2022/10/13 19:01:22 - 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: 775034661 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 ------------------------------------------------------------ 2022/10/13 19:01:23 - 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=(288, 384), heatmap_size=(72, 96), sigma=3) model = dict( type='TopdownPoseEstimator', data_preprocessor=dict( type='PoseDataPreprocessor', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], bgr_to_rgb=True), backbone=dict( type='ShuffleNetV2', widen_factor=1.0, init_cfg=dict(type='Pretrained', checkpoint='mmcls://shufflenet_v2')), head=dict( type='HeatmapHead', in_channels=1024, out_channels=17, loss=dict(type='KeypointMSELoss', use_target_weight=True), decoder=dict( type='MSRAHeatmap', input_size=(288, 384), heatmap_size=(72, 96), sigma=3)), test_cfg=dict(flip_test=True, flip_mode='heatmap', shift_heatmap=True)) dataset_type = 'CocoDataset' data_mode = 'topdown' data_root = 'data/coco/' train_pipeline = [ dict( type='LoadImage', file_client_args=dict( backend='petrel', path_mapping=dict({ './data/': 's3://openmmlab/datasets/detection/', 'data/': 's3://openmmlab/datasets/detection/' }))), dict(type='GetBBoxCenterScale'), dict(type='RandomFlip', direction='horizontal'), dict(type='RandomHalfBody'), dict(type='RandomBBoxTransform'), dict(type='TopdownAffine', input_size=(288, 384)), dict( type='GenerateTarget', target_type='heatmap', encoder=dict( type='MSRAHeatmap', input_size=(288, 384), heatmap_size=(72, 96), sigma=3)), dict(type='PackPoseInputs') ] val_pipeline = [ dict( type='LoadImage', file_client_args=dict( backend='petrel', path_mapping=dict({ './data/': 's3://openmmlab/datasets/detection/', 'data/': 's3://openmmlab/datasets/detection/' }))), dict(type='GetBBoxCenterScale'), dict(type='TopdownAffine', input_size=(288, 384)), dict(type='PackPoseInputs') ] train_dataloader = dict( batch_size=64, num_workers=2, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='CocoDataset', data_root='data/coco/', data_mode='topdown', ann_file='annotations/person_keypoints_train2017.json', data_prefix=dict(img='train2017/'), pipeline=[ dict( type='LoadImage', file_client_args=dict( backend='petrel', path_mapping=dict({ './data/': 's3://openmmlab/datasets/detection/', 'data/': 's3://openmmlab/datasets/detection/' }))), dict(type='GetBBoxCenterScale'), dict(type='RandomFlip', direction='horizontal'), dict(type='RandomHalfBody'), dict(type='RandomBBoxTransform'), dict(type='TopdownAffine', input_size=(288, 384)), dict( type='GenerateTarget', target_type='heatmap', encoder=dict( type='MSRAHeatmap', input_size=(288, 384), heatmap_size=(72, 96), sigma=3)), dict(type='PackPoseInputs') ])) val_dataloader = dict( batch_size=32, num_workers=2, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False, round_up=False), dataset=dict( type='CocoDataset', data_root='data/coco/', data_mode='topdown', ann_file='annotations/person_keypoints_val2017.json', bbox_file= 'data/coco/person_detection_results/COCO_val2017_detections_AP_H_56_person.json', data_prefix=dict(img='val2017/'), test_mode=True, pipeline=[ dict( type='LoadImage', file_client_args=dict( backend='petrel', path_mapping=dict({ './data/': 's3://openmmlab/datasets/detection/', 'data/': 's3://openmmlab/datasets/detection/' }))), dict(type='GetBBoxCenterScale'), dict(type='TopdownAffine', input_size=(288, 384)), dict(type='PackPoseInputs') ])) test_dataloader = dict( batch_size=32, num_workers=2, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False, round_up=False), dataset=dict( type='CocoDataset', data_root='data/coco/', data_mode='topdown', ann_file='annotations/person_keypoints_val2017.json', bbox_file= 'data/coco/person_detection_results/COCO_val2017_detections_AP_H_56_person.json', data_prefix=dict(img='val2017/'), test_mode=True, pipeline=[ dict( type='LoadImage', file_client_args=dict( backend='petrel', path_mapping=dict({ './data/': 's3://openmmlab/datasets/detection/', 'data/': 's3://openmmlab/datasets/detection/' }))), dict(type='GetBBoxCenterScale'), dict(type='TopdownAffine', input_size=(288, 384)), dict(type='PackPoseInputs') ])) val_evaluator = dict( type='CocoMetric', ann_file='data/coco/annotations/person_keypoints_val2017.json') test_evaluator = dict( type='CocoMetric', ann_file='data/coco/annotations/person_keypoints_val2017.json') launcher = 'slurm' work_dir = 'work_dirs/20221013/shufflenetv2_384/' 2022/10/13 19:01:57 - 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. 2022/10/13 19:01:57 - 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. 2022/10/13 19:01:57 - 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. 2022/10/13 19:01:57 - 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. 2022/10/13 19:01:57 - 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. 2022/10/13 19:01:57 - 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. 2022/10/13 19:01:57 - 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. 2022/10/13 19:01:57 - 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. 2022/10/13 19:02:00 - 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. 2022/10/13 19:02:02 - 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. 2022/10/13 19:02:05 - 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. 2022/10/13 19:02:05 - 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.conv1.conv.weight - torch.Size([24, 3, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.conv1.bn.weight - torch.Size([24]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.conv1.bn.bias - torch.Size([24]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch1.0.conv.weight - torch.Size([24, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch1.0.bn.weight - torch.Size([24]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch1.0.bn.bias - torch.Size([24]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch1.1.conv.weight - torch.Size([58, 24, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch1.1.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch1.1.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch2.0.conv.weight - torch.Size([58, 24, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch2.0.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch2.0.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch2.1.conv.weight - torch.Size([58, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch2.1.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch2.1.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch2.2.conv.weight - torch.Size([58, 58, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch2.2.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.0.branch2.2.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.1.branch2.0.conv.weight - torch.Size([58, 58, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.1.branch2.0.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.1.branch2.0.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.1.branch2.1.conv.weight - torch.Size([58, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.1.branch2.1.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.1.branch2.1.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.1.branch2.2.conv.weight - torch.Size([58, 58, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.1.branch2.2.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.1.branch2.2.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.2.branch2.0.conv.weight - torch.Size([58, 58, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.2.branch2.0.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.2.branch2.0.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.2.branch2.1.conv.weight - torch.Size([58, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.2.branch2.1.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.2.branch2.1.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.2.branch2.2.conv.weight - torch.Size([58, 58, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.2.branch2.2.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.2.branch2.2.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.3.branch2.0.conv.weight - torch.Size([58, 58, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.3.branch2.0.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.3.branch2.0.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.3.branch2.1.conv.weight - torch.Size([58, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.3.branch2.1.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.3.branch2.1.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.3.branch2.2.conv.weight - torch.Size([58, 58, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.3.branch2.2.bn.weight - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.0.3.branch2.2.bn.bias - torch.Size([58]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch1.0.conv.weight - torch.Size([116, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch1.0.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch1.0.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch1.1.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch1.1.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch1.1.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch2.0.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch2.0.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch2.0.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch2.1.conv.weight - torch.Size([116, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch2.1.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch2.1.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch2.2.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch2.2.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.0.branch2.2.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.1.branch2.0.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.1.branch2.0.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.1.branch2.0.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.1.branch2.1.conv.weight - torch.Size([116, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.1.branch2.1.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.1.branch2.1.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.1.branch2.2.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.1.branch2.2.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.1.branch2.2.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.2.branch2.0.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.2.branch2.0.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.2.branch2.0.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.2.branch2.1.conv.weight - torch.Size([116, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.2.branch2.1.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.2.branch2.1.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.2.branch2.2.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.2.branch2.2.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.2.branch2.2.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.3.branch2.0.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.3.branch2.0.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.3.branch2.0.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.3.branch2.1.conv.weight - torch.Size([116, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.3.branch2.1.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.3.branch2.1.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.3.branch2.2.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.3.branch2.2.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.3.branch2.2.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.4.branch2.0.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.4.branch2.0.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.4.branch2.0.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.4.branch2.1.conv.weight - torch.Size([116, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.4.branch2.1.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.4.branch2.1.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.4.branch2.2.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.4.branch2.2.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.4.branch2.2.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.5.branch2.0.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.5.branch2.0.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.5.branch2.0.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.5.branch2.1.conv.weight - torch.Size([116, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.5.branch2.1.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.5.branch2.1.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.5.branch2.2.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.5.branch2.2.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.5.branch2.2.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.6.branch2.0.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.6.branch2.0.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.6.branch2.0.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.6.branch2.1.conv.weight - torch.Size([116, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.6.branch2.1.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.6.branch2.1.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.6.branch2.2.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.6.branch2.2.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.6.branch2.2.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.7.branch2.0.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.7.branch2.0.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.7.branch2.0.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.7.branch2.1.conv.weight - torch.Size([116, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.7.branch2.1.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.7.branch2.1.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.7.branch2.2.conv.weight - torch.Size([116, 116, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.7.branch2.2.bn.weight - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.1.7.branch2.2.bn.bias - torch.Size([116]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch1.0.conv.weight - torch.Size([232, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch1.0.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch1.0.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch1.1.conv.weight - torch.Size([232, 232, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch1.1.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch1.1.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch2.0.conv.weight - torch.Size([232, 232, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch2.0.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch2.0.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch2.1.conv.weight - torch.Size([232, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch2.1.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch2.1.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch2.2.conv.weight - torch.Size([232, 232, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch2.2.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.0.branch2.2.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.1.branch2.0.conv.weight - torch.Size([232, 232, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.1.branch2.0.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.1.branch2.0.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.1.branch2.1.conv.weight - torch.Size([232, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.1.branch2.1.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.1.branch2.1.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.1.branch2.2.conv.weight - torch.Size([232, 232, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.1.branch2.2.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.1.branch2.2.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.2.branch2.0.conv.weight - torch.Size([232, 232, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.2.branch2.0.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.2.branch2.0.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.2.branch2.1.conv.weight - torch.Size([232, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.2.branch2.1.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.2.branch2.1.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.2.branch2.2.conv.weight - torch.Size([232, 232, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.2.branch2.2.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.2.branch2.2.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.3.branch2.0.conv.weight - torch.Size([232, 232, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.3.branch2.0.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.3.branch2.0.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.3.branch2.1.conv.weight - torch.Size([232, 1, 3, 3]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.3.branch2.1.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.3.branch2.1.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.3.branch2.2.conv.weight - torch.Size([232, 232, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.3.branch2.2.bn.weight - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.2.3.branch2.2.bn.bias - torch.Size([232]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.3.conv.weight - torch.Size([1024, 464, 1, 1]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.3.bn.weight - torch.Size([1024]): PretrainedInit: load from mmcls://shufflenet_v2 backbone.layers.3.bn.bias - torch.Size([1024]): PretrainedInit: load from mmcls://shufflenet_v2 head.deconv_layers.0.weight - torch.Size([1024, 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 2022/10/13 19:02:05 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384 by HardDiskBackend. 2022/10/13 19:03:17 - mmengine - INFO - Epoch(train) [1][50/293] lr: 4.954910e-05 eta: 1 day, 0:34:26 time: 1.438950 data_time: 0.200538 memory: 4980 loss_kpt: 0.002147 acc_pose: 0.181702 loss: 0.002147 2022/10/13 19:04:03 - mmengine - INFO - Epoch(train) [1][100/293] lr: 9.959920e-05 eta: 20:04:48 time: 0.914558 data_time: 0.079189 memory: 4980 loss_kpt: 0.001895 acc_pose: 0.285124 loss: 0.001895 2022/10/13 19:04:44 - mmengine - INFO - Epoch(train) [1][150/293] lr: 1.496493e-04 eta: 18:05:30 time: 0.829822 data_time: 0.079626 memory: 4980 loss_kpt: 0.001762 acc_pose: 0.310189 loss: 0.001762 2022/10/13 19:05:19 - mmengine - INFO - Epoch(train) [1][200/293] lr: 1.996994e-04 eta: 16:28:12 time: 0.683811 data_time: 0.128695 memory: 4980 loss_kpt: 0.001644 acc_pose: 0.395786 loss: 0.001644 2022/10/13 19:05:54 - mmengine - INFO - Epoch(train) [1][250/293] lr: 2.497495e-04 eta: 15:35:43 time: 0.713752 data_time: 0.090172 memory: 4980 loss_kpt: 0.001553 acc_pose: 0.443196 loss: 0.001553 2022/10/13 19:06:20 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:06:39 - mmengine - INFO - Epoch(train) [2][50/293] lr: 3.428427e-04 eta: 12:18:11 time: 0.384852 data_time: 0.093015 memory: 4980 loss_kpt: 0.001466 acc_pose: 0.521732 loss: 0.001466 2022/10/13 19:06:58 - mmengine - INFO - Epoch(train) [2][100/293] lr: 3.928928e-04 eta: 11:32:34 time: 0.376609 data_time: 0.075443 memory: 4980 loss_kpt: 0.001417 acc_pose: 0.525293 loss: 0.001417 2022/10/13 19:07:16 - mmengine - INFO - Epoch(train) [2][150/293] lr: 4.429429e-04 eta: 10:54:25 time: 0.352657 data_time: 0.061021 memory: 4980 loss_kpt: 0.001389 acc_pose: 0.530326 loss: 0.001389 2022/10/13 19:07:34 - mmengine - INFO - Epoch(train) [2][200/293] lr: 4.929930e-04 eta: 10:25:35 time: 0.368532 data_time: 0.062977 memory: 4980 loss_kpt: 0.001370 acc_pose: 0.499536 loss: 0.001370 2022/10/13 19:07:52 - mmengine - INFO - Epoch(train) [2][250/293] lr: 5.000000e-04 eta: 10:01:26 time: 0.362384 data_time: 0.070048 memory: 4980 loss_kpt: 0.001344 acc_pose: 0.580498 loss: 0.001344 2022/10/13 19:08:07 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:08:26 - mmengine - INFO - Epoch(train) [3][50/293] lr: 5.000000e-04 eta: 9:02:48 time: 0.377140 data_time: 0.082705 memory: 4980 loss_kpt: 0.001302 acc_pose: 0.564099 loss: 0.001302 2022/10/13 19:08:45 - mmengine - INFO - Epoch(train) [3][100/293] lr: 5.000000e-04 eta: 8:50:01 time: 0.368097 data_time: 0.069954 memory: 4980 loss_kpt: 0.001280 acc_pose: 0.517531 loss: 0.001280 2022/10/13 19:09:03 - mmengine - INFO - Epoch(train) [3][150/293] lr: 5.000000e-04 eta: 8:38:35 time: 0.362900 data_time: 0.070762 memory: 4980 loss_kpt: 0.001258 acc_pose: 0.573885 loss: 0.001258 2022/10/13 19:09:20 - mmengine - INFO - Epoch(train) [3][200/293] lr: 5.000000e-04 eta: 8:27:47 time: 0.350726 data_time: 0.069175 memory: 4980 loss_kpt: 0.001259 acc_pose: 0.569771 loss: 0.001259 2022/10/13 19:09:39 - mmengine - INFO - Epoch(train) [3][250/293] lr: 5.000000e-04 eta: 8:19:25 time: 0.370005 data_time: 0.069426 memory: 4980 loss_kpt: 0.001215 acc_pose: 0.577343 loss: 0.001215 2022/10/13 19:09:54 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:10:13 - mmengine - INFO - Epoch(train) [4][50/293] lr: 5.000000e-04 eta: 7:49:14 time: 0.377383 data_time: 0.076700 memory: 4980 loss_kpt: 0.001190 acc_pose: 0.616936 loss: 0.001190 2022/10/13 19:10:31 - mmengine - INFO - Epoch(train) [4][100/293] lr: 5.000000e-04 eta: 7:43:25 time: 0.358983 data_time: 0.078304 memory: 4980 loss_kpt: 0.001211 acc_pose: 0.544148 loss: 0.001211 2022/10/13 19:10:38 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:10:49 - mmengine - INFO - Epoch(train) [4][150/293] lr: 5.000000e-04 eta: 7:37:58 time: 0.355953 data_time: 0.072147 memory: 4980 loss_kpt: 0.001202 acc_pose: 0.596181 loss: 0.001202 2022/10/13 19:11:07 - mmengine - INFO - Epoch(train) [4][200/293] lr: 5.000000e-04 eta: 7:33:05 time: 0.357648 data_time: 0.074316 memory: 4980 loss_kpt: 0.001204 acc_pose: 0.594462 loss: 0.001204 2022/10/13 19:11:25 - mmengine - INFO - Epoch(train) [4][250/293] lr: 5.000000e-04 eta: 7:28:36 time: 0.357743 data_time: 0.080090 memory: 4980 loss_kpt: 0.001195 acc_pose: 0.590911 loss: 0.001195 2022/10/13 19:11:40 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:11:59 - mmengine - INFO - Epoch(train) [5][50/293] lr: 5.000000e-04 eta: 7:09:14 time: 0.374439 data_time: 0.087016 memory: 4980 loss_kpt: 0.001175 acc_pose: 0.574689 loss: 0.001175 2022/10/13 19:12:17 - mmengine - INFO - Epoch(train) [5][100/293] lr: 5.000000e-04 eta: 7:06:24 time: 0.364303 data_time: 0.067422 memory: 4980 loss_kpt: 0.001155 acc_pose: 0.562638 loss: 0.001155 2022/10/13 19:12:35 - mmengine - INFO - Epoch(train) [5][150/293] lr: 5.000000e-04 eta: 7:03:31 time: 0.357921 data_time: 0.071175 memory: 4980 loss_kpt: 0.001157 acc_pose: 0.567372 loss: 0.001157 2022/10/13 19:12:53 - mmengine - INFO - Epoch(train) [5][200/293] lr: 5.000000e-04 eta: 7:01:17 time: 0.370529 data_time: 0.067815 memory: 4980 loss_kpt: 0.001159 acc_pose: 0.617750 loss: 0.001159 2022/10/13 19:13:12 - mmengine - INFO - Epoch(train) [5][250/293] lr: 5.000000e-04 eta: 6:59:13 time: 0.371442 data_time: 0.079088 memory: 4980 loss_kpt: 0.001141 acc_pose: 0.620274 loss: 0.001141 2022/10/13 19:13:27 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:13:46 - mmengine - INFO - Epoch(train) [6][50/293] lr: 5.000000e-04 eta: 6:45:35 time: 0.385142 data_time: 0.141346 memory: 4980 loss_kpt: 0.001163 acc_pose: 0.626201 loss: 0.001163 2022/10/13 19:14:04 - mmengine - INFO - Epoch(train) [6][100/293] lr: 5.000000e-04 eta: 6:43:45 time: 0.358485 data_time: 0.120738 memory: 4980 loss_kpt: 0.001136 acc_pose: 0.556479 loss: 0.001136 2022/10/13 19:14:22 - mmengine - INFO - Epoch(train) [6][150/293] lr: 5.000000e-04 eta: 6:42:01 time: 0.359160 data_time: 0.070364 memory: 4980 loss_kpt: 0.001151 acc_pose: 0.679808 loss: 0.001151 2022/10/13 19:14:40 - mmengine - INFO - Epoch(train) [6][200/293] lr: 5.000000e-04 eta: 6:40:22 time: 0.358456 data_time: 0.064491 memory: 4980 loss_kpt: 0.001138 acc_pose: 0.620737 loss: 0.001138 2022/10/13 19:14:58 - mmengine - INFO - Epoch(train) [6][250/293] lr: 5.000000e-04 eta: 6:38:49 time: 0.359687 data_time: 0.063539 memory: 4980 loss_kpt: 0.001119 acc_pose: 0.590118 loss: 0.001119 2022/10/13 19:15:14 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:15:32 - mmengine - INFO - Epoch(train) [7][50/293] lr: 5.000000e-04 eta: 6:28:00 time: 0.373605 data_time: 0.107561 memory: 4980 loss_kpt: 0.001121 acc_pose: 0.648295 loss: 0.001121 2022/10/13 19:15:50 - mmengine - INFO - Epoch(train) [7][100/293] lr: 5.000000e-04 eta: 6:26:52 time: 0.359589 data_time: 0.066579 memory: 4980 loss_kpt: 0.001116 acc_pose: 0.632303 loss: 0.001116 2022/10/13 19:16:08 - mmengine - INFO - Epoch(train) [7][150/293] lr: 5.000000e-04 eta: 6:25:48 time: 0.360388 data_time: 0.071097 memory: 4980 loss_kpt: 0.001112 acc_pose: 0.613288 loss: 0.001112 2022/10/13 19:16:27 - mmengine - INFO - Epoch(train) [7][200/293] lr: 5.000000e-04 eta: 6:25:13 time: 0.377880 data_time: 0.084195 memory: 4980 loss_kpt: 0.001105 acc_pose: 0.600318 loss: 0.001105 2022/10/13 19:16:43 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:16:46 - mmengine - INFO - Epoch(train) [7][250/293] lr: 5.000000e-04 eta: 6:24:23 time: 0.367909 data_time: 0.082743 memory: 4980 loss_kpt: 0.001104 acc_pose: 0.642696 loss: 0.001104 2022/10/13 19:17:01 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:17:19 - mmengine - INFO - Epoch(train) [8][50/293] lr: 5.000000e-04 eta: 6:15:29 time: 0.368491 data_time: 0.123656 memory: 4980 loss_kpt: 0.001104 acc_pose: 0.675369 loss: 0.001104 2022/10/13 19:17:37 - mmengine - INFO - Epoch(train) [8][100/293] lr: 5.000000e-04 eta: 6:14:38 time: 0.356050 data_time: 0.071957 memory: 4980 loss_kpt: 0.001089 acc_pose: 0.616681 loss: 0.001089 2022/10/13 19:17:55 - mmengine - INFO - Epoch(train) [8][150/293] lr: 5.000000e-04 eta: 6:14:01 time: 0.364583 data_time: 0.084686 memory: 4980 loss_kpt: 0.001111 acc_pose: 0.642809 loss: 0.001111 2022/10/13 19:18:13 - mmengine - INFO - Epoch(train) [8][200/293] lr: 5.000000e-04 eta: 6:13:16 time: 0.358997 data_time: 0.082952 memory: 4980 loss_kpt: 0.001092 acc_pose: 0.642362 loss: 0.001092 2022/10/13 19:18:31 - mmengine - INFO - Epoch(train) [8][250/293] lr: 5.000000e-04 eta: 6:12:42 time: 0.365953 data_time: 0.074353 memory: 4980 loss_kpt: 0.001076 acc_pose: 0.696769 loss: 0.001076 2022/10/13 19:18:47 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:19:06 - mmengine - INFO - Epoch(train) [9][50/293] lr: 5.000000e-04 eta: 6:05:30 time: 0.380517 data_time: 0.084812 memory: 4980 loss_kpt: 0.001083 acc_pose: 0.657762 loss: 0.001083 2022/10/13 19:19:25 - mmengine - INFO - Epoch(train) [9][100/293] lr: 5.000000e-04 eta: 6:05:15 time: 0.374038 data_time: 0.080216 memory: 4980 loss_kpt: 0.001086 acc_pose: 0.652520 loss: 0.001086 2022/10/13 19:19:43 - mmengine - INFO - Epoch(train) [9][150/293] lr: 5.000000e-04 eta: 6:04:54 time: 0.368615 data_time: 0.118748 memory: 4980 loss_kpt: 0.001069 acc_pose: 0.643503 loss: 0.001069 2022/10/13 19:20:01 - mmengine - INFO - Epoch(train) [9][200/293] lr: 5.000000e-04 eta: 6:04:18 time: 0.356340 data_time: 0.117554 memory: 4980 loss_kpt: 0.001090 acc_pose: 0.653705 loss: 0.001090 2022/10/13 19:20:19 - mmengine - INFO - Epoch(train) [9][250/293] lr: 5.000000e-04 eta: 6:03:45 time: 0.357504 data_time: 0.099796 memory: 4980 loss_kpt: 0.001088 acc_pose: 0.614623 loss: 0.001088 2022/10/13 19:20:34 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:20:53 - mmengine - INFO - Epoch(train) [10][50/293] lr: 5.000000e-04 eta: 5:57:36 time: 0.383355 data_time: 0.090143 memory: 4980 loss_kpt: 0.001057 acc_pose: 0.548018 loss: 0.001057 2022/10/13 19:21:12 - mmengine - INFO - Epoch(train) [10][100/293] lr: 5.000000e-04 eta: 5:57:22 time: 0.368846 data_time: 0.069531 memory: 4980 loss_kpt: 0.001087 acc_pose: 0.631115 loss: 0.001087 2022/10/13 19:21:30 - mmengine - INFO - Epoch(train) [10][150/293] lr: 5.000000e-04 eta: 5:57:02 time: 0.362645 data_time: 0.075302 memory: 4980 loss_kpt: 0.001086 acc_pose: 0.649920 loss: 0.001086 2022/10/13 19:21:48 - mmengine - INFO - Epoch(train) [10][200/293] lr: 5.000000e-04 eta: 5:56:41 time: 0.362358 data_time: 0.085009 memory: 4980 loss_kpt: 0.001060 acc_pose: 0.605866 loss: 0.001060 2022/10/13 19:22:07 - mmengine - INFO - Epoch(train) [10][250/293] lr: 5.000000e-04 eta: 5:56:37 time: 0.377930 data_time: 0.077999 memory: 4980 loss_kpt: 0.001074 acc_pose: 0.713290 loss: 0.001074 2022/10/13 19:22:23 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:22:23 - mmengine - INFO - Saving checkpoint at 10 epochs 2022/10/13 19:22:34 - mmengine - INFO - Epoch(val) [10][50/407] eta: 0:01:08 time: 0.192955 data_time: 0.139489 memory: 4980 2022/10/13 19:22:42 - mmengine - INFO - Epoch(val) [10][100/407] eta: 0:00:44 time: 0.145155 data_time: 0.092905 memory: 772 2022/10/13 19:22:49 - mmengine - INFO - Epoch(val) [10][150/407] eta: 0:00:38 time: 0.150055 data_time: 0.095501 memory: 772 2022/10/13 19:22:56 - mmengine - INFO - Epoch(val) [10][200/407] eta: 0:00:29 time: 0.140824 data_time: 0.086932 memory: 772 2022/10/13 19:23:04 - mmengine - INFO - Epoch(val) [10][250/407] eta: 0:00:23 time: 0.148874 data_time: 0.094571 memory: 772 2022/10/13 19:23:11 - mmengine - INFO - Epoch(val) [10][300/407] eta: 0:00:16 time: 0.151074 data_time: 0.097829 memory: 772 2022/10/13 19:23:19 - mmengine - INFO - Epoch(val) [10][350/407] eta: 0:00:08 time: 0.155601 data_time: 0.101902 memory: 772 2022/10/13 19:23:26 - mmengine - INFO - Epoch(val) [10][400/407] eta: 0:00:00 time: 0.142452 data_time: 0.089902 memory: 772 2022/10/13 19:24:04 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 19:24:18 - mmengine - INFO - Epoch(val) [10][407/407] coco/AP: 0.510435 coco/AP .5: 0.810364 coco/AP .75: 0.542591 coco/AP (M): 0.469308 coco/AP (L): 0.581054 coco/AR: 0.582478 coco/AR .5: 0.861933 coco/AR .75: 0.626732 coco/AR (M): 0.530893 coco/AR (L): 0.654478 2022/10/13 19:24:20 - mmengine - INFO - The best checkpoint with 0.5104 coco/AP at 10 epoch is saved to best_coco/AP_epoch_10.pth. 2022/10/13 19:24:39 - mmengine - INFO - Epoch(train) [11][50/293] lr: 5.000000e-04 eta: 5:51:08 time: 0.378451 data_time: 0.163884 memory: 4980 loss_kpt: 0.001035 acc_pose: 0.658886 loss: 0.001035 2022/10/13 19:24:46 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:24:57 - mmengine - INFO - Epoch(train) [11][100/293] lr: 5.000000e-04 eta: 5:50:52 time: 0.362080 data_time: 0.147678 memory: 4980 loss_kpt: 0.001071 acc_pose: 0.629765 loss: 0.001071 2022/10/13 19:25:16 - mmengine - INFO - Epoch(train) [11][150/293] lr: 5.000000e-04 eta: 5:50:42 time: 0.368436 data_time: 0.093583 memory: 4980 loss_kpt: 0.001075 acc_pose: 0.641566 loss: 0.001075 2022/10/13 19:25:33 - mmengine - INFO - Epoch(train) [11][200/293] lr: 5.000000e-04 eta: 5:50:20 time: 0.355577 data_time: 0.068344 memory: 4980 loss_kpt: 0.001053 acc_pose: 0.665057 loss: 0.001053 2022/10/13 19:25:51 - mmengine - INFO - Epoch(train) [11][250/293] lr: 5.000000e-04 eta: 5:50:01 time: 0.358353 data_time: 0.116859 memory: 4980 loss_kpt: 0.001049 acc_pose: 0.626528 loss: 0.001049 2022/10/13 19:26:07 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:26:26 - mmengine - INFO - Epoch(train) [12][50/293] lr: 5.000000e-04 eta: 5:45:10 time: 0.380643 data_time: 0.099355 memory: 4980 loss_kpt: 0.001040 acc_pose: 0.661365 loss: 0.001040 2022/10/13 19:26:44 - mmengine - INFO - Epoch(train) [12][100/293] lr: 5.000000e-04 eta: 5:45:06 time: 0.370881 data_time: 0.079336 memory: 4980 loss_kpt: 0.001048 acc_pose: 0.693107 loss: 0.001048 2022/10/13 19:27:02 - mmengine - INFO - Epoch(train) [12][150/293] lr: 5.000000e-04 eta: 5:44:49 time: 0.357139 data_time: 0.081929 memory: 4980 loss_kpt: 0.001061 acc_pose: 0.663226 loss: 0.001061 2022/10/13 19:27:21 - mmengine - INFO - Epoch(train) [12][200/293] lr: 5.000000e-04 eta: 5:44:40 time: 0.366205 data_time: 0.080155 memory: 4980 loss_kpt: 0.001037 acc_pose: 0.651989 loss: 0.001037 2022/10/13 19:27:39 - mmengine - INFO - Epoch(train) [12][250/293] lr: 5.000000e-04 eta: 5:44:25 time: 0.359518 data_time: 0.068595 memory: 4980 loss_kpt: 0.001047 acc_pose: 0.621844 loss: 0.001047 2022/10/13 19:27:54 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:28:13 - mmengine - INFO - Epoch(train) [13][50/293] lr: 5.000000e-04 eta: 5:39:55 time: 0.369634 data_time: 0.090366 memory: 4980 loss_kpt: 0.001030 acc_pose: 0.625460 loss: 0.001030 2022/10/13 19:28:31 - mmengine - INFO - Epoch(train) [13][100/293] lr: 5.000000e-04 eta: 5:39:46 time: 0.362508 data_time: 0.077648 memory: 4980 loss_kpt: 0.001029 acc_pose: 0.633109 loss: 0.001029 2022/10/13 19:28:49 - mmengine - INFO - Epoch(train) [13][150/293] lr: 5.000000e-04 eta: 5:39:43 time: 0.371175 data_time: 0.072057 memory: 4980 loss_kpt: 0.001032 acc_pose: 0.630652 loss: 0.001032 2022/10/13 19:29:08 - mmengine - INFO - Epoch(train) [13][200/293] lr: 5.000000e-04 eta: 5:39:34 time: 0.362887 data_time: 0.072370 memory: 4980 loss_kpt: 0.001032 acc_pose: 0.646246 loss: 0.001032 2022/10/13 19:29:25 - mmengine - INFO - Epoch(train) [13][250/293] lr: 5.000000e-04 eta: 5:39:18 time: 0.354297 data_time: 0.065392 memory: 4980 loss_kpt: 0.001024 acc_pose: 0.709295 loss: 0.001024 2022/10/13 19:29:41 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:30:00 - mmengine - INFO - Epoch(train) [14][50/293] lr: 5.000000e-04 eta: 5:35:25 time: 0.388768 data_time: 0.085088 memory: 4980 loss_kpt: 0.001036 acc_pose: 0.668872 loss: 0.001036 2022/10/13 19:30:18 - mmengine - INFO - Epoch(train) [14][100/293] lr: 5.000000e-04 eta: 5:35:13 time: 0.355390 data_time: 0.076305 memory: 4980 loss_kpt: 0.001029 acc_pose: 0.691253 loss: 0.001029 2022/10/13 19:30:36 - mmengine - INFO - Epoch(train) [14][150/293] lr: 5.000000e-04 eta: 5:35:04 time: 0.360694 data_time: 0.082464 memory: 4980 loss_kpt: 0.001028 acc_pose: 0.617087 loss: 0.001028 2022/10/13 19:30:51 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:30:54 - mmengine - INFO - Epoch(train) [14][200/293] lr: 5.000000e-04 eta: 5:34:56 time: 0.363172 data_time: 0.067712 memory: 4980 loss_kpt: 0.001033 acc_pose: 0.684007 loss: 0.001033 2022/10/13 19:31:12 - mmengine - INFO - Epoch(train) [14][250/293] lr: 5.000000e-04 eta: 5:34:46 time: 0.359187 data_time: 0.072725 memory: 4980 loss_kpt: 0.001020 acc_pose: 0.635403 loss: 0.001020 2022/10/13 19:31:28 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:31:47 - mmengine - INFO - Epoch(train) [15][50/293] lr: 5.000000e-04 eta: 5:31:01 time: 0.371949 data_time: 0.094561 memory: 4980 loss_kpt: 0.001011 acc_pose: 0.642792 loss: 0.001011 2022/10/13 19:32:05 - mmengine - INFO - Epoch(train) [15][100/293] lr: 5.000000e-04 eta: 5:30:58 time: 0.366603 data_time: 0.083218 memory: 4980 loss_kpt: 0.001014 acc_pose: 0.678626 loss: 0.001014 2022/10/13 19:32:23 - mmengine - INFO - Epoch(train) [15][150/293] lr: 5.000000e-04 eta: 5:30:54 time: 0.366140 data_time: 0.090236 memory: 4980 loss_kpt: 0.001012 acc_pose: 0.716341 loss: 0.001012 2022/10/13 19:32:42 - mmengine - INFO - Epoch(train) [15][200/293] lr: 5.000000e-04 eta: 5:30:47 time: 0.362104 data_time: 0.070333 memory: 4980 loss_kpt: 0.001021 acc_pose: 0.629937 loss: 0.001021 2022/10/13 19:32:59 - mmengine - INFO - Epoch(train) [15][250/293] lr: 5.000000e-04 eta: 5:30:35 time: 0.355354 data_time: 0.061489 memory: 4980 loss_kpt: 0.001015 acc_pose: 0.670521 loss: 0.001015 2022/10/13 19:33:14 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:33:33 - mmengine - INFO - Epoch(train) [16][50/293] lr: 5.000000e-04 eta: 5:27:11 time: 0.378563 data_time: 0.082795 memory: 4980 loss_kpt: 0.001033 acc_pose: 0.666986 loss: 0.001033 2022/10/13 19:33:52 - mmengine - INFO - Epoch(train) [16][100/293] lr: 5.000000e-04 eta: 5:27:07 time: 0.363335 data_time: 0.074818 memory: 4980 loss_kpt: 0.001026 acc_pose: 0.715314 loss: 0.001026 2022/10/13 19:34:10 - mmengine - INFO - Epoch(train) [16][150/293] lr: 5.000000e-04 eta: 5:27:02 time: 0.363833 data_time: 0.069544 memory: 4980 loss_kpt: 0.001021 acc_pose: 0.714759 loss: 0.001021 2022/10/13 19:34:28 - mmengine - INFO - Epoch(train) [16][200/293] lr: 5.000000e-04 eta: 5:26:52 time: 0.355704 data_time: 0.129496 memory: 4980 loss_kpt: 0.001013 acc_pose: 0.623468 loss: 0.001013 2022/10/13 19:34:46 - mmengine - INFO - Epoch(train) [16][250/293] lr: 5.000000e-04 eta: 5:26:49 time: 0.368289 data_time: 0.077289 memory: 4980 loss_kpt: 0.001011 acc_pose: 0.667200 loss: 0.001011 2022/10/13 19:35:01 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:35:21 - mmengine - INFO - Epoch(train) [17][50/293] lr: 5.000000e-04 eta: 5:23:43 time: 0.385176 data_time: 0.096147 memory: 4980 loss_kpt: 0.001013 acc_pose: 0.673314 loss: 0.001013 2022/10/13 19:35:39 - mmengine - INFO - Epoch(train) [17][100/293] lr: 5.000000e-04 eta: 5:23:37 time: 0.360692 data_time: 0.067201 memory: 4980 loss_kpt: 0.001011 acc_pose: 0.669041 loss: 0.001011 2022/10/13 19:35:57 - mmengine - INFO - Epoch(train) [17][150/293] lr: 5.000000e-04 eta: 5:23:29 time: 0.357589 data_time: 0.070416 memory: 4980 loss_kpt: 0.001016 acc_pose: 0.705111 loss: 0.001016 2022/10/13 19:36:15 - mmengine - INFO - Epoch(train) [17][200/293] lr: 5.000000e-04 eta: 5:23:22 time: 0.359244 data_time: 0.063409 memory: 4980 loss_kpt: 0.000997 acc_pose: 0.631020 loss: 0.000997 2022/10/13 19:36:33 - mmengine - INFO - Epoch(train) [17][250/293] lr: 5.000000e-04 eta: 5:23:14 time: 0.359075 data_time: 0.069232 memory: 4980 loss_kpt: 0.001002 acc_pose: 0.665423 loss: 0.001002 2022/10/13 19:36:48 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:36:56 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:37:07 - mmengine - INFO - Epoch(train) [18][50/293] lr: 5.000000e-04 eta: 5:20:19 time: 0.382478 data_time: 0.120387 memory: 4980 loss_kpt: 0.001006 acc_pose: 0.714619 loss: 0.001006 2022/10/13 19:37:25 - mmengine - INFO - Epoch(train) [18][100/293] lr: 5.000000e-04 eta: 5:20:11 time: 0.355724 data_time: 0.073109 memory: 4980 loss_kpt: 0.000991 acc_pose: 0.706344 loss: 0.000991 2022/10/13 19:37:43 - mmengine - INFO - Epoch(train) [18][150/293] lr: 5.000000e-04 eta: 5:20:10 time: 0.368887 data_time: 0.072877 memory: 4980 loss_kpt: 0.001005 acc_pose: 0.700325 loss: 0.001005 2022/10/13 19:38:01 - mmengine - INFO - Epoch(train) [18][200/293] lr: 5.000000e-04 eta: 5:20:03 time: 0.359507 data_time: 0.076174 memory: 4980 loss_kpt: 0.001000 acc_pose: 0.712245 loss: 0.001000 2022/10/13 19:38:20 - mmengine - INFO - Epoch(train) [18][250/293] lr: 5.000000e-04 eta: 5:20:04 time: 0.375427 data_time: 0.080544 memory: 4980 loss_kpt: 0.001021 acc_pose: 0.670066 loss: 0.001021 2022/10/13 19:38:36 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:38:55 - mmengine - INFO - Epoch(train) [19][50/293] lr: 5.000000e-04 eta: 5:17:17 time: 0.377407 data_time: 0.091874 memory: 4980 loss_kpt: 0.001000 acc_pose: 0.645435 loss: 0.001000 2022/10/13 19:39:13 - mmengine - INFO - Epoch(train) [19][100/293] lr: 5.000000e-04 eta: 5:17:13 time: 0.364019 data_time: 0.078287 memory: 4980 loss_kpt: 0.001005 acc_pose: 0.639004 loss: 0.001005 2022/10/13 19:39:32 - mmengine - INFO - Epoch(train) [19][150/293] lr: 5.000000e-04 eta: 5:17:14 time: 0.373420 data_time: 0.066345 memory: 4980 loss_kpt: 0.000992 acc_pose: 0.667914 loss: 0.000992 2022/10/13 19:39:50 - mmengine - INFO - Epoch(train) [19][200/293] lr: 5.000000e-04 eta: 5:17:09 time: 0.362887 data_time: 0.073927 memory: 4980 loss_kpt: 0.000978 acc_pose: 0.713515 loss: 0.000978 2022/10/13 19:40:08 - mmengine - INFO - Epoch(train) [19][250/293] lr: 5.000000e-04 eta: 5:17:07 time: 0.369181 data_time: 0.082857 memory: 4980 loss_kpt: 0.001000 acc_pose: 0.722416 loss: 0.001000 2022/10/13 19:40:23 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:40:42 - mmengine - INFO - Epoch(train) [20][50/293] lr: 5.000000e-04 eta: 5:14:29 time: 0.378199 data_time: 0.084979 memory: 4980 loss_kpt: 0.000969 acc_pose: 0.717733 loss: 0.000969 2022/10/13 19:41:01 - mmengine - INFO - Epoch(train) [20][100/293] lr: 5.000000e-04 eta: 5:14:27 time: 0.366004 data_time: 0.068284 memory: 4980 loss_kpt: 0.001008 acc_pose: 0.652035 loss: 0.001008 2022/10/13 19:41:19 - mmengine - INFO - Epoch(train) [20][150/293] lr: 5.000000e-04 eta: 5:14:24 time: 0.366588 data_time: 0.076355 memory: 4980 loss_kpt: 0.001000 acc_pose: 0.689713 loss: 0.001000 2022/10/13 19:41:37 - mmengine - INFO - Epoch(train) [20][200/293] lr: 5.000000e-04 eta: 5:14:15 time: 0.355594 data_time: 0.104606 memory: 4980 loss_kpt: 0.000978 acc_pose: 0.750832 loss: 0.000978 2022/10/13 19:41:55 - mmengine - INFO - Epoch(train) [20][250/293] lr: 5.000000e-04 eta: 5:14:09 time: 0.360111 data_time: 0.150298 memory: 4980 loss_kpt: 0.000997 acc_pose: 0.703170 loss: 0.000997 2022/10/13 19:42:10 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:42:10 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/10/13 19:42:19 - mmengine - INFO - Epoch(val) [20][50/407] eta: 0:00:45 time: 0.126966 data_time: 0.072438 memory: 4980 2022/10/13 19:42:25 - mmengine - INFO - Epoch(val) [20][100/407] eta: 0:00:38 time: 0.126237 data_time: 0.072585 memory: 772 2022/10/13 19:42:31 - mmengine - INFO - Epoch(val) [20][150/407] eta: 0:00:31 time: 0.121595 data_time: 0.066497 memory: 772 2022/10/13 19:42:37 - mmengine - INFO - Epoch(val) [20][200/407] eta: 0:00:24 time: 0.116736 data_time: 0.059787 memory: 772 2022/10/13 19:42:43 - mmengine - INFO - Epoch(val) [20][250/407] eta: 0:00:19 time: 0.122633 data_time: 0.069035 memory: 772 2022/10/13 19:42:49 - mmengine - INFO - Epoch(val) [20][300/407] eta: 0:00:13 time: 0.127895 data_time: 0.074230 memory: 772 2022/10/13 19:42:56 - mmengine - INFO - Epoch(val) [20][350/407] eta: 0:00:07 time: 0.123249 data_time: 0.069764 memory: 772 2022/10/13 19:43:01 - mmengine - INFO - Epoch(val) [20][400/407] eta: 0:00:00 time: 0.116628 data_time: 0.064005 memory: 772 2022/10/13 19:43:39 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 19:43:53 - mmengine - INFO - Epoch(val) [20][407/407] coco/AP: 0.557842 coco/AP .5: 0.831661 coco/AP .75: 0.611533 coco/AP (M): 0.518440 coco/AP (L): 0.625811 coco/AR: 0.624969 coco/AR .5: 0.877834 coco/AR .75: 0.682620 coco/AR (M): 0.575498 coco/AR (L): 0.693943 2022/10/13 19:43:53 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_10.pth is removed 2022/10/13 19:43:55 - mmengine - INFO - The best checkpoint with 0.5578 coco/AP at 20 epoch is saved to best_coco/AP_epoch_20.pth. 2022/10/13 19:44:14 - mmengine - INFO - Epoch(train) [21][50/293] lr: 5.000000e-04 eta: 5:11:38 time: 0.374275 data_time: 0.138270 memory: 4980 loss_kpt: 0.000980 acc_pose: 0.705237 loss: 0.000980 2022/10/13 19:44:32 - mmengine - INFO - Epoch(train) [21][100/293] lr: 5.000000e-04 eta: 5:11:35 time: 0.367148 data_time: 0.074021 memory: 4980 loss_kpt: 0.000989 acc_pose: 0.676720 loss: 0.000989 2022/10/13 19:44:47 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:44:50 - mmengine - INFO - Epoch(train) [21][150/293] lr: 5.000000e-04 eta: 5:11:32 time: 0.366553 data_time: 0.074862 memory: 4980 loss_kpt: 0.000990 acc_pose: 0.680321 loss: 0.000990 2022/10/13 19:45:09 - mmengine - INFO - Epoch(train) [21][200/293] lr: 5.000000e-04 eta: 5:11:28 time: 0.364758 data_time: 0.078472 memory: 4980 loss_kpt: 0.000985 acc_pose: 0.704852 loss: 0.000985 2022/10/13 19:45:27 - mmengine - INFO - Epoch(train) [21][250/293] lr: 5.000000e-04 eta: 5:11:22 time: 0.360889 data_time: 0.069699 memory: 4980 loss_kpt: 0.000992 acc_pose: 0.642654 loss: 0.000992 2022/10/13 19:45:42 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:46:01 - mmengine - INFO - Epoch(train) [22][50/293] lr: 5.000000e-04 eta: 5:09:02 time: 0.383328 data_time: 0.090312 memory: 4980 loss_kpt: 0.000978 acc_pose: 0.704396 loss: 0.000978 2022/10/13 19:46:19 - mmengine - INFO - Epoch(train) [22][100/293] lr: 5.000000e-04 eta: 5:08:54 time: 0.355288 data_time: 0.077183 memory: 4980 loss_kpt: 0.000981 acc_pose: 0.686838 loss: 0.000981 2022/10/13 19:46:37 - mmengine - INFO - Epoch(train) [22][150/293] lr: 5.000000e-04 eta: 5:08:49 time: 0.361303 data_time: 0.077424 memory: 4980 loss_kpt: 0.000988 acc_pose: 0.682832 loss: 0.000988 2022/10/13 19:46:55 - mmengine - INFO - Epoch(train) [22][200/293] lr: 5.000000e-04 eta: 5:08:44 time: 0.361578 data_time: 0.071981 memory: 4980 loss_kpt: 0.000987 acc_pose: 0.638886 loss: 0.000987 2022/10/13 19:47:13 - mmengine - INFO - Epoch(train) [22][250/293] lr: 5.000000e-04 eta: 5:08:38 time: 0.360576 data_time: 0.077290 memory: 4980 loss_kpt: 0.000959 acc_pose: 0.650397 loss: 0.000959 2022/10/13 19:47:28 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:47:47 - mmengine - INFO - Epoch(train) [23][50/293] lr: 5.000000e-04 eta: 5:06:21 time: 0.375643 data_time: 0.102608 memory: 4980 loss_kpt: 0.000962 acc_pose: 0.707115 loss: 0.000962 2022/10/13 19:48:05 - mmengine - INFO - Epoch(train) [23][100/293] lr: 5.000000e-04 eta: 5:06:17 time: 0.363926 data_time: 0.077196 memory: 4980 loss_kpt: 0.000974 acc_pose: 0.694545 loss: 0.000974 2022/10/13 19:48:23 - mmengine - INFO - Epoch(train) [23][150/293] lr: 5.000000e-04 eta: 5:06:11 time: 0.360125 data_time: 0.068245 memory: 4980 loss_kpt: 0.000962 acc_pose: 0.675216 loss: 0.000962 2022/10/13 19:48:42 - mmengine - INFO - Epoch(train) [23][200/293] lr: 5.000000e-04 eta: 5:06:07 time: 0.365280 data_time: 0.083168 memory: 4980 loss_kpt: 0.000967 acc_pose: 0.624755 loss: 0.000967 2022/10/13 19:49:00 - mmengine - INFO - Epoch(train) [23][250/293] lr: 5.000000e-04 eta: 5:06:03 time: 0.366484 data_time: 0.076071 memory: 4980 loss_kpt: 0.000986 acc_pose: 0.704435 loss: 0.000986 2022/10/13 19:49:15 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:49:34 - mmengine - INFO - Epoch(train) [24][50/293] lr: 5.000000e-04 eta: 5:03:52 time: 0.375164 data_time: 0.118398 memory: 4980 loss_kpt: 0.000969 acc_pose: 0.673421 loss: 0.000969 2022/10/13 19:49:52 - mmengine - INFO - Epoch(train) [24][100/293] lr: 5.000000e-04 eta: 5:03:49 time: 0.366869 data_time: 0.069073 memory: 4980 loss_kpt: 0.000961 acc_pose: 0.693267 loss: 0.000961 2022/10/13 19:50:11 - mmengine - INFO - Epoch(train) [24][150/293] lr: 5.000000e-04 eta: 5:03:45 time: 0.366384 data_time: 0.071414 memory: 4980 loss_kpt: 0.000961 acc_pose: 0.683900 loss: 0.000961 2022/10/13 19:50:29 - mmengine - INFO - Epoch(train) [24][200/293] lr: 5.000000e-04 eta: 5:03:41 time: 0.364322 data_time: 0.080374 memory: 4980 loss_kpt: 0.000969 acc_pose: 0.687570 loss: 0.000969 2022/10/13 19:50:47 - mmengine - INFO - Epoch(train) [24][250/293] lr: 5.000000e-04 eta: 5:03:37 time: 0.367420 data_time: 0.077455 memory: 4980 loss_kpt: 0.000997 acc_pose: 0.692322 loss: 0.000997 2022/10/13 19:50:51 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:51:03 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:51:22 - mmengine - INFO - Epoch(train) [25][50/293] lr: 5.000000e-04 eta: 5:01:37 time: 0.388507 data_time: 0.087484 memory: 4980 loss_kpt: 0.000979 acc_pose: 0.704824 loss: 0.000979 2022/10/13 19:51:40 - mmengine - INFO - Epoch(train) [25][100/293] lr: 5.000000e-04 eta: 5:01:32 time: 0.363636 data_time: 0.077366 memory: 4980 loss_kpt: 0.000984 acc_pose: 0.646705 loss: 0.000984 2022/10/13 19:51:58 - mmengine - INFO - Epoch(train) [25][150/293] lr: 5.000000e-04 eta: 5:01:28 time: 0.366043 data_time: 0.073319 memory: 4980 loss_kpt: 0.000952 acc_pose: 0.698277 loss: 0.000952 2022/10/13 19:52:17 - mmengine - INFO - Epoch(train) [25][200/293] lr: 5.000000e-04 eta: 5:01:25 time: 0.370466 data_time: 0.076167 memory: 4980 loss_kpt: 0.000975 acc_pose: 0.664095 loss: 0.000975 2022/10/13 19:52:35 - mmengine - INFO - Epoch(train) [25][250/293] lr: 5.000000e-04 eta: 5:01:23 time: 0.370223 data_time: 0.071159 memory: 4980 loss_kpt: 0.000970 acc_pose: 0.696383 loss: 0.000970 2022/10/13 19:52:50 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:53:10 - mmengine - INFO - Epoch(train) [26][50/293] lr: 5.000000e-04 eta: 4:59:24 time: 0.381702 data_time: 0.096024 memory: 4980 loss_kpt: 0.000963 acc_pose: 0.705337 loss: 0.000963 2022/10/13 19:53:28 - mmengine - INFO - Epoch(train) [26][100/293] lr: 5.000000e-04 eta: 4:59:20 time: 0.365069 data_time: 0.081164 memory: 4980 loss_kpt: 0.000961 acc_pose: 0.659892 loss: 0.000961 2022/10/13 19:53:46 - mmengine - INFO - Epoch(train) [26][150/293] lr: 5.000000e-04 eta: 4:59:16 time: 0.367907 data_time: 0.093073 memory: 4980 loss_kpt: 0.000970 acc_pose: 0.685834 loss: 0.000970 2022/10/13 19:54:05 - mmengine - INFO - Epoch(train) [26][200/293] lr: 5.000000e-04 eta: 4:59:16 time: 0.377454 data_time: 0.074712 memory: 4980 loss_kpt: 0.000966 acc_pose: 0.675057 loss: 0.000966 2022/10/13 19:54:24 - mmengine - INFO - Epoch(train) [26][250/293] lr: 5.000000e-04 eta: 4:59:13 time: 0.372691 data_time: 0.080910 memory: 4980 loss_kpt: 0.000966 acc_pose: 0.712499 loss: 0.000966 2022/10/13 19:54:39 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:54:58 - mmengine - INFO - Epoch(train) [27][50/293] lr: 5.000000e-04 eta: 4:57:15 time: 0.368553 data_time: 0.122211 memory: 4980 loss_kpt: 0.000949 acc_pose: 0.711080 loss: 0.000949 2022/10/13 19:55:16 - mmengine - INFO - Epoch(train) [27][100/293] lr: 5.000000e-04 eta: 4:57:12 time: 0.370031 data_time: 0.068985 memory: 4980 loss_kpt: 0.000966 acc_pose: 0.665444 loss: 0.000966 2022/10/13 19:55:34 - mmengine - INFO - Epoch(train) [27][150/293] lr: 5.000000e-04 eta: 4:57:04 time: 0.357438 data_time: 0.077318 memory: 4980 loss_kpt: 0.000955 acc_pose: 0.665206 loss: 0.000955 2022/10/13 19:55:52 - mmengine - INFO - Epoch(train) [27][200/293] lr: 5.000000e-04 eta: 4:56:56 time: 0.357561 data_time: 0.079805 memory: 4980 loss_kpt: 0.000954 acc_pose: 0.725714 loss: 0.000954 2022/10/13 19:56:10 - mmengine - INFO - Epoch(train) [27][250/293] lr: 5.000000e-04 eta: 4:56:48 time: 0.356310 data_time: 0.065548 memory: 4980 loss_kpt: 0.000964 acc_pose: 0.719832 loss: 0.000964 2022/10/13 19:56:25 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:56:44 - mmengine - INFO - Epoch(train) [28][50/293] lr: 5.000000e-04 eta: 4:54:58 time: 0.382048 data_time: 0.140031 memory: 4980 loss_kpt: 0.000966 acc_pose: 0.754263 loss: 0.000966 2022/10/13 19:56:59 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:57:02 - mmengine - INFO - Epoch(train) [28][100/293] lr: 5.000000e-04 eta: 4:54:51 time: 0.358426 data_time: 0.070611 memory: 4980 loss_kpt: 0.000955 acc_pose: 0.697085 loss: 0.000955 2022/10/13 19:57:21 - mmengine - INFO - Epoch(train) [28][150/293] lr: 5.000000e-04 eta: 4:54:46 time: 0.365507 data_time: 0.068750 memory: 4980 loss_kpt: 0.000934 acc_pose: 0.732482 loss: 0.000934 2022/10/13 19:57:39 - mmengine - INFO - Epoch(train) [28][200/293] lr: 5.000000e-04 eta: 4:54:41 time: 0.364301 data_time: 0.070430 memory: 4980 loss_kpt: 0.000975 acc_pose: 0.707493 loss: 0.000975 2022/10/13 19:57:57 - mmengine - INFO - Epoch(train) [28][250/293] lr: 5.000000e-04 eta: 4:54:37 time: 0.370347 data_time: 0.075194 memory: 4980 loss_kpt: 0.000958 acc_pose: 0.687153 loss: 0.000958 2022/10/13 19:58:13 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 19:58:31 - mmengine - INFO - Epoch(train) [29][50/293] lr: 5.000000e-04 eta: 4:52:47 time: 0.370834 data_time: 0.087302 memory: 4980 loss_kpt: 0.000942 acc_pose: 0.699415 loss: 0.000942 2022/10/13 19:58:50 - mmengine - INFO - Epoch(train) [29][100/293] lr: 5.000000e-04 eta: 4:52:43 time: 0.369089 data_time: 0.075449 memory: 4980 loss_kpt: 0.000949 acc_pose: 0.710594 loss: 0.000949 2022/10/13 19:59:08 - mmengine - INFO - Epoch(train) [29][150/293] lr: 5.000000e-04 eta: 4:52:39 time: 0.370393 data_time: 0.073927 memory: 4980 loss_kpt: 0.000964 acc_pose: 0.718431 loss: 0.000964 2022/10/13 19:59:26 - mmengine - INFO - Epoch(train) [29][200/293] lr: 5.000000e-04 eta: 4:52:34 time: 0.365425 data_time: 0.074903 memory: 4980 loss_kpt: 0.000960 acc_pose: 0.679481 loss: 0.000960 2022/10/13 19:59:44 - mmengine - INFO - Epoch(train) [29][250/293] lr: 5.000000e-04 eta: 4:52:27 time: 0.359863 data_time: 0.065882 memory: 4980 loss_kpt: 0.000963 acc_pose: 0.676280 loss: 0.000963 2022/10/13 20:00:00 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:00:19 - mmengine - INFO - Epoch(train) [30][50/293] lr: 5.000000e-04 eta: 4:50:44 time: 0.382930 data_time: 0.109969 memory: 4980 loss_kpt: 0.000957 acc_pose: 0.667595 loss: 0.000957 2022/10/13 20:00:37 - mmengine - INFO - Epoch(train) [30][100/293] lr: 5.000000e-04 eta: 4:50:37 time: 0.360342 data_time: 0.071663 memory: 4980 loss_kpt: 0.000969 acc_pose: 0.685573 loss: 0.000969 2022/10/13 20:00:55 - mmengine - INFO - Epoch(train) [30][150/293] lr: 5.000000e-04 eta: 4:50:30 time: 0.359227 data_time: 0.083744 memory: 4980 loss_kpt: 0.000943 acc_pose: 0.691739 loss: 0.000943 2022/10/13 20:01:13 - mmengine - INFO - Epoch(train) [30][200/293] lr: 5.000000e-04 eta: 4:50:22 time: 0.359488 data_time: 0.082723 memory: 4980 loss_kpt: 0.000973 acc_pose: 0.678508 loss: 0.000973 2022/10/13 20:01:32 - mmengine - INFO - Epoch(train) [30][250/293] lr: 5.000000e-04 eta: 4:50:20 time: 0.375965 data_time: 0.066825 memory: 4980 loss_kpt: 0.000965 acc_pose: 0.644719 loss: 0.000965 2022/10/13 20:01:47 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:01:47 - mmengine - INFO - Saving checkpoint at 30 epochs 2022/10/13 20:01:56 - mmengine - INFO - Epoch(val) [30][50/407] eta: 0:00:46 time: 0.130223 data_time: 0.074809 memory: 4980 2022/10/13 20:02:02 - mmengine - INFO - Epoch(val) [30][100/407] eta: 0:00:37 time: 0.121925 data_time: 0.066830 memory: 772 2022/10/13 20:02:08 - mmengine - INFO - Epoch(val) [30][150/407] eta: 0:00:32 time: 0.126065 data_time: 0.070948 memory: 772 2022/10/13 20:02:14 - mmengine - INFO - Epoch(val) [30][200/407] eta: 0:00:25 time: 0.123761 data_time: 0.066737 memory: 772 2022/10/13 20:02:21 - mmengine - INFO - Epoch(val) [30][250/407] eta: 0:00:20 time: 0.129202 data_time: 0.074694 memory: 772 2022/10/13 20:02:27 - mmengine - INFO - Epoch(val) [30][300/407] eta: 0:00:13 time: 0.122772 data_time: 0.068706 memory: 772 2022/10/13 20:02:33 - mmengine - INFO - Epoch(val) [30][350/407] eta: 0:00:07 time: 0.129089 data_time: 0.072685 memory: 772 2022/10/13 20:02:39 - mmengine - INFO - Epoch(val) [30][400/407] eta: 0:00:00 time: 0.115864 data_time: 0.061018 memory: 772 2022/10/13 20:03:16 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 20:03:30 - mmengine - INFO - Epoch(val) [30][407/407] coco/AP: 0.573554 coco/AP .5: 0.840317 coco/AP .75: 0.627189 coco/AP (M): 0.533351 coco/AP (L): 0.642797 coco/AR: 0.640381 coco/AR .5: 0.888067 coco/AR .75: 0.696788 coco/AR (M): 0.591150 coco/AR (L): 0.708770 2022/10/13 20:03:30 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_20.pth is removed 2022/10/13 20:03:32 - mmengine - INFO - The best checkpoint with 0.5736 coco/AP at 30 epoch is saved to best_coco/AP_epoch_30.pth. 2022/10/13 20:03:50 - mmengine - INFO - Epoch(train) [31][50/293] lr: 5.000000e-04 eta: 4:48:37 time: 0.372439 data_time: 0.150910 memory: 4980 loss_kpt: 0.000954 acc_pose: 0.658236 loss: 0.000954 2022/10/13 20:04:09 - mmengine - INFO - Epoch(train) [31][100/293] lr: 5.000000e-04 eta: 4:48:33 time: 0.369816 data_time: 0.130921 memory: 4980 loss_kpt: 0.000964 acc_pose: 0.702942 loss: 0.000964 2022/10/13 20:04:27 - mmengine - INFO - Epoch(train) [31][150/293] lr: 5.000000e-04 eta: 4:48:28 time: 0.369308 data_time: 0.127364 memory: 4980 loss_kpt: 0.000940 acc_pose: 0.704488 loss: 0.000940 2022/10/13 20:04:45 - mmengine - INFO - Epoch(train) [31][200/293] lr: 5.000000e-04 eta: 4:48:21 time: 0.361283 data_time: 0.119651 memory: 4980 loss_kpt: 0.000949 acc_pose: 0.717382 loss: 0.000949 2022/10/13 20:04:49 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:05:03 - mmengine - INFO - Epoch(train) [31][250/293] lr: 5.000000e-04 eta: 4:48:15 time: 0.363350 data_time: 0.083424 memory: 4980 loss_kpt: 0.000948 acc_pose: 0.717145 loss: 0.000948 2022/10/13 20:05:19 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:05:38 - mmengine - INFO - Epoch(train) [32][50/293] lr: 5.000000e-04 eta: 4:46:39 time: 0.384253 data_time: 0.120572 memory: 4980 loss_kpt: 0.000944 acc_pose: 0.716714 loss: 0.000944 2022/10/13 20:05:57 - mmengine - INFO - Epoch(train) [32][100/293] lr: 5.000000e-04 eta: 4:46:32 time: 0.363219 data_time: 0.067374 memory: 4980 loss_kpt: 0.000938 acc_pose: 0.773852 loss: 0.000938 2022/10/13 20:06:15 - mmengine - INFO - Epoch(train) [32][150/293] lr: 5.000000e-04 eta: 4:46:25 time: 0.360505 data_time: 0.072705 memory: 4980 loss_kpt: 0.000951 acc_pose: 0.649624 loss: 0.000951 2022/10/13 20:06:33 - mmengine - INFO - Epoch(train) [32][200/293] lr: 5.000000e-04 eta: 4:46:17 time: 0.361000 data_time: 0.072291 memory: 4980 loss_kpt: 0.000940 acc_pose: 0.681083 loss: 0.000940 2022/10/13 20:06:51 - mmengine - INFO - Epoch(train) [32][250/293] lr: 5.000000e-04 eta: 4:46:09 time: 0.356567 data_time: 0.081173 memory: 4980 loss_kpt: 0.000942 acc_pose: 0.706937 loss: 0.000942 2022/10/13 20:07:06 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:07:25 - mmengine - INFO - Epoch(train) [33][50/293] lr: 5.000000e-04 eta: 4:44:32 time: 0.372912 data_time: 0.092328 memory: 4980 loss_kpt: 0.000955 acc_pose: 0.711226 loss: 0.000955 2022/10/13 20:07:43 - mmengine - INFO - Epoch(train) [33][100/293] lr: 5.000000e-04 eta: 4:44:26 time: 0.363011 data_time: 0.096180 memory: 4980 loss_kpt: 0.000946 acc_pose: 0.754570 loss: 0.000946 2022/10/13 20:08:01 - mmengine - INFO - Epoch(train) [33][150/293] lr: 5.000000e-04 eta: 4:44:18 time: 0.361820 data_time: 0.072711 memory: 4980 loss_kpt: 0.000944 acc_pose: 0.646734 loss: 0.000944 2022/10/13 20:08:20 - mmengine - INFO - Epoch(train) [33][200/293] lr: 5.000000e-04 eta: 4:44:14 time: 0.371701 data_time: 0.080103 memory: 4980 loss_kpt: 0.000932 acc_pose: 0.742058 loss: 0.000932 2022/10/13 20:08:38 - mmengine - INFO - Epoch(train) [33][250/293] lr: 5.000000e-04 eta: 4:44:09 time: 0.369891 data_time: 0.081528 memory: 4980 loss_kpt: 0.000944 acc_pose: 0.712710 loss: 0.000944 2022/10/13 20:08:53 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:09:12 - mmengine - INFO - Epoch(train) [34][50/293] lr: 5.000000e-04 eta: 4:42:35 time: 0.375341 data_time: 0.080458 memory: 4980 loss_kpt: 0.000953 acc_pose: 0.741646 loss: 0.000953 2022/10/13 20:09:30 - mmengine - INFO - Epoch(train) [34][100/293] lr: 5.000000e-04 eta: 4:42:29 time: 0.366402 data_time: 0.073056 memory: 4980 loss_kpt: 0.000953 acc_pose: 0.724144 loss: 0.000953 2022/10/13 20:09:49 - mmengine - INFO - Epoch(train) [34][150/293] lr: 5.000000e-04 eta: 4:42:23 time: 0.364545 data_time: 0.076624 memory: 4980 loss_kpt: 0.000934 acc_pose: 0.693616 loss: 0.000934 2022/10/13 20:10:07 - mmengine - INFO - Epoch(train) [34][200/293] lr: 5.000000e-04 eta: 4:42:16 time: 0.364529 data_time: 0.081767 memory: 4980 loss_kpt: 0.000928 acc_pose: 0.708463 loss: 0.000928 2022/10/13 20:10:25 - mmengine - INFO - Epoch(train) [34][250/293] lr: 5.000000e-04 eta: 4:42:08 time: 0.358694 data_time: 0.073191 memory: 4980 loss_kpt: 0.000916 acc_pose: 0.677255 loss: 0.000916 2022/10/13 20:10:40 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:10:55 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:10:59 - mmengine - INFO - Epoch(train) [35][50/293] lr: 5.000000e-04 eta: 4:40:37 time: 0.374713 data_time: 0.085031 memory: 4980 loss_kpt: 0.000934 acc_pose: 0.717961 loss: 0.000934 2022/10/13 20:11:18 - mmengine - INFO - Epoch(train) [35][100/293] lr: 5.000000e-04 eta: 4:40:31 time: 0.368091 data_time: 0.082284 memory: 4980 loss_kpt: 0.000942 acc_pose: 0.652099 loss: 0.000942 2022/10/13 20:11:36 - mmengine - INFO - Epoch(train) [35][150/293] lr: 5.000000e-04 eta: 4:40:27 time: 0.375327 data_time: 0.068320 memory: 4980 loss_kpt: 0.000933 acc_pose: 0.742600 loss: 0.000933 2022/10/13 20:11:54 - mmengine - INFO - Epoch(train) [35][200/293] lr: 5.000000e-04 eta: 4:40:17 time: 0.354123 data_time: 0.072352 memory: 4980 loss_kpt: 0.000937 acc_pose: 0.645555 loss: 0.000937 2022/10/13 20:12:12 - mmengine - INFO - Epoch(train) [35][250/293] lr: 5.000000e-04 eta: 4:40:10 time: 0.363461 data_time: 0.067322 memory: 4980 loss_kpt: 0.000933 acc_pose: 0.705587 loss: 0.000933 2022/10/13 20:12:27 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:12:46 - mmengine - INFO - Epoch(train) [36][50/293] lr: 5.000000e-04 eta: 4:38:42 time: 0.377874 data_time: 0.130911 memory: 4980 loss_kpt: 0.000941 acc_pose: 0.739827 loss: 0.000941 2022/10/13 20:13:04 - mmengine - INFO - Epoch(train) [36][100/293] lr: 5.000000e-04 eta: 4:38:33 time: 0.358273 data_time: 0.088200 memory: 4980 loss_kpt: 0.000950 acc_pose: 0.738869 loss: 0.000950 2022/10/13 20:13:22 - mmengine - INFO - Epoch(train) [36][150/293] lr: 5.000000e-04 eta: 4:38:27 time: 0.365649 data_time: 0.070256 memory: 4980 loss_kpt: 0.000923 acc_pose: 0.721245 loss: 0.000923 2022/10/13 20:13:41 - mmengine - INFO - Epoch(train) [36][200/293] lr: 5.000000e-04 eta: 4:38:19 time: 0.362791 data_time: 0.076214 memory: 4980 loss_kpt: 0.000934 acc_pose: 0.745268 loss: 0.000934 2022/10/13 20:13:59 - mmengine - INFO - Epoch(train) [36][250/293] lr: 5.000000e-04 eta: 4:38:13 time: 0.371002 data_time: 0.076363 memory: 4980 loss_kpt: 0.000948 acc_pose: 0.706384 loss: 0.000948 2022/10/13 20:14:15 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:14:34 - mmengine - INFO - Epoch(train) [37][50/293] lr: 5.000000e-04 eta: 4:36:47 time: 0.375033 data_time: 0.087480 memory: 4980 loss_kpt: 0.000961 acc_pose: 0.674413 loss: 0.000961 2022/10/13 20:14:52 - mmengine - INFO - Epoch(train) [37][100/293] lr: 5.000000e-04 eta: 4:36:39 time: 0.363119 data_time: 0.074451 memory: 4980 loss_kpt: 0.000949 acc_pose: 0.731554 loss: 0.000949 2022/10/13 20:15:10 - mmengine - INFO - Epoch(train) [37][150/293] lr: 5.000000e-04 eta: 4:36:32 time: 0.364771 data_time: 0.105355 memory: 4980 loss_kpt: 0.000932 acc_pose: 0.659432 loss: 0.000932 2022/10/13 20:15:28 - mmengine - INFO - Epoch(train) [37][200/293] lr: 5.000000e-04 eta: 4:36:26 time: 0.368859 data_time: 0.071869 memory: 4980 loss_kpt: 0.000937 acc_pose: 0.679056 loss: 0.000937 2022/10/13 20:15:46 - mmengine - INFO - Epoch(train) [37][250/293] lr: 5.000000e-04 eta: 4:36:18 time: 0.361445 data_time: 0.069211 memory: 4980 loss_kpt: 0.000941 acc_pose: 0.714984 loss: 0.000941 2022/10/13 20:16:02 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:16:20 - mmengine - INFO - Epoch(train) [38][50/293] lr: 5.000000e-04 eta: 4:34:52 time: 0.368536 data_time: 0.082325 memory: 4980 loss_kpt: 0.000924 acc_pose: 0.749504 loss: 0.000924 2022/10/13 20:16:38 - mmengine - INFO - Epoch(train) [38][100/293] lr: 5.000000e-04 eta: 4:34:44 time: 0.361020 data_time: 0.073799 memory: 4980 loss_kpt: 0.000938 acc_pose: 0.657892 loss: 0.000938 2022/10/13 20:16:56 - mmengine - INFO - Epoch(train) [38][150/293] lr: 5.000000e-04 eta: 4:34:36 time: 0.364951 data_time: 0.070610 memory: 4980 loss_kpt: 0.000930 acc_pose: 0.644679 loss: 0.000930 2022/10/13 20:17:00 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:17:14 - mmengine - INFO - Epoch(train) [38][200/293] lr: 5.000000e-04 eta: 4:34:28 time: 0.360957 data_time: 0.083613 memory: 4980 loss_kpt: 0.000936 acc_pose: 0.675819 loss: 0.000936 2022/10/13 20:17:33 - mmengine - INFO - Epoch(train) [38][250/293] lr: 5.000000e-04 eta: 4:34:23 time: 0.376821 data_time: 0.079715 memory: 4980 loss_kpt: 0.000933 acc_pose: 0.661019 loss: 0.000933 2022/10/13 20:17:48 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:18:07 - mmengine - INFO - Epoch(train) [39][50/293] lr: 5.000000e-04 eta: 4:33:02 time: 0.381283 data_time: 0.097890 memory: 4980 loss_kpt: 0.000930 acc_pose: 0.727319 loss: 0.000930 2022/10/13 20:18:25 - mmengine - INFO - Epoch(train) [39][100/293] lr: 5.000000e-04 eta: 4:32:52 time: 0.354615 data_time: 0.072424 memory: 4980 loss_kpt: 0.000921 acc_pose: 0.723900 loss: 0.000921 2022/10/13 20:18:44 - mmengine - INFO - Epoch(train) [39][150/293] lr: 5.000000e-04 eta: 4:32:46 time: 0.369175 data_time: 0.127023 memory: 4980 loss_kpt: 0.000912 acc_pose: 0.694236 loss: 0.000912 2022/10/13 20:19:01 - mmengine - INFO - Epoch(train) [39][200/293] lr: 5.000000e-04 eta: 4:32:36 time: 0.353312 data_time: 0.109481 memory: 4980 loss_kpt: 0.000935 acc_pose: 0.707264 loss: 0.000935 2022/10/13 20:19:20 - mmengine - INFO - Epoch(train) [39][250/293] lr: 5.000000e-04 eta: 4:32:28 time: 0.366995 data_time: 0.098859 memory: 4980 loss_kpt: 0.000924 acc_pose: 0.639868 loss: 0.000924 2022/10/13 20:19:35 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:19:54 - mmengine - INFO - Epoch(train) [40][50/293] lr: 5.000000e-04 eta: 4:31:09 time: 0.382786 data_time: 0.093945 memory: 4980 loss_kpt: 0.000928 acc_pose: 0.724650 loss: 0.000928 2022/10/13 20:20:12 - mmengine - INFO - Epoch(train) [40][100/293] lr: 5.000000e-04 eta: 4:31:01 time: 0.363488 data_time: 0.079450 memory: 4980 loss_kpt: 0.000940 acc_pose: 0.708852 loss: 0.000940 2022/10/13 20:20:31 - mmengine - INFO - Epoch(train) [40][150/293] lr: 5.000000e-04 eta: 4:30:58 time: 0.382950 data_time: 0.100874 memory: 4980 loss_kpt: 0.000935 acc_pose: 0.684519 loss: 0.000935 2022/10/13 20:20:50 - mmengine - INFO - Epoch(train) [40][200/293] lr: 5.000000e-04 eta: 4:30:55 time: 0.389506 data_time: 0.073397 memory: 4980 loss_kpt: 0.000925 acc_pose: 0.714453 loss: 0.000925 2022/10/13 20:21:10 - mmengine - INFO - Epoch(train) [40][250/293] lr: 5.000000e-04 eta: 4:30:51 time: 0.385088 data_time: 0.067164 memory: 4980 loss_kpt: 0.000936 acc_pose: 0.741947 loss: 0.000936 2022/10/13 20:21:26 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:21:26 - mmengine - INFO - Saving checkpoint at 40 epochs 2022/10/13 20:21:35 - mmengine - INFO - Epoch(val) [40][50/407] eta: 0:00:47 time: 0.134097 data_time: 0.080266 memory: 4980 2022/10/13 20:21:41 - mmengine - INFO - Epoch(val) [40][100/407] eta: 0:00:38 time: 0.126319 data_time: 0.071599 memory: 772 2022/10/13 20:21:48 - mmengine - INFO - Epoch(val) [40][150/407] eta: 0:00:34 time: 0.134555 data_time: 0.081069 memory: 772 2022/10/13 20:21:54 - mmengine - INFO - Epoch(val) [40][200/407] eta: 0:00:25 time: 0.125458 data_time: 0.071214 memory: 772 2022/10/13 20:22:01 - mmengine - INFO - Epoch(val) [40][250/407] eta: 0:00:20 time: 0.133694 data_time: 0.079269 memory: 772 2022/10/13 20:22:07 - mmengine - INFO - Epoch(val) [40][300/407] eta: 0:00:13 time: 0.124789 data_time: 0.065723 memory: 772 2022/10/13 20:22:13 - mmengine - INFO - Epoch(val) [40][350/407] eta: 0:00:07 time: 0.128404 data_time: 0.073780 memory: 772 2022/10/13 20:22:19 - mmengine - INFO - Epoch(val) [40][400/407] eta: 0:00:00 time: 0.120590 data_time: 0.067465 memory: 772 2022/10/13 20:22:57 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 20:23:11 - mmengine - INFO - Epoch(val) [40][407/407] coco/AP: 0.586129 coco/AP .5: 0.849703 coco/AP .75: 0.641099 coco/AP (M): 0.544951 coco/AP (L): 0.656990 coco/AR: 0.651496 coco/AR .5: 0.894207 coco/AR .75: 0.707809 coco/AR (M): 0.601502 coco/AR (L): 0.721665 2022/10/13 20:23:11 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_30.pth is removed 2022/10/13 20:23:12 - mmengine - INFO - The best checkpoint with 0.5861 coco/AP at 40 epoch is saved to best_coco/AP_epoch_40.pth. 2022/10/13 20:23:32 - mmengine - INFO - Epoch(train) [41][50/293] lr: 5.000000e-04 eta: 4:29:34 time: 0.381318 data_time: 0.132351 memory: 4980 loss_kpt: 0.000908 acc_pose: 0.728736 loss: 0.000908 2022/10/13 20:23:50 - mmengine - INFO - Epoch(train) [41][100/293] lr: 5.000000e-04 eta: 4:29:27 time: 0.373035 data_time: 0.070336 memory: 4980 loss_kpt: 0.000936 acc_pose: 0.684027 loss: 0.000936 2022/10/13 20:24:09 - mmengine - INFO - Epoch(train) [41][150/293] lr: 5.000000e-04 eta: 4:29:22 time: 0.375789 data_time: 0.083224 memory: 4980 loss_kpt: 0.000937 acc_pose: 0.700250 loss: 0.000937 2022/10/13 20:24:27 - mmengine - INFO - Epoch(train) [41][200/293] lr: 5.000000e-04 eta: 4:29:13 time: 0.363007 data_time: 0.075167 memory: 4980 loss_kpt: 0.000910 acc_pose: 0.720945 loss: 0.000910 2022/10/13 20:24:46 - mmengine - INFO - Epoch(train) [41][250/293] lr: 5.000000e-04 eta: 4:29:06 time: 0.370393 data_time: 0.073271 memory: 4980 loss_kpt: 0.000922 acc_pose: 0.682278 loss: 0.000922 2022/10/13 20:24:57 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:25:01 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:25:20 - mmengine - INFO - Epoch(train) [42][50/293] lr: 5.000000e-04 eta: 4:27:49 time: 0.376579 data_time: 0.109184 memory: 4980 loss_kpt: 0.000917 acc_pose: 0.669855 loss: 0.000917 2022/10/13 20:25:38 - mmengine - INFO - Epoch(train) [42][100/293] lr: 5.000000e-04 eta: 4:27:39 time: 0.355773 data_time: 0.102650 memory: 4980 loss_kpt: 0.000910 acc_pose: 0.722907 loss: 0.000910 2022/10/13 20:25:56 - mmengine - INFO - Epoch(train) [42][150/293] lr: 5.000000e-04 eta: 4:27:32 time: 0.372697 data_time: 0.074070 memory: 4980 loss_kpt: 0.000924 acc_pose: 0.722794 loss: 0.000924 2022/10/13 20:26:14 - mmengine - INFO - Epoch(train) [42][200/293] lr: 5.000000e-04 eta: 4:27:25 time: 0.366886 data_time: 0.077167 memory: 4980 loss_kpt: 0.000917 acc_pose: 0.671129 loss: 0.000917 2022/10/13 20:26:33 - mmengine - INFO - Epoch(train) [42][250/293] lr: 5.000000e-04 eta: 4:27:15 time: 0.360143 data_time: 0.067740 memory: 4980 loss_kpt: 0.000928 acc_pose: 0.751396 loss: 0.000928 2022/10/13 20:26:48 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:27:07 - mmengine - INFO - Epoch(train) [43][50/293] lr: 5.000000e-04 eta: 4:26:00 time: 0.378249 data_time: 0.086479 memory: 4980 loss_kpt: 0.000930 acc_pose: 0.754709 loss: 0.000930 2022/10/13 20:27:25 - mmengine - INFO - Epoch(train) [43][100/293] lr: 5.000000e-04 eta: 4:25:53 time: 0.370022 data_time: 0.077147 memory: 4980 loss_kpt: 0.000936 acc_pose: 0.731530 loss: 0.000936 2022/10/13 20:27:43 - mmengine - INFO - Epoch(train) [43][150/293] lr: 5.000000e-04 eta: 4:25:43 time: 0.360850 data_time: 0.070617 memory: 4980 loss_kpt: 0.000930 acc_pose: 0.681079 loss: 0.000930 2022/10/13 20:28:01 - mmengine - INFO - Epoch(train) [43][200/293] lr: 5.000000e-04 eta: 4:25:34 time: 0.358475 data_time: 0.075180 memory: 4980 loss_kpt: 0.000929 acc_pose: 0.741431 loss: 0.000929 2022/10/13 20:28:20 - mmengine - INFO - Epoch(train) [43][250/293] lr: 5.000000e-04 eta: 4:25:26 time: 0.366004 data_time: 0.079876 memory: 4980 loss_kpt: 0.000911 acc_pose: 0.704070 loss: 0.000911 2022/10/13 20:28:35 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:28:54 - mmengine - INFO - Epoch(train) [44][50/293] lr: 5.000000e-04 eta: 4:24:11 time: 0.376632 data_time: 0.127153 memory: 4980 loss_kpt: 0.000931 acc_pose: 0.698649 loss: 0.000931 2022/10/13 20:29:11 - mmengine - INFO - Epoch(train) [44][100/293] lr: 5.000000e-04 eta: 4:24:00 time: 0.350488 data_time: 0.075206 memory: 4980 loss_kpt: 0.000922 acc_pose: 0.637876 loss: 0.000922 2022/10/13 20:29:30 - mmengine - INFO - Epoch(train) [44][150/293] lr: 5.000000e-04 eta: 4:23:53 time: 0.373827 data_time: 0.077336 memory: 4980 loss_kpt: 0.000919 acc_pose: 0.719270 loss: 0.000919 2022/10/13 20:29:48 - mmengine - INFO - Epoch(train) [44][200/293] lr: 5.000000e-04 eta: 4:23:44 time: 0.363152 data_time: 0.074601 memory: 4980 loss_kpt: 0.000933 acc_pose: 0.725710 loss: 0.000933 2022/10/13 20:30:06 - mmengine - INFO - Epoch(train) [44][250/293] lr: 5.000000e-04 eta: 4:23:36 time: 0.367669 data_time: 0.089647 memory: 4980 loss_kpt: 0.000925 acc_pose: 0.683323 loss: 0.000925 2022/10/13 20:30:22 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:30:41 - mmengine - INFO - Epoch(train) [45][50/293] lr: 5.000000e-04 eta: 4:22:23 time: 0.373776 data_time: 0.083708 memory: 4980 loss_kpt: 0.000924 acc_pose: 0.724414 loss: 0.000924 2022/10/13 20:30:58 - mmengine - INFO - Epoch(train) [45][100/293] lr: 5.000000e-04 eta: 4:22:12 time: 0.355680 data_time: 0.126631 memory: 4980 loss_kpt: 0.000923 acc_pose: 0.647792 loss: 0.000923 2022/10/13 20:31:01 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:31:17 - mmengine - INFO - Epoch(train) [45][150/293] lr: 5.000000e-04 eta: 4:22:05 time: 0.369648 data_time: 0.084681 memory: 4980 loss_kpt: 0.000923 acc_pose: 0.642393 loss: 0.000923 2022/10/13 20:31:35 - mmengine - INFO - Epoch(train) [45][200/293] lr: 5.000000e-04 eta: 4:21:55 time: 0.360944 data_time: 0.069755 memory: 4980 loss_kpt: 0.000916 acc_pose: 0.683557 loss: 0.000916 2022/10/13 20:31:54 - mmengine - INFO - Epoch(train) [45][250/293] lr: 5.000000e-04 eta: 4:21:48 time: 0.374734 data_time: 0.085501 memory: 4980 loss_kpt: 0.000920 acc_pose: 0.733210 loss: 0.000920 2022/10/13 20:32:09 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:32:28 - mmengine - INFO - Epoch(train) [46][50/293] lr: 5.000000e-04 eta: 4:20:37 time: 0.376696 data_time: 0.103566 memory: 4980 loss_kpt: 0.000907 acc_pose: 0.709100 loss: 0.000907 2022/10/13 20:32:46 - mmengine - INFO - Epoch(train) [46][100/293] lr: 5.000000e-04 eta: 4:20:27 time: 0.357868 data_time: 0.101967 memory: 4980 loss_kpt: 0.000914 acc_pose: 0.705191 loss: 0.000914 2022/10/13 20:33:04 - mmengine - INFO - Epoch(train) [46][150/293] lr: 5.000000e-04 eta: 4:20:17 time: 0.358969 data_time: 0.090898 memory: 4980 loss_kpt: 0.000888 acc_pose: 0.690507 loss: 0.000888 2022/10/13 20:33:22 - mmengine - INFO - Epoch(train) [46][200/293] lr: 5.000000e-04 eta: 4:20:07 time: 0.359997 data_time: 0.070283 memory: 4980 loss_kpt: 0.000934 acc_pose: 0.734453 loss: 0.000934 2022/10/13 20:33:40 - mmengine - INFO - Epoch(train) [46][250/293] lr: 5.000000e-04 eta: 4:19:59 time: 0.367595 data_time: 0.085341 memory: 4980 loss_kpt: 0.000917 acc_pose: 0.715139 loss: 0.000917 2022/10/13 20:33:56 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:34:14 - mmengine - INFO - Epoch(train) [47][50/293] lr: 5.000000e-04 eta: 4:18:48 time: 0.373349 data_time: 0.101467 memory: 4980 loss_kpt: 0.000917 acc_pose: 0.692380 loss: 0.000917 2022/10/13 20:34:32 - mmengine - INFO - Epoch(train) [47][100/293] lr: 5.000000e-04 eta: 4:18:37 time: 0.353060 data_time: 0.068853 memory: 4980 loss_kpt: 0.000916 acc_pose: 0.703012 loss: 0.000916 2022/10/13 20:34:50 - mmengine - INFO - Epoch(train) [47][150/293] lr: 5.000000e-04 eta: 4:18:26 time: 0.357231 data_time: 0.073351 memory: 4980 loss_kpt: 0.000913 acc_pose: 0.679089 loss: 0.000913 2022/10/13 20:35:09 - mmengine - INFO - Epoch(train) [47][200/293] lr: 5.000000e-04 eta: 4:18:21 time: 0.383950 data_time: 0.084360 memory: 4980 loss_kpt: 0.000907 acc_pose: 0.752634 loss: 0.000907 2022/10/13 20:35:28 - mmengine - INFO - Epoch(train) [47][250/293] lr: 5.000000e-04 eta: 4:18:13 time: 0.370900 data_time: 0.076436 memory: 4980 loss_kpt: 0.000913 acc_pose: 0.701421 loss: 0.000913 2022/10/13 20:35:43 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:36:02 - mmengine - INFO - Epoch(train) [48][50/293] lr: 5.000000e-04 eta: 4:17:03 time: 0.372533 data_time: 0.080777 memory: 4980 loss_kpt: 0.000916 acc_pose: 0.676418 loss: 0.000916 2022/10/13 20:36:19 - mmengine - INFO - Epoch(train) [48][100/293] lr: 5.000000e-04 eta: 4:16:53 time: 0.356849 data_time: 0.075941 memory: 4980 loss_kpt: 0.000907 acc_pose: 0.754195 loss: 0.000907 2022/10/13 20:36:38 - mmengine - INFO - Epoch(train) [48][150/293] lr: 5.000000e-04 eta: 4:16:44 time: 0.366329 data_time: 0.067212 memory: 4980 loss_kpt: 0.000913 acc_pose: 0.720601 loss: 0.000913 2022/10/13 20:36:56 - mmengine - INFO - Epoch(train) [48][200/293] lr: 5.000000e-04 eta: 4:16:34 time: 0.361607 data_time: 0.074690 memory: 4980 loss_kpt: 0.000908 acc_pose: 0.715393 loss: 0.000908 2022/10/13 20:37:06 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:37:14 - mmengine - INFO - Epoch(train) [48][250/293] lr: 5.000000e-04 eta: 4:16:24 time: 0.362446 data_time: 0.070684 memory: 4980 loss_kpt: 0.000912 acc_pose: 0.742693 loss: 0.000912 2022/10/13 20:37:29 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:37:48 - mmengine - INFO - Epoch(train) [49][50/293] lr: 5.000000e-04 eta: 4:15:16 time: 0.374816 data_time: 0.101798 memory: 4980 loss_kpt: 0.000914 acc_pose: 0.774011 loss: 0.000914 2022/10/13 20:38:06 - mmengine - INFO - Epoch(train) [49][100/293] lr: 5.000000e-04 eta: 4:15:06 time: 0.357556 data_time: 0.071994 memory: 4980 loss_kpt: 0.000922 acc_pose: 0.733538 loss: 0.000922 2022/10/13 20:38:25 - mmengine - INFO - Epoch(train) [49][150/293] lr: 5.000000e-04 eta: 4:14:58 time: 0.373317 data_time: 0.077782 memory: 4980 loss_kpt: 0.000894 acc_pose: 0.745468 loss: 0.000894 2022/10/13 20:38:43 - mmengine - INFO - Epoch(train) [49][200/293] lr: 5.000000e-04 eta: 4:14:48 time: 0.360637 data_time: 0.073797 memory: 4980 loss_kpt: 0.000907 acc_pose: 0.745944 loss: 0.000907 2022/10/13 20:39:01 - mmengine - INFO - Epoch(train) [49][250/293] lr: 5.000000e-04 eta: 4:14:38 time: 0.364418 data_time: 0.074449 memory: 4980 loss_kpt: 0.000911 acc_pose: 0.691702 loss: 0.000911 2022/10/13 20:39:16 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:39:35 - mmengine - INFO - Epoch(train) [50][50/293] lr: 5.000000e-04 eta: 4:13:31 time: 0.374491 data_time: 0.085650 memory: 4980 loss_kpt: 0.000902 acc_pose: 0.706872 loss: 0.000902 2022/10/13 20:39:52 - mmengine - INFO - Epoch(train) [50][100/293] lr: 5.000000e-04 eta: 4:13:19 time: 0.349869 data_time: 0.070871 memory: 4980 loss_kpt: 0.000933 acc_pose: 0.714626 loss: 0.000933 2022/10/13 20:40:11 - mmengine - INFO - Epoch(train) [50][150/293] lr: 5.000000e-04 eta: 4:13:10 time: 0.361728 data_time: 0.094843 memory: 4980 loss_kpt: 0.000899 acc_pose: 0.730548 loss: 0.000899 2022/10/13 20:40:28 - mmengine - INFO - Epoch(train) [50][200/293] lr: 5.000000e-04 eta: 4:12:59 time: 0.354762 data_time: 0.079744 memory: 4980 loss_kpt: 0.000914 acc_pose: 0.715823 loss: 0.000914 2022/10/13 20:40:47 - mmengine - INFO - Epoch(train) [50][250/293] lr: 5.000000e-04 eta: 4:12:50 time: 0.367455 data_time: 0.069135 memory: 4980 loss_kpt: 0.000918 acc_pose: 0.704722 loss: 0.000918 2022/10/13 20:41:02 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:41:02 - mmengine - INFO - Saving checkpoint at 50 epochs 2022/10/13 20:41:11 - mmengine - INFO - Epoch(val) [50][50/407] eta: 0:00:49 time: 0.137356 data_time: 0.079443 memory: 4980 2022/10/13 20:41:17 - mmengine - INFO - Epoch(val) [50][100/407] eta: 0:00:37 time: 0.121117 data_time: 0.064540 memory: 772 2022/10/13 20:41:23 - mmengine - INFO - Epoch(val) [50][150/407] eta: 0:00:31 time: 0.123154 data_time: 0.068629 memory: 772 2022/10/13 20:41:29 - mmengine - INFO - Epoch(val) [50][200/407] eta: 0:00:26 time: 0.126051 data_time: 0.070669 memory: 772 2022/10/13 20:41:35 - mmengine - INFO - Epoch(val) [50][250/407] eta: 0:00:19 time: 0.122231 data_time: 0.067534 memory: 772 2022/10/13 20:41:41 - mmengine - INFO - Epoch(val) [50][300/407] eta: 0:00:13 time: 0.121650 data_time: 0.068403 memory: 772 2022/10/13 20:41:48 - mmengine - INFO - Epoch(val) [50][350/407] eta: 0:00:07 time: 0.122898 data_time: 0.066484 memory: 772 2022/10/13 20:41:54 - mmengine - INFO - Epoch(val) [50][400/407] eta: 0:00:00 time: 0.128340 data_time: 0.073509 memory: 772 2022/10/13 20:42:31 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 20:42:45 - mmengine - INFO - Epoch(val) [50][407/407] coco/AP: 0.594974 coco/AP .5: 0.852633 coco/AP .75: 0.653358 coco/AP (M): 0.553813 coco/AP (L): 0.664058 coco/AR: 0.658863 coco/AR .5: 0.895781 coco/AR .75: 0.718986 coco/AR (M): 0.609970 coco/AR (L): 0.727536 2022/10/13 20:42:45 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_40.pth is removed 2022/10/13 20:42:47 - mmengine - INFO - The best checkpoint with 0.5950 coco/AP at 50 epoch is saved to best_coco/AP_epoch_50.pth. 2022/10/13 20:43:05 - mmengine - INFO - Epoch(train) [51][50/293] lr: 5.000000e-04 eta: 4:11:42 time: 0.366380 data_time: 0.155274 memory: 4980 loss_kpt: 0.000905 acc_pose: 0.728536 loss: 0.000905 2022/10/13 20:43:23 - mmengine - INFO - Epoch(train) [51][100/293] lr: 5.000000e-04 eta: 4:11:31 time: 0.357703 data_time: 0.100079 memory: 4980 loss_kpt: 0.000918 acc_pose: 0.745954 loss: 0.000918 2022/10/13 20:43:41 - mmengine - INFO - Epoch(train) [51][150/293] lr: 5.000000e-04 eta: 4:11:23 time: 0.370534 data_time: 0.080902 memory: 4980 loss_kpt: 0.000921 acc_pose: 0.734218 loss: 0.000921 2022/10/13 20:44:00 - mmengine - INFO - Epoch(train) [51][200/293] lr: 5.000000e-04 eta: 4:11:13 time: 0.365410 data_time: 0.080958 memory: 4980 loss_kpt: 0.000908 acc_pose: 0.751694 loss: 0.000908 2022/10/13 20:44:17 - mmengine - INFO - Epoch(train) [51][250/293] lr: 5.000000e-04 eta: 4:11:03 time: 0.356539 data_time: 0.075481 memory: 4980 loss_kpt: 0.000904 acc_pose: 0.731757 loss: 0.000904 2022/10/13 20:44:33 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:44:52 - mmengine - INFO - Epoch(train) [52][50/293] lr: 5.000000e-04 eta: 4:09:58 time: 0.375536 data_time: 0.083735 memory: 4980 loss_kpt: 0.000918 acc_pose: 0.743013 loss: 0.000918 2022/10/13 20:44:55 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:45:10 - mmengine - INFO - Epoch(train) [52][100/293] lr: 5.000000e-04 eta: 4:09:47 time: 0.359418 data_time: 0.075374 memory: 4980 loss_kpt: 0.000901 acc_pose: 0.705855 loss: 0.000901 2022/10/13 20:45:28 - mmengine - INFO - Epoch(train) [52][150/293] lr: 5.000000e-04 eta: 4:09:37 time: 0.360863 data_time: 0.079392 memory: 4980 loss_kpt: 0.000905 acc_pose: 0.681191 loss: 0.000905 2022/10/13 20:45:46 - mmengine - INFO - Epoch(train) [52][200/293] lr: 5.000000e-04 eta: 4:09:27 time: 0.362104 data_time: 0.076376 memory: 4980 loss_kpt: 0.000899 acc_pose: 0.728301 loss: 0.000899 2022/10/13 20:46:05 - mmengine - INFO - Epoch(train) [52][250/293] lr: 5.000000e-04 eta: 4:09:19 time: 0.376759 data_time: 0.098205 memory: 4980 loss_kpt: 0.000925 acc_pose: 0.697897 loss: 0.000925 2022/10/13 20:46:20 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:46:39 - mmengine - INFO - Epoch(train) [53][50/293] lr: 5.000000e-04 eta: 4:08:15 time: 0.377047 data_time: 0.094200 memory: 4980 loss_kpt: 0.000923 acc_pose: 0.732754 loss: 0.000923 2022/10/13 20:46:57 - mmengine - INFO - Epoch(train) [53][100/293] lr: 5.000000e-04 eta: 4:08:05 time: 0.363106 data_time: 0.072311 memory: 4980 loss_kpt: 0.000895 acc_pose: 0.731605 loss: 0.000895 2022/10/13 20:47:15 - mmengine - INFO - Epoch(train) [53][150/293] lr: 5.000000e-04 eta: 4:07:55 time: 0.361242 data_time: 0.083521 memory: 4980 loss_kpt: 0.000894 acc_pose: 0.731795 loss: 0.000894 2022/10/13 20:47:33 - mmengine - INFO - Epoch(train) [53][200/293] lr: 5.000000e-04 eta: 4:07:45 time: 0.360626 data_time: 0.079844 memory: 4980 loss_kpt: 0.000897 acc_pose: 0.749474 loss: 0.000897 2022/10/13 20:47:52 - mmengine - INFO - Epoch(train) [53][250/293] lr: 5.000000e-04 eta: 4:07:35 time: 0.363654 data_time: 0.073989 memory: 4980 loss_kpt: 0.000933 acc_pose: 0.736426 loss: 0.000933 2022/10/13 20:48:07 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:48:26 - mmengine - INFO - Epoch(train) [54][50/293] lr: 5.000000e-04 eta: 4:06:33 time: 0.386556 data_time: 0.104433 memory: 4980 loss_kpt: 0.000905 acc_pose: 0.770889 loss: 0.000905 2022/10/13 20:48:44 - mmengine - INFO - Epoch(train) [54][100/293] lr: 5.000000e-04 eta: 4:06:23 time: 0.363608 data_time: 0.091368 memory: 4980 loss_kpt: 0.000899 acc_pose: 0.703519 loss: 0.000899 2022/10/13 20:49:02 - mmengine - INFO - Epoch(train) [54][150/293] lr: 5.000000e-04 eta: 4:06:12 time: 0.353119 data_time: 0.071270 memory: 4980 loss_kpt: 0.000893 acc_pose: 0.728764 loss: 0.000893 2022/10/13 20:49:20 - mmengine - INFO - Epoch(train) [54][200/293] lr: 5.000000e-04 eta: 4:06:00 time: 0.353547 data_time: 0.079919 memory: 4980 loss_kpt: 0.000896 acc_pose: 0.685250 loss: 0.000896 2022/10/13 20:49:37 - mmengine - INFO - Epoch(train) [54][250/293] lr: 5.000000e-04 eta: 4:05:49 time: 0.357977 data_time: 0.080013 memory: 4980 loss_kpt: 0.000897 acc_pose: 0.752692 loss: 0.000897 2022/10/13 20:49:53 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:50:12 - mmengine - INFO - Epoch(train) [55][50/293] lr: 5.000000e-04 eta: 4:04:48 time: 0.382063 data_time: 0.087076 memory: 4980 loss_kpt: 0.000916 acc_pose: 0.747845 loss: 0.000916 2022/10/13 20:50:30 - mmengine - INFO - Epoch(train) [55][100/293] lr: 5.000000e-04 eta: 4:04:36 time: 0.353910 data_time: 0.067672 memory: 4980 loss_kpt: 0.000899 acc_pose: 0.722960 loss: 0.000899 2022/10/13 20:50:48 - mmengine - INFO - Epoch(train) [55][150/293] lr: 5.000000e-04 eta: 4:04:26 time: 0.361848 data_time: 0.079727 memory: 4980 loss_kpt: 0.000920 acc_pose: 0.628474 loss: 0.000920 2022/10/13 20:50:58 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:51:06 - mmengine - INFO - Epoch(train) [55][200/293] lr: 5.000000e-04 eta: 4:04:16 time: 0.363046 data_time: 0.082633 memory: 4980 loss_kpt: 0.000904 acc_pose: 0.703582 loss: 0.000904 2022/10/13 20:51:24 - mmengine - INFO - Epoch(train) [55][250/293] lr: 5.000000e-04 eta: 4:04:05 time: 0.360621 data_time: 0.075926 memory: 4980 loss_kpt: 0.000909 acc_pose: 0.706677 loss: 0.000909 2022/10/13 20:51:39 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:51:58 - mmengine - INFO - Epoch(train) [56][50/293] lr: 5.000000e-04 eta: 4:03:03 time: 0.372664 data_time: 0.091201 memory: 4980 loss_kpt: 0.000904 acc_pose: 0.706150 loss: 0.000904 2022/10/13 20:52:16 - mmengine - INFO - Epoch(train) [56][100/293] lr: 5.000000e-04 eta: 4:02:53 time: 0.359980 data_time: 0.072192 memory: 4980 loss_kpt: 0.000900 acc_pose: 0.748853 loss: 0.000900 2022/10/13 20:52:34 - mmengine - INFO - Epoch(train) [56][150/293] lr: 5.000000e-04 eta: 4:02:42 time: 0.360463 data_time: 0.078533 memory: 4980 loss_kpt: 0.000914 acc_pose: 0.678070 loss: 0.000914 2022/10/13 20:52:51 - mmengine - INFO - Epoch(train) [56][200/293] lr: 5.000000e-04 eta: 4:02:30 time: 0.354202 data_time: 0.067307 memory: 4980 loss_kpt: 0.000914 acc_pose: 0.665626 loss: 0.000914 2022/10/13 20:53:10 - mmengine - INFO - Epoch(train) [56][250/293] lr: 5.000000e-04 eta: 4:02:20 time: 0.366417 data_time: 0.073250 memory: 4980 loss_kpt: 0.000892 acc_pose: 0.745008 loss: 0.000892 2022/10/13 20:53:25 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:53:44 - mmengine - INFO - Epoch(train) [57][50/293] lr: 5.000000e-04 eta: 4:01:20 time: 0.378763 data_time: 0.075790 memory: 4980 loss_kpt: 0.000901 acc_pose: 0.694138 loss: 0.000901 2022/10/13 20:54:01 - mmengine - INFO - Epoch(train) [57][100/293] lr: 5.000000e-04 eta: 4:01:09 time: 0.353094 data_time: 0.067783 memory: 4980 loss_kpt: 0.000903 acc_pose: 0.744781 loss: 0.000903 2022/10/13 20:54:20 - mmengine - INFO - Epoch(train) [57][150/293] lr: 5.000000e-04 eta: 4:00:59 time: 0.365354 data_time: 0.080334 memory: 4980 loss_kpt: 0.000907 acc_pose: 0.720214 loss: 0.000907 2022/10/13 20:54:38 - mmengine - INFO - Epoch(train) [57][200/293] lr: 5.000000e-04 eta: 4:00:50 time: 0.374092 data_time: 0.076346 memory: 4980 loss_kpt: 0.000908 acc_pose: 0.693990 loss: 0.000908 2022/10/13 20:54:57 - mmengine - INFO - Epoch(train) [57][250/293] lr: 5.000000e-04 eta: 4:00:39 time: 0.364054 data_time: 0.088549 memory: 4980 loss_kpt: 0.000906 acc_pose: 0.693357 loss: 0.000906 2022/10/13 20:55:12 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:55:30 - mmengine - INFO - Epoch(train) [58][50/293] lr: 5.000000e-04 eta: 3:59:39 time: 0.370614 data_time: 0.095188 memory: 4980 loss_kpt: 0.000912 acc_pose: 0.750430 loss: 0.000912 2022/10/13 20:55:48 - mmengine - INFO - Epoch(train) [58][100/293] lr: 5.000000e-04 eta: 3:59:29 time: 0.364944 data_time: 0.077842 memory: 4980 loss_kpt: 0.000884 acc_pose: 0.693710 loss: 0.000884 2022/10/13 20:56:06 - mmengine - INFO - Epoch(train) [58][150/293] lr: 5.000000e-04 eta: 3:59:17 time: 0.356140 data_time: 0.063520 memory: 4980 loss_kpt: 0.000902 acc_pose: 0.688735 loss: 0.000902 2022/10/13 20:56:25 - mmengine - INFO - Epoch(train) [58][200/293] lr: 5.000000e-04 eta: 3:59:09 time: 0.379594 data_time: 0.089443 memory: 4980 loss_kpt: 0.000899 acc_pose: 0.721471 loss: 0.000899 2022/10/13 20:56:43 - mmengine - INFO - Epoch(train) [58][250/293] lr: 5.000000e-04 eta: 3:58:58 time: 0.358274 data_time: 0.062503 memory: 4980 loss_kpt: 0.000895 acc_pose: 0.696273 loss: 0.000895 2022/10/13 20:56:59 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:57:02 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:57:17 - mmengine - INFO - Epoch(train) [59][50/293] lr: 5.000000e-04 eta: 3:57:58 time: 0.373281 data_time: 0.092708 memory: 4980 loss_kpt: 0.000895 acc_pose: 0.691968 loss: 0.000895 2022/10/13 20:57:35 - mmengine - INFO - Epoch(train) [59][100/293] lr: 5.000000e-04 eta: 3:57:47 time: 0.356226 data_time: 0.074561 memory: 4980 loss_kpt: 0.000891 acc_pose: 0.688974 loss: 0.000891 2022/10/13 20:57:53 - mmengine - INFO - Epoch(train) [59][150/293] lr: 5.000000e-04 eta: 3:57:36 time: 0.358729 data_time: 0.079577 memory: 4980 loss_kpt: 0.000896 acc_pose: 0.742258 loss: 0.000896 2022/10/13 20:58:11 - mmengine - INFO - Epoch(train) [59][200/293] lr: 5.000000e-04 eta: 3:57:25 time: 0.359781 data_time: 0.068694 memory: 4980 loss_kpt: 0.000896 acc_pose: 0.779230 loss: 0.000896 2022/10/13 20:58:29 - mmengine - INFO - Epoch(train) [59][250/293] lr: 5.000000e-04 eta: 3:57:15 time: 0.368869 data_time: 0.078400 memory: 4980 loss_kpt: 0.000895 acc_pose: 0.748820 loss: 0.000895 2022/10/13 20:58:44 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 20:59:03 - mmengine - INFO - Epoch(train) [60][50/293] lr: 5.000000e-04 eta: 3:56:16 time: 0.371515 data_time: 0.123321 memory: 4980 loss_kpt: 0.000883 acc_pose: 0.682741 loss: 0.000883 2022/10/13 20:59:21 - mmengine - INFO - Epoch(train) [60][100/293] lr: 5.000000e-04 eta: 3:56:04 time: 0.352558 data_time: 0.067983 memory: 4980 loss_kpt: 0.000894 acc_pose: 0.705478 loss: 0.000894 2022/10/13 20:59:39 - mmengine - INFO - Epoch(train) [60][150/293] lr: 5.000000e-04 eta: 3:55:53 time: 0.363378 data_time: 0.093285 memory: 4980 loss_kpt: 0.000891 acc_pose: 0.657055 loss: 0.000891 2022/10/13 20:59:57 - mmengine - INFO - Epoch(train) [60][200/293] lr: 5.000000e-04 eta: 3:55:42 time: 0.360060 data_time: 0.068256 memory: 4980 loss_kpt: 0.000902 acc_pose: 0.756192 loss: 0.000902 2022/10/13 21:00:15 - mmengine - INFO - Epoch(train) [60][250/293] lr: 5.000000e-04 eta: 3:55:30 time: 0.356468 data_time: 0.081039 memory: 4980 loss_kpt: 0.000905 acc_pose: 0.759033 loss: 0.000905 2022/10/13 21:00:30 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:00:30 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/10/13 21:00:38 - mmengine - INFO - Epoch(val) [60][50/407] eta: 0:00:44 time: 0.125705 data_time: 0.071125 memory: 4980 2022/10/13 21:00:44 - mmengine - INFO - Epoch(val) [60][100/407] eta: 0:00:37 time: 0.122616 data_time: 0.064577 memory: 772 2022/10/13 21:00:50 - mmengine - INFO - Epoch(val) [60][150/407] eta: 0:00:32 time: 0.125102 data_time: 0.069829 memory: 772 2022/10/13 21:00:57 - mmengine - INFO - Epoch(val) [60][200/407] eta: 0:00:25 time: 0.123220 data_time: 0.068573 memory: 772 2022/10/13 21:01:03 - mmengine - INFO - Epoch(val) [60][250/407] eta: 0:00:20 time: 0.130452 data_time: 0.074514 memory: 772 2022/10/13 21:01:09 - mmengine - INFO - Epoch(val) [60][300/407] eta: 0:00:12 time: 0.118444 data_time: 0.063038 memory: 772 2022/10/13 21:01:15 - mmengine - INFO - Epoch(val) [60][350/407] eta: 0:00:07 time: 0.124308 data_time: 0.069689 memory: 772 2022/10/13 21:01:21 - mmengine - INFO - Epoch(val) [60][400/407] eta: 0:00:00 time: 0.124739 data_time: 0.071844 memory: 772 2022/10/13 21:01:59 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 21:02:12 - mmengine - INFO - Epoch(val) [60][407/407] coco/AP: 0.597756 coco/AP .5: 0.849209 coco/AP .75: 0.658384 coco/AP (M): 0.557322 coco/AP (L): 0.666963 coco/AR: 0.660548 coco/AR .5: 0.891845 coco/AR .75: 0.722764 coco/AR (M): 0.612374 coco/AR (L): 0.727982 2022/10/13 21:02:12 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_50.pth is removed 2022/10/13 21:02:14 - mmengine - INFO - The best checkpoint with 0.5978 coco/AP at 60 epoch is saved to best_coco/AP_epoch_60.pth. 2022/10/13 21:02:32 - mmengine - INFO - Epoch(train) [61][50/293] lr: 5.000000e-04 eta: 3:54:31 time: 0.359931 data_time: 0.121377 memory: 4980 loss_kpt: 0.000898 acc_pose: 0.728483 loss: 0.000898 2022/10/13 21:02:51 - mmengine - INFO - Epoch(train) [61][100/293] lr: 5.000000e-04 eta: 3:54:21 time: 0.373541 data_time: 0.086697 memory: 4980 loss_kpt: 0.000893 acc_pose: 0.674552 loss: 0.000893 2022/10/13 21:03:09 - mmengine - INFO - Epoch(train) [61][150/293] lr: 5.000000e-04 eta: 3:54:12 time: 0.374305 data_time: 0.077239 memory: 4980 loss_kpt: 0.000894 acc_pose: 0.685266 loss: 0.000894 2022/10/13 21:03:27 - mmengine - INFO - Epoch(train) [61][200/293] lr: 5.000000e-04 eta: 3:54:01 time: 0.359202 data_time: 0.070058 memory: 4980 loss_kpt: 0.000890 acc_pose: 0.679712 loss: 0.000890 2022/10/13 21:03:46 - mmengine - INFO - Epoch(train) [61][250/293] lr: 5.000000e-04 eta: 3:53:50 time: 0.361138 data_time: 0.068051 memory: 4980 loss_kpt: 0.000903 acc_pose: 0.748170 loss: 0.000903 2022/10/13 21:04:01 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:04:20 - mmengine - INFO - Epoch(train) [62][50/293] lr: 5.000000e-04 eta: 3:52:54 time: 0.386445 data_time: 0.117357 memory: 4980 loss_kpt: 0.000891 acc_pose: 0.703306 loss: 0.000891 2022/10/13 21:04:38 - mmengine - INFO - Epoch(train) [62][100/293] lr: 5.000000e-04 eta: 3:52:43 time: 0.359924 data_time: 0.069675 memory: 4980 loss_kpt: 0.000907 acc_pose: 0.777065 loss: 0.000907 2022/10/13 21:04:48 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:04:56 - mmengine - INFO - Epoch(train) [62][150/293] lr: 5.000000e-04 eta: 3:52:32 time: 0.363536 data_time: 0.080675 memory: 4980 loss_kpt: 0.000890 acc_pose: 0.752210 loss: 0.000890 2022/10/13 21:05:14 - mmengine - INFO - Epoch(train) [62][200/293] lr: 5.000000e-04 eta: 3:52:20 time: 0.354784 data_time: 0.080744 memory: 4980 loss_kpt: 0.000889 acc_pose: 0.721528 loss: 0.000889 2022/10/13 21:05:33 - mmengine - INFO - Epoch(train) [62][250/293] lr: 5.000000e-04 eta: 3:52:10 time: 0.369925 data_time: 0.076104 memory: 4980 loss_kpt: 0.000909 acc_pose: 0.747394 loss: 0.000909 2022/10/13 21:05:48 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:06:07 - mmengine - INFO - Epoch(train) [63][50/293] lr: 5.000000e-04 eta: 3:51:14 time: 0.373909 data_time: 0.091525 memory: 4980 loss_kpt: 0.000876 acc_pose: 0.749945 loss: 0.000876 2022/10/13 21:06:25 - mmengine - INFO - Epoch(train) [63][100/293] lr: 5.000000e-04 eta: 3:51:02 time: 0.361182 data_time: 0.076795 memory: 4980 loss_kpt: 0.000884 acc_pose: 0.738406 loss: 0.000884 2022/10/13 21:06:43 - mmengine - INFO - Epoch(train) [63][150/293] lr: 5.000000e-04 eta: 3:50:51 time: 0.358086 data_time: 0.068863 memory: 4980 loss_kpt: 0.000885 acc_pose: 0.738417 loss: 0.000885 2022/10/13 21:07:01 - mmengine - INFO - Epoch(train) [63][200/293] lr: 5.000000e-04 eta: 3:50:39 time: 0.354673 data_time: 0.071033 memory: 4980 loss_kpt: 0.000895 acc_pose: 0.709784 loss: 0.000895 2022/10/13 21:07:19 - mmengine - INFO - Epoch(train) [63][250/293] lr: 5.000000e-04 eta: 3:50:28 time: 0.366399 data_time: 0.075740 memory: 4980 loss_kpt: 0.000901 acc_pose: 0.706591 loss: 0.000901 2022/10/13 21:07:34 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:07:53 - mmengine - INFO - Epoch(train) [64][50/293] lr: 5.000000e-04 eta: 3:49:32 time: 0.373654 data_time: 0.081129 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.722843 loss: 0.000870 2022/10/13 21:08:11 - mmengine - INFO - Epoch(train) [64][100/293] lr: 5.000000e-04 eta: 3:49:21 time: 0.361069 data_time: 0.070070 memory: 4980 loss_kpt: 0.000889 acc_pose: 0.697292 loss: 0.000889 2022/10/13 21:08:29 - mmengine - INFO - Epoch(train) [64][150/293] lr: 5.000000e-04 eta: 3:49:11 time: 0.367732 data_time: 0.078229 memory: 4980 loss_kpt: 0.000888 acc_pose: 0.696652 loss: 0.000888 2022/10/13 21:08:47 - mmengine - INFO - Epoch(train) [64][200/293] lr: 5.000000e-04 eta: 3:48:59 time: 0.355567 data_time: 0.063021 memory: 4980 loss_kpt: 0.000884 acc_pose: 0.703149 loss: 0.000884 2022/10/13 21:09:05 - mmengine - INFO - Epoch(train) [64][250/293] lr: 5.000000e-04 eta: 3:48:48 time: 0.366457 data_time: 0.073791 memory: 4980 loss_kpt: 0.000915 acc_pose: 0.733381 loss: 0.000915 2022/10/13 21:09:21 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:09:39 - mmengine - INFO - Epoch(train) [65][50/293] lr: 5.000000e-04 eta: 3:47:53 time: 0.374815 data_time: 0.095255 memory: 4980 loss_kpt: 0.000883 acc_pose: 0.744001 loss: 0.000883 2022/10/13 21:09:57 - mmengine - INFO - Epoch(train) [65][100/293] lr: 5.000000e-04 eta: 3:47:41 time: 0.357792 data_time: 0.076695 memory: 4980 loss_kpt: 0.000893 acc_pose: 0.715524 loss: 0.000893 2022/10/13 21:10:15 - mmengine - INFO - Epoch(train) [65][150/293] lr: 5.000000e-04 eta: 3:47:29 time: 0.354416 data_time: 0.069391 memory: 4980 loss_kpt: 0.000898 acc_pose: 0.696346 loss: 0.000898 2022/10/13 21:10:33 - mmengine - INFO - Epoch(train) [65][200/293] lr: 5.000000e-04 eta: 3:47:18 time: 0.364325 data_time: 0.075392 memory: 4980 loss_kpt: 0.000893 acc_pose: 0.723781 loss: 0.000893 2022/10/13 21:10:51 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:10:52 - mmengine - INFO - Epoch(train) [65][250/293] lr: 5.000000e-04 eta: 3:47:08 time: 0.372936 data_time: 0.085764 memory: 4980 loss_kpt: 0.000899 acc_pose: 0.695921 loss: 0.000899 2022/10/13 21:11:07 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:11:26 - mmengine - INFO - Epoch(train) [66][50/293] lr: 5.000000e-04 eta: 3:46:14 time: 0.376469 data_time: 0.113056 memory: 4980 loss_kpt: 0.000891 acc_pose: 0.780338 loss: 0.000891 2022/10/13 21:11:45 - mmengine - INFO - Epoch(train) [66][100/293] lr: 5.000000e-04 eta: 3:46:03 time: 0.365358 data_time: 0.072340 memory: 4980 loss_kpt: 0.000892 acc_pose: 0.677344 loss: 0.000892 2022/10/13 21:12:03 - mmengine - INFO - Epoch(train) [66][150/293] lr: 5.000000e-04 eta: 3:45:52 time: 0.367086 data_time: 0.087508 memory: 4980 loss_kpt: 0.000886 acc_pose: 0.779338 loss: 0.000886 2022/10/13 21:12:21 - mmengine - INFO - Epoch(train) [66][200/293] lr: 5.000000e-04 eta: 3:45:41 time: 0.362509 data_time: 0.080621 memory: 4980 loss_kpt: 0.000893 acc_pose: 0.689097 loss: 0.000893 2022/10/13 21:12:40 - mmengine - INFO - Epoch(train) [66][250/293] lr: 5.000000e-04 eta: 3:45:31 time: 0.376802 data_time: 0.075199 memory: 4980 loss_kpt: 0.000888 acc_pose: 0.751493 loss: 0.000888 2022/10/13 21:12:55 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:13:15 - mmengine - INFO - Epoch(train) [67][50/293] lr: 5.000000e-04 eta: 3:44:38 time: 0.385730 data_time: 0.113292 memory: 4980 loss_kpt: 0.000892 acc_pose: 0.721491 loss: 0.000892 2022/10/13 21:13:33 - mmengine - INFO - Epoch(train) [67][100/293] lr: 5.000000e-04 eta: 3:44:27 time: 0.361677 data_time: 0.073113 memory: 4980 loss_kpt: 0.000887 acc_pose: 0.685189 loss: 0.000887 2022/10/13 21:13:51 - mmengine - INFO - Epoch(train) [67][150/293] lr: 5.000000e-04 eta: 3:44:15 time: 0.363573 data_time: 0.076481 memory: 4980 loss_kpt: 0.000880 acc_pose: 0.695147 loss: 0.000880 2022/10/13 21:14:09 - mmengine - INFO - Epoch(train) [67][200/293] lr: 5.000000e-04 eta: 3:44:05 time: 0.371195 data_time: 0.072155 memory: 4980 loss_kpt: 0.000879 acc_pose: 0.722866 loss: 0.000879 2022/10/13 21:14:28 - mmengine - INFO - Epoch(train) [67][250/293] lr: 5.000000e-04 eta: 3:43:54 time: 0.365658 data_time: 0.074544 memory: 4980 loss_kpt: 0.000877 acc_pose: 0.660660 loss: 0.000877 2022/10/13 21:14:43 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:15:02 - mmengine - INFO - Epoch(train) [68][50/293] lr: 5.000000e-04 eta: 3:43:01 time: 0.377863 data_time: 0.096402 memory: 4980 loss_kpt: 0.000874 acc_pose: 0.812439 loss: 0.000874 2022/10/13 21:15:20 - mmengine - INFO - Epoch(train) [68][100/293] lr: 5.000000e-04 eta: 3:42:49 time: 0.364540 data_time: 0.132230 memory: 4980 loss_kpt: 0.000895 acc_pose: 0.775851 loss: 0.000895 2022/10/13 21:15:38 - mmengine - INFO - Epoch(train) [68][150/293] lr: 5.000000e-04 eta: 3:42:38 time: 0.358989 data_time: 0.128827 memory: 4980 loss_kpt: 0.000865 acc_pose: 0.718448 loss: 0.000865 2022/10/13 21:15:57 - mmengine - INFO - Epoch(train) [68][200/293] lr: 5.000000e-04 eta: 3:42:26 time: 0.364849 data_time: 0.126752 memory: 4980 loss_kpt: 0.000876 acc_pose: 0.752429 loss: 0.000876 2022/10/13 21:16:15 - mmengine - INFO - Epoch(train) [68][250/293] lr: 5.000000e-04 eta: 3:42:14 time: 0.357841 data_time: 0.098366 memory: 4980 loss_kpt: 0.000881 acc_pose: 0.717130 loss: 0.000881 2022/10/13 21:16:30 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:16:49 - mmengine - INFO - Epoch(train) [69][50/293] lr: 5.000000e-04 eta: 3:41:22 time: 0.378943 data_time: 0.091776 memory: 4980 loss_kpt: 0.000874 acc_pose: 0.757322 loss: 0.000874 2022/10/13 21:16:58 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:17:06 - mmengine - INFO - Epoch(train) [69][100/293] lr: 5.000000e-04 eta: 3:41:10 time: 0.354034 data_time: 0.068443 memory: 4980 loss_kpt: 0.000885 acc_pose: 0.721582 loss: 0.000885 2022/10/13 21:17:25 - mmengine - INFO - Epoch(train) [69][150/293] lr: 5.000000e-04 eta: 3:40:58 time: 0.363267 data_time: 0.076188 memory: 4980 loss_kpt: 0.000880 acc_pose: 0.727483 loss: 0.000880 2022/10/13 21:17:43 - mmengine - INFO - Epoch(train) [69][200/293] lr: 5.000000e-04 eta: 3:40:46 time: 0.359384 data_time: 0.072823 memory: 4980 loss_kpt: 0.000895 acc_pose: 0.636582 loss: 0.000895 2022/10/13 21:18:01 - mmengine - INFO - Epoch(train) [69][250/293] lr: 5.000000e-04 eta: 3:40:35 time: 0.365189 data_time: 0.072056 memory: 4980 loss_kpt: 0.000880 acc_pose: 0.688487 loss: 0.000880 2022/10/13 21:18:16 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:18:36 - mmengine - INFO - Epoch(train) [70][50/293] lr: 5.000000e-04 eta: 3:39:43 time: 0.382604 data_time: 0.098459 memory: 4980 loss_kpt: 0.000902 acc_pose: 0.676594 loss: 0.000902 2022/10/13 21:18:54 - mmengine - INFO - Epoch(train) [70][100/293] lr: 5.000000e-04 eta: 3:39:33 time: 0.377544 data_time: 0.076733 memory: 4980 loss_kpt: 0.000886 acc_pose: 0.654605 loss: 0.000886 2022/10/13 21:19:13 - mmengine - INFO - Epoch(train) [70][150/293] lr: 5.000000e-04 eta: 3:39:22 time: 0.361591 data_time: 0.083308 memory: 4980 loss_kpt: 0.000885 acc_pose: 0.712794 loss: 0.000885 2022/10/13 21:19:30 - mmengine - INFO - Epoch(train) [70][200/293] lr: 5.000000e-04 eta: 3:39:09 time: 0.357447 data_time: 0.074922 memory: 4980 loss_kpt: 0.000885 acc_pose: 0.709898 loss: 0.000885 2022/10/13 21:19:49 - mmengine - INFO - Epoch(train) [70][250/293] lr: 5.000000e-04 eta: 3:38:58 time: 0.361932 data_time: 0.076324 memory: 4980 loss_kpt: 0.000891 acc_pose: 0.754741 loss: 0.000891 2022/10/13 21:20:04 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:20:04 - mmengine - INFO - Saving checkpoint at 70 epochs 2022/10/13 21:20:12 - mmengine - INFO - Epoch(val) [70][50/407] eta: 0:00:48 time: 0.135147 data_time: 0.077808 memory: 4980 2022/10/13 21:20:19 - mmengine - INFO - Epoch(val) [70][100/407] eta: 0:00:38 time: 0.126305 data_time: 0.067162 memory: 772 2022/10/13 21:20:25 - mmengine - INFO - Epoch(val) [70][150/407] eta: 0:00:32 time: 0.127181 data_time: 0.072971 memory: 772 2022/10/13 21:20:31 - mmengine - INFO - Epoch(val) [70][200/407] eta: 0:00:26 time: 0.126372 data_time: 0.070015 memory: 772 2022/10/13 21:20:37 - mmengine - INFO - Epoch(val) [70][250/407] eta: 0:00:19 time: 0.122052 data_time: 0.065847 memory: 772 2022/10/13 21:20:44 - mmengine - INFO - Epoch(val) [70][300/407] eta: 0:00:13 time: 0.124260 data_time: 0.069031 memory: 772 2022/10/13 21:20:50 - mmengine - INFO - Epoch(val) [70][350/407] eta: 0:00:07 time: 0.125080 data_time: 0.068920 memory: 772 2022/10/13 21:20:56 - mmengine - INFO - Epoch(val) [70][400/407] eta: 0:00:00 time: 0.122713 data_time: 0.070731 memory: 772 2022/10/13 21:21:32 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 21:21:46 - mmengine - INFO - Epoch(val) [70][407/407] coco/AP: 0.603101 coco/AP .5: 0.850561 coco/AP .75: 0.662992 coco/AP (M): 0.562304 coco/AP (L): 0.673837 coco/AR: 0.665712 coco/AR .5: 0.894207 coco/AR .75: 0.726228 coco/AR (M): 0.616007 coco/AR (L): 0.735340 2022/10/13 21:21:46 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_60.pth is removed 2022/10/13 21:21:48 - mmengine - INFO - The best checkpoint with 0.6031 coco/AP at 70 epoch is saved to best_coco/AP_epoch_70.pth. 2022/10/13 21:22:06 - mmengine - INFO - Epoch(train) [71][50/293] lr: 5.000000e-04 eta: 3:38:06 time: 0.371300 data_time: 0.136543 memory: 4980 loss_kpt: 0.000886 acc_pose: 0.741296 loss: 0.000886 2022/10/13 21:22:25 - mmengine - INFO - Epoch(train) [71][100/293] lr: 5.000000e-04 eta: 3:37:54 time: 0.364956 data_time: 0.107513 memory: 4980 loss_kpt: 0.000906 acc_pose: 0.699785 loss: 0.000906 2022/10/13 21:22:43 - mmengine - INFO - Epoch(train) [71][150/293] lr: 5.000000e-04 eta: 3:37:43 time: 0.367573 data_time: 0.104045 memory: 4980 loss_kpt: 0.000880 acc_pose: 0.737597 loss: 0.000880 2022/10/13 21:23:01 - mmengine - INFO - Epoch(train) [71][200/293] lr: 5.000000e-04 eta: 3:37:30 time: 0.354873 data_time: 0.071161 memory: 4980 loss_kpt: 0.000889 acc_pose: 0.707131 loss: 0.000889 2022/10/13 21:23:19 - mmengine - INFO - Epoch(train) [71][250/293] lr: 5.000000e-04 eta: 3:37:19 time: 0.363855 data_time: 0.075658 memory: 4980 loss_kpt: 0.000877 acc_pose: 0.754185 loss: 0.000877 2022/10/13 21:23:34 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:23:53 - mmengine - INFO - Epoch(train) [72][50/293] lr: 5.000000e-04 eta: 3:36:28 time: 0.384164 data_time: 0.123228 memory: 4980 loss_kpt: 0.000875 acc_pose: 0.673693 loss: 0.000875 2022/10/13 21:24:11 - mmengine - INFO - Epoch(train) [72][100/293] lr: 5.000000e-04 eta: 3:36:16 time: 0.356784 data_time: 0.093185 memory: 4980 loss_kpt: 0.000895 acc_pose: 0.707188 loss: 0.000895 2022/10/13 21:24:30 - mmengine - INFO - Epoch(train) [72][150/293] lr: 5.000000e-04 eta: 3:36:05 time: 0.365313 data_time: 0.083343 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.692467 loss: 0.000870 2022/10/13 21:24:47 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:24:48 - mmengine - INFO - Epoch(train) [72][200/293] lr: 5.000000e-04 eta: 3:35:54 time: 0.370822 data_time: 0.076608 memory: 4980 loss_kpt: 0.000878 acc_pose: 0.745354 loss: 0.000878 2022/10/13 21:25:06 - mmengine - INFO - Epoch(train) [72][250/293] lr: 5.000000e-04 eta: 3:35:42 time: 0.362572 data_time: 0.073784 memory: 4980 loss_kpt: 0.000880 acc_pose: 0.714887 loss: 0.000880 2022/10/13 21:25:22 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:25:40 - mmengine - INFO - Epoch(train) [73][50/293] lr: 5.000000e-04 eta: 3:34:51 time: 0.374671 data_time: 0.086455 memory: 4980 loss_kpt: 0.000888 acc_pose: 0.729482 loss: 0.000888 2022/10/13 21:25:59 - mmengine - INFO - Epoch(train) [73][100/293] lr: 5.000000e-04 eta: 3:34:40 time: 0.374320 data_time: 0.077024 memory: 4980 loss_kpt: 0.000871 acc_pose: 0.777644 loss: 0.000871 2022/10/13 21:26:17 - mmengine - INFO - Epoch(train) [73][150/293] lr: 5.000000e-04 eta: 3:34:29 time: 0.367483 data_time: 0.077611 memory: 4980 loss_kpt: 0.000891 acc_pose: 0.728285 loss: 0.000891 2022/10/13 21:26:35 - mmengine - INFO - Epoch(train) [73][200/293] lr: 5.000000e-04 eta: 3:34:17 time: 0.358870 data_time: 0.088999 memory: 4980 loss_kpt: 0.000881 acc_pose: 0.708653 loss: 0.000881 2022/10/13 21:26:54 - mmengine - INFO - Epoch(train) [73][250/293] lr: 5.000000e-04 eta: 3:34:05 time: 0.367458 data_time: 0.068731 memory: 4980 loss_kpt: 0.000893 acc_pose: 0.740627 loss: 0.000893 2022/10/13 21:27:09 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:27:28 - mmengine - INFO - Epoch(train) [74][50/293] lr: 5.000000e-04 eta: 3:33:15 time: 0.375715 data_time: 0.089025 memory: 4980 loss_kpt: 0.000883 acc_pose: 0.700742 loss: 0.000883 2022/10/13 21:27:46 - mmengine - INFO - Epoch(train) [74][100/293] lr: 5.000000e-04 eta: 3:33:03 time: 0.367327 data_time: 0.085631 memory: 4980 loss_kpt: 0.000874 acc_pose: 0.717951 loss: 0.000874 2022/10/13 21:28:04 - mmengine - INFO - Epoch(train) [74][150/293] lr: 5.000000e-04 eta: 3:32:51 time: 0.361816 data_time: 0.068662 memory: 4980 loss_kpt: 0.000894 acc_pose: 0.701949 loss: 0.000894 2022/10/13 21:28:22 - mmengine - INFO - Epoch(train) [74][200/293] lr: 5.000000e-04 eta: 3:32:39 time: 0.359521 data_time: 0.081383 memory: 4980 loss_kpt: 0.000891 acc_pose: 0.724752 loss: 0.000891 2022/10/13 21:28:41 - mmengine - INFO - Epoch(train) [74][250/293] lr: 5.000000e-04 eta: 3:32:28 time: 0.368583 data_time: 0.077894 memory: 4980 loss_kpt: 0.000873 acc_pose: 0.777361 loss: 0.000873 2022/10/13 21:28:56 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:29:15 - mmengine - INFO - Epoch(train) [75][50/293] lr: 5.000000e-04 eta: 3:31:39 time: 0.384761 data_time: 0.100565 memory: 4980 loss_kpt: 0.000869 acc_pose: 0.697693 loss: 0.000869 2022/10/13 21:29:34 - mmengine - INFO - Epoch(train) [75][100/293] lr: 5.000000e-04 eta: 3:31:27 time: 0.366850 data_time: 0.080515 memory: 4980 loss_kpt: 0.000868 acc_pose: 0.752554 loss: 0.000868 2022/10/13 21:29:52 - mmengine - INFO - Epoch(train) [75][150/293] lr: 5.000000e-04 eta: 3:31:16 time: 0.366268 data_time: 0.075752 memory: 4980 loss_kpt: 0.000888 acc_pose: 0.731728 loss: 0.000888 2022/10/13 21:30:11 - mmengine - INFO - Epoch(train) [75][200/293] lr: 5.000000e-04 eta: 3:31:05 time: 0.379246 data_time: 0.086668 memory: 4980 loss_kpt: 0.000892 acc_pose: 0.731888 loss: 0.000892 2022/10/13 21:30:29 - mmengine - INFO - Epoch(train) [75][250/293] lr: 5.000000e-04 eta: 3:30:53 time: 0.362329 data_time: 0.077446 memory: 4980 loss_kpt: 0.000873 acc_pose: 0.669360 loss: 0.000873 2022/10/13 21:30:45 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:30:55 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:31:04 - mmengine - INFO - Epoch(train) [76][50/293] lr: 5.000000e-04 eta: 3:30:05 time: 0.393516 data_time: 0.090862 memory: 4980 loss_kpt: 0.000882 acc_pose: 0.704937 loss: 0.000882 2022/10/13 21:31:23 - mmengine - INFO - Epoch(train) [76][100/293] lr: 5.000000e-04 eta: 3:29:53 time: 0.364525 data_time: 0.072125 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.676766 loss: 0.000870 2022/10/13 21:31:41 - mmengine - INFO - Epoch(train) [76][150/293] lr: 5.000000e-04 eta: 3:29:41 time: 0.357988 data_time: 0.084640 memory: 4980 loss_kpt: 0.000876 acc_pose: 0.678655 loss: 0.000876 2022/10/13 21:31:59 - mmengine - INFO - Epoch(train) [76][200/293] lr: 5.000000e-04 eta: 3:29:29 time: 0.368106 data_time: 0.078831 memory: 4980 loss_kpt: 0.000873 acc_pose: 0.719710 loss: 0.000873 2022/10/13 21:32:17 - mmengine - INFO - Epoch(train) [76][250/293] lr: 5.000000e-04 eta: 3:29:17 time: 0.364133 data_time: 0.081972 memory: 4980 loss_kpt: 0.000886 acc_pose: 0.659777 loss: 0.000886 2022/10/13 21:32:32 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:32:51 - mmengine - INFO - Epoch(train) [77][50/293] lr: 5.000000e-04 eta: 3:28:28 time: 0.372069 data_time: 0.089987 memory: 4980 loss_kpt: 0.000874 acc_pose: 0.728925 loss: 0.000874 2022/10/13 21:33:10 - mmengine - INFO - Epoch(train) [77][100/293] lr: 5.000000e-04 eta: 3:28:17 time: 0.375991 data_time: 0.077419 memory: 4980 loss_kpt: 0.000885 acc_pose: 0.749959 loss: 0.000885 2022/10/13 21:33:28 - mmengine - INFO - Epoch(train) [77][150/293] lr: 5.000000e-04 eta: 3:28:04 time: 0.355808 data_time: 0.067446 memory: 4980 loss_kpt: 0.000885 acc_pose: 0.757518 loss: 0.000885 2022/10/13 21:33:46 - mmengine - INFO - Epoch(train) [77][200/293] lr: 5.000000e-04 eta: 3:27:52 time: 0.360415 data_time: 0.104543 memory: 4980 loss_kpt: 0.000873 acc_pose: 0.720386 loss: 0.000873 2022/10/13 21:34:04 - mmengine - INFO - Epoch(train) [77][250/293] lr: 5.000000e-04 eta: 3:27:40 time: 0.367894 data_time: 0.131355 memory: 4980 loss_kpt: 0.000874 acc_pose: 0.744829 loss: 0.000874 2022/10/13 21:34:19 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:34:38 - mmengine - INFO - Epoch(train) [78][50/293] lr: 5.000000e-04 eta: 3:26:52 time: 0.378882 data_time: 0.087015 memory: 4980 loss_kpt: 0.000873 acc_pose: 0.735292 loss: 0.000873 2022/10/13 21:34:57 - mmengine - INFO - Epoch(train) [78][100/293] lr: 5.000000e-04 eta: 3:26:40 time: 0.366758 data_time: 0.079705 memory: 4980 loss_kpt: 0.000891 acc_pose: 0.744242 loss: 0.000891 2022/10/13 21:35:15 - mmengine - INFO - Epoch(train) [78][150/293] lr: 5.000000e-04 eta: 3:26:28 time: 0.360101 data_time: 0.073278 memory: 4980 loss_kpt: 0.000866 acc_pose: 0.791550 loss: 0.000866 2022/10/13 21:35:32 - mmengine - INFO - Epoch(train) [78][200/293] lr: 5.000000e-04 eta: 3:26:15 time: 0.355969 data_time: 0.073827 memory: 4980 loss_kpt: 0.000895 acc_pose: 0.742314 loss: 0.000895 2022/10/13 21:35:51 - mmengine - INFO - Epoch(train) [78][250/293] lr: 5.000000e-04 eta: 3:26:04 time: 0.379373 data_time: 0.070342 memory: 4980 loss_kpt: 0.000881 acc_pose: 0.728640 loss: 0.000881 2022/10/13 21:36:07 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:36:26 - mmengine - INFO - Epoch(train) [79][50/293] lr: 5.000000e-04 eta: 3:25:16 time: 0.380753 data_time: 0.085796 memory: 4980 loss_kpt: 0.000879 acc_pose: 0.671171 loss: 0.000879 2022/10/13 21:36:44 - mmengine - INFO - Epoch(train) [79][100/293] lr: 5.000000e-04 eta: 3:25:04 time: 0.360804 data_time: 0.090471 memory: 4980 loss_kpt: 0.000879 acc_pose: 0.718878 loss: 0.000879 2022/10/13 21:37:00 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:37:01 - mmengine - INFO - Epoch(train) [79][150/293] lr: 5.000000e-04 eta: 3:24:50 time: 0.347657 data_time: 0.084164 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.722788 loss: 0.000870 2022/10/13 21:37:20 - mmengine - INFO - Epoch(train) [79][200/293] lr: 5.000000e-04 eta: 3:24:39 time: 0.376438 data_time: 0.079924 memory: 4980 loss_kpt: 0.000866 acc_pose: 0.706754 loss: 0.000866 2022/10/13 21:37:38 - mmengine - INFO - Epoch(train) [79][250/293] lr: 5.000000e-04 eta: 3:24:27 time: 0.365768 data_time: 0.077693 memory: 4980 loss_kpt: 0.000882 acc_pose: 0.731402 loss: 0.000882 2022/10/13 21:37:54 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:38:13 - mmengine - INFO - Epoch(train) [80][50/293] lr: 5.000000e-04 eta: 3:23:39 time: 0.373623 data_time: 0.123552 memory: 4980 loss_kpt: 0.000878 acc_pose: 0.641693 loss: 0.000878 2022/10/13 21:38:30 - mmengine - INFO - Epoch(train) [80][100/293] lr: 5.000000e-04 eta: 3:23:26 time: 0.350095 data_time: 0.072450 memory: 4980 loss_kpt: 0.000877 acc_pose: 0.742730 loss: 0.000877 2022/10/13 21:38:49 - mmengine - INFO - Epoch(train) [80][150/293] lr: 5.000000e-04 eta: 3:23:14 time: 0.373073 data_time: 0.077406 memory: 4980 loss_kpt: 0.000881 acc_pose: 0.723671 loss: 0.000881 2022/10/13 21:39:07 - mmengine - INFO - Epoch(train) [80][200/293] lr: 5.000000e-04 eta: 3:23:01 time: 0.358271 data_time: 0.077606 memory: 4980 loss_kpt: 0.000879 acc_pose: 0.754623 loss: 0.000879 2022/10/13 21:39:26 - mmengine - INFO - Epoch(train) [80][250/293] lr: 5.000000e-04 eta: 3:22:51 time: 0.381277 data_time: 0.084433 memory: 4980 loss_kpt: 0.000872 acc_pose: 0.767266 loss: 0.000872 2022/10/13 21:39:41 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:39:41 - mmengine - INFO - Saving checkpoint at 80 epochs 2022/10/13 21:39:49 - mmengine - INFO - Epoch(val) [80][50/407] eta: 0:00:46 time: 0.128854 data_time: 0.075129 memory: 4980 2022/10/13 21:39:56 - mmengine - INFO - Epoch(val) [80][100/407] eta: 0:00:38 time: 0.124314 data_time: 0.068427 memory: 772 2022/10/13 21:40:02 - mmengine - INFO - Epoch(val) [80][150/407] eta: 0:00:32 time: 0.125592 data_time: 0.067756 memory: 772 2022/10/13 21:40:08 - mmengine - INFO - Epoch(val) [80][200/407] eta: 0:00:25 time: 0.124285 data_time: 0.067229 memory: 772 2022/10/13 21:40:14 - mmengine - INFO - Epoch(val) [80][250/407] eta: 0:00:19 time: 0.124615 data_time: 0.068590 memory: 772 2022/10/13 21:40:21 - mmengine - INFO - Epoch(val) [80][300/407] eta: 0:00:13 time: 0.125423 data_time: 0.069741 memory: 772 2022/10/13 21:40:27 - mmengine - INFO - Epoch(val) [80][350/407] eta: 0:00:07 time: 0.133197 data_time: 0.076850 memory: 772 2022/10/13 21:40:33 - mmengine - INFO - Epoch(val) [80][400/407] eta: 0:00:00 time: 0.118091 data_time: 0.063985 memory: 772 2022/10/13 21:41:10 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 21:41:24 - mmengine - INFO - Epoch(val) [80][407/407] coco/AP: 0.605993 coco/AP .5: 0.853160 coco/AP .75: 0.664917 coco/AP (M): 0.565418 coco/AP (L): 0.675894 coco/AR: 0.669600 coco/AR .5: 0.898300 coco/AR .75: 0.727330 coco/AR (M): 0.620076 coco/AR (L): 0.738685 2022/10/13 21:41:24 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_70.pth is removed 2022/10/13 21:41:25 - mmengine - INFO - The best checkpoint with 0.6060 coco/AP at 80 epoch is saved to best_coco/AP_epoch_80.pth. 2022/10/13 21:41:44 - mmengine - INFO - Epoch(train) [81][50/293] lr: 5.000000e-04 eta: 3:22:03 time: 0.370601 data_time: 0.118185 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.737262 loss: 0.000864 2022/10/13 21:42:02 - mmengine - INFO - Epoch(train) [81][100/293] lr: 5.000000e-04 eta: 3:21:50 time: 0.362396 data_time: 0.078540 memory: 4980 loss_kpt: 0.000868 acc_pose: 0.715021 loss: 0.000868 2022/10/13 21:42:20 - mmengine - INFO - Epoch(train) [81][150/293] lr: 5.000000e-04 eta: 3:21:38 time: 0.367702 data_time: 0.071166 memory: 4980 loss_kpt: 0.000886 acc_pose: 0.730642 loss: 0.000886 2022/10/13 21:42:38 - mmengine - INFO - Epoch(train) [81][200/293] lr: 5.000000e-04 eta: 3:21:25 time: 0.352655 data_time: 0.112870 memory: 4980 loss_kpt: 0.000860 acc_pose: 0.597799 loss: 0.000860 2022/10/13 21:42:57 - mmengine - INFO - Epoch(train) [81][250/293] lr: 5.000000e-04 eta: 3:21:14 time: 0.380075 data_time: 0.077235 memory: 4980 loss_kpt: 0.000894 acc_pose: 0.694550 loss: 0.000894 2022/10/13 21:43:13 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:43:32 - mmengine - INFO - Epoch(train) [82][50/293] lr: 5.000000e-04 eta: 3:20:27 time: 0.372279 data_time: 0.089685 memory: 4980 loss_kpt: 0.000879 acc_pose: 0.677931 loss: 0.000879 2022/10/13 21:43:50 - mmengine - INFO - Epoch(train) [82][100/293] lr: 5.000000e-04 eta: 3:20:15 time: 0.369987 data_time: 0.089416 memory: 4980 loss_kpt: 0.000879 acc_pose: 0.721686 loss: 0.000879 2022/10/13 21:44:08 - mmengine - INFO - Epoch(train) [82][150/293] lr: 5.000000e-04 eta: 3:20:02 time: 0.355997 data_time: 0.092074 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.712829 loss: 0.000864 2022/10/13 21:44:27 - mmengine - INFO - Epoch(train) [82][200/293] lr: 5.000000e-04 eta: 3:19:50 time: 0.374291 data_time: 0.086840 memory: 4980 loss_kpt: 0.000869 acc_pose: 0.736309 loss: 0.000869 2022/10/13 21:44:45 - mmengine - INFO - Epoch(train) [82][250/293] lr: 5.000000e-04 eta: 3:19:38 time: 0.364066 data_time: 0.071427 memory: 4980 loss_kpt: 0.000879 acc_pose: 0.702961 loss: 0.000879 2022/10/13 21:44:51 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:45:00 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:45:19 - mmengine - INFO - Epoch(train) [83][50/293] lr: 5.000000e-04 eta: 3:18:51 time: 0.371251 data_time: 0.080295 memory: 4980 loss_kpt: 0.000874 acc_pose: 0.781162 loss: 0.000874 2022/10/13 21:45:38 - mmengine - INFO - Epoch(train) [83][100/293] lr: 5.000000e-04 eta: 3:18:39 time: 0.374110 data_time: 0.083112 memory: 4980 loss_kpt: 0.000876 acc_pose: 0.660699 loss: 0.000876 2022/10/13 21:45:56 - mmengine - INFO - Epoch(train) [83][150/293] lr: 5.000000e-04 eta: 3:18:27 time: 0.362240 data_time: 0.076823 memory: 4980 loss_kpt: 0.000867 acc_pose: 0.693274 loss: 0.000867 2022/10/13 21:46:14 - mmengine - INFO - Epoch(train) [83][200/293] lr: 5.000000e-04 eta: 3:18:14 time: 0.356946 data_time: 0.078859 memory: 4980 loss_kpt: 0.000874 acc_pose: 0.734359 loss: 0.000874 2022/10/13 21:46:32 - mmengine - INFO - Epoch(train) [83][250/293] lr: 5.000000e-04 eta: 3:18:01 time: 0.357738 data_time: 0.074294 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.748912 loss: 0.000864 2022/10/13 21:46:47 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:47:06 - mmengine - INFO - Epoch(train) [84][50/293] lr: 5.000000e-04 eta: 3:17:15 time: 0.376014 data_time: 0.094332 memory: 4980 loss_kpt: 0.000865 acc_pose: 0.687994 loss: 0.000865 2022/10/13 21:47:24 - mmengine - INFO - Epoch(train) [84][100/293] lr: 5.000000e-04 eta: 3:17:02 time: 0.356214 data_time: 0.081326 memory: 4980 loss_kpt: 0.000858 acc_pose: 0.751302 loss: 0.000858 2022/10/13 21:47:42 - mmengine - INFO - Epoch(train) [84][150/293] lr: 5.000000e-04 eta: 3:16:49 time: 0.364398 data_time: 0.098435 memory: 4980 loss_kpt: 0.000894 acc_pose: 0.760453 loss: 0.000894 2022/10/13 21:48:00 - mmengine - INFO - Epoch(train) [84][200/293] lr: 5.000000e-04 eta: 3:16:37 time: 0.364514 data_time: 0.075285 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.715240 loss: 0.000864 2022/10/13 21:48:19 - mmengine - INFO - Epoch(train) [84][250/293] lr: 5.000000e-04 eta: 3:16:24 time: 0.362623 data_time: 0.066627 memory: 4980 loss_kpt: 0.000863 acc_pose: 0.714847 loss: 0.000863 2022/10/13 21:48:34 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:48:53 - mmengine - INFO - Epoch(train) [85][50/293] lr: 5.000000e-04 eta: 3:15:39 time: 0.381476 data_time: 0.097614 memory: 4980 loss_kpt: 0.000878 acc_pose: 0.724228 loss: 0.000878 2022/10/13 21:49:11 - mmengine - INFO - Epoch(train) [85][100/293] lr: 5.000000e-04 eta: 3:15:26 time: 0.368505 data_time: 0.071634 memory: 4980 loss_kpt: 0.000880 acc_pose: 0.699779 loss: 0.000880 2022/10/13 21:49:29 - mmengine - INFO - Epoch(train) [85][150/293] lr: 5.000000e-04 eta: 3:15:14 time: 0.360480 data_time: 0.080571 memory: 4980 loss_kpt: 0.000876 acc_pose: 0.765789 loss: 0.000876 2022/10/13 21:49:48 - mmengine - INFO - Epoch(train) [85][200/293] lr: 5.000000e-04 eta: 3:15:01 time: 0.362511 data_time: 0.068152 memory: 4980 loss_kpt: 0.000876 acc_pose: 0.728590 loss: 0.000876 2022/10/13 21:50:06 - mmengine - INFO - Epoch(train) [85][250/293] lr: 5.000000e-04 eta: 3:14:49 time: 0.374780 data_time: 0.083002 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.769414 loss: 0.000861 2022/10/13 21:50:22 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:50:41 - mmengine - INFO - Epoch(train) [86][50/293] lr: 5.000000e-04 eta: 3:14:04 time: 0.383671 data_time: 0.091428 memory: 4980 loss_kpt: 0.000852 acc_pose: 0.743775 loss: 0.000852 2022/10/13 21:50:57 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:50:59 - mmengine - INFO - Epoch(train) [86][100/293] lr: 5.000000e-04 eta: 3:13:52 time: 0.365038 data_time: 0.071357 memory: 4980 loss_kpt: 0.000857 acc_pose: 0.740739 loss: 0.000857 2022/10/13 21:51:17 - mmengine - INFO - Epoch(train) [86][150/293] lr: 5.000000e-04 eta: 3:13:39 time: 0.362000 data_time: 0.071771 memory: 4980 loss_kpt: 0.000880 acc_pose: 0.742190 loss: 0.000880 2022/10/13 21:51:35 - mmengine - INFO - Epoch(train) [86][200/293] lr: 5.000000e-04 eta: 3:13:26 time: 0.360665 data_time: 0.081946 memory: 4980 loss_kpt: 0.000879 acc_pose: 0.756065 loss: 0.000879 2022/10/13 21:51:54 - mmengine - INFO - Epoch(train) [86][250/293] lr: 5.000000e-04 eta: 3:13:14 time: 0.366842 data_time: 0.077597 memory: 4980 loss_kpt: 0.000871 acc_pose: 0.707203 loss: 0.000871 2022/10/13 21:52:09 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:52:28 - mmengine - INFO - Epoch(train) [87][50/293] lr: 5.000000e-04 eta: 3:12:29 time: 0.379961 data_time: 0.092643 memory: 4980 loss_kpt: 0.000856 acc_pose: 0.768501 loss: 0.000856 2022/10/13 21:52:46 - mmengine - INFO - Epoch(train) [87][100/293] lr: 5.000000e-04 eta: 3:12:15 time: 0.356922 data_time: 0.120244 memory: 4980 loss_kpt: 0.000872 acc_pose: 0.756760 loss: 0.000872 2022/10/13 21:53:04 - mmengine - INFO - Epoch(train) [87][150/293] lr: 5.000000e-04 eta: 3:12:03 time: 0.365685 data_time: 0.093665 memory: 4980 loss_kpt: 0.000885 acc_pose: 0.751706 loss: 0.000885 2022/10/13 21:53:22 - mmengine - INFO - Epoch(train) [87][200/293] lr: 5.000000e-04 eta: 3:11:50 time: 0.363893 data_time: 0.078859 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.692527 loss: 0.000864 2022/10/13 21:53:41 - mmengine - INFO - Epoch(train) [87][250/293] lr: 5.000000e-04 eta: 3:11:39 time: 0.378913 data_time: 0.080497 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.709052 loss: 0.000853 2022/10/13 21:53:57 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:54:16 - mmengine - INFO - Epoch(train) [88][50/293] lr: 5.000000e-04 eta: 3:10:54 time: 0.376147 data_time: 0.089700 memory: 4980 loss_kpt: 0.000869 acc_pose: 0.752813 loss: 0.000869 2022/10/13 21:54:34 - mmengine - INFO - Epoch(train) [88][100/293] lr: 5.000000e-04 eta: 3:10:41 time: 0.366546 data_time: 0.068596 memory: 4980 loss_kpt: 0.000873 acc_pose: 0.674667 loss: 0.000873 2022/10/13 21:54:52 - mmengine - INFO - Epoch(train) [88][150/293] lr: 5.000000e-04 eta: 3:10:28 time: 0.355232 data_time: 0.067717 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.772131 loss: 0.000864 2022/10/13 21:55:10 - mmengine - INFO - Epoch(train) [88][200/293] lr: 5.000000e-04 eta: 3:10:14 time: 0.353057 data_time: 0.085567 memory: 4980 loss_kpt: 0.000878 acc_pose: 0.783956 loss: 0.000878 2022/10/13 21:55:28 - mmengine - INFO - Epoch(train) [88][250/293] lr: 5.000000e-04 eta: 3:10:02 time: 0.364376 data_time: 0.071175 memory: 4980 loss_kpt: 0.000868 acc_pose: 0.740762 loss: 0.000868 2022/10/13 21:55:43 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:56:02 - mmengine - INFO - Epoch(train) [89][50/293] lr: 5.000000e-04 eta: 3:09:17 time: 0.375948 data_time: 0.078414 memory: 4980 loss_kpt: 0.000876 acc_pose: 0.705940 loss: 0.000876 2022/10/13 21:56:20 - mmengine - INFO - Epoch(train) [89][100/293] lr: 5.000000e-04 eta: 3:09:05 time: 0.369636 data_time: 0.071773 memory: 4980 loss_kpt: 0.000873 acc_pose: 0.757319 loss: 0.000873 2022/10/13 21:56:39 - mmengine - INFO - Epoch(train) [89][150/293] lr: 5.000000e-04 eta: 3:08:52 time: 0.369712 data_time: 0.082210 memory: 4980 loss_kpt: 0.000867 acc_pose: 0.769947 loss: 0.000867 2022/10/13 21:56:57 - mmengine - INFO - Epoch(train) [89][200/293] lr: 5.000000e-04 eta: 3:08:40 time: 0.370804 data_time: 0.079344 memory: 4980 loss_kpt: 0.000872 acc_pose: 0.776237 loss: 0.000872 2022/10/13 21:57:03 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:57:16 - mmengine - INFO - Epoch(train) [89][250/293] lr: 5.000000e-04 eta: 3:08:27 time: 0.369663 data_time: 0.074353 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.741558 loss: 0.000870 2022/10/13 21:57:31 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:57:50 - mmengine - INFO - Epoch(train) [90][50/293] lr: 5.000000e-04 eta: 3:07:43 time: 0.375697 data_time: 0.082829 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.704072 loss: 0.000861 2022/10/13 21:58:08 - mmengine - INFO - Epoch(train) [90][100/293] lr: 5.000000e-04 eta: 3:07:30 time: 0.365953 data_time: 0.071561 memory: 4980 loss_kpt: 0.000868 acc_pose: 0.737821 loss: 0.000868 2022/10/13 21:58:26 - mmengine - INFO - Epoch(train) [90][150/293] lr: 5.000000e-04 eta: 3:07:17 time: 0.356276 data_time: 0.070226 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.776116 loss: 0.000870 2022/10/13 21:58:45 - mmengine - INFO - Epoch(train) [90][200/293] lr: 5.000000e-04 eta: 3:07:05 time: 0.381960 data_time: 0.080369 memory: 4980 loss_kpt: 0.000877 acc_pose: 0.679467 loss: 0.000877 2022/10/13 21:59:03 - mmengine - INFO - Epoch(train) [90][250/293] lr: 5.000000e-04 eta: 3:06:53 time: 0.363277 data_time: 0.080623 memory: 4980 loss_kpt: 0.000872 acc_pose: 0.713506 loss: 0.000872 2022/10/13 21:59:19 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 21:59:19 - mmengine - INFO - Saving checkpoint at 90 epochs 2022/10/13 21:59:28 - mmengine - INFO - Epoch(val) [90][50/407] eta: 0:00:47 time: 0.131658 data_time: 0.073034 memory: 4980 2022/10/13 21:59:34 - mmengine - INFO - Epoch(val) [90][100/407] eta: 0:00:38 time: 0.125692 data_time: 0.070972 memory: 772 2022/10/13 21:59:40 - mmengine - INFO - Epoch(val) [90][150/407] eta: 0:00:32 time: 0.128026 data_time: 0.072964 memory: 772 2022/10/13 21:59:46 - mmengine - INFO - Epoch(val) [90][200/407] eta: 0:00:23 time: 0.115766 data_time: 0.059447 memory: 772 2022/10/13 21:59:52 - mmengine - INFO - Epoch(val) [90][250/407] eta: 0:00:19 time: 0.126138 data_time: 0.069875 memory: 772 2022/10/13 21:59:58 - mmengine - INFO - Epoch(val) [90][300/407] eta: 0:00:12 time: 0.120228 data_time: 0.067103 memory: 772 2022/10/13 22:00:05 - mmengine - INFO - Epoch(val) [90][350/407] eta: 0:00:07 time: 0.123280 data_time: 0.070007 memory: 772 2022/10/13 22:00:11 - mmengine - INFO - Epoch(val) [90][400/407] eta: 0:00:00 time: 0.118971 data_time: 0.064632 memory: 772 2022/10/13 22:00:48 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 22:01:02 - mmengine - INFO - Epoch(val) [90][407/407] coco/AP: 0.610837 coco/AP .5: 0.853475 coco/AP .75: 0.671965 coco/AP (M): 0.568485 coco/AP (L): 0.683333 coco/AR: 0.674071 coco/AR .5: 0.898615 coco/AR .75: 0.736461 coco/AR (M): 0.624037 coco/AR (L): 0.744444 2022/10/13 22:01:02 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_80.pth is removed 2022/10/13 22:01:03 - mmengine - INFO - The best checkpoint with 0.6108 coco/AP at 90 epoch is saved to best_coco/AP_epoch_90.pth. 2022/10/13 22:01:22 - mmengine - INFO - Epoch(train) [91][50/293] lr: 5.000000e-04 eta: 3:06:09 time: 0.380639 data_time: 0.148329 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.701118 loss: 0.000850 2022/10/13 22:01:40 - mmengine - INFO - Epoch(train) [91][100/293] lr: 5.000000e-04 eta: 3:05:56 time: 0.363429 data_time: 0.082007 memory: 4980 loss_kpt: 0.000867 acc_pose: 0.737484 loss: 0.000867 2022/10/13 22:01:59 - mmengine - INFO - Epoch(train) [91][150/293] lr: 5.000000e-04 eta: 3:05:43 time: 0.367894 data_time: 0.076599 memory: 4980 loss_kpt: 0.000865 acc_pose: 0.718671 loss: 0.000865 2022/10/13 22:02:17 - mmengine - INFO - Epoch(train) [91][200/293] lr: 5.000000e-04 eta: 3:05:30 time: 0.355870 data_time: 0.082326 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.684088 loss: 0.000864 2022/10/13 22:02:35 - mmengine - INFO - Epoch(train) [91][250/293] lr: 5.000000e-04 eta: 3:05:18 time: 0.373545 data_time: 0.077834 memory: 4980 loss_kpt: 0.000863 acc_pose: 0.724439 loss: 0.000863 2022/10/13 22:02:51 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:03:10 - mmengine - INFO - Epoch(train) [92][50/293] lr: 5.000000e-04 eta: 3:04:34 time: 0.379910 data_time: 0.090367 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.709460 loss: 0.000864 2022/10/13 22:03:29 - mmengine - INFO - Epoch(train) [92][100/293] lr: 5.000000e-04 eta: 3:04:22 time: 0.371185 data_time: 0.069700 memory: 4980 loss_kpt: 0.000875 acc_pose: 0.749283 loss: 0.000875 2022/10/13 22:03:47 - mmengine - INFO - Epoch(train) [92][150/293] lr: 5.000000e-04 eta: 3:04:10 time: 0.376120 data_time: 0.075054 memory: 4980 loss_kpt: 0.000868 acc_pose: 0.776984 loss: 0.000868 2022/10/13 22:04:06 - mmengine - INFO - Epoch(train) [92][200/293] lr: 5.000000e-04 eta: 3:03:56 time: 0.361747 data_time: 0.071502 memory: 4980 loss_kpt: 0.000877 acc_pose: 0.697589 loss: 0.000877 2022/10/13 22:04:24 - mmengine - INFO - Epoch(train) [92][250/293] lr: 5.000000e-04 eta: 3:03:44 time: 0.368412 data_time: 0.078393 memory: 4980 loss_kpt: 0.000855 acc_pose: 0.737048 loss: 0.000855 2022/10/13 22:04:40 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:04:56 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:04:59 - mmengine - INFO - Epoch(train) [93][50/293] lr: 5.000000e-04 eta: 3:03:00 time: 0.377428 data_time: 0.091967 memory: 4980 loss_kpt: 0.000885 acc_pose: 0.707742 loss: 0.000885 2022/10/13 22:05:17 - mmengine - INFO - Epoch(train) [93][100/293] lr: 5.000000e-04 eta: 3:02:47 time: 0.357692 data_time: 0.065332 memory: 4980 loss_kpt: 0.000867 acc_pose: 0.717997 loss: 0.000867 2022/10/13 22:05:35 - mmengine - INFO - Epoch(train) [93][150/293] lr: 5.000000e-04 eta: 3:02:34 time: 0.366212 data_time: 0.083625 memory: 4980 loss_kpt: 0.000863 acc_pose: 0.730340 loss: 0.000863 2022/10/13 22:05:53 - mmengine - INFO - Epoch(train) [93][200/293] lr: 5.000000e-04 eta: 3:02:21 time: 0.362633 data_time: 0.092178 memory: 4980 loss_kpt: 0.000877 acc_pose: 0.702591 loss: 0.000877 2022/10/13 22:06:11 - mmengine - INFO - Epoch(train) [93][250/293] lr: 5.000000e-04 eta: 3:02:08 time: 0.361792 data_time: 0.124215 memory: 4980 loss_kpt: 0.000878 acc_pose: 0.741700 loss: 0.000878 2022/10/13 22:06:27 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:06:46 - mmengine - INFO - Epoch(train) [94][50/293] lr: 5.000000e-04 eta: 3:01:25 time: 0.379258 data_time: 0.087705 memory: 4980 loss_kpt: 0.000872 acc_pose: 0.751008 loss: 0.000872 2022/10/13 22:07:04 - mmengine - INFO - Epoch(train) [94][100/293] lr: 5.000000e-04 eta: 3:01:12 time: 0.364394 data_time: 0.082692 memory: 4980 loss_kpt: 0.000859 acc_pose: 0.742492 loss: 0.000859 2022/10/13 22:07:23 - mmengine - INFO - Epoch(train) [94][150/293] lr: 5.000000e-04 eta: 3:01:00 time: 0.376133 data_time: 0.079589 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.713065 loss: 0.000853 2022/10/13 22:07:41 - mmengine - INFO - Epoch(train) [94][200/293] lr: 5.000000e-04 eta: 3:00:46 time: 0.359069 data_time: 0.065660 memory: 4980 loss_kpt: 0.000865 acc_pose: 0.782261 loss: 0.000865 2022/10/13 22:07:59 - mmengine - INFO - Epoch(train) [94][250/293] lr: 5.000000e-04 eta: 3:00:33 time: 0.364235 data_time: 0.076237 memory: 4980 loss_kpt: 0.000867 acc_pose: 0.680978 loss: 0.000867 2022/10/13 22:08:15 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:08:33 - mmengine - INFO - Epoch(train) [95][50/293] lr: 5.000000e-04 eta: 2:59:50 time: 0.371652 data_time: 0.094547 memory: 4980 loss_kpt: 0.000867 acc_pose: 0.711644 loss: 0.000867 2022/10/13 22:08:52 - mmengine - INFO - Epoch(train) [95][100/293] lr: 5.000000e-04 eta: 2:59:37 time: 0.369925 data_time: 0.078415 memory: 4980 loss_kpt: 0.000856 acc_pose: 0.751034 loss: 0.000856 2022/10/13 22:09:10 - mmengine - INFO - Epoch(train) [95][150/293] lr: 5.000000e-04 eta: 2:59:25 time: 0.374109 data_time: 0.073066 memory: 4980 loss_kpt: 0.000875 acc_pose: 0.691481 loss: 0.000875 2022/10/13 22:09:28 - mmengine - INFO - Epoch(train) [95][200/293] lr: 5.000000e-04 eta: 2:59:12 time: 0.362125 data_time: 0.073313 memory: 4980 loss_kpt: 0.000854 acc_pose: 0.698716 loss: 0.000854 2022/10/13 22:09:47 - mmengine - INFO - Epoch(train) [95][250/293] lr: 5.000000e-04 eta: 2:58:59 time: 0.369218 data_time: 0.082847 memory: 4980 loss_kpt: 0.000860 acc_pose: 0.731446 loss: 0.000860 2022/10/13 22:10:03 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:10:22 - mmengine - INFO - Epoch(train) [96][50/293] lr: 5.000000e-04 eta: 2:58:16 time: 0.375393 data_time: 0.093349 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.753007 loss: 0.000864 2022/10/13 22:10:40 - mmengine - INFO - Epoch(train) [96][100/293] lr: 5.000000e-04 eta: 2:58:03 time: 0.359773 data_time: 0.067766 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.710460 loss: 0.000861 2022/10/13 22:10:58 - mmengine - INFO - Epoch(train) [96][150/293] lr: 5.000000e-04 eta: 2:57:50 time: 0.377222 data_time: 0.076919 memory: 4980 loss_kpt: 0.000872 acc_pose: 0.729355 loss: 0.000872 2022/10/13 22:11:04 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:11:17 - mmengine - INFO - Epoch(train) [96][200/293] lr: 5.000000e-04 eta: 2:57:37 time: 0.368380 data_time: 0.085365 memory: 4980 loss_kpt: 0.000856 acc_pose: 0.784931 loss: 0.000856 2022/10/13 22:11:36 - mmengine - INFO - Epoch(train) [96][250/293] lr: 5.000000e-04 eta: 2:57:25 time: 0.381155 data_time: 0.079570 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.757732 loss: 0.000870 2022/10/13 22:11:52 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:12:10 - mmengine - INFO - Epoch(train) [97][50/293] lr: 5.000000e-04 eta: 2:56:43 time: 0.377024 data_time: 0.098677 memory: 4980 loss_kpt: 0.000876 acc_pose: 0.699412 loss: 0.000876 2022/10/13 22:12:28 - mmengine - INFO - Epoch(train) [97][100/293] lr: 5.000000e-04 eta: 2:56:30 time: 0.359469 data_time: 0.073529 memory: 4980 loss_kpt: 0.000857 acc_pose: 0.689707 loss: 0.000857 2022/10/13 22:12:47 - mmengine - INFO - Epoch(train) [97][150/293] lr: 5.000000e-04 eta: 2:56:17 time: 0.379367 data_time: 0.082164 memory: 4980 loss_kpt: 0.000858 acc_pose: 0.721988 loss: 0.000858 2022/10/13 22:13:05 - mmengine - INFO - Epoch(train) [97][200/293] lr: 5.000000e-04 eta: 2:56:03 time: 0.355195 data_time: 0.071925 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.746096 loss: 0.000853 2022/10/13 22:13:23 - mmengine - INFO - Epoch(train) [97][250/293] lr: 5.000000e-04 eta: 2:55:50 time: 0.362255 data_time: 0.072583 memory: 4980 loss_kpt: 0.000862 acc_pose: 0.665549 loss: 0.000862 2022/10/13 22:13:39 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:13:58 - mmengine - INFO - Epoch(train) [98][50/293] lr: 5.000000e-04 eta: 2:55:08 time: 0.371341 data_time: 0.106213 memory: 4980 loss_kpt: 0.000869 acc_pose: 0.731455 loss: 0.000869 2022/10/13 22:14:16 - mmengine - INFO - Epoch(train) [98][100/293] lr: 5.000000e-04 eta: 2:54:55 time: 0.370458 data_time: 0.075474 memory: 4980 loss_kpt: 0.000874 acc_pose: 0.700128 loss: 0.000874 2022/10/13 22:14:35 - mmengine - INFO - Epoch(train) [98][150/293] lr: 5.000000e-04 eta: 2:54:42 time: 0.377405 data_time: 0.075274 memory: 4980 loss_kpt: 0.000848 acc_pose: 0.702272 loss: 0.000848 2022/10/13 22:14:53 - mmengine - INFO - Epoch(train) [98][200/293] lr: 5.000000e-04 eta: 2:54:29 time: 0.365551 data_time: 0.078205 memory: 4980 loss_kpt: 0.000867 acc_pose: 0.734205 loss: 0.000867 2022/10/13 22:15:12 - mmengine - INFO - Epoch(train) [98][250/293] lr: 5.000000e-04 eta: 2:54:16 time: 0.366367 data_time: 0.075253 memory: 4980 loss_kpt: 0.000868 acc_pose: 0.743814 loss: 0.000868 2022/10/13 22:15:27 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:15:46 - mmengine - INFO - Epoch(train) [99][50/293] lr: 5.000000e-04 eta: 2:53:35 time: 0.382051 data_time: 0.100122 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.719345 loss: 0.000861 2022/10/13 22:16:04 - mmengine - INFO - Epoch(train) [99][100/293] lr: 5.000000e-04 eta: 2:53:21 time: 0.361431 data_time: 0.073976 memory: 4980 loss_kpt: 0.000851 acc_pose: 0.744927 loss: 0.000851 2022/10/13 22:16:23 - mmengine - INFO - Epoch(train) [99][150/293] lr: 5.000000e-04 eta: 2:53:08 time: 0.364184 data_time: 0.073830 memory: 4980 loss_kpt: 0.000881 acc_pose: 0.724124 loss: 0.000881 2022/10/13 22:16:41 - mmengine - INFO - Epoch(train) [99][200/293] lr: 5.000000e-04 eta: 2:52:55 time: 0.375512 data_time: 0.074760 memory: 4980 loss_kpt: 0.000878 acc_pose: 0.715347 loss: 0.000878 2022/10/13 22:16:59 - mmengine - INFO - Epoch(train) [99][250/293] lr: 5.000000e-04 eta: 2:52:42 time: 0.362845 data_time: 0.072912 memory: 4980 loss_kpt: 0.000856 acc_pose: 0.743486 loss: 0.000856 2022/10/13 22:17:13 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:17:15 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:17:34 - mmengine - INFO - Epoch(train) [100][50/293] lr: 5.000000e-04 eta: 2:52:00 time: 0.378928 data_time: 0.093196 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.768747 loss: 0.000870 2022/10/13 22:17:52 - mmengine - INFO - Epoch(train) [100][100/293] lr: 5.000000e-04 eta: 2:51:47 time: 0.360544 data_time: 0.067658 memory: 4980 loss_kpt: 0.000862 acc_pose: 0.750591 loss: 0.000862 2022/10/13 22:18:11 - mmengine - INFO - Epoch(train) [100][150/293] lr: 5.000000e-04 eta: 2:51:34 time: 0.371177 data_time: 0.074043 memory: 4980 loss_kpt: 0.000867 acc_pose: 0.771445 loss: 0.000867 2022/10/13 22:18:29 - mmengine - INFO - Epoch(train) [100][200/293] lr: 5.000000e-04 eta: 2:51:21 time: 0.367594 data_time: 0.087421 memory: 4980 loss_kpt: 0.000860 acc_pose: 0.738145 loss: 0.000860 2022/10/13 22:18:48 - mmengine - INFO - Epoch(train) [100][250/293] lr: 5.000000e-04 eta: 2:51:08 time: 0.384482 data_time: 0.076782 memory: 4980 loss_kpt: 0.000849 acc_pose: 0.756850 loss: 0.000849 2022/10/13 22:19:04 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:19:04 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/10/13 22:19:12 - mmengine - INFO - Epoch(val) [100][50/407] eta: 0:00:45 time: 0.127798 data_time: 0.070550 memory: 4980 2022/10/13 22:19:19 - mmengine - INFO - Epoch(val) [100][100/407] eta: 0:00:38 time: 0.125910 data_time: 0.071278 memory: 772 2022/10/13 22:19:25 - mmengine - INFO - Epoch(val) [100][150/407] eta: 0:00:32 time: 0.128308 data_time: 0.073627 memory: 772 2022/10/13 22:19:31 - mmengine - INFO - Epoch(val) [100][200/407] eta: 0:00:24 time: 0.120127 data_time: 0.065278 memory: 772 2022/10/13 22:19:37 - mmengine - INFO - Epoch(val) [100][250/407] eta: 0:00:18 time: 0.118992 data_time: 0.065854 memory: 772 2022/10/13 22:19:43 - mmengine - INFO - Epoch(val) [100][300/407] eta: 0:00:13 time: 0.123710 data_time: 0.070171 memory: 772 2022/10/13 22:19:50 - mmengine - INFO - Epoch(val) [100][350/407] eta: 0:00:07 time: 0.132578 data_time: 0.078633 memory: 772 2022/10/13 22:19:56 - mmengine - INFO - Epoch(val) [100][400/407] eta: 0:00:00 time: 0.120711 data_time: 0.067149 memory: 772 2022/10/13 22:20:33 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 22:20:47 - mmengine - INFO - Epoch(val) [100][407/407] coco/AP: 0.614803 coco/AP .5: 0.855168 coco/AP .75: 0.679081 coco/AP (M): 0.574499 coco/AP (L): 0.684921 coco/AR: 0.677047 coco/AR .5: 0.898929 coco/AR .75: 0.741656 coco/AR (M): 0.628107 coco/AR (L): 0.746525 2022/10/13 22:20:47 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_90.pth is removed 2022/10/13 22:20:49 - mmengine - INFO - The best checkpoint with 0.6148 coco/AP at 100 epoch is saved to best_coco/AP_epoch_100.pth. 2022/10/13 22:21:08 - mmengine - INFO - Epoch(train) [101][50/293] lr: 5.000000e-04 eta: 2:50:28 time: 0.390201 data_time: 0.145068 memory: 4980 loss_kpt: 0.000868 acc_pose: 0.796712 loss: 0.000868 2022/10/13 22:21:27 - mmengine - INFO - Epoch(train) [101][100/293] lr: 5.000000e-04 eta: 2:50:15 time: 0.374005 data_time: 0.127164 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.699245 loss: 0.000864 2022/10/13 22:21:45 - mmengine - INFO - Epoch(train) [101][150/293] lr: 5.000000e-04 eta: 2:50:01 time: 0.359843 data_time: 0.090401 memory: 4980 loss_kpt: 0.000849 acc_pose: 0.696076 loss: 0.000849 2022/10/13 22:22:03 - mmengine - INFO - Epoch(train) [101][200/293] lr: 5.000000e-04 eta: 2:49:48 time: 0.365140 data_time: 0.070948 memory: 4980 loss_kpt: 0.000863 acc_pose: 0.761683 loss: 0.000863 2022/10/13 22:22:22 - mmengine - INFO - Epoch(train) [101][250/293] lr: 5.000000e-04 eta: 2:49:35 time: 0.374598 data_time: 0.089115 memory: 4980 loss_kpt: 0.000855 acc_pose: 0.698844 loss: 0.000855 2022/10/13 22:22:38 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:22:57 - mmengine - INFO - Epoch(train) [102][50/293] lr: 5.000000e-04 eta: 2:48:54 time: 0.378584 data_time: 0.085008 memory: 4980 loss_kpt: 0.000852 acc_pose: 0.701065 loss: 0.000852 2022/10/13 22:23:15 - mmengine - INFO - Epoch(train) [102][100/293] lr: 5.000000e-04 eta: 2:48:41 time: 0.370397 data_time: 0.079746 memory: 4980 loss_kpt: 0.000866 acc_pose: 0.748377 loss: 0.000866 2022/10/13 22:23:34 - mmengine - INFO - Epoch(train) [102][150/293] lr: 5.000000e-04 eta: 2:48:28 time: 0.370209 data_time: 0.075756 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.708986 loss: 0.000870 2022/10/13 22:23:52 - mmengine - INFO - Epoch(train) [102][200/293] lr: 5.000000e-04 eta: 2:48:15 time: 0.370798 data_time: 0.076423 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.695414 loss: 0.000861 2022/10/13 22:24:10 - mmengine - INFO - Epoch(train) [102][250/293] lr: 5.000000e-04 eta: 2:48:01 time: 0.364776 data_time: 0.086711 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.764968 loss: 0.000864 2022/10/13 22:24:26 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:24:45 - mmengine - INFO - Epoch(train) [103][50/293] lr: 5.000000e-04 eta: 2:47:20 time: 0.371576 data_time: 0.100598 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.742120 loss: 0.000850 2022/10/13 22:25:03 - mmengine - INFO - Epoch(train) [103][100/293] lr: 5.000000e-04 eta: 2:47:07 time: 0.373995 data_time: 0.074552 memory: 4980 loss_kpt: 0.000867 acc_pose: 0.736645 loss: 0.000867 2022/10/13 22:25:08 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:25:22 - mmengine - INFO - Epoch(train) [103][150/293] lr: 5.000000e-04 eta: 2:46:54 time: 0.363429 data_time: 0.080734 memory: 4980 loss_kpt: 0.000858 acc_pose: 0.695740 loss: 0.000858 2022/10/13 22:25:40 - mmengine - INFO - Epoch(train) [103][200/293] lr: 5.000000e-04 eta: 2:46:40 time: 0.359816 data_time: 0.065542 memory: 4980 loss_kpt: 0.000865 acc_pose: 0.693101 loss: 0.000865 2022/10/13 22:25:58 - mmengine - INFO - Epoch(train) [103][250/293] lr: 5.000000e-04 eta: 2:46:27 time: 0.365154 data_time: 0.078466 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.713125 loss: 0.000870 2022/10/13 22:26:13 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:26:33 - mmengine - INFO - Epoch(train) [104][50/293] lr: 5.000000e-04 eta: 2:45:47 time: 0.389722 data_time: 0.099082 memory: 4980 loss_kpt: 0.000839 acc_pose: 0.751701 loss: 0.000839 2022/10/13 22:26:51 - mmengine - INFO - Epoch(train) [104][100/293] lr: 5.000000e-04 eta: 2:45:33 time: 0.366235 data_time: 0.070671 memory: 4980 loss_kpt: 0.000834 acc_pose: 0.749216 loss: 0.000834 2022/10/13 22:27:10 - mmengine - INFO - Epoch(train) [104][150/293] lr: 5.000000e-04 eta: 2:45:20 time: 0.374184 data_time: 0.080045 memory: 4980 loss_kpt: 0.000852 acc_pose: 0.706195 loss: 0.000852 2022/10/13 22:27:28 - mmengine - INFO - Epoch(train) [104][200/293] lr: 5.000000e-04 eta: 2:45:07 time: 0.362673 data_time: 0.074825 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.756436 loss: 0.000850 2022/10/13 22:27:46 - mmengine - INFO - Epoch(train) [104][250/293] lr: 5.000000e-04 eta: 2:44:53 time: 0.364839 data_time: 0.077568 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.702272 loss: 0.000870 2022/10/13 22:28:02 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:28:21 - mmengine - INFO - Epoch(train) [105][50/293] lr: 5.000000e-04 eta: 2:44:13 time: 0.389009 data_time: 0.107961 memory: 4980 loss_kpt: 0.000852 acc_pose: 0.715135 loss: 0.000852 2022/10/13 22:28:39 - mmengine - INFO - Epoch(train) [105][100/293] lr: 5.000000e-04 eta: 2:43:59 time: 0.360553 data_time: 0.091468 memory: 4980 loss_kpt: 0.000844 acc_pose: 0.737816 loss: 0.000844 2022/10/13 22:28:58 - mmengine - INFO - Epoch(train) [105][150/293] lr: 5.000000e-04 eta: 2:43:46 time: 0.369674 data_time: 0.085321 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.717865 loss: 0.000861 2022/10/13 22:29:16 - mmengine - INFO - Epoch(train) [105][200/293] lr: 5.000000e-04 eta: 2:43:32 time: 0.360721 data_time: 0.082097 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.751001 loss: 0.000850 2022/10/13 22:29:35 - mmengine - INFO - Epoch(train) [105][250/293] lr: 5.000000e-04 eta: 2:43:19 time: 0.374516 data_time: 0.076093 memory: 4980 loss_kpt: 0.000852 acc_pose: 0.744502 loss: 0.000852 2022/10/13 22:29:50 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:30:10 - mmengine - INFO - Epoch(train) [106][50/293] lr: 5.000000e-04 eta: 2:42:40 time: 0.385774 data_time: 0.088816 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.713843 loss: 0.000864 2022/10/13 22:30:28 - mmengine - INFO - Epoch(train) [106][100/293] lr: 5.000000e-04 eta: 2:42:26 time: 0.365422 data_time: 0.068023 memory: 4980 loss_kpt: 0.000855 acc_pose: 0.705932 loss: 0.000855 2022/10/13 22:30:46 - mmengine - INFO - Epoch(train) [106][150/293] lr: 5.000000e-04 eta: 2:42:12 time: 0.355555 data_time: 0.073503 memory: 4980 loss_kpt: 0.000859 acc_pose: 0.754707 loss: 0.000859 2022/10/13 22:31:04 - mmengine - INFO - Epoch(train) [106][200/293] lr: 5.000000e-04 eta: 2:41:58 time: 0.365975 data_time: 0.074138 memory: 4980 loss_kpt: 0.000849 acc_pose: 0.706671 loss: 0.000849 2022/10/13 22:31:17 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:31:23 - mmengine - INFO - Epoch(train) [106][250/293] lr: 5.000000e-04 eta: 2:41:45 time: 0.376450 data_time: 0.069472 memory: 4980 loss_kpt: 0.000865 acc_pose: 0.696828 loss: 0.000865 2022/10/13 22:31:39 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:31:58 - mmengine - INFO - Epoch(train) [107][50/293] lr: 5.000000e-04 eta: 2:41:06 time: 0.384204 data_time: 0.118141 memory: 4980 loss_kpt: 0.000866 acc_pose: 0.714503 loss: 0.000866 2022/10/13 22:32:16 - mmengine - INFO - Epoch(train) [107][100/293] lr: 5.000000e-04 eta: 2:40:52 time: 0.355815 data_time: 0.073995 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.722471 loss: 0.000853 2022/10/13 22:32:34 - mmengine - INFO - Epoch(train) [107][150/293] lr: 5.000000e-04 eta: 2:40:39 time: 0.373201 data_time: 0.072427 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.728093 loss: 0.000846 2022/10/13 22:32:52 - mmengine - INFO - Epoch(train) [107][200/293] lr: 5.000000e-04 eta: 2:40:25 time: 0.358800 data_time: 0.077554 memory: 4980 loss_kpt: 0.000856 acc_pose: 0.776407 loss: 0.000856 2022/10/13 22:33:11 - mmengine - INFO - Epoch(train) [107][250/293] lr: 5.000000e-04 eta: 2:40:12 time: 0.376402 data_time: 0.083350 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.760165 loss: 0.000846 2022/10/13 22:33:27 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:33:46 - mmengine - INFO - Epoch(train) [108][50/293] lr: 5.000000e-04 eta: 2:39:32 time: 0.388128 data_time: 0.089838 memory: 4980 loss_kpt: 0.000871 acc_pose: 0.724348 loss: 0.000871 2022/10/13 22:34:05 - mmengine - INFO - Epoch(train) [108][100/293] lr: 5.000000e-04 eta: 2:39:19 time: 0.374486 data_time: 0.086997 memory: 4980 loss_kpt: 0.000860 acc_pose: 0.652582 loss: 0.000860 2022/10/13 22:34:23 - mmengine - INFO - Epoch(train) [108][150/293] lr: 5.000000e-04 eta: 2:39:05 time: 0.364156 data_time: 0.075307 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.764373 loss: 0.000850 2022/10/13 22:34:42 - mmengine - INFO - Epoch(train) [108][200/293] lr: 5.000000e-04 eta: 2:38:52 time: 0.371690 data_time: 0.080674 memory: 4980 loss_kpt: 0.000870 acc_pose: 0.696541 loss: 0.000870 2022/10/13 22:35:00 - mmengine - INFO - Epoch(train) [108][250/293] lr: 5.000000e-04 eta: 2:38:38 time: 0.359882 data_time: 0.075989 memory: 4980 loss_kpt: 0.000860 acc_pose: 0.747063 loss: 0.000860 2022/10/13 22:35:15 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:35:34 - mmengine - INFO - Epoch(train) [109][50/293] lr: 5.000000e-04 eta: 2:37:59 time: 0.385676 data_time: 0.143554 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.708471 loss: 0.000847 2022/10/13 22:35:52 - mmengine - INFO - Epoch(train) [109][100/293] lr: 5.000000e-04 eta: 2:37:45 time: 0.358756 data_time: 0.093509 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.720210 loss: 0.000850 2022/10/13 22:36:10 - mmengine - INFO - Epoch(train) [109][150/293] lr: 5.000000e-04 eta: 2:37:31 time: 0.362500 data_time: 0.080771 memory: 4980 loss_kpt: 0.000856 acc_pose: 0.746056 loss: 0.000856 2022/10/13 22:36:29 - mmengine - INFO - Epoch(train) [109][200/293] lr: 5.000000e-04 eta: 2:37:18 time: 0.368482 data_time: 0.069670 memory: 4980 loss_kpt: 0.000860 acc_pose: 0.711706 loss: 0.000860 2022/10/13 22:36:47 - mmengine - INFO - Epoch(train) [109][250/293] lr: 5.000000e-04 eta: 2:37:04 time: 0.370413 data_time: 0.072856 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.715494 loss: 0.000846 2022/10/13 22:37:03 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:37:22 - mmengine - INFO - Epoch(train) [110][50/293] lr: 5.000000e-04 eta: 2:36:24 time: 0.373871 data_time: 0.087982 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.691406 loss: 0.000850 2022/10/13 22:37:27 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:37:40 - mmengine - INFO - Epoch(train) [110][100/293] lr: 5.000000e-04 eta: 2:36:11 time: 0.361238 data_time: 0.077390 memory: 4980 loss_kpt: 0.000852 acc_pose: 0.777104 loss: 0.000852 2022/10/13 22:37:58 - mmengine - INFO - Epoch(train) [110][150/293] lr: 5.000000e-04 eta: 2:35:57 time: 0.367262 data_time: 0.075662 memory: 4980 loss_kpt: 0.000855 acc_pose: 0.738907 loss: 0.000855 2022/10/13 22:38:17 - mmengine - INFO - Epoch(train) [110][200/293] lr: 5.000000e-04 eta: 2:35:44 time: 0.375308 data_time: 0.085837 memory: 4980 loss_kpt: 0.000860 acc_pose: 0.715125 loss: 0.000860 2022/10/13 22:38:35 - mmengine - INFO - Epoch(train) [110][250/293] lr: 5.000000e-04 eta: 2:35:30 time: 0.367491 data_time: 0.084042 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.750780 loss: 0.000846 2022/10/13 22:38:51 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:38:51 - mmengine - INFO - Saving checkpoint at 110 epochs 2022/10/13 22:39:00 - mmengine - INFO - Epoch(val) [110][50/407] eta: 0:00:46 time: 0.129294 data_time: 0.071709 memory: 4980 2022/10/13 22:39:06 - mmengine - INFO - Epoch(val) [110][100/407] eta: 0:00:38 time: 0.123940 data_time: 0.067647 memory: 772 2022/10/13 22:39:12 - mmengine - INFO - Epoch(val) [110][150/407] eta: 0:00:31 time: 0.124288 data_time: 0.068680 memory: 772 2022/10/13 22:39:18 - mmengine - INFO - Epoch(val) [110][200/407] eta: 0:00:24 time: 0.117751 data_time: 0.061626 memory: 772 2022/10/13 22:39:24 - mmengine - INFO - Epoch(val) [110][250/407] eta: 0:00:20 time: 0.129012 data_time: 0.073200 memory: 772 2022/10/13 22:39:31 - mmengine - INFO - Epoch(val) [110][300/407] eta: 0:00:13 time: 0.122829 data_time: 0.065527 memory: 772 2022/10/13 22:39:37 - mmengine - INFO - Epoch(val) [110][350/407] eta: 0:00:06 time: 0.121893 data_time: 0.068531 memory: 772 2022/10/13 22:39:43 - mmengine - INFO - Epoch(val) [110][400/407] eta: 0:00:00 time: 0.123092 data_time: 0.068840 memory: 772 2022/10/13 22:40:19 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 22:40:33 - mmengine - INFO - Epoch(val) [110][407/407] coco/AP: 0.617497 coco/AP .5: 0.859442 coco/AP .75: 0.679121 coco/AP (M): 0.577105 coco/AP (L): 0.686962 coco/AR: 0.679991 coco/AR .5: 0.901606 coco/AR .75: 0.743230 coco/AR (M): 0.630374 coco/AR (L): 0.749535 2022/10/13 22:40:33 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_100.pth is removed 2022/10/13 22:40:35 - mmengine - INFO - The best checkpoint with 0.6175 coco/AP at 110 epoch is saved to best_coco/AP_epoch_110.pth. 2022/10/13 22:40:54 - mmengine - INFO - Epoch(train) [111][50/293] lr: 5.000000e-04 eta: 2:34:51 time: 0.381815 data_time: 0.159620 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.730788 loss: 0.000864 2022/10/13 22:41:13 - mmengine - INFO - Epoch(train) [111][100/293] lr: 5.000000e-04 eta: 2:34:37 time: 0.368819 data_time: 0.113299 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.758021 loss: 0.000864 2022/10/13 22:41:31 - mmengine - INFO - Epoch(train) [111][150/293] lr: 5.000000e-04 eta: 2:34:24 time: 0.378211 data_time: 0.069757 memory: 4980 loss_kpt: 0.000863 acc_pose: 0.713808 loss: 0.000863 2022/10/13 22:41:49 - mmengine - INFO - Epoch(train) [111][200/293] lr: 5.000000e-04 eta: 2:34:10 time: 0.357087 data_time: 0.071889 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.716257 loss: 0.000846 2022/10/13 22:42:08 - mmengine - INFO - Epoch(train) [111][250/293] lr: 5.000000e-04 eta: 2:33:56 time: 0.364782 data_time: 0.068914 memory: 4980 loss_kpt: 0.000863 acc_pose: 0.723255 loss: 0.000863 2022/10/13 22:42:23 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:42:42 - mmengine - INFO - Epoch(train) [112][50/293] lr: 5.000000e-04 eta: 2:33:17 time: 0.379557 data_time: 0.091263 memory: 4980 loss_kpt: 0.000858 acc_pose: 0.711868 loss: 0.000858 2022/10/13 22:43:00 - mmengine - INFO - Epoch(train) [112][100/293] lr: 5.000000e-04 eta: 2:33:04 time: 0.371539 data_time: 0.081045 memory: 4980 loss_kpt: 0.000865 acc_pose: 0.776100 loss: 0.000865 2022/10/13 22:43:19 - mmengine - INFO - Epoch(train) [112][150/293] lr: 5.000000e-04 eta: 2:32:50 time: 0.369308 data_time: 0.082478 memory: 4980 loss_kpt: 0.000862 acc_pose: 0.714957 loss: 0.000862 2022/10/13 22:43:37 - mmengine - INFO - Epoch(train) [112][200/293] lr: 5.000000e-04 eta: 2:32:36 time: 0.364698 data_time: 0.071301 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.683217 loss: 0.000847 2022/10/13 22:43:55 - mmengine - INFO - Epoch(train) [112][250/293] lr: 5.000000e-04 eta: 2:32:22 time: 0.351967 data_time: 0.068399 memory: 4980 loss_kpt: 0.000855 acc_pose: 0.774418 loss: 0.000855 2022/10/13 22:44:10 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:44:29 - mmengine - INFO - Epoch(train) [113][50/293] lr: 5.000000e-04 eta: 2:31:43 time: 0.378885 data_time: 0.109239 memory: 4980 loss_kpt: 0.000869 acc_pose: 0.725253 loss: 0.000869 2022/10/13 22:44:47 - mmengine - INFO - Epoch(train) [113][100/293] lr: 5.000000e-04 eta: 2:31:29 time: 0.367520 data_time: 0.129308 memory: 4980 loss_kpt: 0.000828 acc_pose: 0.715086 loss: 0.000828 2022/10/13 22:45:06 - mmengine - INFO - Epoch(train) [113][150/293] lr: 5.000000e-04 eta: 2:31:16 time: 0.378212 data_time: 0.115279 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.724215 loss: 0.000853 2022/10/13 22:45:19 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:45:24 - mmengine - INFO - Epoch(train) [113][200/293] lr: 5.000000e-04 eta: 2:31:03 time: 0.369864 data_time: 0.078516 memory: 4980 loss_kpt: 0.000849 acc_pose: 0.739964 loss: 0.000849 2022/10/13 22:45:43 - mmengine - INFO - Epoch(train) [113][250/293] lr: 5.000000e-04 eta: 2:30:49 time: 0.375030 data_time: 0.081704 memory: 4980 loss_kpt: 0.000841 acc_pose: 0.751154 loss: 0.000841 2022/10/13 22:45:58 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:46:17 - mmengine - INFO - Epoch(train) [114][50/293] lr: 5.000000e-04 eta: 2:30:11 time: 0.383045 data_time: 0.101352 memory: 4980 loss_kpt: 0.000855 acc_pose: 0.698203 loss: 0.000855 2022/10/13 22:46:36 - mmengine - INFO - Epoch(train) [114][100/293] lr: 5.000000e-04 eta: 2:29:57 time: 0.364614 data_time: 0.074581 memory: 4980 loss_kpt: 0.000842 acc_pose: 0.779092 loss: 0.000842 2022/10/13 22:46:54 - mmengine - INFO - Epoch(train) [114][150/293] lr: 5.000000e-04 eta: 2:29:43 time: 0.371347 data_time: 0.069611 memory: 4980 loss_kpt: 0.000854 acc_pose: 0.694980 loss: 0.000854 2022/10/13 22:47:13 - mmengine - INFO - Epoch(train) [114][200/293] lr: 5.000000e-04 eta: 2:29:29 time: 0.368272 data_time: 0.077745 memory: 4980 loss_kpt: 0.000855 acc_pose: 0.778594 loss: 0.000855 2022/10/13 22:47:31 - mmengine - INFO - Epoch(train) [114][250/293] lr: 5.000000e-04 eta: 2:29:15 time: 0.360330 data_time: 0.077455 memory: 4980 loss_kpt: 0.000848 acc_pose: 0.711443 loss: 0.000848 2022/10/13 22:47:46 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:48:05 - mmengine - INFO - Epoch(train) [115][50/293] lr: 5.000000e-04 eta: 2:28:37 time: 0.377155 data_time: 0.114243 memory: 4980 loss_kpt: 0.000865 acc_pose: 0.755026 loss: 0.000865 2022/10/13 22:48:23 - mmengine - INFO - Epoch(train) [115][100/293] lr: 5.000000e-04 eta: 2:28:23 time: 0.366300 data_time: 0.113868 memory: 4980 loss_kpt: 0.000859 acc_pose: 0.723434 loss: 0.000859 2022/10/13 22:48:41 - mmengine - INFO - Epoch(train) [115][150/293] lr: 5.000000e-04 eta: 2:28:09 time: 0.355117 data_time: 0.070771 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.701360 loss: 0.000846 2022/10/13 22:48:59 - mmengine - INFO - Epoch(train) [115][200/293] lr: 5.000000e-04 eta: 2:27:55 time: 0.370939 data_time: 0.081482 memory: 4980 loss_kpt: 0.000856 acc_pose: 0.650832 loss: 0.000856 2022/10/13 22:49:17 - mmengine - INFO - Epoch(train) [115][250/293] lr: 5.000000e-04 eta: 2:27:41 time: 0.364592 data_time: 0.070170 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.713643 loss: 0.000853 2022/10/13 22:49:33 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:49:52 - mmengine - INFO - Epoch(train) [116][50/293] lr: 5.000000e-04 eta: 2:27:03 time: 0.376790 data_time: 0.097795 memory: 4980 loss_kpt: 0.000858 acc_pose: 0.656842 loss: 0.000858 2022/10/13 22:50:10 - mmengine - INFO - Epoch(train) [116][100/293] lr: 5.000000e-04 eta: 2:26:48 time: 0.360113 data_time: 0.073749 memory: 4980 loss_kpt: 0.000872 acc_pose: 0.768523 loss: 0.000872 2022/10/13 22:50:28 - mmengine - INFO - Epoch(train) [116][150/293] lr: 5.000000e-04 eta: 2:26:34 time: 0.360928 data_time: 0.072207 memory: 4980 loss_kpt: 0.000849 acc_pose: 0.719761 loss: 0.000849 2022/10/13 22:50:46 - mmengine - INFO - Epoch(train) [116][200/293] lr: 5.000000e-04 eta: 2:26:20 time: 0.357407 data_time: 0.081461 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.740119 loss: 0.000861 2022/10/13 22:51:04 - mmengine - INFO - Epoch(train) [116][250/293] lr: 5.000000e-04 eta: 2:26:06 time: 0.363686 data_time: 0.081283 memory: 4980 loss_kpt: 0.000842 acc_pose: 0.766335 loss: 0.000842 2022/10/13 22:51:20 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:51:25 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:51:39 - mmengine - INFO - Epoch(train) [117][50/293] lr: 5.000000e-04 eta: 2:25:28 time: 0.386823 data_time: 0.095406 memory: 4980 loss_kpt: 0.000856 acc_pose: 0.715189 loss: 0.000856 2022/10/13 22:51:57 - mmengine - INFO - Epoch(train) [117][100/293] lr: 5.000000e-04 eta: 2:25:14 time: 0.367745 data_time: 0.089281 memory: 4980 loss_kpt: 0.000855 acc_pose: 0.700161 loss: 0.000855 2022/10/13 22:52:16 - mmengine - INFO - Epoch(train) [117][150/293] lr: 5.000000e-04 eta: 2:25:00 time: 0.362854 data_time: 0.076475 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.769424 loss: 0.000850 2022/10/13 22:52:33 - mmengine - INFO - Epoch(train) [117][200/293] lr: 5.000000e-04 eta: 2:24:46 time: 0.356216 data_time: 0.081975 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.773421 loss: 0.000847 2022/10/13 22:52:51 - mmengine - INFO - Epoch(train) [117][250/293] lr: 5.000000e-04 eta: 2:24:32 time: 0.358195 data_time: 0.075086 memory: 4980 loss_kpt: 0.000848 acc_pose: 0.741068 loss: 0.000848 2022/10/13 22:53:07 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:53:26 - mmengine - INFO - Epoch(train) [118][50/293] lr: 5.000000e-04 eta: 2:23:54 time: 0.384204 data_time: 0.157745 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.756463 loss: 0.000861 2022/10/13 22:53:44 - mmengine - INFO - Epoch(train) [118][100/293] lr: 5.000000e-04 eta: 2:23:40 time: 0.358286 data_time: 0.109055 memory: 4980 loss_kpt: 0.000858 acc_pose: 0.752301 loss: 0.000858 2022/10/13 22:54:02 - mmengine - INFO - Epoch(train) [118][150/293] lr: 5.000000e-04 eta: 2:23:26 time: 0.363809 data_time: 0.069061 memory: 4980 loss_kpt: 0.000859 acc_pose: 0.727298 loss: 0.000859 2022/10/13 22:54:21 - mmengine - INFO - Epoch(train) [118][200/293] lr: 5.000000e-04 eta: 2:23:12 time: 0.376805 data_time: 0.080961 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.762850 loss: 0.000861 2022/10/13 22:54:39 - mmengine - INFO - Epoch(train) [118][250/293] lr: 5.000000e-04 eta: 2:22:58 time: 0.362493 data_time: 0.077589 memory: 4980 loss_kpt: 0.000849 acc_pose: 0.698198 loss: 0.000849 2022/10/13 22:54:54 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:55:14 - mmengine - INFO - Epoch(train) [119][50/293] lr: 5.000000e-04 eta: 2:22:21 time: 0.392036 data_time: 0.096170 memory: 4980 loss_kpt: 0.000840 acc_pose: 0.785007 loss: 0.000840 2022/10/13 22:55:32 - mmengine - INFO - Epoch(train) [119][100/293] lr: 5.000000e-04 eta: 2:22:06 time: 0.355711 data_time: 0.068431 memory: 4980 loss_kpt: 0.000859 acc_pose: 0.757535 loss: 0.000859 2022/10/13 22:55:50 - mmengine - INFO - Epoch(train) [119][150/293] lr: 5.000000e-04 eta: 2:21:52 time: 0.364104 data_time: 0.083266 memory: 4980 loss_kpt: 0.000855 acc_pose: 0.732153 loss: 0.000855 2022/10/13 22:56:08 - mmengine - INFO - Epoch(train) [119][200/293] lr: 5.000000e-04 eta: 2:21:38 time: 0.361551 data_time: 0.073064 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.728734 loss: 0.000861 2022/10/13 22:56:26 - mmengine - INFO - Epoch(train) [119][250/293] lr: 5.000000e-04 eta: 2:21:24 time: 0.360457 data_time: 0.072723 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.743242 loss: 0.000853 2022/10/13 22:56:42 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:57:01 - mmengine - INFO - Epoch(train) [120][50/293] lr: 5.000000e-04 eta: 2:20:46 time: 0.379760 data_time: 0.106905 memory: 4980 loss_kpt: 0.000848 acc_pose: 0.782254 loss: 0.000848 2022/10/13 22:57:20 - mmengine - INFO - Epoch(train) [120][100/293] lr: 5.000000e-04 eta: 2:20:33 time: 0.375156 data_time: 0.087999 memory: 4980 loss_kpt: 0.000827 acc_pose: 0.800462 loss: 0.000827 2022/10/13 22:57:32 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:57:38 - mmengine - INFO - Epoch(train) [120][150/293] lr: 5.000000e-04 eta: 2:20:18 time: 0.363212 data_time: 0.076338 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.759671 loss: 0.000846 2022/10/13 22:57:56 - mmengine - INFO - Epoch(train) [120][200/293] lr: 5.000000e-04 eta: 2:20:05 time: 0.372336 data_time: 0.064306 memory: 4980 loss_kpt: 0.000851 acc_pose: 0.759810 loss: 0.000851 2022/10/13 22:58:15 - mmengine - INFO - Epoch(train) [120][250/293] lr: 5.000000e-04 eta: 2:19:50 time: 0.362874 data_time: 0.071065 memory: 4980 loss_kpt: 0.000840 acc_pose: 0.705789 loss: 0.000840 2022/10/13 22:58:30 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 22:58:30 - mmengine - INFO - Saving checkpoint at 120 epochs 2022/10/13 22:58:38 - mmengine - INFO - Epoch(val) [120][50/407] eta: 0:00:45 time: 0.128634 data_time: 0.073008 memory: 4980 2022/10/13 22:58:45 - mmengine - INFO - Epoch(val) [120][100/407] eta: 0:00:37 time: 0.122944 data_time: 0.068448 memory: 772 2022/10/13 22:58:51 - mmengine - INFO - Epoch(val) [120][150/407] eta: 0:00:32 time: 0.126005 data_time: 0.071251 memory: 772 2022/10/13 22:58:57 - mmengine - INFO - Epoch(val) [120][200/407] eta: 0:00:25 time: 0.123074 data_time: 0.067960 memory: 772 2022/10/13 22:59:03 - mmengine - INFO - Epoch(val) [120][250/407] eta: 0:00:19 time: 0.125434 data_time: 0.070910 memory: 772 2022/10/13 22:59:10 - mmengine - INFO - Epoch(val) [120][300/407] eta: 0:00:13 time: 0.130071 data_time: 0.075806 memory: 772 2022/10/13 22:59:16 - mmengine - INFO - Epoch(val) [120][350/407] eta: 0:00:07 time: 0.123146 data_time: 0.068511 memory: 772 2022/10/13 22:59:22 - mmengine - INFO - Epoch(val) [120][400/407] eta: 0:00:00 time: 0.121336 data_time: 0.065489 memory: 772 2022/10/13 22:59:59 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 23:00:13 - mmengine - INFO - Epoch(val) [120][407/407] coco/AP: 0.616003 coco/AP .5: 0.857550 coco/AP .75: 0.679282 coco/AP (M): 0.575390 coco/AP (L): 0.685900 coco/AR: 0.679975 coco/AR .5: 0.901763 coco/AR .75: 0.743230 coco/AR (M): 0.631439 coco/AR (L): 0.747826 2022/10/13 23:00:31 - mmengine - INFO - Epoch(train) [121][50/293] lr: 5.000000e-04 eta: 2:19:13 time: 0.377591 data_time: 0.087492 memory: 4980 loss_kpt: 0.000857 acc_pose: 0.767036 loss: 0.000857 2022/10/13 23:00:50 - mmengine - INFO - Epoch(train) [121][100/293] lr: 5.000000e-04 eta: 2:18:59 time: 0.360806 data_time: 0.074614 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.728579 loss: 0.000836 2022/10/13 23:01:08 - mmengine - INFO - Epoch(train) [121][150/293] lr: 5.000000e-04 eta: 2:18:45 time: 0.372475 data_time: 0.077824 memory: 4980 loss_kpt: 0.000864 acc_pose: 0.761396 loss: 0.000864 2022/10/13 23:01:26 - mmengine - INFO - Epoch(train) [121][200/293] lr: 5.000000e-04 eta: 2:18:31 time: 0.361628 data_time: 0.072549 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.764049 loss: 0.000850 2022/10/13 23:01:44 - mmengine - INFO - Epoch(train) [121][250/293] lr: 5.000000e-04 eta: 2:18:16 time: 0.356537 data_time: 0.066978 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.752343 loss: 0.000853 2022/10/13 23:02:00 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:02:19 - mmengine - INFO - Epoch(train) [122][50/293] lr: 5.000000e-04 eta: 2:17:39 time: 0.371931 data_time: 0.122008 memory: 4980 loss_kpt: 0.000834 acc_pose: 0.758937 loss: 0.000834 2022/10/13 23:02:36 - mmengine - INFO - Epoch(train) [122][100/293] lr: 5.000000e-04 eta: 2:17:24 time: 0.356431 data_time: 0.089028 memory: 4980 loss_kpt: 0.000840 acc_pose: 0.708340 loss: 0.000840 2022/10/13 23:02:54 - mmengine - INFO - Epoch(train) [122][150/293] lr: 5.000000e-04 eta: 2:17:10 time: 0.357863 data_time: 0.118167 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.768809 loss: 0.000850 2022/10/13 23:03:12 - mmengine - INFO - Epoch(train) [122][200/293] lr: 5.000000e-04 eta: 2:16:55 time: 0.358663 data_time: 0.064956 memory: 4980 loss_kpt: 0.000831 acc_pose: 0.756681 loss: 0.000831 2022/10/13 23:03:30 - mmengine - INFO - Epoch(train) [122][250/293] lr: 5.000000e-04 eta: 2:16:41 time: 0.358240 data_time: 0.074801 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.763379 loss: 0.000846 2022/10/13 23:03:46 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:04:04 - mmengine - INFO - Epoch(train) [123][50/293] lr: 5.000000e-04 eta: 2:16:03 time: 0.367809 data_time: 0.096116 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.675845 loss: 0.000838 2022/10/13 23:04:22 - mmengine - INFO - Epoch(train) [123][100/293] lr: 5.000000e-04 eta: 2:15:49 time: 0.355410 data_time: 0.072677 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.690412 loss: 0.000853 2022/10/13 23:04:40 - mmengine - INFO - Epoch(train) [123][150/293] lr: 5.000000e-04 eta: 2:15:35 time: 0.358745 data_time: 0.072191 memory: 4980 loss_kpt: 0.000863 acc_pose: 0.735701 loss: 0.000863 2022/10/13 23:04:58 - mmengine - INFO - Epoch(train) [123][200/293] lr: 5.000000e-04 eta: 2:15:20 time: 0.363292 data_time: 0.080098 memory: 4980 loss_kpt: 0.000848 acc_pose: 0.705739 loss: 0.000848 2022/10/13 23:05:16 - mmengine - INFO - Epoch(train) [123][250/293] lr: 5.000000e-04 eta: 2:15:06 time: 0.363763 data_time: 0.076266 memory: 4980 loss_kpt: 0.000852 acc_pose: 0.682487 loss: 0.000852 2022/10/13 23:05:18 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:05:32 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:05:50 - mmengine - INFO - Epoch(train) [124][50/293] lr: 5.000000e-04 eta: 2:14:29 time: 0.376557 data_time: 0.086116 memory: 4980 loss_kpt: 0.000839 acc_pose: 0.703158 loss: 0.000839 2022/10/13 23:06:09 - mmengine - INFO - Epoch(train) [124][100/293] lr: 5.000000e-04 eta: 2:14:15 time: 0.363610 data_time: 0.080927 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.730686 loss: 0.000846 2022/10/13 23:06:26 - mmengine - INFO - Epoch(train) [124][150/293] lr: 5.000000e-04 eta: 2:14:00 time: 0.358492 data_time: 0.078506 memory: 4980 loss_kpt: 0.000851 acc_pose: 0.745967 loss: 0.000851 2022/10/13 23:06:45 - mmengine - INFO - Epoch(train) [124][200/293] lr: 5.000000e-04 eta: 2:13:46 time: 0.361480 data_time: 0.077549 memory: 4980 loss_kpt: 0.000856 acc_pose: 0.779689 loss: 0.000856 2022/10/13 23:07:02 - mmengine - INFO - Epoch(train) [124][250/293] lr: 5.000000e-04 eta: 2:13:32 time: 0.358312 data_time: 0.085702 memory: 4980 loss_kpt: 0.000851 acc_pose: 0.819665 loss: 0.000851 2022/10/13 23:07:17 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:07:36 - mmengine - INFO - Epoch(train) [125][50/293] lr: 5.000000e-04 eta: 2:12:55 time: 0.376943 data_time: 0.092823 memory: 4980 loss_kpt: 0.000844 acc_pose: 0.725970 loss: 0.000844 2022/10/13 23:07:54 - mmengine - INFO - Epoch(train) [125][100/293] lr: 5.000000e-04 eta: 2:12:40 time: 0.363364 data_time: 0.078022 memory: 4980 loss_kpt: 0.000842 acc_pose: 0.708873 loss: 0.000842 2022/10/13 23:08:13 - mmengine - INFO - Epoch(train) [125][150/293] lr: 5.000000e-04 eta: 2:12:26 time: 0.365830 data_time: 0.069684 memory: 4980 loss_kpt: 0.000858 acc_pose: 0.751443 loss: 0.000858 2022/10/13 23:08:31 - mmengine - INFO - Epoch(train) [125][200/293] lr: 5.000000e-04 eta: 2:12:12 time: 0.358833 data_time: 0.074233 memory: 4980 loss_kpt: 0.000839 acc_pose: 0.776876 loss: 0.000839 2022/10/13 23:08:49 - mmengine - INFO - Epoch(train) [125][250/293] lr: 5.000000e-04 eta: 2:11:58 time: 0.369214 data_time: 0.076553 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.690538 loss: 0.000847 2022/10/13 23:09:05 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:09:24 - mmengine - INFO - Epoch(train) [126][50/293] lr: 5.000000e-04 eta: 2:11:21 time: 0.379582 data_time: 0.079906 memory: 4980 loss_kpt: 0.000844 acc_pose: 0.761142 loss: 0.000844 2022/10/13 23:09:42 - mmengine - INFO - Epoch(train) [126][100/293] lr: 5.000000e-04 eta: 2:11:07 time: 0.359589 data_time: 0.076822 memory: 4980 loss_kpt: 0.000834 acc_pose: 0.776107 loss: 0.000834 2022/10/13 23:10:00 - mmengine - INFO - Epoch(train) [126][150/293] lr: 5.000000e-04 eta: 2:10:52 time: 0.365843 data_time: 0.076255 memory: 4980 loss_kpt: 0.000842 acc_pose: 0.735360 loss: 0.000842 2022/10/13 23:10:18 - mmengine - INFO - Epoch(train) [126][200/293] lr: 5.000000e-04 eta: 2:10:38 time: 0.362921 data_time: 0.080615 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.766528 loss: 0.000835 2022/10/13 23:10:36 - mmengine - INFO - Epoch(train) [126][250/293] lr: 5.000000e-04 eta: 2:10:24 time: 0.366559 data_time: 0.087139 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.733661 loss: 0.000838 2022/10/13 23:10:52 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:11:11 - mmengine - INFO - Epoch(train) [127][50/293] lr: 5.000000e-04 eta: 2:09:47 time: 0.379184 data_time: 0.093273 memory: 4980 loss_kpt: 0.000859 acc_pose: 0.733272 loss: 0.000859 2022/10/13 23:11:22 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:11:29 - mmengine - INFO - Epoch(train) [127][100/293] lr: 5.000000e-04 eta: 2:09:33 time: 0.357967 data_time: 0.079771 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.727426 loss: 0.000847 2022/10/13 23:11:47 - mmengine - INFO - Epoch(train) [127][150/293] lr: 5.000000e-04 eta: 2:09:18 time: 0.362432 data_time: 0.075090 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.672952 loss: 0.000861 2022/10/13 23:12:05 - mmengine - INFO - Epoch(train) [127][200/293] lr: 5.000000e-04 eta: 2:09:04 time: 0.365923 data_time: 0.077723 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.727683 loss: 0.000847 2022/10/13 23:12:23 - mmengine - INFO - Epoch(train) [127][250/293] lr: 5.000000e-04 eta: 2:08:50 time: 0.364313 data_time: 0.079508 memory: 4980 loss_kpt: 0.000843 acc_pose: 0.690261 loss: 0.000843 2022/10/13 23:12:39 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:12:58 - mmengine - INFO - Epoch(train) [128][50/293] lr: 5.000000e-04 eta: 2:08:13 time: 0.376452 data_time: 0.088374 memory: 4980 loss_kpt: 0.000851 acc_pose: 0.707986 loss: 0.000851 2022/10/13 23:13:16 - mmengine - INFO - Epoch(train) [128][100/293] lr: 5.000000e-04 eta: 2:07:59 time: 0.360634 data_time: 0.064554 memory: 4980 loss_kpt: 0.000841 acc_pose: 0.782969 loss: 0.000841 2022/10/13 23:13:34 - mmengine - INFO - Epoch(train) [128][150/293] lr: 5.000000e-04 eta: 2:07:44 time: 0.358851 data_time: 0.069223 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.718952 loss: 0.000850 2022/10/13 23:13:51 - mmengine - INFO - Epoch(train) [128][200/293] lr: 5.000000e-04 eta: 2:07:30 time: 0.354607 data_time: 0.083632 memory: 4980 loss_kpt: 0.000833 acc_pose: 0.780672 loss: 0.000833 2022/10/13 23:14:09 - mmengine - INFO - Epoch(train) [128][250/293] lr: 5.000000e-04 eta: 2:07:15 time: 0.360194 data_time: 0.072175 memory: 4980 loss_kpt: 0.000851 acc_pose: 0.779435 loss: 0.000851 2022/10/13 23:14:25 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:14:44 - mmengine - INFO - Epoch(train) [129][50/293] lr: 5.000000e-04 eta: 2:06:39 time: 0.378308 data_time: 0.088847 memory: 4980 loss_kpt: 0.000842 acc_pose: 0.698538 loss: 0.000842 2022/10/13 23:15:02 - mmengine - INFO - Epoch(train) [129][100/293] lr: 5.000000e-04 eta: 2:06:25 time: 0.359752 data_time: 0.080725 memory: 4980 loss_kpt: 0.000837 acc_pose: 0.760136 loss: 0.000837 2022/10/13 23:15:20 - mmengine - INFO - Epoch(train) [129][150/293] lr: 5.000000e-04 eta: 2:06:10 time: 0.364454 data_time: 0.076873 memory: 4980 loss_kpt: 0.000825 acc_pose: 0.766924 loss: 0.000825 2022/10/13 23:15:38 - mmengine - INFO - Epoch(train) [129][200/293] lr: 5.000000e-04 eta: 2:05:56 time: 0.361913 data_time: 0.091413 memory: 4980 loss_kpt: 0.000858 acc_pose: 0.761478 loss: 0.000858 2022/10/13 23:15:56 - mmengine - INFO - Epoch(train) [129][250/293] lr: 5.000000e-04 eta: 2:05:41 time: 0.360394 data_time: 0.109126 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.748446 loss: 0.000853 2022/10/13 23:16:11 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:16:30 - mmengine - INFO - Epoch(train) [130][50/293] lr: 5.000000e-04 eta: 2:05:05 time: 0.377412 data_time: 0.096269 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.731682 loss: 0.000853 2022/10/13 23:16:49 - mmengine - INFO - Epoch(train) [130][100/293] lr: 5.000000e-04 eta: 2:04:51 time: 0.377438 data_time: 0.072002 memory: 4980 loss_kpt: 0.000852 acc_pose: 0.754574 loss: 0.000852 2022/10/13 23:17:07 - mmengine - INFO - Epoch(train) [130][150/293] lr: 5.000000e-04 eta: 2:04:37 time: 0.367265 data_time: 0.069194 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.741086 loss: 0.000847 2022/10/13 23:17:25 - mmengine - INFO - Epoch(train) [130][200/293] lr: 5.000000e-04 eta: 2:04:23 time: 0.363776 data_time: 0.069541 memory: 4980 loss_kpt: 0.000840 acc_pose: 0.747072 loss: 0.000840 2022/10/13 23:17:26 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:17:43 - mmengine - INFO - Epoch(train) [130][250/293] lr: 5.000000e-04 eta: 2:04:08 time: 0.351584 data_time: 0.070315 memory: 4980 loss_kpt: 0.000844 acc_pose: 0.682276 loss: 0.000844 2022/10/13 23:17:58 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:17:58 - mmengine - INFO - Saving checkpoint at 130 epochs 2022/10/13 23:18:07 - mmengine - INFO - Epoch(val) [130][50/407] eta: 0:00:44 time: 0.125369 data_time: 0.070736 memory: 4980 2022/10/13 23:18:13 - mmengine - INFO - Epoch(val) [130][100/407] eta: 0:00:37 time: 0.122895 data_time: 0.067777 memory: 772 2022/10/13 23:18:19 - mmengine - INFO - Epoch(val) [130][150/407] eta: 0:00:32 time: 0.124699 data_time: 0.069902 memory: 772 2022/10/13 23:18:25 - mmengine - INFO - Epoch(val) [130][200/407] eta: 0:00:26 time: 0.127749 data_time: 0.070943 memory: 772 2022/10/13 23:18:32 - mmengine - INFO - Epoch(val) [130][250/407] eta: 0:00:19 time: 0.122848 data_time: 0.068706 memory: 772 2022/10/13 23:18:38 - mmengine - INFO - Epoch(val) [130][300/407] eta: 0:00:13 time: 0.128952 data_time: 0.075088 memory: 772 2022/10/13 23:18:44 - mmengine - INFO - Epoch(val) [130][350/407] eta: 0:00:07 time: 0.128577 data_time: 0.072951 memory: 772 2022/10/13 23:18:50 - mmengine - INFO - Epoch(val) [130][400/407] eta: 0:00:00 time: 0.120540 data_time: 0.065689 memory: 772 2022/10/13 23:19:27 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 23:19:40 - mmengine - INFO - Epoch(val) [130][407/407] coco/AP: 0.621187 coco/AP .5: 0.861379 coco/AP .75: 0.683683 coco/AP (M): 0.582502 coco/AP (L): 0.689877 coco/AR: 0.684162 coco/AR .5: 0.904754 coco/AR .75: 0.745907 coco/AR (M): 0.636465 coco/AR (L): 0.751691 2022/10/13 23:19:40 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_110.pth is removed 2022/10/13 23:19:42 - mmengine - INFO - The best checkpoint with 0.6212 coco/AP at 130 epoch is saved to best_coco/AP_epoch_130.pth. 2022/10/13 23:20:01 - mmengine - INFO - Epoch(train) [131][50/293] lr: 5.000000e-04 eta: 2:03:32 time: 0.379529 data_time: 0.129021 memory: 4980 loss_kpt: 0.000840 acc_pose: 0.738457 loss: 0.000840 2022/10/13 23:20:19 - mmengine - INFO - Epoch(train) [131][100/293] lr: 5.000000e-04 eta: 2:03:17 time: 0.354956 data_time: 0.075044 memory: 4980 loss_kpt: 0.000844 acc_pose: 0.752994 loss: 0.000844 2022/10/13 23:20:37 - mmengine - INFO - Epoch(train) [131][150/293] lr: 5.000000e-04 eta: 2:03:03 time: 0.358180 data_time: 0.066713 memory: 4980 loss_kpt: 0.000831 acc_pose: 0.729731 loss: 0.000831 2022/10/13 23:20:54 - mmengine - INFO - Epoch(train) [131][200/293] lr: 5.000000e-04 eta: 2:02:48 time: 0.350760 data_time: 0.083784 memory: 4980 loss_kpt: 0.000840 acc_pose: 0.739774 loss: 0.000840 2022/10/13 23:21:12 - mmengine - INFO - Epoch(train) [131][250/293] lr: 5.000000e-04 eta: 2:02:33 time: 0.356347 data_time: 0.117387 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.721997 loss: 0.000847 2022/10/13 23:21:28 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:21:47 - mmengine - INFO - Epoch(train) [132][50/293] lr: 5.000000e-04 eta: 2:01:57 time: 0.388288 data_time: 0.091264 memory: 4980 loss_kpt: 0.000843 acc_pose: 0.748596 loss: 0.000843 2022/10/13 23:22:05 - mmengine - INFO - Epoch(train) [132][100/293] lr: 5.000000e-04 eta: 2:01:43 time: 0.362167 data_time: 0.076456 memory: 4980 loss_kpt: 0.000834 acc_pose: 0.749183 loss: 0.000834 2022/10/13 23:22:23 - mmengine - INFO - Epoch(train) [132][150/293] lr: 5.000000e-04 eta: 2:01:28 time: 0.359932 data_time: 0.074749 memory: 4980 loss_kpt: 0.000849 acc_pose: 0.748428 loss: 0.000849 2022/10/13 23:22:41 - mmengine - INFO - Epoch(train) [132][200/293] lr: 5.000000e-04 eta: 2:01:14 time: 0.364466 data_time: 0.080061 memory: 4980 loss_kpt: 0.000840 acc_pose: 0.764233 loss: 0.000840 2022/10/13 23:22:59 - mmengine - INFO - Epoch(train) [132][250/293] lr: 5.000000e-04 eta: 2:00:59 time: 0.355142 data_time: 0.070255 memory: 4980 loss_kpt: 0.000851 acc_pose: 0.777964 loss: 0.000851 2022/10/13 23:23:14 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:23:33 - mmengine - INFO - Epoch(train) [133][50/293] lr: 5.000000e-04 eta: 2:00:24 time: 0.386909 data_time: 0.087765 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.733801 loss: 0.000847 2022/10/13 23:23:51 - mmengine - INFO - Epoch(train) [133][100/293] lr: 5.000000e-04 eta: 2:00:09 time: 0.352747 data_time: 0.070118 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.739704 loss: 0.000847 2022/10/13 23:24:09 - mmengine - INFO - Epoch(train) [133][150/293] lr: 5.000000e-04 eta: 1:59:54 time: 0.360086 data_time: 0.075339 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.677765 loss: 0.000847 2022/10/13 23:24:28 - mmengine - INFO - Epoch(train) [133][200/293] lr: 5.000000e-04 eta: 1:59:40 time: 0.374310 data_time: 0.070119 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.782259 loss: 0.000835 2022/10/13 23:24:46 - mmengine - INFO - Epoch(train) [133][250/293] lr: 5.000000e-04 eta: 1:59:26 time: 0.367702 data_time: 0.074221 memory: 4980 loss_kpt: 0.000834 acc_pose: 0.756541 loss: 0.000834 2022/10/13 23:25:02 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:25:14 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:25:20 - mmengine - INFO - Epoch(train) [134][50/293] lr: 5.000000e-04 eta: 1:58:50 time: 0.378830 data_time: 0.139708 memory: 4980 loss_kpt: 0.000843 acc_pose: 0.721210 loss: 0.000843 2022/10/13 23:25:39 - mmengine - INFO - Epoch(train) [134][100/293] lr: 5.000000e-04 eta: 1:58:36 time: 0.370739 data_time: 0.130207 memory: 4980 loss_kpt: 0.000829 acc_pose: 0.746188 loss: 0.000829 2022/10/13 23:25:57 - mmengine - INFO - Epoch(train) [134][150/293] lr: 5.000000e-04 eta: 1:58:21 time: 0.351393 data_time: 0.092630 memory: 4980 loss_kpt: 0.000834 acc_pose: 0.743830 loss: 0.000834 2022/10/13 23:26:15 - mmengine - INFO - Epoch(train) [134][200/293] lr: 5.000000e-04 eta: 1:58:07 time: 0.364078 data_time: 0.127044 memory: 4980 loss_kpt: 0.000844 acc_pose: 0.707562 loss: 0.000844 2022/10/13 23:26:33 - mmengine - INFO - Epoch(train) [134][250/293] lr: 5.000000e-04 eta: 1:57:52 time: 0.362957 data_time: 0.108728 memory: 4980 loss_kpt: 0.000849 acc_pose: 0.740288 loss: 0.000849 2022/10/13 23:26:48 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:27:07 - mmengine - INFO - Epoch(train) [135][50/293] lr: 5.000000e-04 eta: 1:57:17 time: 0.373335 data_time: 0.097296 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.714326 loss: 0.000836 2022/10/13 23:27:26 - mmengine - INFO - Epoch(train) [135][100/293] lr: 5.000000e-04 eta: 1:57:02 time: 0.369515 data_time: 0.079102 memory: 4980 loss_kpt: 0.000867 acc_pose: 0.655587 loss: 0.000867 2022/10/13 23:27:44 - mmengine - INFO - Epoch(train) [135][150/293] lr: 5.000000e-04 eta: 1:56:48 time: 0.363388 data_time: 0.073840 memory: 4980 loss_kpt: 0.000834 acc_pose: 0.781887 loss: 0.000834 2022/10/13 23:28:02 - mmengine - INFO - Epoch(train) [135][200/293] lr: 5.000000e-04 eta: 1:56:33 time: 0.358594 data_time: 0.085487 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.713174 loss: 0.000850 2022/10/13 23:28:20 - mmengine - INFO - Epoch(train) [135][250/293] lr: 5.000000e-04 eta: 1:56:18 time: 0.358772 data_time: 0.073061 memory: 4980 loss_kpt: 0.000826 acc_pose: 0.755512 loss: 0.000826 2022/10/13 23:28:35 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:28:54 - mmengine - INFO - Epoch(train) [136][50/293] lr: 5.000000e-04 eta: 1:55:43 time: 0.384461 data_time: 0.096260 memory: 4980 loss_kpt: 0.000848 acc_pose: 0.758004 loss: 0.000848 2022/10/13 23:29:12 - mmengine - INFO - Epoch(train) [136][100/293] lr: 5.000000e-04 eta: 1:55:28 time: 0.356725 data_time: 0.111923 memory: 4980 loss_kpt: 0.000830 acc_pose: 0.730741 loss: 0.000830 2022/10/13 23:29:31 - mmengine - INFO - Epoch(train) [136][150/293] lr: 5.000000e-04 eta: 1:55:14 time: 0.377855 data_time: 0.080837 memory: 4980 loss_kpt: 0.000832 acc_pose: 0.719759 loss: 0.000832 2022/10/13 23:29:49 - mmengine - INFO - Epoch(train) [136][200/293] lr: 5.000000e-04 eta: 1:55:00 time: 0.365160 data_time: 0.072159 memory: 4980 loss_kpt: 0.000832 acc_pose: 0.784618 loss: 0.000832 2022/10/13 23:30:08 - mmengine - INFO - Epoch(train) [136][250/293] lr: 5.000000e-04 eta: 1:54:45 time: 0.367965 data_time: 0.072827 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.774782 loss: 0.000835 2022/10/13 23:30:23 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:30:42 - mmengine - INFO - Epoch(train) [137][50/293] lr: 5.000000e-04 eta: 1:54:10 time: 0.377148 data_time: 0.092828 memory: 4980 loss_kpt: 0.000831 acc_pose: 0.763991 loss: 0.000831 2022/10/13 23:31:01 - mmengine - INFO - Epoch(train) [137][100/293] lr: 5.000000e-04 eta: 1:53:56 time: 0.372374 data_time: 0.087878 memory: 4980 loss_kpt: 0.000845 acc_pose: 0.734407 loss: 0.000845 2022/10/13 23:31:18 - mmengine - INFO - Epoch(train) [137][150/293] lr: 5.000000e-04 eta: 1:53:41 time: 0.355505 data_time: 0.067570 memory: 4980 loss_kpt: 0.000842 acc_pose: 0.753449 loss: 0.000842 2022/10/13 23:31:19 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:31:38 - mmengine - INFO - Epoch(train) [137][200/293] lr: 5.000000e-04 eta: 1:53:27 time: 0.384524 data_time: 0.080059 memory: 4980 loss_kpt: 0.000842 acc_pose: 0.779134 loss: 0.000842 2022/10/13 23:31:56 - mmengine - INFO - Epoch(train) [137][250/293] lr: 5.000000e-04 eta: 1:53:12 time: 0.367302 data_time: 0.080984 memory: 4980 loss_kpt: 0.000859 acc_pose: 0.717221 loss: 0.000859 2022/10/13 23:32:12 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:32:31 - mmengine - INFO - Epoch(train) [138][50/293] lr: 5.000000e-04 eta: 1:52:37 time: 0.379149 data_time: 0.102523 memory: 4980 loss_kpt: 0.000848 acc_pose: 0.766567 loss: 0.000848 2022/10/13 23:32:49 - mmengine - INFO - Epoch(train) [138][100/293] lr: 5.000000e-04 eta: 1:52:23 time: 0.359602 data_time: 0.084671 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.794698 loss: 0.000838 2022/10/13 23:33:07 - mmengine - INFO - Epoch(train) [138][150/293] lr: 5.000000e-04 eta: 1:52:08 time: 0.360987 data_time: 0.073962 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.764744 loss: 0.000835 2022/10/13 23:33:25 - mmengine - INFO - Epoch(train) [138][200/293] lr: 5.000000e-04 eta: 1:51:53 time: 0.358340 data_time: 0.071586 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.743326 loss: 0.000836 2022/10/13 23:33:43 - mmengine - INFO - Epoch(train) [138][250/293] lr: 5.000000e-04 eta: 1:51:39 time: 0.359151 data_time: 0.082067 memory: 4980 loss_kpt: 0.000849 acc_pose: 0.719718 loss: 0.000849 2022/10/13 23:33:58 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:34:17 - mmengine - INFO - Epoch(train) [139][50/293] lr: 5.000000e-04 eta: 1:51:03 time: 0.374142 data_time: 0.100518 memory: 4980 loss_kpt: 0.000860 acc_pose: 0.729509 loss: 0.000860 2022/10/13 23:34:35 - mmengine - INFO - Epoch(train) [139][100/293] lr: 5.000000e-04 eta: 1:50:49 time: 0.352328 data_time: 0.071924 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.705866 loss: 0.000836 2022/10/13 23:34:53 - mmengine - INFO - Epoch(train) [139][150/293] lr: 5.000000e-04 eta: 1:50:34 time: 0.370555 data_time: 0.073807 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.732843 loss: 0.000847 2022/10/13 23:35:11 - mmengine - INFO - Epoch(train) [139][200/293] lr: 5.000000e-04 eta: 1:50:19 time: 0.363208 data_time: 0.080284 memory: 4980 loss_kpt: 0.000841 acc_pose: 0.682629 loss: 0.000841 2022/10/13 23:35:30 - mmengine - INFO - Epoch(train) [139][250/293] lr: 5.000000e-04 eta: 1:50:05 time: 0.373955 data_time: 0.081452 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.749506 loss: 0.000836 2022/10/13 23:35:45 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:36:04 - mmengine - INFO - Epoch(train) [140][50/293] lr: 5.000000e-04 eta: 1:49:30 time: 0.376945 data_time: 0.146549 memory: 4980 loss_kpt: 0.000839 acc_pose: 0.709172 loss: 0.000839 2022/10/13 23:36:23 - mmengine - INFO - Epoch(train) [140][100/293] lr: 5.000000e-04 eta: 1:49:16 time: 0.374117 data_time: 0.131099 memory: 4980 loss_kpt: 0.000829 acc_pose: 0.705296 loss: 0.000829 2022/10/13 23:36:41 - mmengine - INFO - Epoch(train) [140][150/293] lr: 5.000000e-04 eta: 1:49:01 time: 0.363361 data_time: 0.112965 memory: 4980 loss_kpt: 0.000839 acc_pose: 0.755070 loss: 0.000839 2022/10/13 23:36:59 - mmengine - INFO - Epoch(train) [140][200/293] lr: 5.000000e-04 eta: 1:48:47 time: 0.366703 data_time: 0.132450 memory: 4980 loss_kpt: 0.000840 acc_pose: 0.725878 loss: 0.000840 2022/10/13 23:37:18 - mmengine - INFO - Epoch(train) [140][250/293] lr: 5.000000e-04 eta: 1:48:32 time: 0.367808 data_time: 0.127760 memory: 4980 loss_kpt: 0.000844 acc_pose: 0.720504 loss: 0.000844 2022/10/13 23:37:26 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:37:33 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:37:33 - mmengine - INFO - Saving checkpoint at 140 epochs 2022/10/13 23:37:41 - mmengine - INFO - Epoch(val) [140][50/407] eta: 0:00:46 time: 0.130676 data_time: 0.074813 memory: 4980 2022/10/13 23:37:47 - mmengine - INFO - Epoch(val) [140][100/407] eta: 0:00:37 time: 0.123122 data_time: 0.066010 memory: 772 2022/10/13 23:37:53 - mmengine - INFO - Epoch(val) [140][150/407] eta: 0:00:31 time: 0.123665 data_time: 0.069303 memory: 772 2022/10/13 23:38:00 - mmengine - INFO - Epoch(val) [140][200/407] eta: 0:00:25 time: 0.122105 data_time: 0.066116 memory: 772 2022/10/13 23:38:06 - mmengine - INFO - Epoch(val) [140][250/407] eta: 0:00:19 time: 0.121896 data_time: 0.066291 memory: 772 2022/10/13 23:38:12 - mmengine - INFO - Epoch(val) [140][300/407] eta: 0:00:12 time: 0.119096 data_time: 0.064118 memory: 772 2022/10/13 23:38:18 - mmengine - INFO - Epoch(val) [140][350/407] eta: 0:00:07 time: 0.126832 data_time: 0.071678 memory: 772 2022/10/13 23:38:24 - mmengine - INFO - Epoch(val) [140][400/407] eta: 0:00:00 time: 0.117645 data_time: 0.064276 memory: 772 2022/10/13 23:39:00 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 23:39:14 - mmengine - INFO - Epoch(val) [140][407/407] coco/AP: 0.622752 coco/AP .5: 0.860867 coco/AP .75: 0.686105 coco/AP (M): 0.580967 coco/AP (L): 0.694191 coco/AR: 0.684588 coco/AR .5: 0.906171 coco/AR .75: 0.746064 coco/AR (M): 0.635346 coco/AR (L): 0.753512 2022/10/13 23:39:14 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_130.pth is removed 2022/10/13 23:39:16 - mmengine - INFO - The best checkpoint with 0.6228 coco/AP at 140 epoch is saved to best_coco/AP_epoch_140.pth. 2022/10/13 23:39:34 - mmengine - INFO - Epoch(train) [141][50/293] lr: 5.000000e-04 eta: 1:47:57 time: 0.375677 data_time: 0.133396 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.742342 loss: 0.000846 2022/10/13 23:39:52 - mmengine - INFO - Epoch(train) [141][100/293] lr: 5.000000e-04 eta: 1:47:42 time: 0.352822 data_time: 0.114706 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.779868 loss: 0.000838 2022/10/13 23:40:10 - mmengine - INFO - Epoch(train) [141][150/293] lr: 5.000000e-04 eta: 1:47:28 time: 0.366503 data_time: 0.132227 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.743459 loss: 0.000835 2022/10/13 23:40:29 - mmengine - INFO - Epoch(train) [141][200/293] lr: 5.000000e-04 eta: 1:47:13 time: 0.364571 data_time: 0.125528 memory: 4980 loss_kpt: 0.000826 acc_pose: 0.757382 loss: 0.000826 2022/10/13 23:40:47 - mmengine - INFO - Epoch(train) [141][250/293] lr: 5.000000e-04 eta: 1:46:58 time: 0.360679 data_time: 0.071252 memory: 4980 loss_kpt: 0.000832 acc_pose: 0.743702 loss: 0.000832 2022/10/13 23:41:02 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:41:21 - mmengine - INFO - Epoch(train) [142][50/293] lr: 5.000000e-04 eta: 1:46:24 time: 0.385940 data_time: 0.093117 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.716743 loss: 0.000846 2022/10/13 23:41:39 - mmengine - INFO - Epoch(train) [142][100/293] lr: 5.000000e-04 eta: 1:46:09 time: 0.357733 data_time: 0.068805 memory: 4980 loss_kpt: 0.000852 acc_pose: 0.670530 loss: 0.000852 2022/10/13 23:41:57 - mmengine - INFO - Epoch(train) [142][150/293] lr: 5.000000e-04 eta: 1:45:54 time: 0.359020 data_time: 0.069707 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.812509 loss: 0.000836 2022/10/13 23:42:15 - mmengine - INFO - Epoch(train) [142][200/293] lr: 5.000000e-04 eta: 1:45:39 time: 0.360159 data_time: 0.070305 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.753691 loss: 0.000850 2022/10/13 23:42:34 - mmengine - INFO - Epoch(train) [142][250/293] lr: 5.000000e-04 eta: 1:45:25 time: 0.368132 data_time: 0.075233 memory: 4980 loss_kpt: 0.000848 acc_pose: 0.733856 loss: 0.000848 2022/10/13 23:42:49 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:43:08 - mmengine - INFO - Epoch(train) [143][50/293] lr: 5.000000e-04 eta: 1:44:50 time: 0.377916 data_time: 0.098104 memory: 4980 loss_kpt: 0.000841 acc_pose: 0.716963 loss: 0.000841 2022/10/13 23:43:26 - mmengine - INFO - Epoch(train) [143][100/293] lr: 5.000000e-04 eta: 1:44:36 time: 0.368308 data_time: 0.098204 memory: 4980 loss_kpt: 0.000845 acc_pose: 0.738991 loss: 0.000845 2022/10/13 23:43:44 - mmengine - INFO - Epoch(train) [143][150/293] lr: 5.000000e-04 eta: 1:44:21 time: 0.359454 data_time: 0.112668 memory: 4980 loss_kpt: 0.000831 acc_pose: 0.752488 loss: 0.000831 2022/10/13 23:44:03 - mmengine - INFO - Epoch(train) [143][200/293] lr: 5.000000e-04 eta: 1:44:06 time: 0.370992 data_time: 0.089870 memory: 4980 loss_kpt: 0.000831 acc_pose: 0.731498 loss: 0.000831 2022/10/13 23:44:21 - mmengine - INFO - Epoch(train) [143][250/293] lr: 5.000000e-04 eta: 1:43:52 time: 0.358111 data_time: 0.074763 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.700334 loss: 0.000836 2022/10/13 23:44:37 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:44:55 - mmengine - INFO - Epoch(train) [144][50/293] lr: 5.000000e-04 eta: 1:43:17 time: 0.368850 data_time: 0.127123 memory: 4980 loss_kpt: 0.000826 acc_pose: 0.780047 loss: 0.000826 2022/10/13 23:45:14 - mmengine - INFO - Epoch(train) [144][100/293] lr: 5.000000e-04 eta: 1:43:02 time: 0.367687 data_time: 0.149573 memory: 4980 loss_kpt: 0.000844 acc_pose: 0.758268 loss: 0.000844 2022/10/13 23:45:14 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:45:31 - mmengine - INFO - Epoch(train) [144][150/293] lr: 5.000000e-04 eta: 1:42:47 time: 0.357721 data_time: 0.136422 memory: 4980 loss_kpt: 0.000845 acc_pose: 0.743522 loss: 0.000845 2022/10/13 23:45:49 - mmengine - INFO - Epoch(train) [144][200/293] lr: 5.000000e-04 eta: 1:42:33 time: 0.358063 data_time: 0.106005 memory: 4980 loss_kpt: 0.000822 acc_pose: 0.681059 loss: 0.000822 2022/10/13 23:46:08 - mmengine - INFO - Epoch(train) [144][250/293] lr: 5.000000e-04 eta: 1:42:18 time: 0.363853 data_time: 0.070758 memory: 4980 loss_kpt: 0.000842 acc_pose: 0.724230 loss: 0.000842 2022/10/13 23:46:23 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:46:41 - mmengine - INFO - Epoch(train) [145][50/293] lr: 5.000000e-04 eta: 1:41:43 time: 0.375870 data_time: 0.084984 memory: 4980 loss_kpt: 0.000837 acc_pose: 0.741897 loss: 0.000837 2022/10/13 23:47:00 - mmengine - INFO - Epoch(train) [145][100/293] lr: 5.000000e-04 eta: 1:41:29 time: 0.365713 data_time: 0.071399 memory: 4980 loss_kpt: 0.000856 acc_pose: 0.737417 loss: 0.000856 2022/10/13 23:47:18 - mmengine - INFO - Epoch(train) [145][150/293] lr: 5.000000e-04 eta: 1:41:14 time: 0.357215 data_time: 0.074784 memory: 4980 loss_kpt: 0.000820 acc_pose: 0.779970 loss: 0.000820 2022/10/13 23:47:36 - mmengine - INFO - Epoch(train) [145][200/293] lr: 5.000000e-04 eta: 1:40:59 time: 0.358934 data_time: 0.076072 memory: 4980 loss_kpt: 0.000839 acc_pose: 0.673310 loss: 0.000839 2022/10/13 23:47:53 - mmengine - INFO - Epoch(train) [145][250/293] lr: 5.000000e-04 eta: 1:40:44 time: 0.355981 data_time: 0.080115 memory: 4980 loss_kpt: 0.000819 acc_pose: 0.772712 loss: 0.000819 2022/10/13 23:48:09 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:48:27 - mmengine - INFO - Epoch(train) [146][50/293] lr: 5.000000e-04 eta: 1:40:10 time: 0.364967 data_time: 0.117181 memory: 4980 loss_kpt: 0.000845 acc_pose: 0.719574 loss: 0.000845 2022/10/13 23:48:45 - mmengine - INFO - Epoch(train) [146][100/293] lr: 5.000000e-04 eta: 1:39:55 time: 0.355293 data_time: 0.072523 memory: 4980 loss_kpt: 0.000855 acc_pose: 0.716120 loss: 0.000855 2022/10/13 23:49:03 - mmengine - INFO - Epoch(train) [146][150/293] lr: 5.000000e-04 eta: 1:39:40 time: 0.359638 data_time: 0.074601 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.722062 loss: 0.000847 2022/10/13 23:49:20 - mmengine - INFO - Epoch(train) [146][200/293] lr: 5.000000e-04 eta: 1:39:25 time: 0.349409 data_time: 0.071031 memory: 4980 loss_kpt: 0.000832 acc_pose: 0.715762 loss: 0.000832 2022/10/13 23:49:38 - mmengine - INFO - Epoch(train) [146][250/293] lr: 5.000000e-04 eta: 1:39:10 time: 0.368829 data_time: 0.072350 memory: 4980 loss_kpt: 0.000827 acc_pose: 0.744786 loss: 0.000827 2022/10/13 23:49:54 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:50:13 - mmengine - INFO - Epoch(train) [147][50/293] lr: 5.000000e-04 eta: 1:38:36 time: 0.387231 data_time: 0.096697 memory: 4980 loss_kpt: 0.000833 acc_pose: 0.745484 loss: 0.000833 2022/10/13 23:50:32 - mmengine - INFO - Epoch(train) [147][100/293] lr: 5.000000e-04 eta: 1:38:21 time: 0.369199 data_time: 0.080157 memory: 4980 loss_kpt: 0.000823 acc_pose: 0.738199 loss: 0.000823 2022/10/13 23:50:50 - mmengine - INFO - Epoch(train) [147][150/293] lr: 5.000000e-04 eta: 1:38:07 time: 0.371671 data_time: 0.077768 memory: 4980 loss_kpt: 0.000844 acc_pose: 0.730934 loss: 0.000844 2022/10/13 23:51:08 - mmengine - INFO - Epoch(train) [147][200/293] lr: 5.000000e-04 eta: 1:37:52 time: 0.350984 data_time: 0.074694 memory: 4980 loss_kpt: 0.000851 acc_pose: 0.733893 loss: 0.000851 2022/10/13 23:51:16 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:51:26 - mmengine - INFO - Epoch(train) [147][250/293] lr: 5.000000e-04 eta: 1:37:37 time: 0.363107 data_time: 0.115822 memory: 4980 loss_kpt: 0.000839 acc_pose: 0.738656 loss: 0.000839 2022/10/13 23:51:41 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:52:00 - mmengine - INFO - Epoch(train) [148][50/293] lr: 5.000000e-04 eta: 1:37:03 time: 0.374650 data_time: 0.120505 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.729152 loss: 0.000853 2022/10/13 23:52:18 - mmengine - INFO - Epoch(train) [148][100/293] lr: 5.000000e-04 eta: 1:36:48 time: 0.362797 data_time: 0.069000 memory: 4980 loss_kpt: 0.000832 acc_pose: 0.817649 loss: 0.000832 2022/10/13 23:52:37 - mmengine - INFO - Epoch(train) [148][150/293] lr: 5.000000e-04 eta: 1:36:34 time: 0.374873 data_time: 0.082237 memory: 4980 loss_kpt: 0.000840 acc_pose: 0.779225 loss: 0.000840 2022/10/13 23:52:55 - mmengine - INFO - Epoch(train) [148][200/293] lr: 5.000000e-04 eta: 1:36:19 time: 0.359545 data_time: 0.071964 memory: 4980 loss_kpt: 0.000844 acc_pose: 0.743433 loss: 0.000844 2022/10/13 23:53:13 - mmengine - INFO - Epoch(train) [148][250/293] lr: 5.000000e-04 eta: 1:36:04 time: 0.355699 data_time: 0.073261 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.742249 loss: 0.000835 2022/10/13 23:53:28 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:53:46 - mmengine - INFO - Epoch(train) [149][50/293] lr: 5.000000e-04 eta: 1:35:30 time: 0.371401 data_time: 0.104677 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.730277 loss: 0.000836 2022/10/13 23:54:04 - mmengine - INFO - Epoch(train) [149][100/293] lr: 5.000000e-04 eta: 1:35:15 time: 0.361790 data_time: 0.075514 memory: 4980 loss_kpt: 0.000832 acc_pose: 0.665558 loss: 0.000832 2022/10/13 23:54:22 - mmengine - INFO - Epoch(train) [149][150/293] lr: 5.000000e-04 eta: 1:35:00 time: 0.359157 data_time: 0.087806 memory: 4980 loss_kpt: 0.000828 acc_pose: 0.772238 loss: 0.000828 2022/10/13 23:54:40 - mmengine - INFO - Epoch(train) [149][200/293] lr: 5.000000e-04 eta: 1:34:45 time: 0.344833 data_time: 0.099847 memory: 4980 loss_kpt: 0.000829 acc_pose: 0.771609 loss: 0.000829 2022/10/13 23:54:58 - mmengine - INFO - Epoch(train) [149][250/293] lr: 5.000000e-04 eta: 1:34:30 time: 0.369638 data_time: 0.095915 memory: 4980 loss_kpt: 0.000827 acc_pose: 0.784167 loss: 0.000827 2022/10/13 23:55:13 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:55:32 - mmengine - INFO - Epoch(train) [150][50/293] lr: 5.000000e-04 eta: 1:33:56 time: 0.379548 data_time: 0.112323 memory: 4980 loss_kpt: 0.000819 acc_pose: 0.769714 loss: 0.000819 2022/10/13 23:55:50 - mmengine - INFO - Epoch(train) [150][100/293] lr: 5.000000e-04 eta: 1:33:41 time: 0.359285 data_time: 0.073080 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.787054 loss: 0.000836 2022/10/13 23:56:09 - mmengine - INFO - Epoch(train) [150][150/293] lr: 5.000000e-04 eta: 1:33:26 time: 0.363928 data_time: 0.076645 memory: 4980 loss_kpt: 0.000861 acc_pose: 0.729781 loss: 0.000861 2022/10/13 23:56:27 - mmengine - INFO - Epoch(train) [150][200/293] lr: 5.000000e-04 eta: 1:33:12 time: 0.362688 data_time: 0.091315 memory: 4980 loss_kpt: 0.000825 acc_pose: 0.782885 loss: 0.000825 2022/10/13 23:56:45 - mmengine - INFO - Epoch(train) [150][250/293] lr: 5.000000e-04 eta: 1:32:57 time: 0.360192 data_time: 0.077290 memory: 4980 loss_kpt: 0.000843 acc_pose: 0.735581 loss: 0.000843 2022/10/13 23:57:00 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:57:00 - mmengine - INFO - Saving checkpoint at 150 epochs 2022/10/13 23:57:08 - mmengine - INFO - Epoch(val) [150][50/407] eta: 0:00:46 time: 0.128876 data_time: 0.074047 memory: 4980 2022/10/13 23:57:15 - mmengine - INFO - Epoch(val) [150][100/407] eta: 0:00:39 time: 0.129047 data_time: 0.074212 memory: 772 2022/10/13 23:57:21 - mmengine - INFO - Epoch(val) [150][150/407] eta: 0:00:30 time: 0.119891 data_time: 0.063738 memory: 772 2022/10/13 23:57:27 - mmengine - INFO - Epoch(val) [150][200/407] eta: 0:00:24 time: 0.117142 data_time: 0.063202 memory: 772 2022/10/13 23:57:33 - mmengine - INFO - Epoch(val) [150][250/407] eta: 0:00:19 time: 0.127141 data_time: 0.073119 memory: 772 2022/10/13 23:57:39 - mmengine - INFO - Epoch(val) [150][300/407] eta: 0:00:13 time: 0.127553 data_time: 0.073559 memory: 772 2022/10/13 23:57:46 - mmengine - INFO - Epoch(val) [150][350/407] eta: 0:00:07 time: 0.125232 data_time: 0.068349 memory: 772 2022/10/13 23:57:52 - mmengine - INFO - Epoch(val) [150][400/407] eta: 0:00:00 time: 0.122514 data_time: 0.069942 memory: 772 2022/10/13 23:58:28 - mmengine - INFO - Evaluating CocoMetric... 2022/10/13 23:58:42 - mmengine - INFO - Epoch(val) [150][407/407] coco/AP: 0.624849 coco/AP .5: 0.860246 coco/AP .75: 0.689390 coco/AP (M): 0.582874 coco/AP (L): 0.697107 coco/AR: 0.687768 coco/AR .5: 0.902078 coco/AR .75: 0.750472 coco/AR (M): 0.637667 coco/AR (L): 0.758268 2022/10/13 23:58:42 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_140.pth is removed 2022/10/13 23:58:44 - mmengine - INFO - The best checkpoint with 0.6248 coco/AP at 150 epoch is saved to best_coco/AP_epoch_150.pth. 2022/10/13 23:59:02 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/13 23:59:02 - mmengine - INFO - Epoch(train) [151][50/293] lr: 5.000000e-04 eta: 1:32:23 time: 0.372104 data_time: 0.141171 memory: 4980 loss_kpt: 0.000831 acc_pose: 0.721640 loss: 0.000831 2022/10/13 23:59:20 - mmengine - INFO - Epoch(train) [151][100/293] lr: 5.000000e-04 eta: 1:32:08 time: 0.360986 data_time: 0.119722 memory: 4980 loss_kpt: 0.000839 acc_pose: 0.751985 loss: 0.000839 2022/10/13 23:59:38 - mmengine - INFO - Epoch(train) [151][150/293] lr: 5.000000e-04 eta: 1:31:53 time: 0.352529 data_time: 0.140624 memory: 4980 loss_kpt: 0.000828 acc_pose: 0.694543 loss: 0.000828 2022/10/13 23:59:56 - mmengine - INFO - Epoch(train) [151][200/293] lr: 5.000000e-04 eta: 1:31:38 time: 0.363027 data_time: 0.149801 memory: 4980 loss_kpt: 0.000833 acc_pose: 0.670342 loss: 0.000833 2022/10/14 00:00:14 - mmengine - INFO - Epoch(train) [151][250/293] lr: 5.000000e-04 eta: 1:31:23 time: 0.360744 data_time: 0.131177 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.769336 loss: 0.000847 2022/10/14 00:00:30 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:00:49 - mmengine - INFO - Epoch(train) [152][50/293] lr: 5.000000e-04 eta: 1:30:50 time: 0.382605 data_time: 0.096067 memory: 4980 loss_kpt: 0.000833 acc_pose: 0.717495 loss: 0.000833 2022/10/14 00:01:07 - mmengine - INFO - Epoch(train) [152][100/293] lr: 5.000000e-04 eta: 1:30:35 time: 0.373070 data_time: 0.093498 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.736815 loss: 0.000850 2022/10/14 00:01:25 - mmengine - INFO - Epoch(train) [152][150/293] lr: 5.000000e-04 eta: 1:30:20 time: 0.350791 data_time: 0.099197 memory: 4980 loss_kpt: 0.000845 acc_pose: 0.743501 loss: 0.000845 2022/10/14 00:01:42 - mmengine - INFO - Epoch(train) [152][200/293] lr: 5.000000e-04 eta: 1:30:04 time: 0.347807 data_time: 0.072359 memory: 4980 loss_kpt: 0.000853 acc_pose: 0.720215 loss: 0.000853 2022/10/14 00:02:00 - mmengine - INFO - Epoch(train) [152][250/293] lr: 5.000000e-04 eta: 1:29:49 time: 0.357916 data_time: 0.067091 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.756273 loss: 0.000836 2022/10/14 00:02:15 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:02:34 - mmengine - INFO - Epoch(train) [153][50/293] lr: 5.000000e-04 eta: 1:29:16 time: 0.363877 data_time: 0.101702 memory: 4980 loss_kpt: 0.000828 acc_pose: 0.748558 loss: 0.000828 2022/10/14 00:02:52 - mmengine - INFO - Epoch(train) [153][100/293] lr: 5.000000e-04 eta: 1:29:01 time: 0.366747 data_time: 0.116927 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.752560 loss: 0.000836 2022/10/14 00:03:10 - mmengine - INFO - Epoch(train) [153][150/293] lr: 5.000000e-04 eta: 1:28:46 time: 0.360396 data_time: 0.117624 memory: 4980 loss_kpt: 0.000837 acc_pose: 0.739136 loss: 0.000837 2022/10/14 00:03:28 - mmengine - INFO - Epoch(train) [153][200/293] lr: 5.000000e-04 eta: 1:28:31 time: 0.362674 data_time: 0.112638 memory: 4980 loss_kpt: 0.000827 acc_pose: 0.719159 loss: 0.000827 2022/10/14 00:03:46 - mmengine - INFO - Epoch(train) [153][250/293] lr: 5.000000e-04 eta: 1:28:16 time: 0.353754 data_time: 0.068619 memory: 4980 loss_kpt: 0.000820 acc_pose: 0.675321 loss: 0.000820 2022/10/14 00:04:01 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:04:19 - mmengine - INFO - Epoch(train) [154][50/293] lr: 5.000000e-04 eta: 1:27:42 time: 0.372028 data_time: 0.130931 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.719628 loss: 0.000838 2022/10/14 00:04:37 - mmengine - INFO - Epoch(train) [154][100/293] lr: 5.000000e-04 eta: 1:27:27 time: 0.358242 data_time: 0.118985 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.766833 loss: 0.000835 2022/10/14 00:04:55 - mmengine - INFO - Epoch(train) [154][150/293] lr: 5.000000e-04 eta: 1:27:12 time: 0.360459 data_time: 0.086832 memory: 4980 loss_kpt: 0.000846 acc_pose: 0.720686 loss: 0.000846 2022/10/14 00:05:03 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:05:13 - mmengine - INFO - Epoch(train) [154][200/293] lr: 5.000000e-04 eta: 1:26:57 time: 0.354567 data_time: 0.071440 memory: 4980 loss_kpt: 0.000830 acc_pose: 0.776351 loss: 0.000830 2022/10/14 00:05:31 - mmengine - INFO - Epoch(train) [154][250/293] lr: 5.000000e-04 eta: 1:26:42 time: 0.354832 data_time: 0.074136 memory: 4980 loss_kpt: 0.000828 acc_pose: 0.790168 loss: 0.000828 2022/10/14 00:05:46 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:06:06 - mmengine - INFO - Epoch(train) [155][50/293] lr: 5.000000e-04 eta: 1:26:09 time: 0.383421 data_time: 0.095899 memory: 4980 loss_kpt: 0.000825 acc_pose: 0.723378 loss: 0.000825 2022/10/14 00:06:23 - mmengine - INFO - Epoch(train) [155][100/293] lr: 5.000000e-04 eta: 1:25:54 time: 0.355790 data_time: 0.109643 memory: 4980 loss_kpt: 0.000843 acc_pose: 0.716745 loss: 0.000843 2022/10/14 00:06:41 - mmengine - INFO - Epoch(train) [155][150/293] lr: 5.000000e-04 eta: 1:25:39 time: 0.354658 data_time: 0.074835 memory: 4980 loss_kpt: 0.000831 acc_pose: 0.688548 loss: 0.000831 2022/10/14 00:06:59 - mmengine - INFO - Epoch(train) [155][200/293] lr: 5.000000e-04 eta: 1:25:24 time: 0.366284 data_time: 0.077002 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.716497 loss: 0.000836 2022/10/14 00:07:17 - mmengine - INFO - Epoch(train) [155][250/293] lr: 5.000000e-04 eta: 1:25:09 time: 0.357849 data_time: 0.067854 memory: 4980 loss_kpt: 0.000821 acc_pose: 0.753930 loss: 0.000821 2022/10/14 00:07:32 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:07:51 - mmengine - INFO - Epoch(train) [156][50/293] lr: 5.000000e-04 eta: 1:24:36 time: 0.379790 data_time: 0.105200 memory: 4980 loss_kpt: 0.000824 acc_pose: 0.745216 loss: 0.000824 2022/10/14 00:08:09 - mmengine - INFO - Epoch(train) [156][100/293] lr: 5.000000e-04 eta: 1:24:21 time: 0.354877 data_time: 0.078008 memory: 4980 loss_kpt: 0.000848 acc_pose: 0.735127 loss: 0.000848 2022/10/14 00:08:27 - mmengine - INFO - Epoch(train) [156][150/293] lr: 5.000000e-04 eta: 1:24:06 time: 0.356867 data_time: 0.067347 memory: 4980 loss_kpt: 0.000828 acc_pose: 0.713881 loss: 0.000828 2022/10/14 00:08:45 - mmengine - INFO - Epoch(train) [156][200/293] lr: 5.000000e-04 eta: 1:23:50 time: 0.350762 data_time: 0.067816 memory: 4980 loss_kpt: 0.000850 acc_pose: 0.806966 loss: 0.000850 2022/10/14 00:09:03 - mmengine - INFO - Epoch(train) [156][250/293] lr: 5.000000e-04 eta: 1:23:36 time: 0.373225 data_time: 0.078076 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.762887 loss: 0.000836 2022/10/14 00:09:18 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:09:37 - mmengine - INFO - Epoch(train) [157][50/293] lr: 5.000000e-04 eta: 1:23:03 time: 0.373086 data_time: 0.091357 memory: 4980 loss_kpt: 0.000837 acc_pose: 0.735776 loss: 0.000837 2022/10/14 00:09:55 - mmengine - INFO - Epoch(train) [157][100/293] lr: 5.000000e-04 eta: 1:22:47 time: 0.358430 data_time: 0.074995 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.784164 loss: 0.000835 2022/10/14 00:10:13 - mmengine - INFO - Epoch(train) [157][150/293] lr: 5.000000e-04 eta: 1:22:32 time: 0.360557 data_time: 0.067937 memory: 4980 loss_kpt: 0.000839 acc_pose: 0.688122 loss: 0.000839 2022/10/14 00:10:31 - mmengine - INFO - Epoch(train) [157][200/293] lr: 5.000000e-04 eta: 1:22:17 time: 0.360474 data_time: 0.073662 memory: 4980 loss_kpt: 0.000832 acc_pose: 0.713175 loss: 0.000832 2022/10/14 00:10:49 - mmengine - INFO - Epoch(train) [157][250/293] lr: 5.000000e-04 eta: 1:22:02 time: 0.358807 data_time: 0.072061 memory: 4980 loss_kpt: 0.000824 acc_pose: 0.779772 loss: 0.000824 2022/10/14 00:11:04 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:11:04 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:11:23 - mmengine - INFO - Epoch(train) [158][50/293] lr: 5.000000e-04 eta: 1:21:29 time: 0.372690 data_time: 0.081856 memory: 4980 loss_kpt: 0.000828 acc_pose: 0.765629 loss: 0.000828 2022/10/14 00:11:41 - mmengine - INFO - Epoch(train) [158][100/293] lr: 5.000000e-04 eta: 1:21:14 time: 0.362335 data_time: 0.076645 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.693877 loss: 0.000835 2022/10/14 00:11:59 - mmengine - INFO - Epoch(train) [158][150/293] lr: 5.000000e-04 eta: 1:20:59 time: 0.363373 data_time: 0.079936 memory: 4980 loss_kpt: 0.000833 acc_pose: 0.758812 loss: 0.000833 2022/10/14 00:12:17 - mmengine - INFO - Epoch(train) [158][200/293] lr: 5.000000e-04 eta: 1:20:44 time: 0.365938 data_time: 0.075153 memory: 4980 loss_kpt: 0.000834 acc_pose: 0.699936 loss: 0.000834 2022/10/14 00:12:36 - mmengine - INFO - Epoch(train) [158][250/293] lr: 5.000000e-04 eta: 1:20:29 time: 0.363615 data_time: 0.076782 memory: 4980 loss_kpt: 0.000831 acc_pose: 0.746935 loss: 0.000831 2022/10/14 00:12:51 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:13:09 - mmengine - INFO - Epoch(train) [159][50/293] lr: 5.000000e-04 eta: 1:19:56 time: 0.367991 data_time: 0.088967 memory: 4980 loss_kpt: 0.000833 acc_pose: 0.735019 loss: 0.000833 2022/10/14 00:13:28 - mmengine - INFO - Epoch(train) [159][100/293] lr: 5.000000e-04 eta: 1:19:41 time: 0.366541 data_time: 0.101776 memory: 4980 loss_kpt: 0.000826 acc_pose: 0.707075 loss: 0.000826 2022/10/14 00:13:46 - mmengine - INFO - Epoch(train) [159][150/293] lr: 5.000000e-04 eta: 1:19:26 time: 0.356452 data_time: 0.067038 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.729616 loss: 0.000838 2022/10/14 00:14:04 - mmengine - INFO - Epoch(train) [159][200/293] lr: 5.000000e-04 eta: 1:19:11 time: 0.361207 data_time: 0.067725 memory: 4980 loss_kpt: 0.000819 acc_pose: 0.716669 loss: 0.000819 2022/10/14 00:14:22 - mmengine - INFO - Epoch(train) [159][250/293] lr: 5.000000e-04 eta: 1:18:56 time: 0.362472 data_time: 0.073892 memory: 4980 loss_kpt: 0.000837 acc_pose: 0.796746 loss: 0.000837 2022/10/14 00:14:37 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:14:56 - mmengine - INFO - Epoch(train) [160][50/293] lr: 5.000000e-04 eta: 1:18:23 time: 0.387431 data_time: 0.115550 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.751970 loss: 0.000835 2022/10/14 00:15:14 - mmengine - INFO - Epoch(train) [160][100/293] lr: 5.000000e-04 eta: 1:18:08 time: 0.362399 data_time: 0.099148 memory: 4980 loss_kpt: 0.000823 acc_pose: 0.691166 loss: 0.000823 2022/10/14 00:15:32 - mmengine - INFO - Epoch(train) [160][150/293] lr: 5.000000e-04 eta: 1:17:53 time: 0.356230 data_time: 0.115009 memory: 4980 loss_kpt: 0.000826 acc_pose: 0.677656 loss: 0.000826 2022/10/14 00:15:50 - mmengine - INFO - Epoch(train) [160][200/293] lr: 5.000000e-04 eta: 1:17:38 time: 0.360832 data_time: 0.108934 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.687931 loss: 0.000838 2022/10/14 00:16:08 - mmengine - INFO - Epoch(train) [160][250/293] lr: 5.000000e-04 eta: 1:17:23 time: 0.366741 data_time: 0.121733 memory: 4980 loss_kpt: 0.000849 acc_pose: 0.698443 loss: 0.000849 2022/10/14 00:16:24 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:16:24 - mmengine - INFO - Saving checkpoint at 160 epochs 2022/10/14 00:16:32 - mmengine - INFO - Epoch(val) [160][50/407] eta: 0:00:47 time: 0.132603 data_time: 0.075506 memory: 4980 2022/10/14 00:16:38 - mmengine - INFO - Epoch(val) [160][100/407] eta: 0:00:36 time: 0.119475 data_time: 0.064761 memory: 772 2022/10/14 00:16:45 - mmengine - INFO - Epoch(val) [160][150/407] eta: 0:00:33 time: 0.131956 data_time: 0.078150 memory: 772 2022/10/14 00:16:51 - mmengine - INFO - Epoch(val) [160][200/407] eta: 0:00:25 time: 0.122216 data_time: 0.065956 memory: 772 2022/10/14 00:16:57 - mmengine - INFO - Epoch(val) [160][250/407] eta: 0:00:19 time: 0.125216 data_time: 0.070538 memory: 772 2022/10/14 00:17:04 - mmengine - INFO - Epoch(val) [160][300/407] eta: 0:00:13 time: 0.125711 data_time: 0.069829 memory: 772 2022/10/14 00:17:10 - mmengine - INFO - Epoch(val) [160][350/407] eta: 0:00:07 time: 0.123319 data_time: 0.068515 memory: 772 2022/10/14 00:17:16 - mmengine - INFO - Epoch(val) [160][400/407] eta: 0:00:00 time: 0.116387 data_time: 0.064176 memory: 772 2022/10/14 00:17:52 - mmengine - INFO - Evaluating CocoMetric... 2022/10/14 00:18:06 - mmengine - INFO - Epoch(val) [160][407/407] coco/AP: 0.623681 coco/AP .5: 0.860374 coco/AP .75: 0.686908 coco/AP (M): 0.581756 coco/AP (L): 0.695006 coco/AR: 0.686036 coco/AR .5: 0.903338 coco/AR .75: 0.749055 coco/AR (M): 0.635783 coco/AR (L): 0.756708 2022/10/14 00:18:25 - mmengine - INFO - Epoch(train) [161][50/293] lr: 5.000000e-04 eta: 1:16:51 time: 0.380716 data_time: 0.124297 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.742965 loss: 0.000838 2022/10/14 00:18:43 - mmengine - INFO - Epoch(train) [161][100/293] lr: 5.000000e-04 eta: 1:16:35 time: 0.361175 data_time: 0.067851 memory: 4980 loss_kpt: 0.000845 acc_pose: 0.741575 loss: 0.000845 2022/10/14 00:18:50 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:19:01 - mmengine - INFO - Epoch(train) [161][150/293] lr: 5.000000e-04 eta: 1:16:20 time: 0.360293 data_time: 0.078764 memory: 4980 loss_kpt: 0.000821 acc_pose: 0.764191 loss: 0.000821 2022/10/14 00:19:19 - mmengine - INFO - Epoch(train) [161][200/293] lr: 5.000000e-04 eta: 1:16:05 time: 0.357888 data_time: 0.076813 memory: 4980 loss_kpt: 0.000829 acc_pose: 0.745313 loss: 0.000829 2022/10/14 00:19:36 - mmengine - INFO - Epoch(train) [161][250/293] lr: 5.000000e-04 eta: 1:15:50 time: 0.351876 data_time: 0.071974 memory: 4980 loss_kpt: 0.000837 acc_pose: 0.707157 loss: 0.000837 2022/10/14 00:19:51 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:20:11 - mmengine - INFO - Epoch(train) [162][50/293] lr: 5.000000e-04 eta: 1:15:18 time: 0.390757 data_time: 0.095960 memory: 4980 loss_kpt: 0.000834 acc_pose: 0.702820 loss: 0.000834 2022/10/14 00:20:29 - mmengine - INFO - Epoch(train) [162][100/293] lr: 5.000000e-04 eta: 1:15:03 time: 0.365659 data_time: 0.081959 memory: 4980 loss_kpt: 0.000834 acc_pose: 0.778911 loss: 0.000834 2022/10/14 00:20:47 - mmengine - INFO - Epoch(train) [162][150/293] lr: 5.000000e-04 eta: 1:14:47 time: 0.360838 data_time: 0.072954 memory: 4980 loss_kpt: 0.000843 acc_pose: 0.757096 loss: 0.000843 2022/10/14 00:21:05 - mmengine - INFO - Epoch(train) [162][200/293] lr: 5.000000e-04 eta: 1:14:32 time: 0.359744 data_time: 0.071088 memory: 4980 loss_kpt: 0.000828 acc_pose: 0.761406 loss: 0.000828 2022/10/14 00:21:23 - mmengine - INFO - Epoch(train) [162][250/293] lr: 5.000000e-04 eta: 1:14:17 time: 0.358238 data_time: 0.070738 memory: 4980 loss_kpt: 0.000843 acc_pose: 0.729630 loss: 0.000843 2022/10/14 00:21:38 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:21:57 - mmengine - INFO - Epoch(train) [163][50/293] lr: 5.000000e-04 eta: 1:13:44 time: 0.370691 data_time: 0.094996 memory: 4980 loss_kpt: 0.000833 acc_pose: 0.735866 loss: 0.000833 2022/10/14 00:22:15 - mmengine - INFO - Epoch(train) [163][100/293] lr: 5.000000e-04 eta: 1:13:29 time: 0.359073 data_time: 0.072580 memory: 4980 loss_kpt: 0.000832 acc_pose: 0.743590 loss: 0.000832 2022/10/14 00:22:33 - mmengine - INFO - Epoch(train) [163][150/293] lr: 5.000000e-04 eta: 1:13:14 time: 0.358952 data_time: 0.066871 memory: 4980 loss_kpt: 0.000837 acc_pose: 0.701048 loss: 0.000837 2022/10/14 00:22:51 - mmengine - INFO - Epoch(train) [163][200/293] lr: 5.000000e-04 eta: 1:12:59 time: 0.362787 data_time: 0.086318 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.734659 loss: 0.000835 2022/10/14 00:23:09 - mmengine - INFO - Epoch(train) [163][250/293] lr: 5.000000e-04 eta: 1:12:44 time: 0.367293 data_time: 0.076830 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.774565 loss: 0.000836 2022/10/14 00:23:25 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:23:43 - mmengine - INFO - Epoch(train) [164][50/293] lr: 5.000000e-04 eta: 1:12:12 time: 0.370482 data_time: 0.083220 memory: 4980 loss_kpt: 0.000820 acc_pose: 0.732688 loss: 0.000820 2022/10/14 00:24:01 - mmengine - INFO - Epoch(train) [164][100/293] lr: 5.000000e-04 eta: 1:11:56 time: 0.359144 data_time: 0.072578 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.728266 loss: 0.000838 2022/10/14 00:24:19 - mmengine - INFO - Epoch(train) [164][150/293] lr: 5.000000e-04 eta: 1:11:41 time: 0.364476 data_time: 0.078975 memory: 4980 loss_kpt: 0.000828 acc_pose: 0.743910 loss: 0.000828 2022/10/14 00:24:37 - mmengine - INFO - Epoch(train) [164][200/293] lr: 5.000000e-04 eta: 1:11:26 time: 0.352479 data_time: 0.095696 memory: 4980 loss_kpt: 0.000833 acc_pose: 0.750008 loss: 0.000833 2022/10/14 00:24:52 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:24:55 - mmengine - INFO - Epoch(train) [164][250/293] lr: 5.000000e-04 eta: 1:11:11 time: 0.363735 data_time: 0.070386 memory: 4980 loss_kpt: 0.000827 acc_pose: 0.753620 loss: 0.000827 2022/10/14 00:25:10 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:25:29 - mmengine - INFO - Epoch(train) [165][50/293] lr: 5.000000e-04 eta: 1:10:39 time: 0.376106 data_time: 0.127538 memory: 4980 loss_kpt: 0.000832 acc_pose: 0.785055 loss: 0.000832 2022/10/14 00:25:47 - mmengine - INFO - Epoch(train) [165][100/293] lr: 5.000000e-04 eta: 1:10:23 time: 0.359088 data_time: 0.112266 memory: 4980 loss_kpt: 0.000824 acc_pose: 0.768793 loss: 0.000824 2022/10/14 00:26:05 - mmengine - INFO - Epoch(train) [165][150/293] lr: 5.000000e-04 eta: 1:10:08 time: 0.360502 data_time: 0.123222 memory: 4980 loss_kpt: 0.000829 acc_pose: 0.718336 loss: 0.000829 2022/10/14 00:26:24 - mmengine - INFO - Epoch(train) [165][200/293] lr: 5.000000e-04 eta: 1:09:53 time: 0.384996 data_time: 0.141070 memory: 4980 loss_kpt: 0.000851 acc_pose: 0.731027 loss: 0.000851 2022/10/14 00:26:43 - mmengine - INFO - Epoch(train) [165][250/293] lr: 5.000000e-04 eta: 1:09:38 time: 0.364747 data_time: 0.130632 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.758650 loss: 0.000836 2022/10/14 00:26:58 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:27:17 - mmengine - INFO - Epoch(train) [166][50/293] lr: 5.000000e-04 eta: 1:09:06 time: 0.382228 data_time: 0.111830 memory: 4980 loss_kpt: 0.000824 acc_pose: 0.720476 loss: 0.000824 2022/10/14 00:27:35 - mmengine - INFO - Epoch(train) [166][100/293] lr: 5.000000e-04 eta: 1:08:51 time: 0.356864 data_time: 0.073987 memory: 4980 loss_kpt: 0.000829 acc_pose: 0.687186 loss: 0.000829 2022/10/14 00:27:53 - mmengine - INFO - Epoch(train) [166][150/293] lr: 5.000000e-04 eta: 1:08:36 time: 0.361801 data_time: 0.079190 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.741552 loss: 0.000838 2022/10/14 00:28:11 - mmengine - INFO - Epoch(train) [166][200/293] lr: 5.000000e-04 eta: 1:08:20 time: 0.357915 data_time: 0.071725 memory: 4980 loss_kpt: 0.000825 acc_pose: 0.721080 loss: 0.000825 2022/10/14 00:28:30 - mmengine - INFO - Epoch(train) [166][250/293] lr: 5.000000e-04 eta: 1:08:05 time: 0.374961 data_time: 0.088249 memory: 4980 loss_kpt: 0.000837 acc_pose: 0.689384 loss: 0.000837 2022/10/14 00:28:45 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:29:03 - mmengine - INFO - Epoch(train) [167][50/293] lr: 5.000000e-04 eta: 1:07:33 time: 0.375891 data_time: 0.097081 memory: 4980 loss_kpt: 0.000825 acc_pose: 0.720782 loss: 0.000825 2022/10/14 00:29:21 - mmengine - INFO - Epoch(train) [167][100/293] lr: 5.000000e-04 eta: 1:07:18 time: 0.361505 data_time: 0.075415 memory: 4980 loss_kpt: 0.000824 acc_pose: 0.774337 loss: 0.000824 2022/10/14 00:29:40 - mmengine - INFO - Epoch(train) [167][150/293] lr: 5.000000e-04 eta: 1:07:03 time: 0.369518 data_time: 0.072832 memory: 4980 loss_kpt: 0.000830 acc_pose: 0.762508 loss: 0.000830 2022/10/14 00:29:58 - mmengine - INFO - Epoch(train) [167][200/293] lr: 5.000000e-04 eta: 1:06:48 time: 0.369382 data_time: 0.075543 memory: 4980 loss_kpt: 0.000825 acc_pose: 0.796825 loss: 0.000825 2022/10/14 00:30:16 - mmengine - INFO - Epoch(train) [167][250/293] lr: 5.000000e-04 eta: 1:06:33 time: 0.358209 data_time: 0.070404 memory: 4980 loss_kpt: 0.000830 acc_pose: 0.797808 loss: 0.000830 2022/10/14 00:30:31 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:30:50 - mmengine - INFO - Epoch(train) [168][50/293] lr: 5.000000e-04 eta: 1:06:01 time: 0.377509 data_time: 0.121359 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.711356 loss: 0.000835 2022/10/14 00:30:57 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:31:08 - mmengine - INFO - Epoch(train) [168][100/293] lr: 5.000000e-04 eta: 1:05:45 time: 0.361755 data_time: 0.068115 memory: 4980 loss_kpt: 0.000835 acc_pose: 0.698058 loss: 0.000835 2022/10/14 00:31:26 - mmengine - INFO - Epoch(train) [168][150/293] lr: 5.000000e-04 eta: 1:05:30 time: 0.354044 data_time: 0.077318 memory: 4980 loss_kpt: 0.000847 acc_pose: 0.728660 loss: 0.000847 2022/10/14 00:31:44 - mmengine - INFO - Epoch(train) [168][200/293] lr: 5.000000e-04 eta: 1:05:15 time: 0.366532 data_time: 0.075263 memory: 4980 loss_kpt: 0.000836 acc_pose: 0.725892 loss: 0.000836 2022/10/14 00:32:02 - mmengine - INFO - Epoch(train) [168][250/293] lr: 5.000000e-04 eta: 1:05:00 time: 0.356572 data_time: 0.073790 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.734198 loss: 0.000838 2022/10/14 00:32:18 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:32:37 - mmengine - INFO - Epoch(train) [169][50/293] lr: 5.000000e-04 eta: 1:04:28 time: 0.382812 data_time: 0.120473 memory: 4980 loss_kpt: 0.000811 acc_pose: 0.739043 loss: 0.000811 2022/10/14 00:32:55 - mmengine - INFO - Epoch(train) [169][100/293] lr: 5.000000e-04 eta: 1:04:13 time: 0.361477 data_time: 0.074482 memory: 4980 loss_kpt: 0.000828 acc_pose: 0.707489 loss: 0.000828 2022/10/14 00:33:13 - mmengine - INFO - Epoch(train) [169][150/293] lr: 5.000000e-04 eta: 1:03:57 time: 0.359610 data_time: 0.078297 memory: 4980 loss_kpt: 0.000838 acc_pose: 0.775228 loss: 0.000838 2022/10/14 00:33:31 - mmengine - INFO - Epoch(train) [169][200/293] lr: 5.000000e-04 eta: 1:03:42 time: 0.351312 data_time: 0.072424 memory: 4980 loss_kpt: 0.000843 acc_pose: 0.738414 loss: 0.000843 2022/10/14 00:33:49 - mmengine - INFO - Epoch(train) [169][250/293] lr: 5.000000e-04 eta: 1:03:27 time: 0.354095 data_time: 0.075032 memory: 4980 loss_kpt: 0.000839 acc_pose: 0.742367 loss: 0.000839 2022/10/14 00:34:04 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:34:23 - mmengine - INFO - Epoch(train) [170][50/293] lr: 5.000000e-04 eta: 1:02:55 time: 0.383179 data_time: 0.138452 memory: 4980 loss_kpt: 0.000845 acc_pose: 0.724790 loss: 0.000845 2022/10/14 00:34:41 - mmengine - INFO - Epoch(train) [170][100/293] lr: 5.000000e-04 eta: 1:02:40 time: 0.355521 data_time: 0.115216 memory: 4980 loss_kpt: 0.000831 acc_pose: 0.777657 loss: 0.000831 2022/10/14 00:34:59 - mmengine - INFO - Epoch(train) [170][150/293] lr: 5.000000e-04 eta: 1:02:24 time: 0.360531 data_time: 0.073581 memory: 4980 loss_kpt: 0.000816 acc_pose: 0.748756 loss: 0.000816 2022/10/14 00:35:18 - mmengine - INFO - Epoch(train) [170][200/293] lr: 5.000000e-04 eta: 1:02:09 time: 0.371620 data_time: 0.079767 memory: 4980 loss_kpt: 0.000822 acc_pose: 0.745732 loss: 0.000822 2022/10/14 00:35:36 - mmengine - INFO - Epoch(train) [170][250/293] lr: 5.000000e-04 eta: 1:01:54 time: 0.366586 data_time: 0.077772 memory: 4980 loss_kpt: 0.000834 acc_pose: 0.765290 loss: 0.000834 2022/10/14 00:35:52 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:35:52 - mmengine - INFO - Saving checkpoint at 170 epochs 2022/10/14 00:36:00 - mmengine - INFO - Epoch(val) [170][50/407] eta: 0:00:45 time: 0.127015 data_time: 0.071240 memory: 4980 2022/10/14 00:36:06 - mmengine - INFO - Epoch(val) [170][100/407] eta: 0:00:39 time: 0.130059 data_time: 0.074715 memory: 772 2022/10/14 00:36:13 - mmengine - INFO - Epoch(val) [170][150/407] eta: 0:00:32 time: 0.125771 data_time: 0.070009 memory: 772 2022/10/14 00:36:19 - mmengine - INFO - Epoch(val) [170][200/407] eta: 0:00:25 time: 0.125033 data_time: 0.070252 memory: 772 2022/10/14 00:36:25 - mmengine - INFO - Epoch(val) [170][250/407] eta: 0:00:19 time: 0.125238 data_time: 0.065877 memory: 772 2022/10/14 00:36:32 - mmengine - INFO - Epoch(val) [170][300/407] eta: 0:00:13 time: 0.126569 data_time: 0.073611 memory: 772 2022/10/14 00:36:38 - mmengine - INFO - Epoch(val) [170][350/407] eta: 0:00:07 time: 0.130388 data_time: 0.074112 memory: 772 2022/10/14 00:36:44 - mmengine - INFO - Epoch(val) [170][400/407] eta: 0:00:00 time: 0.117234 data_time: 0.065093 memory: 772 2022/10/14 00:37:21 - mmengine - INFO - Evaluating CocoMetric... 2022/10/14 00:37:35 - mmengine - INFO - Epoch(val) [170][407/407] coco/AP: 0.624646 coco/AP .5: 0.861483 coco/AP .75: 0.693263 coco/AP (M): 0.583721 coco/AP (L): 0.695310 coco/AR: 0.686414 coco/AR .5: 0.906171 coco/AR .75: 0.750157 coco/AR (M): 0.637203 coco/AR (L): 0.755518 2022/10/14 00:37:54 - mmengine - INFO - Epoch(train) [171][50/293] lr: 5.000000e-05 eta: 1:01:22 time: 0.368500 data_time: 0.092151 memory: 4980 loss_kpt: 0.000820 acc_pose: 0.735259 loss: 0.000820 2022/10/14 00:38:12 - mmengine - INFO - Epoch(train) [171][100/293] lr: 5.000000e-05 eta: 1:01:07 time: 0.359328 data_time: 0.071583 memory: 4980 loss_kpt: 0.000811 acc_pose: 0.744314 loss: 0.000811 2022/10/14 00:38:30 - mmengine - INFO - Epoch(train) [171][150/293] lr: 5.000000e-05 eta: 1:00:51 time: 0.359143 data_time: 0.068482 memory: 4980 loss_kpt: 0.000819 acc_pose: 0.739792 loss: 0.000819 2022/10/14 00:38:44 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:38:48 - mmengine - INFO - Epoch(train) [171][200/293] lr: 5.000000e-05 eta: 1:00:36 time: 0.371613 data_time: 0.091444 memory: 4980 loss_kpt: 0.000825 acc_pose: 0.787796 loss: 0.000825 2022/10/14 00:39:06 - mmengine - INFO - Epoch(train) [171][250/293] lr: 5.000000e-05 eta: 1:00:21 time: 0.366810 data_time: 0.077252 memory: 4980 loss_kpt: 0.000814 acc_pose: 0.701973 loss: 0.000814 2022/10/14 00:39:22 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:39:41 - mmengine - INFO - Epoch(train) [172][50/293] lr: 5.000000e-05 eta: 0:59:49 time: 0.382392 data_time: 0.107385 memory: 4980 loss_kpt: 0.000821 acc_pose: 0.776019 loss: 0.000821 2022/10/14 00:39:59 - mmengine - INFO - Epoch(train) [172][100/293] lr: 5.000000e-05 eta: 0:59:34 time: 0.362620 data_time: 0.073279 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.740090 loss: 0.000806 2022/10/14 00:40:17 - mmengine - INFO - Epoch(train) [172][150/293] lr: 5.000000e-05 eta: 0:59:19 time: 0.359697 data_time: 0.071928 memory: 4980 loss_kpt: 0.000807 acc_pose: 0.721182 loss: 0.000807 2022/10/14 00:40:35 - mmengine - INFO - Epoch(train) [172][200/293] lr: 5.000000e-05 eta: 0:59:04 time: 0.367297 data_time: 0.079114 memory: 4980 loss_kpt: 0.000797 acc_pose: 0.778180 loss: 0.000797 2022/10/14 00:40:53 - mmengine - INFO - Epoch(train) [172][250/293] lr: 5.000000e-05 eta: 0:58:48 time: 0.358507 data_time: 0.076854 memory: 4980 loss_kpt: 0.000813 acc_pose: 0.778386 loss: 0.000813 2022/10/14 00:41:08 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:41:27 - mmengine - INFO - Epoch(train) [173][50/293] lr: 5.000000e-05 eta: 0:58:17 time: 0.379321 data_time: 0.086930 memory: 4980 loss_kpt: 0.000805 acc_pose: 0.743896 loss: 0.000805 2022/10/14 00:41:45 - mmengine - INFO - Epoch(train) [173][100/293] lr: 5.000000e-05 eta: 0:58:01 time: 0.359652 data_time: 0.080431 memory: 4980 loss_kpt: 0.000815 acc_pose: 0.762252 loss: 0.000815 2022/10/14 00:42:04 - mmengine - INFO - Epoch(train) [173][150/293] lr: 5.000000e-05 eta: 0:57:46 time: 0.365918 data_time: 0.082426 memory: 4980 loss_kpt: 0.000823 acc_pose: 0.762889 loss: 0.000823 2022/10/14 00:42:21 - mmengine - INFO - Epoch(train) [173][200/293] lr: 5.000000e-05 eta: 0:57:31 time: 0.354043 data_time: 0.071501 memory: 4980 loss_kpt: 0.000824 acc_pose: 0.782979 loss: 0.000824 2022/10/14 00:42:40 - mmengine - INFO - Epoch(train) [173][250/293] lr: 5.000000e-05 eta: 0:57:16 time: 0.367743 data_time: 0.077454 memory: 4980 loss_kpt: 0.000810 acc_pose: 0.754457 loss: 0.000810 2022/10/14 00:42:55 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:43:14 - mmengine - INFO - Epoch(train) [174][50/293] lr: 5.000000e-05 eta: 0:56:44 time: 0.384728 data_time: 0.158145 memory: 4980 loss_kpt: 0.000809 acc_pose: 0.777542 loss: 0.000809 2022/10/14 00:43:32 - mmengine - INFO - Epoch(train) [174][100/293] lr: 5.000000e-05 eta: 0:56:29 time: 0.353215 data_time: 0.108148 memory: 4980 loss_kpt: 0.000803 acc_pose: 0.727815 loss: 0.000803 2022/10/14 00:43:50 - mmengine - INFO - Epoch(train) [174][150/293] lr: 5.000000e-05 eta: 0:56:13 time: 0.363552 data_time: 0.103569 memory: 4980 loss_kpt: 0.000803 acc_pose: 0.778636 loss: 0.000803 2022/10/14 00:44:09 - mmengine - INFO - Epoch(train) [174][200/293] lr: 5.000000e-05 eta: 0:55:58 time: 0.364197 data_time: 0.108337 memory: 4980 loss_kpt: 0.000808 acc_pose: 0.758517 loss: 0.000808 2022/10/14 00:44:27 - mmengine - INFO - Epoch(train) [174][250/293] lr: 5.000000e-05 eta: 0:55:43 time: 0.362649 data_time: 0.084420 memory: 4980 loss_kpt: 0.000803 acc_pose: 0.728921 loss: 0.000803 2022/10/14 00:44:42 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:44:49 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:45:01 - mmengine - INFO - Epoch(train) [175][50/293] lr: 5.000000e-05 eta: 0:55:11 time: 0.384149 data_time: 0.090475 memory: 4980 loss_kpt: 0.000815 acc_pose: 0.793172 loss: 0.000815 2022/10/14 00:45:19 - mmengine - INFO - Epoch(train) [175][100/293] lr: 5.000000e-05 eta: 0:54:56 time: 0.358029 data_time: 0.117764 memory: 4980 loss_kpt: 0.000812 acc_pose: 0.733148 loss: 0.000812 2022/10/14 00:45:37 - mmengine - INFO - Epoch(train) [175][150/293] lr: 5.000000e-05 eta: 0:54:41 time: 0.363397 data_time: 0.110603 memory: 4980 loss_kpt: 0.000818 acc_pose: 0.786009 loss: 0.000818 2022/10/14 00:45:56 - mmengine - INFO - Epoch(train) [175][200/293] lr: 5.000000e-05 eta: 0:54:26 time: 0.372309 data_time: 0.120998 memory: 4980 loss_kpt: 0.000803 acc_pose: 0.754728 loss: 0.000803 2022/10/14 00:46:13 - mmengine - INFO - Epoch(train) [175][250/293] lr: 5.000000e-05 eta: 0:54:10 time: 0.347786 data_time: 0.095013 memory: 4980 loss_kpt: 0.000816 acc_pose: 0.769026 loss: 0.000816 2022/10/14 00:46:28 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:46:47 - mmengine - INFO - Epoch(train) [176][50/293] lr: 5.000000e-05 eta: 0:53:39 time: 0.377905 data_time: 0.093721 memory: 4980 loss_kpt: 0.000810 acc_pose: 0.737577 loss: 0.000810 2022/10/14 00:47:05 - mmengine - INFO - Epoch(train) [176][100/293] lr: 5.000000e-05 eta: 0:53:23 time: 0.360348 data_time: 0.071964 memory: 4980 loss_kpt: 0.000812 acc_pose: 0.813453 loss: 0.000812 2022/10/14 00:47:23 - mmengine - INFO - Epoch(train) [176][150/293] lr: 5.000000e-05 eta: 0:53:08 time: 0.355595 data_time: 0.072345 memory: 4980 loss_kpt: 0.000821 acc_pose: 0.709479 loss: 0.000821 2022/10/14 00:47:41 - mmengine - INFO - Epoch(train) [176][200/293] lr: 5.000000e-05 eta: 0:52:53 time: 0.356093 data_time: 0.070531 memory: 4980 loss_kpt: 0.000813 acc_pose: 0.767298 loss: 0.000813 2022/10/14 00:47:59 - mmengine - INFO - Epoch(train) [176][250/293] lr: 5.000000e-05 eta: 0:52:37 time: 0.366956 data_time: 0.074193 memory: 4980 loss_kpt: 0.000809 acc_pose: 0.758884 loss: 0.000809 2022/10/14 00:48:14 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:48:33 - mmengine - INFO - Epoch(train) [177][50/293] lr: 5.000000e-05 eta: 0:52:06 time: 0.371321 data_time: 0.096792 memory: 4980 loss_kpt: 0.000822 acc_pose: 0.786222 loss: 0.000822 2022/10/14 00:48:52 - mmengine - INFO - Epoch(train) [177][100/293] lr: 5.000000e-05 eta: 0:51:51 time: 0.371184 data_time: 0.074416 memory: 4980 loss_kpt: 0.000800 acc_pose: 0.743041 loss: 0.000800 2022/10/14 00:49:10 - mmengine - INFO - Epoch(train) [177][150/293] lr: 5.000000e-05 eta: 0:51:35 time: 0.360535 data_time: 0.072302 memory: 4980 loss_kpt: 0.000813 acc_pose: 0.695428 loss: 0.000813 2022/10/14 00:49:27 - mmengine - INFO - Epoch(train) [177][200/293] lr: 5.000000e-05 eta: 0:51:20 time: 0.354066 data_time: 0.074563 memory: 4980 loss_kpt: 0.000805 acc_pose: 0.700033 loss: 0.000805 2022/10/14 00:49:45 - mmengine - INFO - Epoch(train) [177][250/293] lr: 5.000000e-05 eta: 0:51:05 time: 0.360449 data_time: 0.071273 memory: 4980 loss_kpt: 0.000797 acc_pose: 0.780503 loss: 0.000797 2022/10/14 00:50:01 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:50:19 - mmengine - INFO - Epoch(train) [178][50/293] lr: 5.000000e-05 eta: 0:50:33 time: 0.377391 data_time: 0.096794 memory: 4980 loss_kpt: 0.000798 acc_pose: 0.727856 loss: 0.000798 2022/10/14 00:50:38 - mmengine - INFO - Epoch(train) [178][100/293] lr: 5.000000e-05 eta: 0:50:18 time: 0.361889 data_time: 0.069455 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.776836 loss: 0.000806 2022/10/14 00:50:52 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:50:56 - mmengine - INFO - Epoch(train) [178][150/293] lr: 5.000000e-05 eta: 0:50:03 time: 0.372446 data_time: 0.074151 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.715100 loss: 0.000806 2022/10/14 00:51:14 - mmengine - INFO - Epoch(train) [178][200/293] lr: 5.000000e-05 eta: 0:49:47 time: 0.360149 data_time: 0.070499 memory: 4980 loss_kpt: 0.000820 acc_pose: 0.741413 loss: 0.000820 2022/10/14 00:51:32 - mmengine - INFO - Epoch(train) [178][250/293] lr: 5.000000e-05 eta: 0:49:32 time: 0.358563 data_time: 0.076430 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.775368 loss: 0.000804 2022/10/14 00:51:47 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:52:06 - mmengine - INFO - Epoch(train) [179][50/293] lr: 5.000000e-05 eta: 0:49:01 time: 0.376995 data_time: 0.089694 memory: 4980 loss_kpt: 0.000810 acc_pose: 0.738185 loss: 0.000810 2022/10/14 00:52:25 - mmengine - INFO - Epoch(train) [179][100/293] lr: 5.000000e-05 eta: 0:48:45 time: 0.368582 data_time: 0.083286 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.752061 loss: 0.000806 2022/10/14 00:52:43 - mmengine - INFO - Epoch(train) [179][150/293] lr: 5.000000e-05 eta: 0:48:30 time: 0.364942 data_time: 0.074794 memory: 4980 loss_kpt: 0.000791 acc_pose: 0.763603 loss: 0.000791 2022/10/14 00:53:01 - mmengine - INFO - Epoch(train) [179][200/293] lr: 5.000000e-05 eta: 0:48:15 time: 0.361138 data_time: 0.069629 memory: 4980 loss_kpt: 0.000817 acc_pose: 0.756825 loss: 0.000817 2022/10/14 00:53:19 - mmengine - INFO - Epoch(train) [179][250/293] lr: 5.000000e-05 eta: 0:47:59 time: 0.356997 data_time: 0.077256 memory: 4980 loss_kpt: 0.000811 acc_pose: 0.758693 loss: 0.000811 2022/10/14 00:53:34 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:53:53 - mmengine - INFO - Epoch(train) [180][50/293] lr: 5.000000e-05 eta: 0:47:28 time: 0.373114 data_time: 0.090982 memory: 4980 loss_kpt: 0.000794 acc_pose: 0.695808 loss: 0.000794 2022/10/14 00:54:11 - mmengine - INFO - Epoch(train) [180][100/293] lr: 5.000000e-05 eta: 0:47:13 time: 0.360682 data_time: 0.070643 memory: 4980 loss_kpt: 0.000778 acc_pose: 0.782433 loss: 0.000778 2022/10/14 00:54:29 - mmengine - INFO - Epoch(train) [180][150/293] lr: 5.000000e-05 eta: 0:46:57 time: 0.361035 data_time: 0.068507 memory: 4980 loss_kpt: 0.000820 acc_pose: 0.768760 loss: 0.000820 2022/10/14 00:54:47 - mmengine - INFO - Epoch(train) [180][200/293] lr: 5.000000e-05 eta: 0:46:42 time: 0.361306 data_time: 0.077555 memory: 4980 loss_kpt: 0.000812 acc_pose: 0.770260 loss: 0.000812 2022/10/14 00:55:05 - mmengine - INFO - Epoch(train) [180][250/293] lr: 5.000000e-05 eta: 0:46:27 time: 0.364212 data_time: 0.093129 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.760647 loss: 0.000806 2022/10/14 00:55:20 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:55:20 - mmengine - INFO - Saving checkpoint at 180 epochs 2022/10/14 00:55:29 - mmengine - INFO - Epoch(val) [180][50/407] eta: 0:00:46 time: 0.130873 data_time: 0.076649 memory: 4980 2022/10/14 00:55:35 - mmengine - INFO - Epoch(val) [180][100/407] eta: 0:00:39 time: 0.127369 data_time: 0.071487 memory: 772 2022/10/14 00:55:42 - mmengine - INFO - Epoch(val) [180][150/407] eta: 0:00:31 time: 0.120710 data_time: 0.065585 memory: 772 2022/10/14 00:55:47 - mmengine - INFO - Epoch(val) [180][200/407] eta: 0:00:24 time: 0.118183 data_time: 0.063182 memory: 772 2022/10/14 00:55:54 - mmengine - INFO - Epoch(val) [180][250/407] eta: 0:00:19 time: 0.124749 data_time: 0.069757 memory: 772 2022/10/14 00:56:00 - mmengine - INFO - Epoch(val) [180][300/407] eta: 0:00:13 time: 0.125579 data_time: 0.071373 memory: 772 2022/10/14 00:56:06 - mmengine - INFO - Epoch(val) [180][350/407] eta: 0:00:06 time: 0.122042 data_time: 0.067586 memory: 772 2022/10/14 00:56:12 - mmengine - INFO - Epoch(val) [180][400/407] eta: 0:00:00 time: 0.122710 data_time: 0.065293 memory: 772 2022/10/14 00:56:48 - mmengine - INFO - Evaluating CocoMetric... 2022/10/14 00:57:02 - mmengine - INFO - Epoch(val) [180][407/407] coco/AP: 0.635345 coco/AP .5: 0.864353 coco/AP .75: 0.699736 coco/AP (M): 0.595351 coco/AP (L): 0.705877 coco/AR: 0.697025 coco/AR .5: 0.908218 coco/AR .75: 0.759446 coco/AR (M): 0.647146 coco/AR (L): 0.766964 2022/10/14 00:57:02 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_150.pth is removed 2022/10/14 00:57:04 - mmengine - INFO - The best checkpoint with 0.6353 coco/AP at 180 epoch is saved to best_coco/AP_epoch_180.pth. 2022/10/14 00:57:22 - mmengine - INFO - Epoch(train) [181][50/293] lr: 5.000000e-05 eta: 0:45:55 time: 0.360557 data_time: 0.130526 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.739358 loss: 0.000806 2022/10/14 00:57:40 - mmengine - INFO - Epoch(train) [181][100/293] lr: 5.000000e-05 eta: 0:45:40 time: 0.358939 data_time: 0.092722 memory: 4980 loss_kpt: 0.000809 acc_pose: 0.764889 loss: 0.000809 2022/10/14 00:57:58 - mmengine - INFO - Epoch(train) [181][150/293] lr: 5.000000e-05 eta: 0:45:25 time: 0.356260 data_time: 0.068121 memory: 4980 loss_kpt: 0.000811 acc_pose: 0.714600 loss: 0.000811 2022/10/14 00:58:16 - mmengine - INFO - Epoch(train) [181][200/293] lr: 5.000000e-05 eta: 0:45:09 time: 0.371574 data_time: 0.075553 memory: 4980 loss_kpt: 0.000799 acc_pose: 0.738278 loss: 0.000799 2022/10/14 00:58:34 - mmengine - INFO - Epoch(train) [181][250/293] lr: 5.000000e-05 eta: 0:44:54 time: 0.354265 data_time: 0.070869 memory: 4980 loss_kpt: 0.000809 acc_pose: 0.754460 loss: 0.000809 2022/10/14 00:58:38 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:58:49 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 00:59:08 - mmengine - INFO - Epoch(train) [182][50/293] lr: 5.000000e-05 eta: 0:44:23 time: 0.368118 data_time: 0.116790 memory: 4980 loss_kpt: 0.000797 acc_pose: 0.761236 loss: 0.000797 2022/10/14 00:59:26 - mmengine - INFO - Epoch(train) [182][100/293] lr: 5.000000e-05 eta: 0:44:07 time: 0.359205 data_time: 0.126840 memory: 4980 loss_kpt: 0.000805 acc_pose: 0.768675 loss: 0.000805 2022/10/14 00:59:43 - mmengine - INFO - Epoch(train) [182][150/293] lr: 5.000000e-05 eta: 0:43:52 time: 0.355298 data_time: 0.091397 memory: 4980 loss_kpt: 0.000805 acc_pose: 0.774413 loss: 0.000805 2022/10/14 01:00:01 - mmengine - INFO - Epoch(train) [182][200/293] lr: 5.000000e-05 eta: 0:43:36 time: 0.360045 data_time: 0.072650 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.770213 loss: 0.000806 2022/10/14 01:00:19 - mmengine - INFO - Epoch(train) [182][250/293] lr: 5.000000e-05 eta: 0:43:21 time: 0.360883 data_time: 0.074109 memory: 4980 loss_kpt: 0.000801 acc_pose: 0.729392 loss: 0.000801 2022/10/14 01:00:35 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:00:53 - mmengine - INFO - Epoch(train) [183][50/293] lr: 5.000000e-05 eta: 0:42:50 time: 0.362910 data_time: 0.087630 memory: 4980 loss_kpt: 0.000785 acc_pose: 0.731447 loss: 0.000785 2022/10/14 01:01:11 - mmengine - INFO - Epoch(train) [183][100/293] lr: 5.000000e-05 eta: 0:42:35 time: 0.357709 data_time: 0.068454 memory: 4980 loss_kpt: 0.000805 acc_pose: 0.711665 loss: 0.000805 2022/10/14 01:01:29 - mmengine - INFO - Epoch(train) [183][150/293] lr: 5.000000e-05 eta: 0:42:19 time: 0.362961 data_time: 0.078301 memory: 4980 loss_kpt: 0.000800 acc_pose: 0.815798 loss: 0.000800 2022/10/14 01:01:47 - mmengine - INFO - Epoch(train) [183][200/293] lr: 5.000000e-05 eta: 0:42:04 time: 0.358731 data_time: 0.085804 memory: 4980 loss_kpt: 0.000811 acc_pose: 0.690218 loss: 0.000811 2022/10/14 01:02:04 - mmengine - INFO - Epoch(train) [183][250/293] lr: 5.000000e-05 eta: 0:41:48 time: 0.352836 data_time: 0.087688 memory: 4980 loss_kpt: 0.000810 acc_pose: 0.703740 loss: 0.000810 2022/10/14 01:02:20 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:02:39 - mmengine - INFO - Epoch(train) [184][50/293] lr: 5.000000e-05 eta: 0:41:17 time: 0.378294 data_time: 0.095178 memory: 4980 loss_kpt: 0.000816 acc_pose: 0.718146 loss: 0.000816 2022/10/14 01:02:56 - mmengine - INFO - Epoch(train) [184][100/293] lr: 5.000000e-05 eta: 0:41:02 time: 0.352638 data_time: 0.074865 memory: 4980 loss_kpt: 0.000798 acc_pose: 0.710107 loss: 0.000798 2022/10/14 01:03:14 - mmengine - INFO - Epoch(train) [184][150/293] lr: 5.000000e-05 eta: 0:40:46 time: 0.359531 data_time: 0.077292 memory: 4980 loss_kpt: 0.000796 acc_pose: 0.732127 loss: 0.000796 2022/10/14 01:03:32 - mmengine - INFO - Epoch(train) [184][200/293] lr: 5.000000e-05 eta: 0:40:31 time: 0.359843 data_time: 0.066569 memory: 4980 loss_kpt: 0.000813 acc_pose: 0.734843 loss: 0.000813 2022/10/14 01:03:51 - mmengine - INFO - Epoch(train) [184][250/293] lr: 5.000000e-05 eta: 0:40:16 time: 0.363685 data_time: 0.071525 memory: 4980 loss_kpt: 0.000795 acc_pose: 0.707702 loss: 0.000795 2022/10/14 01:04:06 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:04:25 - mmengine - INFO - Epoch(train) [185][50/293] lr: 5.000000e-05 eta: 0:39:45 time: 0.380153 data_time: 0.090850 memory: 4980 loss_kpt: 0.000791 acc_pose: 0.765116 loss: 0.000791 2022/10/14 01:04:39 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:04:43 - mmengine - INFO - Epoch(train) [185][100/293] lr: 5.000000e-05 eta: 0:39:29 time: 0.362020 data_time: 0.078137 memory: 4980 loss_kpt: 0.000808 acc_pose: 0.740182 loss: 0.000808 2022/10/14 01:05:01 - mmengine - INFO - Epoch(train) [185][150/293] lr: 5.000000e-05 eta: 0:39:14 time: 0.367156 data_time: 0.081579 memory: 4980 loss_kpt: 0.000814 acc_pose: 0.767954 loss: 0.000814 2022/10/14 01:05:19 - mmengine - INFO - Epoch(train) [185][200/293] lr: 5.000000e-05 eta: 0:38:58 time: 0.363053 data_time: 0.069803 memory: 4980 loss_kpt: 0.000798 acc_pose: 0.765456 loss: 0.000798 2022/10/14 01:05:37 - mmengine - INFO - Epoch(train) [185][250/293] lr: 5.000000e-05 eta: 0:38:43 time: 0.360628 data_time: 0.073117 memory: 4980 loss_kpt: 0.000801 acc_pose: 0.825353 loss: 0.000801 2022/10/14 01:05:53 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:06:11 - mmengine - INFO - Epoch(train) [186][50/293] lr: 5.000000e-05 eta: 0:38:12 time: 0.366377 data_time: 0.114469 memory: 4980 loss_kpt: 0.000801 acc_pose: 0.744043 loss: 0.000801 2022/10/14 01:06:29 - mmengine - INFO - Epoch(train) [186][100/293] lr: 5.000000e-05 eta: 0:37:57 time: 0.358227 data_time: 0.101601 memory: 4980 loss_kpt: 0.000814 acc_pose: 0.685899 loss: 0.000814 2022/10/14 01:06:47 - mmengine - INFO - Epoch(train) [186][150/293] lr: 5.000000e-05 eta: 0:37:41 time: 0.360632 data_time: 0.073351 memory: 4980 loss_kpt: 0.000800 acc_pose: 0.714794 loss: 0.000800 2022/10/14 01:07:05 - mmengine - INFO - Epoch(train) [186][200/293] lr: 5.000000e-05 eta: 0:37:26 time: 0.357940 data_time: 0.078208 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.758321 loss: 0.000806 2022/10/14 01:07:23 - mmengine - INFO - Epoch(train) [186][250/293] lr: 5.000000e-05 eta: 0:37:10 time: 0.355104 data_time: 0.085222 memory: 4980 loss_kpt: 0.000793 acc_pose: 0.742015 loss: 0.000793 2022/10/14 01:07:38 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:07:57 - mmengine - INFO - Epoch(train) [187][50/293] lr: 5.000000e-05 eta: 0:36:40 time: 0.371036 data_time: 0.132759 memory: 4980 loss_kpt: 0.000820 acc_pose: 0.761933 loss: 0.000820 2022/10/14 01:08:14 - mmengine - INFO - Epoch(train) [187][100/293] lr: 5.000000e-05 eta: 0:36:24 time: 0.352192 data_time: 0.113835 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.745898 loss: 0.000806 2022/10/14 01:08:33 - mmengine - INFO - Epoch(train) [187][150/293] lr: 5.000000e-05 eta: 0:36:09 time: 0.368606 data_time: 0.107410 memory: 4980 loss_kpt: 0.000813 acc_pose: 0.770696 loss: 0.000813 2022/10/14 01:08:51 - mmengine - INFO - Epoch(train) [187][200/293] lr: 5.000000e-05 eta: 0:35:53 time: 0.356309 data_time: 0.114446 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.764872 loss: 0.000804 2022/10/14 01:09:09 - mmengine - INFO - Epoch(train) [187][250/293] lr: 5.000000e-05 eta: 0:35:38 time: 0.364663 data_time: 0.125661 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.694708 loss: 0.000806 2022/10/14 01:09:24 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:09:42 - mmengine - INFO - Epoch(train) [188][50/293] lr: 5.000000e-05 eta: 0:35:07 time: 0.372146 data_time: 0.100027 memory: 4980 loss_kpt: 0.000794 acc_pose: 0.771179 loss: 0.000794 2022/10/14 01:10:00 - mmengine - INFO - Epoch(train) [188][100/293] lr: 5.000000e-05 eta: 0:34:52 time: 0.358406 data_time: 0.094034 memory: 4980 loss_kpt: 0.000798 acc_pose: 0.768146 loss: 0.000798 2022/10/14 01:10:18 - mmengine - INFO - Epoch(train) [188][150/293] lr: 5.000000e-05 eta: 0:34:36 time: 0.359926 data_time: 0.095140 memory: 4980 loss_kpt: 0.000791 acc_pose: 0.764624 loss: 0.000791 2022/10/14 01:10:36 - mmengine - INFO - Epoch(train) [188][200/293] lr: 5.000000e-05 eta: 0:34:21 time: 0.357324 data_time: 0.086194 memory: 4980 loss_kpt: 0.000812 acc_pose: 0.722190 loss: 0.000812 2022/10/14 01:10:39 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:10:55 - mmengine - INFO - Epoch(train) [188][250/293] lr: 5.000000e-05 eta: 0:34:05 time: 0.366446 data_time: 0.072597 memory: 4980 loss_kpt: 0.000793 acc_pose: 0.723649 loss: 0.000793 2022/10/14 01:11:10 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:11:29 - mmengine - INFO - Epoch(train) [189][50/293] lr: 5.000000e-05 eta: 0:33:35 time: 0.374012 data_time: 0.091744 memory: 4980 loss_kpt: 0.000815 acc_pose: 0.760393 loss: 0.000815 2022/10/14 01:11:47 - mmengine - INFO - Epoch(train) [189][100/293] lr: 5.000000e-05 eta: 0:33:19 time: 0.376422 data_time: 0.081488 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.814179 loss: 0.000804 2022/10/14 01:12:05 - mmengine - INFO - Epoch(train) [189][150/293] lr: 5.000000e-05 eta: 0:33:04 time: 0.352857 data_time: 0.074562 memory: 4980 loss_kpt: 0.000801 acc_pose: 0.686683 loss: 0.000801 2022/10/14 01:12:23 - mmengine - INFO - Epoch(train) [189][200/293] lr: 5.000000e-05 eta: 0:32:48 time: 0.361832 data_time: 0.073677 memory: 4980 loss_kpt: 0.000805 acc_pose: 0.739242 loss: 0.000805 2022/10/14 01:12:41 - mmengine - INFO - Epoch(train) [189][250/293] lr: 5.000000e-05 eta: 0:32:33 time: 0.365634 data_time: 0.076122 memory: 4980 loss_kpt: 0.000823 acc_pose: 0.778833 loss: 0.000823 2022/10/14 01:12:57 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:13:15 - mmengine - INFO - Epoch(train) [190][50/293] lr: 5.000000e-05 eta: 0:32:02 time: 0.368522 data_time: 0.118548 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.744554 loss: 0.000804 2022/10/14 01:13:35 - mmengine - INFO - Epoch(train) [190][100/293] lr: 5.000000e-05 eta: 0:31:47 time: 0.387362 data_time: 0.088429 memory: 4980 loss_kpt: 0.000792 acc_pose: 0.793546 loss: 0.000792 2022/10/14 01:13:53 - mmengine - INFO - Epoch(train) [190][150/293] lr: 5.000000e-05 eta: 0:31:31 time: 0.369260 data_time: 0.079713 memory: 4980 loss_kpt: 0.000795 acc_pose: 0.786932 loss: 0.000795 2022/10/14 01:14:11 - mmengine - INFO - Epoch(train) [190][200/293] lr: 5.000000e-05 eta: 0:31:16 time: 0.351702 data_time: 0.075058 memory: 4980 loss_kpt: 0.000799 acc_pose: 0.776257 loss: 0.000799 2022/10/14 01:14:29 - mmengine - INFO - Epoch(train) [190][250/293] lr: 5.000000e-05 eta: 0:31:00 time: 0.356673 data_time: 0.079234 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.795212 loss: 0.000806 2022/10/14 01:14:44 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:14:44 - mmengine - INFO - Saving checkpoint at 190 epochs 2022/10/14 01:14:53 - mmengine - INFO - Epoch(val) [190][50/407] eta: 0:00:45 time: 0.126260 data_time: 0.071712 memory: 4980 2022/10/14 01:14:59 - mmengine - INFO - Epoch(val) [190][100/407] eta: 0:00:38 time: 0.125959 data_time: 0.071197 memory: 772 2022/10/14 01:15:05 - mmengine - INFO - Epoch(val) [190][150/407] eta: 0:00:33 time: 0.129707 data_time: 0.074065 memory: 772 2022/10/14 01:15:12 - mmengine - INFO - Epoch(val) [190][200/407] eta: 0:00:25 time: 0.124908 data_time: 0.065077 memory: 772 2022/10/14 01:15:18 - mmengine - INFO - Epoch(val) [190][250/407] eta: 0:00:20 time: 0.130142 data_time: 0.073198 memory: 772 2022/10/14 01:15:24 - mmengine - INFO - Epoch(val) [190][300/407] eta: 0:00:12 time: 0.117420 data_time: 0.059342 memory: 772 2022/10/14 01:15:30 - mmengine - INFO - Epoch(val) [190][350/407] eta: 0:00:06 time: 0.120096 data_time: 0.065694 memory: 772 2022/10/14 01:15:36 - mmengine - INFO - Epoch(val) [190][400/407] eta: 0:00:00 time: 0.119865 data_time: 0.065704 memory: 772 2022/10/14 01:16:13 - mmengine - INFO - Evaluating CocoMetric... 2022/10/14 01:16:27 - mmengine - INFO - Epoch(val) [190][407/407] coco/AP: 0.635928 coco/AP .5: 0.863521 coco/AP .75: 0.705178 coco/AP (M): 0.596598 coco/AP (L): 0.706169 coco/AR: 0.697229 coco/AR .5: 0.907903 coco/AR .75: 0.762752 coco/AR (M): 0.648429 coco/AR (L): 0.766184 2022/10/14 01:16:27 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_180.pth is removed 2022/10/14 01:16:29 - mmengine - INFO - The best checkpoint with 0.6359 coco/AP at 190 epoch is saved to best_coco/AP_epoch_190.pth. 2022/10/14 01:16:47 - mmengine - INFO - Epoch(train) [191][50/293] lr: 5.000000e-05 eta: 0:30:30 time: 0.374419 data_time: 0.120030 memory: 4980 loss_kpt: 0.000803 acc_pose: 0.748521 loss: 0.000803 2022/10/14 01:17:05 - mmengine - INFO - Epoch(train) [191][100/293] lr: 5.000000e-05 eta: 0:30:14 time: 0.359029 data_time: 0.085580 memory: 4980 loss_kpt: 0.000794 acc_pose: 0.796829 loss: 0.000794 2022/10/14 01:17:23 - mmengine - INFO - Epoch(train) [191][150/293] lr: 5.000000e-05 eta: 0:29:59 time: 0.363922 data_time: 0.108707 memory: 4980 loss_kpt: 0.000785 acc_pose: 0.798019 loss: 0.000785 2022/10/14 01:17:42 - mmengine - INFO - Epoch(train) [191][200/293] lr: 5.000000e-05 eta: 0:29:43 time: 0.361647 data_time: 0.070257 memory: 4980 loss_kpt: 0.000805 acc_pose: 0.743528 loss: 0.000805 2022/10/14 01:18:00 - mmengine - INFO - Epoch(train) [191][250/293] lr: 5.000000e-05 eta: 0:29:28 time: 0.362934 data_time: 0.079365 memory: 4980 loss_kpt: 0.000800 acc_pose: 0.774539 loss: 0.000800 2022/10/14 01:18:15 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:18:29 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:18:34 - mmengine - INFO - Epoch(train) [192][50/293] lr: 5.000000e-05 eta: 0:28:57 time: 0.377341 data_time: 0.099594 memory: 4980 loss_kpt: 0.000801 acc_pose: 0.752354 loss: 0.000801 2022/10/14 01:18:52 - mmengine - INFO - Epoch(train) [192][100/293] lr: 5.000000e-05 eta: 0:28:42 time: 0.354597 data_time: 0.070778 memory: 4980 loss_kpt: 0.000793 acc_pose: 0.689677 loss: 0.000793 2022/10/14 01:19:10 - mmengine - INFO - Epoch(train) [192][150/293] lr: 5.000000e-05 eta: 0:28:26 time: 0.357614 data_time: 0.077495 memory: 4980 loss_kpt: 0.000788 acc_pose: 0.786128 loss: 0.000788 2022/10/14 01:19:27 - mmengine - INFO - Epoch(train) [192][200/293] lr: 5.000000e-05 eta: 0:28:11 time: 0.350302 data_time: 0.071024 memory: 4980 loss_kpt: 0.000790 acc_pose: 0.778994 loss: 0.000790 2022/10/14 01:19:45 - mmengine - INFO - Epoch(train) [192][250/293] lr: 5.000000e-05 eta: 0:27:55 time: 0.363961 data_time: 0.094578 memory: 4980 loss_kpt: 0.000799 acc_pose: 0.817951 loss: 0.000799 2022/10/14 01:20:00 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:20:19 - mmengine - INFO - Epoch(train) [193][50/293] lr: 5.000000e-05 eta: 0:27:25 time: 0.372941 data_time: 0.087955 memory: 4980 loss_kpt: 0.000805 acc_pose: 0.755897 loss: 0.000805 2022/10/14 01:20:37 - mmengine - INFO - Epoch(train) [193][100/293] lr: 5.000000e-05 eta: 0:27:09 time: 0.367001 data_time: 0.071031 memory: 4980 loss_kpt: 0.000805 acc_pose: 0.724815 loss: 0.000805 2022/10/14 01:20:56 - mmengine - INFO - Epoch(train) [193][150/293] lr: 5.000000e-05 eta: 0:26:54 time: 0.368061 data_time: 0.072343 memory: 4980 loss_kpt: 0.000812 acc_pose: 0.785973 loss: 0.000812 2022/10/14 01:21:13 - mmengine - INFO - Epoch(train) [193][200/293] lr: 5.000000e-05 eta: 0:26:38 time: 0.348590 data_time: 0.078763 memory: 4980 loss_kpt: 0.000805 acc_pose: 0.803467 loss: 0.000805 2022/10/14 01:21:31 - mmengine - INFO - Epoch(train) [193][250/293] lr: 5.000000e-05 eta: 0:26:23 time: 0.360503 data_time: 0.085204 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.782756 loss: 0.000804 2022/10/14 01:21:47 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:22:06 - mmengine - INFO - Epoch(train) [194][50/293] lr: 5.000000e-05 eta: 0:25:52 time: 0.377200 data_time: 0.097009 memory: 4980 loss_kpt: 0.000805 acc_pose: 0.792975 loss: 0.000805 2022/10/14 01:22:24 - mmengine - INFO - Epoch(train) [194][100/293] lr: 5.000000e-05 eta: 0:25:37 time: 0.365509 data_time: 0.072054 memory: 4980 loss_kpt: 0.000791 acc_pose: 0.792890 loss: 0.000791 2022/10/14 01:22:42 - mmengine - INFO - Epoch(train) [194][150/293] lr: 5.000000e-05 eta: 0:25:21 time: 0.357730 data_time: 0.068909 memory: 4980 loss_kpt: 0.000824 acc_pose: 0.712328 loss: 0.000824 2022/10/14 01:23:00 - mmengine - INFO - Epoch(train) [194][200/293] lr: 5.000000e-05 eta: 0:25:06 time: 0.356783 data_time: 0.074133 memory: 4980 loss_kpt: 0.000819 acc_pose: 0.733764 loss: 0.000819 2022/10/14 01:23:18 - mmengine - INFO - Epoch(train) [194][250/293] lr: 5.000000e-05 eta: 0:24:50 time: 0.358508 data_time: 0.076958 memory: 4980 loss_kpt: 0.000793 acc_pose: 0.730027 loss: 0.000793 2022/10/14 01:23:33 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:23:52 - mmengine - INFO - Epoch(train) [195][50/293] lr: 5.000000e-05 eta: 0:24:20 time: 0.377727 data_time: 0.091643 memory: 4980 loss_kpt: 0.000789 acc_pose: 0.742872 loss: 0.000789 2022/10/14 01:24:10 - mmengine - INFO - Epoch(train) [195][100/293] lr: 5.000000e-05 eta: 0:24:05 time: 0.365493 data_time: 0.084972 memory: 4980 loss_kpt: 0.000795 acc_pose: 0.809020 loss: 0.000795 2022/10/14 01:24:28 - mmengine - INFO - Epoch(train) [195][150/293] lr: 5.000000e-05 eta: 0:23:49 time: 0.356692 data_time: 0.074835 memory: 4980 loss_kpt: 0.000808 acc_pose: 0.708614 loss: 0.000808 2022/10/14 01:24:31 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:24:46 - mmengine - INFO - Epoch(train) [195][200/293] lr: 5.000000e-05 eta: 0:23:33 time: 0.357302 data_time: 0.102720 memory: 4980 loss_kpt: 0.000801 acc_pose: 0.795091 loss: 0.000801 2022/10/14 01:25:04 - mmengine - INFO - Epoch(train) [195][250/293] lr: 5.000000e-05 eta: 0:23:18 time: 0.362537 data_time: 0.085856 memory: 4980 loss_kpt: 0.000791 acc_pose: 0.750929 loss: 0.000791 2022/10/14 01:25:19 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:25:39 - mmengine - INFO - Epoch(train) [196][50/293] lr: 5.000000e-05 eta: 0:22:48 time: 0.390765 data_time: 0.093795 memory: 4980 loss_kpt: 0.000789 acc_pose: 0.787112 loss: 0.000789 2022/10/14 01:25:57 - mmengine - INFO - Epoch(train) [196][100/293] lr: 5.000000e-05 eta: 0:22:32 time: 0.361534 data_time: 0.099615 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.686568 loss: 0.000804 2022/10/14 01:26:14 - mmengine - INFO - Epoch(train) [196][150/293] lr: 5.000000e-05 eta: 0:22:17 time: 0.351086 data_time: 0.124509 memory: 4980 loss_kpt: 0.000797 acc_pose: 0.735974 loss: 0.000797 2022/10/14 01:26:32 - mmengine - INFO - Epoch(train) [196][200/293] lr: 5.000000e-05 eta: 0:22:01 time: 0.356962 data_time: 0.139717 memory: 4980 loss_kpt: 0.000816 acc_pose: 0.764898 loss: 0.000816 2022/10/14 01:26:51 - mmengine - INFO - Epoch(train) [196][250/293] lr: 5.000000e-05 eta: 0:21:45 time: 0.370635 data_time: 0.082147 memory: 4980 loss_kpt: 0.000803 acc_pose: 0.701334 loss: 0.000803 2022/10/14 01:27:05 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:27:24 - mmengine - INFO - Epoch(train) [197][50/293] lr: 5.000000e-05 eta: 0:21:15 time: 0.366446 data_time: 0.124821 memory: 4980 loss_kpt: 0.000810 acc_pose: 0.712789 loss: 0.000810 2022/10/14 01:27:42 - mmengine - INFO - Epoch(train) [197][100/293] lr: 5.000000e-05 eta: 0:21:00 time: 0.362461 data_time: 0.087991 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.769570 loss: 0.000804 2022/10/14 01:28:00 - mmengine - INFO - Epoch(train) [197][150/293] lr: 5.000000e-05 eta: 0:20:44 time: 0.366507 data_time: 0.076849 memory: 4980 loss_kpt: 0.000803 acc_pose: 0.745787 loss: 0.000803 2022/10/14 01:28:18 - mmengine - INFO - Epoch(train) [197][200/293] lr: 5.000000e-05 eta: 0:20:29 time: 0.352941 data_time: 0.075451 memory: 4980 loss_kpt: 0.000803 acc_pose: 0.758041 loss: 0.000803 2022/10/14 01:28:36 - mmengine - INFO - Epoch(train) [197][250/293] lr: 5.000000e-05 eta: 0:20:13 time: 0.364172 data_time: 0.092417 memory: 4980 loss_kpt: 0.000816 acc_pose: 0.801429 loss: 0.000816 2022/10/14 01:28:51 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:29:10 - mmengine - INFO - Epoch(train) [198][50/293] lr: 5.000000e-05 eta: 0:19:43 time: 0.368385 data_time: 0.081542 memory: 4980 loss_kpt: 0.000801 acc_pose: 0.783519 loss: 0.000801 2022/10/14 01:29:28 - mmengine - INFO - Epoch(train) [198][100/293] lr: 5.000000e-05 eta: 0:19:27 time: 0.360806 data_time: 0.066251 memory: 4980 loss_kpt: 0.000797 acc_pose: 0.759702 loss: 0.000797 2022/10/14 01:29:46 - mmengine - INFO - Epoch(train) [198][150/293] lr: 5.000000e-05 eta: 0:19:12 time: 0.361242 data_time: 0.072202 memory: 4980 loss_kpt: 0.000810 acc_pose: 0.705846 loss: 0.000810 2022/10/14 01:30:04 - mmengine - INFO - Epoch(train) [198][200/293] lr: 5.000000e-05 eta: 0:18:56 time: 0.362175 data_time: 0.076567 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.739882 loss: 0.000804 2022/10/14 01:30:22 - mmengine - INFO - Epoch(train) [198][250/293] lr: 5.000000e-05 eta: 0:18:41 time: 0.363388 data_time: 0.072262 memory: 4980 loss_kpt: 0.000799 acc_pose: 0.747608 loss: 0.000799 2022/10/14 01:30:33 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:30:38 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:30:56 - mmengine - INFO - Epoch(train) [199][50/293] lr: 5.000000e-05 eta: 0:18:11 time: 0.371003 data_time: 0.100747 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.743746 loss: 0.000804 2022/10/14 01:31:15 - mmengine - INFO - Epoch(train) [199][100/293] lr: 5.000000e-05 eta: 0:17:55 time: 0.362829 data_time: 0.078508 memory: 4980 loss_kpt: 0.000797 acc_pose: 0.739296 loss: 0.000797 2022/10/14 01:31:33 - mmengine - INFO - Epoch(train) [199][150/293] lr: 5.000000e-05 eta: 0:17:39 time: 0.363809 data_time: 0.072666 memory: 4980 loss_kpt: 0.000783 acc_pose: 0.741733 loss: 0.000783 2022/10/14 01:31:50 - mmengine - INFO - Epoch(train) [199][200/293] lr: 5.000000e-05 eta: 0:17:24 time: 0.354420 data_time: 0.069048 memory: 4980 loss_kpt: 0.000816 acc_pose: 0.754855 loss: 0.000816 2022/10/14 01:32:08 - mmengine - INFO - Epoch(train) [199][250/293] lr: 5.000000e-05 eta: 0:17:08 time: 0.357830 data_time: 0.071639 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.838745 loss: 0.000806 2022/10/14 01:32:24 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:32:43 - mmengine - INFO - Epoch(train) [200][50/293] lr: 5.000000e-05 eta: 0:16:38 time: 0.374083 data_time: 0.145097 memory: 4980 loss_kpt: 0.000800 acc_pose: 0.776146 loss: 0.000800 2022/10/14 01:33:01 - mmengine - INFO - Epoch(train) [200][100/293] lr: 5.000000e-05 eta: 0:16:23 time: 0.362284 data_time: 0.069667 memory: 4980 loss_kpt: 0.000807 acc_pose: 0.753103 loss: 0.000807 2022/10/14 01:33:19 - mmengine - INFO - Epoch(train) [200][150/293] lr: 5.000000e-05 eta: 0:16:07 time: 0.361897 data_time: 0.074685 memory: 4980 loss_kpt: 0.000803 acc_pose: 0.772784 loss: 0.000803 2022/10/14 01:33:36 - mmengine - INFO - Epoch(train) [200][200/293] lr: 5.000000e-05 eta: 0:15:51 time: 0.348095 data_time: 0.069630 memory: 4980 loss_kpt: 0.000798 acc_pose: 0.724518 loss: 0.000798 2022/10/14 01:33:55 - mmengine - INFO - Epoch(train) [200][250/293] lr: 5.000000e-05 eta: 0:15:36 time: 0.367156 data_time: 0.087180 memory: 4980 loss_kpt: 0.000795 acc_pose: 0.778897 loss: 0.000795 2022/10/14 01:34:10 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:34:10 - mmengine - INFO - Saving checkpoint at 200 epochs 2022/10/14 01:34:19 - mmengine - INFO - Epoch(val) [200][50/407] eta: 0:00:50 time: 0.142679 data_time: 0.088571 memory: 4980 2022/10/14 01:34:26 - mmengine - INFO - Epoch(val) [200][100/407] eta: 0:00:41 time: 0.133994 data_time: 0.077910 memory: 772 2022/10/14 01:34:32 - mmengine - INFO - Epoch(val) [200][150/407] eta: 0:00:32 time: 0.125453 data_time: 0.069524 memory: 772 2022/10/14 01:34:39 - mmengine - INFO - Epoch(val) [200][200/407] eta: 0:00:26 time: 0.125962 data_time: 0.067557 memory: 772 2022/10/14 01:34:45 - mmengine - INFO - Epoch(val) [200][250/407] eta: 0:00:18 time: 0.119288 data_time: 0.066281 memory: 772 2022/10/14 01:34:51 - mmengine - INFO - Epoch(val) [200][300/407] eta: 0:00:13 time: 0.127940 data_time: 0.072870 memory: 772 2022/10/14 01:34:57 - mmengine - INFO - Epoch(val) [200][350/407] eta: 0:00:07 time: 0.130208 data_time: 0.074709 memory: 772 2022/10/14 01:35:03 - mmengine - INFO - Epoch(val) [200][400/407] eta: 0:00:00 time: 0.116454 data_time: 0.065484 memory: 772 2022/10/14 01:35:40 - mmengine - INFO - Evaluating CocoMetric... 2022/10/14 01:35:54 - mmengine - INFO - Epoch(val) [200][407/407] coco/AP: 0.636968 coco/AP .5: 0.864341 coco/AP .75: 0.705183 coco/AP (M): 0.596180 coco/AP (L): 0.708659 coco/AR: 0.698079 coco/AR .5: 0.908690 coco/AR .75: 0.762594 coco/AR (M): 0.649467 coco/AR (L): 0.766630 2022/10/14 01:35:54 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_190.pth is removed 2022/10/14 01:35:56 - mmengine - INFO - The best checkpoint with 0.6370 coco/AP at 200 epoch is saved to best_coco/AP_epoch_200.pth. 2022/10/14 01:36:15 - mmengine - INFO - Epoch(train) [201][50/293] lr: 5.000000e-06 eta: 0:15:06 time: 0.377277 data_time: 0.135386 memory: 4980 loss_kpt: 0.000812 acc_pose: 0.766237 loss: 0.000812 2022/10/14 01:36:33 - mmengine - INFO - Epoch(train) [201][100/293] lr: 5.000000e-06 eta: 0:14:50 time: 0.356781 data_time: 0.116205 memory: 4980 loss_kpt: 0.000810 acc_pose: 0.816184 loss: 0.000810 2022/10/14 01:36:51 - mmengine - INFO - Epoch(train) [201][150/293] lr: 5.000000e-06 eta: 0:14:35 time: 0.360595 data_time: 0.076432 memory: 4980 loss_kpt: 0.000808 acc_pose: 0.753563 loss: 0.000808 2022/10/14 01:37:09 - mmengine - INFO - Epoch(train) [201][200/293] lr: 5.000000e-06 eta: 0:14:19 time: 0.359013 data_time: 0.069929 memory: 4980 loss_kpt: 0.000792 acc_pose: 0.702418 loss: 0.000792 2022/10/14 01:37:26 - mmengine - INFO - Epoch(train) [201][250/293] lr: 5.000000e-06 eta: 0:14:03 time: 0.357302 data_time: 0.072894 memory: 4980 loss_kpt: 0.000783 acc_pose: 0.794948 loss: 0.000783 2022/10/14 01:37:42 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:38:01 - mmengine - INFO - Epoch(train) [202][50/293] lr: 5.000000e-06 eta: 0:13:34 time: 0.383550 data_time: 0.098368 memory: 4980 loss_kpt: 0.000781 acc_pose: 0.784101 loss: 0.000781 2022/10/14 01:38:19 - mmengine - INFO - Epoch(train) [202][100/293] lr: 5.000000e-06 eta: 0:13:18 time: 0.360128 data_time: 0.077329 memory: 4980 loss_kpt: 0.000796 acc_pose: 0.770656 loss: 0.000796 2022/10/14 01:38:22 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:38:37 - mmengine - INFO - Epoch(train) [202][150/293] lr: 5.000000e-06 eta: 0:13:02 time: 0.364472 data_time: 0.070932 memory: 4980 loss_kpt: 0.000803 acc_pose: 0.760609 loss: 0.000803 2022/10/14 01:38:55 - mmengine - INFO - Epoch(train) [202][200/293] lr: 5.000000e-06 eta: 0:12:47 time: 0.358347 data_time: 0.065917 memory: 4980 loss_kpt: 0.000794 acc_pose: 0.735252 loss: 0.000794 2022/10/14 01:39:13 - mmengine - INFO - Epoch(train) [202][250/293] lr: 5.000000e-06 eta: 0:12:31 time: 0.360646 data_time: 0.074346 memory: 4980 loss_kpt: 0.000814 acc_pose: 0.741325 loss: 0.000814 2022/10/14 01:39:29 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:39:48 - mmengine - INFO - Epoch(train) [203][50/293] lr: 5.000000e-06 eta: 0:12:01 time: 0.371933 data_time: 0.117595 memory: 4980 loss_kpt: 0.000807 acc_pose: 0.797106 loss: 0.000807 2022/10/14 01:40:06 - mmengine - INFO - Epoch(train) [203][100/293] lr: 5.000000e-06 eta: 0:11:46 time: 0.365552 data_time: 0.107460 memory: 4980 loss_kpt: 0.000806 acc_pose: 0.761942 loss: 0.000806 2022/10/14 01:40:24 - mmengine - INFO - Epoch(train) [203][150/293] lr: 5.000000e-06 eta: 0:11:30 time: 0.353070 data_time: 0.109854 memory: 4980 loss_kpt: 0.000784 acc_pose: 0.744673 loss: 0.000784 2022/10/14 01:40:42 - mmengine - INFO - Epoch(train) [203][200/293] lr: 5.000000e-06 eta: 0:11:15 time: 0.365727 data_time: 0.076558 memory: 4980 loss_kpt: 0.000810 acc_pose: 0.777684 loss: 0.000810 2022/10/14 01:41:00 - mmengine - INFO - Epoch(train) [203][250/293] lr: 5.000000e-06 eta: 0:10:59 time: 0.358302 data_time: 0.074837 memory: 4980 loss_kpt: 0.000786 acc_pose: 0.733857 loss: 0.000786 2022/10/14 01:41:15 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:41:33 - mmengine - INFO - Epoch(train) [204][50/293] lr: 5.000000e-06 eta: 0:10:29 time: 0.365271 data_time: 0.100994 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.740723 loss: 0.000804 2022/10/14 01:41:52 - mmengine - INFO - Epoch(train) [204][100/293] lr: 5.000000e-06 eta: 0:10:14 time: 0.368176 data_time: 0.074093 memory: 4980 loss_kpt: 0.000800 acc_pose: 0.730799 loss: 0.000800 2022/10/14 01:42:10 - mmengine - INFO - Epoch(train) [204][150/293] lr: 5.000000e-06 eta: 0:09:58 time: 0.360234 data_time: 0.072318 memory: 4980 loss_kpt: 0.000799 acc_pose: 0.718283 loss: 0.000799 2022/10/14 01:42:28 - mmengine - INFO - Epoch(train) [204][200/293] lr: 5.000000e-06 eta: 0:09:42 time: 0.365772 data_time: 0.080063 memory: 4980 loss_kpt: 0.000799 acc_pose: 0.809675 loss: 0.000799 2022/10/14 01:42:46 - mmengine - INFO - Epoch(train) [204][250/293] lr: 5.000000e-06 eta: 0:09:27 time: 0.357565 data_time: 0.071576 memory: 4980 loss_kpt: 0.000798 acc_pose: 0.800004 loss: 0.000798 2022/10/14 01:43:02 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:43:20 - mmengine - INFO - Epoch(train) [205][50/293] lr: 5.000000e-06 eta: 0:08:57 time: 0.373324 data_time: 0.086003 memory: 4980 loss_kpt: 0.000790 acc_pose: 0.778585 loss: 0.000790 2022/10/14 01:43:38 - mmengine - INFO - Epoch(train) [205][100/293] lr: 5.000000e-06 eta: 0:08:41 time: 0.362986 data_time: 0.072754 memory: 4980 loss_kpt: 0.000796 acc_pose: 0.777536 loss: 0.000796 2022/10/14 01:43:56 - mmengine - INFO - Epoch(train) [205][150/293] lr: 5.000000e-06 eta: 0:08:26 time: 0.361872 data_time: 0.071020 memory: 4980 loss_kpt: 0.000815 acc_pose: 0.736113 loss: 0.000815 2022/10/14 01:44:14 - mmengine - INFO - Epoch(train) [205][200/293] lr: 5.000000e-06 eta: 0:08:10 time: 0.356618 data_time: 0.074751 memory: 4980 loss_kpt: 0.000795 acc_pose: 0.767253 loss: 0.000795 2022/10/14 01:44:25 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:44:32 - mmengine - INFO - Epoch(train) [205][250/293] lr: 5.000000e-06 eta: 0:07:54 time: 0.358410 data_time: 0.072769 memory: 4980 loss_kpt: 0.000797 acc_pose: 0.777012 loss: 0.000797 2022/10/14 01:44:47 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:45:06 - mmengine - INFO - Epoch(train) [206][50/293] lr: 5.000000e-06 eta: 0:07:25 time: 0.374280 data_time: 0.135214 memory: 4980 loss_kpt: 0.000809 acc_pose: 0.768531 loss: 0.000809 2022/10/14 01:45:24 - mmengine - INFO - Epoch(train) [206][100/293] lr: 5.000000e-06 eta: 0:07:09 time: 0.360719 data_time: 0.107044 memory: 4980 loss_kpt: 0.000794 acc_pose: 0.766490 loss: 0.000794 2022/10/14 01:45:42 - mmengine - INFO - Epoch(train) [206][150/293] lr: 5.000000e-06 eta: 0:06:53 time: 0.360941 data_time: 0.085952 memory: 4980 loss_kpt: 0.000809 acc_pose: 0.762845 loss: 0.000809 2022/10/14 01:46:01 - mmengine - INFO - Epoch(train) [206][200/293] lr: 5.000000e-06 eta: 0:06:38 time: 0.365987 data_time: 0.077435 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.702396 loss: 0.000804 2022/10/14 01:46:18 - mmengine - INFO - Epoch(train) [206][250/293] lr: 5.000000e-06 eta: 0:06:22 time: 0.352829 data_time: 0.108595 memory: 4980 loss_kpt: 0.000804 acc_pose: 0.803815 loss: 0.000804 2022/10/14 01:46:34 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:46:54 - mmengine - INFO - Epoch(train) [207][50/293] lr: 5.000000e-06 eta: 0:05:53 time: 0.392820 data_time: 0.101492 memory: 4980 loss_kpt: 0.000796 acc_pose: 0.699281 loss: 0.000796 2022/10/14 01:47:14 - mmengine - INFO - Epoch(train) [207][100/293] lr: 5.000000e-06 eta: 0:05:37 time: 0.400028 data_time: 0.073623 memory: 4980 loss_kpt: 0.000810 acc_pose: 0.758293 loss: 0.000810 2022/10/14 01:47:33 - mmengine - INFO - Epoch(train) [207][150/293] lr: 5.000000e-06 eta: 0:05:21 time: 0.392752 data_time: 0.079408 memory: 4980 loss_kpt: 0.000793 acc_pose: 0.741362 loss: 0.000793 2022/10/14 01:47:52 - mmengine - INFO - Epoch(train) [207][200/293] lr: 5.000000e-06 eta: 0:05:06 time: 0.384565 data_time: 0.089487 memory: 4980 loss_kpt: 0.000800 acc_pose: 0.721258 loss: 0.000800 2022/10/14 01:48:12 - mmengine - INFO - Epoch(train) [207][250/293] lr: 5.000000e-06 eta: 0:04:50 time: 0.395874 data_time: 0.114199 memory: 4980 loss_kpt: 0.000801 acc_pose: 0.752589 loss: 0.000801 2022/10/14 01:48:28 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:48:47 - mmengine - INFO - Epoch(train) [208][50/293] lr: 5.000000e-06 eta: 0:04:20 time: 0.386445 data_time: 0.082352 memory: 4980 loss_kpt: 0.000799 acc_pose: 0.764737 loss: 0.000799 2022/10/14 01:49:06 - mmengine - INFO - Epoch(train) [208][100/293] lr: 5.000000e-06 eta: 0:04:05 time: 0.376474 data_time: 0.075837 memory: 4980 loss_kpt: 0.000793 acc_pose: 0.787085 loss: 0.000793 2022/10/14 01:49:25 - mmengine - INFO - Epoch(train) [208][150/293] lr: 5.000000e-06 eta: 0:03:49 time: 0.369316 data_time: 0.080413 memory: 4980 loss_kpt: 0.000789 acc_pose: 0.754260 loss: 0.000789 2022/10/14 01:49:44 - mmengine - INFO - Epoch(train) [208][200/293] lr: 5.000000e-06 eta: 0:03:33 time: 0.383900 data_time: 0.090490 memory: 4980 loss_kpt: 0.000807 acc_pose: 0.750666 loss: 0.000807 2022/10/14 01:50:02 - mmengine - INFO - Epoch(train) [208][250/293] lr: 5.000000e-06 eta: 0:03:18 time: 0.364253 data_time: 0.070431 memory: 4980 loss_kpt: 0.000798 acc_pose: 0.720555 loss: 0.000798 2022/10/14 01:50:18 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:50:37 - mmengine - INFO - Epoch(train) [209][50/293] lr: 5.000000e-06 eta: 0:02:48 time: 0.381878 data_time: 0.093435 memory: 4980 loss_kpt: 0.000800 acc_pose: 0.761180 loss: 0.000800 2022/10/14 01:50:39 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:50:55 - mmengine - INFO - Epoch(train) [209][100/293] lr: 5.000000e-06 eta: 0:02:32 time: 0.364177 data_time: 0.066391 memory: 4980 loss_kpt: 0.000799 acc_pose: 0.764695 loss: 0.000799 2022/10/14 01:51:12 - mmengine - INFO - Epoch(train) [209][150/293] lr: 5.000000e-06 eta: 0:02:17 time: 0.345968 data_time: 0.084525 memory: 4980 loss_kpt: 0.000783 acc_pose: 0.786319 loss: 0.000783 2022/10/14 01:51:30 - mmengine - INFO - Epoch(train) [209][200/293] lr: 5.000000e-06 eta: 0:02:01 time: 0.352259 data_time: 0.070599 memory: 4980 loss_kpt: 0.000803 acc_pose: 0.766270 loss: 0.000803 2022/10/14 01:51:48 - mmengine - INFO - Epoch(train) [209][250/293] lr: 5.000000e-06 eta: 0:01:45 time: 0.355393 data_time: 0.095490 memory: 4980 loss_kpt: 0.000802 acc_pose: 0.792403 loss: 0.000802 2022/10/14 01:52:03 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:52:22 - mmengine - INFO - Epoch(train) [210][50/293] lr: 5.000000e-06 eta: 0:01:16 time: 0.372972 data_time: 0.102963 memory: 4980 loss_kpt: 0.000799 acc_pose: 0.692663 loss: 0.000799 2022/10/14 01:52:39 - mmengine - INFO - Epoch(train) [210][100/293] lr: 5.000000e-06 eta: 0:01:00 time: 0.350861 data_time: 0.085850 memory: 4980 loss_kpt: 0.000795 acc_pose: 0.752260 loss: 0.000795 2022/10/14 01:52:57 - mmengine - INFO - Epoch(train) [210][150/293] lr: 5.000000e-06 eta: 0:00:45 time: 0.357148 data_time: 0.125301 memory: 4980 loss_kpt: 0.000807 acc_pose: 0.716096 loss: 0.000807 2022/10/14 01:53:16 - mmengine - INFO - Epoch(train) [210][200/293] lr: 5.000000e-06 eta: 0:00:29 time: 0.365207 data_time: 0.082665 memory: 4980 loss_kpt: 0.000785 acc_pose: 0.745626 loss: 0.000785 2022/10/14 01:53:34 - mmengine - INFO - Epoch(train) [210][250/293] lr: 5.000000e-06 eta: 0:00:13 time: 0.365730 data_time: 0.110851 memory: 4980 loss_kpt: 0.000793 acc_pose: 0.774972 loss: 0.000793 2022/10/14 01:53:49 - mmengine - INFO - Exp name: td-hm_shufflenetv2_8xb64-210e_coco-384x288_20221013_190117 2022/10/14 01:53:49 - mmengine - INFO - Saving checkpoint at 210 epochs 2022/10/14 01:53:58 - mmengine - INFO - Epoch(val) [210][50/407] eta: 0:00:44 time: 0.125879 data_time: 0.067567 memory: 4980 2022/10/14 01:54:04 - mmengine - INFO - Epoch(val) [210][100/407] eta: 0:00:38 time: 0.126441 data_time: 0.073012 memory: 772 2022/10/14 01:54:10 - mmengine - INFO - Epoch(val) [210][150/407] eta: 0:00:31 time: 0.121882 data_time: 0.066670 memory: 772 2022/10/14 01:54:16 - mmengine - INFO - Epoch(val) [210][200/407] eta: 0:00:25 time: 0.121660 data_time: 0.067329 memory: 772 2022/10/14 01:54:22 - mmengine - INFO - Epoch(val) [210][250/407] eta: 0:00:18 time: 0.119454 data_time: 0.059783 memory: 772 2022/10/14 01:54:28 - mmengine - INFO - Epoch(val) [210][300/407] eta: 0:00:12 time: 0.118444 data_time: 0.066149 memory: 772 2022/10/14 01:54:34 - mmengine - INFO - Epoch(val) [210][350/407] eta: 0:00:07 time: 0.125864 data_time: 0.070141 memory: 772 2022/10/14 01:54:40 - mmengine - INFO - Epoch(val) [210][400/407] eta: 0:00:00 time: 0.116418 data_time: 0.061206 memory: 772 2022/10/14 01:55:16 - mmengine - INFO - Evaluating CocoMetric... 2022/10/14 01:55:30 - mmengine - INFO - Epoch(val) [210][407/407] coco/AP: 0.638249 coco/AP .5: 0.866388 coco/AP .75: 0.707147 coco/AP (M): 0.598970 coco/AP (L): 0.708068 coco/AR: 0.699355 coco/AR .5: 0.910579 coco/AR .75: 0.765428 coco/AR (M): 0.651325 coco/AR (L): 0.767261 2022/10/14 01:55:30 - mmengine - INFO - The previous best checkpoint /mnt/petrelfs/liqikai/openmmlab/pt112cu113py38/mmpose/work_dirs/20221013/shufflenetv2_384/best_coco/AP_epoch_200.pth is removed 2022/10/14 01:55:32 - mmengine - INFO - The best checkpoint with 0.6382 coco/AP at 210 epoch is saved to best_coco/AP_epoch_210.pth.