586] lr: 5.000000e-04 eta: 5:08:19 time: 0.230678 data_time: 0.024982 memory: 7326 loss_kpt: 0.000618 acc_pose: 0.850919 loss: 0.000618 2022/10/20 12:33:49 - mmengine - INFO - Epoch(train) [63][450/586] lr: 5.000000e-04 eta: 5:08:09 time: 0.224326 data_time: 0.025492 memory: 7326 loss_kpt: 0.000653 acc_pose: 0.824312 loss: 0.000653 2022/10/20 12:34:00 - mmengine - INFO - Epoch(train) [63][500/586] lr: 5.000000e-04 eta: 5:08:00 time: 0.223481 data_time: 0.023990 memory: 7326 loss_kpt: 0.000627 acc_pose: 0.814081 loss: 0.000627 2022/10/20 12:34:12 - mmengine - INFO - Epoch(train) [63][550/586] lr: 5.000000e-04 eta: 5:07:51 time: 0.228458 data_time: 0.023658 memory: 7326 loss_kpt: 0.000649 acc_pose: 0.838484 loss: 0.000649 2022/10/20 12:34:20 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:34:32 - mmengine - INFO - Epoch(train) [64][50/586] lr: 5.000000e-04 eta: 5:07:17 time: 0.239479 data_time: 0.041420 memory: 7326 loss_kpt: 0.000640 acc_pose: 0.872668 loss: 0.000640 2022/10/20 12:34:39 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:34:43 - mmengine - INFO - Epoch(train) [64][100/586] lr: 5.000000e-04 eta: 5:07:07 time: 0.223033 data_time: 0.026311 memory: 7326 loss_kpt: 0.000649 acc_pose: 0.760747 loss: 0.000649 2022/10/20 12:34:55 - mmengine - INFO - Epoch(train) [64][150/586] lr: 5.000000e-04 eta: 5:06:59 time: 0.231888 data_time: 0.024687 memory: 7326 loss_kpt: 0.000664 acc_pose: 0.808950 loss: 0.000664 2022/10/20 12:35:06 - mmengine - INFO - Epoch(train) [64][200/586] lr: 5.000000e-04 eta: 5:06:50 time: 0.226797 data_time: 0.023035 memory: 7326 loss_kpt: 0.000630 acc_pose: 0.795625 loss: 0.000630 2022/10/20 12:35:18 - mmengine - INFO - Epoch(train) [64][250/586] lr: 5.000000e-04 eta: 5:06:41 time: 0.229925 data_time: 0.024985 memory: 7326 loss_kpt: 0.000651 acc_pose: 0.855500 loss: 0.000651 2022/10/20 12:35:29 - mmengine - INFO - Epoch(train) [64][300/586] lr: 5.000000e-04 eta: 5:06:31 time: 0.226036 data_time: 0.024561 memory: 7326 loss_kpt: 0.000657 acc_pose: 0.828187 loss: 0.000657 2022/10/20 12:35:40 - mmengine - INFO - Epoch(train) [64][350/586] lr: 5.000000e-04 eta: 5:06:22 time: 0.225492 data_time: 0.024422 memory: 7326 loss_kpt: 0.000664 acc_pose: 0.820306 loss: 0.000664 2022/10/20 12:35:52 - mmengine - INFO - Epoch(train) [64][400/586] lr: 5.000000e-04 eta: 5:06:13 time: 0.232718 data_time: 0.027874 memory: 7326 loss_kpt: 0.000638 acc_pose: 0.765258 loss: 0.000638 2022/10/20 12:36:03 - mmengine - INFO - Epoch(train) [64][450/586] lr: 5.000000e-04 eta: 5:06:03 time: 0.221128 data_time: 0.027320 memory: 7326 loss_kpt: 0.000630 acc_pose: 0.815667 loss: 0.000630 2022/10/20 12:36:14 - mmengine - INFO - Epoch(train) [64][500/586] lr: 5.000000e-04 eta: 5:05:54 time: 0.224307 data_time: 0.023139 memory: 7326 loss_kpt: 0.000649 acc_pose: 0.867078 loss: 0.000649 2022/10/20 12:36:26 - mmengine - INFO - Epoch(train) [64][550/586] lr: 5.000000e-04 eta: 5:05:45 time: 0.229316 data_time: 0.027691 memory: 7326 loss_kpt: 0.000633 acc_pose: 0.875769 loss: 0.000633 2022/10/20 12:36:34 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:36:45 - mmengine - INFO - Epoch(train) [65][50/586] lr: 5.000000e-04 eta: 5:05:11 time: 0.234727 data_time: 0.031268 memory: 7326 loss_kpt: 0.000634 acc_pose: 0.886185 loss: 0.000634 2022/10/20 12:36:57 - mmengine - INFO - Epoch(train) [65][100/586] lr: 5.000000e-04 eta: 5:05:02 time: 0.226916 data_time: 0.023080 memory: 7326 loss_kpt: 0.000633 acc_pose: 0.787494 loss: 0.000633 2022/10/20 12:37:08 - mmengine - INFO - Epoch(train) [65][150/586] lr: 5.000000e-04 eta: 5:04:52 time: 0.220598 data_time: 0.023464 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.827542 loss: 0.000642 2022/10/20 12:37:19 - mmengine - INFO - Epoch(train) [65][200/586] lr: 5.000000e-04 eta: 5:04:42 time: 0.225467 data_time: 0.025689 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.874731 loss: 0.000636 2022/10/20 12:37:31 - mmengine - INFO - Epoch(train) [65][250/586] lr: 5.000000e-04 eta: 5:04:34 time: 0.229664 data_time: 0.024227 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.763453 loss: 0.000642 2022/10/20 12:37:42 - mmengine - INFO - Epoch(train) [65][300/586] lr: 5.000000e-04 eta: 5:04:25 time: 0.230627 data_time: 0.028326 memory: 7326 loss_kpt: 0.000633 acc_pose: 0.775996 loss: 0.000633 2022/10/20 12:37:53 - mmengine - INFO - Epoch(train) [65][350/586] lr: 5.000000e-04 eta: 5:04:15 time: 0.222878 data_time: 0.024480 memory: 7326 loss_kpt: 0.000640 acc_pose: 0.801972 loss: 0.000640 2022/10/20 12:38:04 - mmengine - INFO - Epoch(train) [65][400/586] lr: 5.000000e-04 eta: 5:04:05 time: 0.221820 data_time: 0.025156 memory: 7326 loss_kpt: 0.000627 acc_pose: 0.781290 loss: 0.000627 2022/10/20 12:38:16 - mmengine - INFO - Epoch(train) [65][450/586] lr: 5.000000e-04 eta: 5:03:57 time: 0.234554 data_time: 0.025477 memory: 7326 loss_kpt: 0.000662 acc_pose: 0.885960 loss: 0.000662 2022/10/20 12:38:27 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:38:27 - mmengine - INFO - Epoch(train) [65][500/586] lr: 5.000000e-04 eta: 5:03:47 time: 0.226042 data_time: 0.027076 memory: 7326 loss_kpt: 0.000673 acc_pose: 0.816330 loss: 0.000673 2022/10/20 12:38:39 - mmengine - INFO - Epoch(train) [65][550/586] lr: 5.000000e-04 eta: 5:03:37 time: 0.222669 data_time: 0.025679 memory: 7326 loss_kpt: 0.000648 acc_pose: 0.852449 loss: 0.000648 2022/10/20 12:38:46 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:38:58 - mmengine - INFO - Epoch(train) [66][50/586] lr: 5.000000e-04 eta: 5:03:04 time: 0.236474 data_time: 0.037232 memory: 7326 loss_kpt: 0.000637 acc_pose: 0.822221 loss: 0.000637 2022/10/20 12:39:09 - mmengine - INFO - Epoch(train) [66][100/586] lr: 5.000000e-04 eta: 5:02:55 time: 0.225809 data_time: 0.022904 memory: 7326 loss_kpt: 0.000663 acc_pose: 0.856164 loss: 0.000663 2022/10/20 12:39:21 - mmengine - INFO - Epoch(train) [66][150/586] lr: 5.000000e-04 eta: 5:02:46 time: 0.226352 data_time: 0.026734 memory: 7326 loss_kpt: 0.000628 acc_pose: 0.817814 loss: 0.000628 2022/10/20 12:39:32 - mmengine - INFO - Epoch(train) [66][200/586] lr: 5.000000e-04 eta: 5:02:37 time: 0.232570 data_time: 0.028494 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.801515 loss: 0.000636 2022/10/20 12:39:44 - mmengine - INFO - Epoch(train) [66][250/586] lr: 5.000000e-04 eta: 5:02:27 time: 0.226022 data_time: 0.028821 memory: 7326 loss_kpt: 0.000634 acc_pose: 0.806772 loss: 0.000634 2022/10/20 12:39:55 - mmengine - INFO - Epoch(train) [66][300/586] lr: 5.000000e-04 eta: 5:02:18 time: 0.229130 data_time: 0.023283 memory: 7326 loss_kpt: 0.000651 acc_pose: 0.840909 loss: 0.000651 2022/10/20 12:40:06 - mmengine - INFO - Epoch(train) [66][350/586] lr: 5.000000e-04 eta: 5:02:09 time: 0.224208 data_time: 0.026237 memory: 7326 loss_kpt: 0.000653 acc_pose: 0.850365 loss: 0.000653 2022/10/20 12:40:18 - mmengine - INFO - Epoch(train) [66][400/586] lr: 5.000000e-04 eta: 5:02:00 time: 0.236433 data_time: 0.028659 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.864105 loss: 0.000641 2022/10/20 12:40:29 - mmengine - INFO - Epoch(train) [66][450/586] lr: 5.000000e-04 eta: 5:01:50 time: 0.217770 data_time: 0.024334 memory: 7326 loss_kpt: 0.000648 acc_pose: 0.779242 loss: 0.000648 2022/10/20 12:40:40 - mmengine - INFO - Epoch(train) [66][500/586] lr: 5.000000e-04 eta: 5:01:41 time: 0.225193 data_time: 0.028513 memory: 7326 loss_kpt: 0.000646 acc_pose: 0.876249 loss: 0.000646 2022/10/20 12:40:52 - mmengine - INFO - Epoch(train) [66][550/586] lr: 5.000000e-04 eta: 5:01:31 time: 0.228137 data_time: 0.025202 memory: 7326 loss_kpt: 0.000649 acc_pose: 0.864205 loss: 0.000649 2022/10/20 12:41:00 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:41:12 - mmengine - INFO - Epoch(train) [67][50/586] lr: 5.000000e-04 eta: 5:00:59 time: 0.238342 data_time: 0.031440 memory: 7326 loss_kpt: 0.000632 acc_pose: 0.840885 loss: 0.000632 2022/10/20 12:41:23 - mmengine - INFO - Epoch(train) [67][100/586] lr: 5.000000e-04 eta: 5:00:49 time: 0.221444 data_time: 0.024536 memory: 7326 loss_kpt: 0.000631 acc_pose: 0.804818 loss: 0.000631 2022/10/20 12:41:34 - mmengine - INFO - Epoch(train) [67][150/586] lr: 5.000000e-04 eta: 5:00:39 time: 0.225548 data_time: 0.024020 memory: 7326 loss_kpt: 0.000667 acc_pose: 0.817718 loss: 0.000667 2022/10/20 12:41:45 - mmengine - INFO - Epoch(train) [67][200/586] lr: 5.000000e-04 eta: 5:00:30 time: 0.224593 data_time: 0.025083 memory: 7326 loss_kpt: 0.000651 acc_pose: 0.775366 loss: 0.000651 2022/10/20 12:41:57 - mmengine - INFO - Epoch(train) [67][250/586] lr: 5.000000e-04 eta: 5:00:21 time: 0.234507 data_time: 0.029122 memory: 7326 loss_kpt: 0.000654 acc_pose: 0.823114 loss: 0.000654 2022/10/20 12:42:09 - mmengine - INFO - Epoch(train) [67][300/586] lr: 5.000000e-04 eta: 5:00:13 time: 0.232065 data_time: 0.024365 memory: 7326 loss_kpt: 0.000639 acc_pose: 0.829757 loss: 0.000639 2022/10/20 12:42:14 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:42:20 - mmengine - INFO - Epoch(train) [67][350/586] lr: 5.000000e-04 eta: 5:00:03 time: 0.226708 data_time: 0.025825 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.791930 loss: 0.000619 2022/10/20 12:42:31 - mmengine - INFO - Epoch(train) [67][400/586] lr: 5.000000e-04 eta: 4:59:53 time: 0.222097 data_time: 0.024110 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.827210 loss: 0.000622 2022/10/20 12:42:42 - mmengine - INFO - Epoch(train) [67][450/586] lr: 5.000000e-04 eta: 4:59:44 time: 0.225776 data_time: 0.026233 memory: 7326 loss_kpt: 0.000640 acc_pose: 0.758190 loss: 0.000640 2022/10/20 12:42:54 - mmengine - INFO - Epoch(train) [67][500/586] lr: 5.000000e-04 eta: 4:59:34 time: 0.223483 data_time: 0.023429 memory: 7326 loss_kpt: 0.000648 acc_pose: 0.828029 loss: 0.000648 2022/10/20 12:43:05 - mmengine - INFO - Epoch(train) [67][550/586] lr: 5.000000e-04 eta: 4:59:25 time: 0.227847 data_time: 0.030659 memory: 7326 loss_kpt: 0.000652 acc_pose: 0.850990 loss: 0.000652 2022/10/20 12:43:13 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:43:25 - mmengine - INFO - Epoch(train) [68][50/586] lr: 5.000000e-04 eta: 4:58:53 time: 0.239603 data_time: 0.033041 memory: 7326 loss_kpt: 0.000648 acc_pose: 0.818332 loss: 0.000648 2022/10/20 12:43:36 - mmengine - INFO - Epoch(train) [68][100/586] lr: 5.000000e-04 eta: 4:58:43 time: 0.226483 data_time: 0.024668 memory: 7326 loss_kpt: 0.000631 acc_pose: 0.856454 loss: 0.000631 2022/10/20 12:43:47 - mmengine - INFO - Epoch(train) [68][150/586] lr: 5.000000e-04 eta: 4:58:34 time: 0.223479 data_time: 0.027331 memory: 7326 loss_kpt: 0.000633 acc_pose: 0.828080 loss: 0.000633 2022/10/20 12:43:59 - mmengine - INFO - Epoch(train) [68][200/586] lr: 5.000000e-04 eta: 4:58:24 time: 0.227425 data_time: 0.024742 memory: 7326 loss_kpt: 0.000638 acc_pose: 0.762960 loss: 0.000638 2022/10/20 12:44:10 - mmengine - INFO - Epoch(train) [68][250/586] lr: 5.000000e-04 eta: 4:58:14 time: 0.221212 data_time: 0.024323 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.809299 loss: 0.000641 2022/10/20 12:44:21 - mmengine - INFO - Epoch(train) [68][300/586] lr: 5.000000e-04 eta: 4:58:05 time: 0.225274 data_time: 0.028114 memory: 7326 loss_kpt: 0.000628 acc_pose: 0.844266 loss: 0.000628 2022/10/20 12:44:32 - mmengine - INFO - Epoch(train) [68][350/586] lr: 5.000000e-04 eta: 4:57:55 time: 0.221633 data_time: 0.025149 memory: 7326 loss_kpt: 0.000649 acc_pose: 0.827711 loss: 0.000649 2022/10/20 12:44:44 - mmengine - INFO - Epoch(train) [68][400/586] lr: 5.000000e-04 eta: 4:57:46 time: 0.235176 data_time: 0.023997 memory: 7326 loss_kpt: 0.000650 acc_pose: 0.840573 loss: 0.000650 2022/10/20 12:44:55 - mmengine - INFO - Epoch(train) [68][450/586] lr: 5.000000e-04 eta: 4:57:36 time: 0.216956 data_time: 0.024050 memory: 7326 loss_kpt: 0.000631 acc_pose: 0.837068 loss: 0.000631 2022/10/20 12:45:06 - mmengine - INFO - Epoch(train) [68][500/586] lr: 5.000000e-04 eta: 4:57:27 time: 0.231547 data_time: 0.031581 memory: 7326 loss_kpt: 0.000658 acc_pose: 0.795151 loss: 0.000658 2022/10/20 12:45:18 - mmengine - INFO - Epoch(train) [68][550/586] lr: 5.000000e-04 eta: 4:57:18 time: 0.228374 data_time: 0.027053 memory: 7326 loss_kpt: 0.000644 acc_pose: 0.811826 loss: 0.000644 2022/10/20 12:45:26 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:45:37 - mmengine - INFO - Epoch(train) [69][50/586] lr: 5.000000e-04 eta: 4:56:45 time: 0.234883 data_time: 0.031287 memory: 7326 loss_kpt: 0.000623 acc_pose: 0.843752 loss: 0.000623 2022/10/20 12:45:49 - mmengine - INFO - Epoch(train) [69][100/586] lr: 5.000000e-04 eta: 4:56:36 time: 0.228459 data_time: 0.028368 memory: 7326 loss_kpt: 0.000617 acc_pose: 0.816307 loss: 0.000617 2022/10/20 12:46:00 - mmengine - INFO - Epoch(train) [69][150/586] lr: 5.000000e-04 eta: 4:56:27 time: 0.223776 data_time: 0.025182 memory: 7326 loss_kpt: 0.000637 acc_pose: 0.781009 loss: 0.000637 2022/10/20 12:46:00 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:46:12 - mmengine - INFO - Epoch(train) [69][200/586] lr: 5.000000e-04 eta: 4:56:17 time: 0.230039 data_time: 0.025406 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.781579 loss: 0.000619 2022/10/20 12:46:23 - mmengine - INFO - Epoch(train) [69][250/586] lr: 5.000000e-04 eta: 4:56:08 time: 0.226681 data_time: 0.028680 memory: 7326 loss_kpt: 0.000628 acc_pose: 0.859699 loss: 0.000628 2022/10/20 12:46:34 - mmengine - INFO - Epoch(train) [69][300/586] lr: 5.000000e-04 eta: 4:55:59 time: 0.226245 data_time: 0.023646 memory: 7326 loss_kpt: 0.000623 acc_pose: 0.870713 loss: 0.000623 2022/10/20 12:46:45 - mmengine - INFO - Epoch(train) [69][350/586] lr: 5.000000e-04 eta: 4:55:49 time: 0.220680 data_time: 0.024867 memory: 7326 loss_kpt: 0.000633 acc_pose: 0.886536 loss: 0.000633 2022/10/20 12:46:57 - mmengine - INFO - Epoch(train) [69][400/586] lr: 5.000000e-04 eta: 4:55:39 time: 0.229368 data_time: 0.024288 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.783247 loss: 0.000642 2022/10/20 12:47:08 - mmengine - INFO - Epoch(train) [69][450/586] lr: 5.000000e-04 eta: 4:55:30 time: 0.226577 data_time: 0.030344 memory: 7326 loss_kpt: 0.000635 acc_pose: 0.868118 loss: 0.000635 2022/10/20 12:47:19 - mmengine - INFO - Epoch(train) [69][500/586] lr: 5.000000e-04 eta: 4:55:20 time: 0.223165 data_time: 0.031134 memory: 7326 loss_kpt: 0.000645 acc_pose: 0.844355 loss: 0.000645 2022/10/20 12:47:31 - mmengine - INFO - Epoch(train) [69][550/586] lr: 5.000000e-04 eta: 4:55:11 time: 0.228800 data_time: 0.027216 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.824867 loss: 0.000641 2022/10/20 12:47:39 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:47:50 - mmengine - INFO - Epoch(train) [70][50/586] lr: 5.000000e-04 eta: 4:54:39 time: 0.238633 data_time: 0.033674 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.843299 loss: 0.000636 2022/10/20 12:48:02 - mmengine - INFO - Epoch(train) [70][100/586] lr: 5.000000e-04 eta: 4:54:30 time: 0.230041 data_time: 0.023763 memory: 7326 loss_kpt: 0.000643 acc_pose: 0.863101 loss: 0.000643 2022/10/20 12:48:13 - mmengine - INFO - Epoch(train) [70][150/586] lr: 5.000000e-04 eta: 4:54:21 time: 0.225698 data_time: 0.025194 memory: 7326 loss_kpt: 0.000649 acc_pose: 0.856202 loss: 0.000649 2022/10/20 12:48:25 - mmengine - INFO - Epoch(train) [70][200/586] lr: 5.000000e-04 eta: 4:54:11 time: 0.225455 data_time: 0.023829 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.831352 loss: 0.000625 2022/10/20 12:48:36 - mmengine - INFO - Epoch(train) [70][250/586] lr: 5.000000e-04 eta: 4:54:01 time: 0.225011 data_time: 0.027762 memory: 7326 loss_kpt: 0.000618 acc_pose: 0.843854 loss: 0.000618 2022/10/20 12:48:47 - mmengine - INFO - Epoch(train) [70][300/586] lr: 5.000000e-04 eta: 4:53:52 time: 0.224745 data_time: 0.022992 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.768513 loss: 0.000625 2022/10/20 12:48:58 - mmengine - INFO - Epoch(train) [70][350/586] lr: 5.000000e-04 eta: 4:53:42 time: 0.222458 data_time: 0.024454 memory: 7326 loss_kpt: 0.000653 acc_pose: 0.882848 loss: 0.000653 2022/10/20 12:49:10 - mmengine - INFO - Epoch(train) [70][400/586] lr: 5.000000e-04 eta: 4:53:34 time: 0.239080 data_time: 0.026338 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.852444 loss: 0.000641 2022/10/20 12:49:21 - mmengine - INFO - Epoch(train) [70][450/586] lr: 5.000000e-04 eta: 4:53:24 time: 0.221205 data_time: 0.026152 memory: 7326 loss_kpt: 0.000632 acc_pose: 0.848602 loss: 0.000632 2022/10/20 12:49:33 - mmengine - INFO - Epoch(train) [70][500/586] lr: 5.000000e-04 eta: 4:53:15 time: 0.230687 data_time: 0.026760 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.841302 loss: 0.000625 2022/10/20 12:49:44 - mmengine - INFO - Epoch(train) [70][550/586] lr: 5.000000e-04 eta: 4:53:05 time: 0.226064 data_time: 0.027524 memory: 7326 loss_kpt: 0.000637 acc_pose: 0.818669 loss: 0.000637 2022/10/20 12:49:48 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:49:52 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:49:52 - mmengine - INFO - Saving checkpoint at 70 epochs 2022/10/20 12:50:02 - mmengine - INFO - Epoch(val) [70][50/407] eta: 0:00:42 time: 0.119816 data_time: 0.036956 memory: 7326 2022/10/20 12:50:08 - mmengine - INFO - Epoch(val) [70][100/407] eta: 0:00:36 time: 0.117346 data_time: 0.030055 memory: 1680 2022/10/20 12:50:14 - mmengine - INFO - Epoch(val) [70][150/407] eta: 0:00:29 time: 0.113310 data_time: 0.030310 memory: 1680 2022/10/20 12:50:20 - mmengine - INFO - Epoch(val) [70][200/407] eta: 0:00:24 time: 0.118755 data_time: 0.037091 memory: 1680 2022/10/20 12:50:25 - mmengine - INFO - Epoch(val) [70][250/407] eta: 0:00:18 time: 0.116275 data_time: 0.032349 memory: 1680 2022/10/20 12:50:31 - mmengine - INFO - Epoch(val) [70][300/407] eta: 0:00:12 time: 0.118316 data_time: 0.035306 memory: 1680 2022/10/20 12:50:38 - mmengine - INFO - Epoch(val) [70][350/407] eta: 0:00:07 time: 0.124849 data_time: 0.041585 memory: 1680 2022/10/20 12:50:43 - mmengine - INFO - Epoch(val) [70][400/407] eta: 0:00:00 time: 0.109923 data_time: 0.032494 memory: 1680 2022/10/20 12:51:15 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 12:51:28 - mmengine - INFO - Epoch(val) [70][407/407] coco/AP: 0.717566 coco/AP .5: 0.896423 coco/AP .75: 0.795972 coco/AP (M): 0.682154 coco/AP (L): 0.783634 coco/AR: 0.773866 coco/AR .5: 0.934981 coco/AR .75: 0.843199 coco/AR (M): 0.730565 coco/AR (L): 0.835786 2022/10/20 12:51:28 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_60.pth is removed 2022/10/20 12:51:30 - mmengine - INFO - The best checkpoint with 0.7176 coco/AP at 70 epoch is saved to best_coco/AP_epoch_70.pth. 2022/10/20 12:51:42 - mmengine - INFO - Epoch(train) [71][50/586] lr: 5.000000e-04 eta: 4:52:34 time: 0.237308 data_time: 0.030283 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.847695 loss: 0.000619 2022/10/20 12:51:54 - mmengine - INFO - Epoch(train) [71][100/586] lr: 5.000000e-04 eta: 4:52:24 time: 0.224056 data_time: 0.025153 memory: 7326 loss_kpt: 0.000637 acc_pose: 0.815292 loss: 0.000637 2022/10/20 12:52:05 - mmengine - INFO - Epoch(train) [71][150/586] lr: 5.000000e-04 eta: 4:52:14 time: 0.221391 data_time: 0.023850 memory: 7326 loss_kpt: 0.000648 acc_pose: 0.789833 loss: 0.000648 2022/10/20 12:52:16 - mmengine - INFO - Epoch(train) [71][200/586] lr: 5.000000e-04 eta: 4:52:05 time: 0.232210 data_time: 0.025469 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.815410 loss: 0.000622 2022/10/20 12:52:28 - mmengine - INFO - Epoch(train) [71][250/586] lr: 5.000000e-04 eta: 4:51:55 time: 0.225773 data_time: 0.026288 memory: 7326 loss_kpt: 0.000660 acc_pose: 0.760007 loss: 0.000660 2022/10/20 12:52:39 - mmengine - INFO - Epoch(train) [71][300/586] lr: 5.000000e-04 eta: 4:51:47 time: 0.231947 data_time: 0.024893 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.841593 loss: 0.000625 2022/10/20 12:52:50 - mmengine - INFO - Epoch(train) [71][350/586] lr: 5.000000e-04 eta: 4:51:37 time: 0.225122 data_time: 0.025207 memory: 7326 loss_kpt: 0.000649 acc_pose: 0.875889 loss: 0.000649 2022/10/20 12:53:01 - mmengine - INFO - Epoch(train) [71][400/586] lr: 5.000000e-04 eta: 4:51:27 time: 0.217912 data_time: 0.023378 memory: 7326 loss_kpt: 0.000651 acc_pose: 0.819368 loss: 0.000651 2022/10/20 12:53:13 - mmengine - INFO - Epoch(train) [71][450/586] lr: 5.000000e-04 eta: 4:51:18 time: 0.232420 data_time: 0.027082 memory: 7326 loss_kpt: 0.000617 acc_pose: 0.760463 loss: 0.000617 2022/10/20 12:53:24 - mmengine - INFO - Epoch(train) [71][500/586] lr: 5.000000e-04 eta: 4:51:08 time: 0.224584 data_time: 0.024936 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.859468 loss: 0.000636 2022/10/20 12:53:36 - mmengine - INFO - Epoch(train) [71][550/586] lr: 5.000000e-04 eta: 4:50:59 time: 0.227285 data_time: 0.026156 memory: 7326 loss_kpt: 0.000630 acc_pose: 0.825170 loss: 0.000630 2022/10/20 12:53:44 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:53:55 - mmengine - INFO - Epoch(train) [72][50/586] lr: 5.000000e-04 eta: 4:50:27 time: 0.236375 data_time: 0.033253 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.822079 loss: 0.000636 2022/10/20 12:54:06 - mmengine - INFO - Epoch(train) [72][100/586] lr: 5.000000e-04 eta: 4:50:17 time: 0.222375 data_time: 0.027325 memory: 7326 loss_kpt: 0.000628 acc_pose: 0.813541 loss: 0.000628 2022/10/20 12:54:18 - mmengine - INFO - Epoch(train) [72][150/586] lr: 5.000000e-04 eta: 4:50:08 time: 0.229627 data_time: 0.024274 memory: 7326 loss_kpt: 0.000620 acc_pose: 0.807710 loss: 0.000620 2022/10/20 12:54:29 - mmengine - INFO - Epoch(train) [72][200/586] lr: 5.000000e-04 eta: 4:49:58 time: 0.222035 data_time: 0.026183 memory: 7326 loss_kpt: 0.000628 acc_pose: 0.805132 loss: 0.000628 2022/10/20 12:54:40 - mmengine - INFO - Epoch(train) [72][250/586] lr: 5.000000e-04 eta: 4:49:49 time: 0.228132 data_time: 0.025393 memory: 7326 loss_kpt: 0.000633 acc_pose: 0.864970 loss: 0.000633 2022/10/20 12:54:52 - mmengine - INFO - Epoch(train) [72][300/586] lr: 5.000000e-04 eta: 4:49:39 time: 0.228104 data_time: 0.024369 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.863835 loss: 0.000625 2022/10/20 12:55:03 - mmengine - INFO - Epoch(train) [72][350/586] lr: 5.000000e-04 eta: 4:49:29 time: 0.220339 data_time: 0.026113 memory: 7326 loss_kpt: 0.000637 acc_pose: 0.852059 loss: 0.000637 2022/10/20 12:55:13 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:55:14 - mmengine - INFO - Epoch(train) [72][400/586] lr: 5.000000e-04 eta: 4:49:20 time: 0.228860 data_time: 0.023127 memory: 7326 loss_kpt: 0.000627 acc_pose: 0.808701 loss: 0.000627 2022/10/20 12:55:26 - mmengine - INFO - Epoch(train) [72][450/586] lr: 5.000000e-04 eta: 4:49:11 time: 0.226923 data_time: 0.023382 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.842875 loss: 0.000641 2022/10/20 12:55:37 - mmengine - INFO - Epoch(train) [72][500/586] lr: 5.000000e-04 eta: 4:49:01 time: 0.224939 data_time: 0.025625 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.794256 loss: 0.000614 2022/10/20 12:55:48 - mmengine - INFO - Epoch(train) [72][550/586] lr: 5.000000e-04 eta: 4:48:52 time: 0.230053 data_time: 0.029973 memory: 7326 loss_kpt: 0.000626 acc_pose: 0.855680 loss: 0.000626 2022/10/20 12:55:56 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:56:08 - mmengine - INFO - Epoch(train) [73][50/586] lr: 5.000000e-04 eta: 4:48:21 time: 0.237130 data_time: 0.036519 memory: 7326 loss_kpt: 0.000621 acc_pose: 0.757433 loss: 0.000621 2022/10/20 12:56:20 - mmengine - INFO - Epoch(train) [73][100/586] lr: 5.000000e-04 eta: 4:48:11 time: 0.225638 data_time: 0.025971 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.819626 loss: 0.000625 2022/10/20 12:56:31 - mmengine - INFO - Epoch(train) [73][150/586] lr: 5.000000e-04 eta: 4:48:01 time: 0.219016 data_time: 0.024768 memory: 7326 loss_kpt: 0.000634 acc_pose: 0.872334 loss: 0.000634 2022/10/20 12:56:42 - mmengine - INFO - Epoch(train) [73][200/586] lr: 5.000000e-04 eta: 4:47:52 time: 0.228358 data_time: 0.025264 memory: 7326 loss_kpt: 0.000638 acc_pose: 0.838421 loss: 0.000638 2022/10/20 12:56:53 - mmengine - INFO - Epoch(train) [73][250/586] lr: 5.000000e-04 eta: 4:47:42 time: 0.229025 data_time: 0.023082 memory: 7326 loss_kpt: 0.000634 acc_pose: 0.804313 loss: 0.000634 2022/10/20 12:57:05 - mmengine - INFO - Epoch(train) [73][300/586] lr: 5.000000e-04 eta: 4:47:33 time: 0.226457 data_time: 0.024288 memory: 7326 loss_kpt: 0.000631 acc_pose: 0.847118 loss: 0.000631 2022/10/20 12:57:16 - mmengine - INFO - Epoch(train) [73][350/586] lr: 5.000000e-04 eta: 4:47:23 time: 0.223837 data_time: 0.025450 memory: 7326 loss_kpt: 0.000620 acc_pose: 0.824858 loss: 0.000620 2022/10/20 12:57:27 - mmengine - INFO - Epoch(train) [73][400/586] lr: 5.000000e-04 eta: 4:47:13 time: 0.222640 data_time: 0.025828 memory: 7326 loss_kpt: 0.000639 acc_pose: 0.833211 loss: 0.000639 2022/10/20 12:57:39 - mmengine - INFO - Epoch(train) [73][450/586] lr: 5.000000e-04 eta: 4:47:04 time: 0.228748 data_time: 0.024559 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.819022 loss: 0.000642 2022/10/20 12:57:50 - mmengine - INFO - Epoch(train) [73][500/586] lr: 5.000000e-04 eta: 4:46:55 time: 0.236198 data_time: 0.026826 memory: 7326 loss_kpt: 0.000645 acc_pose: 0.861656 loss: 0.000645 2022/10/20 12:58:02 - mmengine - INFO - Epoch(train) [73][550/586] lr: 5.000000e-04 eta: 4:46:45 time: 0.222872 data_time: 0.024130 memory: 7326 loss_kpt: 0.000647 acc_pose: 0.806459 loss: 0.000647 2022/10/20 12:58:10 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:58:21 - mmengine - INFO - Epoch(train) [74][50/586] lr: 5.000000e-04 eta: 4:46:14 time: 0.234329 data_time: 0.035926 memory: 7326 loss_kpt: 0.000632 acc_pose: 0.879053 loss: 0.000632 2022/10/20 12:58:33 - mmengine - INFO - Epoch(train) [74][100/586] lr: 5.000000e-04 eta: 4:46:05 time: 0.228183 data_time: 0.023716 memory: 7326 loss_kpt: 0.000620 acc_pose: 0.832878 loss: 0.000620 2022/10/20 12:58:44 - mmengine - INFO - Epoch(train) [74][150/586] lr: 5.000000e-04 eta: 4:45:56 time: 0.231579 data_time: 0.023255 memory: 7326 loss_kpt: 0.000620 acc_pose: 0.792016 loss: 0.000620 2022/10/20 12:58:56 - mmengine - INFO - Epoch(train) [74][200/586] lr: 5.000000e-04 eta: 4:45:46 time: 0.225734 data_time: 0.024098 memory: 7326 loss_kpt: 0.000626 acc_pose: 0.880191 loss: 0.000626 2022/10/20 12:59:01 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 12:59:07 - mmengine - INFO - Epoch(train) [74][250/586] lr: 5.000000e-04 eta: 4:45:37 time: 0.231388 data_time: 0.025033 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.858379 loss: 0.000636 2022/10/20 12:59:19 - mmengine - INFO - Epoch(train) [74][300/586] lr: 5.000000e-04 eta: 4:45:28 time: 0.233713 data_time: 0.023345 memory: 7326 loss_kpt: 0.000626 acc_pose: 0.833999 loss: 0.000626 2022/10/20 12:59:30 - mmengine - INFO - Epoch(train) [74][350/586] lr: 5.000000e-04 eta: 4:45:18 time: 0.223063 data_time: 0.025538 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.834458 loss: 0.000636 2022/10/20 12:59:41 - mmengine - INFO - Epoch(train) [74][400/586] lr: 5.000000e-04 eta: 4:45:09 time: 0.227327 data_time: 0.023261 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.788716 loss: 0.000636 2022/10/20 12:59:53 - mmengine - INFO - Epoch(train) [74][450/586] lr: 5.000000e-04 eta: 4:44:59 time: 0.228066 data_time: 0.024667 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.848062 loss: 0.000641 2022/10/20 13:00:04 - mmengine - INFO - Epoch(train) [74][500/586] lr: 5.000000e-04 eta: 4:44:50 time: 0.227255 data_time: 0.026389 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.775676 loss: 0.000636 2022/10/20 13:00:16 - mmengine - INFO - Epoch(train) [74][550/586] lr: 5.000000e-04 eta: 4:44:40 time: 0.227818 data_time: 0.024613 memory: 7326 loss_kpt: 0.000613 acc_pose: 0.813598 loss: 0.000613 2022/10/20 13:00:24 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:00:36 - mmengine - INFO - Epoch(train) [75][50/586] lr: 5.000000e-04 eta: 4:44:10 time: 0.240913 data_time: 0.039669 memory: 7326 loss_kpt: 0.000621 acc_pose: 0.863176 loss: 0.000621 2022/10/20 13:00:47 - mmengine - INFO - Epoch(train) [75][100/586] lr: 5.000000e-04 eta: 4:44:00 time: 0.224935 data_time: 0.025695 memory: 7326 loss_kpt: 0.000626 acc_pose: 0.849359 loss: 0.000626 2022/10/20 13:00:58 - mmengine - INFO - Epoch(train) [75][150/586] lr: 5.000000e-04 eta: 4:43:50 time: 0.221509 data_time: 0.023280 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.796295 loss: 0.000641 2022/10/20 13:01:10 - mmengine - INFO - Epoch(train) [75][200/586] lr: 5.000000e-04 eta: 4:43:41 time: 0.232774 data_time: 0.027727 memory: 7326 loss_kpt: 0.000624 acc_pose: 0.823045 loss: 0.000624 2022/10/20 13:01:21 - mmengine - INFO - Epoch(train) [75][250/586] lr: 5.000000e-04 eta: 4:43:32 time: 0.225143 data_time: 0.025439 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.848836 loss: 0.000642 2022/10/20 13:01:32 - mmengine - INFO - Epoch(train) [75][300/586] lr: 5.000000e-04 eta: 4:43:22 time: 0.227054 data_time: 0.022787 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.876309 loss: 0.000601 2022/10/20 13:01:44 - mmengine - INFO - Epoch(train) [75][350/586] lr: 5.000000e-04 eta: 4:43:13 time: 0.227729 data_time: 0.025540 memory: 7326 loss_kpt: 0.000630 acc_pose: 0.856044 loss: 0.000630 2022/10/20 13:01:55 - mmengine - INFO - Epoch(train) [75][400/586] lr: 5.000000e-04 eta: 4:43:04 time: 0.231616 data_time: 0.022915 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.793835 loss: 0.000636 2022/10/20 13:02:07 - mmengine - INFO - Epoch(train) [75][450/586] lr: 5.000000e-04 eta: 4:42:54 time: 0.229060 data_time: 0.030243 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.822377 loss: 0.000625 2022/10/20 13:02:18 - mmengine - INFO - Epoch(train) [75][500/586] lr: 5.000000e-04 eta: 4:42:45 time: 0.230108 data_time: 0.023148 memory: 7326 loss_kpt: 0.000624 acc_pose: 0.799030 loss: 0.000624 2022/10/20 13:02:30 - mmengine - INFO - Epoch(train) [75][550/586] lr: 5.000000e-04 eta: 4:42:36 time: 0.230215 data_time: 0.026769 memory: 7326 loss_kpt: 0.000627 acc_pose: 0.881561 loss: 0.000627 2022/10/20 13:02:38 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:02:50 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:02:50 - mmengine - INFO - Epoch(train) [76][50/586] lr: 5.000000e-04 eta: 4:42:06 time: 0.246245 data_time: 0.033828 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.832334 loss: 0.000642 2022/10/20 13:03:01 - mmengine - INFO - Epoch(train) [76][100/586] lr: 5.000000e-04 eta: 4:41:56 time: 0.222805 data_time: 0.028493 memory: 7326 loss_kpt: 0.000611 acc_pose: 0.875769 loss: 0.000611 2022/10/20 13:03:12 - mmengine - INFO - Epoch(train) [76][150/586] lr: 5.000000e-04 eta: 4:41:47 time: 0.227974 data_time: 0.022308 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.888452 loss: 0.000619 2022/10/20 13:03:24 - mmengine - INFO - Epoch(train) [76][200/586] lr: 5.000000e-04 eta: 4:41:38 time: 0.232842 data_time: 0.024835 memory: 7326 loss_kpt: 0.000635 acc_pose: 0.844400 loss: 0.000635 2022/10/20 13:03:35 - mmengine - INFO - Epoch(train) [76][250/586] lr: 5.000000e-04 eta: 4:41:28 time: 0.218045 data_time: 0.024499 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.873142 loss: 0.000622 2022/10/20 13:03:46 - mmengine - INFO - Epoch(train) [76][300/586] lr: 5.000000e-04 eta: 4:41:18 time: 0.226448 data_time: 0.026219 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.888190 loss: 0.000641 2022/10/20 13:03:58 - mmengine - INFO - Epoch(train) [76][350/586] lr: 5.000000e-04 eta: 4:41:08 time: 0.225486 data_time: 0.025197 memory: 7326 loss_kpt: 0.000638 acc_pose: 0.885542 loss: 0.000638 2022/10/20 13:04:09 - mmengine - INFO - Epoch(train) [76][400/586] lr: 5.000000e-04 eta: 4:40:59 time: 0.228928 data_time: 0.023140 memory: 7326 loss_kpt: 0.000627 acc_pose: 0.798966 loss: 0.000627 2022/10/20 13:04:20 - mmengine - INFO - Epoch(train) [76][450/586] lr: 5.000000e-04 eta: 4:40:49 time: 0.228518 data_time: 0.025956 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.849354 loss: 0.000636 2022/10/20 13:04:32 - mmengine - INFO - Epoch(train) [76][500/586] lr: 5.000000e-04 eta: 4:40:40 time: 0.225573 data_time: 0.024928 memory: 7326 loss_kpt: 0.000630 acc_pose: 0.802755 loss: 0.000630 2022/10/20 13:04:43 - mmengine - INFO - Epoch(train) [76][550/586] lr: 5.000000e-04 eta: 4:40:30 time: 0.221707 data_time: 0.026211 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.854061 loss: 0.000641 2022/10/20 13:04:51 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:05:03 - mmengine - INFO - Epoch(train) [77][50/586] lr: 5.000000e-04 eta: 4:40:00 time: 0.238918 data_time: 0.029887 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.868083 loss: 0.000622 2022/10/20 13:05:14 - mmengine - INFO - Epoch(train) [77][100/586] lr: 5.000000e-04 eta: 4:39:50 time: 0.230028 data_time: 0.029370 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.820344 loss: 0.000593 2022/10/20 13:05:26 - mmengine - INFO - Epoch(train) [77][150/586] lr: 5.000000e-04 eta: 4:39:41 time: 0.224698 data_time: 0.024310 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.824763 loss: 0.000625 2022/10/20 13:05:37 - mmengine - INFO - Epoch(train) [77][200/586] lr: 5.000000e-04 eta: 4:39:31 time: 0.225400 data_time: 0.026898 memory: 7326 loss_kpt: 0.000624 acc_pose: 0.875138 loss: 0.000624 2022/10/20 13:05:48 - mmengine - INFO - Epoch(train) [77][250/586] lr: 5.000000e-04 eta: 4:39:22 time: 0.229105 data_time: 0.024484 memory: 7326 loss_kpt: 0.000620 acc_pose: 0.884409 loss: 0.000620 2022/10/20 13:06:00 - mmengine - INFO - Epoch(train) [77][300/586] lr: 5.000000e-04 eta: 4:39:12 time: 0.228538 data_time: 0.025121 memory: 7326 loss_kpt: 0.000640 acc_pose: 0.798127 loss: 0.000640 2022/10/20 13:06:11 - mmengine - INFO - Epoch(train) [77][350/586] lr: 5.000000e-04 eta: 4:39:02 time: 0.226446 data_time: 0.026593 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.829779 loss: 0.000622 2022/10/20 13:06:23 - mmengine - INFO - Epoch(train) [77][400/586] lr: 5.000000e-04 eta: 4:38:53 time: 0.231846 data_time: 0.025322 memory: 7326 loss_kpt: 0.000628 acc_pose: 0.934223 loss: 0.000628 2022/10/20 13:06:34 - mmengine - INFO - Epoch(train) [77][450/586] lr: 5.000000e-04 eta: 4:38:44 time: 0.225549 data_time: 0.030953 memory: 7326 loss_kpt: 0.000606 acc_pose: 0.780520 loss: 0.000606 2022/10/20 13:06:37 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:06:46 - mmengine - INFO - Epoch(train) [77][500/586] lr: 5.000000e-04 eta: 4:38:35 time: 0.236026 data_time: 0.028128 memory: 7326 loss_kpt: 0.000623 acc_pose: 0.860670 loss: 0.000623 2022/10/20 13:06:57 - mmengine - INFO - Epoch(train) [77][550/586] lr: 5.000000e-04 eta: 4:38:25 time: 0.222872 data_time: 0.024566 memory: 7326 loss_kpt: 0.000607 acc_pose: 0.814769 loss: 0.000607 2022/10/20 13:07:05 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:07:17 - mmengine - INFO - Epoch(train) [78][50/586] lr: 5.000000e-04 eta: 4:37:55 time: 0.238163 data_time: 0.038536 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.826495 loss: 0.000642 2022/10/20 13:07:28 - mmengine - INFO - Epoch(train) [78][100/586] lr: 5.000000e-04 eta: 4:37:45 time: 0.224020 data_time: 0.025269 memory: 7326 loss_kpt: 0.000646 acc_pose: 0.857756 loss: 0.000646 2022/10/20 13:07:40 - mmengine - INFO - Epoch(train) [78][150/586] lr: 5.000000e-04 eta: 4:37:36 time: 0.230653 data_time: 0.024426 memory: 7326 loss_kpt: 0.000628 acc_pose: 0.834265 loss: 0.000628 2022/10/20 13:07:51 - mmengine - INFO - Epoch(train) [78][200/586] lr: 5.000000e-04 eta: 4:37:27 time: 0.229894 data_time: 0.023599 memory: 7326 loss_kpt: 0.000637 acc_pose: 0.793153 loss: 0.000637 2022/10/20 13:08:03 - mmengine - INFO - Epoch(train) [78][250/586] lr: 5.000000e-04 eta: 4:37:18 time: 0.234530 data_time: 0.027048 memory: 7326 loss_kpt: 0.000634 acc_pose: 0.834802 loss: 0.000634 2022/10/20 13:08:14 - mmengine - INFO - Epoch(train) [78][300/586] lr: 5.000000e-04 eta: 4:37:08 time: 0.225576 data_time: 0.028669 memory: 7326 loss_kpt: 0.000629 acc_pose: 0.859946 loss: 0.000629 2022/10/20 13:08:26 - mmengine - INFO - Epoch(train) [78][350/586] lr: 5.000000e-04 eta: 4:36:58 time: 0.228587 data_time: 0.028274 memory: 7326 loss_kpt: 0.000634 acc_pose: 0.817648 loss: 0.000634 2022/10/20 13:08:38 - mmengine - INFO - Epoch(train) [78][400/586] lr: 5.000000e-04 eta: 4:36:50 time: 0.238717 data_time: 0.024723 memory: 7326 loss_kpt: 0.000648 acc_pose: 0.729178 loss: 0.000648 2022/10/20 13:08:49 - mmengine - INFO - Epoch(train) [78][450/586] lr: 5.000000e-04 eta: 4:36:40 time: 0.226768 data_time: 0.027073 memory: 7326 loss_kpt: 0.000637 acc_pose: 0.803981 loss: 0.000637 2022/10/20 13:09:01 - mmengine - INFO - Epoch(train) [78][500/586] lr: 5.000000e-04 eta: 4:36:31 time: 0.228984 data_time: 0.025384 memory: 7326 loss_kpt: 0.000642 acc_pose: 0.896164 loss: 0.000642 2022/10/20 13:09:12 - mmengine - INFO - Epoch(train) [78][550/586] lr: 5.000000e-04 eta: 4:36:21 time: 0.223817 data_time: 0.025744 memory: 7326 loss_kpt: 0.000616 acc_pose: 0.740494 loss: 0.000616 2022/10/20 13:09:20 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:09:32 - mmengine - INFO - Epoch(train) [79][50/586] lr: 5.000000e-04 eta: 4:35:52 time: 0.242499 data_time: 0.033780 memory: 7326 loss_kpt: 0.000639 acc_pose: 0.860987 loss: 0.000639 2022/10/20 13:09:43 - mmengine - INFO - Epoch(train) [79][100/586] lr: 5.000000e-04 eta: 4:35:42 time: 0.227365 data_time: 0.024900 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.842727 loss: 0.000622 2022/10/20 13:09:55 - mmengine - INFO - Epoch(train) [79][150/586] lr: 5.000000e-04 eta: 4:35:33 time: 0.234878 data_time: 0.029618 memory: 7326 loss_kpt: 0.000617 acc_pose: 0.828401 loss: 0.000617 2022/10/20 13:10:06 - mmengine - INFO - Epoch(train) [79][200/586] lr: 5.000000e-04 eta: 4:35:24 time: 0.229780 data_time: 0.029094 memory: 7326 loss_kpt: 0.000643 acc_pose: 0.849079 loss: 0.000643 2022/10/20 13:10:18 - mmengine - INFO - Epoch(train) [79][250/586] lr: 5.000000e-04 eta: 4:35:15 time: 0.239359 data_time: 0.025878 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.830521 loss: 0.000625 2022/10/20 13:10:28 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:10:30 - mmengine - INFO - Epoch(train) [79][300/586] lr: 5.000000e-04 eta: 4:35:06 time: 0.231510 data_time: 0.025157 memory: 7326 loss_kpt: 0.000623 acc_pose: 0.862259 loss: 0.000623 2022/10/20 13:10:42 - mmengine - INFO - Epoch(train) [79][350/586] lr: 5.000000e-04 eta: 4:34:57 time: 0.231530 data_time: 0.030921 memory: 7326 loss_kpt: 0.000613 acc_pose: 0.886798 loss: 0.000613 2022/10/20 13:10:53 - mmengine - INFO - Epoch(train) [79][400/586] lr: 5.000000e-04 eta: 4:34:47 time: 0.231283 data_time: 0.022896 memory: 7326 loss_kpt: 0.000638 acc_pose: 0.795754 loss: 0.000638 2022/10/20 13:11:05 - mmengine - INFO - Epoch(train) [79][450/586] lr: 5.000000e-04 eta: 4:34:38 time: 0.230012 data_time: 0.023619 memory: 7326 loss_kpt: 0.000618 acc_pose: 0.844636 loss: 0.000618 2022/10/20 13:11:16 - mmengine - INFO - Epoch(train) [79][500/586] lr: 5.000000e-04 eta: 4:34:28 time: 0.227613 data_time: 0.027781 memory: 7326 loss_kpt: 0.000621 acc_pose: 0.828546 loss: 0.000621 2022/10/20 13:11:28 - mmengine - INFO - Epoch(train) [79][550/586] lr: 5.000000e-04 eta: 4:34:19 time: 0.231925 data_time: 0.027240 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.875148 loss: 0.000636 2022/10/20 13:11:36 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:11:48 - mmengine - INFO - Epoch(train) [80][50/586] lr: 5.000000e-04 eta: 4:33:50 time: 0.233172 data_time: 0.034144 memory: 7326 loss_kpt: 0.000648 acc_pose: 0.861250 loss: 0.000648 2022/10/20 13:11:59 - mmengine - INFO - Epoch(train) [80][100/586] lr: 5.000000e-04 eta: 4:33:40 time: 0.231414 data_time: 0.024301 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.819553 loss: 0.000619 2022/10/20 13:12:11 - mmengine - INFO - Epoch(train) [80][150/586] lr: 5.000000e-04 eta: 4:33:31 time: 0.235021 data_time: 0.026200 memory: 7326 loss_kpt: 0.000634 acc_pose: 0.836319 loss: 0.000634 2022/10/20 13:12:23 - mmengine - INFO - Epoch(train) [80][200/586] lr: 5.000000e-04 eta: 4:33:23 time: 0.248605 data_time: 0.025270 memory: 7326 loss_kpt: 0.000623 acc_pose: 0.837155 loss: 0.000623 2022/10/20 13:12:35 - mmengine - INFO - Epoch(train) [80][250/586] lr: 5.000000e-04 eta: 4:33:14 time: 0.228324 data_time: 0.028955 memory: 7326 loss_kpt: 0.000626 acc_pose: 0.882187 loss: 0.000626 2022/10/20 13:12:46 - mmengine - INFO - Epoch(train) [80][300/586] lr: 5.000000e-04 eta: 4:33:04 time: 0.228399 data_time: 0.024881 memory: 7326 loss_kpt: 0.000623 acc_pose: 0.863935 loss: 0.000623 2022/10/20 13:12:58 - mmengine - INFO - Epoch(train) [80][350/586] lr: 5.000000e-04 eta: 4:32:55 time: 0.230494 data_time: 0.025223 memory: 7326 loss_kpt: 0.000624 acc_pose: 0.865813 loss: 0.000624 2022/10/20 13:13:09 - mmengine - INFO - Epoch(train) [80][400/586] lr: 5.000000e-04 eta: 4:32:45 time: 0.230547 data_time: 0.024103 memory: 7326 loss_kpt: 0.000632 acc_pose: 0.861496 loss: 0.000632 2022/10/20 13:13:21 - mmengine - INFO - Epoch(train) [80][450/586] lr: 5.000000e-04 eta: 4:32:36 time: 0.227598 data_time: 0.022998 memory: 7326 loss_kpt: 0.000604 acc_pose: 0.850632 loss: 0.000604 2022/10/20 13:13:32 - mmengine - INFO - Epoch(train) [80][500/586] lr: 5.000000e-04 eta: 4:32:26 time: 0.230406 data_time: 0.029304 memory: 7326 loss_kpt: 0.000629 acc_pose: 0.873461 loss: 0.000629 2022/10/20 13:13:43 - mmengine - INFO - Epoch(train) [80][550/586] lr: 5.000000e-04 eta: 4:32:16 time: 0.222135 data_time: 0.025285 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.802747 loss: 0.000625 2022/10/20 13:13:52 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:13:52 - mmengine - INFO - Saving checkpoint at 80 epochs 2022/10/20 13:14:03 - mmengine - INFO - Epoch(val) [80][50/407] eta: 0:00:47 time: 0.132906 data_time: 0.050528 memory: 7326 2022/10/20 13:14:10 - mmengine - INFO - Epoch(val) [80][100/407] eta: 0:00:46 time: 0.150306 data_time: 0.070928 memory: 1680 2022/10/20 13:14:16 - mmengine - INFO - Epoch(val) [80][150/407] eta: 0:00:32 time: 0.126342 data_time: 0.046261 memory: 1680 2022/10/20 13:14:24 - mmengine - INFO - Epoch(val) [80][200/407] eta: 0:00:31 time: 0.152627 data_time: 0.069659 memory: 1680 2022/10/20 13:14:31 - mmengine - INFO - Epoch(val) [80][250/407] eta: 0:00:22 time: 0.141537 data_time: 0.062394 memory: 1680 2022/10/20 13:14:42 - mmengine - INFO - Epoch(val) [80][300/407] eta: 0:00:22 time: 0.205913 data_time: 0.127680 memory: 1680 2022/10/20 13:14:53 - mmengine - INFO - Epoch(val) [80][350/407] eta: 0:00:13 time: 0.238659 data_time: 0.160487 memory: 1680 2022/10/20 13:15:00 - mmengine - INFO - Epoch(val) [80][400/407] eta: 0:00:00 time: 0.121826 data_time: 0.038856 memory: 1680 2022/10/20 13:15:41 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 13:15:53 - mmengine - INFO - Epoch(val) [80][407/407] coco/AP: 0.716942 coco/AP .5: 0.898234 coco/AP .75: 0.798109 coco/AP (M): 0.677971 coco/AP (L): 0.785159 coco/AR: 0.771914 coco/AR .5: 0.935453 coco/AR .75: 0.843356 coco/AR (M): 0.726414 coco/AR (L): 0.837198 2022/10/20 13:16:06 - mmengine - INFO - Epoch(train) [81][50/586] lr: 5.000000e-04 eta: 4:31:49 time: 0.252695 data_time: 0.034038 memory: 7326 loss_kpt: 0.000643 acc_pose: 0.819349 loss: 0.000643 2022/10/20 13:16:18 - mmengine - INFO - Epoch(train) [81][100/586] lr: 5.000000e-04 eta: 4:31:39 time: 0.234844 data_time: 0.024131 memory: 7326 loss_kpt: 0.000616 acc_pose: 0.894787 loss: 0.000616 2022/10/20 13:16:22 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:16:30 - mmengine - INFO - Epoch(train) [81][150/586] lr: 5.000000e-04 eta: 4:31:31 time: 0.240267 data_time: 0.028469 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.865495 loss: 0.000601 2022/10/20 13:16:41 - mmengine - INFO - Epoch(train) [81][200/586] lr: 5.000000e-04 eta: 4:31:21 time: 0.228217 data_time: 0.024346 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.769697 loss: 0.000622 2022/10/20 13:16:53 - mmengine - INFO - Epoch(train) [81][250/586] lr: 5.000000e-04 eta: 4:31:12 time: 0.236980 data_time: 0.025590 memory: 7326 loss_kpt: 0.000621 acc_pose: 0.843579 loss: 0.000621 2022/10/20 13:17:05 - mmengine - INFO - Epoch(train) [81][300/586] lr: 5.000000e-04 eta: 4:31:03 time: 0.229247 data_time: 0.025205 memory: 7326 loss_kpt: 0.000631 acc_pose: 0.877033 loss: 0.000631 2022/10/20 13:17:16 - mmengine - INFO - Epoch(train) [81][350/586] lr: 5.000000e-04 eta: 4:30:54 time: 0.231952 data_time: 0.026397 memory: 7326 loss_kpt: 0.000623 acc_pose: 0.741279 loss: 0.000623 2022/10/20 13:17:28 - mmengine - INFO - Epoch(train) [81][400/586] lr: 5.000000e-04 eta: 4:30:44 time: 0.228698 data_time: 0.028747 memory: 7326 loss_kpt: 0.000611 acc_pose: 0.852625 loss: 0.000611 2022/10/20 13:17:39 - mmengine - INFO - Epoch(train) [81][450/586] lr: 5.000000e-04 eta: 4:30:34 time: 0.229094 data_time: 0.025747 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.834120 loss: 0.000614 2022/10/20 13:17:50 - mmengine - INFO - Epoch(train) [81][500/586] lr: 5.000000e-04 eta: 4:30:24 time: 0.223343 data_time: 0.024568 memory: 7326 loss_kpt: 0.000630 acc_pose: 0.825027 loss: 0.000630 2022/10/20 13:18:02 - mmengine - INFO - Epoch(train) [81][550/586] lr: 5.000000e-04 eta: 4:30:16 time: 0.236849 data_time: 0.032018 memory: 7326 loss_kpt: 0.000621 acc_pose: 0.789434 loss: 0.000621 2022/10/20 13:18:11 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:18:23 - mmengine - INFO - Epoch(train) [82][50/586] lr: 5.000000e-04 eta: 4:29:47 time: 0.240673 data_time: 0.037218 memory: 7326 loss_kpt: 0.000624 acc_pose: 0.764358 loss: 0.000624 2022/10/20 13:18:34 - mmengine - INFO - Epoch(train) [82][100/586] lr: 5.000000e-04 eta: 4:29:37 time: 0.225565 data_time: 0.026580 memory: 7326 loss_kpt: 0.000637 acc_pose: 0.872842 loss: 0.000637 2022/10/20 13:18:46 - mmengine - INFO - Epoch(train) [82][150/586] lr: 5.000000e-04 eta: 4:29:28 time: 0.240091 data_time: 0.026237 memory: 7326 loss_kpt: 0.000626 acc_pose: 0.855021 loss: 0.000626 2022/10/20 13:18:58 - mmengine - INFO - Epoch(train) [82][200/586] lr: 5.000000e-04 eta: 4:29:19 time: 0.236717 data_time: 0.027543 memory: 7326 loss_kpt: 0.000624 acc_pose: 0.844602 loss: 0.000624 2022/10/20 13:19:10 - mmengine - INFO - Epoch(train) [82][250/586] lr: 5.000000e-04 eta: 4:29:11 time: 0.244628 data_time: 0.027044 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.839120 loss: 0.000625 2022/10/20 13:19:22 - mmengine - INFO - Epoch(train) [82][300/586] lr: 5.000000e-04 eta: 4:29:02 time: 0.238502 data_time: 0.028725 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.855755 loss: 0.000636 2022/10/20 13:19:34 - mmengine - INFO - Epoch(train) [82][350/586] lr: 5.000000e-04 eta: 4:28:54 time: 0.247484 data_time: 0.023886 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.831310 loss: 0.000619 2022/10/20 13:19:47 - mmengine - INFO - Epoch(train) [82][400/586] lr: 5.000000e-04 eta: 4:28:47 time: 0.257207 data_time: 0.025986 memory: 7326 loss_kpt: 0.000631 acc_pose: 0.869101 loss: 0.000631 2022/10/20 13:19:59 - mmengine - INFO - Epoch(train) [82][450/586] lr: 5.000000e-04 eta: 4:28:38 time: 0.240071 data_time: 0.030233 memory: 7326 loss_kpt: 0.000627 acc_pose: 0.803731 loss: 0.000627 2022/10/20 13:20:12 - mmengine - INFO - Epoch(train) [82][500/586] lr: 5.000000e-04 eta: 4:28:30 time: 0.248831 data_time: 0.025094 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.884395 loss: 0.000619 2022/10/20 13:20:20 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:20:24 - mmengine - INFO - Epoch(train) [82][550/586] lr: 5.000000e-04 eta: 4:28:22 time: 0.246731 data_time: 0.029552 memory: 7326 loss_kpt: 0.000623 acc_pose: 0.889938 loss: 0.000623 2022/10/20 13:20:32 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:20:45 - mmengine - INFO - Epoch(train) [83][50/586] lr: 5.000000e-04 eta: 4:27:54 time: 0.246164 data_time: 0.031807 memory: 7326 loss_kpt: 0.000616 acc_pose: 0.885158 loss: 0.000616 2022/10/20 13:20:56 - mmengine - INFO - Epoch(train) [83][100/586] lr: 5.000000e-04 eta: 4:27:44 time: 0.226097 data_time: 0.028190 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.820853 loss: 0.000605 2022/10/20 13:21:08 - mmengine - INFO - Epoch(train) [83][150/586] lr: 5.000000e-04 eta: 4:27:36 time: 0.248140 data_time: 0.029300 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.869141 loss: 0.000595 2022/10/20 13:21:20 - mmengine - INFO - Epoch(train) [83][200/586] lr: 5.000000e-04 eta: 4:27:27 time: 0.239122 data_time: 0.025460 memory: 7326 loss_kpt: 0.000645 acc_pose: 0.794935 loss: 0.000645 2022/10/20 13:21:32 - mmengine - INFO - Epoch(train) [83][250/586] lr: 5.000000e-04 eta: 4:27:18 time: 0.233314 data_time: 0.024442 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.836223 loss: 0.000622 2022/10/20 13:21:44 - mmengine - INFO - Epoch(train) [83][300/586] lr: 5.000000e-04 eta: 4:27:09 time: 0.242027 data_time: 0.023407 memory: 7326 loss_kpt: 0.000621 acc_pose: 0.875438 loss: 0.000621 2022/10/20 13:21:57 - mmengine - INFO - Epoch(train) [83][350/586] lr: 5.000000e-04 eta: 4:27:01 time: 0.250466 data_time: 0.027151 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.827083 loss: 0.000625 2022/10/20 13:22:09 - mmengine - INFO - Epoch(train) [83][400/586] lr: 5.000000e-04 eta: 4:26:52 time: 0.235098 data_time: 0.027508 memory: 7326 loss_kpt: 0.000627 acc_pose: 0.832988 loss: 0.000627 2022/10/20 13:22:20 - mmengine - INFO - Epoch(train) [83][450/586] lr: 5.000000e-04 eta: 4:26:43 time: 0.230050 data_time: 0.026826 memory: 7326 loss_kpt: 0.000626 acc_pose: 0.846807 loss: 0.000626 2022/10/20 13:22:32 - mmengine - INFO - Epoch(train) [83][500/586] lr: 5.000000e-04 eta: 4:26:34 time: 0.240654 data_time: 0.028962 memory: 7326 loss_kpt: 0.000604 acc_pose: 0.883597 loss: 0.000604 2022/10/20 13:22:44 - mmengine - INFO - Epoch(train) [83][550/586] lr: 5.000000e-04 eta: 4:26:25 time: 0.238592 data_time: 0.025009 memory: 7326 loss_kpt: 0.000627 acc_pose: 0.892225 loss: 0.000627 2022/10/20 13:22:54 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:23:07 - mmengine - INFO - Epoch(train) [84][50/586] lr: 5.000000e-04 eta: 4:25:58 time: 0.263104 data_time: 0.033056 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.826710 loss: 0.000612 2022/10/20 13:23:19 - mmengine - INFO - Epoch(train) [84][100/586] lr: 5.000000e-04 eta: 4:25:50 time: 0.247130 data_time: 0.026665 memory: 7326 loss_kpt: 0.000600 acc_pose: 0.848339 loss: 0.000600 2022/10/20 13:23:31 - mmengine - INFO - Epoch(train) [84][150/586] lr: 5.000000e-04 eta: 4:25:41 time: 0.233902 data_time: 0.027107 memory: 7326 loss_kpt: 0.000633 acc_pose: 0.831781 loss: 0.000633 2022/10/20 13:23:43 - mmengine - INFO - Epoch(train) [84][200/586] lr: 5.000000e-04 eta: 4:25:33 time: 0.250737 data_time: 0.029390 memory: 7326 loss_kpt: 0.000629 acc_pose: 0.812971 loss: 0.000629 2022/10/20 13:23:56 - mmengine - INFO - Epoch(train) [84][250/586] lr: 5.000000e-04 eta: 4:25:25 time: 0.257339 data_time: 0.024211 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.855888 loss: 0.000605 2022/10/20 13:24:09 - mmengine - INFO - Epoch(train) [84][300/586] lr: 5.000000e-04 eta: 4:25:17 time: 0.249290 data_time: 0.024668 memory: 7326 loss_kpt: 0.000616 acc_pose: 0.883061 loss: 0.000616 2022/10/20 13:24:20 - mmengine - INFO - Epoch(train) [84][350/586] lr: 5.000000e-04 eta: 4:25:08 time: 0.235200 data_time: 0.027166 memory: 7326 loss_kpt: 0.000636 acc_pose: 0.895236 loss: 0.000636 2022/10/20 13:24:23 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:24:32 - mmengine - INFO - Epoch(train) [84][400/586] lr: 5.000000e-04 eta: 4:24:59 time: 0.236617 data_time: 0.024102 memory: 7326 loss_kpt: 0.000634 acc_pose: 0.872129 loss: 0.000634 2022/10/20 13:24:45 - mmengine - INFO - Epoch(train) [84][450/586] lr: 5.000000e-04 eta: 4:24:51 time: 0.245763 data_time: 0.025749 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.872356 loss: 0.000610 2022/10/20 13:24:56 - mmengine - INFO - Epoch(train) [84][500/586] lr: 5.000000e-04 eta: 4:24:41 time: 0.236255 data_time: 0.029201 memory: 7326 loss_kpt: 0.000608 acc_pose: 0.870679 loss: 0.000608 2022/10/20 13:25:09 - mmengine - INFO - Epoch(train) [84][550/586] lr: 5.000000e-04 eta: 4:24:34 time: 0.258612 data_time: 0.023440 memory: 7326 loss_kpt: 0.000624 acc_pose: 0.857680 loss: 0.000624 2022/10/20 13:25:18 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:25:32 - mmengine - INFO - Epoch(train) [85][50/586] lr: 5.000000e-04 eta: 4:24:08 time: 0.269810 data_time: 0.031259 memory: 7326 loss_kpt: 0.000609 acc_pose: 0.803745 loss: 0.000609 2022/10/20 13:25:43 - mmengine - INFO - Epoch(train) [85][100/586] lr: 5.000000e-04 eta: 4:23:59 time: 0.235459 data_time: 0.025850 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.866196 loss: 0.000610 2022/10/20 13:25:56 - mmengine - INFO - Epoch(train) [85][150/586] lr: 5.000000e-04 eta: 4:23:50 time: 0.242655 data_time: 0.025110 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.876457 loss: 0.000625 2022/10/20 13:26:07 - mmengine - INFO - Epoch(train) [85][200/586] lr: 5.000000e-04 eta: 4:23:41 time: 0.234208 data_time: 0.023894 memory: 7326 loss_kpt: 0.000632 acc_pose: 0.809679 loss: 0.000632 2022/10/20 13:26:21 - mmengine - INFO - Epoch(train) [85][250/586] lr: 5.000000e-04 eta: 4:23:35 time: 0.274046 data_time: 0.025925 memory: 7326 loss_kpt: 0.000618 acc_pose: 0.849172 loss: 0.000618 2022/10/20 13:26:34 - mmengine - INFO - Epoch(train) [85][300/586] lr: 5.000000e-04 eta: 4:23:27 time: 0.252018 data_time: 0.025031 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.838886 loss: 0.000610 2022/10/20 13:26:46 - mmengine - INFO - Epoch(train) [85][350/586] lr: 5.000000e-04 eta: 4:23:18 time: 0.246407 data_time: 0.025133 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.836347 loss: 0.000625 2022/10/20 13:26:58 - mmengine - INFO - Epoch(train) [85][400/586] lr: 5.000000e-04 eta: 4:23:10 time: 0.244927 data_time: 0.026371 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.899965 loss: 0.000605 2022/10/20 13:27:10 - mmengine - INFO - Epoch(train) [85][450/586] lr: 5.000000e-04 eta: 4:23:00 time: 0.233056 data_time: 0.026065 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.778457 loss: 0.000625 2022/10/20 13:27:23 - mmengine - INFO - Epoch(train) [85][500/586] lr: 5.000000e-04 eta: 4:22:53 time: 0.261403 data_time: 0.026800 memory: 7326 loss_kpt: 0.000629 acc_pose: 0.857102 loss: 0.000629 2022/10/20 13:27:35 - mmengine - INFO - Epoch(train) [85][550/586] lr: 5.000000e-04 eta: 4:22:44 time: 0.246405 data_time: 0.036666 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.846012 loss: 0.000614 2022/10/20 13:27:44 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:27:56 - mmengine - INFO - Epoch(train) [86][50/586] lr: 5.000000e-04 eta: 4:22:17 time: 0.248537 data_time: 0.031327 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.832736 loss: 0.000625 2022/10/20 13:28:08 - mmengine - INFO - Epoch(train) [86][100/586] lr: 5.000000e-04 eta: 4:22:09 time: 0.246472 data_time: 0.027769 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.841822 loss: 0.000619 2022/10/20 13:28:21 - mmengine - INFO - Epoch(train) [86][150/586] lr: 5.000000e-04 eta: 4:22:00 time: 0.251497 data_time: 0.025980 memory: 7326 loss_kpt: 0.000639 acc_pose: 0.873577 loss: 0.000639 2022/10/20 13:28:30 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:28:32 - mmengine - INFO - Epoch(train) [86][200/586] lr: 5.000000e-04 eta: 4:21:50 time: 0.225503 data_time: 0.026912 memory: 7326 loss_kpt: 0.000603 acc_pose: 0.867672 loss: 0.000603 2022/10/20 13:28:45 - mmengine - INFO - Epoch(train) [86][250/586] lr: 5.000000e-04 eta: 4:21:43 time: 0.259627 data_time: 0.029125 memory: 7326 loss_kpt: 0.000631 acc_pose: 0.854403 loss: 0.000631 2022/10/20 13:28:58 - mmengine - INFO - Epoch(train) [86][300/586] lr: 5.000000e-04 eta: 4:21:35 time: 0.247804 data_time: 0.025909 memory: 7326 loss_kpt: 0.000634 acc_pose: 0.813008 loss: 0.000634 2022/10/20 13:29:09 - mmengine - INFO - Epoch(train) [86][350/586] lr: 5.000000e-04 eta: 4:21:26 time: 0.238198 data_time: 0.028438 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.770793 loss: 0.000592 2022/10/20 13:29:21 - mmengine - INFO - Epoch(train) [86][400/586] lr: 5.000000e-04 eta: 4:21:16 time: 0.232546 data_time: 0.026766 memory: 7326 loss_kpt: 0.000626 acc_pose: 0.862383 loss: 0.000626 2022/10/20 13:29:35 - mmengine - INFO - Epoch(train) [86][450/586] lr: 5.000000e-04 eta: 4:21:09 time: 0.267834 data_time: 0.026929 memory: 7326 loss_kpt: 0.000618 acc_pose: 0.853199 loss: 0.000618 2022/10/20 13:29:47 - mmengine - INFO - Epoch(train) [86][500/586] lr: 5.000000e-04 eta: 4:21:00 time: 0.240368 data_time: 0.025341 memory: 7326 loss_kpt: 0.000617 acc_pose: 0.836133 loss: 0.000617 2022/10/20 13:30:00 - mmengine - INFO - Epoch(train) [86][550/586] lr: 5.000000e-04 eta: 4:20:53 time: 0.265321 data_time: 0.025366 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.810973 loss: 0.000625 2022/10/20 13:30:09 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:30:21 - mmengine - INFO - Epoch(train) [87][50/586] lr: 5.000000e-04 eta: 4:20:26 time: 0.253070 data_time: 0.037492 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.800842 loss: 0.000619 2022/10/20 13:30:33 - mmengine - INFO - Epoch(train) [87][100/586] lr: 5.000000e-04 eta: 4:20:17 time: 0.235648 data_time: 0.025106 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.866414 loss: 0.000610 2022/10/20 13:30:45 - mmengine - INFO - Epoch(train) [87][150/586] lr: 5.000000e-04 eta: 4:20:07 time: 0.233473 data_time: 0.023545 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.853228 loss: 0.000612 2022/10/20 13:30:57 - mmengine - INFO - Epoch(train) [87][200/586] lr: 5.000000e-04 eta: 4:19:59 time: 0.245658 data_time: 0.024740 memory: 7326 loss_kpt: 0.000618 acc_pose: 0.860669 loss: 0.000618 2022/10/20 13:31:09 - mmengine - INFO - Epoch(train) [87][250/586] lr: 5.000000e-04 eta: 4:19:49 time: 0.233633 data_time: 0.028676 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.867628 loss: 0.000619 2022/10/20 13:31:22 - mmengine - INFO - Epoch(train) [87][300/586] lr: 5.000000e-04 eta: 4:19:42 time: 0.263217 data_time: 0.024092 memory: 7326 loss_kpt: 0.000608 acc_pose: 0.862222 loss: 0.000608 2022/10/20 13:31:35 - mmengine - INFO - Epoch(train) [87][350/586] lr: 5.000000e-04 eta: 4:19:34 time: 0.262038 data_time: 0.028734 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.856113 loss: 0.000605 2022/10/20 13:31:47 - mmengine - INFO - Epoch(train) [87][400/586] lr: 5.000000e-04 eta: 4:19:25 time: 0.233598 data_time: 0.023898 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.801568 loss: 0.000601 2022/10/20 13:32:00 - mmengine - INFO - Epoch(train) [87][450/586] lr: 5.000000e-04 eta: 4:19:17 time: 0.257873 data_time: 0.024212 memory: 7326 loss_kpt: 0.000621 acc_pose: 0.863140 loss: 0.000621 2022/10/20 13:32:14 - mmengine - INFO - Epoch(train) [87][500/586] lr: 5.000000e-04 eta: 4:19:12 time: 0.290434 data_time: 0.024329 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.872245 loss: 0.000622 2022/10/20 13:32:30 - mmengine - INFO - Epoch(train) [87][550/586] lr: 5.000000e-04 eta: 4:19:08 time: 0.314092 data_time: 0.022987 memory: 7326 loss_kpt: 0.000627 acc_pose: 0.778538 loss: 0.000627 2022/10/20 13:32:39 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:32:46 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:32:56 - mmengine - INFO - Epoch(train) [88][50/586] lr: 5.000000e-04 eta: 4:18:48 time: 0.345636 data_time: 0.037565 memory: 7326 loss_kpt: 0.000604 acc_pose: 0.805264 loss: 0.000604 2022/10/20 13:33:09 - mmengine - INFO - Epoch(train) [88][100/586] lr: 5.000000e-04 eta: 4:18:40 time: 0.254789 data_time: 0.025647 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.834628 loss: 0.000610 2022/10/20 13:33:25 - mmengine - INFO - Epoch(train) [88][150/586] lr: 5.000000e-04 eta: 4:18:36 time: 0.322729 data_time: 0.022794 memory: 7326 loss_kpt: 0.000607 acc_pose: 0.884231 loss: 0.000607 2022/10/20 13:33:40 - mmengine - INFO - Epoch(train) [88][200/586] lr: 5.000000e-04 eta: 4:18:31 time: 0.286539 data_time: 0.023688 memory: 7326 loss_kpt: 0.000613 acc_pose: 0.783554 loss: 0.000613 2022/10/20 13:33:53 - mmengine - INFO - Epoch(train) [88][250/586] lr: 5.000000e-04 eta: 4:18:23 time: 0.264015 data_time: 0.025098 memory: 7326 loss_kpt: 0.000620 acc_pose: 0.854856 loss: 0.000620 2022/10/20 13:34:09 - mmengine - INFO - Epoch(train) [88][300/586] lr: 5.000000e-04 eta: 4:18:20 time: 0.317626 data_time: 0.024022 memory: 7326 loss_kpt: 0.000603 acc_pose: 0.834447 loss: 0.000603 2022/10/20 13:34:23 - mmengine - INFO - Epoch(train) [88][350/586] lr: 5.000000e-04 eta: 4:18:13 time: 0.274094 data_time: 0.025445 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.676508 loss: 0.000614 2022/10/20 13:34:37 - mmengine - INFO - Epoch(train) [88][400/586] lr: 5.000000e-04 eta: 4:18:07 time: 0.287713 data_time: 0.028727 memory: 7326 loss_kpt: 0.000620 acc_pose: 0.801448 loss: 0.000620 2022/10/20 13:34:52 - mmengine - INFO - Epoch(train) [88][450/586] lr: 5.000000e-04 eta: 4:18:02 time: 0.306342 data_time: 0.027875 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.880360 loss: 0.000614 2022/10/20 13:35:08 - mmengine - INFO - Epoch(train) [88][500/586] lr: 5.000000e-04 eta: 4:17:58 time: 0.304545 data_time: 0.027350 memory: 7326 loss_kpt: 0.000617 acc_pose: 0.786198 loss: 0.000617 2022/10/20 13:35:24 - mmengine - INFO - Epoch(train) [88][550/586] lr: 5.000000e-04 eta: 4:17:56 time: 0.339515 data_time: 0.026359 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.829707 loss: 0.000610 2022/10/20 13:35:36 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:35:53 - mmengine - INFO - Epoch(train) [89][50/586] lr: 5.000000e-04 eta: 4:17:34 time: 0.328724 data_time: 0.033211 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.830164 loss: 0.000593 2022/10/20 13:36:07 - mmengine - INFO - Epoch(train) [89][100/586] lr: 5.000000e-04 eta: 4:17:28 time: 0.290818 data_time: 0.025461 memory: 7326 loss_kpt: 0.000633 acc_pose: 0.820462 loss: 0.000633 2022/10/20 13:36:21 - mmengine - INFO - Epoch(train) [89][150/586] lr: 5.000000e-04 eta: 4:17:22 time: 0.275990 data_time: 0.028114 memory: 7326 loss_kpt: 0.000609 acc_pose: 0.863759 loss: 0.000609 2022/10/20 13:36:35 - mmengine - INFO - Epoch(train) [89][200/586] lr: 5.000000e-04 eta: 4:17:15 time: 0.278248 data_time: 0.031232 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.867261 loss: 0.000612 2022/10/20 13:36:50 - mmengine - INFO - Epoch(train) [89][250/586] lr: 5.000000e-04 eta: 4:17:09 time: 0.292700 data_time: 0.024206 memory: 7326 loss_kpt: 0.000606 acc_pose: 0.831845 loss: 0.000606 2022/10/20 13:37:04 - mmengine - INFO - Epoch(train) [89][300/586] lr: 5.000000e-04 eta: 4:17:03 time: 0.280758 data_time: 0.030287 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.838792 loss: 0.000619 2022/10/20 13:37:16 - mmengine - INFO - Epoch(train) [89][350/586] lr: 5.000000e-04 eta: 4:16:55 time: 0.252223 data_time: 0.027588 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.874383 loss: 0.000619 2022/10/20 13:37:29 - mmengine - INFO - Epoch(train) [89][400/586] lr: 5.000000e-04 eta: 4:16:47 time: 0.259861 data_time: 0.026338 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.830611 loss: 0.000610 2022/10/20 13:37:38 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:37:43 - mmengine - INFO - Epoch(train) [89][450/586] lr: 5.000000e-04 eta: 4:16:40 time: 0.275184 data_time: 0.023231 memory: 7326 loss_kpt: 0.000615 acc_pose: 0.826567 loss: 0.000615 2022/10/20 13:37:57 - mmengine - INFO - Epoch(train) [89][500/586] lr: 5.000000e-04 eta: 4:16:33 time: 0.282624 data_time: 0.024956 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.826079 loss: 0.000595 2022/10/20 13:38:15 - mmengine - INFO - Epoch(train) [89][550/586] lr: 5.000000e-04 eta: 4:16:32 time: 0.352685 data_time: 0.043837 memory: 7326 loss_kpt: 0.000621 acc_pose: 0.877187 loss: 0.000621 2022/10/20 13:38:23 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:38:36 - mmengine - INFO - Epoch(train) [90][50/586] lr: 5.000000e-04 eta: 4:16:05 time: 0.245447 data_time: 0.037164 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.868345 loss: 0.000614 2022/10/20 13:38:49 - mmengine - INFO - Epoch(train) [90][100/586] lr: 5.000000e-04 eta: 4:15:58 time: 0.276195 data_time: 0.025805 memory: 7326 loss_kpt: 0.000611 acc_pose: 0.848265 loss: 0.000611 2022/10/20 13:39:03 - mmengine - INFO - Epoch(train) [90][150/586] lr: 5.000000e-04 eta: 4:15:50 time: 0.267534 data_time: 0.025745 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.862236 loss: 0.000614 2022/10/20 13:39:17 - mmengine - INFO - Epoch(train) [90][200/586] lr: 5.000000e-04 eta: 4:15:43 time: 0.276092 data_time: 0.025694 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.801095 loss: 0.000614 2022/10/20 13:39:30 - mmengine - INFO - Epoch(train) [90][250/586] lr: 5.000000e-04 eta: 4:15:36 time: 0.261805 data_time: 0.025458 memory: 7326 loss_kpt: 0.000624 acc_pose: 0.842151 loss: 0.000624 2022/10/20 13:39:43 - mmengine - INFO - Epoch(train) [90][300/586] lr: 5.000000e-04 eta: 4:15:28 time: 0.258886 data_time: 0.023651 memory: 7326 loss_kpt: 0.000611 acc_pose: 0.803031 loss: 0.000611 2022/10/20 13:39:55 - mmengine - INFO - Epoch(train) [90][350/586] lr: 5.000000e-04 eta: 4:15:19 time: 0.247980 data_time: 0.027046 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.883654 loss: 0.000612 2022/10/20 13:40:07 - mmengine - INFO - Epoch(train) [90][400/586] lr: 5.000000e-04 eta: 4:15:10 time: 0.240104 data_time: 0.025676 memory: 7326 loss_kpt: 0.000641 acc_pose: 0.772966 loss: 0.000641 2022/10/20 13:40:19 - mmengine - INFO - Epoch(train) [90][450/586] lr: 5.000000e-04 eta: 4:15:00 time: 0.241657 data_time: 0.028232 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.759664 loss: 0.000614 2022/10/20 13:40:33 - mmengine - INFO - Epoch(train) [90][500/586] lr: 5.000000e-04 eta: 4:14:54 time: 0.278126 data_time: 0.057835 memory: 7326 loss_kpt: 0.000617 acc_pose: 0.747820 loss: 0.000617 2022/10/20 13:40:46 - mmengine - INFO - Epoch(train) [90][550/586] lr: 5.000000e-04 eta: 4:14:46 time: 0.266115 data_time: 0.027223 memory: 7326 loss_kpt: 0.000602 acc_pose: 0.847778 loss: 0.000602 2022/10/20 13:40:56 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:40:56 - mmengine - INFO - Saving checkpoint at 90 epochs 2022/10/20 13:41:12 - mmengine - INFO - Epoch(val) [90][50/407] eta: 0:01:24 time: 0.237434 data_time: 0.156688 memory: 7326 2022/10/20 13:41:20 - mmengine - INFO - Epoch(val) [90][100/407] eta: 0:00:53 time: 0.173491 data_time: 0.097221 memory: 1680 2022/10/20 13:41:28 - mmengine - INFO - Epoch(val) [90][150/407] eta: 0:00:39 time: 0.155025 data_time: 0.077284 memory: 1680 2022/10/20 13:41:37 - mmengine - INFO - Epoch(val) [90][200/407] eta: 0:00:37 time: 0.182685 data_time: 0.104341 memory: 1680 2022/10/20 13:41:45 - mmengine - INFO - Epoch(val) [90][250/407] eta: 0:00:24 time: 0.153573 data_time: 0.077292 memory: 1680 2022/10/20 13:41:58 - mmengine - INFO - Epoch(val) [90][300/407] eta: 0:00:28 time: 0.268531 data_time: 0.192536 memory: 1680 2022/10/20 13:42:10 - mmengine - INFO - Epoch(val) [90][350/407] eta: 0:00:13 time: 0.231103 data_time: 0.153986 memory: 1680 2022/10/20 13:42:18 - mmengine - INFO - Epoch(val) [90][400/407] eta: 0:00:01 time: 0.159554 data_time: 0.082660 memory: 1680 2022/10/20 13:43:50 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 13:44:03 - mmengine - INFO - Epoch(val) [90][407/407] coco/AP: 0.720451 coco/AP .5: 0.897995 coco/AP .75: 0.799892 coco/AP (M): 0.682132 coco/AP (L): 0.788565 coco/AR: 0.777409 coco/AR .5: 0.937343 coco/AR .75: 0.849024 coco/AR (M): 0.732969 coco/AR (L): 0.841323 2022/10/20 13:44:03 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_70.pth is removed 2022/10/20 13:44:05 - mmengine - INFO - The best checkpoint with 0.7205 coco/AP at 90 epoch is saved to best_coco/AP_epoch_90.pth. 2022/10/20 13:44:19 - mmengine - INFO - Epoch(train) [91][50/586] lr: 5.000000e-04 eta: 4:14:20 time: 0.272372 data_time: 0.058937 memory: 7326 loss_kpt: 0.000618 acc_pose: 0.742930 loss: 0.000618 2022/10/20 13:44:32 - mmengine - INFO - Epoch(train) [91][100/586] lr: 5.000000e-04 eta: 4:14:13 time: 0.265013 data_time: 0.034425 memory: 7326 loss_kpt: 0.000615 acc_pose: 0.792917 loss: 0.000615 2022/10/20 13:44:47 - mmengine - INFO - Epoch(train) [91][150/586] lr: 5.000000e-04 eta: 4:14:06 time: 0.284692 data_time: 0.071747 memory: 7326 loss_kpt: 0.000625 acc_pose: 0.858905 loss: 0.000625 2022/10/20 13:45:00 - mmengine - INFO - Epoch(train) [91][200/586] lr: 5.000000e-04 eta: 4:13:59 time: 0.276017 data_time: 0.028812 memory: 7326 loss_kpt: 0.000613 acc_pose: 0.838097 loss: 0.000613 2022/10/20 13:45:14 - mmengine - INFO - Epoch(train) [91][250/586] lr: 5.000000e-04 eta: 4:13:52 time: 0.265235 data_time: 0.041196 memory: 7326 loss_kpt: 0.000602 acc_pose: 0.832139 loss: 0.000602 2022/10/20 13:45:16 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:45:27 - mmengine - INFO - Epoch(train) [91][300/586] lr: 5.000000e-04 eta: 4:13:44 time: 0.266814 data_time: 0.042179 memory: 7326 loss_kpt: 0.000607 acc_pose: 0.822892 loss: 0.000607 2022/10/20 13:45:41 - mmengine - INFO - Epoch(train) [91][350/586] lr: 5.000000e-04 eta: 4:13:37 time: 0.273540 data_time: 0.046704 memory: 7326 loss_kpt: 0.000618 acc_pose: 0.826301 loss: 0.000618 2022/10/20 13:45:53 - mmengine - INFO - Epoch(train) [91][400/586] lr: 5.000000e-04 eta: 4:13:29 time: 0.254838 data_time: 0.035751 memory: 7326 loss_kpt: 0.000608 acc_pose: 0.910314 loss: 0.000608 2022/10/20 13:46:06 - mmengine - INFO - Epoch(train) [91][450/586] lr: 5.000000e-04 eta: 4:13:20 time: 0.250491 data_time: 0.046623 memory: 7326 loss_kpt: 0.000628 acc_pose: 0.821018 loss: 0.000628 2022/10/20 13:46:21 - mmengine - INFO - Epoch(train) [91][500/586] lr: 5.000000e-04 eta: 4:13:14 time: 0.299332 data_time: 0.060893 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.851294 loss: 0.000601 2022/10/20 13:46:35 - mmengine - INFO - Epoch(train) [91][550/586] lr: 5.000000e-04 eta: 4:13:07 time: 0.271067 data_time: 0.030033 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.866508 loss: 0.000612 2022/10/20 13:46:44 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:46:57 - mmengine - INFO - Epoch(train) [92][50/586] lr: 5.000000e-04 eta: 4:12:41 time: 0.270207 data_time: 0.040773 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.859695 loss: 0.000610 2022/10/20 13:47:11 - mmengine - INFO - Epoch(train) [92][100/586] lr: 5.000000e-04 eta: 4:12:34 time: 0.270275 data_time: 0.038001 memory: 7326 loss_kpt: 0.000607 acc_pose: 0.820881 loss: 0.000607 2022/10/20 13:47:26 - mmengine - INFO - Epoch(train) [92][150/586] lr: 5.000000e-04 eta: 4:12:29 time: 0.300875 data_time: 0.054088 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.863945 loss: 0.000605 2022/10/20 13:47:39 - mmengine - INFO - Epoch(train) [92][200/586] lr: 5.000000e-04 eta: 4:12:21 time: 0.263968 data_time: 0.046709 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.856841 loss: 0.000601 2022/10/20 13:47:52 - mmengine - INFO - Epoch(train) [92][250/586] lr: 5.000000e-04 eta: 4:12:12 time: 0.249191 data_time: 0.029786 memory: 7326 loss_kpt: 0.000606 acc_pose: 0.864170 loss: 0.000606 2022/10/20 13:48:06 - mmengine - INFO - Epoch(train) [92][300/586] lr: 5.000000e-04 eta: 4:12:06 time: 0.290077 data_time: 0.035574 memory: 7326 loss_kpt: 0.000616 acc_pose: 0.808489 loss: 0.000616 2022/10/20 13:48:19 - mmengine - INFO - Epoch(train) [92][350/586] lr: 5.000000e-04 eta: 4:11:57 time: 0.261127 data_time: 0.032423 memory: 7326 loss_kpt: 0.000603 acc_pose: 0.816535 loss: 0.000603 2022/10/20 13:48:33 - mmengine - INFO - Epoch(train) [92][400/586] lr: 5.000000e-04 eta: 4:11:50 time: 0.274233 data_time: 0.050443 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.832922 loss: 0.000612 2022/10/20 13:48:47 - mmengine - INFO - Epoch(train) [92][450/586] lr: 5.000000e-04 eta: 4:11:43 time: 0.277113 data_time: 0.062416 memory: 7326 loss_kpt: 0.000602 acc_pose: 0.851158 loss: 0.000602 2022/10/20 13:49:00 - mmengine - INFO - Epoch(train) [92][500/586] lr: 5.000000e-04 eta: 4:11:35 time: 0.266535 data_time: 0.047629 memory: 7326 loss_kpt: 0.000617 acc_pose: 0.809241 loss: 0.000617 2022/10/20 13:49:13 - mmengine - INFO - Epoch(train) [92][550/586] lr: 5.000000e-04 eta: 4:11:27 time: 0.260874 data_time: 0.031336 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.840421 loss: 0.000594 2022/10/20 13:49:23 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:49:37 - mmengine - INFO - Epoch(train) [93][50/586] lr: 5.000000e-04 eta: 4:11:02 time: 0.272831 data_time: 0.050355 memory: 7326 loss_kpt: 0.000603 acc_pose: 0.839752 loss: 0.000603 2022/10/20 13:49:47 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:49:50 - mmengine - INFO - Epoch(train) [93][100/586] lr: 5.000000e-04 eta: 4:10:54 time: 0.259363 data_time: 0.036257 memory: 7326 loss_kpt: 0.000607 acc_pose: 0.810453 loss: 0.000607 2022/10/20 13:50:03 - mmengine - INFO - Epoch(train) [93][150/586] lr: 5.000000e-04 eta: 4:10:46 time: 0.270856 data_time: 0.028843 memory: 7326 loss_kpt: 0.000620 acc_pose: 0.816724 loss: 0.000620 2022/10/20 13:50:16 - mmengine - INFO - Epoch(train) [93][200/586] lr: 5.000000e-04 eta: 4:10:37 time: 0.248202 data_time: 0.028738 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.825610 loss: 0.000587 2022/10/20 13:50:29 - mmengine - INFO - Epoch(train) [93][250/586] lr: 5.000000e-04 eta: 4:10:29 time: 0.265258 data_time: 0.037059 memory: 7326 loss_kpt: 0.000613 acc_pose: 0.877948 loss: 0.000613 2022/10/20 13:50:47 - mmengine - INFO - Epoch(train) [93][300/586] lr: 5.000000e-04 eta: 4:10:27 time: 0.354391 data_time: 0.106115 memory: 7326 loss_kpt: 0.000603 acc_pose: 0.838628 loss: 0.000603 2022/10/20 13:51:01 - mmengine - INFO - Epoch(train) [93][350/586] lr: 5.000000e-04 eta: 4:10:21 time: 0.290384 data_time: 0.038445 memory: 7326 loss_kpt: 0.000617 acc_pose: 0.829246 loss: 0.000617 2022/10/20 13:51:16 - mmengine - INFO - Epoch(train) [93][400/586] lr: 5.000000e-04 eta: 4:10:15 time: 0.299666 data_time: 0.027065 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.808576 loss: 0.000622 2022/10/20 13:51:31 - mmengine - INFO - Epoch(train) [93][450/586] lr: 5.000000e-04 eta: 4:10:09 time: 0.305042 data_time: 0.031831 memory: 7326 loss_kpt: 0.000620 acc_pose: 0.805289 loss: 0.000620 2022/10/20 13:51:45 - mmengine - INFO - Epoch(train) [93][500/586] lr: 5.000000e-04 eta: 4:10:02 time: 0.273894 data_time: 0.030173 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.775691 loss: 0.000605 2022/10/20 13:52:00 - mmengine - INFO - Epoch(train) [93][550/586] lr: 5.000000e-04 eta: 4:09:56 time: 0.294719 data_time: 0.034939 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.854911 loss: 0.000601 2022/10/20 13:52:11 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:52:26 - mmengine - INFO - Epoch(train) [94][50/586] lr: 5.000000e-04 eta: 4:09:33 time: 0.304972 data_time: 0.097275 memory: 7326 loss_kpt: 0.000620 acc_pose: 0.850011 loss: 0.000620 2022/10/20 13:52:41 - mmengine - INFO - Epoch(train) [94][100/586] lr: 5.000000e-04 eta: 4:09:27 time: 0.299560 data_time: 0.047197 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.834638 loss: 0.000595 2022/10/20 13:52:55 - mmengine - INFO - Epoch(train) [94][150/586] lr: 5.000000e-04 eta: 4:09:20 time: 0.290285 data_time: 0.071606 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.888034 loss: 0.000596 2022/10/20 13:53:14 - mmengine - INFO - Epoch(train) [94][200/586] lr: 5.000000e-04 eta: 4:09:18 time: 0.361778 data_time: 0.110241 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.877600 loss: 0.000589 2022/10/20 13:53:29 - mmengine - INFO - Epoch(train) [94][250/586] lr: 5.000000e-04 eta: 4:09:13 time: 0.308391 data_time: 0.037542 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.864205 loss: 0.000612 2022/10/20 13:53:44 - mmengine - INFO - Epoch(train) [94][300/586] lr: 5.000000e-04 eta: 4:09:07 time: 0.295863 data_time: 0.024315 memory: 7326 loss_kpt: 0.000599 acc_pose: 0.860403 loss: 0.000599 2022/10/20 13:53:59 - mmengine - INFO - Epoch(train) [94][350/586] lr: 5.000000e-04 eta: 4:09:01 time: 0.309779 data_time: 0.058049 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.818549 loss: 0.000610 2022/10/20 13:54:15 - mmengine - INFO - Epoch(train) [94][400/586] lr: 5.000000e-04 eta: 4:08:57 time: 0.319886 data_time: 0.042056 memory: 7326 loss_kpt: 0.000616 acc_pose: 0.805784 loss: 0.000616 2022/10/20 13:54:33 - mmengine - INFO - Epoch(train) [94][450/586] lr: 5.000000e-04 eta: 4:08:54 time: 0.356923 data_time: 0.025477 memory: 7326 loss_kpt: 0.000613 acc_pose: 0.858458 loss: 0.000613 2022/10/20 13:54:50 - mmengine - INFO - Epoch(train) [94][500/586] lr: 5.000000e-04 eta: 4:08:51 time: 0.343198 data_time: 0.023718 memory: 7326 loss_kpt: 0.000609 acc_pose: 0.860019 loss: 0.000609 2022/10/20 13:54:51 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:55:07 - mmengine - INFO - Epoch(train) [94][550/586] lr: 5.000000e-04 eta: 4:08:47 time: 0.330112 data_time: 0.046117 memory: 7326 loss_kpt: 0.000618 acc_pose: 0.805647 loss: 0.000618 2022/10/20 13:55:17 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:55:33 - mmengine - INFO - Epoch(train) [95][50/586] lr: 5.000000e-04 eta: 4:08:25 time: 0.320832 data_time: 0.042032 memory: 7326 loss_kpt: 0.000626 acc_pose: 0.822864 loss: 0.000626 2022/10/20 13:55:48 - mmengine - INFO - Epoch(train) [95][100/586] lr: 5.000000e-04 eta: 4:08:19 time: 0.300045 data_time: 0.044929 memory: 7326 loss_kpt: 0.000616 acc_pose: 0.825180 loss: 0.000616 2022/10/20 13:56:02 - mmengine - INFO - Epoch(train) [95][150/586] lr: 5.000000e-04 eta: 4:08:11 time: 0.270226 data_time: 0.025922 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.833112 loss: 0.000605 2022/10/20 13:56:18 - mmengine - INFO - Epoch(train) [95][200/586] lr: 5.000000e-04 eta: 4:08:05 time: 0.312102 data_time: 0.028714 memory: 7326 loss_kpt: 0.000602 acc_pose: 0.861861 loss: 0.000602 2022/10/20 13:56:34 - mmengine - INFO - Epoch(train) [95][250/586] lr: 5.000000e-04 eta: 4:08:01 time: 0.333732 data_time: 0.028963 memory: 7326 loss_kpt: 0.000604 acc_pose: 0.787662 loss: 0.000604 2022/10/20 13:56:51 - mmengine - INFO - Epoch(train) [95][300/586] lr: 5.000000e-04 eta: 4:07:57 time: 0.329479 data_time: 0.025549 memory: 7326 loss_kpt: 0.000599 acc_pose: 0.847936 loss: 0.000599 2022/10/20 13:57:05 - mmengine - INFO - Epoch(train) [95][350/586] lr: 5.000000e-04 eta: 4:07:50 time: 0.284966 data_time: 0.032219 memory: 7326 loss_kpt: 0.000606 acc_pose: 0.852126 loss: 0.000606 2022/10/20 13:57:22 - mmengine - INFO - Epoch(train) [95][400/586] lr: 5.000000e-04 eta: 4:07:47 time: 0.345517 data_time: 0.025717 memory: 7326 loss_kpt: 0.000611 acc_pose: 0.876249 loss: 0.000611 2022/10/20 13:57:36 - mmengine - INFO - Epoch(train) [95][450/586] lr: 5.000000e-04 eta: 4:07:39 time: 0.276838 data_time: 0.028661 memory: 7326 loss_kpt: 0.000600 acc_pose: 0.861034 loss: 0.000600 2022/10/20 13:57:52 - mmengine - INFO - Epoch(train) [95][500/586] lr: 5.000000e-04 eta: 4:07:34 time: 0.317112 data_time: 0.026259 memory: 7326 loss_kpt: 0.000582 acc_pose: 0.800178 loss: 0.000582 2022/10/20 13:58:06 - mmengine - INFO - Epoch(train) [95][550/586] lr: 5.000000e-04 eta: 4:07:27 time: 0.287959 data_time: 0.031679 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.881319 loss: 0.000596 2022/10/20 13:58:18 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 13:58:33 - mmengine - INFO - Epoch(train) [96][50/586] lr: 5.000000e-04 eta: 4:07:03 time: 0.289663 data_time: 0.037342 memory: 7326 loss_kpt: 0.000608 acc_pose: 0.834304 loss: 0.000608 2022/10/20 13:58:46 - mmengine - INFO - Epoch(train) [96][100/586] lr: 5.000000e-04 eta: 4:06:55 time: 0.267117 data_time: 0.033686 memory: 7326 loss_kpt: 0.000609 acc_pose: 0.856675 loss: 0.000609 2022/10/20 13:59:00 - mmengine - INFO - Epoch(train) [96][150/586] lr: 5.000000e-04 eta: 4:06:47 time: 0.273643 data_time: 0.026500 memory: 7326 loss_kpt: 0.000631 acc_pose: 0.815782 loss: 0.000631 2022/10/20 13:59:17 - mmengine - INFO - Epoch(train) [96][200/586] lr: 5.000000e-04 eta: 4:06:43 time: 0.339363 data_time: 0.046229 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.852298 loss: 0.000595 2022/10/20 13:59:34 - mmengine - INFO - Epoch(train) [96][250/586] lr: 5.000000e-04 eta: 4:06:39 time: 0.335622 data_time: 0.028764 memory: 7326 loss_kpt: 0.000622 acc_pose: 0.827236 loss: 0.000622 2022/10/20 13:59:48 - mmengine - INFO - Epoch(train) [96][300/586] lr: 5.000000e-04 eta: 4:06:32 time: 0.284706 data_time: 0.042638 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.872087 loss: 0.000596 2022/10/20 13:59:56 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:00:01 - mmengine - INFO - Epoch(train) [96][350/586] lr: 5.000000e-04 eta: 4:06:23 time: 0.263236 data_time: 0.031914 memory: 7326 loss_kpt: 0.000603 acc_pose: 0.851456 loss: 0.000603 2022/10/20 14:00:14 - mmengine - INFO - Epoch(train) [96][400/586] lr: 5.000000e-04 eta: 4:06:15 time: 0.263847 data_time: 0.029305 memory: 7326 loss_kpt: 0.000602 acc_pose: 0.868862 loss: 0.000602 2022/10/20 14:00:30 - mmengine - INFO - Epoch(train) [96][450/586] lr: 5.000000e-04 eta: 4:06:09 time: 0.305565 data_time: 0.039602 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.846869 loss: 0.000614 2022/10/20 14:00:44 - mmengine - INFO - Epoch(train) [96][500/586] lr: 5.000000e-04 eta: 4:06:02 time: 0.294453 data_time: 0.030245 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.903868 loss: 0.000584 2022/10/20 14:00:59 - mmengine - INFO - Epoch(train) [96][550/586] lr: 5.000000e-04 eta: 4:05:55 time: 0.284678 data_time: 0.034568 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.848849 loss: 0.000601 2022/10/20 14:01:08 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:01:26 - mmengine - INFO - Epoch(train) [97][50/586] lr: 5.000000e-04 eta: 4:05:35 time: 0.359159 data_time: 0.034501 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.819824 loss: 0.000596 2022/10/20 14:01:40 - mmengine - INFO - Epoch(train) [97][100/586] lr: 5.000000e-04 eta: 4:05:27 time: 0.279537 data_time: 0.026210 memory: 7326 loss_kpt: 0.000607 acc_pose: 0.847453 loss: 0.000607 2022/10/20 14:01:55 - mmengine - INFO - Epoch(train) [97][150/586] lr: 5.000000e-04 eta: 4:05:20 time: 0.291421 data_time: 0.039072 memory: 7326 loss_kpt: 0.000600 acc_pose: 0.790221 loss: 0.000600 2022/10/20 14:02:09 - mmengine - INFO - Epoch(train) [97][200/586] lr: 5.000000e-04 eta: 4:05:13 time: 0.274985 data_time: 0.040553 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.851246 loss: 0.000594 2022/10/20 14:02:22 - mmengine - INFO - Epoch(train) [97][250/586] lr: 5.000000e-04 eta: 4:05:05 time: 0.271166 data_time: 0.039218 memory: 7326 loss_kpt: 0.000603 acc_pose: 0.822805 loss: 0.000603 2022/10/20 14:02:36 - mmengine - INFO - Epoch(train) [97][300/586] lr: 5.000000e-04 eta: 4:04:57 time: 0.281770 data_time: 0.029542 memory: 7326 loss_kpt: 0.000602 acc_pose: 0.827741 loss: 0.000602 2022/10/20 14:02:52 - mmengine - INFO - Epoch(train) [97][350/586] lr: 5.000000e-04 eta: 4:04:51 time: 0.311088 data_time: 0.034608 memory: 7326 loss_kpt: 0.000609 acc_pose: 0.875246 loss: 0.000609 2022/10/20 14:03:06 - mmengine - INFO - Epoch(train) [97][400/586] lr: 5.000000e-04 eta: 4:04:44 time: 0.278921 data_time: 0.029891 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.841627 loss: 0.000594 2022/10/20 14:03:20 - mmengine - INFO - Epoch(train) [97][450/586] lr: 5.000000e-04 eta: 4:04:36 time: 0.284784 data_time: 0.037688 memory: 7326 loss_kpt: 0.000603 acc_pose: 0.833100 loss: 0.000603 2022/10/20 14:03:36 - mmengine - INFO - Epoch(train) [97][500/586] lr: 5.000000e-04 eta: 4:04:30 time: 0.308167 data_time: 0.033592 memory: 7326 loss_kpt: 0.000615 acc_pose: 0.865633 loss: 0.000615 2022/10/20 14:03:50 - mmengine - INFO - Epoch(train) [97][550/586] lr: 5.000000e-04 eta: 4:04:23 time: 0.290864 data_time: 0.026038 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.885941 loss: 0.000610 2022/10/20 14:04:00 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:04:15 - mmengine - INFO - Epoch(train) [98][50/586] lr: 5.000000e-04 eta: 4:04:00 time: 0.305478 data_time: 0.051578 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.887508 loss: 0.000612 2022/10/20 14:04:31 - mmengine - INFO - Epoch(train) [98][100/586] lr: 5.000000e-04 eta: 4:03:54 time: 0.310411 data_time: 0.044989 memory: 7326 loss_kpt: 0.000613 acc_pose: 0.898653 loss: 0.000613 2022/10/20 14:04:45 - mmengine - INFO - Epoch(train) [98][150/586] lr: 5.000000e-04 eta: 4:03:47 time: 0.292584 data_time: 0.036738 memory: 7326 loss_kpt: 0.000603 acc_pose: 0.910266 loss: 0.000603 2022/10/20 14:04:48 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:05:00 - mmengine - INFO - Epoch(train) [98][200/586] lr: 5.000000e-04 eta: 4:03:40 time: 0.285746 data_time: 0.044300 memory: 7326 loss_kpt: 0.000600 acc_pose: 0.892398 loss: 0.000600 2022/10/20 14:05:13 - mmengine - INFO - Epoch(train) [98][250/586] lr: 5.000000e-04 eta: 4:03:32 time: 0.270665 data_time: 0.031582 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.842274 loss: 0.000590 2022/10/20 14:05:27 - mmengine - INFO - Epoch(train) [98][300/586] lr: 5.000000e-04 eta: 4:03:24 time: 0.276763 data_time: 0.028675 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.864558 loss: 0.000586 2022/10/20 14:05:41 - mmengine - INFO - Epoch(train) [98][350/586] lr: 5.000000e-04 eta: 4:03:16 time: 0.286306 data_time: 0.056099 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.822115 loss: 0.000619 2022/10/20 14:05:55 - mmengine - INFO - Epoch(train) [98][400/586] lr: 5.000000e-04 eta: 4:03:09 time: 0.280561 data_time: 0.050119 memory: 7326 loss_kpt: 0.000597 acc_pose: 0.776195 loss: 0.000597 2022/10/20 14:06:10 - mmengine - INFO - Epoch(train) [98][450/586] lr: 5.000000e-04 eta: 4:03:01 time: 0.287860 data_time: 0.073369 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.850215 loss: 0.000587 2022/10/20 14:06:24 - mmengine - INFO - Epoch(train) [98][500/586] lr: 5.000000e-04 eta: 4:02:54 time: 0.279740 data_time: 0.031197 memory: 7326 loss_kpt: 0.000591 acc_pose: 0.825879 loss: 0.000591 2022/10/20 14:06:38 - mmengine - INFO - Epoch(train) [98][550/586] lr: 5.000000e-04 eta: 4:02:46 time: 0.279490 data_time: 0.051159 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.837146 loss: 0.000590 2022/10/20 14:06:48 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:07:03 - mmengine - INFO - Epoch(train) [99][50/586] lr: 5.000000e-04 eta: 4:02:22 time: 0.303114 data_time: 0.033903 memory: 7326 loss_kpt: 0.000606 acc_pose: 0.829495 loss: 0.000606 2022/10/20 14:07:17 - mmengine - INFO - Epoch(train) [99][100/586] lr: 5.000000e-04 eta: 4:02:14 time: 0.263752 data_time: 0.040312 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.812929 loss: 0.000596 2022/10/20 14:07:33 - mmengine - INFO - Epoch(train) [99][150/586] lr: 5.000000e-04 eta: 4:02:09 time: 0.331167 data_time: 0.087380 memory: 7326 loss_kpt: 0.000627 acc_pose: 0.853280 loss: 0.000627 2022/10/20 14:07:49 - mmengine - INFO - Epoch(train) [99][200/586] lr: 5.000000e-04 eta: 4:02:03 time: 0.318351 data_time: 0.037718 memory: 7326 loss_kpt: 0.000598 acc_pose: 0.828249 loss: 0.000598 2022/10/20 14:08:13 - mmengine - INFO - Epoch(train) [99][250/586] lr: 5.000000e-04 eta: 4:02:06 time: 0.475325 data_time: 0.085536 memory: 7326 loss_kpt: 0.000602 acc_pose: 0.850424 loss: 0.000602 2022/10/20 14:08:29 - mmengine - INFO - Epoch(train) [99][300/586] lr: 5.000000e-04 eta: 4:02:01 time: 0.325746 data_time: 0.043161 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.854484 loss: 0.000605 2022/10/20 14:08:46 - mmengine - INFO - Epoch(train) [99][350/586] lr: 5.000000e-04 eta: 4:01:56 time: 0.330427 data_time: 0.030641 memory: 7326 loss_kpt: 0.000606 acc_pose: 0.843919 loss: 0.000606 2022/10/20 14:09:06 - mmengine - INFO - Epoch(train) [99][400/586] lr: 5.000000e-04 eta: 4:01:56 time: 0.413894 data_time: 0.029157 memory: 7326 loss_kpt: 0.000615 acc_pose: 0.925701 loss: 0.000615 2022/10/20 14:09:29 - mmengine - INFO - Epoch(train) [99][450/586] lr: 5.000000e-04 eta: 4:01:58 time: 0.456195 data_time: 0.023075 memory: 7326 loss_kpt: 0.000598 acc_pose: 0.820442 loss: 0.000598 2022/10/20 14:09:45 - mmengine - INFO - Epoch(train) [99][500/586] lr: 5.000000e-04 eta: 4:01:52 time: 0.317088 data_time: 0.040310 memory: 7326 loss_kpt: 0.000602 acc_pose: 0.845599 loss: 0.000602 2022/10/20 14:10:02 - mmengine - INFO - Epoch(train) [99][550/586] lr: 5.000000e-04 eta: 4:01:48 time: 0.348846 data_time: 0.047531 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.897305 loss: 0.000596 2022/10/20 14:10:13 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:10:18 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:10:38 - mmengine - INFO - Epoch(train) [100][50/586] lr: 5.000000e-04 eta: 4:01:29 time: 0.393965 data_time: 0.042847 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.800836 loss: 0.000584 2022/10/20 14:10:55 - mmengine - INFO - Epoch(train) [100][100/586] lr: 5.000000e-04 eta: 4:01:25 time: 0.345187 data_time: 0.024090 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.896159 loss: 0.000587 2022/10/20 14:11:15 - mmengine - INFO - Epoch(train) [100][150/586] lr: 5.000000e-04 eta: 4:01:24 time: 0.397635 data_time: 0.025393 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.838233 loss: 0.000610 2022/10/20 14:11:29 - mmengine - INFO - Epoch(train) [100][200/586] lr: 5.000000e-04 eta: 4:01:16 time: 0.285353 data_time: 0.025846 memory: 7326 loss_kpt: 0.000606 acc_pose: 0.874907 loss: 0.000606 2022/10/20 14:11:47 - mmengine - INFO - Epoch(train) [100][250/586] lr: 5.000000e-04 eta: 4:01:12 time: 0.347170 data_time: 0.024868 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.863860 loss: 0.000610 2022/10/20 14:12:05 - mmengine - INFO - Epoch(train) [100][300/586] lr: 5.000000e-04 eta: 4:01:08 time: 0.368490 data_time: 0.023078 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.849852 loss: 0.000590 2022/10/20 14:12:24 - mmengine - INFO - Epoch(train) [100][350/586] lr: 5.000000e-04 eta: 4:01:05 time: 0.367739 data_time: 0.026049 memory: 7326 loss_kpt: 0.000588 acc_pose: 0.863198 loss: 0.000588 2022/10/20 14:12:43 - mmengine - INFO - Epoch(train) [100][400/586] lr: 5.000000e-04 eta: 4:01:03 time: 0.393305 data_time: 0.024606 memory: 7326 loss_kpt: 0.000604 acc_pose: 0.835488 loss: 0.000604 2022/10/20 14:13:03 - mmengine - INFO - Epoch(train) [100][450/586] lr: 5.000000e-04 eta: 4:01:01 time: 0.384342 data_time: 0.032074 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.876219 loss: 0.000592 2022/10/20 14:13:21 - mmengine - INFO - Epoch(train) [100][500/586] lr: 5.000000e-04 eta: 4:00:58 time: 0.361158 data_time: 0.042744 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.850975 loss: 0.000592 2022/10/20 14:13:40 - mmengine - INFO - Epoch(train) [100][550/586] lr: 5.000000e-04 eta: 4:00:56 time: 0.395779 data_time: 0.024797 memory: 7326 loss_kpt: 0.000602 acc_pose: 0.844431 loss: 0.000602 2022/10/20 14:13:55 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:13:55 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/10/20 14:14:12 - mmengine - INFO - Epoch(val) [100][50/407] eta: 0:01:38 time: 0.275313 data_time: 0.196876 memory: 7326 2022/10/20 14:14:23 - mmengine - INFO - Epoch(val) [100][100/407] eta: 0:01:07 time: 0.220432 data_time: 0.142197 memory: 1680 2022/10/20 14:14:32 - mmengine - INFO - Epoch(val) [100][150/407] eta: 0:00:46 time: 0.181645 data_time: 0.103692 memory: 1680 2022/10/20 14:14:43 - mmengine - INFO - Epoch(val) [100][200/407] eta: 0:00:43 time: 0.210599 data_time: 0.132338 memory: 1680 2022/10/20 14:14:55 - mmengine - INFO - Epoch(val) [100][250/407] eta: 0:00:38 time: 0.244620 data_time: 0.166079 memory: 1680 2022/10/20 14:15:17 - mmengine - INFO - Epoch(val) [100][300/407] eta: 0:00:45 time: 0.426144 data_time: 0.342704 memory: 1680 2022/10/20 14:15:44 - mmengine - INFO - Epoch(val) [100][350/407] eta: 0:00:30 time: 0.539987 data_time: 0.461537 memory: 1680 2022/10/20 14:15:56 - mmengine - INFO - Epoch(val) [100][400/407] eta: 0:00:01 time: 0.240154 data_time: 0.162551 memory: 1680 2022/10/20 14:16:48 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 14:17:01 - mmengine - INFO - Epoch(val) [100][407/407] coco/AP: 0.726053 coco/AP .5: 0.897985 coco/AP .75: 0.803922 coco/AP (M): 0.690198 coco/AP (L): 0.792997 coco/AR: 0.781943 coco/AR .5: 0.936713 coco/AR .75: 0.850283 coco/AR (M): 0.739060 coco/AR (L): 0.843887 2022/10/20 14:17:01 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_90.pth is removed 2022/10/20 14:17:03 - mmengine - INFO - The best checkpoint with 0.7261 coco/AP at 100 epoch is saved to best_coco/AP_epoch_100.pth. 2022/10/20 14:17:23 - mmengine - INFO - Epoch(train) [101][50/586] lr: 5.000000e-04 eta: 4:00:37 time: 0.396452 data_time: 0.073777 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.785474 loss: 0.000587 2022/10/20 14:17:40 - mmengine - INFO - Epoch(train) [101][100/586] lr: 5.000000e-04 eta: 4:00:33 time: 0.344462 data_time: 0.096655 memory: 7326 loss_kpt: 0.000608 acc_pose: 0.873716 loss: 0.000608 2022/10/20 14:18:06 - mmengine - INFO - Epoch(train) [101][150/586] lr: 5.000000e-04 eta: 4:00:37 time: 0.510305 data_time: 0.116173 memory: 7326 loss_kpt: 0.000591 acc_pose: 0.857211 loss: 0.000591 2022/10/20 14:18:22 - mmengine - INFO - Epoch(train) [101][200/586] lr: 5.000000e-04 eta: 4:00:31 time: 0.328750 data_time: 0.045115 memory: 7326 loss_kpt: 0.000598 acc_pose: 0.838902 loss: 0.000598 2022/10/20 14:18:40 - mmengine - INFO - Epoch(train) [101][250/586] lr: 5.000000e-04 eta: 4:00:28 time: 0.363441 data_time: 0.125831 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.852620 loss: 0.000610 2022/10/20 14:18:59 - mmengine - INFO - Epoch(train) [101][300/586] lr: 5.000000e-04 eta: 4:00:25 time: 0.378131 data_time: 0.039013 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.790892 loss: 0.000601 2022/10/20 14:19:21 - mmengine - INFO - Epoch(train) [101][350/586] lr: 5.000000e-04 eta: 4:00:25 time: 0.437010 data_time: 0.039592 memory: 7326 loss_kpt: 0.000607 acc_pose: 0.872347 loss: 0.000607 2022/10/20 14:19:39 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:19:39 - mmengine - INFO - Epoch(train) [101][400/586] lr: 5.000000e-04 eta: 4:00:21 time: 0.352703 data_time: 0.067426 memory: 7326 loss_kpt: 0.000608 acc_pose: 0.806406 loss: 0.000608 2022/10/20 14:19:59 - mmengine - INFO - Epoch(train) [101][450/586] lr: 5.000000e-04 eta: 4:00:20 time: 0.411258 data_time: 0.025212 memory: 7326 loss_kpt: 0.000626 acc_pose: 0.898777 loss: 0.000626 2022/10/20 14:20:21 - mmengine - INFO - Epoch(train) [101][500/586] lr: 5.000000e-04 eta: 4:00:20 time: 0.438501 data_time: 0.025298 memory: 7326 loss_kpt: 0.000578 acc_pose: 0.862875 loss: 0.000578 2022/10/20 14:20:39 - mmengine - INFO - Epoch(train) [101][550/586] lr: 5.000000e-04 eta: 4:00:15 time: 0.347462 data_time: 0.063576 memory: 7326 loss_kpt: 0.000611 acc_pose: 0.836833 loss: 0.000611 2022/10/20 14:20:53 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:21:11 - mmengine - INFO - Epoch(train) [102][50/586] lr: 5.000000e-04 eta: 3:59:54 time: 0.353489 data_time: 0.036715 memory: 7326 loss_kpt: 0.000597 acc_pose: 0.813755 loss: 0.000597 2022/10/20 14:21:29 - mmengine - INFO - Epoch(train) [102][100/586] lr: 5.000000e-04 eta: 3:59:50 time: 0.369176 data_time: 0.102025 memory: 7326 loss_kpt: 0.000602 acc_pose: 0.847669 loss: 0.000602 2022/10/20 14:21:47 - mmengine - INFO - Epoch(train) [102][150/586] lr: 5.000000e-04 eta: 3:59:46 time: 0.349248 data_time: 0.028553 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.873336 loss: 0.000601 2022/10/20 14:22:04 - mmengine - INFO - Epoch(train) [102][200/586] lr: 5.000000e-04 eta: 3:59:41 time: 0.340915 data_time: 0.073281 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.902510 loss: 0.000590 2022/10/20 14:22:22 - mmengine - INFO - Epoch(train) [102][250/586] lr: 5.000000e-04 eta: 3:59:37 time: 0.365536 data_time: 0.024769 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.856812 loss: 0.000593 2022/10/20 14:22:37 - mmengine - INFO - Epoch(train) [102][300/586] lr: 5.000000e-04 eta: 3:59:29 time: 0.291015 data_time: 0.028709 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.831040 loss: 0.000612 2022/10/20 14:22:54 - mmengine - INFO - Epoch(train) [102][350/586] lr: 5.000000e-04 eta: 3:59:24 time: 0.344768 data_time: 0.027152 memory: 7326 loss_kpt: 0.000588 acc_pose: 0.815370 loss: 0.000588 2022/10/20 14:23:10 - mmengine - INFO - Epoch(train) [102][400/586] lr: 5.000000e-04 eta: 3:59:18 time: 0.324185 data_time: 0.025006 memory: 7326 loss_kpt: 0.000600 acc_pose: 0.849784 loss: 0.000600 2022/10/20 14:23:30 - mmengine - INFO - Epoch(train) [102][450/586] lr: 5.000000e-04 eta: 3:59:15 time: 0.390703 data_time: 0.023795 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.863978 loss: 0.000605 2022/10/20 14:23:46 - mmengine - INFO - Epoch(train) [102][500/586] lr: 5.000000e-04 eta: 3:59:10 time: 0.338060 data_time: 0.023112 memory: 7326 loss_kpt: 0.000607 acc_pose: 0.841063 loss: 0.000607 2022/10/20 14:24:03 - mmengine - INFO - Epoch(train) [102][550/586] lr: 5.000000e-04 eta: 3:59:05 time: 0.335207 data_time: 0.023680 memory: 7326 loss_kpt: 0.000608 acc_pose: 0.813835 loss: 0.000608 2022/10/20 14:24:16 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:24:34 - mmengine - INFO - Epoch(train) [103][50/586] lr: 5.000000e-04 eta: 3:58:44 time: 0.371923 data_time: 0.036215 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.828805 loss: 0.000605 2022/10/20 14:24:49 - mmengine - INFO - Epoch(train) [103][100/586] lr: 5.000000e-04 eta: 3:58:36 time: 0.295861 data_time: 0.024414 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.775865 loss: 0.000592 2022/10/20 14:25:05 - mmengine - INFO - Epoch(train) [103][150/586] lr: 5.000000e-04 eta: 3:58:30 time: 0.321258 data_time: 0.027079 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.816436 loss: 0.000595 2022/10/20 14:25:21 - mmengine - INFO - Epoch(train) [103][200/586] lr: 5.000000e-04 eta: 3:58:24 time: 0.320078 data_time: 0.034169 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.837449 loss: 0.000589 2022/10/20 14:25:30 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:25:35 - mmengine - INFO - Epoch(train) [103][250/586] lr: 5.000000e-04 eta: 3:58:15 time: 0.277865 data_time: 0.024593 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.877895 loss: 0.000589 2022/10/20 14:25:49 - mmengine - INFO - Epoch(train) [103][300/586] lr: 5.000000e-04 eta: 3:58:06 time: 0.267958 data_time: 0.027804 memory: 7326 loss_kpt: 0.000607 acc_pose: 0.866302 loss: 0.000607 2022/10/20 14:26:02 - mmengine - INFO - Epoch(train) [103][350/586] lr: 5.000000e-04 eta: 3:57:57 time: 0.266890 data_time: 0.028849 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.867478 loss: 0.000595 2022/10/20 14:26:15 - mmengine - INFO - Epoch(train) [103][400/586] lr: 5.000000e-04 eta: 3:57:47 time: 0.257987 data_time: 0.028700 memory: 7326 loss_kpt: 0.000606 acc_pose: 0.741189 loss: 0.000606 2022/10/20 14:26:27 - mmengine - INFO - Epoch(train) [103][450/586] lr: 5.000000e-04 eta: 3:57:37 time: 0.248196 data_time: 0.038799 memory: 7326 loss_kpt: 0.000599 acc_pose: 0.807980 loss: 0.000599 2022/10/20 14:26:41 - mmengine - INFO - Epoch(train) [103][500/586] lr: 5.000000e-04 eta: 3:57:28 time: 0.275613 data_time: 0.026009 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.878295 loss: 0.000593 2022/10/20 14:26:57 - mmengine - INFO - Epoch(train) [103][550/586] lr: 5.000000e-04 eta: 3:57:21 time: 0.321568 data_time: 0.028836 memory: 7326 loss_kpt: 0.000609 acc_pose: 0.869508 loss: 0.000609 2022/10/20 14:27:06 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:27:22 - mmengine - INFO - Epoch(train) [104][50/586] lr: 5.000000e-04 eta: 3:56:58 time: 0.314620 data_time: 0.034578 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.785837 loss: 0.000596 2022/10/20 14:27:43 - mmengine - INFO - Epoch(train) [104][100/586] lr: 5.000000e-04 eta: 3:56:56 time: 0.417025 data_time: 0.025107 memory: 7326 loss_kpt: 0.000603 acc_pose: 0.777156 loss: 0.000603 2022/10/20 14:27:59 - mmengine - INFO - Epoch(train) [104][150/586] lr: 5.000000e-04 eta: 3:56:50 time: 0.329288 data_time: 0.021970 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.831284 loss: 0.000584 2022/10/20 14:28:19 - mmengine - INFO - Epoch(train) [104][200/586] lr: 5.000000e-04 eta: 3:56:48 time: 0.399755 data_time: 0.025275 memory: 7326 loss_kpt: 0.000608 acc_pose: 0.894394 loss: 0.000608 2022/10/20 14:28:37 - mmengine - INFO - Epoch(train) [104][250/586] lr: 5.000000e-04 eta: 3:56:43 time: 0.343161 data_time: 0.022804 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.832423 loss: 0.000583 2022/10/20 14:28:53 - mmengine - INFO - Epoch(train) [104][300/586] lr: 5.000000e-04 eta: 3:56:37 time: 0.331638 data_time: 0.028352 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.896713 loss: 0.000594 2022/10/20 14:29:11 - mmengine - INFO - Epoch(train) [104][350/586] lr: 5.000000e-04 eta: 3:56:32 time: 0.364550 data_time: 0.024337 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.799443 loss: 0.000614 2022/10/20 14:29:26 - mmengine - INFO - Epoch(train) [104][400/586] lr: 5.000000e-04 eta: 3:56:24 time: 0.294181 data_time: 0.028616 memory: 7326 loss_kpt: 0.000607 acc_pose: 0.833692 loss: 0.000607 2022/10/20 14:29:42 - mmengine - INFO - Epoch(train) [104][450/586] lr: 5.000000e-04 eta: 3:56:18 time: 0.325090 data_time: 0.024701 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.877056 loss: 0.000605 2022/10/20 14:29:56 - mmengine - INFO - Epoch(train) [104][500/586] lr: 5.000000e-04 eta: 3:56:09 time: 0.276182 data_time: 0.027405 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.832240 loss: 0.000587 2022/10/20 14:30:11 - mmengine - INFO - Epoch(train) [104][550/586] lr: 5.000000e-04 eta: 3:56:01 time: 0.294884 data_time: 0.037224 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.848718 loss: 0.000566 2022/10/20 14:30:21 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:30:35 - mmengine - INFO - Epoch(train) [105][50/586] lr: 5.000000e-04 eta: 3:55:36 time: 0.279427 data_time: 0.033965 memory: 7326 loss_kpt: 0.000609 acc_pose: 0.851914 loss: 0.000609 2022/10/20 14:30:37 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:30:50 - mmengine - INFO - Epoch(train) [105][100/586] lr: 5.000000e-04 eta: 3:55:27 time: 0.289658 data_time: 0.025680 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.862950 loss: 0.000592 2022/10/20 14:31:06 - mmengine - INFO - Epoch(train) [105][150/586] lr: 5.000000e-04 eta: 3:55:20 time: 0.312636 data_time: 0.026583 memory: 7326 loss_kpt: 0.000604 acc_pose: 0.832065 loss: 0.000604 2022/10/20 14:31:21 - mmengine - INFO - Epoch(train) [105][200/586] lr: 5.000000e-04 eta: 3:55:13 time: 0.300094 data_time: 0.025454 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.875948 loss: 0.000612 2022/10/20 14:31:34 - mmengine - INFO - Epoch(train) [105][250/586] lr: 5.000000e-04 eta: 3:55:04 time: 0.278778 data_time: 0.027984 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.875141 loss: 0.000601 2022/10/20 14:31:50 - mmengine - INFO - Epoch(train) [105][300/586] lr: 5.000000e-04 eta: 3:54:57 time: 0.316877 data_time: 0.024957 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.710389 loss: 0.000586 2022/10/20 14:32:07 - mmengine - INFO - Epoch(train) [105][350/586] lr: 5.000000e-04 eta: 3:54:51 time: 0.333754 data_time: 0.026175 memory: 7326 loss_kpt: 0.000604 acc_pose: 0.854254 loss: 0.000604 2022/10/20 14:32:22 - mmengine - INFO - Epoch(train) [105][400/586] lr: 5.000000e-04 eta: 3:54:43 time: 0.295715 data_time: 0.026689 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.892204 loss: 0.000585 2022/10/20 14:32:34 - mmengine - INFO - Epoch(train) [105][450/586] lr: 5.000000e-04 eta: 3:54:33 time: 0.252424 data_time: 0.035135 memory: 7326 loss_kpt: 0.000604 acc_pose: 0.832726 loss: 0.000604 2022/10/20 14:32:49 - mmengine - INFO - Epoch(train) [105][500/586] lr: 5.000000e-04 eta: 3:54:24 time: 0.286976 data_time: 0.029064 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.775229 loss: 0.000612 2022/10/20 14:33:05 - mmengine - INFO - Epoch(train) [105][550/586] lr: 5.000000e-04 eta: 3:54:18 time: 0.330738 data_time: 0.043592 memory: 7326 loss_kpt: 0.000608 acc_pose: 0.802179 loss: 0.000608 2022/10/20 14:33:20 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:33:35 - mmengine - INFO - Epoch(train) [106][50/586] lr: 5.000000e-04 eta: 3:53:54 time: 0.304181 data_time: 0.060606 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.818469 loss: 0.000594 2022/10/20 14:33:49 - mmengine - INFO - Epoch(train) [106][100/586] lr: 5.000000e-04 eta: 3:53:45 time: 0.286369 data_time: 0.027888 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.856363 loss: 0.000614 2022/10/20 14:34:03 - mmengine - INFO - Epoch(train) [106][150/586] lr: 5.000000e-04 eta: 3:53:36 time: 0.278383 data_time: 0.024643 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.847121 loss: 0.000583 2022/10/20 14:34:17 - mmengine - INFO - Epoch(train) [106][200/586] lr: 5.000000e-04 eta: 3:53:27 time: 0.269672 data_time: 0.024828 memory: 7326 loss_kpt: 0.000609 acc_pose: 0.863756 loss: 0.000609 2022/10/20 14:34:33 - mmengine - INFO - Epoch(train) [106][250/586] lr: 5.000000e-04 eta: 3:53:20 time: 0.321370 data_time: 0.024359 memory: 7326 loss_kpt: 0.000581 acc_pose: 0.820570 loss: 0.000581 2022/10/20 14:34:50 - mmengine - INFO - Epoch(train) [106][300/586] lr: 5.000000e-04 eta: 3:53:15 time: 0.348737 data_time: 0.025406 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.748171 loss: 0.000601 2022/10/20 14:35:06 - mmengine - INFO - Epoch(train) [106][350/586] lr: 5.000000e-04 eta: 3:53:08 time: 0.317582 data_time: 0.025514 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.861667 loss: 0.000584 2022/10/20 14:35:23 - mmengine - INFO - Epoch(train) [106][400/586] lr: 5.000000e-04 eta: 3:53:02 time: 0.338593 data_time: 0.028525 memory: 7326 loss_kpt: 0.000600 acc_pose: 0.869256 loss: 0.000600 2022/10/20 14:35:39 - mmengine - INFO - Epoch(train) [106][450/586] lr: 5.000000e-04 eta: 3:52:54 time: 0.312711 data_time: 0.034845 memory: 7326 loss_kpt: 0.000600 acc_pose: 0.860685 loss: 0.000600 2022/10/20 14:35:46 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:35:57 - mmengine - INFO - Epoch(train) [106][500/586] lr: 5.000000e-04 eta: 3:52:49 time: 0.359553 data_time: 0.023518 memory: 7326 loss_kpt: 0.000600 acc_pose: 0.834139 loss: 0.000600 2022/10/20 14:36:16 - mmengine - INFO - Epoch(train) [106][550/586] lr: 5.000000e-04 eta: 3:52:46 time: 0.397699 data_time: 0.026832 memory: 7326 loss_kpt: 0.000598 acc_pose: 0.878765 loss: 0.000598 2022/10/20 14:36:30 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:36:52 - mmengine - INFO - Epoch(train) [107][50/586] lr: 5.000000e-04 eta: 3:52:29 time: 0.442375 data_time: 0.030208 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.831698 loss: 0.000614 2022/10/20 14:37:09 - mmengine - INFO - Epoch(train) [107][100/586] lr: 5.000000e-04 eta: 3:52:23 time: 0.345431 data_time: 0.024427 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.847470 loss: 0.000583 2022/10/20 14:37:26 - mmengine - INFO - Epoch(train) [107][150/586] lr: 5.000000e-04 eta: 3:52:17 time: 0.332932 data_time: 0.024813 memory: 7326 loss_kpt: 0.000598 acc_pose: 0.877678 loss: 0.000598 2022/10/20 14:37:44 - mmengine - INFO - Epoch(train) [107][200/586] lr: 5.000000e-04 eta: 3:52:12 time: 0.364984 data_time: 0.024633 memory: 7326 loss_kpt: 0.000582 acc_pose: 0.834846 loss: 0.000582 2022/10/20 14:37:57 - mmengine - INFO - Epoch(train) [107][250/586] lr: 5.000000e-04 eta: 3:52:02 time: 0.254261 data_time: 0.027234 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.825636 loss: 0.000585 2022/10/20 14:38:10 - mmengine - INFO - Epoch(train) [107][300/586] lr: 5.000000e-04 eta: 3:51:52 time: 0.275502 data_time: 0.026485 memory: 7326 loss_kpt: 0.000588 acc_pose: 0.844785 loss: 0.000588 2022/10/20 14:38:24 - mmengine - INFO - Epoch(train) [107][350/586] lr: 5.000000e-04 eta: 3:51:43 time: 0.278710 data_time: 0.035810 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.811449 loss: 0.000592 2022/10/20 14:38:37 - mmengine - INFO - Epoch(train) [107][400/586] lr: 5.000000e-04 eta: 3:51:33 time: 0.259603 data_time: 0.025667 memory: 7326 loss_kpt: 0.000578 acc_pose: 0.916012 loss: 0.000578 2022/10/20 14:38:52 - mmengine - INFO - Epoch(train) [107][450/586] lr: 5.000000e-04 eta: 3:51:24 time: 0.283854 data_time: 0.031377 memory: 7326 loss_kpt: 0.000604 acc_pose: 0.822858 loss: 0.000604 2022/10/20 14:39:05 - mmengine - INFO - Epoch(train) [107][500/586] lr: 5.000000e-04 eta: 3:51:15 time: 0.274115 data_time: 0.026074 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.892511 loss: 0.000594 2022/10/20 14:39:19 - mmengine - INFO - Epoch(train) [107][550/586] lr: 5.000000e-04 eta: 3:51:06 time: 0.270067 data_time: 0.025391 memory: 7326 loss_kpt: 0.000609 acc_pose: 0.844805 loss: 0.000609 2022/10/20 14:39:29 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:39:44 - mmengine - INFO - Epoch(train) [108][50/586] lr: 5.000000e-04 eta: 3:50:41 time: 0.302292 data_time: 0.050688 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.884471 loss: 0.000589 2022/10/20 14:40:00 - mmengine - INFO - Epoch(train) [108][100/586] lr: 5.000000e-04 eta: 3:50:34 time: 0.314026 data_time: 0.024837 memory: 7326 loss_kpt: 0.000600 acc_pose: 0.899631 loss: 0.000600 2022/10/20 14:40:22 - mmengine - INFO - Epoch(train) [108][150/586] lr: 5.000000e-04 eta: 3:50:33 time: 0.444522 data_time: 0.023619 memory: 7326 loss_kpt: 0.000588 acc_pose: 0.876733 loss: 0.000588 2022/10/20 14:40:44 - mmengine - INFO - Epoch(train) [108][200/586] lr: 5.000000e-04 eta: 3:50:31 time: 0.434456 data_time: 0.026340 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.833651 loss: 0.000594 2022/10/20 14:41:04 - mmengine - INFO - Epoch(train) [108][250/586] lr: 5.000000e-04 eta: 3:50:28 time: 0.413130 data_time: 0.022415 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.790173 loss: 0.000585 2022/10/20 14:41:29 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:41:30 - mmengine - INFO - Epoch(train) [108][300/586] lr: 5.000000e-04 eta: 3:50:30 time: 0.506740 data_time: 0.140890 memory: 7326 loss_kpt: 0.000608 acc_pose: 0.817567 loss: 0.000608 2022/10/20 14:41:51 - mmengine - INFO - Epoch(train) [108][350/586] lr: 5.000000e-04 eta: 3:50:28 time: 0.429513 data_time: 0.023511 memory: 7326 loss_kpt: 0.000604 acc_pose: 0.838935 loss: 0.000604 2022/10/20 14:42:12 - mmengine - INFO - Epoch(train) [108][400/586] lr: 5.000000e-04 eta: 3:50:25 time: 0.418726 data_time: 0.023501 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.832246 loss: 0.000593 2022/10/20 14:42:31 - mmengine - INFO - Epoch(train) [108][450/586] lr: 5.000000e-04 eta: 3:50:21 time: 0.381662 data_time: 0.026695 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.838631 loss: 0.000590 2022/10/20 14:42:52 - mmengine - INFO - Epoch(train) [108][500/586] lr: 5.000000e-04 eta: 3:50:19 time: 0.425474 data_time: 0.022083 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.861144 loss: 0.000595 2022/10/20 14:43:14 - mmengine - INFO - Epoch(train) [108][550/586] lr: 5.000000e-04 eta: 3:50:16 time: 0.427695 data_time: 0.024123 memory: 7326 loss_kpt: 0.000591 acc_pose: 0.836546 loss: 0.000591 2022/10/20 14:43:27 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:43:53 - mmengine - INFO - Epoch(train) [109][50/586] lr: 5.000000e-04 eta: 3:50:01 time: 0.499790 data_time: 0.028666 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.885256 loss: 0.000593 2022/10/20 14:44:12 - mmengine - INFO - Epoch(train) [109][100/586] lr: 5.000000e-04 eta: 3:49:58 time: 0.394273 data_time: 0.027098 memory: 7326 loss_kpt: 0.000612 acc_pose: 0.886788 loss: 0.000612 2022/10/20 14:44:33 - mmengine - INFO - Epoch(train) [109][150/586] lr: 5.000000e-04 eta: 3:49:55 time: 0.420511 data_time: 0.026114 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.844867 loss: 0.000593 2022/10/20 14:44:51 - mmengine - INFO - Epoch(train) [109][200/586] lr: 5.000000e-04 eta: 3:49:50 time: 0.363758 data_time: 0.024767 memory: 7326 loss_kpt: 0.000579 acc_pose: 0.828092 loss: 0.000579 2022/10/20 14:45:11 - mmengine - INFO - Epoch(train) [109][250/586] lr: 5.000000e-04 eta: 3:49:45 time: 0.391484 data_time: 0.022984 memory: 7326 loss_kpt: 0.000605 acc_pose: 0.840588 loss: 0.000605 2022/10/20 14:45:35 - mmengine - INFO - Epoch(train) [109][300/586] lr: 5.000000e-04 eta: 3:49:46 time: 0.483845 data_time: 0.034206 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.877380 loss: 0.000585 2022/10/20 14:46:00 - mmengine - INFO - Epoch(train) [109][350/586] lr: 5.000000e-04 eta: 3:49:46 time: 0.487723 data_time: 0.022850 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.820490 loss: 0.000596 2022/10/20 14:46:23 - mmengine - INFO - Epoch(train) [109][400/586] lr: 5.000000e-04 eta: 3:49:45 time: 0.459285 data_time: 0.029583 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.821157 loss: 0.000590 2022/10/20 14:46:48 - mmengine - INFO - Epoch(train) [109][450/586] lr: 5.000000e-04 eta: 3:49:47 time: 0.515591 data_time: 0.023382 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.805677 loss: 0.000587 2022/10/20 14:47:10 - mmengine - INFO - Epoch(train) [109][500/586] lr: 5.000000e-04 eta: 3:49:44 time: 0.427265 data_time: 0.033722 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.831296 loss: 0.000592 2022/10/20 14:47:36 - mmengine - INFO - Epoch(train) [109][550/586] lr: 5.000000e-04 eta: 3:49:46 time: 0.526191 data_time: 0.027580 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.863922 loss: 0.000593 2022/10/20 14:47:58 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:48:20 - mmengine - INFO - Epoch(train) [110][50/586] lr: 5.000000e-04 eta: 3:49:28 time: 0.439793 data_time: 0.029728 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.857857 loss: 0.000589 2022/10/20 14:48:42 - mmengine - INFO - Epoch(train) [110][100/586] lr: 5.000000e-04 eta: 3:49:26 time: 0.447814 data_time: 0.023977 memory: 7326 loss_kpt: 0.000577 acc_pose: 0.882798 loss: 0.000577 2022/10/20 14:48:54 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:49:03 - mmengine - INFO - Epoch(train) [110][150/586] lr: 5.000000e-04 eta: 3:49:23 time: 0.415949 data_time: 0.024034 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.891017 loss: 0.000592 2022/10/20 14:49:23 - mmengine - INFO - Epoch(train) [110][200/586] lr: 5.000000e-04 eta: 3:49:18 time: 0.389880 data_time: 0.023417 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.849802 loss: 0.000585 2022/10/20 14:49:34 - mmengine - INFO - Epoch(train) [110][250/586] lr: 5.000000e-04 eta: 3:49:07 time: 0.229020 data_time: 0.026318 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.896758 loss: 0.000587 2022/10/20 14:49:45 - mmengine - INFO - Epoch(train) [110][300/586] lr: 5.000000e-04 eta: 3:48:54 time: 0.222286 data_time: 0.027218 memory: 7326 loss_kpt: 0.000604 acc_pose: 0.821036 loss: 0.000604 2022/10/20 14:49:57 - mmengine - INFO - Epoch(train) [110][350/586] lr: 5.000000e-04 eta: 3:48:43 time: 0.230619 data_time: 0.025910 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.861206 loss: 0.000585 2022/10/20 14:50:09 - mmengine - INFO - Epoch(train) [110][400/586] lr: 5.000000e-04 eta: 3:48:31 time: 0.232687 data_time: 0.027961 memory: 7326 loss_kpt: 0.000598 acc_pose: 0.888578 loss: 0.000598 2022/10/20 14:50:20 - mmengine - INFO - Epoch(train) [110][450/586] lr: 5.000000e-04 eta: 3:48:19 time: 0.224776 data_time: 0.031170 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.853570 loss: 0.000586 2022/10/20 14:50:32 - mmengine - INFO - Epoch(train) [110][500/586] lr: 5.000000e-04 eta: 3:48:07 time: 0.235649 data_time: 0.027050 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.853063 loss: 0.000589 2022/10/20 14:50:43 - mmengine - INFO - Epoch(train) [110][550/586] lr: 5.000000e-04 eta: 3:47:56 time: 0.229282 data_time: 0.023633 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.835419 loss: 0.000594 2022/10/20 14:50:51 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:50:51 - mmengine - INFO - Saving checkpoint at 110 epochs 2022/10/20 14:51:01 - mmengine - INFO - Epoch(val) [110][50/407] eta: 0:00:42 time: 0.118647 data_time: 0.033781 memory: 7326 2022/10/20 14:51:07 - mmengine - INFO - Epoch(val) [110][100/407] eta: 0:00:34 time: 0.113967 data_time: 0.031518 memory: 1680 2022/10/20 14:51:12 - mmengine - INFO - Epoch(val) [110][150/407] eta: 0:00:28 time: 0.110419 data_time: 0.027337 memory: 1680 2022/10/20 14:51:19 - mmengine - INFO - Epoch(val) [110][200/407] eta: 0:00:26 time: 0.126037 data_time: 0.041048 memory: 1680 2022/10/20 14:51:24 - mmengine - INFO - Epoch(val) [110][250/407] eta: 0:00:17 time: 0.108352 data_time: 0.026515 memory: 1680 2022/10/20 14:51:30 - mmengine - INFO - Epoch(val) [110][300/407] eta: 0:00:13 time: 0.125532 data_time: 0.042960 memory: 1680 2022/10/20 14:51:36 - mmengine - INFO - Epoch(val) [110][350/407] eta: 0:00:06 time: 0.118730 data_time: 0.035901 memory: 1680 2022/10/20 14:51:42 - mmengine - INFO - Epoch(val) [110][400/407] eta: 0:00:00 time: 0.110123 data_time: 0.031373 memory: 1680 2022/10/20 14:52:14 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 14:52:27 - mmengine - INFO - Epoch(val) [110][407/407] coco/AP: 0.725255 coco/AP .5: 0.898459 coco/AP .75: 0.804716 coco/AP (M): 0.688584 coco/AP (L): 0.792454 coco/AR: 0.780337 coco/AR .5: 0.936555 coco/AR .75: 0.850441 coco/AR (M): 0.736793 coco/AR (L): 0.843181 2022/10/20 14:52:39 - mmengine - INFO - Epoch(train) [111][50/586] lr: 5.000000e-04 eta: 3:47:28 time: 0.238734 data_time: 0.036617 memory: 7326 loss_kpt: 0.000591 acc_pose: 0.823859 loss: 0.000591 2022/10/20 14:52:51 - mmengine - INFO - Epoch(train) [111][100/586] lr: 5.000000e-04 eta: 3:47:16 time: 0.226506 data_time: 0.031792 memory: 7326 loss_kpt: 0.000619 acc_pose: 0.841948 loss: 0.000619 2022/10/20 14:53:02 - mmengine - INFO - Epoch(train) [111][150/586] lr: 5.000000e-04 eta: 3:47:04 time: 0.228483 data_time: 0.024884 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.848260 loss: 0.000568 2022/10/20 14:53:13 - mmengine - INFO - Epoch(train) [111][200/586] lr: 5.000000e-04 eta: 3:46:52 time: 0.227172 data_time: 0.026263 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.848940 loss: 0.000589 2022/10/20 14:53:25 - mmengine - INFO - Epoch(train) [111][250/586] lr: 5.000000e-04 eta: 3:46:40 time: 0.228094 data_time: 0.027506 memory: 7326 loss_kpt: 0.000598 acc_pose: 0.836339 loss: 0.000598 2022/10/20 14:53:37 - mmengine - INFO - Epoch(train) [111][300/586] lr: 5.000000e-04 eta: 3:46:29 time: 0.235849 data_time: 0.031586 memory: 7326 loss_kpt: 0.000598 acc_pose: 0.832695 loss: 0.000598 2022/10/20 14:53:48 - mmengine - INFO - Epoch(train) [111][350/586] lr: 5.000000e-04 eta: 3:46:17 time: 0.225932 data_time: 0.025158 memory: 7326 loss_kpt: 0.000588 acc_pose: 0.826379 loss: 0.000588 2022/10/20 14:54:00 - mmengine - INFO - Epoch(train) [111][400/586] lr: 5.000000e-04 eta: 3:46:05 time: 0.232689 data_time: 0.027033 memory: 7326 loss_kpt: 0.000599 acc_pose: 0.862262 loss: 0.000599 2022/10/20 14:54:11 - mmengine - INFO - Epoch(train) [111][450/586] lr: 5.000000e-04 eta: 3:45:54 time: 0.232232 data_time: 0.029653 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.885293 loss: 0.000594 2022/10/20 14:54:23 - mmengine - INFO - Epoch(train) [111][500/586] lr: 5.000000e-04 eta: 3:45:42 time: 0.231356 data_time: 0.028005 memory: 7326 loss_kpt: 0.000597 acc_pose: 0.877367 loss: 0.000597 2022/10/20 14:54:32 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:54:34 - mmengine - INFO - Epoch(train) [111][550/586] lr: 5.000000e-04 eta: 3:45:30 time: 0.225077 data_time: 0.027726 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.841402 loss: 0.000610 2022/10/20 14:54:42 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:54:54 - mmengine - INFO - Epoch(train) [112][50/586] lr: 5.000000e-04 eta: 3:45:03 time: 0.241407 data_time: 0.030769 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.875150 loss: 0.000594 2022/10/20 14:55:06 - mmengine - INFO - Epoch(train) [112][100/586] lr: 5.000000e-04 eta: 3:44:51 time: 0.234186 data_time: 0.026735 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.835757 loss: 0.000594 2022/10/20 14:55:17 - mmengine - INFO - Epoch(train) [112][150/586] lr: 5.000000e-04 eta: 3:44:39 time: 0.225114 data_time: 0.026272 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.925823 loss: 0.000596 2022/10/20 14:55:29 - mmengine - INFO - Epoch(train) [112][200/586] lr: 5.000000e-04 eta: 3:44:27 time: 0.223292 data_time: 0.027454 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.882081 loss: 0.000584 2022/10/20 14:55:40 - mmengine - INFO - Epoch(train) [112][250/586] lr: 5.000000e-04 eta: 3:44:15 time: 0.228677 data_time: 0.030230 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.874859 loss: 0.000596 2022/10/20 14:55:51 - mmengine - INFO - Epoch(train) [112][300/586] lr: 5.000000e-04 eta: 3:44:03 time: 0.224871 data_time: 0.026613 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.802337 loss: 0.000594 2022/10/20 14:56:02 - mmengine - INFO - Epoch(train) [112][350/586] lr: 5.000000e-04 eta: 3:43:51 time: 0.225052 data_time: 0.024591 memory: 7326 loss_kpt: 0.000577 acc_pose: 0.776653 loss: 0.000577 2022/10/20 14:56:14 - mmengine - INFO - Epoch(train) [112][400/586] lr: 5.000000e-04 eta: 3:43:39 time: 0.225746 data_time: 0.024158 memory: 7326 loss_kpt: 0.000608 acc_pose: 0.867909 loss: 0.000608 2022/10/20 14:56:25 - mmengine - INFO - Epoch(train) [112][450/586] lr: 5.000000e-04 eta: 3:43:28 time: 0.232178 data_time: 0.029948 memory: 7326 loss_kpt: 0.000576 acc_pose: 0.828444 loss: 0.000576 2022/10/20 14:56:37 - mmengine - INFO - Epoch(train) [112][500/586] lr: 5.000000e-04 eta: 3:43:16 time: 0.224304 data_time: 0.024091 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.876580 loss: 0.000590 2022/10/20 14:56:48 - mmengine - INFO - Epoch(train) [112][550/586] lr: 5.000000e-04 eta: 3:43:04 time: 0.234294 data_time: 0.027155 memory: 7326 loss_kpt: 0.000616 acc_pose: 0.833090 loss: 0.000616 2022/10/20 14:56:56 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:57:08 - mmengine - INFO - Epoch(train) [113][50/586] lr: 5.000000e-04 eta: 3:42:36 time: 0.230408 data_time: 0.030411 memory: 7326 loss_kpt: 0.000597 acc_pose: 0.848317 loss: 0.000597 2022/10/20 14:57:20 - mmengine - INFO - Epoch(train) [113][100/586] lr: 5.000000e-04 eta: 3:42:25 time: 0.230637 data_time: 0.027330 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.856157 loss: 0.000593 2022/10/20 14:57:31 - mmengine - INFO - Epoch(train) [113][150/586] lr: 5.000000e-04 eta: 3:42:13 time: 0.220857 data_time: 0.025830 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.883931 loss: 0.000595 2022/10/20 14:57:42 - mmengine - INFO - Epoch(train) [113][200/586] lr: 5.000000e-04 eta: 3:42:01 time: 0.224156 data_time: 0.022384 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.866921 loss: 0.000570 2022/10/20 14:57:53 - mmengine - INFO - Epoch(train) [113][250/586] lr: 5.000000e-04 eta: 3:41:49 time: 0.232171 data_time: 0.027793 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.834710 loss: 0.000592 2022/10/20 14:58:05 - mmengine - INFO - Epoch(train) [113][300/586] lr: 5.000000e-04 eta: 3:41:37 time: 0.234236 data_time: 0.024319 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.781588 loss: 0.000584 2022/10/20 14:58:17 - mmengine - INFO - Epoch(train) [113][350/586] lr: 5.000000e-04 eta: 3:41:26 time: 0.234384 data_time: 0.031145 memory: 7326 loss_kpt: 0.000598 acc_pose: 0.849193 loss: 0.000598 2022/10/20 14:58:21 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:58:29 - mmengine - INFO - Epoch(train) [113][400/586] lr: 5.000000e-04 eta: 3:41:14 time: 0.237985 data_time: 0.027511 memory: 7326 loss_kpt: 0.000582 acc_pose: 0.847697 loss: 0.000582 2022/10/20 14:58:40 - mmengine - INFO - Epoch(train) [113][450/586] lr: 5.000000e-04 eta: 3:41:03 time: 0.231375 data_time: 0.030091 memory: 7326 loss_kpt: 0.000588 acc_pose: 0.874812 loss: 0.000588 2022/10/20 14:58:52 - mmengine - INFO - Epoch(train) [113][500/586] lr: 5.000000e-04 eta: 3:40:51 time: 0.229295 data_time: 0.027155 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.847448 loss: 0.000573 2022/10/20 14:59:04 - mmengine - INFO - Epoch(train) [113][550/586] lr: 5.000000e-04 eta: 3:40:39 time: 0.235635 data_time: 0.028228 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.786304 loss: 0.000585 2022/10/20 14:59:12 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 14:59:24 - mmengine - INFO - Epoch(train) [114][50/586] lr: 5.000000e-04 eta: 3:40:13 time: 0.249287 data_time: 0.035355 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.864850 loss: 0.000589 2022/10/20 14:59:36 - mmengine - INFO - Epoch(train) [114][100/586] lr: 5.000000e-04 eta: 3:40:01 time: 0.229761 data_time: 0.028694 memory: 7326 loss_kpt: 0.000597 acc_pose: 0.813431 loss: 0.000597 2022/10/20 14:59:47 - mmengine - INFO - Epoch(train) [114][150/586] lr: 5.000000e-04 eta: 3:39:49 time: 0.223724 data_time: 0.027871 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.836809 loss: 0.000568 2022/10/20 14:59:59 - mmengine - INFO - Epoch(train) [114][200/586] lr: 5.000000e-04 eta: 3:39:38 time: 0.239317 data_time: 0.032744 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.873521 loss: 0.000583 2022/10/20 15:00:12 - mmengine - INFO - Epoch(train) [114][250/586] lr: 5.000000e-04 eta: 3:39:27 time: 0.262237 data_time: 0.029760 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.886796 loss: 0.000601 2022/10/20 15:00:24 - mmengine - INFO - Epoch(train) [114][300/586] lr: 5.000000e-04 eta: 3:39:16 time: 0.237861 data_time: 0.030832 memory: 7326 loss_kpt: 0.000578 acc_pose: 0.881166 loss: 0.000578 2022/10/20 15:00:36 - mmengine - INFO - Epoch(train) [114][350/586] lr: 5.000000e-04 eta: 3:39:04 time: 0.232379 data_time: 0.030186 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.891660 loss: 0.000590 2022/10/20 15:00:47 - mmengine - INFO - Epoch(train) [114][400/586] lr: 5.000000e-04 eta: 3:38:53 time: 0.236010 data_time: 0.026421 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.804307 loss: 0.000572 2022/10/20 15:00:59 - mmengine - INFO - Epoch(train) [114][450/586] lr: 5.000000e-04 eta: 3:38:42 time: 0.240830 data_time: 0.034993 memory: 7326 loss_kpt: 0.000599 acc_pose: 0.823869 loss: 0.000599 2022/10/20 15:01:12 - mmengine - INFO - Epoch(train) [114][500/586] lr: 5.000000e-04 eta: 3:38:30 time: 0.244612 data_time: 0.038854 memory: 7326 loss_kpt: 0.000614 acc_pose: 0.871917 loss: 0.000614 2022/10/20 15:01:24 - mmengine - INFO - Epoch(train) [114][550/586] lr: 5.000000e-04 eta: 3:38:19 time: 0.240326 data_time: 0.030355 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.800801 loss: 0.000593 2022/10/20 15:01:32 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:01:44 - mmengine - INFO - Epoch(train) [115][50/586] lr: 5.000000e-04 eta: 3:37:52 time: 0.243459 data_time: 0.034669 memory: 7326 loss_kpt: 0.000578 acc_pose: 0.864434 loss: 0.000578 2022/10/20 15:01:56 - mmengine - INFO - Epoch(train) [115][100/586] lr: 5.000000e-04 eta: 3:37:41 time: 0.241526 data_time: 0.029852 memory: 7326 loss_kpt: 0.000599 acc_pose: 0.893677 loss: 0.000599 2022/10/20 15:02:09 - mmengine - INFO - Epoch(train) [115][150/586] lr: 5.000000e-04 eta: 3:37:31 time: 0.271944 data_time: 0.029242 memory: 7326 loss_kpt: 0.000601 acc_pose: 0.848984 loss: 0.000601 2022/10/20 15:02:26 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:02:27 - mmengine - INFO - Epoch(train) [115][200/586] lr: 5.000000e-04 eta: 3:37:25 time: 0.351762 data_time: 0.048405 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.789685 loss: 0.000572 2022/10/20 15:02:40 - mmengine - INFO - Epoch(train) [115][250/586] lr: 5.000000e-04 eta: 3:37:14 time: 0.252984 data_time: 0.028497 memory: 7326 loss_kpt: 0.000578 acc_pose: 0.920015 loss: 0.000578 2022/10/20 15:02:52 - mmengine - INFO - Epoch(train) [115][300/586] lr: 5.000000e-04 eta: 3:37:03 time: 0.250559 data_time: 0.032715 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.821442 loss: 0.000585 2022/10/20 15:03:05 - mmengine - INFO - Epoch(train) [115][350/586] lr: 5.000000e-04 eta: 3:36:52 time: 0.248219 data_time: 0.036985 memory: 7326 loss_kpt: 0.000606 acc_pose: 0.845112 loss: 0.000606 2022/10/20 15:03:17 - mmengine - INFO - Epoch(train) [115][400/586] lr: 5.000000e-04 eta: 3:36:41 time: 0.241094 data_time: 0.036958 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.862749 loss: 0.000564 2022/10/20 15:03:30 - mmengine - INFO - Epoch(train) [115][450/586] lr: 5.000000e-04 eta: 3:36:31 time: 0.269509 data_time: 0.027074 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.857224 loss: 0.000571 2022/10/20 15:03:44 - mmengine - INFO - Epoch(train) [115][500/586] lr: 5.000000e-04 eta: 3:36:21 time: 0.273108 data_time: 0.076865 memory: 7326 loss_kpt: 0.000580 acc_pose: 0.889138 loss: 0.000580 2022/10/20 15:03:57 - mmengine - INFO - Epoch(train) [115][550/586] lr: 5.000000e-04 eta: 3:36:10 time: 0.254203 data_time: 0.037259 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.749917 loss: 0.000583 2022/10/20 15:04:06 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:04:20 - mmengine - INFO - Epoch(train) [116][50/586] lr: 5.000000e-04 eta: 3:35:45 time: 0.288701 data_time: 0.065360 memory: 7326 loss_kpt: 0.000597 acc_pose: 0.868540 loss: 0.000597 2022/10/20 15:04:34 - mmengine - INFO - Epoch(train) [116][100/586] lr: 5.000000e-04 eta: 3:35:36 time: 0.282771 data_time: 0.033965 memory: 7326 loss_kpt: 0.000582 acc_pose: 0.913076 loss: 0.000582 2022/10/20 15:04:50 - mmengine - INFO - Epoch(train) [116][150/586] lr: 5.000000e-04 eta: 3:35:27 time: 0.317158 data_time: 0.028439 memory: 7326 loss_kpt: 0.000576 acc_pose: 0.801231 loss: 0.000576 2022/10/20 15:05:05 - mmengine - INFO - Epoch(train) [116][200/586] lr: 5.000000e-04 eta: 3:35:18 time: 0.291785 data_time: 0.027658 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.827755 loss: 0.000586 2022/10/20 15:05:18 - mmengine - INFO - Epoch(train) [116][250/586] lr: 5.000000e-04 eta: 3:35:08 time: 0.271954 data_time: 0.056120 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.839335 loss: 0.000572 2022/10/20 15:05:31 - mmengine - INFO - Epoch(train) [116][300/586] lr: 5.000000e-04 eta: 3:34:58 time: 0.260350 data_time: 0.060178 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.843765 loss: 0.000596 2022/10/20 15:05:49 - mmengine - INFO - Epoch(train) [116][350/586] lr: 5.000000e-04 eta: 3:34:51 time: 0.346785 data_time: 0.128245 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.900259 loss: 0.000573 2022/10/20 15:06:02 - mmengine - INFO - Epoch(train) [116][400/586] lr: 5.000000e-04 eta: 3:34:41 time: 0.271612 data_time: 0.048760 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.856612 loss: 0.000570 2022/10/20 15:06:15 - mmengine - INFO - Epoch(train) [116][450/586] lr: 5.000000e-04 eta: 3:34:30 time: 0.252993 data_time: 0.036333 memory: 7326 loss_kpt: 0.000607 acc_pose: 0.822549 loss: 0.000607 2022/10/20 15:06:29 - mmengine - INFO - Epoch(train) [116][500/586] lr: 5.000000e-04 eta: 3:34:20 time: 0.288675 data_time: 0.092168 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.829202 loss: 0.000575 2022/10/20 15:06:44 - mmengine - INFO - Epoch(train) [116][550/586] lr: 5.000000e-04 eta: 3:34:11 time: 0.288152 data_time: 0.056123 memory: 7326 loss_kpt: 0.000580 acc_pose: 0.825414 loss: 0.000580 2022/10/20 15:06:55 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:07:04 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:07:11 - mmengine - INFO - Epoch(train) [117][50/586] lr: 5.000000e-04 eta: 3:33:48 time: 0.333572 data_time: 0.089820 memory: 7326 loss_kpt: 0.000580 acc_pose: 0.824112 loss: 0.000580 2022/10/20 15:07:30 - mmengine - INFO - Epoch(train) [117][100/586] lr: 5.000000e-04 eta: 3:33:42 time: 0.379930 data_time: 0.177930 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.806138 loss: 0.000571 2022/10/20 15:07:50 - mmengine - INFO - Epoch(train) [117][150/586] lr: 5.000000e-04 eta: 3:33:38 time: 0.403005 data_time: 0.128453 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.860030 loss: 0.000563 2022/10/20 15:08:07 - mmengine - INFO - Epoch(train) [117][200/586] lr: 5.000000e-04 eta: 3:33:30 time: 0.333602 data_time: 0.030275 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.889182 loss: 0.000592 2022/10/20 15:08:25 - mmengine - INFO - Epoch(train) [117][250/586] lr: 5.000000e-04 eta: 3:33:23 time: 0.349739 data_time: 0.043896 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.868500 loss: 0.000584 2022/10/20 15:08:38 - mmengine - INFO - Epoch(train) [117][300/586] lr: 5.000000e-04 eta: 3:33:13 time: 0.267513 data_time: 0.032846 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.826157 loss: 0.000593 2022/10/20 15:08:55 - mmengine - INFO - Epoch(train) [117][350/586] lr: 5.000000e-04 eta: 3:33:05 time: 0.329033 data_time: 0.035224 memory: 7326 loss_kpt: 0.000577 acc_pose: 0.878463 loss: 0.000577 2022/10/20 15:09:12 - mmengine - INFO - Epoch(train) [117][400/586] lr: 5.000000e-04 eta: 3:32:58 time: 0.347066 data_time: 0.027589 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.907562 loss: 0.000575 2022/10/20 15:09:27 - mmengine - INFO - Epoch(train) [117][450/586] lr: 5.000000e-04 eta: 3:32:48 time: 0.295380 data_time: 0.032217 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.886985 loss: 0.000575 2022/10/20 15:09:42 - mmengine - INFO - Epoch(train) [117][500/586] lr: 5.000000e-04 eta: 3:32:39 time: 0.298554 data_time: 0.029437 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.800142 loss: 0.000593 2022/10/20 15:10:00 - mmengine - INFO - Epoch(train) [117][550/586] lr: 5.000000e-04 eta: 3:32:33 time: 0.360924 data_time: 0.028488 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.834395 loss: 0.000571 2022/10/20 15:10:11 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:10:32 - mmengine - INFO - Epoch(train) [118][50/586] lr: 5.000000e-04 eta: 3:32:13 time: 0.403758 data_time: 0.047382 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.824628 loss: 0.000575 2022/10/20 15:10:53 - mmengine - INFO - Epoch(train) [118][100/586] lr: 5.000000e-04 eta: 3:32:09 time: 0.435351 data_time: 0.030578 memory: 7326 loss_kpt: 0.000580 acc_pose: 0.890085 loss: 0.000580 2022/10/20 15:11:18 - mmengine - INFO - Epoch(train) [118][150/586] lr: 5.000000e-04 eta: 3:32:07 time: 0.488354 data_time: 0.024934 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.885079 loss: 0.000583 2022/10/20 15:11:39 - mmengine - INFO - Epoch(train) [118][200/586] lr: 5.000000e-04 eta: 3:32:03 time: 0.427665 data_time: 0.070256 memory: 7326 loss_kpt: 0.000582 acc_pose: 0.859260 loss: 0.000582 2022/10/20 15:12:00 - mmengine - INFO - Epoch(train) [118][250/586] lr: 5.000000e-04 eta: 3:31:59 time: 0.424892 data_time: 0.039156 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.857388 loss: 0.000596 2022/10/20 15:12:22 - mmengine - INFO - Epoch(train) [118][300/586] lr: 5.000000e-04 eta: 3:31:55 time: 0.437746 data_time: 0.097776 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.810561 loss: 0.000586 2022/10/20 15:12:42 - mmengine - INFO - Epoch(train) [118][350/586] lr: 5.000000e-04 eta: 3:31:50 time: 0.395904 data_time: 0.161840 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.852391 loss: 0.000583 2022/10/20 15:13:08 - mmengine - INFO - Epoch(train) [118][400/586] lr: 5.000000e-04 eta: 3:31:49 time: 0.515370 data_time: 0.273442 memory: 7326 loss_kpt: 0.000576 acc_pose: 0.872394 loss: 0.000576 2022/10/20 15:13:24 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:13:29 - mmengine - INFO - Epoch(train) [118][450/586] lr: 5.000000e-04 eta: 3:31:45 time: 0.421366 data_time: 0.143053 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.769440 loss: 0.000584 2022/10/20 15:13:53 - mmengine - INFO - Epoch(train) [118][500/586] lr: 5.000000e-04 eta: 3:31:43 time: 0.484552 data_time: 0.024025 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.886206 loss: 0.000594 2022/10/20 15:14:21 - mmengine - INFO - Epoch(train) [118][550/586] lr: 5.000000e-04 eta: 3:31:44 time: 0.557358 data_time: 0.023268 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.852555 loss: 0.000564 2022/10/20 15:14:37 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:15:07 - mmengine - INFO - Epoch(train) [119][50/586] lr: 5.000000e-04 eta: 3:31:30 time: 0.585726 data_time: 0.113742 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.837565 loss: 0.000574 2022/10/20 15:15:29 - mmengine - INFO - Epoch(train) [119][100/586] lr: 5.000000e-04 eta: 3:31:27 time: 0.448857 data_time: 0.060000 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.908741 loss: 0.000589 2022/10/20 15:16:08 - mmengine - INFO - Epoch(train) [119][150/586] lr: 5.000000e-04 eta: 3:31:36 time: 0.782094 data_time: 0.080271 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.834943 loss: 0.000568 2022/10/20 15:16:37 - mmengine - INFO - Epoch(train) [119][200/586] lr: 5.000000e-04 eta: 3:31:38 time: 0.583292 data_time: 0.167339 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.853271 loss: 0.000593 2022/10/20 15:17:03 - mmengine - INFO - Epoch(train) [119][250/586] lr: 5.000000e-04 eta: 3:31:37 time: 0.516331 data_time: 0.193653 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.885515 loss: 0.000594 2022/10/20 15:17:28 - mmengine - INFO - Epoch(train) [119][300/586] lr: 5.000000e-04 eta: 3:31:35 time: 0.504468 data_time: 0.187117 memory: 7326 loss_kpt: 0.000581 acc_pose: 0.884062 loss: 0.000581 2022/10/20 15:17:50 - mmengine - INFO - Epoch(train) [119][350/586] lr: 5.000000e-04 eta: 3:31:31 time: 0.429976 data_time: 0.053549 memory: 7326 loss_kpt: 0.000580 acc_pose: 0.847384 loss: 0.000580 2022/10/20 15:18:20 - mmengine - INFO - Epoch(train) [119][400/586] lr: 5.000000e-04 eta: 3:31:33 time: 0.593162 data_time: 0.046289 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.814246 loss: 0.000587 2022/10/20 15:18:49 - mmengine - INFO - Epoch(train) [119][450/586] lr: 5.000000e-04 eta: 3:31:34 time: 0.580581 data_time: 0.024656 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.814870 loss: 0.000586 2022/10/20 15:19:33 - mmengine - INFO - Epoch(train) [119][500/586] lr: 5.000000e-04 eta: 3:31:47 time: 0.879349 data_time: 0.043217 memory: 7326 loss_kpt: 0.000578 acc_pose: 0.868104 loss: 0.000578 2022/10/20 15:20:37 - mmengine - INFO - Epoch(train) [119][550/586] lr: 5.000000e-04 eta: 3:32:15 time: 1.292701 data_time: 0.023950 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.789430 loss: 0.000574 2022/10/20 15:21:09 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:21:41 - mmengine - INFO - Epoch(train) [120][50/586] lr: 5.000000e-04 eta: 3:32:03 time: 0.634873 data_time: 0.213335 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.821079 loss: 0.000594 2022/10/20 15:22:05 - mmengine - INFO - Epoch(train) [120][100/586] lr: 5.000000e-04 eta: 3:32:01 time: 0.488762 data_time: 0.138474 memory: 7326 loss_kpt: 0.000578 acc_pose: 0.864747 loss: 0.000578 2022/10/20 15:22:35 - mmengine - INFO - Epoch(train) [120][150/586] lr: 5.000000e-04 eta: 3:32:03 time: 0.596232 data_time: 0.177544 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.861780 loss: 0.000583 2022/10/20 15:22:52 - mmengine - INFO - Epoch(train) [120][200/586] lr: 5.000000e-04 eta: 3:31:54 time: 0.336452 data_time: 0.032665 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.808750 loss: 0.000593 2022/10/20 15:23:09 - mmengine - INFO - Epoch(train) [120][250/586] lr: 5.000000e-04 eta: 3:31:46 time: 0.332244 data_time: 0.030658 memory: 7326 loss_kpt: 0.000579 acc_pose: 0.867065 loss: 0.000579 2022/10/20 15:23:17 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:23:35 - mmengine - INFO - Epoch(train) [120][300/586] lr: 5.000000e-04 eta: 3:31:45 time: 0.524114 data_time: 0.024398 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.847147 loss: 0.000575 2022/10/20 15:24:02 - mmengine - INFO - Epoch(train) [120][350/586] lr: 5.000000e-04 eta: 3:31:44 time: 0.541758 data_time: 0.031265 memory: 7326 loss_kpt: 0.000597 acc_pose: 0.828384 loss: 0.000597 2022/10/20 15:24:30 - mmengine - INFO - Epoch(train) [120][400/586] lr: 5.000000e-04 eta: 3:31:44 time: 0.566001 data_time: 0.094633 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.885688 loss: 0.000594 2022/10/20 15:24:43 - mmengine - INFO - Epoch(train) [120][450/586] lr: 5.000000e-04 eta: 3:31:33 time: 0.244700 data_time: 0.025936 memory: 7326 loss_kpt: 0.000588 acc_pose: 0.825699 loss: 0.000588 2022/10/20 15:24:59 - mmengine - INFO - Epoch(train) [120][500/586] lr: 5.000000e-04 eta: 3:31:24 time: 0.335369 data_time: 0.049736 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.844153 loss: 0.000583 2022/10/20 15:25:17 - mmengine - INFO - Epoch(train) [120][550/586] lr: 5.000000e-04 eta: 3:31:16 time: 0.349768 data_time: 0.029586 memory: 7326 loss_kpt: 0.000569 acc_pose: 0.881285 loss: 0.000569 2022/10/20 15:25:31 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:25:31 - mmengine - INFO - Saving checkpoint at 120 epochs 2022/10/20 15:25:43 - mmengine - INFO - Epoch(val) [120][50/407] eta: 0:00:52 time: 0.146587 data_time: 0.060779 memory: 7326 2022/10/20 15:25:53 - mmengine - INFO - Epoch(val) [120][100/407] eta: 0:00:58 time: 0.191120 data_time: 0.111051 memory: 1680 2022/10/20 15:26:00 - mmengine - INFO - Epoch(val) [120][150/407] eta: 0:00:40 time: 0.159518 data_time: 0.082402 memory: 1680 2022/10/20 15:26:10 - mmengine - INFO - Epoch(val) [120][200/407] eta: 0:00:39 time: 0.190920 data_time: 0.113042 memory: 1680 2022/10/20 15:26:20 - mmengine - INFO - Epoch(val) [120][250/407] eta: 0:00:31 time: 0.198563 data_time: 0.118085 memory: 1680 2022/10/20 15:26:27 - mmengine - INFO - Epoch(val) [120][300/407] eta: 0:00:14 time: 0.133890 data_time: 0.054905 memory: 1680 2022/10/20 15:26:40 - mmengine - INFO - Epoch(val) [120][350/407] eta: 0:00:15 time: 0.270234 data_time: 0.190846 memory: 1680 2022/10/20 15:26:48 - mmengine - INFO - Epoch(val) [120][400/407] eta: 0:00:01 time: 0.150625 data_time: 0.072719 memory: 1680 2022/10/20 15:27:21 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 15:27:34 - mmengine - INFO - Epoch(val) [120][407/407] coco/AP: 0.727426 coco/AP .5: 0.900961 coco/AP .75: 0.802495 coco/AP (M): 0.690325 coco/AP (L): 0.794246 coco/AR: 0.782321 coco/AR .5: 0.939547 coco/AR .75: 0.847292 coco/AR (M): 0.739907 coco/AR (L): 0.843515 2022/10/20 15:27:34 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_100.pth is removed 2022/10/20 15:27:36 - mmengine - INFO - The best checkpoint with 0.7274 coco/AP at 120 epoch is saved to best_coco/AP_epoch_120.pth. 2022/10/20 15:27:54 - mmengine - INFO - Epoch(train) [121][50/586] lr: 5.000000e-04 eta: 3:30:54 time: 0.366092 data_time: 0.036230 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.877589 loss: 0.000590 2022/10/20 15:28:23 - mmengine - INFO - Epoch(train) [121][100/586] lr: 5.000000e-04 eta: 3:30:54 time: 0.571727 data_time: 0.028367 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.888353 loss: 0.000589 2022/10/20 15:28:46 - mmengine - INFO - Epoch(train) [121][150/586] lr: 5.000000e-04 eta: 3:30:50 time: 0.455414 data_time: 0.026739 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.882926 loss: 0.000583 2022/10/20 15:29:00 - mmengine - INFO - Epoch(train) [121][200/586] lr: 5.000000e-04 eta: 3:30:40 time: 0.280656 data_time: 0.041533 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.879174 loss: 0.000595 2022/10/20 15:29:21 - mmengine - INFO - Epoch(train) [121][250/586] lr: 5.000000e-04 eta: 3:30:34 time: 0.418191 data_time: 0.028536 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.831378 loss: 0.000590 2022/10/20 15:29:49 - mmengine - INFO - Epoch(train) [121][300/586] lr: 5.000000e-04 eta: 3:30:34 time: 0.557868 data_time: 0.036472 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.831486 loss: 0.000575 2022/10/20 15:30:12 - mmengine - INFO - Epoch(train) [121][350/586] lr: 5.000000e-04 eta: 3:30:30 time: 0.460713 data_time: 0.025578 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.822153 loss: 0.000575 2022/10/20 15:30:38 - mmengine - INFO - Epoch(train) [121][400/586] lr: 5.000000e-04 eta: 3:30:29 time: 0.528283 data_time: 0.276924 memory: 7326 loss_kpt: 0.000582 acc_pose: 0.821650 loss: 0.000582 2022/10/20 15:31:28 - mmengine - INFO - Epoch(train) [121][450/586] lr: 5.000000e-04 eta: 3:30:45 time: 1.005034 data_time: 0.250935 memory: 7326 loss_kpt: 0.000588 acc_pose: 0.815969 loss: 0.000588 2022/10/20 15:31:46 - mmengine - INFO - Epoch(train) [121][500/586] lr: 5.000000e-04 eta: 3:30:37 time: 0.363260 data_time: 0.029580 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.874638 loss: 0.000586 2022/10/20 15:32:33 - mmengine - INFO - Epoch(train) [121][550/586] lr: 5.000000e-04 eta: 3:30:50 time: 0.927667 data_time: 0.024830 memory: 7326 loss_kpt: 0.000591 acc_pose: 0.839531 loss: 0.000591 2022/10/20 15:34:27 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:34:50 - mmengine - INFO - Epoch(train) [122][50/586] lr: 5.000000e-04 eta: 3:30:31 time: 0.451152 data_time: 0.052458 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.877967 loss: 0.000595 2022/10/20 15:35:14 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:35:15 - mmengine - INFO - Epoch(train) [122][100/586] lr: 5.000000e-04 eta: 3:30:28 time: 0.506575 data_time: 0.065472 memory: 7326 loss_kpt: 0.000582 acc_pose: 0.919966 loss: 0.000582 2022/10/20 15:35:29 - mmengine - INFO - Epoch(train) [122][150/586] lr: 5.000000e-04 eta: 3:30:18 time: 0.285810 data_time: 0.024530 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.786006 loss: 0.000584 2022/10/20 15:35:55 - mmengine - INFO - Epoch(train) [122][200/586] lr: 5.000000e-04 eta: 3:30:15 time: 0.507221 data_time: 0.026467 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.859786 loss: 0.000575 2022/10/20 15:36:15 - mmengine - INFO - Epoch(train) [122][250/586] lr: 5.000000e-04 eta: 3:30:09 time: 0.393935 data_time: 0.026559 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.820131 loss: 0.000586 2022/10/20 15:36:35 - mmengine - INFO - Epoch(train) [122][300/586] lr: 5.000000e-04 eta: 3:30:03 time: 0.416897 data_time: 0.050149 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.846401 loss: 0.000571 2022/10/20 15:37:19 - mmengine - INFO - Epoch(train) [122][350/586] lr: 5.000000e-04 eta: 3:30:14 time: 0.880483 data_time: 0.118430 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.837114 loss: 0.000586 2022/10/20 15:37:36 - mmengine - INFO - Epoch(train) [122][400/586] lr: 5.000000e-04 eta: 3:30:05 time: 0.340725 data_time: 0.028648 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.844349 loss: 0.000573 2022/10/20 15:37:55 - mmengine - INFO - Epoch(train) [122][450/586] lr: 5.000000e-04 eta: 3:29:58 time: 0.373151 data_time: 0.035137 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.867589 loss: 0.000573 2022/10/20 15:38:17 - mmengine - INFO - Epoch(train) [122][500/586] lr: 5.000000e-04 eta: 3:29:53 time: 0.436695 data_time: 0.023885 memory: 7326 loss_kpt: 0.000577 acc_pose: 0.878417 loss: 0.000577 2022/10/20 15:38:42 - mmengine - INFO - Epoch(train) [122][550/586] lr: 5.000000e-04 eta: 3:29:50 time: 0.498616 data_time: 0.023816 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.870559 loss: 0.000592 2022/10/20 15:38:55 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:39:15 - mmengine - INFO - Epoch(train) [123][50/586] lr: 5.000000e-04 eta: 3:29:27 time: 0.384159 data_time: 0.061688 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.799800 loss: 0.000575 2022/10/20 15:39:35 - mmengine - INFO - Epoch(train) [123][100/586] lr: 5.000000e-04 eta: 3:29:21 time: 0.418943 data_time: 0.025211 memory: 7326 loss_kpt: 0.000603 acc_pose: 0.819369 loss: 0.000603 2022/10/20 15:40:09 - mmengine - INFO - Epoch(train) [123][150/586] lr: 5.000000e-04 eta: 3:29:25 time: 0.673255 data_time: 0.036912 memory: 7326 loss_kpt: 0.000576 acc_pose: 0.869187 loss: 0.000576 2022/10/20 15:40:27 - mmengine - INFO - Epoch(train) [123][200/586] lr: 5.000000e-04 eta: 3:29:17 time: 0.361824 data_time: 0.024942 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.850831 loss: 0.000594 2022/10/20 15:40:44 - mmengine - INFO - Epoch(train) [123][250/586] lr: 5.000000e-04 eta: 3:29:08 time: 0.342777 data_time: 0.029837 memory: 7326 loss_kpt: 0.000567 acc_pose: 0.893337 loss: 0.000567 2022/10/20 15:41:18 - mmengine - INFO - Epoch(train) [123][300/586] lr: 5.000000e-04 eta: 3:29:11 time: 0.673916 data_time: 0.024400 memory: 7326 loss_kpt: 0.000596 acc_pose: 0.811303 loss: 0.000596 2022/10/20 15:41:37 - mmengine - INFO - Epoch(train) [123][350/586] lr: 5.000000e-04 eta: 3:29:04 time: 0.378093 data_time: 0.045936 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.851293 loss: 0.000583 2022/10/20 15:41:59 - mmengine - INFO - Epoch(train) [123][400/586] lr: 5.000000e-04 eta: 3:28:58 time: 0.438641 data_time: 0.039548 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.879748 loss: 0.000575 2022/10/20 15:42:18 - mmengine - INFO - Epoch(train) [123][450/586] lr: 5.000000e-04 eta: 3:28:51 time: 0.383438 data_time: 0.054315 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.800319 loss: 0.000575 2022/10/20 15:42:45 - mmengine - INFO - Epoch(train) [123][500/586] lr: 5.000000e-04 eta: 3:28:49 time: 0.540568 data_time: 0.099987 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.816299 loss: 0.000584 2022/10/20 15:42:47 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:43:02 - mmengine - INFO - Epoch(train) [123][550/586] lr: 5.000000e-04 eta: 3:28:40 time: 0.327879 data_time: 0.027224 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.855261 loss: 0.000574 2022/10/20 15:43:16 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:43:33 - mmengine - INFO - Epoch(train) [124][50/586] lr: 5.000000e-04 eta: 3:28:16 time: 0.339225 data_time: 0.034514 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.841633 loss: 0.000583 2022/10/20 15:43:51 - mmengine - INFO - Epoch(train) [124][100/586] lr: 5.000000e-04 eta: 3:28:07 time: 0.356201 data_time: 0.032613 memory: 7326 loss_kpt: 0.000579 acc_pose: 0.848579 loss: 0.000579 2022/10/20 15:44:11 - mmengine - INFO - Epoch(train) [124][150/586] lr: 5.000000e-04 eta: 3:28:00 time: 0.395470 data_time: 0.043486 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.874394 loss: 0.000590 2022/10/20 15:44:26 - mmengine - INFO - Epoch(train) [124][200/586] lr: 5.000000e-04 eta: 3:27:50 time: 0.297157 data_time: 0.034206 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.806236 loss: 0.000553 2022/10/20 15:44:40 - mmengine - INFO - Epoch(train) [124][250/586] lr: 5.000000e-04 eta: 3:27:39 time: 0.293029 data_time: 0.050158 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.864277 loss: 0.000583 2022/10/20 15:44:56 - mmengine - INFO - Epoch(train) [124][300/586] lr: 5.000000e-04 eta: 3:27:30 time: 0.318843 data_time: 0.027109 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.884961 loss: 0.000585 2022/10/20 15:45:10 - mmengine - INFO - Epoch(train) [124][350/586] lr: 5.000000e-04 eta: 3:27:19 time: 0.283431 data_time: 0.030236 memory: 7326 loss_kpt: 0.000567 acc_pose: 0.860436 loss: 0.000567 2022/10/20 15:45:38 - mmengine - INFO - Epoch(train) [124][400/586] lr: 5.000000e-04 eta: 3:27:17 time: 0.552782 data_time: 0.023398 memory: 7326 loss_kpt: 0.000610 acc_pose: 0.862364 loss: 0.000610 2022/10/20 15:45:53 - mmengine - INFO - Epoch(train) [124][450/586] lr: 5.000000e-04 eta: 3:27:06 time: 0.291564 data_time: 0.031107 memory: 7326 loss_kpt: 0.000592 acc_pose: 0.869818 loss: 0.000592 2022/10/20 15:46:07 - mmengine - INFO - Epoch(train) [124][500/586] lr: 5.000000e-04 eta: 3:26:55 time: 0.286173 data_time: 0.031221 memory: 7326 loss_kpt: 0.000588 acc_pose: 0.845176 loss: 0.000588 2022/10/20 15:46:20 - mmengine - INFO - Epoch(train) [124][550/586] lr: 5.000000e-04 eta: 3:26:43 time: 0.255021 data_time: 0.027770 memory: 7326 loss_kpt: 0.000588 acc_pose: 0.804222 loss: 0.000588 2022/10/20 15:46:29 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:46:47 - mmengine - INFO - Epoch(train) [125][50/586] lr: 5.000000e-04 eta: 3:26:20 time: 0.357758 data_time: 0.046508 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.867506 loss: 0.000595 2022/10/20 15:47:07 - mmengine - INFO - Epoch(train) [125][100/586] lr: 5.000000e-04 eta: 3:26:13 time: 0.406102 data_time: 0.029676 memory: 7326 loss_kpt: 0.000579 acc_pose: 0.868835 loss: 0.000579 2022/10/20 15:47:34 - mmengine - INFO - Epoch(train) [125][150/586] lr: 5.000000e-04 eta: 3:26:11 time: 0.543513 data_time: 0.029415 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.752461 loss: 0.000561 2022/10/20 15:48:25 - mmengine - INFO - Epoch(train) [125][200/586] lr: 5.000000e-04 eta: 3:26:25 time: 1.004714 data_time: 0.030520 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.809325 loss: 0.000563 2022/10/20 15:49:02 - mmengine - INFO - Epoch(train) [125][250/586] lr: 5.000000e-04 eta: 3:26:30 time: 0.741632 data_time: 0.080635 memory: 7326 loss_kpt: 0.000578 acc_pose: 0.855377 loss: 0.000578 2022/10/20 15:49:32 - mmengine - INFO - Epoch(train) [125][300/586] lr: 5.000000e-04 eta: 3:26:30 time: 0.605151 data_time: 0.060305 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.806537 loss: 0.000573 2022/10/20 15:49:50 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:49:56 - mmengine - INFO - Epoch(train) [125][350/586] lr: 5.000000e-04 eta: 3:26:25 time: 0.475483 data_time: 0.081623 memory: 7326 loss_kpt: 0.000593 acc_pose: 0.883067 loss: 0.000593 2022/10/20 15:50:23 - mmengine - INFO - Epoch(train) [125][400/586] lr: 5.000000e-04 eta: 3:26:23 time: 0.546856 data_time: 0.104056 memory: 7326 loss_kpt: 0.000578 acc_pose: 0.900133 loss: 0.000578 2022/10/20 15:50:47 - mmengine - INFO - Epoch(train) [125][450/586] lr: 5.000000e-04 eta: 3:26:19 time: 0.482475 data_time: 0.026684 memory: 7326 loss_kpt: 0.000567 acc_pose: 0.850893 loss: 0.000567 2022/10/20 15:51:09 - mmengine - INFO - Epoch(train) [125][500/586] lr: 5.000000e-04 eta: 3:26:13 time: 0.433970 data_time: 0.114543 memory: 7326 loss_kpt: 0.000576 acc_pose: 0.820876 loss: 0.000576 2022/10/20 15:51:30 - mmengine - INFO - Epoch(train) [125][550/586] lr: 5.000000e-04 eta: 3:26:06 time: 0.423733 data_time: 0.027457 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.891752 loss: 0.000565 2022/10/20 15:51:46 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:52:08 - mmengine - INFO - Epoch(train) [126][50/586] lr: 5.000000e-04 eta: 3:25:45 time: 0.442333 data_time: 0.048794 memory: 7326 loss_kpt: 0.000576 acc_pose: 0.841795 loss: 0.000576 2022/10/20 15:52:27 - mmengine - INFO - Epoch(train) [126][100/586] lr: 5.000000e-04 eta: 3:25:37 time: 0.368431 data_time: 0.041811 memory: 7326 loss_kpt: 0.000569 acc_pose: 0.855480 loss: 0.000569 2022/10/20 15:52:48 - mmengine - INFO - Epoch(train) [126][150/586] lr: 5.000000e-04 eta: 3:25:30 time: 0.415410 data_time: 0.028146 memory: 7326 loss_kpt: 0.000579 acc_pose: 0.849061 loss: 0.000579 2022/10/20 15:53:07 - mmengine - INFO - Epoch(train) [126][200/586] lr: 5.000000e-04 eta: 3:25:22 time: 0.382728 data_time: 0.044919 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.836189 loss: 0.000568 2022/10/20 15:53:29 - mmengine - INFO - Epoch(train) [126][250/586] lr: 5.000000e-04 eta: 3:25:17 time: 0.446246 data_time: 0.023267 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.904367 loss: 0.000570 2022/10/20 15:53:48 - mmengine - INFO - Epoch(train) [126][300/586] lr: 5.000000e-04 eta: 3:25:08 time: 0.370852 data_time: 0.025887 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.875161 loss: 0.000572 2022/10/20 15:54:02 - mmengine - INFO - Epoch(train) [126][350/586] lr: 5.000000e-04 eta: 3:24:57 time: 0.286956 data_time: 0.032248 memory: 7326 loss_kpt: 0.000579 acc_pose: 0.880350 loss: 0.000579 2022/10/20 15:54:20 - mmengine - INFO - Epoch(train) [126][400/586] lr: 5.000000e-04 eta: 3:24:49 time: 0.360694 data_time: 0.035151 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.859104 loss: 0.000586 2022/10/20 15:54:40 - mmengine - INFO - Epoch(train) [126][450/586] lr: 5.000000e-04 eta: 3:24:41 time: 0.400294 data_time: 0.048201 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.797595 loss: 0.000587 2022/10/20 15:55:05 - mmengine - INFO - Epoch(train) [126][500/586] lr: 5.000000e-04 eta: 3:24:37 time: 0.491442 data_time: 0.022742 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.884976 loss: 0.000573 2022/10/20 15:55:26 - mmengine - INFO - Epoch(train) [126][550/586] lr: 5.000000e-04 eta: 3:24:31 time: 0.431757 data_time: 0.023244 memory: 7326 loss_kpt: 0.000579 acc_pose: 0.800710 loss: 0.000579 2022/10/20 15:55:37 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:56:00 - mmengine - INFO - Epoch(train) [127][50/586] lr: 5.000000e-04 eta: 3:24:10 time: 0.456885 data_time: 0.031670 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.875449 loss: 0.000568 2022/10/20 15:56:19 - mmengine - INFO - Epoch(train) [127][100/586] lr: 5.000000e-04 eta: 3:24:02 time: 0.376290 data_time: 0.033055 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.869047 loss: 0.000561 2022/10/20 15:56:42 - mmengine - INFO - Epoch(train) [127][150/586] lr: 5.000000e-04 eta: 3:23:56 time: 0.456521 data_time: 0.030101 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.870681 loss: 0.000568 2022/10/20 15:56:47 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:56:59 - mmengine - INFO - Epoch(train) [127][200/586] lr: 5.000000e-04 eta: 3:23:47 time: 0.335969 data_time: 0.061976 memory: 7326 loss_kpt: 0.000581 acc_pose: 0.874587 loss: 0.000581 2022/10/20 15:57:18 - mmengine - INFO - Epoch(train) [127][250/586] lr: 5.000000e-04 eta: 3:23:39 time: 0.393150 data_time: 0.038211 memory: 7326 loss_kpt: 0.000591 acc_pose: 0.852359 loss: 0.000591 2022/10/20 15:57:33 - mmengine - INFO - Epoch(train) [127][300/586] lr: 5.000000e-04 eta: 3:23:28 time: 0.296969 data_time: 0.043462 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.854555 loss: 0.000584 2022/10/20 15:57:49 - mmengine - INFO - Epoch(train) [127][350/586] lr: 5.000000e-04 eta: 3:23:17 time: 0.307431 data_time: 0.048829 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.804989 loss: 0.000572 2022/10/20 15:58:04 - mmengine - INFO - Epoch(train) [127][400/586] lr: 5.000000e-04 eta: 3:23:07 time: 0.312816 data_time: 0.062241 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.893145 loss: 0.000586 2022/10/20 15:58:22 - mmengine - INFO - Epoch(train) [127][450/586] lr: 5.000000e-04 eta: 3:22:58 time: 0.362639 data_time: 0.051591 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.787052 loss: 0.000589 2022/10/20 15:58:42 - mmengine - INFO - Epoch(train) [127][500/586] lr: 5.000000e-04 eta: 3:22:51 time: 0.402176 data_time: 0.053705 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.829518 loss: 0.000587 2022/10/20 15:58:59 - mmengine - INFO - Epoch(train) [127][550/586] lr: 5.000000e-04 eta: 3:22:41 time: 0.324343 data_time: 0.052955 memory: 7326 loss_kpt: 0.000600 acc_pose: 0.788331 loss: 0.000600 2022/10/20 15:59:14 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 15:59:29 - mmengine - INFO - Epoch(train) [128][50/586] lr: 5.000000e-04 eta: 3:22:15 time: 0.308635 data_time: 0.041443 memory: 7326 loss_kpt: 0.000576 acc_pose: 0.872615 loss: 0.000576 2022/10/20 15:59:44 - mmengine - INFO - Epoch(train) [128][100/586] lr: 5.000000e-04 eta: 3:22:04 time: 0.299359 data_time: 0.041819 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.797788 loss: 0.000583 2022/10/20 16:00:04 - mmengine - INFO - Epoch(train) [128][150/586] lr: 5.000000e-04 eta: 3:21:57 time: 0.397858 data_time: 0.183970 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.844024 loss: 0.000557 2022/10/20 16:00:21 - mmengine - INFO - Epoch(train) [128][200/586] lr: 5.000000e-04 eta: 3:21:47 time: 0.338883 data_time: 0.101334 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.851172 loss: 0.000564 2022/10/20 16:00:36 - mmengine - INFO - Epoch(train) [128][250/586] lr: 5.000000e-04 eta: 3:21:37 time: 0.308738 data_time: 0.082940 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.877537 loss: 0.000559 2022/10/20 16:00:49 - mmengine - INFO - Epoch(train) [128][300/586] lr: 5.000000e-04 eta: 3:21:24 time: 0.254633 data_time: 0.032268 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.848635 loss: 0.000575 2022/10/20 16:01:04 - mmengine - INFO - Epoch(train) [128][350/586] lr: 5.000000e-04 eta: 3:21:13 time: 0.294580 data_time: 0.029374 memory: 7326 loss_kpt: 0.000594 acc_pose: 0.821220 loss: 0.000594 2022/10/20 16:01:22 - mmengine - INFO - Epoch(train) [128][400/586] lr: 5.000000e-04 eta: 3:21:05 time: 0.372334 data_time: 0.093611 memory: 7326 loss_kpt: 0.000580 acc_pose: 0.812550 loss: 0.000580 2022/10/20 16:01:42 - mmengine - INFO - Epoch(train) [128][450/586] lr: 5.000000e-04 eta: 3:20:57 time: 0.392487 data_time: 0.127546 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.855454 loss: 0.000565 2022/10/20 16:02:06 - mmengine - INFO - Epoch(train) [128][500/586] lr: 5.000000e-04 eta: 3:20:52 time: 0.487793 data_time: 0.064183 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.751655 loss: 0.000574 2022/10/20 16:02:30 - mmengine - INFO - Epoch(train) [128][550/586] lr: 5.000000e-04 eta: 3:20:47 time: 0.477937 data_time: 0.035098 memory: 7326 loss_kpt: 0.000552 acc_pose: 0.860472 loss: 0.000552 2022/10/20 16:02:41 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:02:44 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:03:08 - mmengine - INFO - Epoch(train) [129][50/586] lr: 5.000000e-04 eta: 3:20:27 time: 0.485855 data_time: 0.134919 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.885011 loss: 0.000589 2022/10/20 16:03:32 - mmengine - INFO - Epoch(train) [129][100/586] lr: 5.000000e-04 eta: 3:20:21 time: 0.472095 data_time: 0.125298 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.897643 loss: 0.000584 2022/10/20 16:03:55 - mmengine - INFO - Epoch(train) [129][150/586] lr: 5.000000e-04 eta: 3:20:15 time: 0.454058 data_time: 0.039138 memory: 7326 loss_kpt: 0.000579 acc_pose: 0.873142 loss: 0.000579 2022/10/20 16:04:23 - mmengine - INFO - Epoch(train) [129][200/586] lr: 5.000000e-04 eta: 3:20:13 time: 0.570858 data_time: 0.036129 memory: 7326 loss_kpt: 0.000579 acc_pose: 0.882462 loss: 0.000579 2022/10/20 16:04:47 - mmengine - INFO - Epoch(train) [129][250/586] lr: 5.000000e-04 eta: 3:20:08 time: 0.483575 data_time: 0.036726 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.842980 loss: 0.000568 2022/10/20 16:05:26 - mmengine - INFO - Epoch(train) [129][300/586] lr: 5.000000e-04 eta: 3:20:11 time: 0.763285 data_time: 0.024264 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.822137 loss: 0.000570 2022/10/20 16:05:44 - mmengine - INFO - Epoch(train) [129][350/586] lr: 5.000000e-04 eta: 3:20:02 time: 0.359875 data_time: 0.072127 memory: 7326 loss_kpt: 0.000595 acc_pose: 0.850055 loss: 0.000595 2022/10/20 16:06:02 - mmengine - INFO - Epoch(train) [129][400/586] lr: 5.000000e-04 eta: 3:19:54 time: 0.376260 data_time: 0.076410 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.794536 loss: 0.000566 2022/10/20 16:06:22 - mmengine - INFO - Epoch(train) [129][450/586] lr: 5.000000e-04 eta: 3:19:45 time: 0.390612 data_time: 0.044518 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.853405 loss: 0.000565 2022/10/20 16:06:48 - mmengine - INFO - Epoch(train) [129][500/586] lr: 5.000000e-04 eta: 3:19:42 time: 0.528550 data_time: 0.029420 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.862077 loss: 0.000573 2022/10/20 16:07:09 - mmengine - INFO - Epoch(train) [129][550/586] lr: 5.000000e-04 eta: 3:19:34 time: 0.408680 data_time: 0.027544 memory: 7326 loss_kpt: 0.000582 acc_pose: 0.846214 loss: 0.000582 2022/10/20 16:07:28 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:07:55 - mmengine - INFO - Epoch(train) [130][50/586] lr: 5.000000e-04 eta: 3:19:16 time: 0.551701 data_time: 0.092789 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.867291 loss: 0.000558 2022/10/20 16:08:23 - mmengine - INFO - Epoch(train) [130][100/586] lr: 5.000000e-04 eta: 3:19:13 time: 0.558069 data_time: 0.048907 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.870058 loss: 0.000566 2022/10/20 16:08:45 - mmengine - INFO - Epoch(train) [130][150/586] lr: 5.000000e-04 eta: 3:19:06 time: 0.440795 data_time: 0.101828 memory: 7326 loss_kpt: 0.000577 acc_pose: 0.862512 loss: 0.000577 2022/10/20 16:09:15 - mmengine - INFO - Epoch(train) [130][200/586] lr: 5.000000e-04 eta: 3:19:05 time: 0.607877 data_time: 0.042142 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.887436 loss: 0.000556 2022/10/20 16:09:44 - mmengine - INFO - Epoch(train) [130][250/586] lr: 5.000000e-04 eta: 3:19:02 time: 0.561341 data_time: 0.068675 memory: 7326 loss_kpt: 0.000577 acc_pose: 0.841218 loss: 0.000577 2022/10/20 16:10:12 - mmengine - INFO - Epoch(train) [130][300/586] lr: 5.000000e-04 eta: 3:18:59 time: 0.565956 data_time: 0.175753 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.860180 loss: 0.000585 2022/10/20 16:10:45 - mmengine - INFO - Epoch(train) [130][350/586] lr: 5.000000e-04 eta: 3:18:59 time: 0.671893 data_time: 0.134239 memory: 7326 loss_kpt: 0.000569 acc_pose: 0.894886 loss: 0.000569 2022/10/20 16:11:13 - mmengine - INFO - Epoch(train) [130][400/586] lr: 5.000000e-04 eta: 3:18:55 time: 0.551189 data_time: 0.034084 memory: 7326 loss_kpt: 0.000584 acc_pose: 0.752495 loss: 0.000584 2022/10/20 16:11:15 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:11:37 - mmengine - INFO - Epoch(train) [130][450/586] lr: 5.000000e-04 eta: 3:18:50 time: 0.478278 data_time: 0.029875 memory: 7326 loss_kpt: 0.000578 acc_pose: 0.840589 loss: 0.000578 2022/10/20 16:11:58 - mmengine - INFO - Epoch(train) [130][500/586] lr: 5.000000e-04 eta: 3:18:42 time: 0.428952 data_time: 0.072168 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.883017 loss: 0.000572 2022/10/20 16:12:17 - mmengine - INFO - Epoch(train) [130][550/586] lr: 5.000000e-04 eta: 3:18:33 time: 0.368752 data_time: 0.099432 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.816158 loss: 0.000585 2022/10/20 16:12:29 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:12:29 - mmengine - INFO - Saving checkpoint at 130 epochs 2022/10/20 16:12:47 - mmengine - INFO - Epoch(val) [130][50/407] eta: 0:01:42 time: 0.286918 data_time: 0.208233 memory: 7326 2022/10/20 16:13:08 - mmengine - INFO - Epoch(val) [130][100/407] eta: 0:02:06 time: 0.413224 data_time: 0.332526 memory: 1680 2022/10/20 16:13:19 - mmengine - INFO - Epoch(val) [130][150/407] eta: 0:00:58 time: 0.228473 data_time: 0.151595 memory: 1680 2022/10/20 16:13:33 - mmengine - INFO - Epoch(val) [130][200/407] eta: 0:00:57 time: 0.277858 data_time: 0.201192 memory: 1680 2022/10/20 16:13:49 - mmengine - INFO - Epoch(val) [130][250/407] eta: 0:00:48 time: 0.310641 data_time: 0.233085 memory: 1680 2022/10/20 16:14:07 - mmengine - INFO - Epoch(val) [130][300/407] eta: 0:00:40 time: 0.378204 data_time: 0.300162 memory: 1680 2022/10/20 16:14:14 - mmengine - INFO - Epoch(val) [130][350/407] eta: 0:00:07 time: 0.126098 data_time: 0.048865 memory: 1680 2022/10/20 16:14:32 - mmengine - INFO - Epoch(val) [130][400/407] eta: 0:00:02 time: 0.358588 data_time: 0.280115 memory: 1680 2022/10/20 16:16:54 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 16:17:07 - mmengine - INFO - Epoch(val) [130][407/407] coco/AP: 0.726799 coco/AP .5: 0.899579 coco/AP .75: 0.805314 coco/AP (M): 0.690126 coco/AP (L): 0.793314 coco/AR: 0.783344 coco/AR .5: 0.939232 coco/AR .75: 0.852173 coco/AR (M): 0.740317 coco/AR (L): 0.845522 2022/10/20 16:17:41 - mmengine - INFO - Epoch(train) [131][50/586] lr: 5.000000e-04 eta: 3:18:19 time: 0.690160 data_time: 0.044933 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.821177 loss: 0.000568 2022/10/20 16:18:24 - mmengine - INFO - Epoch(train) [131][100/586] lr: 5.000000e-04 eta: 3:18:25 time: 0.859969 data_time: 0.208394 memory: 7326 loss_kpt: 0.000577 acc_pose: 0.852687 loss: 0.000577 2022/10/20 16:18:48 - mmengine - INFO - Epoch(train) [131][150/586] lr: 5.000000e-04 eta: 3:18:19 time: 0.471425 data_time: 0.061706 memory: 7326 loss_kpt: 0.000577 acc_pose: 0.848117 loss: 0.000577 2022/10/20 16:19:16 - mmengine - INFO - Epoch(train) [131][200/586] lr: 5.000000e-04 eta: 3:18:16 time: 0.568327 data_time: 0.045833 memory: 7326 loss_kpt: 0.000599 acc_pose: 0.808245 loss: 0.000599 2022/10/20 16:19:40 - mmengine - INFO - Epoch(train) [131][250/586] lr: 5.000000e-04 eta: 3:18:10 time: 0.467472 data_time: 0.119288 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.908513 loss: 0.000571 2022/10/20 16:20:07 - mmengine - INFO - Epoch(train) [131][300/586] lr: 5.000000e-04 eta: 3:18:06 time: 0.545022 data_time: 0.041241 memory: 7326 loss_kpt: 0.000606 acc_pose: 0.783456 loss: 0.000606 2022/10/20 16:20:44 - mmengine - INFO - Epoch(train) [131][350/586] lr: 5.000000e-04 eta: 3:18:08 time: 0.745558 data_time: 0.112916 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.932418 loss: 0.000568 2022/10/20 16:21:22 - mmengine - INFO - Epoch(train) [131][400/586] lr: 5.000000e-04 eta: 3:18:10 time: 0.759399 data_time: 0.039786 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.916068 loss: 0.000565 2022/10/20 16:21:46 - mmengine - INFO - Epoch(train) [131][450/586] lr: 5.000000e-04 eta: 3:18:04 time: 0.472737 data_time: 0.061375 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.878504 loss: 0.000574 2022/10/20 16:22:15 - mmengine - INFO - Epoch(train) [131][500/586] lr: 5.000000e-04 eta: 3:18:01 time: 0.571401 data_time: 0.141524 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.862091 loss: 0.000553 2022/10/20 16:22:55 - mmengine - INFO - Epoch(train) [131][550/586] lr: 5.000000e-04 eta: 3:18:05 time: 0.816549 data_time: 0.489234 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.868340 loss: 0.000565 2022/10/20 16:23:21 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:23:45 - mmengine - INFO - Epoch(train) [132][50/586] lr: 5.000000e-04 eta: 3:17:44 time: 0.483273 data_time: 0.046244 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.862853 loss: 0.000586 2022/10/20 16:24:09 - mmengine - INFO - Epoch(train) [132][100/586] lr: 5.000000e-04 eta: 3:17:38 time: 0.484457 data_time: 0.057486 memory: 7326 loss_kpt: 0.000576 acc_pose: 0.780063 loss: 0.000576 2022/10/20 16:24:57 - mmengine - INFO - Epoch(train) [132][150/586] lr: 5.000000e-04 eta: 3:17:47 time: 0.963031 data_time: 0.074251 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.853604 loss: 0.000575 2022/10/20 16:25:11 - mmengine - INFO - Epoch(train) [132][200/586] lr: 5.000000e-04 eta: 3:17:34 time: 0.282134 data_time: 0.030923 memory: 7326 loss_kpt: 0.000582 acc_pose: 0.758043 loss: 0.000582 2022/10/20 16:25:19 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:25:23 - mmengine - INFO - Epoch(train) [132][250/586] lr: 5.000000e-04 eta: 3:17:21 time: 0.228643 data_time: 0.023558 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.852058 loss: 0.000558 2022/10/20 16:25:34 - mmengine - INFO - Epoch(train) [132][300/586] lr: 5.000000e-04 eta: 3:17:07 time: 0.225841 data_time: 0.024625 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.888904 loss: 0.000568 2022/10/20 16:25:45 - mmengine - INFO - Epoch(train) [132][350/586] lr: 5.000000e-04 eta: 3:16:53 time: 0.221927 data_time: 0.026016 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.866245 loss: 0.000583 2022/10/20 16:25:56 - mmengine - INFO - Epoch(train) [132][400/586] lr: 5.000000e-04 eta: 3:16:39 time: 0.223161 data_time: 0.024896 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.891141 loss: 0.000571 2022/10/20 16:26:08 - mmengine - INFO - Epoch(train) [132][450/586] lr: 5.000000e-04 eta: 3:16:26 time: 0.232387 data_time: 0.027790 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.887959 loss: 0.000571 2022/10/20 16:26:20 - mmengine - INFO - Epoch(train) [132][500/586] lr: 5.000000e-04 eta: 3:16:12 time: 0.229059 data_time: 0.024817 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.864295 loss: 0.000574 2022/10/20 16:26:31 - mmengine - INFO - Epoch(train) [132][550/586] lr: 5.000000e-04 eta: 3:15:58 time: 0.223507 data_time: 0.023847 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.864930 loss: 0.000559 2022/10/20 16:26:39 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:26:51 - mmengine - INFO - Epoch(train) [133][50/586] lr: 5.000000e-04 eta: 3:15:30 time: 0.233169 data_time: 0.037083 memory: 7326 loss_kpt: 0.000569 acc_pose: 0.839399 loss: 0.000569 2022/10/20 16:27:02 - mmengine - INFO - Epoch(train) [133][100/586] lr: 5.000000e-04 eta: 3:15:16 time: 0.226508 data_time: 0.026439 memory: 7326 loss_kpt: 0.000569 acc_pose: 0.849296 loss: 0.000569 2022/10/20 16:27:13 - mmengine - INFO - Epoch(train) [133][150/586] lr: 5.000000e-04 eta: 3:15:02 time: 0.226664 data_time: 0.025119 memory: 7326 loss_kpt: 0.000552 acc_pose: 0.861988 loss: 0.000552 2022/10/20 16:27:25 - mmengine - INFO - Epoch(train) [133][200/586] lr: 5.000000e-04 eta: 3:14:49 time: 0.226011 data_time: 0.026873 memory: 7326 loss_kpt: 0.000577 acc_pose: 0.840425 loss: 0.000577 2022/10/20 16:27:36 - mmengine - INFO - Epoch(train) [133][250/586] lr: 5.000000e-04 eta: 3:14:35 time: 0.221797 data_time: 0.025510 memory: 7326 loss_kpt: 0.000577 acc_pose: 0.920569 loss: 0.000577 2022/10/20 16:27:47 - mmengine - INFO - Epoch(train) [133][300/586] lr: 5.000000e-04 eta: 3:14:21 time: 0.229613 data_time: 0.031496 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.876474 loss: 0.000574 2022/10/20 16:27:59 - mmengine - INFO - Epoch(train) [133][350/586] lr: 5.000000e-04 eta: 3:14:07 time: 0.227915 data_time: 0.023840 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.873636 loss: 0.000571 2022/10/20 16:28:10 - mmengine - INFO - Epoch(train) [133][400/586] lr: 5.000000e-04 eta: 3:13:54 time: 0.222942 data_time: 0.023179 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.911313 loss: 0.000565 2022/10/20 16:28:21 - mmengine - INFO - Epoch(train) [133][450/586] lr: 5.000000e-04 eta: 3:13:40 time: 0.226511 data_time: 0.024784 memory: 7326 loss_kpt: 0.000591 acc_pose: 0.897317 loss: 0.000591 2022/10/20 16:28:32 - mmengine - INFO - Epoch(train) [133][500/586] lr: 5.000000e-04 eta: 3:13:26 time: 0.221204 data_time: 0.022922 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.879259 loss: 0.000573 2022/10/20 16:28:43 - mmengine - INFO - Epoch(train) [133][550/586] lr: 5.000000e-04 eta: 3:13:12 time: 0.222960 data_time: 0.022393 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.865899 loss: 0.000575 2022/10/20 16:28:52 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:29:04 - mmengine - INFO - Epoch(train) [134][50/586] lr: 5.000000e-04 eta: 3:12:44 time: 0.234309 data_time: 0.033064 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.825599 loss: 0.000587 2022/10/20 16:29:06 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:29:15 - mmengine - INFO - Epoch(train) [134][100/586] lr: 5.000000e-04 eta: 3:12:31 time: 0.238922 data_time: 0.023242 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.849596 loss: 0.000556 2022/10/20 16:29:27 - mmengine - INFO - Epoch(train) [134][150/586] lr: 5.000000e-04 eta: 3:12:17 time: 0.225686 data_time: 0.025196 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.808737 loss: 0.000551 2022/10/20 16:29:38 - mmengine - INFO - Epoch(train) [134][200/586] lr: 5.000000e-04 eta: 3:12:03 time: 0.225028 data_time: 0.031651 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.824565 loss: 0.000565 2022/10/20 16:29:50 - mmengine - INFO - Epoch(train) [134][250/586] lr: 5.000000e-04 eta: 3:11:50 time: 0.231613 data_time: 0.025025 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.857051 loss: 0.000572 2022/10/20 16:30:01 - mmengine - INFO - Epoch(train) [134][300/586] lr: 5.000000e-04 eta: 3:11:36 time: 0.228164 data_time: 0.025719 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.807611 loss: 0.000561 2022/10/20 16:30:12 - mmengine - INFO - Epoch(train) [134][350/586] lr: 5.000000e-04 eta: 3:11:22 time: 0.223431 data_time: 0.025177 memory: 7326 loss_kpt: 0.000577 acc_pose: 0.831676 loss: 0.000577 2022/10/20 16:30:23 - mmengine - INFO - Epoch(train) [134][400/586] lr: 5.000000e-04 eta: 3:11:09 time: 0.222899 data_time: 0.025051 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.863627 loss: 0.000560 2022/10/20 16:30:35 - mmengine - INFO - Epoch(train) [134][450/586] lr: 5.000000e-04 eta: 3:10:55 time: 0.230342 data_time: 0.029194 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.859411 loss: 0.000566 2022/10/20 16:30:46 - mmengine - INFO - Epoch(train) [134][500/586] lr: 5.000000e-04 eta: 3:10:41 time: 0.223627 data_time: 0.023548 memory: 7326 loss_kpt: 0.000569 acc_pose: 0.815797 loss: 0.000569 2022/10/20 16:30:57 - mmengine - INFO - Epoch(train) [134][550/586] lr: 5.000000e-04 eta: 3:10:28 time: 0.225151 data_time: 0.025564 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.876187 loss: 0.000575 2022/10/20 16:31:06 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:31:17 - mmengine - INFO - Epoch(train) [135][50/586] lr: 5.000000e-04 eta: 3:10:00 time: 0.233090 data_time: 0.033339 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.875696 loss: 0.000589 2022/10/20 16:31:29 - mmengine - INFO - Epoch(train) [135][100/586] lr: 5.000000e-04 eta: 3:09:46 time: 0.233503 data_time: 0.027728 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.826590 loss: 0.000573 2022/10/20 16:31:41 - mmengine - INFO - Epoch(train) [135][150/586] lr: 5.000000e-04 eta: 3:09:33 time: 0.233120 data_time: 0.026250 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.850969 loss: 0.000573 2022/10/20 16:31:52 - mmengine - INFO - Epoch(train) [135][200/586] lr: 5.000000e-04 eta: 3:09:19 time: 0.220658 data_time: 0.024381 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.889317 loss: 0.000570 2022/10/20 16:32:03 - mmengine - INFO - Epoch(train) [135][250/586] lr: 5.000000e-04 eta: 3:09:05 time: 0.221361 data_time: 0.023683 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.859301 loss: 0.000571 2022/10/20 16:32:14 - mmengine - INFO - Epoch(train) [135][300/586] lr: 5.000000e-04 eta: 3:08:52 time: 0.228954 data_time: 0.029034 memory: 7326 loss_kpt: 0.000578 acc_pose: 0.902956 loss: 0.000578 2022/10/20 16:32:26 - mmengine - INFO - Epoch(train) [135][350/586] lr: 5.000000e-04 eta: 3:08:38 time: 0.230429 data_time: 0.024116 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.874892 loss: 0.000566 2022/10/20 16:32:37 - mmengine - INFO - Epoch(train) [135][400/586] lr: 5.000000e-04 eta: 3:08:24 time: 0.227588 data_time: 0.025889 memory: 7326 loss_kpt: 0.000590 acc_pose: 0.874269 loss: 0.000590 2022/10/20 16:32:48 - mmengine - INFO - Epoch(train) [135][450/586] lr: 5.000000e-04 eta: 3:08:11 time: 0.218095 data_time: 0.026341 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.849399 loss: 0.000574 2022/10/20 16:32:54 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:32:59 - mmengine - INFO - Epoch(train) [135][500/586] lr: 5.000000e-04 eta: 3:07:57 time: 0.225309 data_time: 0.024560 memory: 7326 loss_kpt: 0.000554 acc_pose: 0.889028 loss: 0.000554 2022/10/20 16:33:11 - mmengine - INFO - Epoch(train) [135][550/586] lr: 5.000000e-04 eta: 3:07:43 time: 0.225275 data_time: 0.022505 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.853552 loss: 0.000564 2022/10/20 16:33:19 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:33:31 - mmengine - INFO - Epoch(train) [136][50/586] lr: 5.000000e-04 eta: 3:07:16 time: 0.242143 data_time: 0.035642 memory: 7326 loss_kpt: 0.000569 acc_pose: 0.888521 loss: 0.000569 2022/10/20 16:33:42 - mmengine - INFO - Epoch(train) [136][100/586] lr: 5.000000e-04 eta: 3:07:02 time: 0.220630 data_time: 0.023696 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.820301 loss: 0.000566 2022/10/20 16:33:53 - mmengine - INFO - Epoch(train) [136][150/586] lr: 5.000000e-04 eta: 3:06:48 time: 0.224316 data_time: 0.026553 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.830254 loss: 0.000571 2022/10/20 16:34:05 - mmengine - INFO - Epoch(train) [136][200/586] lr: 5.000000e-04 eta: 3:06:35 time: 0.229209 data_time: 0.026731 memory: 7326 loss_kpt: 0.000579 acc_pose: 0.840807 loss: 0.000579 2022/10/20 16:34:16 - mmengine - INFO - Epoch(train) [136][250/586] lr: 5.000000e-04 eta: 3:06:21 time: 0.228276 data_time: 0.025668 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.891624 loss: 0.000571 2022/10/20 16:34:27 - mmengine - INFO - Epoch(train) [136][300/586] lr: 5.000000e-04 eta: 3:06:07 time: 0.222503 data_time: 0.022762 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.856311 loss: 0.000558 2022/10/20 16:34:39 - mmengine - INFO - Epoch(train) [136][350/586] lr: 5.000000e-04 eta: 3:05:54 time: 0.224096 data_time: 0.024355 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.800026 loss: 0.000556 2022/10/20 16:34:50 - mmengine - INFO - Epoch(train) [136][400/586] lr: 5.000000e-04 eta: 3:05:40 time: 0.225112 data_time: 0.025686 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.871921 loss: 0.000561 2022/10/20 16:35:01 - mmengine - INFO - Epoch(train) [136][450/586] lr: 5.000000e-04 eta: 3:05:27 time: 0.229125 data_time: 0.025638 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.854667 loss: 0.000574 2022/10/20 16:35:12 - mmengine - INFO - Epoch(train) [136][500/586] lr: 5.000000e-04 eta: 3:05:13 time: 0.221130 data_time: 0.023175 memory: 7326 loss_kpt: 0.000585 acc_pose: 0.854264 loss: 0.000585 2022/10/20 16:35:24 - mmengine - INFO - Epoch(train) [136][550/586] lr: 5.000000e-04 eta: 3:04:59 time: 0.228130 data_time: 0.026147 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.831244 loss: 0.000572 2022/10/20 16:35:32 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:35:43 - mmengine - INFO - Epoch(train) [137][50/586] lr: 5.000000e-04 eta: 3:04:32 time: 0.228092 data_time: 0.032292 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.809643 loss: 0.000572 2022/10/20 16:35:55 - mmengine - INFO - Epoch(train) [137][100/586] lr: 5.000000e-04 eta: 3:04:18 time: 0.231667 data_time: 0.025544 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.823928 loss: 0.000575 2022/10/20 16:36:06 - mmengine - INFO - Epoch(train) [137][150/586] lr: 5.000000e-04 eta: 3:04:04 time: 0.219909 data_time: 0.025415 memory: 7326 loss_kpt: 0.000554 acc_pose: 0.894318 loss: 0.000554 2022/10/20 16:36:18 - mmengine - INFO - Epoch(train) [137][200/586] lr: 5.000000e-04 eta: 3:03:51 time: 0.232940 data_time: 0.023667 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.857199 loss: 0.000573 2022/10/20 16:36:29 - mmengine - INFO - Epoch(train) [137][250/586] lr: 5.000000e-04 eta: 3:03:37 time: 0.220761 data_time: 0.022516 memory: 7326 loss_kpt: 0.000562 acc_pose: 0.863575 loss: 0.000562 2022/10/20 16:36:40 - mmengine - INFO - Epoch(train) [137][300/586] lr: 5.000000e-04 eta: 3:03:24 time: 0.221088 data_time: 0.025320 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.894845 loss: 0.000547 2022/10/20 16:36:41 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:36:51 - mmengine - INFO - Epoch(train) [137][350/586] lr: 5.000000e-04 eta: 3:03:10 time: 0.233309 data_time: 0.023236 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.906291 loss: 0.000570 2022/10/20 16:37:03 - mmengine - INFO - Epoch(train) [137][400/586] lr: 5.000000e-04 eta: 3:02:57 time: 0.227598 data_time: 0.023532 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.848343 loss: 0.000563 2022/10/20 16:37:14 - mmengine - INFO - Epoch(train) [137][450/586] lr: 5.000000e-04 eta: 3:02:43 time: 0.220936 data_time: 0.024723 memory: 7326 loss_kpt: 0.000587 acc_pose: 0.910758 loss: 0.000587 2022/10/20 16:37:25 - mmengine - INFO - Epoch(train) [137][500/586] lr: 5.000000e-04 eta: 3:02:29 time: 0.224030 data_time: 0.025644 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.917753 loss: 0.000566 2022/10/20 16:37:37 - mmengine - INFO - Epoch(train) [137][550/586] lr: 5.000000e-04 eta: 3:02:16 time: 0.231004 data_time: 0.028001 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.879751 loss: 0.000574 2022/10/20 16:37:45 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:37:57 - mmengine - INFO - Epoch(train) [138][50/586] lr: 5.000000e-04 eta: 3:01:49 time: 0.239083 data_time: 0.030598 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.859671 loss: 0.000573 2022/10/20 16:38:08 - mmengine - INFO - Epoch(train) [138][100/586] lr: 5.000000e-04 eta: 3:01:35 time: 0.222517 data_time: 0.023911 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.848945 loss: 0.000553 2022/10/20 16:38:20 - mmengine - INFO - Epoch(train) [138][150/586] lr: 5.000000e-04 eta: 3:01:22 time: 0.233320 data_time: 0.029400 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.827806 loss: 0.000560 2022/10/20 16:38:31 - mmengine - INFO - Epoch(train) [138][200/586] lr: 5.000000e-04 eta: 3:01:08 time: 0.229198 data_time: 0.027465 memory: 7326 loss_kpt: 0.000576 acc_pose: 0.842333 loss: 0.000576 2022/10/20 16:38:43 - mmengine - INFO - Epoch(train) [138][250/586] lr: 5.000000e-04 eta: 3:00:55 time: 0.232790 data_time: 0.024044 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.900436 loss: 0.000565 2022/10/20 16:38:54 - mmengine - INFO - Epoch(train) [138][300/586] lr: 5.000000e-04 eta: 3:00:41 time: 0.226389 data_time: 0.023823 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.850276 loss: 0.000570 2022/10/20 16:39:05 - mmengine - INFO - Epoch(train) [138][350/586] lr: 5.000000e-04 eta: 3:00:28 time: 0.220559 data_time: 0.023676 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.846220 loss: 0.000563 2022/10/20 16:39:16 - mmengine - INFO - Epoch(train) [138][400/586] lr: 5.000000e-04 eta: 3:00:14 time: 0.221285 data_time: 0.023403 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.834362 loss: 0.000568 2022/10/20 16:39:28 - mmengine - INFO - Epoch(train) [138][450/586] lr: 5.000000e-04 eta: 3:00:00 time: 0.225194 data_time: 0.024040 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.870073 loss: 0.000558 2022/10/20 16:39:39 - mmengine - INFO - Epoch(train) [138][500/586] lr: 5.000000e-04 eta: 2:59:47 time: 0.230223 data_time: 0.022173 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.874182 loss: 0.000565 2022/10/20 16:39:50 - mmengine - INFO - Epoch(train) [138][550/586] lr: 5.000000e-04 eta: 2:59:33 time: 0.222291 data_time: 0.024808 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.847838 loss: 0.000565 2022/10/20 16:39:58 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:40:10 - mmengine - INFO - Epoch(train) [139][50/586] lr: 5.000000e-04 eta: 2:59:06 time: 0.234754 data_time: 0.030924 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.815166 loss: 0.000561 2022/10/20 16:40:22 - mmengine - INFO - Epoch(train) [139][100/586] lr: 5.000000e-04 eta: 2:58:53 time: 0.228523 data_time: 0.024496 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.863557 loss: 0.000565 2022/10/20 16:40:29 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:40:33 - mmengine - INFO - Epoch(train) [139][150/586] lr: 5.000000e-04 eta: 2:58:39 time: 0.230964 data_time: 0.025326 memory: 7326 loss_kpt: 0.000555 acc_pose: 0.836097 loss: 0.000555 2022/10/20 16:40:45 - mmengine - INFO - Epoch(train) [139][200/586] lr: 5.000000e-04 eta: 2:58:26 time: 0.226680 data_time: 0.025328 memory: 7326 loss_kpt: 0.000569 acc_pose: 0.860097 loss: 0.000569 2022/10/20 16:40:56 - mmengine - INFO - Epoch(train) [139][250/586] lr: 5.000000e-04 eta: 2:58:12 time: 0.229329 data_time: 0.024362 memory: 7326 loss_kpt: 0.000586 acc_pose: 0.796934 loss: 0.000586 2022/10/20 16:41:07 - mmengine - INFO - Epoch(train) [139][300/586] lr: 5.000000e-04 eta: 2:57:59 time: 0.224256 data_time: 0.023988 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.856916 loss: 0.000559 2022/10/20 16:41:19 - mmengine - INFO - Epoch(train) [139][350/586] lr: 5.000000e-04 eta: 2:57:46 time: 0.230243 data_time: 0.023630 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.855849 loss: 0.000559 2022/10/20 16:41:30 - mmengine - INFO - Epoch(train) [139][400/586] lr: 5.000000e-04 eta: 2:57:32 time: 0.230161 data_time: 0.025015 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.863823 loss: 0.000570 2022/10/20 16:41:41 - mmengine - INFO - Epoch(train) [139][450/586] lr: 5.000000e-04 eta: 2:57:18 time: 0.217132 data_time: 0.024512 memory: 7326 loss_kpt: 0.000581 acc_pose: 0.809511 loss: 0.000581 2022/10/20 16:41:52 - mmengine - INFO - Epoch(train) [139][500/586] lr: 5.000000e-04 eta: 2:57:05 time: 0.221758 data_time: 0.022473 memory: 7326 loss_kpt: 0.000562 acc_pose: 0.874774 loss: 0.000562 2022/10/20 16:42:03 - mmengine - INFO - Epoch(train) [139][550/586] lr: 5.000000e-04 eta: 2:56:51 time: 0.222136 data_time: 0.030800 memory: 7326 loss_kpt: 0.000567 acc_pose: 0.851046 loss: 0.000567 2022/10/20 16:42:12 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:42:24 - mmengine - INFO - Epoch(train) [140][50/586] lr: 5.000000e-04 eta: 2:56:24 time: 0.235890 data_time: 0.030220 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.906643 loss: 0.000556 2022/10/20 16:42:35 - mmengine - INFO - Epoch(train) [140][100/586] lr: 5.000000e-04 eta: 2:56:11 time: 0.223028 data_time: 0.025788 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.900385 loss: 0.000559 2022/10/20 16:42:46 - mmengine - INFO - Epoch(train) [140][150/586] lr: 5.000000e-04 eta: 2:55:57 time: 0.225317 data_time: 0.022934 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.842534 loss: 0.000571 2022/10/20 16:42:58 - mmengine - INFO - Epoch(train) [140][200/586] lr: 5.000000e-04 eta: 2:55:44 time: 0.228480 data_time: 0.027075 memory: 7326 loss_kpt: 0.000549 acc_pose: 0.844793 loss: 0.000549 2022/10/20 16:43:09 - mmengine - INFO - Epoch(train) [140][250/586] lr: 5.000000e-04 eta: 2:55:30 time: 0.228045 data_time: 0.023895 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.873395 loss: 0.000561 2022/10/20 16:43:20 - mmengine - INFO - Epoch(train) [140][300/586] lr: 5.000000e-04 eta: 2:55:17 time: 0.224267 data_time: 0.024459 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.901722 loss: 0.000559 2022/10/20 16:43:32 - mmengine - INFO - Epoch(train) [140][350/586] lr: 5.000000e-04 eta: 2:55:04 time: 0.229282 data_time: 0.023177 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.789131 loss: 0.000564 2022/10/20 16:43:43 - mmengine - INFO - Epoch(train) [140][400/586] lr: 5.000000e-04 eta: 2:54:50 time: 0.217363 data_time: 0.022754 memory: 7326 loss_kpt: 0.000562 acc_pose: 0.843505 loss: 0.000562 2022/10/20 16:43:54 - mmengine - INFO - Epoch(train) [140][450/586] lr: 5.000000e-04 eta: 2:54:36 time: 0.228215 data_time: 0.027432 memory: 7326 loss_kpt: 0.000567 acc_pose: 0.749850 loss: 0.000567 2022/10/20 16:44:06 - mmengine - INFO - Epoch(train) [140][500/586] lr: 5.000000e-04 eta: 2:54:23 time: 0.231438 data_time: 0.023867 memory: 7326 loss_kpt: 0.000589 acc_pose: 0.891380 loss: 0.000589 2022/10/20 16:44:16 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:44:17 - mmengine - INFO - Epoch(train) [140][550/586] lr: 5.000000e-04 eta: 2:54:10 time: 0.222980 data_time: 0.025712 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.826558 loss: 0.000557 2022/10/20 16:44:25 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:44:25 - mmengine - INFO - Saving checkpoint at 140 epochs 2022/10/20 16:44:35 - mmengine - INFO - Epoch(val) [140][50/407] eta: 0:00:42 time: 0.118857 data_time: 0.036292 memory: 7326 2022/10/20 16:44:41 - mmengine - INFO - Epoch(val) [140][100/407] eta: 0:00:35 time: 0.116050 data_time: 0.034520 memory: 1680 2022/10/20 16:44:47 - mmengine - INFO - Epoch(val) [140][150/407] eta: 0:00:28 time: 0.109905 data_time: 0.026370 memory: 1680 2022/10/20 16:44:52 - mmengine - INFO - Epoch(val) [140][200/407] eta: 0:00:23 time: 0.115651 data_time: 0.031299 memory: 1680 2022/10/20 16:44:58 - mmengine - INFO - Epoch(val) [140][250/407] eta: 0:00:17 time: 0.112736 data_time: 0.031888 memory: 1680 2022/10/20 16:45:04 - mmengine - INFO - Epoch(val) [140][300/407] eta: 0:00:12 time: 0.115727 data_time: 0.035367 memory: 1680 2022/10/20 16:45:10 - mmengine - INFO - Epoch(val) [140][350/407] eta: 0:00:07 time: 0.130181 data_time: 0.044189 memory: 1680 2022/10/20 16:45:15 - mmengine - INFO - Epoch(val) [140][400/407] eta: 0:00:00 time: 0.101434 data_time: 0.023084 memory: 1680 2022/10/20 16:45:48 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 16:46:01 - mmengine - INFO - Epoch(val) [140][407/407] coco/AP: 0.726543 coco/AP .5: 0.899100 coco/AP .75: 0.803320 coco/AP (M): 0.690354 coco/AP (L): 0.792938 coco/AR: 0.781533 coco/AR .5: 0.937185 coco/AR .75: 0.848709 coco/AR (M): 0.738487 coco/AR (L): 0.844036 2022/10/20 16:46:13 - mmengine - INFO - Epoch(train) [141][50/586] lr: 5.000000e-04 eta: 2:53:43 time: 0.242475 data_time: 0.035473 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.874518 loss: 0.000559 2022/10/20 16:46:25 - mmengine - INFO - Epoch(train) [141][100/586] lr: 5.000000e-04 eta: 2:53:30 time: 0.237335 data_time: 0.023492 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.798848 loss: 0.000583 2022/10/20 16:46:36 - mmengine - INFO - Epoch(train) [141][150/586] lr: 5.000000e-04 eta: 2:53:17 time: 0.235009 data_time: 0.024821 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.919259 loss: 0.000568 2022/10/20 16:46:48 - mmengine - INFO - Epoch(train) [141][200/586] lr: 5.000000e-04 eta: 2:53:03 time: 0.222993 data_time: 0.024482 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.860445 loss: 0.000583 2022/10/20 16:46:59 - mmengine - INFO - Epoch(train) [141][250/586] lr: 5.000000e-04 eta: 2:52:50 time: 0.223892 data_time: 0.024187 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.848310 loss: 0.000563 2022/10/20 16:47:10 - mmengine - INFO - Epoch(train) [141][300/586] lr: 5.000000e-04 eta: 2:52:36 time: 0.226156 data_time: 0.024165 memory: 7326 loss_kpt: 0.000569 acc_pose: 0.842369 loss: 0.000569 2022/10/20 16:47:22 - mmengine - INFO - Epoch(train) [141][350/586] lr: 5.000000e-04 eta: 2:52:23 time: 0.230556 data_time: 0.024714 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.864736 loss: 0.000573 2022/10/20 16:47:33 - mmengine - INFO - Epoch(train) [141][400/586] lr: 5.000000e-04 eta: 2:52:10 time: 0.229529 data_time: 0.023641 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.856060 loss: 0.000556 2022/10/20 16:47:44 - mmengine - INFO - Epoch(train) [141][450/586] lr: 5.000000e-04 eta: 2:51:56 time: 0.223893 data_time: 0.026062 memory: 7326 loss_kpt: 0.000567 acc_pose: 0.859725 loss: 0.000567 2022/10/20 16:47:56 - mmengine - INFO - Epoch(train) [141][500/586] lr: 5.000000e-04 eta: 2:51:43 time: 0.222476 data_time: 0.023622 memory: 7326 loss_kpt: 0.000550 acc_pose: 0.851006 loss: 0.000550 2022/10/20 16:48:07 - mmengine - INFO - Epoch(train) [141][550/586] lr: 5.000000e-04 eta: 2:51:29 time: 0.220989 data_time: 0.026093 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.849661 loss: 0.000558 2022/10/20 16:48:15 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:48:27 - mmengine - INFO - Epoch(train) [142][50/586] lr: 5.000000e-04 eta: 2:51:02 time: 0.245711 data_time: 0.035111 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.820774 loss: 0.000572 2022/10/20 16:48:38 - mmengine - INFO - Epoch(train) [142][100/586] lr: 5.000000e-04 eta: 2:50:49 time: 0.220349 data_time: 0.023469 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.893206 loss: 0.000568 2022/10/20 16:48:50 - mmengine - INFO - Epoch(train) [142][150/586] lr: 5.000000e-04 eta: 2:50:36 time: 0.232354 data_time: 0.023098 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.800784 loss: 0.000559 2022/10/20 16:49:01 - mmengine - INFO - Epoch(train) [142][200/586] lr: 5.000000e-04 eta: 2:50:22 time: 0.226996 data_time: 0.026445 memory: 7326 loss_kpt: 0.000567 acc_pose: 0.884804 loss: 0.000567 2022/10/20 16:49:12 - mmengine - INFO - Epoch(train) [142][250/586] lr: 5.000000e-04 eta: 2:50:09 time: 0.223080 data_time: 0.022824 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.845651 loss: 0.000565 2022/10/20 16:49:24 - mmengine - INFO - Epoch(train) [142][300/586] lr: 5.000000e-04 eta: 2:49:56 time: 0.233589 data_time: 0.024557 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.880906 loss: 0.000559 2022/10/20 16:49:36 - mmengine - INFO - Epoch(train) [142][350/586] lr: 5.000000e-04 eta: 2:49:42 time: 0.233415 data_time: 0.025423 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.815573 loss: 0.000570 2022/10/20 16:49:41 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:49:47 - mmengine - INFO - Epoch(train) [142][400/586] lr: 5.000000e-04 eta: 2:49:29 time: 0.219471 data_time: 0.023908 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.923205 loss: 0.000561 2022/10/20 16:49:58 - mmengine - INFO - Epoch(train) [142][450/586] lr: 5.000000e-04 eta: 2:49:16 time: 0.227601 data_time: 0.027950 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.912344 loss: 0.000558 2022/10/20 16:50:10 - mmengine - INFO - Epoch(train) [142][500/586] lr: 5.000000e-04 eta: 2:49:02 time: 0.233372 data_time: 0.024047 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.831546 loss: 0.000561 2022/10/20 16:50:21 - mmengine - INFO - Epoch(train) [142][550/586] lr: 5.000000e-04 eta: 2:48:49 time: 0.219167 data_time: 0.027163 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.826904 loss: 0.000566 2022/10/20 16:50:29 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:50:40 - mmengine - INFO - Epoch(train) [143][50/586] lr: 5.000000e-04 eta: 2:48:22 time: 0.231251 data_time: 0.030612 memory: 7326 loss_kpt: 0.000583 acc_pose: 0.862907 loss: 0.000583 2022/10/20 16:50:52 - mmengine - INFO - Epoch(train) [143][100/586] lr: 5.000000e-04 eta: 2:48:09 time: 0.231116 data_time: 0.031163 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.873976 loss: 0.000551 2022/10/20 16:51:04 - mmengine - INFO - Epoch(train) [143][150/586] lr: 5.000000e-04 eta: 2:47:56 time: 0.235466 data_time: 0.023021 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.858494 loss: 0.000565 2022/10/20 16:51:15 - mmengine - INFO - Epoch(train) [143][200/586] lr: 5.000000e-04 eta: 2:47:42 time: 0.222729 data_time: 0.026437 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.889197 loss: 0.000553 2022/10/20 16:51:26 - mmengine - INFO - Epoch(train) [143][250/586] lr: 5.000000e-04 eta: 2:47:29 time: 0.225395 data_time: 0.023604 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.928458 loss: 0.000560 2022/10/20 16:51:37 - mmengine - INFO - Epoch(train) [143][300/586] lr: 5.000000e-04 eta: 2:47:16 time: 0.223919 data_time: 0.026654 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.851942 loss: 0.000566 2022/10/20 16:51:49 - mmengine - INFO - Epoch(train) [143][350/586] lr: 5.000000e-04 eta: 2:47:02 time: 0.231570 data_time: 0.026190 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.869148 loss: 0.000563 2022/10/20 16:52:01 - mmengine - INFO - Epoch(train) [143][400/586] lr: 5.000000e-04 eta: 2:46:49 time: 0.237678 data_time: 0.025540 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.819965 loss: 0.000556 2022/10/20 16:52:12 - mmengine - INFO - Epoch(train) [143][450/586] lr: 5.000000e-04 eta: 2:46:36 time: 0.217758 data_time: 0.026670 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.887883 loss: 0.000565 2022/10/20 16:52:23 - mmengine - INFO - Epoch(train) [143][500/586] lr: 5.000000e-04 eta: 2:46:22 time: 0.220352 data_time: 0.023581 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.897552 loss: 0.000573 2022/10/20 16:52:34 - mmengine - INFO - Epoch(train) [143][550/586] lr: 5.000000e-04 eta: 2:46:09 time: 0.234909 data_time: 0.028301 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.891617 loss: 0.000556 2022/10/20 16:52:42 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:52:54 - mmengine - INFO - Epoch(train) [144][50/586] lr: 5.000000e-04 eta: 2:45:43 time: 0.244233 data_time: 0.031343 memory: 7326 loss_kpt: 0.000567 acc_pose: 0.822174 loss: 0.000567 2022/10/20 16:53:06 - mmengine - INFO - Epoch(train) [144][100/586] lr: 5.000000e-04 eta: 2:45:30 time: 0.224950 data_time: 0.025131 memory: 7326 loss_kpt: 0.000555 acc_pose: 0.772058 loss: 0.000555 2022/10/20 16:53:17 - mmengine - INFO - Epoch(train) [144][150/586] lr: 5.000000e-04 eta: 2:45:16 time: 0.222074 data_time: 0.025233 memory: 7326 loss_kpt: 0.000549 acc_pose: 0.838062 loss: 0.000549 2022/10/20 16:53:28 - mmengine - INFO - Epoch(train) [144][200/586] lr: 5.000000e-04 eta: 2:45:03 time: 0.223994 data_time: 0.031394 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.839347 loss: 0.000571 2022/10/20 16:53:28 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:53:40 - mmengine - INFO - Epoch(train) [144][250/586] lr: 5.000000e-04 eta: 2:44:50 time: 0.230871 data_time: 0.023958 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.923081 loss: 0.000564 2022/10/20 16:53:52 - mmengine - INFO - Epoch(train) [144][300/586] lr: 5.000000e-04 eta: 2:44:37 time: 0.244410 data_time: 0.029401 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.889156 loss: 0.000566 2022/10/20 16:54:04 - mmengine - INFO - Epoch(train) [144][350/586] lr: 5.000000e-04 eta: 2:44:24 time: 0.238236 data_time: 0.027895 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.782042 loss: 0.000553 2022/10/20 16:54:15 - mmengine - INFO - Epoch(train) [144][400/586] lr: 5.000000e-04 eta: 2:44:10 time: 0.220617 data_time: 0.027896 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.912915 loss: 0.000570 2022/10/20 16:54:27 - mmengine - INFO - Epoch(train) [144][450/586] lr: 5.000000e-04 eta: 2:43:57 time: 0.251690 data_time: 0.030914 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.795543 loss: 0.000560 2022/10/20 16:54:39 - mmengine - INFO - Epoch(train) [144][500/586] lr: 5.000000e-04 eta: 2:43:44 time: 0.238132 data_time: 0.035829 memory: 7326 loss_kpt: 0.000562 acc_pose: 0.865691 loss: 0.000562 2022/10/20 16:54:57 - mmengine - INFO - Epoch(train) [144][550/586] lr: 5.000000e-04 eta: 2:43:34 time: 0.350944 data_time: 0.039923 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.793419 loss: 0.000560 2022/10/20 16:55:05 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:55:17 - mmengine - INFO - Epoch(train) [145][50/586] lr: 5.000000e-04 eta: 2:43:08 time: 0.234744 data_time: 0.032154 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.828961 loss: 0.000572 2022/10/20 16:55:28 - mmengine - INFO - Epoch(train) [145][100/586] lr: 5.000000e-04 eta: 2:42:54 time: 0.226674 data_time: 0.027118 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.840545 loss: 0.000570 2022/10/20 16:55:40 - mmengine - INFO - Epoch(train) [145][150/586] lr: 5.000000e-04 eta: 2:42:41 time: 0.232459 data_time: 0.023165 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.859363 loss: 0.000558 2022/10/20 16:55:51 - mmengine - INFO - Epoch(train) [145][200/586] lr: 5.000000e-04 eta: 2:42:28 time: 0.225444 data_time: 0.025281 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.891332 loss: 0.000570 2022/10/20 16:56:02 - mmengine - INFO - Epoch(train) [145][250/586] lr: 5.000000e-04 eta: 2:42:15 time: 0.224389 data_time: 0.023038 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.860562 loss: 0.000563 2022/10/20 16:56:14 - mmengine - INFO - Epoch(train) [145][300/586] lr: 5.000000e-04 eta: 2:42:01 time: 0.229543 data_time: 0.027514 memory: 7326 loss_kpt: 0.000541 acc_pose: 0.849079 loss: 0.000541 2022/10/20 16:56:25 - mmengine - INFO - Epoch(train) [145][350/586] lr: 5.000000e-04 eta: 2:41:48 time: 0.229485 data_time: 0.024667 memory: 7326 loss_kpt: 0.000588 acc_pose: 0.879533 loss: 0.000588 2022/10/20 16:56:37 - mmengine - INFO - Epoch(train) [145][400/586] lr: 5.000000e-04 eta: 2:41:35 time: 0.227109 data_time: 0.028634 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.900079 loss: 0.000557 2022/10/20 16:56:48 - mmengine - INFO - Epoch(train) [145][450/586] lr: 5.000000e-04 eta: 2:41:21 time: 0.220805 data_time: 0.024658 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.850158 loss: 0.000560 2022/10/20 16:56:59 - mmengine - INFO - Epoch(train) [145][500/586] lr: 5.000000e-04 eta: 2:41:08 time: 0.224822 data_time: 0.024470 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.811748 loss: 0.000556 2022/10/20 16:57:10 - mmengine - INFO - Epoch(train) [145][550/586] lr: 5.000000e-04 eta: 2:40:55 time: 0.224734 data_time: 0.026627 memory: 7326 loss_kpt: 0.000567 acc_pose: 0.794441 loss: 0.000567 2022/10/20 16:57:18 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:57:26 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:57:30 - mmengine - INFO - Epoch(train) [146][50/586] lr: 5.000000e-04 eta: 2:40:29 time: 0.240278 data_time: 0.034291 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.836772 loss: 0.000568 2022/10/20 16:57:41 - mmengine - INFO - Epoch(train) [146][100/586] lr: 5.000000e-04 eta: 2:40:15 time: 0.222649 data_time: 0.023593 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.828493 loss: 0.000553 2022/10/20 16:57:53 - mmengine - INFO - Epoch(train) [146][150/586] lr: 5.000000e-04 eta: 2:40:02 time: 0.228655 data_time: 0.023901 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.830260 loss: 0.000563 2022/10/20 16:58:04 - mmengine - INFO - Epoch(train) [146][200/586] lr: 5.000000e-04 eta: 2:39:49 time: 0.232423 data_time: 0.028132 memory: 7326 loss_kpt: 0.000562 acc_pose: 0.871440 loss: 0.000562 2022/10/20 16:58:16 - mmengine - INFO - Epoch(train) [146][250/586] lr: 5.000000e-04 eta: 2:39:36 time: 0.224537 data_time: 0.022692 memory: 7326 loss_kpt: 0.000548 acc_pose: 0.775766 loss: 0.000548 2022/10/20 16:58:27 - mmengine - INFO - Epoch(train) [146][300/586] lr: 5.000000e-04 eta: 2:39:22 time: 0.222172 data_time: 0.024455 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.817910 loss: 0.000571 2022/10/20 16:58:38 - mmengine - INFO - Epoch(train) [146][350/586] lr: 5.000000e-04 eta: 2:39:09 time: 0.223963 data_time: 0.024411 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.888872 loss: 0.000563 2022/10/20 16:58:50 - mmengine - INFO - Epoch(train) [146][400/586] lr: 5.000000e-04 eta: 2:38:56 time: 0.231068 data_time: 0.022999 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.814734 loss: 0.000572 2022/10/20 16:59:01 - mmengine - INFO - Epoch(train) [146][450/586] lr: 5.000000e-04 eta: 2:38:43 time: 0.228100 data_time: 0.027684 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.797013 loss: 0.000558 2022/10/20 16:59:12 - mmengine - INFO - Epoch(train) [146][500/586] lr: 5.000000e-04 eta: 2:38:30 time: 0.225232 data_time: 0.023682 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.841755 loss: 0.000560 2022/10/20 16:59:23 - mmengine - INFO - Epoch(train) [146][550/586] lr: 5.000000e-04 eta: 2:38:16 time: 0.222880 data_time: 0.024691 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.856300 loss: 0.000561 2022/10/20 16:59:31 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 16:59:43 - mmengine - INFO - Epoch(train) [147][50/586] lr: 5.000000e-04 eta: 2:37:50 time: 0.231476 data_time: 0.031327 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.832747 loss: 0.000565 2022/10/20 16:59:55 - mmengine - INFO - Epoch(train) [147][100/586] lr: 5.000000e-04 eta: 2:37:37 time: 0.230657 data_time: 0.028418 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.839474 loss: 0.000564 2022/10/20 17:00:06 - mmengine - INFO - Epoch(train) [147][150/586] lr: 5.000000e-04 eta: 2:37:24 time: 0.227088 data_time: 0.022914 memory: 7326 loss_kpt: 0.000552 acc_pose: 0.907318 loss: 0.000552 2022/10/20 17:00:17 - mmengine - INFO - Epoch(train) [147][200/586] lr: 5.000000e-04 eta: 2:37:10 time: 0.223449 data_time: 0.025901 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.849079 loss: 0.000557 2022/10/20 17:00:28 - mmengine - INFO - Epoch(train) [147][250/586] lr: 5.000000e-04 eta: 2:36:57 time: 0.224642 data_time: 0.022579 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.821168 loss: 0.000563 2022/10/20 17:00:40 - mmengine - INFO - Epoch(train) [147][300/586] lr: 5.000000e-04 eta: 2:36:44 time: 0.225907 data_time: 0.030166 memory: 7326 loss_kpt: 0.000581 acc_pose: 0.843644 loss: 0.000581 2022/10/20 17:00:51 - mmengine - INFO - Epoch(train) [147][350/586] lr: 5.000000e-04 eta: 2:36:31 time: 0.229011 data_time: 0.024172 memory: 7326 loss_kpt: 0.000582 acc_pose: 0.841025 loss: 0.000582 2022/10/20 17:01:03 - mmengine - INFO - Epoch(train) [147][400/586] lr: 5.000000e-04 eta: 2:36:18 time: 0.230622 data_time: 0.025392 memory: 7326 loss_kpt: 0.000554 acc_pose: 0.868909 loss: 0.000554 2022/10/20 17:01:13 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:01:14 - mmengine - INFO - Epoch(train) [147][450/586] lr: 5.000000e-04 eta: 2:36:04 time: 0.224787 data_time: 0.024047 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.859093 loss: 0.000561 2022/10/20 17:01:25 - mmengine - INFO - Epoch(train) [147][500/586] lr: 5.000000e-04 eta: 2:35:51 time: 0.223418 data_time: 0.025264 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.915667 loss: 0.000568 2022/10/20 17:01:37 - mmengine - INFO - Epoch(train) [147][550/586] lr: 5.000000e-04 eta: 2:35:38 time: 0.232126 data_time: 0.027634 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.862513 loss: 0.000561 2022/10/20 17:01:45 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:01:57 - mmengine - INFO - Epoch(train) [148][50/586] lr: 5.000000e-04 eta: 2:35:12 time: 0.233058 data_time: 0.031544 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.883465 loss: 0.000559 2022/10/20 17:02:08 - mmengine - INFO - Epoch(train) [148][100/586] lr: 5.000000e-04 eta: 2:34:59 time: 0.223520 data_time: 0.023493 memory: 7326 loss_kpt: 0.000543 acc_pose: 0.900078 loss: 0.000543 2022/10/20 17:02:19 - mmengine - INFO - Epoch(train) [148][150/586] lr: 5.000000e-04 eta: 2:34:46 time: 0.229509 data_time: 0.025210 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.891346 loss: 0.000563 2022/10/20 17:02:31 - mmengine - INFO - Epoch(train) [148][200/586] lr: 5.000000e-04 eta: 2:34:33 time: 0.229166 data_time: 0.022037 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.844590 loss: 0.000553 2022/10/20 17:02:42 - mmengine - INFO - Epoch(train) [148][250/586] lr: 5.000000e-04 eta: 2:34:19 time: 0.229579 data_time: 0.023630 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.800333 loss: 0.000563 2022/10/20 17:02:53 - mmengine - INFO - Epoch(train) [148][300/586] lr: 5.000000e-04 eta: 2:34:06 time: 0.225460 data_time: 0.025423 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.876730 loss: 0.000556 2022/10/20 17:03:05 - mmengine - INFO - Epoch(train) [148][350/586] lr: 5.000000e-04 eta: 2:33:53 time: 0.227294 data_time: 0.024776 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.828738 loss: 0.000570 2022/10/20 17:03:16 - mmengine - INFO - Epoch(train) [148][400/586] lr: 5.000000e-04 eta: 2:33:40 time: 0.230546 data_time: 0.024107 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.858526 loss: 0.000563 2022/10/20 17:03:28 - mmengine - INFO - Epoch(train) [148][450/586] lr: 5.000000e-04 eta: 2:33:27 time: 0.228170 data_time: 0.027069 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.883745 loss: 0.000563 2022/10/20 17:03:39 - mmengine - INFO - Epoch(train) [148][500/586] lr: 5.000000e-04 eta: 2:33:14 time: 0.227546 data_time: 0.024955 memory: 7326 loss_kpt: 0.000573 acc_pose: 0.870718 loss: 0.000573 2022/10/20 17:03:50 - mmengine - INFO - Epoch(train) [148][550/586] lr: 5.000000e-04 eta: 2:33:00 time: 0.222706 data_time: 0.025083 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.858660 loss: 0.000563 2022/10/20 17:03:58 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:04:10 - mmengine - INFO - Epoch(train) [149][50/586] lr: 5.000000e-04 eta: 2:32:34 time: 0.228025 data_time: 0.029711 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.810224 loss: 0.000563 2022/10/20 17:04:21 - mmengine - INFO - Epoch(train) [149][100/586] lr: 5.000000e-04 eta: 2:32:21 time: 0.232923 data_time: 0.026993 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.881631 loss: 0.000563 2022/10/20 17:04:33 - mmengine - INFO - Epoch(train) [149][150/586] lr: 5.000000e-04 eta: 2:32:08 time: 0.228568 data_time: 0.022940 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.813564 loss: 0.000559 2022/10/20 17:04:44 - mmengine - INFO - Epoch(train) [149][200/586] lr: 5.000000e-04 eta: 2:31:55 time: 0.227971 data_time: 0.022040 memory: 7326 loss_kpt: 0.000581 acc_pose: 0.858627 loss: 0.000581 2022/10/20 17:04:56 - mmengine - INFO - Epoch(train) [149][250/586] lr: 5.000000e-04 eta: 2:31:42 time: 0.225483 data_time: 0.024792 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.855724 loss: 0.000564 2022/10/20 17:05:01 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:05:07 - mmengine - INFO - Epoch(train) [149][300/586] lr: 5.000000e-04 eta: 2:31:29 time: 0.225713 data_time: 0.023924 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.840590 loss: 0.000563 2022/10/20 17:05:18 - mmengine - INFO - Epoch(train) [149][350/586] lr: 5.000000e-04 eta: 2:31:16 time: 0.231869 data_time: 0.022893 memory: 7326 loss_kpt: 0.000548 acc_pose: 0.888289 loss: 0.000548 2022/10/20 17:05:30 - mmengine - INFO - Epoch(train) [149][400/586] lr: 5.000000e-04 eta: 2:31:03 time: 0.225638 data_time: 0.025078 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.867203 loss: 0.000561 2022/10/20 17:05:41 - mmengine - INFO - Epoch(train) [149][450/586] lr: 5.000000e-04 eta: 2:30:49 time: 0.219649 data_time: 0.022790 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.890273 loss: 0.000571 2022/10/20 17:05:52 - mmengine - INFO - Epoch(train) [149][500/586] lr: 5.000000e-04 eta: 2:30:36 time: 0.226933 data_time: 0.028081 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.889026 loss: 0.000560 2022/10/20 17:06:04 - mmengine - INFO - Epoch(train) [149][550/586] lr: 5.000000e-04 eta: 2:30:23 time: 0.229269 data_time: 0.022083 memory: 7326 loss_kpt: 0.000591 acc_pose: 0.806305 loss: 0.000591 2022/10/20 17:06:12 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:06:24 - mmengine - INFO - Epoch(train) [150][50/586] lr: 5.000000e-04 eta: 2:29:58 time: 0.240161 data_time: 0.030243 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.891022 loss: 0.000556 2022/10/20 17:06:35 - mmengine - INFO - Epoch(train) [150][100/586] lr: 5.000000e-04 eta: 2:29:44 time: 0.225365 data_time: 0.024260 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.883643 loss: 0.000560 2022/10/20 17:06:46 - mmengine - INFO - Epoch(train) [150][150/586] lr: 5.000000e-04 eta: 2:29:31 time: 0.225537 data_time: 0.023821 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.890500 loss: 0.000564 2022/10/20 17:06:58 - mmengine - INFO - Epoch(train) [150][200/586] lr: 5.000000e-04 eta: 2:29:18 time: 0.227554 data_time: 0.023105 memory: 7326 loss_kpt: 0.000549 acc_pose: 0.874830 loss: 0.000549 2022/10/20 17:07:09 - mmengine - INFO - Epoch(train) [150][250/586] lr: 5.000000e-04 eta: 2:29:05 time: 0.227222 data_time: 0.027868 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.868640 loss: 0.000566 2022/10/20 17:07:20 - mmengine - INFO - Epoch(train) [150][300/586] lr: 5.000000e-04 eta: 2:28:52 time: 0.223163 data_time: 0.025874 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.884075 loss: 0.000570 2022/10/20 17:07:32 - mmengine - INFO - Epoch(train) [150][350/586] lr: 5.000000e-04 eta: 2:28:39 time: 0.223467 data_time: 0.023606 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.873509 loss: 0.000558 2022/10/20 17:07:43 - mmengine - INFO - Epoch(train) [150][400/586] lr: 5.000000e-04 eta: 2:28:26 time: 0.229535 data_time: 0.022848 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.882240 loss: 0.000547 2022/10/20 17:07:54 - mmengine - INFO - Epoch(train) [150][450/586] lr: 5.000000e-04 eta: 2:28:13 time: 0.229328 data_time: 0.030063 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.898404 loss: 0.000563 2022/10/20 17:08:06 - mmengine - INFO - Epoch(train) [150][500/586] lr: 5.000000e-04 eta: 2:27:59 time: 0.222319 data_time: 0.024803 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.886558 loss: 0.000566 2022/10/20 17:08:17 - mmengine - INFO - Epoch(train) [150][550/586] lr: 5.000000e-04 eta: 2:27:46 time: 0.224506 data_time: 0.023515 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.859544 loss: 0.000559 2022/10/20 17:08:25 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:08:25 - mmengine - INFO - Saving checkpoint at 150 epochs 2022/10/20 17:08:35 - mmengine - INFO - Epoch(val) [150][50/407] eta: 0:00:43 time: 0.121264 data_time: 0.038664 memory: 7326 2022/10/20 17:08:41 - mmengine - INFO - Epoch(val) [150][100/407] eta: 0:00:35 time: 0.117223 data_time: 0.032921 memory: 1680 2022/10/20 17:08:47 - mmengine - INFO - Epoch(val) [150][150/407] eta: 0:00:29 time: 0.116049 data_time: 0.031745 memory: 1680 2022/10/20 17:08:53 - mmengine - INFO - Epoch(val) [150][200/407] eta: 0:00:23 time: 0.113051 data_time: 0.029436 memory: 1680 2022/10/20 17:08:58 - mmengine - INFO - Epoch(val) [150][250/407] eta: 0:00:17 time: 0.112803 data_time: 0.030498 memory: 1680 2022/10/20 17:09:04 - mmengine - INFO - Epoch(val) [150][300/407] eta: 0:00:12 time: 0.116086 data_time: 0.034655 memory: 1680 2022/10/20 17:09:10 - mmengine - INFO - Epoch(val) [150][350/407] eta: 0:00:06 time: 0.119275 data_time: 0.030013 memory: 1680 2022/10/20 17:09:15 - mmengine - INFO - Epoch(val) [150][400/407] eta: 0:00:00 time: 0.099445 data_time: 0.021785 memory: 1680 2022/10/20 17:09:48 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 17:10:01 - mmengine - INFO - Epoch(val) [150][407/407] coco/AP: 0.724792 coco/AP .5: 0.898104 coco/AP .75: 0.802217 coco/AP (M): 0.686004 coco/AP (L): 0.796096 coco/AR: 0.780526 coco/AR .5: 0.937815 coco/AR .75: 0.849969 coco/AR (M): 0.735646 coco/AR (L): 0.845448 2022/10/20 17:10:12 - mmengine - INFO - Epoch(train) [151][50/586] lr: 5.000000e-04 eta: 2:27:21 time: 0.231400 data_time: 0.030510 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.870569 loss: 0.000564 2022/10/20 17:10:24 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:10:24 - mmengine - INFO - Epoch(train) [151][100/586] lr: 5.000000e-04 eta: 2:27:08 time: 0.233775 data_time: 0.027872 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.843206 loss: 0.000561 2022/10/20 17:10:35 - mmengine - INFO - Epoch(train) [151][150/586] lr: 5.000000e-04 eta: 2:26:54 time: 0.225050 data_time: 0.025782 memory: 7326 loss_kpt: 0.000575 acc_pose: 0.846159 loss: 0.000575 2022/10/20 17:10:47 - mmengine - INFO - Epoch(train) [151][200/586] lr: 5.000000e-04 eta: 2:26:41 time: 0.231373 data_time: 0.026847 memory: 7326 loss_kpt: 0.000576 acc_pose: 0.847784 loss: 0.000576 2022/10/20 17:10:58 - mmengine - INFO - Epoch(train) [151][250/586] lr: 5.000000e-04 eta: 2:26:28 time: 0.224570 data_time: 0.023503 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.859465 loss: 0.000560 2022/10/20 17:11:09 - mmengine - INFO - Epoch(train) [151][300/586] lr: 5.000000e-04 eta: 2:26:15 time: 0.224431 data_time: 0.025588 memory: 7326 loss_kpt: 0.000554 acc_pose: 0.910674 loss: 0.000554 2022/10/20 17:11:21 - mmengine - INFO - Epoch(train) [151][350/586] lr: 5.000000e-04 eta: 2:26:02 time: 0.236869 data_time: 0.023894 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.873592 loss: 0.000566 2022/10/20 17:11:32 - mmengine - INFO - Epoch(train) [151][400/586] lr: 5.000000e-04 eta: 2:25:49 time: 0.223165 data_time: 0.023076 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.879516 loss: 0.000561 2022/10/20 17:11:44 - mmengine - INFO - Epoch(train) [151][450/586] lr: 5.000000e-04 eta: 2:25:36 time: 0.226483 data_time: 0.027412 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.891336 loss: 0.000561 2022/10/20 17:11:55 - mmengine - INFO - Epoch(train) [151][500/586] lr: 5.000000e-04 eta: 2:25:23 time: 0.228247 data_time: 0.025324 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.876683 loss: 0.000563 2022/10/20 17:12:07 - mmengine - INFO - Epoch(train) [151][550/586] lr: 5.000000e-04 eta: 2:25:10 time: 0.231452 data_time: 0.023870 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.752705 loss: 0.000563 2022/10/20 17:12:15 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:12:27 - mmengine - INFO - Epoch(train) [152][50/586] lr: 5.000000e-04 eta: 2:24:45 time: 0.239492 data_time: 0.030169 memory: 7326 loss_kpt: 0.000541 acc_pose: 0.888428 loss: 0.000541 2022/10/20 17:12:38 - mmengine - INFO - Epoch(train) [152][100/586] lr: 5.000000e-04 eta: 2:24:31 time: 0.218965 data_time: 0.024792 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.855317 loss: 0.000564 2022/10/20 17:12:49 - mmengine - INFO - Epoch(train) [152][150/586] lr: 5.000000e-04 eta: 2:24:18 time: 0.226242 data_time: 0.026737 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.859012 loss: 0.000566 2022/10/20 17:13:01 - mmengine - INFO - Epoch(train) [152][200/586] lr: 5.000000e-04 eta: 2:24:05 time: 0.226861 data_time: 0.024432 memory: 7326 loss_kpt: 0.000543 acc_pose: 0.905652 loss: 0.000543 2022/10/20 17:13:12 - mmengine - INFO - Epoch(train) [152][250/586] lr: 5.000000e-04 eta: 2:23:52 time: 0.230930 data_time: 0.023521 memory: 7326 loss_kpt: 0.000555 acc_pose: 0.881148 loss: 0.000555 2022/10/20 17:13:24 - mmengine - INFO - Epoch(train) [152][300/586] lr: 5.000000e-04 eta: 2:23:39 time: 0.226611 data_time: 0.023741 memory: 7326 loss_kpt: 0.000555 acc_pose: 0.912824 loss: 0.000555 2022/10/20 17:13:35 - mmengine - INFO - Epoch(train) [152][350/586] lr: 5.000000e-04 eta: 2:23:26 time: 0.219323 data_time: 0.024695 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.929010 loss: 0.000551 2022/10/20 17:13:46 - mmengine - INFO - Epoch(train) [152][400/586] lr: 5.000000e-04 eta: 2:23:13 time: 0.224742 data_time: 0.023685 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.794688 loss: 0.000559 2022/10/20 17:13:58 - mmengine - INFO - Epoch(train) [152][450/586] lr: 5.000000e-04 eta: 2:23:00 time: 0.235335 data_time: 0.023471 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.889208 loss: 0.000564 2022/10/20 17:14:09 - mmengine - INFO - Epoch(train) [152][500/586] lr: 5.000000e-04 eta: 2:22:47 time: 0.222372 data_time: 0.023360 memory: 7326 loss_kpt: 0.000538 acc_pose: 0.829447 loss: 0.000538 2022/10/20 17:14:12 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:14:20 - mmengine - INFO - Epoch(train) [152][550/586] lr: 5.000000e-04 eta: 2:22:34 time: 0.227605 data_time: 0.023206 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.850256 loss: 0.000571 2022/10/20 17:14:28 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:14:40 - mmengine - INFO - Epoch(train) [153][50/586] lr: 5.000000e-04 eta: 2:22:08 time: 0.227030 data_time: 0.033026 memory: 7326 loss_kpt: 0.000544 acc_pose: 0.854652 loss: 0.000544 2022/10/20 17:14:51 - mmengine - INFO - Epoch(train) [153][100/586] lr: 5.000000e-04 eta: 2:21:55 time: 0.232536 data_time: 0.023225 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.885057 loss: 0.000557 2022/10/20 17:15:03 - mmengine - INFO - Epoch(train) [153][150/586] lr: 5.000000e-04 eta: 2:21:42 time: 0.228241 data_time: 0.025954 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.792159 loss: 0.000551 2022/10/20 17:15:14 - mmengine - INFO - Epoch(train) [153][200/586] lr: 5.000000e-04 eta: 2:21:29 time: 0.227845 data_time: 0.029704 memory: 7326 loss_kpt: 0.000549 acc_pose: 0.901192 loss: 0.000549 2022/10/20 17:15:25 - mmengine - INFO - Epoch(train) [153][250/586] lr: 5.000000e-04 eta: 2:21:16 time: 0.224401 data_time: 0.022861 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.860028 loss: 0.000559 2022/10/20 17:15:37 - mmengine - INFO - Epoch(train) [153][300/586] lr: 5.000000e-04 eta: 2:21:03 time: 0.224235 data_time: 0.022945 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.886996 loss: 0.000560 2022/10/20 17:15:48 - mmengine - INFO - Epoch(train) [153][350/586] lr: 5.000000e-04 eta: 2:20:50 time: 0.235908 data_time: 0.026903 memory: 7326 loss_kpt: 0.000540 acc_pose: 0.909704 loss: 0.000540 2022/10/20 17:16:00 - mmengine - INFO - Epoch(train) [153][400/586] lr: 5.000000e-04 eta: 2:20:37 time: 0.225257 data_time: 0.027777 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.865680 loss: 0.000572 2022/10/20 17:16:11 - mmengine - INFO - Epoch(train) [153][450/586] lr: 5.000000e-04 eta: 2:20:24 time: 0.222208 data_time: 0.023304 memory: 7326 loss_kpt: 0.000538 acc_pose: 0.841906 loss: 0.000538 2022/10/20 17:16:22 - mmengine - INFO - Epoch(train) [153][500/586] lr: 5.000000e-04 eta: 2:20:11 time: 0.226429 data_time: 0.023887 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.875136 loss: 0.000558 2022/10/20 17:16:33 - mmengine - INFO - Epoch(train) [153][550/586] lr: 5.000000e-04 eta: 2:19:58 time: 0.226482 data_time: 0.023857 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.817938 loss: 0.000556 2022/10/20 17:16:42 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:16:53 - mmengine - INFO - Epoch(train) [154][50/586] lr: 5.000000e-04 eta: 2:19:33 time: 0.232452 data_time: 0.030809 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.826413 loss: 0.000568 2022/10/20 17:17:05 - mmengine - INFO - Epoch(train) [154][100/586] lr: 5.000000e-04 eta: 2:19:20 time: 0.224375 data_time: 0.025264 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.907521 loss: 0.000556 2022/10/20 17:17:16 - mmengine - INFO - Epoch(train) [154][150/586] lr: 5.000000e-04 eta: 2:19:07 time: 0.228536 data_time: 0.026208 memory: 7326 loss_kpt: 0.000562 acc_pose: 0.830172 loss: 0.000562 2022/10/20 17:17:27 - mmengine - INFO - Epoch(train) [154][200/586] lr: 5.000000e-04 eta: 2:18:54 time: 0.229788 data_time: 0.024940 memory: 7326 loss_kpt: 0.000567 acc_pose: 0.855637 loss: 0.000567 2022/10/20 17:17:39 - mmengine - INFO - Epoch(train) [154][250/586] lr: 5.000000e-04 eta: 2:18:41 time: 0.231876 data_time: 0.024314 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.863127 loss: 0.000557 2022/10/20 17:17:50 - mmengine - INFO - Epoch(train) [154][300/586] lr: 5.000000e-04 eta: 2:18:28 time: 0.225399 data_time: 0.025501 memory: 7326 loss_kpt: 0.000555 acc_pose: 0.821039 loss: 0.000555 2022/10/20 17:18:00 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:18:02 - mmengine - INFO - Epoch(train) [154][350/586] lr: 5.000000e-04 eta: 2:18:15 time: 0.222923 data_time: 0.026429 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.870035 loss: 0.000564 2022/10/20 17:18:13 - mmengine - INFO - Epoch(train) [154][400/586] lr: 5.000000e-04 eta: 2:18:02 time: 0.227065 data_time: 0.024525 memory: 7326 loss_kpt: 0.000562 acc_pose: 0.809156 loss: 0.000562 2022/10/20 17:18:24 - mmengine - INFO - Epoch(train) [154][450/586] lr: 5.000000e-04 eta: 2:17:49 time: 0.230837 data_time: 0.026835 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.840727 loss: 0.000547 2022/10/20 17:18:36 - mmengine - INFO - Epoch(train) [154][500/586] lr: 5.000000e-04 eta: 2:17:36 time: 0.228027 data_time: 0.024869 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.933309 loss: 0.000561 2022/10/20 17:18:47 - mmengine - INFO - Epoch(train) [154][550/586] lr: 5.000000e-04 eta: 2:17:23 time: 0.226947 data_time: 0.023900 memory: 7326 loss_kpt: 0.000526 acc_pose: 0.856089 loss: 0.000526 2022/10/20 17:18:55 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:19:07 - mmengine - INFO - Epoch(train) [155][50/586] lr: 5.000000e-04 eta: 2:16:58 time: 0.238505 data_time: 0.032496 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.809495 loss: 0.000551 2022/10/20 17:19:19 - mmengine - INFO - Epoch(train) [155][100/586] lr: 5.000000e-04 eta: 2:16:45 time: 0.228616 data_time: 0.026453 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.866357 loss: 0.000547 2022/10/20 17:19:30 - mmengine - INFO - Epoch(train) [155][150/586] lr: 5.000000e-04 eta: 2:16:32 time: 0.225756 data_time: 0.026255 memory: 7326 loss_kpt: 0.000543 acc_pose: 0.872694 loss: 0.000543 2022/10/20 17:19:41 - mmengine - INFO - Epoch(train) [155][200/586] lr: 5.000000e-04 eta: 2:16:19 time: 0.229070 data_time: 0.028045 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.830897 loss: 0.000561 2022/10/20 17:19:53 - mmengine - INFO - Epoch(train) [155][250/586] lr: 5.000000e-04 eta: 2:16:06 time: 0.225014 data_time: 0.025546 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.885535 loss: 0.000547 2022/10/20 17:20:04 - mmengine - INFO - Epoch(train) [155][300/586] lr: 5.000000e-04 eta: 2:15:53 time: 0.228963 data_time: 0.023394 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.867077 loss: 0.000565 2022/10/20 17:20:16 - mmengine - INFO - Epoch(train) [155][350/586] lr: 5.000000e-04 eta: 2:15:40 time: 0.229468 data_time: 0.030128 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.893977 loss: 0.000551 2022/10/20 17:20:27 - mmengine - INFO - Epoch(train) [155][400/586] lr: 5.000000e-04 eta: 2:15:27 time: 0.228931 data_time: 0.024634 memory: 7326 loss_kpt: 0.000554 acc_pose: 0.882198 loss: 0.000554 2022/10/20 17:20:38 - mmengine - INFO - Epoch(train) [155][450/586] lr: 5.000000e-04 eta: 2:15:14 time: 0.220231 data_time: 0.023785 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.865558 loss: 0.000559 2022/10/20 17:20:49 - mmengine - INFO - Epoch(train) [155][500/586] lr: 5.000000e-04 eta: 2:15:01 time: 0.222788 data_time: 0.023002 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.754866 loss: 0.000557 2022/10/20 17:21:01 - mmengine - INFO - Epoch(train) [155][550/586] lr: 5.000000e-04 eta: 2:14:49 time: 0.239283 data_time: 0.023677 memory: 7326 loss_kpt: 0.000540 acc_pose: 0.839570 loss: 0.000540 2022/10/20 17:21:09 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:21:21 - mmengine - INFO - Epoch(train) [156][50/586] lr: 5.000000e-04 eta: 2:14:24 time: 0.239956 data_time: 0.037879 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.867712 loss: 0.000556 2022/10/20 17:21:32 - mmengine - INFO - Epoch(train) [156][100/586] lr: 5.000000e-04 eta: 2:14:11 time: 0.221429 data_time: 0.026104 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.827017 loss: 0.000561 2022/10/20 17:21:44 - mmengine - INFO - Epoch(train) [156][150/586] lr: 5.000000e-04 eta: 2:13:58 time: 0.227049 data_time: 0.027862 memory: 7326 loss_kpt: 0.000548 acc_pose: 0.856243 loss: 0.000548 2022/10/20 17:21:48 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:21:55 - mmengine - INFO - Epoch(train) [156][200/586] lr: 5.000000e-04 eta: 2:13:45 time: 0.230402 data_time: 0.024491 memory: 7326 loss_kpt: 0.000569 acc_pose: 0.891816 loss: 0.000569 2022/10/20 17:22:06 - mmengine - INFO - Epoch(train) [156][250/586] lr: 5.000000e-04 eta: 2:13:32 time: 0.224972 data_time: 0.025794 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.846579 loss: 0.000547 2022/10/20 17:22:18 - mmengine - INFO - Epoch(train) [156][300/586] lr: 5.000000e-04 eta: 2:13:19 time: 0.229966 data_time: 0.025323 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.828203 loss: 0.000560 2022/10/20 17:22:29 - mmengine - INFO - Epoch(train) [156][350/586] lr: 5.000000e-04 eta: 2:13:06 time: 0.223473 data_time: 0.025745 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.854324 loss: 0.000556 2022/10/20 17:22:40 - mmengine - INFO - Epoch(train) [156][400/586] lr: 5.000000e-04 eta: 2:12:53 time: 0.225867 data_time: 0.023384 memory: 7326 loss_kpt: 0.000554 acc_pose: 0.874308 loss: 0.000554 2022/10/20 17:22:52 - mmengine - INFO - Epoch(train) [156][450/586] lr: 5.000000e-04 eta: 2:12:40 time: 0.229120 data_time: 0.026826 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.812662 loss: 0.000558 2022/10/20 17:23:03 - mmengine - INFO - Epoch(train) [156][500/586] lr: 5.000000e-04 eta: 2:12:27 time: 0.227482 data_time: 0.024358 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.829911 loss: 0.000553 2022/10/20 17:23:15 - mmengine - INFO - Epoch(train) [156][550/586] lr: 5.000000e-04 eta: 2:12:14 time: 0.229363 data_time: 0.022544 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.787399 loss: 0.000574 2022/10/20 17:23:23 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:23:35 - mmengine - INFO - Epoch(train) [157][50/586] lr: 5.000000e-04 eta: 2:11:49 time: 0.244774 data_time: 0.030202 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.836144 loss: 0.000559 2022/10/20 17:23:46 - mmengine - INFO - Epoch(train) [157][100/586] lr: 5.000000e-04 eta: 2:11:37 time: 0.227478 data_time: 0.028051 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.776671 loss: 0.000557 2022/10/20 17:23:58 - mmengine - INFO - Epoch(train) [157][150/586] lr: 5.000000e-04 eta: 2:11:24 time: 0.225355 data_time: 0.023704 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.889331 loss: 0.000551 2022/10/20 17:24:09 - mmengine - INFO - Epoch(train) [157][200/586] lr: 5.000000e-04 eta: 2:11:11 time: 0.235718 data_time: 0.027272 memory: 7326 loss_kpt: 0.000543 acc_pose: 0.892083 loss: 0.000543 2022/10/20 17:24:21 - mmengine - INFO - Epoch(train) [157][250/586] lr: 5.000000e-04 eta: 2:10:58 time: 0.229331 data_time: 0.023818 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.877691 loss: 0.000551 2022/10/20 17:24:32 - mmengine - INFO - Epoch(train) [157][300/586] lr: 5.000000e-04 eta: 2:10:45 time: 0.224365 data_time: 0.026162 memory: 7326 loss_kpt: 0.000535 acc_pose: 0.898109 loss: 0.000535 2022/10/20 17:24:43 - mmengine - INFO - Epoch(train) [157][350/586] lr: 5.000000e-04 eta: 2:10:32 time: 0.225392 data_time: 0.029619 memory: 7326 loss_kpt: 0.000534 acc_pose: 0.926158 loss: 0.000534 2022/10/20 17:24:55 - mmengine - INFO - Epoch(train) [157][400/586] lr: 5.000000e-04 eta: 2:10:19 time: 0.232480 data_time: 0.022829 memory: 7326 loss_kpt: 0.000567 acc_pose: 0.868539 loss: 0.000567 2022/10/20 17:25:06 - mmengine - INFO - Epoch(train) [157][450/586] lr: 5.000000e-04 eta: 2:10:06 time: 0.219640 data_time: 0.025565 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.850833 loss: 0.000563 2022/10/20 17:25:17 - mmengine - INFO - Epoch(train) [157][500/586] lr: 5.000000e-04 eta: 2:09:53 time: 0.220626 data_time: 0.024172 memory: 7326 loss_kpt: 0.000570 acc_pose: 0.851472 loss: 0.000570 2022/10/20 17:25:29 - mmengine - INFO - Epoch(train) [157][550/586] lr: 5.000000e-04 eta: 2:09:40 time: 0.229219 data_time: 0.023899 memory: 7326 loss_kpt: 0.000555 acc_pose: 0.845361 loss: 0.000555 2022/10/20 17:25:36 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:25:36 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:25:48 - mmengine - INFO - Epoch(train) [158][50/586] lr: 5.000000e-04 eta: 2:09:16 time: 0.236796 data_time: 0.031013 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.923278 loss: 0.000547 2022/10/20 17:25:59 - mmengine - INFO - Epoch(train) [158][100/586] lr: 5.000000e-04 eta: 2:09:03 time: 0.220228 data_time: 0.026850 memory: 7326 loss_kpt: 0.000542 acc_pose: 0.837345 loss: 0.000542 2022/10/20 17:26:11 - mmengine - INFO - Epoch(train) [158][150/586] lr: 5.000000e-04 eta: 2:08:50 time: 0.222626 data_time: 0.024088 memory: 7326 loss_kpt: 0.000536 acc_pose: 0.883006 loss: 0.000536 2022/10/20 17:26:22 - mmengine - INFO - Epoch(train) [158][200/586] lr: 5.000000e-04 eta: 2:08:37 time: 0.228413 data_time: 0.022986 memory: 7326 loss_kpt: 0.000562 acc_pose: 0.873277 loss: 0.000562 2022/10/20 17:26:34 - mmengine - INFO - Epoch(train) [158][250/586] lr: 5.000000e-04 eta: 2:08:24 time: 0.232314 data_time: 0.025195 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.858155 loss: 0.000547 2022/10/20 17:26:45 - mmengine - INFO - Epoch(train) [158][300/586] lr: 5.000000e-04 eta: 2:08:11 time: 0.228563 data_time: 0.022449 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.846922 loss: 0.000556 2022/10/20 17:26:56 - mmengine - INFO - Epoch(train) [158][350/586] lr: 5.000000e-04 eta: 2:07:58 time: 0.221905 data_time: 0.024954 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.879790 loss: 0.000551 2022/10/20 17:27:08 - mmengine - INFO - Epoch(train) [158][400/586] lr: 5.000000e-04 eta: 2:07:45 time: 0.228846 data_time: 0.022627 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.843556 loss: 0.000558 2022/10/20 17:27:19 - mmengine - INFO - Epoch(train) [158][450/586] lr: 5.000000e-04 eta: 2:07:32 time: 0.225013 data_time: 0.024163 memory: 7326 loss_kpt: 0.000545 acc_pose: 0.924833 loss: 0.000545 2022/10/20 17:27:30 - mmengine - INFO - Epoch(train) [158][500/586] lr: 5.000000e-04 eta: 2:07:19 time: 0.225610 data_time: 0.024997 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.781486 loss: 0.000547 2022/10/20 17:27:42 - mmengine - INFO - Epoch(train) [158][550/586] lr: 5.000000e-04 eta: 2:07:07 time: 0.227177 data_time: 0.024194 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.913246 loss: 0.000560 2022/10/20 17:27:49 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:28:01 - mmengine - INFO - Epoch(train) [159][50/586] lr: 5.000000e-04 eta: 2:06:42 time: 0.232632 data_time: 0.031839 memory: 7326 loss_kpt: 0.000537 acc_pose: 0.907752 loss: 0.000537 2022/10/20 17:28:12 - mmengine - INFO - Epoch(train) [159][100/586] lr: 5.000000e-04 eta: 2:06:29 time: 0.226810 data_time: 0.022986 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.855422 loss: 0.000557 2022/10/20 17:28:24 - mmengine - INFO - Epoch(train) [159][150/586] lr: 5.000000e-04 eta: 2:06:16 time: 0.224933 data_time: 0.023763 memory: 7326 loss_kpt: 0.000548 acc_pose: 0.839836 loss: 0.000548 2022/10/20 17:28:35 - mmengine - INFO - Epoch(train) [159][200/586] lr: 5.000000e-04 eta: 2:06:03 time: 0.234014 data_time: 0.022690 memory: 7326 loss_kpt: 0.000539 acc_pose: 0.881274 loss: 0.000539 2022/10/20 17:28:46 - mmengine - INFO - Epoch(train) [159][250/586] lr: 5.000000e-04 eta: 2:05:50 time: 0.221439 data_time: 0.028888 memory: 7326 loss_kpt: 0.000555 acc_pose: 0.858546 loss: 0.000555 2022/10/20 17:28:58 - mmengine - INFO - Epoch(train) [159][300/586] lr: 5.000000e-04 eta: 2:05:37 time: 0.229149 data_time: 0.023968 memory: 7326 loss_kpt: 0.000548 acc_pose: 0.884973 loss: 0.000548 2022/10/20 17:29:09 - mmengine - INFO - Epoch(train) [159][350/586] lr: 5.000000e-04 eta: 2:05:25 time: 0.225326 data_time: 0.026694 memory: 7326 loss_kpt: 0.000545 acc_pose: 0.803616 loss: 0.000545 2022/10/20 17:29:21 - mmengine - INFO - Epoch(train) [159][400/586] lr: 5.000000e-04 eta: 2:05:12 time: 0.230425 data_time: 0.024654 memory: 7326 loss_kpt: 0.000538 acc_pose: 0.815992 loss: 0.000538 2022/10/20 17:29:23 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:29:32 - mmengine - INFO - Epoch(train) [159][450/586] lr: 5.000000e-04 eta: 2:04:59 time: 0.221768 data_time: 0.025895 memory: 7326 loss_kpt: 0.000571 acc_pose: 0.830786 loss: 0.000571 2022/10/20 17:29:43 - mmengine - INFO - Epoch(train) [159][500/586] lr: 5.000000e-04 eta: 2:04:46 time: 0.222737 data_time: 0.022791 memory: 7326 loss_kpt: 0.000546 acc_pose: 0.909270 loss: 0.000546 2022/10/20 17:29:54 - mmengine - INFO - Epoch(train) [159][550/586] lr: 5.000000e-04 eta: 2:04:33 time: 0.227168 data_time: 0.023444 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.872336 loss: 0.000553 2022/10/20 17:30:03 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:30:15 - mmengine - INFO - Epoch(train) [160][50/586] lr: 5.000000e-04 eta: 2:04:09 time: 0.239315 data_time: 0.031458 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.840253 loss: 0.000547 2022/10/20 17:30:26 - mmengine - INFO - Epoch(train) [160][100/586] lr: 5.000000e-04 eta: 2:03:56 time: 0.218774 data_time: 0.023935 memory: 7326 loss_kpt: 0.000566 acc_pose: 0.877541 loss: 0.000566 2022/10/20 17:30:37 - mmengine - INFO - Epoch(train) [160][150/586] lr: 5.000000e-04 eta: 2:03:43 time: 0.225196 data_time: 0.025310 memory: 7326 loss_kpt: 0.000552 acc_pose: 0.864267 loss: 0.000552 2022/10/20 17:30:48 - mmengine - INFO - Epoch(train) [160][200/586] lr: 5.000000e-04 eta: 2:03:30 time: 0.229740 data_time: 0.023677 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.858432 loss: 0.000551 2022/10/20 17:31:00 - mmengine - INFO - Epoch(train) [160][250/586] lr: 5.000000e-04 eta: 2:03:17 time: 0.231227 data_time: 0.031192 memory: 7326 loss_kpt: 0.000543 acc_pose: 0.890710 loss: 0.000543 2022/10/20 17:31:11 - mmengine - INFO - Epoch(train) [160][300/586] lr: 5.000000e-04 eta: 2:03:04 time: 0.226486 data_time: 0.023344 memory: 7326 loss_kpt: 0.000550 acc_pose: 0.864465 loss: 0.000550 2022/10/20 17:31:22 - mmengine - INFO - Epoch(train) [160][350/586] lr: 5.000000e-04 eta: 2:02:51 time: 0.221966 data_time: 0.023846 memory: 7326 loss_kpt: 0.000580 acc_pose: 0.831708 loss: 0.000580 2022/10/20 17:31:34 - mmengine - INFO - Epoch(train) [160][400/586] lr: 5.000000e-04 eta: 2:02:38 time: 0.225016 data_time: 0.023479 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.859050 loss: 0.000557 2022/10/20 17:31:45 - mmengine - INFO - Epoch(train) [160][450/586] lr: 5.000000e-04 eta: 2:02:26 time: 0.229731 data_time: 0.023894 memory: 7326 loss_kpt: 0.000560 acc_pose: 0.841804 loss: 0.000560 2022/10/20 17:31:56 - mmengine - INFO - Epoch(train) [160][500/586] lr: 5.000000e-04 eta: 2:02:13 time: 0.222602 data_time: 0.023206 memory: 7326 loss_kpt: 0.000555 acc_pose: 0.851391 loss: 0.000555 2022/10/20 17:32:07 - mmengine - INFO - Epoch(train) [160][550/586] lr: 5.000000e-04 eta: 2:02:00 time: 0.221593 data_time: 0.023945 memory: 7326 loss_kpt: 0.000533 acc_pose: 0.827408 loss: 0.000533 2022/10/20 17:32:16 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:32:16 - mmengine - INFO - Saving checkpoint at 160 epochs 2022/10/20 17:32:26 - mmengine - INFO - Epoch(val) [160][50/407] eta: 0:00:44 time: 0.123478 data_time: 0.040437 memory: 7326 2022/10/20 17:32:32 - mmengine - INFO - Epoch(val) [160][100/407] eta: 0:00:34 time: 0.113986 data_time: 0.031218 memory: 1680 2022/10/20 17:32:37 - mmengine - INFO - Epoch(val) [160][150/407] eta: 0:00:28 time: 0.110565 data_time: 0.026622 memory: 1680 2022/10/20 17:32:43 - mmengine - INFO - Epoch(val) [160][200/407] eta: 0:00:24 time: 0.118549 data_time: 0.035958 memory: 1680 2022/10/20 17:32:49 - mmengine - INFO - Epoch(val) [160][250/407] eta: 0:00:18 time: 0.116814 data_time: 0.033050 memory: 1680 2022/10/20 17:32:55 - mmengine - INFO - Epoch(val) [160][300/407] eta: 0:00:11 time: 0.111764 data_time: 0.029918 memory: 1680 2022/10/20 17:33:01 - mmengine - INFO - Epoch(val) [160][350/407] eta: 0:00:06 time: 0.116552 data_time: 0.034910 memory: 1680 2022/10/20 17:33:06 - mmengine - INFO - Epoch(val) [160][400/407] eta: 0:00:00 time: 0.101933 data_time: 0.023969 memory: 1680 2022/10/20 17:33:38 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 17:33:50 - mmengine - INFO - Epoch(val) [160][407/407] coco/AP: 0.727641 coco/AP .5: 0.900296 coco/AP .75: 0.802836 coco/AP (M): 0.690423 coco/AP (L): 0.794255 coco/AR: 0.782950 coco/AR .5: 0.939389 coco/AR .75: 0.849339 coco/AR (M): 0.739934 coco/AR (L): 0.845002 2022/10/20 17:33:50 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_120.pth is removed 2022/10/20 17:33:53 - mmengine - INFO - The best checkpoint with 0.7276 coco/AP at 160 epoch is saved to best_coco/AP_epoch_160.pth. 2022/10/20 17:34:04 - mmengine - INFO - Epoch(train) [161][50/586] lr: 5.000000e-04 eta: 2:01:35 time: 0.232233 data_time: 0.034816 memory: 7326 loss_kpt: 0.000555 acc_pose: 0.905185 loss: 0.000555 2022/10/20 17:34:16 - mmengine - INFO - Epoch(train) [161][100/586] lr: 5.000000e-04 eta: 2:01:23 time: 0.227952 data_time: 0.025279 memory: 7326 loss_kpt: 0.000538 acc_pose: 0.838774 loss: 0.000538 2022/10/20 17:34:27 - mmengine - INFO - Epoch(train) [161][150/586] lr: 5.000000e-04 eta: 2:01:10 time: 0.227640 data_time: 0.023592 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.777981 loss: 0.000563 2022/10/20 17:34:39 - mmengine - INFO - Epoch(train) [161][200/586] lr: 5.000000e-04 eta: 2:00:57 time: 0.226031 data_time: 0.024165 memory: 7326 loss_kpt: 0.000539 acc_pose: 0.861093 loss: 0.000539 2022/10/20 17:34:48 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:34:50 - mmengine - INFO - Epoch(train) [161][250/586] lr: 5.000000e-04 eta: 2:00:44 time: 0.229032 data_time: 0.029551 memory: 7326 loss_kpt: 0.000550 acc_pose: 0.849471 loss: 0.000550 2022/10/20 17:35:02 - mmengine - INFO - Epoch(train) [161][300/586] lr: 5.000000e-04 eta: 2:00:31 time: 0.230241 data_time: 0.029340 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.885081 loss: 0.000553 2022/10/20 17:35:13 - mmengine - INFO - Epoch(train) [161][350/586] lr: 5.000000e-04 eta: 2:00:19 time: 0.226598 data_time: 0.024873 memory: 7326 loss_kpt: 0.000552 acc_pose: 0.869152 loss: 0.000552 2022/10/20 17:35:25 - mmengine - INFO - Epoch(train) [161][400/586] lr: 5.000000e-04 eta: 2:00:06 time: 0.234223 data_time: 0.022996 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.916422 loss: 0.000556 2022/10/20 17:35:36 - mmengine - INFO - Epoch(train) [161][450/586] lr: 5.000000e-04 eta: 1:59:53 time: 0.218710 data_time: 0.026829 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.842558 loss: 0.000547 2022/10/20 17:35:47 - mmengine - INFO - Epoch(train) [161][500/586] lr: 5.000000e-04 eta: 1:59:40 time: 0.229575 data_time: 0.024803 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.856324 loss: 0.000565 2022/10/20 17:35:59 - mmengine - INFO - Epoch(train) [161][550/586] lr: 5.000000e-04 eta: 1:59:27 time: 0.235449 data_time: 0.024147 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.870632 loss: 0.000563 2022/10/20 17:36:07 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:36:19 - mmengine - INFO - Epoch(train) [162][50/586] lr: 5.000000e-04 eta: 1:59:03 time: 0.236522 data_time: 0.030799 memory: 7326 loss_kpt: 0.000540 acc_pose: 0.932006 loss: 0.000540 2022/10/20 17:36:30 - mmengine - INFO - Epoch(train) [162][100/586] lr: 5.000000e-04 eta: 1:58:50 time: 0.220980 data_time: 0.023447 memory: 7326 loss_kpt: 0.000532 acc_pose: 0.884935 loss: 0.000532 2022/10/20 17:36:41 - mmengine - INFO - Epoch(train) [162][150/586] lr: 5.000000e-04 eta: 1:58:37 time: 0.230048 data_time: 0.027632 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.849379 loss: 0.000547 2022/10/20 17:36:53 - mmengine - INFO - Epoch(train) [162][200/586] lr: 5.000000e-04 eta: 1:58:25 time: 0.235391 data_time: 0.026568 memory: 7326 loss_kpt: 0.000555 acc_pose: 0.887452 loss: 0.000555 2022/10/20 17:37:05 - mmengine - INFO - Epoch(train) [162][250/586] lr: 5.000000e-04 eta: 1:58:12 time: 0.234877 data_time: 0.025499 memory: 7326 loss_kpt: 0.000544 acc_pose: 0.882524 loss: 0.000544 2022/10/20 17:37:16 - mmengine - INFO - Epoch(train) [162][300/586] lr: 5.000000e-04 eta: 1:57:59 time: 0.225931 data_time: 0.024115 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.818221 loss: 0.000559 2022/10/20 17:37:28 - mmengine - INFO - Epoch(train) [162][350/586] lr: 5.000000e-04 eta: 1:57:46 time: 0.225616 data_time: 0.029006 memory: 7326 loss_kpt: 0.000548 acc_pose: 0.888309 loss: 0.000548 2022/10/20 17:37:39 - mmengine - INFO - Epoch(train) [162][400/586] lr: 5.000000e-04 eta: 1:57:34 time: 0.233369 data_time: 0.024043 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.916756 loss: 0.000553 2022/10/20 17:37:51 - mmengine - INFO - Epoch(train) [162][450/586] lr: 5.000000e-04 eta: 1:57:21 time: 0.227345 data_time: 0.025215 memory: 7326 loss_kpt: 0.000554 acc_pose: 0.934711 loss: 0.000554 2022/10/20 17:38:02 - mmengine - INFO - Epoch(train) [162][500/586] lr: 5.000000e-04 eta: 1:57:08 time: 0.223394 data_time: 0.024994 memory: 7326 loss_kpt: 0.000579 acc_pose: 0.835621 loss: 0.000579 2022/10/20 17:38:13 - mmengine - INFO - Epoch(train) [162][550/586] lr: 5.000000e-04 eta: 1:56:55 time: 0.223829 data_time: 0.028337 memory: 7326 loss_kpt: 0.000548 acc_pose: 0.851085 loss: 0.000548 2022/10/20 17:38:21 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:38:33 - mmengine - INFO - Epoch(train) [163][50/586] lr: 5.000000e-04 eta: 1:56:31 time: 0.234014 data_time: 0.033028 memory: 7326 loss_kpt: 0.000550 acc_pose: 0.933837 loss: 0.000550 2022/10/20 17:38:37 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:38:45 - mmengine - INFO - Epoch(train) [163][100/586] lr: 5.000000e-04 eta: 1:56:18 time: 0.232094 data_time: 0.024258 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.847332 loss: 0.000563 2022/10/20 17:38:56 - mmengine - INFO - Epoch(train) [163][150/586] lr: 5.000000e-04 eta: 1:56:06 time: 0.228686 data_time: 0.026307 memory: 7326 loss_kpt: 0.000541 acc_pose: 0.805268 loss: 0.000541 2022/10/20 17:39:07 - mmengine - INFO - Epoch(train) [163][200/586] lr: 5.000000e-04 eta: 1:55:53 time: 0.221661 data_time: 0.024160 memory: 7326 loss_kpt: 0.000563 acc_pose: 0.799915 loss: 0.000563 2022/10/20 17:39:19 - mmengine - INFO - Epoch(train) [163][250/586] lr: 5.000000e-04 eta: 1:55:40 time: 0.226686 data_time: 0.025058 memory: 7326 loss_kpt: 0.000535 acc_pose: 0.921550 loss: 0.000535 2022/10/20 17:39:31 - mmengine - INFO - Epoch(train) [163][300/586] lr: 5.000000e-04 eta: 1:55:27 time: 0.239909 data_time: 0.026482 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.854127 loss: 0.000551 2022/10/20 17:39:42 - mmengine - INFO - Epoch(train) [163][350/586] lr: 5.000000e-04 eta: 1:55:15 time: 0.228365 data_time: 0.030218 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.856089 loss: 0.000559 2022/10/20 17:39:53 - mmengine - INFO - Epoch(train) [163][400/586] lr: 5.000000e-04 eta: 1:55:02 time: 0.229304 data_time: 0.025963 memory: 7326 loss_kpt: 0.000568 acc_pose: 0.861483 loss: 0.000568 2022/10/20 17:40:05 - mmengine - INFO - Epoch(train) [163][450/586] lr: 5.000000e-04 eta: 1:54:49 time: 0.221740 data_time: 0.025402 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.833145 loss: 0.000557 2022/10/20 17:40:16 - mmengine - INFO - Epoch(train) [163][500/586] lr: 5.000000e-04 eta: 1:54:36 time: 0.230398 data_time: 0.028712 memory: 7326 loss_kpt: 0.000543 acc_pose: 0.888685 loss: 0.000543 2022/10/20 17:40:27 - mmengine - INFO - Epoch(train) [163][550/586] lr: 5.000000e-04 eta: 1:54:24 time: 0.228275 data_time: 0.026680 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.803171 loss: 0.000561 2022/10/20 17:40:35 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:40:47 - mmengine - INFO - Epoch(train) [164][50/586] lr: 5.000000e-04 eta: 1:54:00 time: 0.240037 data_time: 0.031594 memory: 7326 loss_kpt: 0.000522 acc_pose: 0.900070 loss: 0.000522 2022/10/20 17:40:59 - mmengine - INFO - Epoch(train) [164][100/586] lr: 5.000000e-04 eta: 1:53:47 time: 0.225640 data_time: 0.026904 memory: 7326 loss_kpt: 0.000538 acc_pose: 0.871147 loss: 0.000538 2022/10/20 17:41:10 - mmengine - INFO - Epoch(train) [164][150/586] lr: 5.000000e-04 eta: 1:53:34 time: 0.230594 data_time: 0.030652 memory: 7326 loss_kpt: 0.000542 acc_pose: 0.892145 loss: 0.000542 2022/10/20 17:41:22 - mmengine - INFO - Epoch(train) [164][200/586] lr: 5.000000e-04 eta: 1:53:21 time: 0.227445 data_time: 0.028071 memory: 7326 loss_kpt: 0.000538 acc_pose: 0.872507 loss: 0.000538 2022/10/20 17:41:33 - mmengine - INFO - Epoch(train) [164][250/586] lr: 5.000000e-04 eta: 1:53:09 time: 0.231418 data_time: 0.026011 memory: 7326 loss_kpt: 0.000541 acc_pose: 0.937195 loss: 0.000541 2022/10/20 17:41:45 - mmengine - INFO - Epoch(train) [164][300/586] lr: 5.000000e-04 eta: 1:52:56 time: 0.225390 data_time: 0.026275 memory: 7326 loss_kpt: 0.000538 acc_pose: 0.918928 loss: 0.000538 2022/10/20 17:41:56 - mmengine - INFO - Epoch(train) [164][350/586] lr: 5.000000e-04 eta: 1:52:43 time: 0.233925 data_time: 0.027185 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.872049 loss: 0.000565 2022/10/20 17:42:08 - mmengine - INFO - Epoch(train) [164][400/586] lr: 5.000000e-04 eta: 1:52:31 time: 0.239332 data_time: 0.025997 memory: 7326 loss_kpt: 0.000564 acc_pose: 0.876277 loss: 0.000564 2022/10/20 17:42:20 - mmengine - INFO - Epoch(train) [164][450/586] lr: 5.000000e-04 eta: 1:52:18 time: 0.228320 data_time: 0.024265 memory: 7326 loss_kpt: 0.000531 acc_pose: 0.767915 loss: 0.000531 2022/10/20 17:42:27 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:42:31 - mmengine - INFO - Epoch(train) [164][500/586] lr: 5.000000e-04 eta: 1:52:05 time: 0.223068 data_time: 0.024616 memory: 7326 loss_kpt: 0.000540 acc_pose: 0.901369 loss: 0.000540 2022/10/20 17:42:42 - mmengine - INFO - Epoch(train) [164][550/586] lr: 5.000000e-04 eta: 1:51:52 time: 0.221525 data_time: 0.025685 memory: 7326 loss_kpt: 0.000544 acc_pose: 0.917749 loss: 0.000544 2022/10/20 17:42:50 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:43:02 - mmengine - INFO - Epoch(train) [165][50/586] lr: 5.000000e-04 eta: 1:51:28 time: 0.243741 data_time: 0.033503 memory: 7326 loss_kpt: 0.000533 acc_pose: 0.799612 loss: 0.000533 2022/10/20 17:43:14 - mmengine - INFO - Epoch(train) [165][100/586] lr: 5.000000e-04 eta: 1:51:16 time: 0.228785 data_time: 0.026041 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.866893 loss: 0.000547 2022/10/20 17:43:25 - mmengine - INFO - Epoch(train) [165][150/586] lr: 5.000000e-04 eta: 1:51:03 time: 0.223351 data_time: 0.026598 memory: 7326 loss_kpt: 0.000542 acc_pose: 0.861746 loss: 0.000542 2022/10/20 17:43:36 - mmengine - INFO - Epoch(train) [165][200/586] lr: 5.000000e-04 eta: 1:50:50 time: 0.224787 data_time: 0.030410 memory: 7326 loss_kpt: 0.000543 acc_pose: 0.857824 loss: 0.000543 2022/10/20 17:43:48 - mmengine - INFO - Epoch(train) [165][250/586] lr: 5.000000e-04 eta: 1:50:37 time: 0.238234 data_time: 0.025638 memory: 7326 loss_kpt: 0.000554 acc_pose: 0.837342 loss: 0.000554 2022/10/20 17:44:00 - mmengine - INFO - Epoch(train) [165][300/586] lr: 5.000000e-04 eta: 1:50:25 time: 0.227854 data_time: 0.029273 memory: 7326 loss_kpt: 0.000542 acc_pose: 0.869624 loss: 0.000542 2022/10/20 17:44:11 - mmengine - INFO - Epoch(train) [165][350/586] lr: 5.000000e-04 eta: 1:50:12 time: 0.228755 data_time: 0.025669 memory: 7326 loss_kpt: 0.000534 acc_pose: 0.788893 loss: 0.000534 2022/10/20 17:44:22 - mmengine - INFO - Epoch(train) [165][400/586] lr: 5.000000e-04 eta: 1:49:59 time: 0.224336 data_time: 0.027155 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.837177 loss: 0.000556 2022/10/20 17:44:34 - mmengine - INFO - Epoch(train) [165][450/586] lr: 5.000000e-04 eta: 1:49:47 time: 0.231555 data_time: 0.033441 memory: 7326 loss_kpt: 0.000557 acc_pose: 0.865021 loss: 0.000557 2022/10/20 17:44:46 - mmengine - INFO - Epoch(train) [165][500/586] lr: 5.000000e-04 eta: 1:49:34 time: 0.232284 data_time: 0.026812 memory: 7326 loss_kpt: 0.000572 acc_pose: 0.790292 loss: 0.000572 2022/10/20 17:44:57 - mmengine - INFO - Epoch(train) [165][550/586] lr: 5.000000e-04 eta: 1:49:21 time: 0.225383 data_time: 0.024528 memory: 7326 loss_kpt: 0.000543 acc_pose: 0.903102 loss: 0.000543 2022/10/20 17:45:05 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:45:17 - mmengine - INFO - Epoch(train) [166][50/586] lr: 5.000000e-04 eta: 1:48:57 time: 0.239264 data_time: 0.033564 memory: 7326 loss_kpt: 0.000538 acc_pose: 0.822841 loss: 0.000538 2022/10/20 17:45:28 - mmengine - INFO - Epoch(train) [166][100/586] lr: 5.000000e-04 eta: 1:48:45 time: 0.228528 data_time: 0.031693 memory: 7326 loss_kpt: 0.000540 acc_pose: 0.885727 loss: 0.000540 2022/10/20 17:45:40 - mmengine - INFO - Epoch(train) [166][150/586] lr: 5.000000e-04 eta: 1:48:32 time: 0.229220 data_time: 0.025308 memory: 7326 loss_kpt: 0.000545 acc_pose: 0.925292 loss: 0.000545 2022/10/20 17:45:51 - mmengine - INFO - Epoch(train) [166][200/586] lr: 5.000000e-04 eta: 1:48:19 time: 0.229072 data_time: 0.025985 memory: 7326 loss_kpt: 0.000540 acc_pose: 0.892721 loss: 0.000540 2022/10/20 17:46:02 - mmengine - INFO - Epoch(train) [166][250/586] lr: 5.000000e-04 eta: 1:48:07 time: 0.224047 data_time: 0.026756 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.836772 loss: 0.000547 2022/10/20 17:46:14 - mmengine - INFO - Epoch(train) [166][300/586] lr: 5.000000e-04 eta: 1:47:54 time: 0.227663 data_time: 0.032145 memory: 7326 loss_kpt: 0.000535 acc_pose: 0.854037 loss: 0.000535 2022/10/20 17:46:16 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:46:26 - mmengine - INFO - Epoch(train) [166][350/586] lr: 5.000000e-04 eta: 1:47:41 time: 0.236657 data_time: 0.034331 memory: 7326 loss_kpt: 0.000559 acc_pose: 0.892048 loss: 0.000559 2022/10/20 17:46:37 - mmengine - INFO - Epoch(train) [166][400/586] lr: 5.000000e-04 eta: 1:47:29 time: 0.232703 data_time: 0.025958 memory: 7326 loss_kpt: 0.000538 acc_pose: 0.787808 loss: 0.000538 2022/10/20 17:46:49 - mmengine - INFO - Epoch(train) [166][450/586] lr: 5.000000e-04 eta: 1:47:16 time: 0.235140 data_time: 0.026365 memory: 7326 loss_kpt: 0.000539 acc_pose: 0.797796 loss: 0.000539 2022/10/20 17:47:01 - mmengine - INFO - Epoch(train) [166][500/586] lr: 5.000000e-04 eta: 1:47:03 time: 0.229059 data_time: 0.025122 memory: 7326 loss_kpt: 0.000541 acc_pose: 0.873392 loss: 0.000541 2022/10/20 17:47:12 - mmengine - INFO - Epoch(train) [166][550/586] lr: 5.000000e-04 eta: 1:46:51 time: 0.227950 data_time: 0.023500 memory: 7326 loss_kpt: 0.000561 acc_pose: 0.814997 loss: 0.000561 2022/10/20 17:47:20 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:47:32 - mmengine - INFO - Epoch(train) [167][50/586] lr: 5.000000e-04 eta: 1:46:27 time: 0.242421 data_time: 0.032301 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.854253 loss: 0.000547 2022/10/20 17:47:44 - mmengine - INFO - Epoch(train) [167][100/586] lr: 5.000000e-04 eta: 1:46:14 time: 0.232295 data_time: 0.025227 memory: 7326 loss_kpt: 0.000538 acc_pose: 0.913119 loss: 0.000538 2022/10/20 17:47:55 - mmengine - INFO - Epoch(train) [167][150/586] lr: 5.000000e-04 eta: 1:46:02 time: 0.223658 data_time: 0.026984 memory: 7326 loss_kpt: 0.000533 acc_pose: 0.852550 loss: 0.000533 2022/10/20 17:48:06 - mmengine - INFO - Epoch(train) [167][200/586] lr: 5.000000e-04 eta: 1:45:49 time: 0.222553 data_time: 0.027230 memory: 7326 loss_kpt: 0.000556 acc_pose: 0.891973 loss: 0.000556 2022/10/20 17:48:18 - mmengine - INFO - Epoch(train) [167][250/586] lr: 5.000000e-04 eta: 1:45:36 time: 0.231269 data_time: 0.024595 memory: 7326 loss_kpt: 0.000535 acc_pose: 0.889289 loss: 0.000535 2022/10/20 17:48:29 - mmengine - INFO - Epoch(train) [167][300/586] lr: 5.000000e-04 eta: 1:45:23 time: 0.224483 data_time: 0.026181 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.885563 loss: 0.000551 2022/10/20 17:48:41 - mmengine - INFO - Epoch(train) [167][350/586] lr: 5.000000e-04 eta: 1:45:11 time: 0.233757 data_time: 0.031310 memory: 7326 loss_kpt: 0.000550 acc_pose: 0.863683 loss: 0.000550 2022/10/20 17:48:52 - mmengine - INFO - Epoch(train) [167][400/586] lr: 5.000000e-04 eta: 1:44:58 time: 0.228597 data_time: 0.023749 memory: 7326 loss_kpt: 0.000544 acc_pose: 0.925154 loss: 0.000544 2022/10/20 17:49:04 - mmengine - INFO - Epoch(train) [167][450/586] lr: 5.000000e-04 eta: 1:44:46 time: 0.236529 data_time: 0.029128 memory: 7326 loss_kpt: 0.000544 acc_pose: 0.913354 loss: 0.000544 2022/10/20 17:49:16 - mmengine - INFO - Epoch(train) [167][500/586] lr: 5.000000e-04 eta: 1:44:33 time: 0.227946 data_time: 0.026508 memory: 7326 loss_kpt: 0.000565 acc_pose: 0.830398 loss: 0.000565 2022/10/20 17:49:27 - mmengine - INFO - Epoch(train) [167][550/586] lr: 5.000000e-04 eta: 1:44:20 time: 0.229441 data_time: 0.025090 memory: 7326 loss_kpt: 0.000537 acc_pose: 0.882328 loss: 0.000537 2022/10/20 17:49:35 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:49:47 - mmengine - INFO - Epoch(train) [168][50/586] lr: 5.000000e-04 eta: 1:43:57 time: 0.236041 data_time: 0.037429 memory: 7326 loss_kpt: 0.000542 acc_pose: 0.869082 loss: 0.000542 2022/10/20 17:49:58 - mmengine - INFO - Epoch(train) [168][100/586] lr: 5.000000e-04 eta: 1:43:44 time: 0.230056 data_time: 0.026003 memory: 7326 loss_kpt: 0.000549 acc_pose: 0.887266 loss: 0.000549 2022/10/20 17:50:07 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:50:10 - mmengine - INFO - Epoch(train) [168][150/586] lr: 5.000000e-04 eta: 1:43:31 time: 0.222586 data_time: 0.024345 memory: 7326 loss_kpt: 0.000532 acc_pose: 0.855203 loss: 0.000532 2022/10/20 17:50:21 - mmengine - INFO - Epoch(train) [168][200/586] lr: 5.000000e-04 eta: 1:43:19 time: 0.237405 data_time: 0.024218 memory: 7326 loss_kpt: 0.000541 acc_pose: 0.839506 loss: 0.000541 2022/10/20 17:50:33 - mmengine - INFO - Epoch(train) [168][250/586] lr: 5.000000e-04 eta: 1:43:06 time: 0.220230 data_time: 0.025812 memory: 7326 loss_kpt: 0.000549 acc_pose: 0.876547 loss: 0.000549 2022/10/20 17:50:44 - mmengine - INFO - Epoch(train) [168][300/586] lr: 5.000000e-04 eta: 1:42:53 time: 0.228225 data_time: 0.027509 memory: 7326 loss_kpt: 0.000553 acc_pose: 0.875963 loss: 0.000553 2022/10/20 17:50:56 - mmengine - INFO - Epoch(train) [168][350/586] lr: 5.000000e-04 eta: 1:42:41 time: 0.235933 data_time: 0.026086 memory: 7326 loss_kpt: 0.000541 acc_pose: 0.839237 loss: 0.000541 2022/10/20 17:51:07 - mmengine - INFO - Epoch(train) [168][400/586] lr: 5.000000e-04 eta: 1:42:28 time: 0.226610 data_time: 0.027389 memory: 7326 loss_kpt: 0.000552 acc_pose: 0.891176 loss: 0.000552 2022/10/20 17:51:18 - mmengine - INFO - Epoch(train) [168][450/586] lr: 5.000000e-04 eta: 1:42:15 time: 0.224033 data_time: 0.026023 memory: 7326 loss_kpt: 0.000558 acc_pose: 0.804842 loss: 0.000558 2022/10/20 17:51:30 - mmengine - INFO - Epoch(train) [168][500/586] lr: 5.000000e-04 eta: 1:42:03 time: 0.227213 data_time: 0.025790 memory: 7326 loss_kpt: 0.000541 acc_pose: 0.917583 loss: 0.000541 2022/10/20 17:51:42 - mmengine - INFO - Epoch(train) [168][550/586] lr: 5.000000e-04 eta: 1:41:50 time: 0.236465 data_time: 0.029004 memory: 7326 loss_kpt: 0.000551 acc_pose: 0.848518 loss: 0.000551 2022/10/20 17:51:50 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:52:02 - mmengine - INFO - Epoch(train) [169][50/586] lr: 5.000000e-04 eta: 1:41:27 time: 0.241537 data_time: 0.035102 memory: 7326 loss_kpt: 0.000537 acc_pose: 0.937934 loss: 0.000537 2022/10/20 17:52:13 - mmengine - INFO - Epoch(train) [169][100/586] lr: 5.000000e-04 eta: 1:41:14 time: 0.222921 data_time: 0.027176 memory: 7326 loss_kpt: 0.000534 acc_pose: 0.845867 loss: 0.000534 2022/10/20 17:52:24 - mmengine - INFO - Epoch(train) [169][150/586] lr: 5.000000e-04 eta: 1:41:01 time: 0.223184 data_time: 0.024551 memory: 7326 loss_kpt: 0.000539 acc_pose: 0.881448 loss: 0.000539 2022/10/20 17:52:36 - mmengine - INFO - Epoch(train) [169][200/586] lr: 5.000000e-04 eta: 1:40:49 time: 0.235411 data_time: 0.026947 memory: 7326 loss_kpt: 0.000554 acc_pose: 0.857584 loss: 0.000554 2022/10/20 17:52:47 - mmengine - INFO - Epoch(train) [169][250/586] lr: 5.000000e-04 eta: 1:40:36 time: 0.223905 data_time: 0.026758 memory: 7326 loss_kpt: 0.000546 acc_pose: 0.856358 loss: 0.000546 2022/10/20 17:52:59 - mmengine - INFO - Epoch(train) [169][300/586] lr: 5.000000e-04 eta: 1:40:23 time: 0.236483 data_time: 0.027024 memory: 7326 loss_kpt: 0.000552 acc_pose: 0.779032 loss: 0.000552 2022/10/20 17:53:10 - mmengine - INFO - Epoch(train) [169][350/586] lr: 5.000000e-04 eta: 1:40:11 time: 0.221819 data_time: 0.026361 memory: 7326 loss_kpt: 0.000554 acc_pose: 0.850184 loss: 0.000554 2022/10/20 17:53:21 - mmengine - INFO - Epoch(train) [169][400/586] lr: 5.000000e-04 eta: 1:39:58 time: 0.228963 data_time: 0.034339 memory: 7326 loss_kpt: 0.000574 acc_pose: 0.891893 loss: 0.000574 2022/10/20 17:53:33 - mmengine - INFO - Epoch(train) [169][450/586] lr: 5.000000e-04 eta: 1:39:45 time: 0.227078 data_time: 0.023936 memory: 7326 loss_kpt: 0.000549 acc_pose: 0.845311 loss: 0.000549 2022/10/20 17:53:45 - mmengine - INFO - Epoch(train) [169][500/586] lr: 5.000000e-04 eta: 1:39:33 time: 0.235988 data_time: 0.027713 memory: 7326 loss_kpt: 0.000536 acc_pose: 0.824803 loss: 0.000536 2022/10/20 17:53:56 - mmengine - INFO - Epoch(train) [169][550/586] lr: 5.000000e-04 eta: 1:39:20 time: 0.225934 data_time: 0.025182 memory: 7326 loss_kpt: 0.000542 acc_pose: 0.913797 loss: 0.000542 2022/10/20 17:53:56 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:54:04 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:54:16 - mmengine - INFO - Epoch(train) [170][50/586] lr: 5.000000e-04 eta: 1:38:57 time: 0.235481 data_time: 0.032597 memory: 7326 loss_kpt: 0.000550 acc_pose: 0.840640 loss: 0.000550 2022/10/20 17:54:27 - mmengine - INFO - Epoch(train) [170][100/586] lr: 5.000000e-04 eta: 1:38:44 time: 0.228703 data_time: 0.023877 memory: 7326 loss_kpt: 0.000541 acc_pose: 0.901708 loss: 0.000541 2022/10/20 17:54:39 - mmengine - INFO - Epoch(train) [170][150/586] lr: 5.000000e-04 eta: 1:38:31 time: 0.226727 data_time: 0.024726 memory: 7326 loss_kpt: 0.000547 acc_pose: 0.838290 loss: 0.000547 2022/10/20 17:54:50 - mmengine - INFO - Epoch(train) [170][200/586] lr: 5.000000e-04 eta: 1:38:19 time: 0.222600 data_time: 0.024358 memory: 7326 loss_kpt: 0.000548 acc_pose: 0.831612 loss: 0.000548 2022/10/20 17:55:01 - mmengine - INFO - Epoch(train) [170][250/586] lr: 5.000000e-04 eta: 1:38:06 time: 0.223383 data_time: 0.026374 memory: 7326 loss_kpt: 0.000530 acc_pose: 0.883197 loss: 0.000530 2022/10/20 17:55:13 - mmengine - INFO - Epoch(train) [170][300/586] lr: 5.000000e-04 eta: 1:37:54 time: 0.240426 data_time: 0.031613 memory: 7326 loss_kpt: 0.000539 acc_pose: 0.878997 loss: 0.000539 2022/10/20 17:55:24 - mmengine - INFO - Epoch(train) [170][350/586] lr: 5.000000e-04 eta: 1:37:41 time: 0.224680 data_time: 0.026188 memory: 7326 loss_kpt: 0.000536 acc_pose: 0.877323 loss: 0.000536 2022/10/20 17:55:36 - mmengine - INFO - Epoch(train) [170][400/586] lr: 5.000000e-04 eta: 1:37:28 time: 0.230144 data_time: 0.026621 memory: 7326 loss_kpt: 0.000554 acc_pose: 0.842679 loss: 0.000554 2022/10/20 17:55:47 - mmengine - INFO - Epoch(train) [170][450/586] lr: 5.000000e-04 eta: 1:37:16 time: 0.222472 data_time: 0.025777 memory: 7326 loss_kpt: 0.000541 acc_pose: 0.875460 loss: 0.000541 2022/10/20 17:55:58 - mmengine - INFO - Epoch(train) [170][500/586] lr: 5.000000e-04 eta: 1:37:03 time: 0.226270 data_time: 0.025584 memory: 7326 loss_kpt: 0.000552 acc_pose: 0.897586 loss: 0.000552 2022/10/20 17:56:10 - mmengine - INFO - Epoch(train) [170][550/586] lr: 5.000000e-04 eta: 1:36:50 time: 0.233127 data_time: 0.025532 memory: 7326 loss_kpt: 0.000542 acc_pose: 0.913168 loss: 0.000542 2022/10/20 17:56:18 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:56:18 - mmengine - INFO - Saving checkpoint at 170 epochs 2022/10/20 17:56:28 - mmengine - INFO - Epoch(val) [170][50/407] eta: 0:00:44 time: 0.123462 data_time: 0.038909 memory: 7326 2022/10/20 17:56:34 - mmengine - INFO - Epoch(val) [170][100/407] eta: 0:00:37 time: 0.121498 data_time: 0.039415 memory: 1680 2022/10/20 17:56:40 - mmengine - INFO - Epoch(val) [170][150/407] eta: 0:00:28 time: 0.112126 data_time: 0.030331 memory: 1680 2022/10/20 17:56:46 - mmengine - INFO - Epoch(val) [170][200/407] eta: 0:00:23 time: 0.112779 data_time: 0.029685 memory: 1680 2022/10/20 17:56:51 - mmengine - INFO - Epoch(val) [170][250/407] eta: 0:00:18 time: 0.114947 data_time: 0.033992 memory: 1680 2022/10/20 17:56:57 - mmengine - INFO - Epoch(val) [170][300/407] eta: 0:00:11 time: 0.109647 data_time: 0.026637 memory: 1680 2022/10/20 17:57:03 - mmengine - INFO - Epoch(val) [170][350/407] eta: 0:00:07 time: 0.124040 data_time: 0.041524 memory: 1680 2022/10/20 17:57:08 - mmengine - INFO - Epoch(val) [170][400/407] eta: 0:00:00 time: 0.105186 data_time: 0.026064 memory: 1680 2022/10/20 17:57:41 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 17:57:54 - mmengine - INFO - Epoch(val) [170][407/407] coco/AP: 0.726353 coco/AP .5: 0.897613 coco/AP .75: 0.801105 coco/AP (M): 0.688654 coco/AP (L): 0.796554 coco/AR: 0.782116 coco/AR .5: 0.937657 coco/AR .75: 0.848866 coco/AR (M): 0.737340 coco/AR (L): 0.846748 2022/10/20 17:58:06 - mmengine - INFO - Epoch(train) [171][50/586] lr: 5.000000e-05 eta: 1:36:27 time: 0.248861 data_time: 0.030718 memory: 7326 loss_kpt: 0.000525 acc_pose: 0.825378 loss: 0.000525 2022/10/20 17:58:18 - mmengine - INFO - Epoch(train) [171][100/586] lr: 5.000000e-05 eta: 1:36:14 time: 0.224060 data_time: 0.025784 memory: 7326 loss_kpt: 0.000533 acc_pose: 0.889813 loss: 0.000533 2022/10/20 17:58:29 - mmengine - INFO - Epoch(train) [171][150/586] lr: 5.000000e-05 eta: 1:36:02 time: 0.220768 data_time: 0.023655 memory: 7326 loss_kpt: 0.000541 acc_pose: 0.862168 loss: 0.000541 2022/10/20 17:58:40 - mmengine - INFO - Epoch(train) [171][200/586] lr: 5.000000e-05 eta: 1:35:49 time: 0.235184 data_time: 0.029354 memory: 7326 loss_kpt: 0.000534 acc_pose: 0.851048 loss: 0.000534 2022/10/20 17:58:52 - mmengine - INFO - Epoch(train) [171][250/586] lr: 5.000000e-05 eta: 1:35:37 time: 0.235474 data_time: 0.029592 memory: 7326 loss_kpt: 0.000519 acc_pose: 0.904781 loss: 0.000519 2022/10/20 17:59:04 - mmengine - INFO - Epoch(train) [171][300/586] lr: 5.000000e-05 eta: 1:35:24 time: 0.230732 data_time: 0.024464 memory: 7326 loss_kpt: 0.000515 acc_pose: 0.884006 loss: 0.000515 2022/10/20 17:59:15 - mmengine - INFO - Epoch(train) [171][350/586] lr: 5.000000e-05 eta: 1:35:12 time: 0.225330 data_time: 0.025067 memory: 7326 loss_kpt: 0.000517 acc_pose: 0.890596 loss: 0.000517 2022/10/20 17:59:22 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 17:59:27 - mmengine - INFO - Epoch(train) [171][400/586] lr: 5.000000e-05 eta: 1:34:59 time: 0.237379 data_time: 0.027758 memory: 7326 loss_kpt: 0.000519 acc_pose: 0.877228 loss: 0.000519 2022/10/20 17:59:38 - mmengine - INFO - Epoch(train) [171][450/586] lr: 5.000000e-05 eta: 1:34:46 time: 0.225984 data_time: 0.027526 memory: 7326 loss_kpt: 0.000527 acc_pose: 0.867454 loss: 0.000527 2022/10/20 17:59:50 - mmengine - INFO - Epoch(train) [171][500/586] lr: 5.000000e-05 eta: 1:34:34 time: 0.225463 data_time: 0.025857 memory: 7326 loss_kpt: 0.000518 acc_pose: 0.862017 loss: 0.000518 2022/10/20 18:00:01 - mmengine - INFO - Epoch(train) [171][550/586] lr: 5.000000e-05 eta: 1:34:21 time: 0.226988 data_time: 0.026641 memory: 7326 loss_kpt: 0.000525 acc_pose: 0.846265 loss: 0.000525 2022/10/20 18:00:09 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:00:22 - mmengine - INFO - Epoch(train) [172][50/586] lr: 5.000000e-05 eta: 1:33:58 time: 0.247059 data_time: 0.034375 memory: 7326 loss_kpt: 0.000513 acc_pose: 0.866662 loss: 0.000513 2022/10/20 18:00:33 - mmengine - INFO - Epoch(train) [172][100/586] lr: 5.000000e-05 eta: 1:33:45 time: 0.228270 data_time: 0.026144 memory: 7326 loss_kpt: 0.000527 acc_pose: 0.832278 loss: 0.000527 2022/10/20 18:00:44 - mmengine - INFO - Epoch(train) [172][150/586] lr: 5.000000e-05 eta: 1:33:33 time: 0.225714 data_time: 0.023999 memory: 7326 loss_kpt: 0.000506 acc_pose: 0.923286 loss: 0.000506 2022/10/20 18:00:56 - mmengine - INFO - Epoch(train) [172][200/586] lr: 5.000000e-05 eta: 1:33:20 time: 0.222384 data_time: 0.025660 memory: 7326 loss_kpt: 0.000515 acc_pose: 0.908923 loss: 0.000515 2022/10/20 18:01:07 - mmengine - INFO - Epoch(train) [172][250/586] lr: 5.000000e-05 eta: 1:33:08 time: 0.225139 data_time: 0.025249 memory: 7326 loss_kpt: 0.000507 acc_pose: 0.869646 loss: 0.000507 2022/10/20 18:01:18 - mmengine - INFO - Epoch(train) [172][300/586] lr: 5.000000e-05 eta: 1:32:55 time: 0.231869 data_time: 0.023225 memory: 7326 loss_kpt: 0.000517 acc_pose: 0.860523 loss: 0.000517 2022/10/20 18:01:30 - mmengine - INFO - Epoch(train) [172][350/586] lr: 5.000000e-05 eta: 1:32:42 time: 0.235114 data_time: 0.027332 memory: 7326 loss_kpt: 0.000524 acc_pose: 0.843780 loss: 0.000524 2022/10/20 18:01:41 - mmengine - INFO - Epoch(train) [172][400/586] lr: 5.000000e-05 eta: 1:32:30 time: 0.220065 data_time: 0.024416 memory: 7326 loss_kpt: 0.000522 acc_pose: 0.881874 loss: 0.000522 2022/10/20 18:01:53 - mmengine - INFO - Epoch(train) [172][450/586] lr: 5.000000e-05 eta: 1:32:17 time: 0.226756 data_time: 0.024107 memory: 7326 loss_kpt: 0.000516 acc_pose: 0.864258 loss: 0.000516 2022/10/20 18:02:04 - mmengine - INFO - Epoch(train) [172][500/586] lr: 5.000000e-05 eta: 1:32:05 time: 0.224696 data_time: 0.025562 memory: 7326 loss_kpt: 0.000519 acc_pose: 0.892079 loss: 0.000519 2022/10/20 18:02:15 - mmengine - INFO - Epoch(train) [172][550/586] lr: 5.000000e-05 eta: 1:31:52 time: 0.232412 data_time: 0.027486 memory: 7326 loss_kpt: 0.000520 acc_pose: 0.870947 loss: 0.000520 2022/10/20 18:02:24 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:02:36 - mmengine - INFO - Epoch(train) [173][50/586] lr: 5.000000e-05 eta: 1:31:29 time: 0.242005 data_time: 0.034886 memory: 7326 loss_kpt: 0.000521 acc_pose: 0.859371 loss: 0.000521 2022/10/20 18:02:47 - mmengine - INFO - Epoch(train) [173][100/586] lr: 5.000000e-05 eta: 1:31:16 time: 0.230554 data_time: 0.029747 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.920822 loss: 0.000492 2022/10/20 18:02:59 - mmengine - INFO - Epoch(train) [173][150/586] lr: 5.000000e-05 eta: 1:31:04 time: 0.226509 data_time: 0.027235 memory: 7326 loss_kpt: 0.000519 acc_pose: 0.863299 loss: 0.000519 2022/10/20 18:03:10 - mmengine - INFO - Epoch(train) [173][200/586] lr: 5.000000e-05 eta: 1:30:51 time: 0.223795 data_time: 0.026430 memory: 7326 loss_kpt: 0.000510 acc_pose: 0.854915 loss: 0.000510 2022/10/20 18:03:12 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:03:22 - mmengine - INFO - Epoch(train) [173][250/586] lr: 5.000000e-05 eta: 1:30:39 time: 0.234347 data_time: 0.026140 memory: 7326 loss_kpt: 0.000533 acc_pose: 0.918857 loss: 0.000533 2022/10/20 18:03:33 - mmengine - INFO - Epoch(train) [173][300/586] lr: 5.000000e-05 eta: 1:30:26 time: 0.224944 data_time: 0.026562 memory: 7326 loss_kpt: 0.000527 acc_pose: 0.778382 loss: 0.000527 2022/10/20 18:03:44 - mmengine - INFO - Epoch(train) [173][350/586] lr: 5.000000e-05 eta: 1:30:13 time: 0.220378 data_time: 0.025665 memory: 7326 loss_kpt: 0.000512 acc_pose: 0.856537 loss: 0.000512 2022/10/20 18:03:55 - mmengine - INFO - Epoch(train) [173][400/586] lr: 5.000000e-05 eta: 1:30:01 time: 0.232326 data_time: 0.024807 memory: 7326 loss_kpt: 0.000532 acc_pose: 0.832263 loss: 0.000532 2022/10/20 18:04:07 - mmengine - INFO - Epoch(train) [173][450/586] lr: 5.000000e-05 eta: 1:29:48 time: 0.228887 data_time: 0.025607 memory: 7326 loss_kpt: 0.000504 acc_pose: 0.913530 loss: 0.000504 2022/10/20 18:04:18 - mmengine - INFO - Epoch(train) [173][500/586] lr: 5.000000e-05 eta: 1:29:36 time: 0.218871 data_time: 0.026102 memory: 7326 loss_kpt: 0.000522 acc_pose: 0.875595 loss: 0.000522 2022/10/20 18:04:29 - mmengine - INFO - Epoch(train) [173][550/586] lr: 5.000000e-05 eta: 1:29:23 time: 0.225443 data_time: 0.026290 memory: 7326 loss_kpt: 0.000515 acc_pose: 0.830143 loss: 0.000515 2022/10/20 18:04:38 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:04:50 - mmengine - INFO - Epoch(train) [174][50/586] lr: 5.000000e-05 eta: 1:29:00 time: 0.246305 data_time: 0.031930 memory: 7326 loss_kpt: 0.000525 acc_pose: 0.902001 loss: 0.000525 2022/10/20 18:05:02 - mmengine - INFO - Epoch(train) [174][100/586] lr: 5.000000e-05 eta: 1:28:47 time: 0.233147 data_time: 0.028132 memory: 7326 loss_kpt: 0.000513 acc_pose: 0.867271 loss: 0.000513 2022/10/20 18:05:13 - mmengine - INFO - Epoch(train) [174][150/586] lr: 5.000000e-05 eta: 1:28:35 time: 0.231383 data_time: 0.032246 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.899309 loss: 0.000500 2022/10/20 18:05:24 - mmengine - INFO - Epoch(train) [174][200/586] lr: 5.000000e-05 eta: 1:28:22 time: 0.223248 data_time: 0.024230 memory: 7326 loss_kpt: 0.000518 acc_pose: 0.822557 loss: 0.000518 2022/10/20 18:05:36 - mmengine - INFO - Epoch(train) [174][250/586] lr: 5.000000e-05 eta: 1:28:10 time: 0.234343 data_time: 0.026091 memory: 7326 loss_kpt: 0.000507 acc_pose: 0.878248 loss: 0.000507 2022/10/20 18:05:47 - mmengine - INFO - Epoch(train) [174][300/586] lr: 5.000000e-05 eta: 1:27:57 time: 0.226570 data_time: 0.023557 memory: 7326 loss_kpt: 0.000525 acc_pose: 0.875951 loss: 0.000525 2022/10/20 18:05:59 - mmengine - INFO - Epoch(train) [174][350/586] lr: 5.000000e-05 eta: 1:27:45 time: 0.228898 data_time: 0.028954 memory: 7326 loss_kpt: 0.000509 acc_pose: 0.892917 loss: 0.000509 2022/10/20 18:06:10 - mmengine - INFO - Epoch(train) [174][400/586] lr: 5.000000e-05 eta: 1:27:32 time: 0.222946 data_time: 0.024848 memory: 7326 loss_kpt: 0.000511 acc_pose: 0.892419 loss: 0.000511 2022/10/20 18:06:21 - mmengine - INFO - Epoch(train) [174][450/586] lr: 5.000000e-05 eta: 1:27:20 time: 0.225044 data_time: 0.024171 memory: 7326 loss_kpt: 0.000524 acc_pose: 0.918384 loss: 0.000524 2022/10/20 18:06:33 - mmengine - INFO - Epoch(train) [174][500/586] lr: 5.000000e-05 eta: 1:27:07 time: 0.230477 data_time: 0.029702 memory: 7326 loss_kpt: 0.000505 acc_pose: 0.908027 loss: 0.000505 2022/10/20 18:06:45 - mmengine - INFO - Epoch(train) [174][550/586] lr: 5.000000e-05 eta: 1:26:55 time: 0.239201 data_time: 0.029325 memory: 7326 loss_kpt: 0.000493 acc_pose: 0.897241 loss: 0.000493 2022/10/20 18:06:53 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:07:02 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:07:05 - mmengine - INFO - Epoch(train) [175][50/586] lr: 5.000000e-05 eta: 1:26:32 time: 0.242500 data_time: 0.044835 memory: 7326 loss_kpt: 0.000512 acc_pose: 0.897202 loss: 0.000512 2022/10/20 18:07:17 - mmengine - INFO - Epoch(train) [175][100/586] lr: 5.000000e-05 eta: 1:26:19 time: 0.231571 data_time: 0.024647 memory: 7326 loss_kpt: 0.000531 acc_pose: 0.904718 loss: 0.000531 2022/10/20 18:07:28 - mmengine - INFO - Epoch(train) [175][150/586] lr: 5.000000e-05 eta: 1:26:07 time: 0.229412 data_time: 0.026945 memory: 7326 loss_kpt: 0.000513 acc_pose: 0.865785 loss: 0.000513 2022/10/20 18:07:40 - mmengine - INFO - Epoch(train) [175][200/586] lr: 5.000000e-05 eta: 1:25:54 time: 0.230470 data_time: 0.029335 memory: 7326 loss_kpt: 0.000511 acc_pose: 0.865111 loss: 0.000511 2022/10/20 18:07:51 - mmengine - INFO - Epoch(train) [175][250/586] lr: 5.000000e-05 eta: 1:25:42 time: 0.228821 data_time: 0.026727 memory: 7326 loss_kpt: 0.000508 acc_pose: 0.921513 loss: 0.000508 2022/10/20 18:08:02 - mmengine - INFO - Epoch(train) [175][300/586] lr: 5.000000e-05 eta: 1:25:29 time: 0.227710 data_time: 0.023815 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.902030 loss: 0.000489 2022/10/20 18:08:14 - mmengine - INFO - Epoch(train) [175][350/586] lr: 5.000000e-05 eta: 1:25:17 time: 0.228746 data_time: 0.024713 memory: 7326 loss_kpt: 0.000505 acc_pose: 0.905947 loss: 0.000505 2022/10/20 18:08:26 - mmengine - INFO - Epoch(train) [175][400/586] lr: 5.000000e-05 eta: 1:25:04 time: 0.230937 data_time: 0.025191 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.846885 loss: 0.000500 2022/10/20 18:08:37 - mmengine - INFO - Epoch(train) [175][450/586] lr: 5.000000e-05 eta: 1:24:52 time: 0.229114 data_time: 0.031329 memory: 7326 loss_kpt: 0.000514 acc_pose: 0.872637 loss: 0.000514 2022/10/20 18:08:48 - mmengine - INFO - Epoch(train) [175][500/586] lr: 5.000000e-05 eta: 1:24:39 time: 0.222747 data_time: 0.028211 memory: 7326 loss_kpt: 0.000510 acc_pose: 0.848100 loss: 0.000510 2022/10/20 18:09:00 - mmengine - INFO - Epoch(train) [175][550/586] lr: 5.000000e-05 eta: 1:24:26 time: 0.228977 data_time: 0.025442 memory: 7326 loss_kpt: 0.000522 acc_pose: 0.918004 loss: 0.000522 2022/10/20 18:09:08 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:09:20 - mmengine - INFO - Epoch(train) [176][50/586] lr: 5.000000e-05 eta: 1:24:03 time: 0.234986 data_time: 0.032575 memory: 7326 loss_kpt: 0.000519 acc_pose: 0.910229 loss: 0.000519 2022/10/20 18:09:31 - mmengine - INFO - Epoch(train) [176][100/586] lr: 5.000000e-05 eta: 1:23:51 time: 0.234141 data_time: 0.023992 memory: 7326 loss_kpt: 0.000511 acc_pose: 0.874693 loss: 0.000511 2022/10/20 18:09:43 - mmengine - INFO - Epoch(train) [176][150/586] lr: 5.000000e-05 eta: 1:23:38 time: 0.228698 data_time: 0.026852 memory: 7326 loss_kpt: 0.000522 acc_pose: 0.885819 loss: 0.000522 2022/10/20 18:09:54 - mmengine - INFO - Epoch(train) [176][200/586] lr: 5.000000e-05 eta: 1:23:26 time: 0.226256 data_time: 0.026812 memory: 7326 loss_kpt: 0.000503 acc_pose: 0.930182 loss: 0.000503 2022/10/20 18:10:06 - mmengine - INFO - Epoch(train) [176][250/586] lr: 5.000000e-05 eta: 1:23:13 time: 0.233992 data_time: 0.028146 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.912641 loss: 0.000499 2022/10/20 18:10:17 - mmengine - INFO - Epoch(train) [176][300/586] lr: 5.000000e-05 eta: 1:23:01 time: 0.230819 data_time: 0.024453 memory: 7326 loss_kpt: 0.000506 acc_pose: 0.922033 loss: 0.000506 2022/10/20 18:10:29 - mmengine - INFO - Epoch(train) [176][350/586] lr: 5.000000e-05 eta: 1:22:48 time: 0.229456 data_time: 0.024966 memory: 7326 loss_kpt: 0.000505 acc_pose: 0.927290 loss: 0.000505 2022/10/20 18:10:40 - mmengine - INFO - Epoch(train) [176][400/586] lr: 5.000000e-05 eta: 1:22:36 time: 0.223514 data_time: 0.025565 memory: 7326 loss_kpt: 0.000515 acc_pose: 0.905554 loss: 0.000515 2022/10/20 18:10:52 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:10:52 - mmengine - INFO - Epoch(train) [176][450/586] lr: 5.000000e-05 eta: 1:22:23 time: 0.228221 data_time: 0.026321 memory: 7326 loss_kpt: 0.000503 acc_pose: 0.913877 loss: 0.000503 2022/10/20 18:11:03 - mmengine - INFO - Epoch(train) [176][500/586] lr: 5.000000e-05 eta: 1:22:11 time: 0.225648 data_time: 0.024108 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.895950 loss: 0.000501 2022/10/20 18:11:14 - mmengine - INFO - Epoch(train) [176][550/586] lr: 5.000000e-05 eta: 1:21:58 time: 0.228406 data_time: 0.030671 memory: 7326 loss_kpt: 0.000509 acc_pose: 0.889462 loss: 0.000509 2022/10/20 18:11:22 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:11:34 - mmengine - INFO - Epoch(train) [177][50/586] lr: 5.000000e-05 eta: 1:21:35 time: 0.234537 data_time: 0.033327 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.826890 loss: 0.000496 2022/10/20 18:11:46 - mmengine - INFO - Epoch(train) [177][100/586] lr: 5.000000e-05 eta: 1:21:23 time: 0.229404 data_time: 0.025225 memory: 7326 loss_kpt: 0.000509 acc_pose: 0.923717 loss: 0.000509 2022/10/20 18:11:57 - mmengine - INFO - Epoch(train) [177][150/586] lr: 5.000000e-05 eta: 1:21:10 time: 0.234157 data_time: 0.026089 memory: 7326 loss_kpt: 0.000512 acc_pose: 0.872079 loss: 0.000512 2022/10/20 18:12:09 - mmengine - INFO - Epoch(train) [177][200/586] lr: 5.000000e-05 eta: 1:20:58 time: 0.234561 data_time: 0.029507 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.914733 loss: 0.000489 2022/10/20 18:12:20 - mmengine - INFO - Epoch(train) [177][250/586] lr: 5.000000e-05 eta: 1:20:46 time: 0.223916 data_time: 0.024944 memory: 7326 loss_kpt: 0.000525 acc_pose: 0.793018 loss: 0.000525 2022/10/20 18:12:32 - mmengine - INFO - Epoch(train) [177][300/586] lr: 5.000000e-05 eta: 1:20:33 time: 0.222825 data_time: 0.027498 memory: 7326 loss_kpt: 0.000495 acc_pose: 0.896399 loss: 0.000495 2022/10/20 18:12:43 - mmengine - INFO - Epoch(train) [177][350/586] lr: 5.000000e-05 eta: 1:20:21 time: 0.231670 data_time: 0.027099 memory: 7326 loss_kpt: 0.000514 acc_pose: 0.905505 loss: 0.000514 2022/10/20 18:12:54 - mmengine - INFO - Epoch(train) [177][400/586] lr: 5.000000e-05 eta: 1:20:08 time: 0.225774 data_time: 0.026430 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.911822 loss: 0.000490 2022/10/20 18:13:06 - mmengine - INFO - Epoch(train) [177][450/586] lr: 5.000000e-05 eta: 1:19:56 time: 0.228195 data_time: 0.029900 memory: 7326 loss_kpt: 0.000512 acc_pose: 0.879674 loss: 0.000512 2022/10/20 18:13:17 - mmengine - INFO - Epoch(train) [177][500/586] lr: 5.000000e-05 eta: 1:19:43 time: 0.220735 data_time: 0.029317 memory: 7326 loss_kpt: 0.000504 acc_pose: 0.887008 loss: 0.000504 2022/10/20 18:13:28 - mmengine - INFO - Epoch(train) [177][550/586] lr: 5.000000e-05 eta: 1:19:31 time: 0.229537 data_time: 0.024771 memory: 7326 loss_kpt: 0.000505 acc_pose: 0.905117 loss: 0.000505 2022/10/20 18:13:37 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:13:49 - mmengine - INFO - Epoch(train) [178][50/586] lr: 5.000000e-05 eta: 1:19:08 time: 0.245212 data_time: 0.039897 memory: 7326 loss_kpt: 0.000507 acc_pose: 0.926160 loss: 0.000507 2022/10/20 18:14:01 - mmengine - INFO - Epoch(train) [178][100/586] lr: 5.000000e-05 eta: 1:18:55 time: 0.228452 data_time: 0.028859 memory: 7326 loss_kpt: 0.000510 acc_pose: 0.842481 loss: 0.000510 2022/10/20 18:14:12 - mmengine - INFO - Epoch(train) [178][150/586] lr: 5.000000e-05 eta: 1:18:43 time: 0.224586 data_time: 0.025698 memory: 7326 loss_kpt: 0.000510 acc_pose: 0.849189 loss: 0.000510 2022/10/20 18:14:24 - mmengine - INFO - Epoch(train) [178][200/586] lr: 5.000000e-05 eta: 1:18:30 time: 0.234292 data_time: 0.025927 memory: 7326 loss_kpt: 0.000513 acc_pose: 0.895189 loss: 0.000513 2022/10/20 18:14:35 - mmengine - INFO - Epoch(train) [178][250/586] lr: 5.000000e-05 eta: 1:18:18 time: 0.234457 data_time: 0.025870 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.900453 loss: 0.000490 2022/10/20 18:14:42 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:14:47 - mmengine - INFO - Epoch(train) [178][300/586] lr: 5.000000e-05 eta: 1:18:05 time: 0.227153 data_time: 0.029264 memory: 7326 loss_kpt: 0.000515 acc_pose: 0.895774 loss: 0.000515 2022/10/20 18:14:58 - mmengine - INFO - Epoch(train) [178][350/586] lr: 5.000000e-05 eta: 1:17:53 time: 0.224609 data_time: 0.024619 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.884671 loss: 0.000501 2022/10/20 18:15:09 - mmengine - INFO - Epoch(train) [178][400/586] lr: 5.000000e-05 eta: 1:17:40 time: 0.226188 data_time: 0.024875 memory: 7326 loss_kpt: 0.000505 acc_pose: 0.896495 loss: 0.000505 2022/10/20 18:15:21 - mmengine - INFO - Epoch(train) [178][450/586] lr: 5.000000e-05 eta: 1:17:28 time: 0.229967 data_time: 0.023444 memory: 7326 loss_kpt: 0.000506 acc_pose: 0.873629 loss: 0.000506 2022/10/20 18:15:32 - mmengine - INFO - Epoch(train) [178][500/586] lr: 5.000000e-05 eta: 1:17:15 time: 0.225515 data_time: 0.024259 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.847289 loss: 0.000501 2022/10/20 18:15:44 - mmengine - INFO - Epoch(train) [178][550/586] lr: 5.000000e-05 eta: 1:17:03 time: 0.228181 data_time: 0.028784 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.909261 loss: 0.000498 2022/10/20 18:15:52 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:16:04 - mmengine - INFO - Epoch(train) [179][50/586] lr: 5.000000e-05 eta: 1:16:40 time: 0.251484 data_time: 0.039048 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.881251 loss: 0.000502 2022/10/20 18:16:16 - mmengine - INFO - Epoch(train) [179][100/586] lr: 5.000000e-05 eta: 1:16:28 time: 0.237145 data_time: 0.026873 memory: 7326 loss_kpt: 0.000516 acc_pose: 0.880269 loss: 0.000516 2022/10/20 18:16:28 - mmengine - INFO - Epoch(train) [179][150/586] lr: 5.000000e-05 eta: 1:16:15 time: 0.228560 data_time: 0.026837 memory: 7326 loss_kpt: 0.000510 acc_pose: 0.825178 loss: 0.000510 2022/10/20 18:16:39 - mmengine - INFO - Epoch(train) [179][200/586] lr: 5.000000e-05 eta: 1:16:03 time: 0.227641 data_time: 0.025752 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.868953 loss: 0.000500 2022/10/20 18:16:50 - mmengine - INFO - Epoch(train) [179][250/586] lr: 5.000000e-05 eta: 1:15:51 time: 0.225574 data_time: 0.023612 memory: 7326 loss_kpt: 0.000508 acc_pose: 0.906978 loss: 0.000508 2022/10/20 18:17:02 - mmengine - INFO - Epoch(train) [179][300/586] lr: 5.000000e-05 eta: 1:15:38 time: 0.227625 data_time: 0.026123 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.934628 loss: 0.000491 2022/10/20 18:17:13 - mmengine - INFO - Epoch(train) [179][350/586] lr: 5.000000e-05 eta: 1:15:26 time: 0.226539 data_time: 0.024496 memory: 7326 loss_kpt: 0.000494 acc_pose: 0.860879 loss: 0.000494 2022/10/20 18:17:25 - mmengine - INFO - Epoch(train) [179][400/586] lr: 5.000000e-05 eta: 1:15:13 time: 0.229981 data_time: 0.032609 memory: 7326 loss_kpt: 0.000511 acc_pose: 0.879713 loss: 0.000511 2022/10/20 18:17:36 - mmengine - INFO - Epoch(train) [179][450/586] lr: 5.000000e-05 eta: 1:15:01 time: 0.228019 data_time: 0.027494 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.887922 loss: 0.000501 2022/10/20 18:17:47 - mmengine - INFO - Epoch(train) [179][500/586] lr: 5.000000e-05 eta: 1:14:48 time: 0.225788 data_time: 0.023641 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.877476 loss: 0.000492 2022/10/20 18:17:59 - mmengine - INFO - Epoch(train) [179][550/586] lr: 5.000000e-05 eta: 1:14:36 time: 0.226096 data_time: 0.025135 memory: 7326 loss_kpt: 0.000524 acc_pose: 0.925633 loss: 0.000524 2022/10/20 18:18:07 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:18:19 - mmengine - INFO - Epoch(train) [180][50/586] lr: 5.000000e-05 eta: 1:14:13 time: 0.238783 data_time: 0.037283 memory: 7326 loss_kpt: 0.000517 acc_pose: 0.886209 loss: 0.000517 2022/10/20 18:18:30 - mmengine - INFO - Epoch(train) [180][100/586] lr: 5.000000e-05 eta: 1:14:01 time: 0.229638 data_time: 0.025947 memory: 7326 loss_kpt: 0.000510 acc_pose: 0.872399 loss: 0.000510 2022/10/20 18:18:32 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:18:42 - mmengine - INFO - Epoch(train) [180][150/586] lr: 5.000000e-05 eta: 1:13:48 time: 0.227597 data_time: 0.025216 memory: 7326 loss_kpt: 0.000506 acc_pose: 0.935033 loss: 0.000506 2022/10/20 18:18:53 - mmengine - INFO - Epoch(train) [180][200/586] lr: 5.000000e-05 eta: 1:13:36 time: 0.227692 data_time: 0.026463 memory: 7326 loss_kpt: 0.000513 acc_pose: 0.866181 loss: 0.000513 2022/10/20 18:19:05 - mmengine - INFO - Epoch(train) [180][250/586] lr: 5.000000e-05 eta: 1:13:23 time: 0.233458 data_time: 0.025656 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.890444 loss: 0.000502 2022/10/20 18:19:16 - mmengine - INFO - Epoch(train) [180][300/586] lr: 5.000000e-05 eta: 1:13:11 time: 0.229810 data_time: 0.026471 memory: 7326 loss_kpt: 0.000494 acc_pose: 0.864394 loss: 0.000494 2022/10/20 18:19:28 - mmengine - INFO - Epoch(train) [180][350/586] lr: 5.000000e-05 eta: 1:12:58 time: 0.226888 data_time: 0.025465 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.929839 loss: 0.000501 2022/10/20 18:19:39 - mmengine - INFO - Epoch(train) [180][400/586] lr: 5.000000e-05 eta: 1:12:46 time: 0.230232 data_time: 0.027017 memory: 7326 loss_kpt: 0.000512 acc_pose: 0.817717 loss: 0.000512 2022/10/20 18:19:51 - mmengine - INFO - Epoch(train) [180][450/586] lr: 5.000000e-05 eta: 1:12:34 time: 0.228008 data_time: 0.022671 memory: 7326 loss_kpt: 0.000511 acc_pose: 0.880993 loss: 0.000511 2022/10/20 18:20:02 - mmengine - INFO - Epoch(train) [180][500/586] lr: 5.000000e-05 eta: 1:12:21 time: 0.227728 data_time: 0.024735 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.904071 loss: 0.000497 2022/10/20 18:20:13 - mmengine - INFO - Epoch(train) [180][550/586] lr: 5.000000e-05 eta: 1:12:09 time: 0.230649 data_time: 0.029421 memory: 7326 loss_kpt: 0.000512 acc_pose: 0.905462 loss: 0.000512 2022/10/20 18:20:21 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:20:21 - mmengine - INFO - Saving checkpoint at 180 epochs 2022/10/20 18:20:32 - mmengine - INFO - Epoch(val) [180][50/407] eta: 0:00:46 time: 0.129970 data_time: 0.040860 memory: 7326 2022/10/20 18:20:38 - mmengine - INFO - Epoch(val) [180][100/407] eta: 0:00:34 time: 0.112481 data_time: 0.030626 memory: 1680 2022/10/20 18:20:44 - mmengine - INFO - Epoch(val) [180][150/407] eta: 0:00:32 time: 0.127690 data_time: 0.045432 memory: 1680 2022/10/20 18:20:50 - mmengine - INFO - Epoch(val) [180][200/407] eta: 0:00:25 time: 0.121901 data_time: 0.038521 memory: 1680 2022/10/20 18:20:56 - mmengine - INFO - Epoch(val) [180][250/407] eta: 0:00:17 time: 0.111841 data_time: 0.028846 memory: 1680 2022/10/20 18:21:02 - mmengine - INFO - Epoch(val) [180][300/407] eta: 0:00:12 time: 0.119576 data_time: 0.036136 memory: 1680 2022/10/20 18:21:08 - mmengine - INFO - Epoch(val) [180][350/407] eta: 0:00:06 time: 0.118107 data_time: 0.035259 memory: 1680 2022/10/20 18:21:13 - mmengine - INFO - Epoch(val) [180][400/407] eta: 0:00:00 time: 0.100885 data_time: 0.022024 memory: 1680 2022/10/20 18:21:45 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 18:21:58 - mmengine - INFO - Epoch(val) [180][407/407] coco/AP: 0.736280 coco/AP .5: 0.904239 coco/AP .75: 0.816172 coco/AP (M): 0.700420 coco/AP (L): 0.802626 coco/AR: 0.790586 coco/AR .5: 0.940649 coco/AR .75: 0.860359 coco/AR (M): 0.747828 coco/AR (L): 0.852471 2022/10/20 18:21:58 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_160.pth is removed 2022/10/20 18:22:00 - mmengine - INFO - The best checkpoint with 0.7363 coco/AP at 180 epoch is saved to best_coco/AP_epoch_180.pth. 2022/10/20 18:22:12 - mmengine - INFO - Epoch(train) [181][50/586] lr: 5.000000e-05 eta: 1:11:46 time: 0.232864 data_time: 0.028893 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.881127 loss: 0.000497 2022/10/20 18:22:24 - mmengine - INFO - Epoch(train) [181][100/586] lr: 5.000000e-05 eta: 1:11:34 time: 0.237115 data_time: 0.024353 memory: 7326 loss_kpt: 0.000505 acc_pose: 0.923875 loss: 0.000505 2022/10/20 18:22:36 - mmengine - INFO - Epoch(train) [181][150/586] lr: 5.000000e-05 eta: 1:11:21 time: 0.236181 data_time: 0.028852 memory: 7326 loss_kpt: 0.000507 acc_pose: 0.916372 loss: 0.000507 2022/10/20 18:22:47 - mmengine - INFO - Epoch(train) [181][200/586] lr: 5.000000e-05 eta: 1:11:09 time: 0.226746 data_time: 0.028743 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.883484 loss: 0.000491 2022/10/20 18:22:59 - mmengine - INFO - Epoch(train) [181][250/586] lr: 5.000000e-05 eta: 1:10:56 time: 0.228705 data_time: 0.025956 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.888946 loss: 0.000496 2022/10/20 18:23:10 - mmengine - INFO - Epoch(train) [181][300/586] lr: 5.000000e-05 eta: 1:10:44 time: 0.229019 data_time: 0.025450 memory: 7326 loss_kpt: 0.000512 acc_pose: 0.901314 loss: 0.000512 2022/10/20 18:23:21 - mmengine - INFO - Epoch(train) [181][350/586] lr: 5.000000e-05 eta: 1:10:32 time: 0.224772 data_time: 0.024458 memory: 7326 loss_kpt: 0.000513 acc_pose: 0.905523 loss: 0.000513 2022/10/20 18:23:33 - mmengine - INFO - Epoch(train) [181][400/586] lr: 5.000000e-05 eta: 1:10:19 time: 0.234043 data_time: 0.030021 memory: 7326 loss_kpt: 0.000493 acc_pose: 0.896728 loss: 0.000493 2022/10/20 18:23:44 - mmengine - INFO - Epoch(train) [181][450/586] lr: 5.000000e-05 eta: 1:10:07 time: 0.223280 data_time: 0.025005 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.891009 loss: 0.000499 2022/10/20 18:23:56 - mmengine - INFO - Epoch(train) [181][500/586] lr: 5.000000e-05 eta: 1:09:54 time: 0.229363 data_time: 0.024884 memory: 7326 loss_kpt: 0.000513 acc_pose: 0.888113 loss: 0.000513 2022/10/20 18:24:00 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:24:07 - mmengine - INFO - Epoch(train) [181][550/586] lr: 5.000000e-05 eta: 1:09:42 time: 0.227342 data_time: 0.025062 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.882131 loss: 0.000501 2022/10/20 18:24:15 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:24:27 - mmengine - INFO - Epoch(train) [182][50/586] lr: 5.000000e-05 eta: 1:09:19 time: 0.236394 data_time: 0.036104 memory: 7326 loss_kpt: 0.000507 acc_pose: 0.891365 loss: 0.000507 2022/10/20 18:24:38 - mmengine - INFO - Epoch(train) [182][100/586] lr: 5.000000e-05 eta: 1:09:07 time: 0.221092 data_time: 0.025919 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.936332 loss: 0.000497 2022/10/20 18:24:50 - mmengine - INFO - Epoch(train) [182][150/586] lr: 5.000000e-05 eta: 1:08:54 time: 0.240228 data_time: 0.028453 memory: 7326 loss_kpt: 0.000484 acc_pose: 0.860317 loss: 0.000484 2022/10/20 18:25:02 - mmengine - INFO - Epoch(train) [182][200/586] lr: 5.000000e-05 eta: 1:08:42 time: 0.234724 data_time: 0.025206 memory: 7326 loss_kpt: 0.000504 acc_pose: 0.887149 loss: 0.000504 2022/10/20 18:25:13 - mmengine - INFO - Epoch(train) [182][250/586] lr: 5.000000e-05 eta: 1:08:30 time: 0.231674 data_time: 0.026932 memory: 7326 loss_kpt: 0.000484 acc_pose: 0.886632 loss: 0.000484 2022/10/20 18:25:25 - mmengine - INFO - Epoch(train) [182][300/586] lr: 5.000000e-05 eta: 1:08:17 time: 0.227263 data_time: 0.030448 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.932791 loss: 0.000496 2022/10/20 18:25:36 - mmengine - INFO - Epoch(train) [182][350/586] lr: 5.000000e-05 eta: 1:08:05 time: 0.227625 data_time: 0.025904 memory: 7326 loss_kpt: 0.000505 acc_pose: 0.865514 loss: 0.000505 2022/10/20 18:25:47 - mmengine - INFO - Epoch(train) [182][400/586] lr: 5.000000e-05 eta: 1:07:52 time: 0.225434 data_time: 0.026456 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.859133 loss: 0.000498 2022/10/20 18:25:59 - mmengine - INFO - Epoch(train) [182][450/586] lr: 5.000000e-05 eta: 1:07:40 time: 0.227450 data_time: 0.027316 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.917186 loss: 0.000502 2022/10/20 18:26:10 - mmengine - INFO - Epoch(train) [182][500/586] lr: 5.000000e-05 eta: 1:07:28 time: 0.233503 data_time: 0.023979 memory: 7326 loss_kpt: 0.000514 acc_pose: 0.824082 loss: 0.000514 2022/10/20 18:26:21 - mmengine - INFO - Epoch(train) [182][550/586] lr: 5.000000e-05 eta: 1:07:15 time: 0.218434 data_time: 0.024765 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.893391 loss: 0.000498 2022/10/20 18:26:29 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:26:41 - mmengine - INFO - Epoch(train) [183][50/586] lr: 5.000000e-05 eta: 1:06:53 time: 0.235096 data_time: 0.032830 memory: 7326 loss_kpt: 0.000504 acc_pose: 0.851239 loss: 0.000504 2022/10/20 18:26:53 - mmengine - INFO - Epoch(train) [183][100/586] lr: 5.000000e-05 eta: 1:06:40 time: 0.228485 data_time: 0.024267 memory: 7326 loss_kpt: 0.000507 acc_pose: 0.881449 loss: 0.000507 2022/10/20 18:27:04 - mmengine - INFO - Epoch(train) [183][150/586] lr: 5.000000e-05 eta: 1:06:28 time: 0.233973 data_time: 0.031458 memory: 7326 loss_kpt: 0.000493 acc_pose: 0.906978 loss: 0.000493 2022/10/20 18:27:15 - mmengine - INFO - Epoch(train) [183][200/586] lr: 5.000000e-05 eta: 1:06:16 time: 0.223239 data_time: 0.024379 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.883926 loss: 0.000498 2022/10/20 18:27:27 - mmengine - INFO - Epoch(train) [183][250/586] lr: 5.000000e-05 eta: 1:06:03 time: 0.229551 data_time: 0.023702 memory: 7326 loss_kpt: 0.000476 acc_pose: 0.874473 loss: 0.000476 2022/10/20 18:27:39 - mmengine - INFO - Epoch(train) [183][300/586] lr: 5.000000e-05 eta: 1:05:51 time: 0.237535 data_time: 0.025604 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.903445 loss: 0.000502 2022/10/20 18:27:50 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:27:50 - mmengine - INFO - Epoch(train) [183][350/586] lr: 5.000000e-05 eta: 1:05:38 time: 0.232328 data_time: 0.026716 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.864220 loss: 0.000499 2022/10/20 18:28:02 - mmengine - INFO - Epoch(train) [183][400/586] lr: 5.000000e-05 eta: 1:05:26 time: 0.225385 data_time: 0.028000 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.888675 loss: 0.000496 2022/10/20 18:28:13 - mmengine - INFO - Epoch(train) [183][450/586] lr: 5.000000e-05 eta: 1:05:14 time: 0.226064 data_time: 0.025018 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.898797 loss: 0.000500 2022/10/20 18:28:24 - mmengine - INFO - Epoch(train) [183][500/586] lr: 5.000000e-05 eta: 1:05:01 time: 0.224891 data_time: 0.024468 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.879960 loss: 0.000500 2022/10/20 18:28:36 - mmengine - INFO - Epoch(train) [183][550/586] lr: 5.000000e-05 eta: 1:04:49 time: 0.232211 data_time: 0.025317 memory: 7326 loss_kpt: 0.000512 acc_pose: 0.891203 loss: 0.000512 2022/10/20 18:28:44 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:28:56 - mmengine - INFO - Epoch(train) [184][50/586] lr: 5.000000e-05 eta: 1:04:26 time: 0.227372 data_time: 0.033420 memory: 7326 loss_kpt: 0.000512 acc_pose: 0.906222 loss: 0.000512 2022/10/20 18:29:07 - mmengine - INFO - Epoch(train) [184][100/586] lr: 5.000000e-05 eta: 1:04:14 time: 0.228232 data_time: 0.024331 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.860620 loss: 0.000488 2022/10/20 18:29:19 - mmengine - INFO - Epoch(train) [184][150/586] lr: 5.000000e-05 eta: 1:04:02 time: 0.228038 data_time: 0.027261 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.799315 loss: 0.000498 2022/10/20 18:29:30 - mmengine - INFO - Epoch(train) [184][200/586] lr: 5.000000e-05 eta: 1:03:49 time: 0.227305 data_time: 0.024970 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.891196 loss: 0.000490 2022/10/20 18:29:42 - mmengine - INFO - Epoch(train) [184][250/586] lr: 5.000000e-05 eta: 1:03:37 time: 0.232636 data_time: 0.025585 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.914643 loss: 0.000499 2022/10/20 18:29:53 - mmengine - INFO - Epoch(train) [184][300/586] lr: 5.000000e-05 eta: 1:03:24 time: 0.222940 data_time: 0.026693 memory: 7326 loss_kpt: 0.000504 acc_pose: 0.817401 loss: 0.000504 2022/10/20 18:30:04 - mmengine - INFO - Epoch(train) [184][350/586] lr: 5.000000e-05 eta: 1:03:12 time: 0.234009 data_time: 0.024813 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.942643 loss: 0.000488 2022/10/20 18:30:16 - mmengine - INFO - Epoch(train) [184][400/586] lr: 5.000000e-05 eta: 1:03:00 time: 0.232669 data_time: 0.023677 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.872520 loss: 0.000491 2022/10/20 18:30:28 - mmengine - INFO - Epoch(train) [184][450/586] lr: 5.000000e-05 eta: 1:02:47 time: 0.239568 data_time: 0.026486 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.888060 loss: 0.000500 2022/10/20 18:30:39 - mmengine - INFO - Epoch(train) [184][500/586] lr: 5.000000e-05 eta: 1:02:35 time: 0.223904 data_time: 0.029346 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.879933 loss: 0.000488 2022/10/20 18:30:51 - mmengine - INFO - Epoch(train) [184][550/586] lr: 5.000000e-05 eta: 1:02:23 time: 0.230756 data_time: 0.024593 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.877596 loss: 0.000488 2022/10/20 18:30:59 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:31:11 - mmengine - INFO - Epoch(train) [185][50/586] lr: 5.000000e-05 eta: 1:02:00 time: 0.241013 data_time: 0.032593 memory: 7326 loss_kpt: 0.000505 acc_pose: 0.846336 loss: 0.000505 2022/10/20 18:31:22 - mmengine - INFO - Epoch(train) [185][100/586] lr: 5.000000e-05 eta: 1:01:48 time: 0.227174 data_time: 0.027683 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.898695 loss: 0.000491 2022/10/20 18:31:34 - mmengine - INFO - Epoch(train) [185][150/586] lr: 5.000000e-05 eta: 1:01:36 time: 0.226098 data_time: 0.031825 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.857033 loss: 0.000501 2022/10/20 18:31:39 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:31:45 - mmengine - INFO - Epoch(train) [185][200/586] lr: 5.000000e-05 eta: 1:01:23 time: 0.225715 data_time: 0.028597 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.874648 loss: 0.000490 2022/10/20 18:31:56 - mmengine - INFO - Epoch(train) [185][250/586] lr: 5.000000e-05 eta: 1:01:11 time: 0.226716 data_time: 0.025084 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.936296 loss: 0.000491 2022/10/20 18:32:08 - mmengine - INFO - Epoch(train) [185][300/586] lr: 5.000000e-05 eta: 1:00:58 time: 0.232406 data_time: 0.024260 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.879629 loss: 0.000500 2022/10/20 18:32:20 - mmengine - INFO - Epoch(train) [185][350/586] lr: 5.000000e-05 eta: 1:00:46 time: 0.232954 data_time: 0.023984 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.866662 loss: 0.000502 2022/10/20 18:32:31 - mmengine - INFO - Epoch(train) [185][400/586] lr: 5.000000e-05 eta: 1:00:34 time: 0.230112 data_time: 0.023999 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.819682 loss: 0.000500 2022/10/20 18:32:43 - mmengine - INFO - Epoch(train) [185][450/586] lr: 5.000000e-05 eta: 1:00:21 time: 0.233167 data_time: 0.028237 memory: 7326 loss_kpt: 0.000495 acc_pose: 0.919869 loss: 0.000495 2022/10/20 18:32:54 - mmengine - INFO - Epoch(train) [185][500/586] lr: 5.000000e-05 eta: 1:00:09 time: 0.231078 data_time: 0.023698 memory: 7326 loss_kpt: 0.000482 acc_pose: 0.867406 loss: 0.000482 2022/10/20 18:33:06 - mmengine - INFO - Epoch(train) [185][550/586] lr: 5.000000e-05 eta: 0:59:57 time: 0.234852 data_time: 0.028327 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.867510 loss: 0.000498 2022/10/20 18:33:14 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:33:26 - mmengine - INFO - Epoch(train) [186][50/586] lr: 5.000000e-05 eta: 0:59:34 time: 0.230747 data_time: 0.037693 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.905877 loss: 0.000498 2022/10/20 18:33:37 - mmengine - INFO - Epoch(train) [186][100/586] lr: 5.000000e-05 eta: 0:59:22 time: 0.226781 data_time: 0.025280 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.860209 loss: 0.000492 2022/10/20 18:33:48 - mmengine - INFO - Epoch(train) [186][150/586] lr: 5.000000e-05 eta: 0:59:10 time: 0.226770 data_time: 0.024658 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.875041 loss: 0.000502 2022/10/20 18:34:00 - mmengine - INFO - Epoch(train) [186][200/586] lr: 5.000000e-05 eta: 0:58:57 time: 0.237575 data_time: 0.028627 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.902698 loss: 0.000500 2022/10/20 18:34:12 - mmengine - INFO - Epoch(train) [186][250/586] lr: 5.000000e-05 eta: 0:58:45 time: 0.224232 data_time: 0.026267 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.908359 loss: 0.000498 2022/10/20 18:34:23 - mmengine - INFO - Epoch(train) [186][300/586] lr: 5.000000e-05 eta: 0:58:33 time: 0.230636 data_time: 0.025341 memory: 7326 loss_kpt: 0.000509 acc_pose: 0.890755 loss: 0.000509 2022/10/20 18:34:35 - mmengine - INFO - Epoch(train) [186][350/586] lr: 5.000000e-05 eta: 0:58:20 time: 0.229240 data_time: 0.030238 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.881294 loss: 0.000498 2022/10/20 18:34:46 - mmengine - INFO - Epoch(train) [186][400/586] lr: 5.000000e-05 eta: 0:58:08 time: 0.231408 data_time: 0.027345 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.919960 loss: 0.000492 2022/10/20 18:34:57 - mmengine - INFO - Epoch(train) [186][450/586] lr: 5.000000e-05 eta: 0:57:56 time: 0.223090 data_time: 0.024662 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.919847 loss: 0.000500 2022/10/20 18:35:09 - mmengine - INFO - Epoch(train) [186][500/586] lr: 5.000000e-05 eta: 0:57:43 time: 0.230199 data_time: 0.025186 memory: 7326 loss_kpt: 0.000508 acc_pose: 0.909921 loss: 0.000508 2022/10/20 18:35:21 - mmengine - INFO - Epoch(train) [186][550/586] lr: 5.000000e-05 eta: 0:57:31 time: 0.233079 data_time: 0.029096 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.909231 loss: 0.000500 2022/10/20 18:35:29 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:35:30 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:35:41 - mmengine - INFO - Epoch(train) [187][50/586] lr: 5.000000e-05 eta: 0:57:09 time: 0.254093 data_time: 0.040291 memory: 7326 loss_kpt: 0.000495 acc_pose: 0.868234 loss: 0.000495 2022/10/20 18:35:53 - mmengine - INFO - Epoch(train) [187][100/586] lr: 5.000000e-05 eta: 0:56:57 time: 0.224442 data_time: 0.024739 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.883738 loss: 0.000496 2022/10/20 18:36:04 - mmengine - INFO - Epoch(train) [187][150/586] lr: 5.000000e-05 eta: 0:56:44 time: 0.222475 data_time: 0.027259 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.884498 loss: 0.000497 2022/10/20 18:36:15 - mmengine - INFO - Epoch(train) [187][200/586] lr: 5.000000e-05 eta: 0:56:32 time: 0.228227 data_time: 0.022461 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.908558 loss: 0.000499 2022/10/20 18:36:27 - mmengine - INFO - Epoch(train) [187][250/586] lr: 5.000000e-05 eta: 0:56:19 time: 0.227159 data_time: 0.026089 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.850391 loss: 0.000499 2022/10/20 18:36:38 - mmengine - INFO - Epoch(train) [187][300/586] lr: 5.000000e-05 eta: 0:56:07 time: 0.230016 data_time: 0.030054 memory: 7326 loss_kpt: 0.000506 acc_pose: 0.819652 loss: 0.000506 2022/10/20 18:36:49 - mmengine - INFO - Epoch(train) [187][350/586] lr: 5.000000e-05 eta: 0:55:55 time: 0.225689 data_time: 0.026221 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.880700 loss: 0.000488 2022/10/20 18:37:00 - mmengine - INFO - Epoch(train) [187][400/586] lr: 5.000000e-05 eta: 0:55:42 time: 0.218821 data_time: 0.024620 memory: 7326 loss_kpt: 0.000481 acc_pose: 0.839771 loss: 0.000481 2022/10/20 18:37:12 - mmengine - INFO - Epoch(train) [187][450/586] lr: 5.000000e-05 eta: 0:55:30 time: 0.228159 data_time: 0.025839 memory: 7326 loss_kpt: 0.000510 acc_pose: 0.834640 loss: 0.000510 2022/10/20 18:37:23 - mmengine - INFO - Epoch(train) [187][500/586] lr: 5.000000e-05 eta: 0:55:18 time: 0.231289 data_time: 0.024554 memory: 7326 loss_kpt: 0.000477 acc_pose: 0.874413 loss: 0.000477 2022/10/20 18:37:35 - mmengine - INFO - Epoch(train) [187][550/586] lr: 5.000000e-05 eta: 0:55:05 time: 0.229274 data_time: 0.026447 memory: 7326 loss_kpt: 0.000507 acc_pose: 0.933434 loss: 0.000507 2022/10/20 18:37:43 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:37:55 - mmengine - INFO - Epoch(train) [188][50/586] lr: 5.000000e-05 eta: 0:54:43 time: 0.244761 data_time: 0.036895 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.915719 loss: 0.000491 2022/10/20 18:38:06 - mmengine - INFO - Epoch(train) [188][100/586] lr: 5.000000e-05 eta: 0:54:31 time: 0.229151 data_time: 0.026513 memory: 7326 loss_kpt: 0.000495 acc_pose: 0.849784 loss: 0.000495 2022/10/20 18:38:18 - mmengine - INFO - Epoch(train) [188][150/586] lr: 5.000000e-05 eta: 0:54:19 time: 0.236221 data_time: 0.023576 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.925456 loss: 0.000499 2022/10/20 18:38:30 - mmengine - INFO - Epoch(train) [188][200/586] lr: 5.000000e-05 eta: 0:54:06 time: 0.229959 data_time: 0.026673 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.880665 loss: 0.000498 2022/10/20 18:38:42 - mmengine - INFO - Epoch(train) [188][250/586] lr: 5.000000e-05 eta: 0:53:54 time: 0.239141 data_time: 0.025615 memory: 7326 loss_kpt: 0.000503 acc_pose: 0.845141 loss: 0.000503 2022/10/20 18:38:53 - mmengine - INFO - Epoch(train) [188][300/586] lr: 5.000000e-05 eta: 0:53:42 time: 0.231529 data_time: 0.026679 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.915790 loss: 0.000488 2022/10/20 18:39:05 - mmengine - INFO - Epoch(train) [188][350/586] lr: 5.000000e-05 eta: 0:53:30 time: 0.239517 data_time: 0.024820 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.881956 loss: 0.000501 2022/10/20 18:39:16 - mmengine - INFO - Epoch(train) [188][400/586] lr: 5.000000e-05 eta: 0:53:17 time: 0.221283 data_time: 0.022768 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.875281 loss: 0.000497 2022/10/20 18:39:21 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:39:28 - mmengine - INFO - Epoch(train) [188][450/586] lr: 5.000000e-05 eta: 0:53:05 time: 0.235291 data_time: 0.030932 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.851372 loss: 0.000485 2022/10/20 18:39:40 - mmengine - INFO - Epoch(train) [188][500/586] lr: 5.000000e-05 eta: 0:52:53 time: 0.234971 data_time: 0.027779 memory: 7326 loss_kpt: 0.000494 acc_pose: 0.870058 loss: 0.000494 2022/10/20 18:39:51 - mmengine - INFO - Epoch(train) [188][550/586] lr: 5.000000e-05 eta: 0:52:40 time: 0.228254 data_time: 0.025663 memory: 7326 loss_kpt: 0.000509 acc_pose: 0.890241 loss: 0.000509 2022/10/20 18:40:00 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:40:11 - mmengine - INFO - Epoch(train) [189][50/586] lr: 5.000000e-05 eta: 0:52:18 time: 0.233800 data_time: 0.033462 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.907953 loss: 0.000497 2022/10/20 18:40:23 - mmengine - INFO - Epoch(train) [189][100/586] lr: 5.000000e-05 eta: 0:52:06 time: 0.223534 data_time: 0.031686 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.892349 loss: 0.000498 2022/10/20 18:40:34 - mmengine - INFO - Epoch(train) [189][150/586] lr: 5.000000e-05 eta: 0:51:54 time: 0.230240 data_time: 0.027092 memory: 7326 loss_kpt: 0.000495 acc_pose: 0.907210 loss: 0.000495 2022/10/20 18:40:46 - mmengine - INFO - Epoch(train) [189][200/586] lr: 5.000000e-05 eta: 0:51:41 time: 0.232967 data_time: 0.025404 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.862682 loss: 0.000489 2022/10/20 18:40:58 - mmengine - INFO - Epoch(train) [189][250/586] lr: 5.000000e-05 eta: 0:51:29 time: 0.235412 data_time: 0.028134 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.887922 loss: 0.000492 2022/10/20 18:41:09 - mmengine - INFO - Epoch(train) [189][300/586] lr: 5.000000e-05 eta: 0:51:17 time: 0.230598 data_time: 0.031994 memory: 7326 loss_kpt: 0.000494 acc_pose: 0.869227 loss: 0.000494 2022/10/20 18:41:21 - mmengine - INFO - Epoch(train) [189][350/586] lr: 5.000000e-05 eta: 0:51:04 time: 0.234152 data_time: 0.025307 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.866911 loss: 0.000496 2022/10/20 18:41:33 - mmengine - INFO - Epoch(train) [189][400/586] lr: 5.000000e-05 eta: 0:50:52 time: 0.232262 data_time: 0.031167 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.893228 loss: 0.000500 2022/10/20 18:41:44 - mmengine - INFO - Epoch(train) [189][450/586] lr: 5.000000e-05 eta: 0:50:40 time: 0.229572 data_time: 0.025836 memory: 7326 loss_kpt: 0.000487 acc_pose: 0.900269 loss: 0.000487 2022/10/20 18:41:56 - mmengine - INFO - Epoch(train) [189][500/586] lr: 5.000000e-05 eta: 0:50:28 time: 0.232603 data_time: 0.026013 memory: 7326 loss_kpt: 0.000479 acc_pose: 0.813483 loss: 0.000479 2022/10/20 18:42:07 - mmengine - INFO - Epoch(train) [189][550/586] lr: 5.000000e-05 eta: 0:50:15 time: 0.229904 data_time: 0.026525 memory: 7326 loss_kpt: 0.000503 acc_pose: 0.868605 loss: 0.000503 2022/10/20 18:42:15 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:42:27 - mmengine - INFO - Epoch(train) [190][50/586] lr: 5.000000e-05 eta: 0:49:53 time: 0.237908 data_time: 0.032825 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.823864 loss: 0.000492 2022/10/20 18:42:39 - mmengine - INFO - Epoch(train) [190][100/586] lr: 5.000000e-05 eta: 0:49:41 time: 0.233072 data_time: 0.024452 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.862757 loss: 0.000496 2022/10/20 18:42:50 - mmengine - INFO - Epoch(train) [190][150/586] lr: 5.000000e-05 eta: 0:49:29 time: 0.227330 data_time: 0.024234 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.917246 loss: 0.000492 2022/10/20 18:43:02 - mmengine - INFO - Epoch(train) [190][200/586] lr: 5.000000e-05 eta: 0:49:16 time: 0.238743 data_time: 0.026519 memory: 7326 loss_kpt: 0.000486 acc_pose: 0.860681 loss: 0.000486 2022/10/20 18:43:13 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:43:14 - mmengine - INFO - Epoch(train) [190][250/586] lr: 5.000000e-05 eta: 0:49:04 time: 0.235941 data_time: 0.025030 memory: 7326 loss_kpt: 0.000509 acc_pose: 0.866399 loss: 0.000509 2022/10/20 18:43:26 - mmengine - INFO - Epoch(train) [190][300/586] lr: 5.000000e-05 eta: 0:48:52 time: 0.235927 data_time: 0.024347 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.889447 loss: 0.000498 2022/10/20 18:43:37 - mmengine - INFO - Epoch(train) [190][350/586] lr: 5.000000e-05 eta: 0:48:40 time: 0.228710 data_time: 0.028338 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.915942 loss: 0.000502 2022/10/20 18:43:49 - mmengine - INFO - Epoch(train) [190][400/586] lr: 5.000000e-05 eta: 0:48:27 time: 0.228599 data_time: 0.033069 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.920302 loss: 0.000490 2022/10/20 18:44:01 - mmengine - INFO - Epoch(train) [190][450/586] lr: 5.000000e-05 eta: 0:48:15 time: 0.238490 data_time: 0.023173 memory: 7326 loss_kpt: 0.000506 acc_pose: 0.906644 loss: 0.000506 2022/10/20 18:44:13 - mmengine - INFO - Epoch(train) [190][500/586] lr: 5.000000e-05 eta: 0:48:03 time: 0.237311 data_time: 0.024783 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.882421 loss: 0.000500 2022/10/20 18:44:25 - mmengine - INFO - Epoch(train) [190][550/586] lr: 5.000000e-05 eta: 0:47:51 time: 0.238667 data_time: 0.030634 memory: 7326 loss_kpt: 0.000509 acc_pose: 0.847403 loss: 0.000509 2022/10/20 18:44:33 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:44:33 - mmengine - INFO - Saving checkpoint at 190 epochs 2022/10/20 18:44:45 - mmengine - INFO - Epoch(val) [190][50/407] eta: 0:00:53 time: 0.148744 data_time: 0.067555 memory: 7326 2022/10/20 18:44:52 - mmengine - INFO - Epoch(val) [190][100/407] eta: 0:00:44 time: 0.146179 data_time: 0.065957 memory: 1680 2022/10/20 18:45:00 - mmengine - INFO - Epoch(val) [190][150/407] eta: 0:00:40 time: 0.159359 data_time: 0.080967 memory: 1680 2022/10/20 18:45:07 - mmengine - INFO - Epoch(val) [190][200/407] eta: 0:00:28 time: 0.139240 data_time: 0.059185 memory: 1680 2022/10/20 18:45:14 - mmengine - INFO - Epoch(val) [190][250/407] eta: 0:00:21 time: 0.140107 data_time: 0.058716 memory: 1680 2022/10/20 18:45:21 - mmengine - INFO - Epoch(val) [190][300/407] eta: 0:00:14 time: 0.132525 data_time: 0.052880 memory: 1680 2022/10/20 18:45:28 - mmengine - INFO - Epoch(val) [190][350/407] eta: 0:00:07 time: 0.138944 data_time: 0.058941 memory: 1680 2022/10/20 18:45:35 - mmengine - INFO - Epoch(val) [190][400/407] eta: 0:00:00 time: 0.138533 data_time: 0.060489 memory: 1680 2022/10/20 18:46:19 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 18:46:32 - mmengine - INFO - Epoch(val) [190][407/407] coco/AP: 0.735679 coco/AP .5: 0.900870 coco/AP .75: 0.815761 coco/AP (M): 0.699101 coco/AP (L): 0.803803 coco/AR: 0.790255 coco/AR .5: 0.939232 coco/AR .75: 0.860674 coco/AR (M): 0.747173 coco/AR (L): 0.852768 2022/10/20 18:46:44 - mmengine - INFO - Epoch(train) [191][50/586] lr: 5.000000e-05 eta: 0:47:29 time: 0.255271 data_time: 0.032249 memory: 7326 loss_kpt: 0.000483 acc_pose: 0.895174 loss: 0.000483 2022/10/20 18:46:57 - mmengine - INFO - Epoch(train) [191][100/586] lr: 5.000000e-05 eta: 0:47:17 time: 0.257474 data_time: 0.029280 memory: 7326 loss_kpt: 0.000506 acc_pose: 0.869403 loss: 0.000506 2022/10/20 18:47:09 - mmengine - INFO - Epoch(train) [191][150/586] lr: 5.000000e-05 eta: 0:47:04 time: 0.244249 data_time: 0.027442 memory: 7326 loss_kpt: 0.000493 acc_pose: 0.852907 loss: 0.000493 2022/10/20 18:47:22 - mmengine - INFO - Epoch(train) [191][200/586] lr: 5.000000e-05 eta: 0:46:52 time: 0.252019 data_time: 0.041066 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.872084 loss: 0.000502 2022/10/20 18:47:35 - mmengine - INFO - Epoch(train) [191][250/586] lr: 5.000000e-05 eta: 0:46:40 time: 0.261132 data_time: 0.024939 memory: 7326 loss_kpt: 0.000484 acc_pose: 0.919051 loss: 0.000484 2022/10/20 18:47:47 - mmengine - INFO - Epoch(train) [191][300/586] lr: 5.000000e-05 eta: 0:46:28 time: 0.235564 data_time: 0.026553 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.892937 loss: 0.000498 2022/10/20 18:47:59 - mmengine - INFO - Epoch(train) [191][350/586] lr: 5.000000e-05 eta: 0:46:16 time: 0.243491 data_time: 0.037784 memory: 7326 loss_kpt: 0.000504 acc_pose: 0.879500 loss: 0.000504 2022/10/20 18:48:11 - mmengine - INFO - Epoch(train) [191][400/586] lr: 5.000000e-05 eta: 0:46:03 time: 0.239069 data_time: 0.031948 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.870746 loss: 0.000500 2022/10/20 18:48:24 - mmengine - INFO - Epoch(train) [191][450/586] lr: 5.000000e-05 eta: 0:45:51 time: 0.248869 data_time: 0.026540 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.899618 loss: 0.000496 2022/10/20 18:48:36 - mmengine - INFO - Epoch(train) [191][500/586] lr: 5.000000e-05 eta: 0:45:39 time: 0.254557 data_time: 0.028395 memory: 7326 loss_kpt: 0.000512 acc_pose: 0.864759 loss: 0.000512 2022/10/20 18:48:50 - mmengine - INFO - Epoch(train) [191][550/586] lr: 5.000000e-05 eta: 0:45:27 time: 0.264061 data_time: 0.024379 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.881137 loss: 0.000485 2022/10/20 18:48:59 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:49:12 - mmengine - INFO - Epoch(train) [192][50/586] lr: 5.000000e-05 eta: 0:45:05 time: 0.259986 data_time: 0.033572 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.844544 loss: 0.000500 2022/10/20 18:49:17 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:49:24 - mmengine - INFO - Epoch(train) [192][100/586] lr: 5.000000e-05 eta: 0:44:53 time: 0.244649 data_time: 0.043317 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.866129 loss: 0.000498 2022/10/20 18:49:36 - mmengine - INFO - Epoch(train) [192][150/586] lr: 5.000000e-05 eta: 0:44:41 time: 0.239816 data_time: 0.024616 memory: 7326 loss_kpt: 0.000506 acc_pose: 0.883366 loss: 0.000506 2022/10/20 18:49:47 - mmengine - INFO - Epoch(train) [192][200/586] lr: 5.000000e-05 eta: 0:44:28 time: 0.231188 data_time: 0.028141 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.866585 loss: 0.000501 2022/10/20 18:50:01 - mmengine - INFO - Epoch(train) [192][250/586] lr: 5.000000e-05 eta: 0:44:16 time: 0.266953 data_time: 0.026792 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.871733 loss: 0.000490 2022/10/20 18:50:14 - mmengine - INFO - Epoch(train) [192][300/586] lr: 5.000000e-05 eta: 0:44:04 time: 0.256665 data_time: 0.026790 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.886961 loss: 0.000499 2022/10/20 18:50:26 - mmengine - INFO - Epoch(train) [192][350/586] lr: 5.000000e-05 eta: 0:43:52 time: 0.249990 data_time: 0.025158 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.890029 loss: 0.000489 2022/10/20 18:50:39 - mmengine - INFO - Epoch(train) [192][400/586] lr: 5.000000e-05 eta: 0:43:40 time: 0.258667 data_time: 0.026211 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.898436 loss: 0.000492 2022/10/20 18:50:51 - mmengine - INFO - Epoch(train) [192][450/586] lr: 5.000000e-05 eta: 0:43:28 time: 0.233409 data_time: 0.031284 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.898800 loss: 0.000485 2022/10/20 18:51:04 - mmengine - INFO - Epoch(train) [192][500/586] lr: 5.000000e-05 eta: 0:43:16 time: 0.269039 data_time: 0.026806 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.753930 loss: 0.000490 2022/10/20 18:51:17 - mmengine - INFO - Epoch(train) [192][550/586] lr: 5.000000e-05 eta: 0:43:03 time: 0.250029 data_time: 0.037403 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.867569 loss: 0.000489 2022/10/20 18:51:27 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:51:40 - mmengine - INFO - Epoch(train) [193][50/586] lr: 5.000000e-05 eta: 0:42:42 time: 0.262291 data_time: 0.042025 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.901474 loss: 0.000492 2022/10/20 18:51:53 - mmengine - INFO - Epoch(train) [193][100/586] lr: 5.000000e-05 eta: 0:42:29 time: 0.249858 data_time: 0.028204 memory: 7326 loss_kpt: 0.000494 acc_pose: 0.888630 loss: 0.000494 2022/10/20 18:52:05 - mmengine - INFO - Epoch(train) [193][150/586] lr: 5.000000e-05 eta: 0:42:17 time: 0.240465 data_time: 0.026834 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.880030 loss: 0.000485 2022/10/20 18:52:18 - mmengine - INFO - Epoch(train) [193][200/586] lr: 5.000000e-05 eta: 0:42:05 time: 0.263619 data_time: 0.029059 memory: 7326 loss_kpt: 0.000487 acc_pose: 0.839047 loss: 0.000487 2022/10/20 18:52:32 - mmengine - INFO - Epoch(train) [193][250/586] lr: 5.000000e-05 eta: 0:41:53 time: 0.267708 data_time: 0.026218 memory: 7326 loss_kpt: 0.000487 acc_pose: 0.889289 loss: 0.000487 2022/10/20 18:52:46 - mmengine - INFO - Epoch(train) [193][300/586] lr: 5.000000e-05 eta: 0:41:41 time: 0.291163 data_time: 0.035898 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.904348 loss: 0.000496 2022/10/20 18:53:01 - mmengine - INFO - Epoch(train) [193][350/586] lr: 5.000000e-05 eta: 0:41:29 time: 0.287464 data_time: 0.026013 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.925371 loss: 0.000497 2022/10/20 18:53:14 - mmengine - INFO - Epoch(train) [193][400/586] lr: 5.000000e-05 eta: 0:41:17 time: 0.266621 data_time: 0.032861 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.905102 loss: 0.000491 2022/10/20 18:53:29 - mmengine - INFO - Epoch(train) [193][450/586] lr: 5.000000e-05 eta: 0:41:05 time: 0.303693 data_time: 0.046935 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.849019 loss: 0.000490 2022/10/20 18:53:39 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:53:42 - mmengine - INFO - Epoch(train) [193][500/586] lr: 5.000000e-05 eta: 0:40:53 time: 0.263454 data_time: 0.036442 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.866245 loss: 0.000491 2022/10/20 18:53:56 - mmengine - INFO - Epoch(train) [193][550/586] lr: 5.000000e-05 eta: 0:40:41 time: 0.277230 data_time: 0.074179 memory: 7326 loss_kpt: 0.000495 acc_pose: 0.909309 loss: 0.000495 2022/10/20 18:54:06 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:54:20 - mmengine - INFO - Epoch(train) [194][50/586] lr: 5.000000e-05 eta: 0:40:19 time: 0.272261 data_time: 0.053326 memory: 7326 loss_kpt: 0.000479 acc_pose: 0.885495 loss: 0.000479 2022/10/20 18:54:33 - mmengine - INFO - Epoch(train) [194][100/586] lr: 5.000000e-05 eta: 0:40:07 time: 0.279410 data_time: 0.069614 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.919527 loss: 0.000497 2022/10/20 18:54:47 - mmengine - INFO - Epoch(train) [194][150/586] lr: 5.000000e-05 eta: 0:39:55 time: 0.261419 data_time: 0.034973 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.867506 loss: 0.000496 2022/10/20 18:54:59 - mmengine - INFO - Epoch(train) [194][200/586] lr: 5.000000e-05 eta: 0:39:43 time: 0.238697 data_time: 0.032268 memory: 7326 loss_kpt: 0.000479 acc_pose: 0.891093 loss: 0.000479 2022/10/20 18:55:11 - mmengine - INFO - Epoch(train) [194][250/586] lr: 5.000000e-05 eta: 0:39:31 time: 0.251560 data_time: 0.032224 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.913012 loss: 0.000485 2022/10/20 18:55:26 - mmengine - INFO - Epoch(train) [194][300/586] lr: 5.000000e-05 eta: 0:39:19 time: 0.289549 data_time: 0.027439 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.875558 loss: 0.000500 2022/10/20 18:55:41 - mmengine - INFO - Epoch(train) [194][350/586] lr: 5.000000e-05 eta: 0:39:07 time: 0.297647 data_time: 0.043169 memory: 7326 loss_kpt: 0.000509 acc_pose: 0.882242 loss: 0.000509 2022/10/20 18:55:54 - mmengine - INFO - Epoch(train) [194][400/586] lr: 5.000000e-05 eta: 0:38:54 time: 0.265055 data_time: 0.029932 memory: 7326 loss_kpt: 0.000505 acc_pose: 0.863400 loss: 0.000505 2022/10/20 18:56:09 - mmengine - INFO - Epoch(train) [194][450/586] lr: 5.000000e-05 eta: 0:38:43 time: 0.311234 data_time: 0.029873 memory: 7326 loss_kpt: 0.000480 acc_pose: 0.925312 loss: 0.000480 2022/10/20 18:56:23 - mmengine - INFO - Epoch(train) [194][500/586] lr: 5.000000e-05 eta: 0:38:30 time: 0.276575 data_time: 0.042144 memory: 7326 loss_kpt: 0.000472 acc_pose: 0.882721 loss: 0.000472 2022/10/20 18:56:36 - mmengine - INFO - Epoch(train) [194][550/586] lr: 5.000000e-05 eta: 0:38:18 time: 0.261434 data_time: 0.025969 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.892240 loss: 0.000502 2022/10/20 18:56:46 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:57:01 - mmengine - INFO - Epoch(train) [195][50/586] lr: 5.000000e-05 eta: 0:37:57 time: 0.301244 data_time: 0.063321 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.880077 loss: 0.000501 2022/10/20 18:57:15 - mmengine - INFO - Epoch(train) [195][100/586] lr: 5.000000e-05 eta: 0:37:45 time: 0.281169 data_time: 0.035643 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.871598 loss: 0.000488 2022/10/20 18:57:34 - mmengine - INFO - Epoch(train) [195][150/586] lr: 5.000000e-05 eta: 0:37:33 time: 0.369027 data_time: 0.028753 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.822678 loss: 0.000492 2022/10/20 18:57:50 - mmengine - INFO - Epoch(train) [195][200/586] lr: 5.000000e-05 eta: 0:37:21 time: 0.324523 data_time: 0.040620 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.907332 loss: 0.000496 2022/10/20 18:58:07 - mmengine - INFO - Epoch(train) [195][250/586] lr: 5.000000e-05 eta: 0:37:09 time: 0.331657 data_time: 0.040970 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.796568 loss: 0.000501 2022/10/20 18:58:24 - mmengine - INFO - Epoch(train) [195][300/586] lr: 5.000000e-05 eta: 0:36:57 time: 0.340264 data_time: 0.027069 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.865549 loss: 0.000491 2022/10/20 18:58:31 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 18:58:42 - mmengine - INFO - Epoch(train) [195][350/586] lr: 5.000000e-05 eta: 0:36:46 time: 0.357879 data_time: 0.025764 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.864253 loss: 0.000491 2022/10/20 18:59:06 - mmengine - INFO - Epoch(train) [195][400/586] lr: 5.000000e-05 eta: 0:36:34 time: 0.492264 data_time: 0.044191 memory: 7326 loss_kpt: 0.000508 acc_pose: 0.853442 loss: 0.000508 2022/10/20 18:59:29 - mmengine - INFO - Epoch(train) [195][450/586] lr: 5.000000e-05 eta: 0:36:23 time: 0.459728 data_time: 0.043304 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.862667 loss: 0.000492 2022/10/20 18:59:45 - mmengine - INFO - Epoch(train) [195][500/586] lr: 5.000000e-05 eta: 0:36:11 time: 0.322019 data_time: 0.026421 memory: 7326 loss_kpt: 0.000477 acc_pose: 0.832438 loss: 0.000477 2022/10/20 18:59:59 - mmengine - INFO - Epoch(train) [195][550/586] lr: 5.000000e-05 eta: 0:35:59 time: 0.268653 data_time: 0.031465 memory: 7326 loss_kpt: 0.000494 acc_pose: 0.911968 loss: 0.000494 2022/10/20 19:00:11 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:00:27 - mmengine - INFO - Epoch(train) [196][50/586] lr: 5.000000e-05 eta: 0:35:38 time: 0.325098 data_time: 0.049755 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.905671 loss: 0.000500 2022/10/20 19:00:46 - mmengine - INFO - Epoch(train) [196][100/586] lr: 5.000000e-05 eta: 0:35:26 time: 0.383261 data_time: 0.027489 memory: 7326 loss_kpt: 0.000493 acc_pose: 0.831340 loss: 0.000493 2022/10/20 19:01:02 - mmengine - INFO - Epoch(train) [196][150/586] lr: 5.000000e-05 eta: 0:35:14 time: 0.308769 data_time: 0.027260 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.879129 loss: 0.000500 2022/10/20 19:01:16 - mmengine - INFO - Epoch(train) [196][200/586] lr: 5.000000e-05 eta: 0:35:02 time: 0.278669 data_time: 0.036379 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.844974 loss: 0.000499 2022/10/20 19:01:35 - mmengine - INFO - Epoch(train) [196][250/586] lr: 5.000000e-05 eta: 0:34:50 time: 0.374165 data_time: 0.027441 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.902300 loss: 0.000489 2022/10/20 19:01:56 - mmengine - INFO - Epoch(train) [196][300/586] lr: 5.000000e-05 eta: 0:34:38 time: 0.432692 data_time: 0.031146 memory: 7326 loss_kpt: 0.000487 acc_pose: 0.885874 loss: 0.000487 2022/10/20 19:02:13 - mmengine - INFO - Epoch(train) [196][350/586] lr: 5.000000e-05 eta: 0:34:27 time: 0.343663 data_time: 0.024970 memory: 7326 loss_kpt: 0.000476 acc_pose: 0.801181 loss: 0.000476 2022/10/20 19:02:34 - mmengine - INFO - Epoch(train) [196][400/586] lr: 5.000000e-05 eta: 0:34:15 time: 0.401947 data_time: 0.055475 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.912426 loss: 0.000502 2022/10/20 19:03:02 - mmengine - INFO - Epoch(train) [196][450/586] lr: 5.000000e-05 eta: 0:34:04 time: 0.562748 data_time: 0.029107 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.858085 loss: 0.000496 2022/10/20 19:03:31 - mmengine - INFO - Epoch(train) [196][500/586] lr: 5.000000e-05 eta: 0:33:53 time: 0.585967 data_time: 0.055021 memory: 7326 loss_kpt: 0.000482 acc_pose: 0.892125 loss: 0.000482 2022/10/20 19:03:49 - mmengine - INFO - Epoch(train) [196][550/586] lr: 5.000000e-05 eta: 0:33:41 time: 0.351648 data_time: 0.035448 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.910802 loss: 0.000491 2022/10/20 19:04:01 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:04:18 - mmengine - INFO - Epoch(train) [197][50/586] lr: 5.000000e-05 eta: 0:33:19 time: 0.327051 data_time: 0.033786 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.916177 loss: 0.000491 2022/10/20 19:04:37 - mmengine - INFO - Epoch(train) [197][100/586] lr: 5.000000e-05 eta: 0:33:08 time: 0.388187 data_time: 0.025876 memory: 7326 loss_kpt: 0.000487 acc_pose: 0.894074 loss: 0.000487 2022/10/20 19:04:50 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:04:53 - mmengine - INFO - Epoch(train) [197][150/586] lr: 5.000000e-05 eta: 0:32:56 time: 0.325644 data_time: 0.059588 memory: 7326 loss_kpt: 0.000475 acc_pose: 0.896853 loss: 0.000475 2022/10/20 19:05:11 - mmengine - INFO - Epoch(train) [197][200/586] lr: 5.000000e-05 eta: 0:32:44 time: 0.359615 data_time: 0.027372 memory: 7326 loss_kpt: 0.000506 acc_pose: 0.913807 loss: 0.000506 2022/10/20 19:05:28 - mmengine - INFO - Epoch(train) [197][250/586] lr: 5.000000e-05 eta: 0:32:32 time: 0.327536 data_time: 0.026997 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.882264 loss: 0.000488 2022/10/20 19:05:47 - mmengine - INFO - Epoch(train) [197][300/586] lr: 5.000000e-05 eta: 0:32:20 time: 0.383229 data_time: 0.029473 memory: 7326 loss_kpt: 0.000472 acc_pose: 0.902867 loss: 0.000472 2022/10/20 19:06:03 - mmengine - INFO - Epoch(train) [197][350/586] lr: 5.000000e-05 eta: 0:32:08 time: 0.315112 data_time: 0.026152 memory: 7326 loss_kpt: 0.000493 acc_pose: 0.905015 loss: 0.000493 2022/10/20 19:06:24 - mmengine - INFO - Epoch(train) [197][400/586] lr: 5.000000e-05 eta: 0:31:56 time: 0.433463 data_time: 0.027414 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.876815 loss: 0.000501 2022/10/20 19:06:41 - mmengine - INFO - Epoch(train) [197][450/586] lr: 5.000000e-05 eta: 0:31:44 time: 0.337398 data_time: 0.025676 memory: 7326 loss_kpt: 0.000484 acc_pose: 0.916704 loss: 0.000484 2022/10/20 19:07:00 - mmengine - INFO - Epoch(train) [197][500/586] lr: 5.000000e-05 eta: 0:31:33 time: 0.383812 data_time: 0.025712 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.878930 loss: 0.000490 2022/10/20 19:07:15 - mmengine - INFO - Epoch(train) [197][550/586] lr: 5.000000e-05 eta: 0:31:20 time: 0.294617 data_time: 0.032798 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.878957 loss: 0.000491 2022/10/20 19:07:24 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:07:42 - mmengine - INFO - Epoch(train) [198][50/586] lr: 5.000000e-05 eta: 0:30:59 time: 0.353421 data_time: 0.042195 memory: 7326 loss_kpt: 0.000506 acc_pose: 0.881971 loss: 0.000506 2022/10/20 19:08:01 - mmengine - INFO - Epoch(train) [198][100/586] lr: 5.000000e-05 eta: 0:30:47 time: 0.391703 data_time: 0.029555 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.858409 loss: 0.000490 2022/10/20 19:08:19 - mmengine - INFO - Epoch(train) [198][150/586] lr: 5.000000e-05 eta: 0:30:35 time: 0.350275 data_time: 0.024146 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.888507 loss: 0.000499 2022/10/20 19:08:35 - mmengine - INFO - Epoch(train) [198][200/586] lr: 5.000000e-05 eta: 0:30:23 time: 0.328650 data_time: 0.027948 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.950552 loss: 0.000496 2022/10/20 19:08:50 - mmengine - INFO - Epoch(train) [198][250/586] lr: 5.000000e-05 eta: 0:30:11 time: 0.294655 data_time: 0.026523 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.854780 loss: 0.000500 2022/10/20 19:09:06 - mmengine - INFO - Epoch(train) [198][300/586] lr: 5.000000e-05 eta: 0:29:59 time: 0.315425 data_time: 0.025715 memory: 7326 loss_kpt: 0.000495 acc_pose: 0.919000 loss: 0.000495 2022/10/20 19:09:23 - mmengine - INFO - Epoch(train) [198][350/586] lr: 5.000000e-05 eta: 0:29:47 time: 0.350110 data_time: 0.032958 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.892857 loss: 0.000496 2022/10/20 19:09:39 - mmengine - INFO - Epoch(train) [198][400/586] lr: 5.000000e-05 eta: 0:29:35 time: 0.317065 data_time: 0.027551 memory: 7326 loss_kpt: 0.000480 acc_pose: 0.903742 loss: 0.000480 2022/10/20 19:09:59 - mmengine - INFO - Epoch(train) [198][450/586] lr: 5.000000e-05 eta: 0:29:23 time: 0.391859 data_time: 0.112064 memory: 7326 loss_kpt: 0.000503 acc_pose: 0.846343 loss: 0.000503 2022/10/20 19:10:16 - mmengine - INFO - Epoch(train) [198][500/586] lr: 5.000000e-05 eta: 0:29:11 time: 0.336426 data_time: 0.024752 memory: 7326 loss_kpt: 0.000486 acc_pose: 0.881481 loss: 0.000486 2022/10/20 19:10:30 - mmengine - INFO - Epoch(train) [198][550/586] lr: 5.000000e-05 eta: 0:28:59 time: 0.292136 data_time: 0.040395 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.901869 loss: 0.000490 2022/10/20 19:10:33 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:10:41 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:10:59 - mmengine - INFO - Epoch(train) [199][50/586] lr: 5.000000e-05 eta: 0:28:38 time: 0.359471 data_time: 0.034662 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.852027 loss: 0.000488 2022/10/20 19:11:12 - mmengine - INFO - Epoch(train) [199][100/586] lr: 5.000000e-05 eta: 0:28:25 time: 0.278037 data_time: 0.025172 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.917157 loss: 0.000488 2022/10/20 19:11:30 - mmengine - INFO - Epoch(train) [199][150/586] lr: 5.000000e-05 eta: 0:28:13 time: 0.344434 data_time: 0.027331 memory: 7326 loss_kpt: 0.000481 acc_pose: 0.867665 loss: 0.000481 2022/10/20 19:11:44 - mmengine - INFO - Epoch(train) [199][200/586] lr: 5.000000e-05 eta: 0:28:01 time: 0.275748 data_time: 0.034027 memory: 7326 loss_kpt: 0.000478 acc_pose: 0.877946 loss: 0.000478 2022/10/20 19:12:01 - mmengine - INFO - Epoch(train) [199][250/586] lr: 5.000000e-05 eta: 0:27:49 time: 0.352304 data_time: 0.027544 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.927127 loss: 0.000499 2022/10/20 19:12:17 - mmengine - INFO - Epoch(train) [199][300/586] lr: 5.000000e-05 eta: 0:27:37 time: 0.310005 data_time: 0.028821 memory: 7326 loss_kpt: 0.000494 acc_pose: 0.865064 loss: 0.000494 2022/10/20 19:12:32 - mmengine - INFO - Epoch(train) [199][350/586] lr: 5.000000e-05 eta: 0:27:25 time: 0.308662 data_time: 0.031934 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.924355 loss: 0.000492 2022/10/20 19:12:47 - mmengine - INFO - Epoch(train) [199][400/586] lr: 5.000000e-05 eta: 0:27:13 time: 0.301992 data_time: 0.026045 memory: 7326 loss_kpt: 0.000479 acc_pose: 0.872527 loss: 0.000479 2022/10/20 19:13:06 - mmengine - INFO - Epoch(train) [199][450/586] lr: 5.000000e-05 eta: 0:27:01 time: 0.368904 data_time: 0.029026 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.890103 loss: 0.000498 2022/10/20 19:13:21 - mmengine - INFO - Epoch(train) [199][500/586] lr: 5.000000e-05 eta: 0:26:49 time: 0.303140 data_time: 0.045969 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.825223 loss: 0.000498 2022/10/20 19:13:38 - mmengine - INFO - Epoch(train) [199][550/586] lr: 5.000000e-05 eta: 0:26:37 time: 0.348156 data_time: 0.065697 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.886075 loss: 0.000497 2022/10/20 19:13:52 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:14:13 - mmengine - INFO - Epoch(train) [200][50/586] lr: 5.000000e-05 eta: 0:26:15 time: 0.429207 data_time: 0.126211 memory: 7326 loss_kpt: 0.000484 acc_pose: 0.874688 loss: 0.000484 2022/10/20 19:14:28 - mmengine - INFO - Epoch(train) [200][100/586] lr: 5.000000e-05 eta: 0:26:03 time: 0.297704 data_time: 0.035120 memory: 7326 loss_kpt: 0.000484 acc_pose: 0.915568 loss: 0.000484 2022/10/20 19:14:44 - mmengine - INFO - Epoch(train) [200][150/586] lr: 5.000000e-05 eta: 0:25:51 time: 0.311176 data_time: 0.026502 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.901212 loss: 0.000489 2022/10/20 19:15:02 - mmengine - INFO - Epoch(train) [200][200/586] lr: 5.000000e-05 eta: 0:25:39 time: 0.371482 data_time: 0.033434 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.943410 loss: 0.000498 2022/10/20 19:15:25 - mmengine - INFO - Epoch(train) [200][250/586] lr: 5.000000e-05 eta: 0:25:27 time: 0.456019 data_time: 0.026871 memory: 7326 loss_kpt: 0.000481 acc_pose: 0.847873 loss: 0.000481 2022/10/20 19:15:45 - mmengine - INFO - Epoch(train) [200][300/586] lr: 5.000000e-05 eta: 0:25:15 time: 0.397606 data_time: 0.026106 memory: 7326 loss_kpt: 0.000476 acc_pose: 0.916729 loss: 0.000476 2022/10/20 19:16:01 - mmengine - INFO - Epoch(train) [200][350/586] lr: 5.000000e-05 eta: 0:25:03 time: 0.307512 data_time: 0.031347 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.930087 loss: 0.000499 2022/10/20 19:16:11 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:16:16 - mmengine - INFO - Epoch(train) [200][400/586] lr: 5.000000e-05 eta: 0:24:51 time: 0.312706 data_time: 0.029220 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.936761 loss: 0.000500 2022/10/20 19:16:31 - mmengine - INFO - Epoch(train) [200][450/586] lr: 5.000000e-05 eta: 0:24:39 time: 0.293737 data_time: 0.045164 memory: 7326 loss_kpt: 0.000482 acc_pose: 0.903382 loss: 0.000482 2022/10/20 19:16:47 - mmengine - INFO - Epoch(train) [200][500/586] lr: 5.000000e-05 eta: 0:24:27 time: 0.316739 data_time: 0.026548 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.934884 loss: 0.000488 2022/10/20 19:17:07 - mmengine - INFO - Epoch(train) [200][550/586] lr: 5.000000e-05 eta: 0:24:15 time: 0.404019 data_time: 0.028941 memory: 7326 loss_kpt: 0.000483 acc_pose: 0.880159 loss: 0.000483 2022/10/20 19:17:19 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:17:19 - mmengine - INFO - Saving checkpoint at 200 epochs 2022/10/20 19:17:37 - mmengine - INFO - Epoch(val) [200][50/407] eta: 0:01:36 time: 0.271302 data_time: 0.188454 memory: 7326 2022/10/20 19:17:51 - mmengine - INFO - Epoch(val) [200][100/407] eta: 0:01:25 time: 0.279579 data_time: 0.201801 memory: 1680 2022/10/20 19:17:59 - mmengine - INFO - Epoch(val) [200][150/407] eta: 0:00:41 time: 0.161523 data_time: 0.083867 memory: 1680 2022/10/20 19:18:15 - mmengine - INFO - Epoch(val) [200][200/407] eta: 0:01:06 time: 0.320026 data_time: 0.241530 memory: 1680 2022/10/20 19:18:26 - mmengine - INFO - Epoch(val) [200][250/407] eta: 0:00:34 time: 0.220952 data_time: 0.142794 memory: 1680 2022/10/20 19:18:33 - mmengine - INFO - Epoch(val) [200][300/407] eta: 0:00:15 time: 0.148637 data_time: 0.071296 memory: 1680 2022/10/20 19:18:42 - mmengine - INFO - Epoch(val) [200][350/407] eta: 0:00:10 time: 0.179342 data_time: 0.100412 memory: 1680 2022/10/20 19:18:53 - mmengine - INFO - Epoch(val) [200][400/407] eta: 0:00:01 time: 0.206472 data_time: 0.129918 memory: 1680 2022/10/20 19:19:56 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 19:20:09 - mmengine - INFO - Epoch(val) [200][407/407] coco/AP: 0.736409 coco/AP .5: 0.901558 coco/AP .75: 0.816376 coco/AP (M): 0.699924 coco/AP (L): 0.802843 coco/AR: 0.789956 coco/AR .5: 0.938917 coco/AR .75: 0.860989 coco/AR (M): 0.747883 coco/AR (L): 0.851171 2022/10/20 19:20:09 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_180.pth is removed 2022/10/20 19:20:11 - mmengine - INFO - The best checkpoint with 0.7364 coco/AP at 200 epoch is saved to best_coco/AP_epoch_200.pth. 2022/10/20 19:20:27 - mmengine - INFO - Epoch(train) [201][50/586] lr: 5.000000e-06 eta: 0:23:53 time: 0.327490 data_time: 0.106447 memory: 7326 loss_kpt: 0.000487 acc_pose: 0.872079 loss: 0.000487 2022/10/20 19:20:43 - mmengine - INFO - Epoch(train) [201][100/586] lr: 5.000000e-06 eta: 0:23:41 time: 0.315731 data_time: 0.044408 memory: 7326 loss_kpt: 0.000481 acc_pose: 0.925526 loss: 0.000481 2022/10/20 19:20:58 - mmengine - INFO - Epoch(train) [201][150/586] lr: 5.000000e-06 eta: 0:23:29 time: 0.300190 data_time: 0.033005 memory: 7326 loss_kpt: 0.000476 acc_pose: 0.877589 loss: 0.000476 2022/10/20 19:21:15 - mmengine - INFO - Epoch(train) [201][200/586] lr: 5.000000e-06 eta: 0:23:17 time: 0.337311 data_time: 0.026493 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.940750 loss: 0.000489 2022/10/20 19:21:32 - mmengine - INFO - Epoch(train) [201][250/586] lr: 5.000000e-06 eta: 0:23:05 time: 0.340513 data_time: 0.030387 memory: 7326 loss_kpt: 0.000494 acc_pose: 0.861555 loss: 0.000494 2022/10/20 19:21:52 - mmengine - INFO - Epoch(train) [201][300/586] lr: 5.000000e-06 eta: 0:22:53 time: 0.400207 data_time: 0.049001 memory: 7326 loss_kpt: 0.000486 acc_pose: 0.917920 loss: 0.000486 2022/10/20 19:22:10 - mmengine - INFO - Epoch(train) [201][350/586] lr: 5.000000e-06 eta: 0:22:41 time: 0.357098 data_time: 0.082007 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.842825 loss: 0.000490 2022/10/20 19:22:25 - mmengine - INFO - Epoch(train) [201][400/586] lr: 5.000000e-06 eta: 0:22:28 time: 0.305551 data_time: 0.043497 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.881944 loss: 0.000488 2022/10/20 19:22:45 - mmengine - INFO - Epoch(train) [201][450/586] lr: 5.000000e-06 eta: 0:22:16 time: 0.385581 data_time: 0.048090 memory: 7326 loss_kpt: 0.000479 acc_pose: 0.907022 loss: 0.000479 2022/10/20 19:23:03 - mmengine - INFO - Epoch(train) [201][500/586] lr: 5.000000e-06 eta: 0:22:04 time: 0.360317 data_time: 0.029721 memory: 7326 loss_kpt: 0.000474 acc_pose: 0.914120 loss: 0.000474 2022/10/20 19:23:17 - mmengine - INFO - Epoch(train) [201][550/586] lr: 5.000000e-06 eta: 0:21:52 time: 0.289872 data_time: 0.046107 memory: 7326 loss_kpt: 0.000481 acc_pose: 0.850037 loss: 0.000481 2022/10/20 19:23:29 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:23:45 - mmengine - INFO - Epoch(train) [202][50/586] lr: 5.000000e-06 eta: 0:21:31 time: 0.314379 data_time: 0.058078 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.896471 loss: 0.000488 2022/10/20 19:24:01 - mmengine - INFO - Epoch(train) [202][100/586] lr: 5.000000e-06 eta: 0:21:18 time: 0.318873 data_time: 0.029966 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.906728 loss: 0.000489 2022/10/20 19:24:17 - mmengine - INFO - Epoch(train) [202][150/586] lr: 5.000000e-06 eta: 0:21:06 time: 0.319969 data_time: 0.087539 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.891170 loss: 0.000490 2022/10/20 19:24:32 - mmengine - INFO - Epoch(train) [202][200/586] lr: 5.000000e-06 eta: 0:20:54 time: 0.296411 data_time: 0.088378 memory: 7326 loss_kpt: 0.000486 acc_pose: 0.888720 loss: 0.000486 2022/10/20 19:24:35 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:24:46 - mmengine - INFO - Epoch(train) [202][250/586] lr: 5.000000e-06 eta: 0:20:42 time: 0.282282 data_time: 0.027984 memory: 7326 loss_kpt: 0.000473 acc_pose: 0.892598 loss: 0.000473 2022/10/20 19:25:01 - mmengine - INFO - Epoch(train) [202][300/586] lr: 5.000000e-06 eta: 0:20:29 time: 0.299438 data_time: 0.028891 memory: 7326 loss_kpt: 0.000493 acc_pose: 0.855594 loss: 0.000493 2022/10/20 19:25:15 - mmengine - INFO - Epoch(train) [202][350/586] lr: 5.000000e-06 eta: 0:20:17 time: 0.285059 data_time: 0.034426 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.900198 loss: 0.000488 2022/10/20 19:25:28 - mmengine - INFO - Epoch(train) [202][400/586] lr: 5.000000e-06 eta: 0:20:05 time: 0.258863 data_time: 0.029385 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.890645 loss: 0.000485 2022/10/20 19:25:44 - mmengine - INFO - Epoch(train) [202][450/586] lr: 5.000000e-06 eta: 0:19:53 time: 0.321988 data_time: 0.029837 memory: 7326 loss_kpt: 0.000482 acc_pose: 0.895494 loss: 0.000482 2022/10/20 19:26:01 - mmengine - INFO - Epoch(train) [202][500/586] lr: 5.000000e-06 eta: 0:19:40 time: 0.329955 data_time: 0.063493 memory: 7326 loss_kpt: 0.000479 acc_pose: 0.890422 loss: 0.000479 2022/10/20 19:26:18 - mmengine - INFO - Epoch(train) [202][550/586] lr: 5.000000e-06 eta: 0:19:28 time: 0.344189 data_time: 0.027901 memory: 7326 loss_kpt: 0.000495 acc_pose: 0.893942 loss: 0.000495 2022/10/20 19:26:33 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:26:55 - mmengine - INFO - Epoch(train) [203][50/586] lr: 5.000000e-06 eta: 0:19:07 time: 0.433631 data_time: 0.043383 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.893850 loss: 0.000485 2022/10/20 19:27:16 - mmengine - INFO - Epoch(train) [203][100/586] lr: 5.000000e-06 eta: 0:18:55 time: 0.428183 data_time: 0.112163 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.882241 loss: 0.000491 2022/10/20 19:27:36 - mmengine - INFO - Epoch(train) [203][150/586] lr: 5.000000e-06 eta: 0:18:43 time: 0.383960 data_time: 0.024712 memory: 7326 loss_kpt: 0.000486 acc_pose: 0.923545 loss: 0.000486 2022/10/20 19:27:53 - mmengine - INFO - Epoch(train) [203][200/586] lr: 5.000000e-06 eta: 0:18:31 time: 0.339783 data_time: 0.035489 memory: 7326 loss_kpt: 0.000477 acc_pose: 0.801617 loss: 0.000477 2022/10/20 19:28:13 - mmengine - INFO - Epoch(train) [203][250/586] lr: 5.000000e-06 eta: 0:18:18 time: 0.414921 data_time: 0.044850 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.889477 loss: 0.000502 2022/10/20 19:28:32 - mmengine - INFO - Epoch(train) [203][300/586] lr: 5.000000e-06 eta: 0:18:06 time: 0.376739 data_time: 0.026940 memory: 7326 loss_kpt: 0.000484 acc_pose: 0.900117 loss: 0.000484 2022/10/20 19:28:54 - mmengine - INFO - Epoch(train) [203][350/586] lr: 5.000000e-06 eta: 0:17:54 time: 0.438254 data_time: 0.046588 memory: 7326 loss_kpt: 0.000476 acc_pose: 0.903002 loss: 0.000476 2022/10/20 19:29:12 - mmengine - INFO - Epoch(train) [203][400/586] lr: 5.000000e-06 eta: 0:17:42 time: 0.359681 data_time: 0.031575 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.896993 loss: 0.000491 2022/10/20 19:29:32 - mmengine - INFO - Epoch(train) [203][450/586] lr: 5.000000e-06 eta: 0:17:30 time: 0.389565 data_time: 0.028258 memory: 7326 loss_kpt: 0.000482 acc_pose: 0.916001 loss: 0.000482 2022/10/20 19:29:53 - mmengine - INFO - Epoch(train) [203][500/586] lr: 5.000000e-06 eta: 0:17:18 time: 0.428593 data_time: 0.024924 memory: 7326 loss_kpt: 0.000482 acc_pose: 0.905756 loss: 0.000482 2022/10/20 19:30:18 - mmengine - INFO - Epoch(train) [203][550/586] lr: 5.000000e-06 eta: 0:17:06 time: 0.501303 data_time: 0.025986 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.904672 loss: 0.000489 2022/10/20 19:30:32 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:30:48 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:30:51 - mmengine - INFO - Epoch(train) [204][50/586] lr: 5.000000e-06 eta: 0:16:45 time: 0.380462 data_time: 0.049802 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.826062 loss: 0.000496 2022/10/20 19:31:12 - mmengine - INFO - Epoch(train) [204][100/586] lr: 5.000000e-06 eta: 0:16:32 time: 0.418633 data_time: 0.024146 memory: 7326 loss_kpt: 0.000508 acc_pose: 0.889747 loss: 0.000508 2022/10/20 19:31:27 - mmengine - INFO - Epoch(train) [204][150/586] lr: 5.000000e-06 eta: 0:16:20 time: 0.306189 data_time: 0.025026 memory: 7326 loss_kpt: 0.000482 acc_pose: 0.859565 loss: 0.000482 2022/10/20 19:31:43 - mmengine - INFO - Epoch(train) [204][200/586] lr: 5.000000e-06 eta: 0:16:08 time: 0.302957 data_time: 0.027474 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.843548 loss: 0.000485 2022/10/20 19:32:02 - mmengine - INFO - Epoch(train) [204][250/586] lr: 5.000000e-06 eta: 0:15:56 time: 0.387930 data_time: 0.023515 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.886513 loss: 0.000485 2022/10/20 19:32:18 - mmengine - INFO - Epoch(train) [204][300/586] lr: 5.000000e-06 eta: 0:15:43 time: 0.316194 data_time: 0.025950 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.905973 loss: 0.000490 2022/10/20 19:32:34 - mmengine - INFO - Epoch(train) [204][350/586] lr: 5.000000e-06 eta: 0:15:31 time: 0.323967 data_time: 0.045564 memory: 7326 loss_kpt: 0.000512 acc_pose: 0.894270 loss: 0.000512 2022/10/20 19:32:53 - mmengine - INFO - Epoch(train) [204][400/586] lr: 5.000000e-06 eta: 0:15:19 time: 0.379877 data_time: 0.028911 memory: 7326 loss_kpt: 0.000473 acc_pose: 0.871901 loss: 0.000473 2022/10/20 19:33:10 - mmengine - INFO - Epoch(train) [204][450/586] lr: 5.000000e-06 eta: 0:15:07 time: 0.343547 data_time: 0.052676 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.915255 loss: 0.000501 2022/10/20 19:33:27 - mmengine - INFO - Epoch(train) [204][500/586] lr: 5.000000e-06 eta: 0:14:54 time: 0.330423 data_time: 0.025815 memory: 7326 loss_kpt: 0.000484 acc_pose: 0.890674 loss: 0.000484 2022/10/20 19:33:46 - mmengine - INFO - Epoch(train) [204][550/586] lr: 5.000000e-06 eta: 0:14:42 time: 0.378862 data_time: 0.028390 memory: 7326 loss_kpt: 0.000478 acc_pose: 0.895679 loss: 0.000478 2022/10/20 19:34:00 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:34:22 - mmengine - INFO - Epoch(train) [205][50/586] lr: 5.000000e-06 eta: 0:14:21 time: 0.442511 data_time: 0.040887 memory: 7326 loss_kpt: 0.000487 acc_pose: 0.876985 loss: 0.000487 2022/10/20 19:34:41 - mmengine - INFO - Epoch(train) [205][100/586] lr: 5.000000e-06 eta: 0:14:08 time: 0.378616 data_time: 0.032176 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.884112 loss: 0.000491 2022/10/20 19:34:58 - mmengine - INFO - Epoch(train) [205][150/586] lr: 5.000000e-06 eta: 0:13:56 time: 0.337544 data_time: 0.034779 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.865526 loss: 0.000485 2022/10/20 19:35:19 - mmengine - INFO - Epoch(train) [205][200/586] lr: 5.000000e-06 eta: 0:13:44 time: 0.423727 data_time: 0.025775 memory: 7326 loss_kpt: 0.000508 acc_pose: 0.883814 loss: 0.000508 2022/10/20 19:35:34 - mmengine - INFO - Epoch(train) [205][250/586] lr: 5.000000e-06 eta: 0:13:32 time: 0.308179 data_time: 0.059825 memory: 7326 loss_kpt: 0.000479 acc_pose: 0.919821 loss: 0.000479 2022/10/20 19:35:49 - mmengine - INFO - Epoch(train) [205][300/586] lr: 5.000000e-06 eta: 0:13:19 time: 0.285851 data_time: 0.042719 memory: 7326 loss_kpt: 0.000483 acc_pose: 0.904102 loss: 0.000483 2022/10/20 19:36:11 - mmengine - INFO - Epoch(train) [205][350/586] lr: 5.000000e-06 eta: 0:13:07 time: 0.440742 data_time: 0.035231 memory: 7326 loss_kpt: 0.000504 acc_pose: 0.877063 loss: 0.000504 2022/10/20 19:36:30 - mmengine - INFO - Epoch(train) [205][400/586] lr: 5.000000e-06 eta: 0:12:55 time: 0.375941 data_time: 0.091044 memory: 7326 loss_kpt: 0.000478 acc_pose: 0.901322 loss: 0.000478 2022/10/20 19:36:47 - mmengine - INFO - Epoch(train) [205][450/586] lr: 5.000000e-06 eta: 0:12:42 time: 0.358153 data_time: 0.043894 memory: 7326 loss_kpt: 0.000502 acc_pose: 0.906866 loss: 0.000502 2022/10/20 19:36:50 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:37:10 - mmengine - INFO - Epoch(train) [205][500/586] lr: 5.000000e-06 eta: 0:12:30 time: 0.449811 data_time: 0.025939 memory: 7326 loss_kpt: 0.000479 acc_pose: 0.872313 loss: 0.000479 2022/10/20 19:37:29 - mmengine - INFO - Epoch(train) [205][550/586] lr: 5.000000e-06 eta: 0:12:18 time: 0.383351 data_time: 0.031288 memory: 7326 loss_kpt: 0.000499 acc_pose: 0.865364 loss: 0.000499 2022/10/20 19:37:39 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:37:54 - mmengine - INFO - Epoch(train) [206][50/586] lr: 5.000000e-06 eta: 0:11:56 time: 0.298825 data_time: 0.053712 memory: 7326 loss_kpt: 0.000483 acc_pose: 0.903737 loss: 0.000483 2022/10/20 19:38:19 - mmengine - INFO - Epoch(train) [206][100/586] lr: 5.000000e-06 eta: 0:11:44 time: 0.490103 data_time: 0.030593 memory: 7326 loss_kpt: 0.000486 acc_pose: 0.936001 loss: 0.000486 2022/10/20 19:38:38 - mmengine - INFO - Epoch(train) [206][150/586] lr: 5.000000e-06 eta: 0:11:32 time: 0.387043 data_time: 0.030368 memory: 7326 loss_kpt: 0.000476 acc_pose: 0.911816 loss: 0.000476 2022/10/20 19:39:01 - mmengine - INFO - Epoch(train) [206][200/586] lr: 5.000000e-06 eta: 0:11:20 time: 0.462358 data_time: 0.024358 memory: 7326 loss_kpt: 0.000486 acc_pose: 0.902646 loss: 0.000486 2022/10/20 19:39:21 - mmengine - INFO - Epoch(train) [206][250/586] lr: 5.000000e-06 eta: 0:11:07 time: 0.397450 data_time: 0.028211 memory: 7326 loss_kpt: 0.000492 acc_pose: 0.924329 loss: 0.000492 2022/10/20 19:39:36 - mmengine - INFO - Epoch(train) [206][300/586] lr: 5.000000e-06 eta: 0:10:55 time: 0.288611 data_time: 0.035532 memory: 7326 loss_kpt: 0.000473 acc_pose: 0.905534 loss: 0.000473 2022/10/20 19:39:57 - mmengine - INFO - Epoch(train) [206][350/586] lr: 5.000000e-06 eta: 0:10:43 time: 0.417479 data_time: 0.058451 memory: 7326 loss_kpt: 0.000494 acc_pose: 0.887451 loss: 0.000494 2022/10/20 19:40:13 - mmengine - INFO - Epoch(train) [206][400/586] lr: 5.000000e-06 eta: 0:10:30 time: 0.333643 data_time: 0.032994 memory: 7326 loss_kpt: 0.000479 acc_pose: 0.885057 loss: 0.000479 2022/10/20 19:40:30 - mmengine - INFO - Epoch(train) [206][450/586] lr: 5.000000e-06 eta: 0:10:18 time: 0.339966 data_time: 0.038496 memory: 7326 loss_kpt: 0.000482 acc_pose: 0.913292 loss: 0.000482 2022/10/20 19:40:46 - mmengine - INFO - Epoch(train) [206][500/586] lr: 5.000000e-06 eta: 0:10:06 time: 0.313984 data_time: 0.026422 memory: 7326 loss_kpt: 0.000480 acc_pose: 0.871401 loss: 0.000480 2022/10/20 19:41:03 - mmengine - INFO - Epoch(train) [206][550/586] lr: 5.000000e-06 eta: 0:09:53 time: 0.337401 data_time: 0.037240 memory: 7326 loss_kpt: 0.000500 acc_pose: 0.869799 loss: 0.000500 2022/10/20 19:41:15 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:41:30 - mmengine - INFO - Epoch(train) [207][50/586] lr: 5.000000e-06 eta: 0:09:32 time: 0.300159 data_time: 0.048571 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.914533 loss: 0.000497 2022/10/20 19:41:53 - mmengine - INFO - Epoch(train) [207][100/586] lr: 5.000000e-06 eta: 0:09:19 time: 0.462632 data_time: 0.027693 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.932585 loss: 0.000496 2022/10/20 19:42:12 - mmengine - INFO - Epoch(train) [207][150/586] lr: 5.000000e-06 eta: 0:09:07 time: 0.369937 data_time: 0.029101 memory: 7326 loss_kpt: 0.000479 acc_pose: 0.891240 loss: 0.000479 2022/10/20 19:42:29 - mmengine - INFO - Epoch(train) [207][200/586] lr: 5.000000e-06 eta: 0:08:55 time: 0.337581 data_time: 0.029071 memory: 7326 loss_kpt: 0.000486 acc_pose: 0.902831 loss: 0.000486 2022/10/20 19:42:44 - mmengine - INFO - Epoch(train) [207][250/586] lr: 5.000000e-06 eta: 0:08:42 time: 0.316735 data_time: 0.027400 memory: 7326 loss_kpt: 0.000474 acc_pose: 0.844757 loss: 0.000474 2022/10/20 19:42:55 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:43:01 - mmengine - INFO - Epoch(train) [207][300/586] lr: 5.000000e-06 eta: 0:08:30 time: 0.330276 data_time: 0.026672 memory: 7326 loss_kpt: 0.000503 acc_pose: 0.915694 loss: 0.000503 2022/10/20 19:43:22 - mmengine - INFO - Epoch(train) [207][350/586] lr: 5.000000e-06 eta: 0:08:17 time: 0.420890 data_time: 0.026060 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.878255 loss: 0.000489 2022/10/20 19:43:39 - mmengine - INFO - Epoch(train) [207][400/586] lr: 5.000000e-06 eta: 0:08:05 time: 0.343056 data_time: 0.051524 memory: 7326 loss_kpt: 0.000494 acc_pose: 0.787502 loss: 0.000494 2022/10/20 19:44:00 - mmengine - INFO - Epoch(train) [207][450/586] lr: 5.000000e-06 eta: 0:07:53 time: 0.405098 data_time: 0.058757 memory: 7326 loss_kpt: 0.000501 acc_pose: 0.828671 loss: 0.000501 2022/10/20 19:44:19 - mmengine - INFO - Epoch(train) [207][500/586] lr: 5.000000e-06 eta: 0:07:40 time: 0.382358 data_time: 0.039232 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.888222 loss: 0.000485 2022/10/20 19:44:39 - mmengine - INFO - Epoch(train) [207][550/586] lr: 5.000000e-06 eta: 0:07:28 time: 0.408303 data_time: 0.040172 memory: 7326 loss_kpt: 0.000477 acc_pose: 0.884513 loss: 0.000477 2022/10/20 19:44:52 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:45:12 - mmengine - INFO - Epoch(train) [208][50/586] lr: 5.000000e-06 eta: 0:07:06 time: 0.386825 data_time: 0.053883 memory: 7326 loss_kpt: 0.000469 acc_pose: 0.851520 loss: 0.000469 2022/10/20 19:45:28 - mmengine - INFO - Epoch(train) [208][100/586] lr: 5.000000e-06 eta: 0:06:54 time: 0.324778 data_time: 0.045872 memory: 7326 loss_kpt: 0.000506 acc_pose: 0.928798 loss: 0.000506 2022/10/20 19:45:50 - mmengine - INFO - Epoch(train) [208][150/586] lr: 5.000000e-06 eta: 0:06:42 time: 0.436927 data_time: 0.028572 memory: 7326 loss_kpt: 0.000476 acc_pose: 0.866200 loss: 0.000476 2022/10/20 19:46:06 - mmengine - INFO - Epoch(train) [208][200/586] lr: 5.000000e-06 eta: 0:06:29 time: 0.331033 data_time: 0.025378 memory: 7326 loss_kpt: 0.000467 acc_pose: 0.921234 loss: 0.000467 2022/10/20 19:46:23 - mmengine - INFO - Epoch(train) [208][250/586] lr: 5.000000e-06 eta: 0:06:17 time: 0.336995 data_time: 0.036606 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.826567 loss: 0.000497 2022/10/20 19:46:41 - mmengine - INFO - Epoch(train) [208][300/586] lr: 5.000000e-06 eta: 0:06:04 time: 0.347242 data_time: 0.031044 memory: 7326 loss_kpt: 0.000478 acc_pose: 0.880415 loss: 0.000478 2022/10/20 19:47:02 - mmengine - INFO - Epoch(train) [208][350/586] lr: 5.000000e-06 eta: 0:05:52 time: 0.436629 data_time: 0.028383 memory: 7326 loss_kpt: 0.000489 acc_pose: 0.834553 loss: 0.000489 2022/10/20 19:47:22 - mmengine - INFO - Epoch(train) [208][400/586] lr: 5.000000e-06 eta: 0:05:39 time: 0.391402 data_time: 0.051114 memory: 7326 loss_kpt: 0.000495 acc_pose: 0.920427 loss: 0.000495 2022/10/20 19:47:40 - mmengine - INFO - Epoch(train) [208][450/586] lr: 5.000000e-06 eta: 0:05:27 time: 0.353278 data_time: 0.033901 memory: 7326 loss_kpt: 0.000487 acc_pose: 0.896728 loss: 0.000487 2022/10/20 19:48:03 - mmengine - INFO - Epoch(train) [208][500/586] lr: 5.000000e-06 eta: 0:05:15 time: 0.464779 data_time: 0.029545 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.884144 loss: 0.000488 2022/10/20 19:48:25 - mmengine - INFO - Epoch(train) [208][550/586] lr: 5.000000e-06 eta: 0:05:02 time: 0.439763 data_time: 0.084785 memory: 7326 loss_kpt: 0.000486 acc_pose: 0.930041 loss: 0.000486 2022/10/20 19:48:45 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:49:14 - mmengine - INFO - Epoch(train) [209][50/586] lr: 5.000000e-06 eta: 0:04:41 time: 0.564477 data_time: 0.043314 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.888814 loss: 0.000488 2022/10/20 19:49:38 - mmengine - INFO - Epoch(train) [209][100/586] lr: 5.000000e-06 eta: 0:04:28 time: 0.498822 data_time: 0.034687 memory: 7326 loss_kpt: 0.000495 acc_pose: 0.866398 loss: 0.000495 2022/10/20 19:49:52 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:50:28 - mmengine - INFO - Epoch(train) [209][150/586] lr: 5.000000e-06 eta: 0:04:16 time: 0.993528 data_time: 0.025550 memory: 7326 loss_kpt: 0.000478 acc_pose: 0.870054 loss: 0.000478 2022/10/20 19:50:52 - mmengine - INFO - Epoch(train) [209][200/586] lr: 5.000000e-06 eta: 0:04:04 time: 0.473582 data_time: 0.066968 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.899661 loss: 0.000498 2022/10/20 19:51:48 - mmengine - INFO - Epoch(train) [209][250/586] lr: 5.000000e-06 eta: 0:03:51 time: 1.119567 data_time: 0.027087 memory: 7326 loss_kpt: 0.000476 acc_pose: 0.863324 loss: 0.000476 2022/10/20 19:52:44 - mmengine - INFO - Epoch(train) [209][300/586] lr: 5.000000e-06 eta: 0:03:39 time: 1.118458 data_time: 0.051624 memory: 7326 loss_kpt: 0.000491 acc_pose: 0.897139 loss: 0.000491 2022/10/20 19:53:26 - mmengine - INFO - Epoch(train) [209][350/586] lr: 5.000000e-06 eta: 0:03:27 time: 0.846461 data_time: 0.118407 memory: 7326 loss_kpt: 0.000473 acc_pose: 0.877535 loss: 0.000473 2022/10/20 19:54:25 - mmengine - INFO - Epoch(train) [209][400/586] lr: 5.000000e-06 eta: 0:03:14 time: 1.179666 data_time: 0.025915 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.874529 loss: 0.000485 2022/10/20 19:55:14 - mmengine - INFO - Epoch(train) [209][450/586] lr: 5.000000e-06 eta: 0:03:02 time: 0.969145 data_time: 0.052824 memory: 7326 loss_kpt: 0.000484 acc_pose: 0.892957 loss: 0.000484 2022/10/20 19:55:58 - mmengine - INFO - Epoch(train) [209][500/586] lr: 5.000000e-06 eta: 0:02:49 time: 0.879626 data_time: 0.071045 memory: 7326 loss_kpt: 0.000484 acc_pose: 0.906562 loss: 0.000484 2022/10/20 19:56:48 - mmengine - INFO - Epoch(train) [209][550/586] lr: 5.000000e-06 eta: 0:02:37 time: 0.996996 data_time: 0.094027 memory: 7326 loss_kpt: 0.000487 acc_pose: 0.856125 loss: 0.000487 2022/10/20 19:57:08 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 19:57:54 - mmengine - INFO - Epoch(train) [210][50/586] lr: 5.000000e-06 eta: 0:02:15 time: 0.927550 data_time: 0.030245 memory: 7326 loss_kpt: 0.000482 acc_pose: 0.905904 loss: 0.000482 2022/10/20 19:58:22 - mmengine - INFO - Epoch(train) [210][100/586] lr: 5.000000e-06 eta: 0:02:03 time: 0.558356 data_time: 0.030603 memory: 7326 loss_kpt: 0.000490 acc_pose: 0.901241 loss: 0.000490 2022/10/20 19:59:02 - mmengine - INFO - Epoch(train) [210][150/586] lr: 5.000000e-06 eta: 0:01:50 time: 0.803875 data_time: 0.026121 memory: 7326 loss_kpt: 0.000482 acc_pose: 0.903778 loss: 0.000482 2022/10/20 19:59:27 - mmengine - INFO - Epoch(train) [210][200/586] lr: 5.000000e-06 eta: 0:01:37 time: 0.492669 data_time: 0.049712 memory: 7326 loss_kpt: 0.000496 acc_pose: 0.867656 loss: 0.000496 2022/10/20 19:59:49 - mmengine - INFO - Epoch(train) [210][250/586] lr: 5.000000e-06 eta: 0:01:25 time: 0.430180 data_time: 0.028702 memory: 7326 loss_kpt: 0.000488 acc_pose: 0.845218 loss: 0.000488 2022/10/20 20:00:30 - mmengine - INFO - Epoch(train) [210][300/586] lr: 5.000000e-06 eta: 0:01:12 time: 0.833163 data_time: 0.162231 memory: 7326 loss_kpt: 0.000479 acc_pose: 0.899943 loss: 0.000479 2022/10/20 20:01:02 - mmengine - INFO - Epoch(train) [210][350/586] lr: 5.000000e-06 eta: 0:01:00 time: 0.645443 data_time: 0.118483 memory: 7326 loss_kpt: 0.000480 acc_pose: 0.885842 loss: 0.000480 2022/10/20 20:01:51 - mmengine - INFO - Epoch(train) [210][400/586] lr: 5.000000e-06 eta: 0:00:47 time: 0.964448 data_time: 0.327232 memory: 7326 loss_kpt: 0.000498 acc_pose: 0.847047 loss: 0.000498 2022/10/20 20:02:52 - mmengine - INFO - Epoch(train) [210][450/586] lr: 5.000000e-06 eta: 0:00:34 time: 1.229061 data_time: 0.179806 memory: 7326 loss_kpt: 0.000483 acc_pose: 0.833733 loss: 0.000483 2022/10/20 20:03:58 - mmengine - INFO - Epoch(train) [210][500/586] lr: 5.000000e-06 eta: 0:00:21 time: 1.317502 data_time: 0.025611 memory: 7326 loss_kpt: 0.000497 acc_pose: 0.875258 loss: 0.000497 2022/10/20 20:04:39 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 20:05:21 - mmengine - INFO - Epoch(train) [210][550/586] lr: 5.000000e-06 eta: 0:00:09 time: 1.648398 data_time: 0.023172 memory: 7326 loss_kpt: 0.000485 acc_pose: 0.791660 loss: 0.000485 2022/10/20 20:05:56 - mmengine - INFO - Exp name: td-hm_resnetv1d152_8xb32-210e_coco-256x192_20221020_100239 2022/10/20 20:05:56 - mmengine - INFO - Saving checkpoint at 210 epochs 2022/10/20 20:06:31 - mmengine - INFO - Epoch(val) [210][50/407] eta: 0:03:42 time: 0.623148 data_time: 0.545309 memory: 7326 2022/10/20 20:06:52 - mmengine - INFO - Epoch(val) [210][100/407] eta: 0:02:07 time: 0.414946 data_time: 0.337085 memory: 1680 2022/10/20 20:07:06 - mmengine - INFO - Epoch(val) [210][150/407] eta: 0:01:12 time: 0.281524 data_time: 0.200150 memory: 1680 2022/10/20 20:07:24 - mmengine - INFO - Epoch(val) [210][200/407] eta: 0:01:13 time: 0.354899 data_time: 0.277692 memory: 1680 2022/10/20 20:07:42 - mmengine - INFO - Epoch(val) [210][250/407] eta: 0:00:58 time: 0.374616 data_time: 0.296859 memory: 1680 2022/10/20 20:07:53 - mmengine - INFO - Epoch(val) [210][300/407] eta: 0:00:22 time: 0.209923 data_time: 0.132195 memory: 1680 2022/10/20 20:08:07 - mmengine - INFO - Epoch(val) [210][350/407] eta: 0:00:15 time: 0.276494 data_time: 0.200092 memory: 1680 2022/10/20 20:08:29 - mmengine - INFO - Epoch(val) [210][400/407] eta: 0:00:03 time: 0.450696 data_time: 0.373408 memory: 1680 2022/10/20 20:11:55 - mmengine - INFO - Evaluating CocoMetric... 2022/10/20 20:12:07 - mmengine - INFO - Epoch(val) [210][407/407] coco/AP: 0.736547 coco/AP .5: 0.903612 coco/AP .75: 0.813750 coco/AP (M): 0.700337 coco/AP (L): 0.803706 coco/AR: 0.790491 coco/AR .5: 0.940176 coco/AR .75: 0.859729 coco/AR (M): 0.747828 coco/AR (L): 0.852508 2022/10/20 20:12:07 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221020/resnetv1d152_256/best_coco/AP_epoch_200.pth is removed 2022/10/20 20:12:10 - mmengine - INFO - The best checkpoint with 0.7365 coco/AP at 210 epoch is saved to best_coco/AP_epoch_210.pth.