2022/09/19 17:21:14 - mmengine - INFO - ------------------------------------------------------------ System environment: sys.platform: linux Python: 3.7.13 (default, Mar 29 2022, 02:18:16) [GCC 7.5.0] CUDA available: True numpy_random_seed: 1159080279 GPU 0,1,2,3,4,5,6,7: NVIDIA A100-SXM4-80GB CUDA_HOME: /mnt/cache/share/cuda-11.1 NVCC: Cuda compilation tools, release 11.1, V11.1.74 GCC: gcc (GCC) 5.4.0 PyTorch: 1.9.0+cu111 PyTorch compiling details: PyTorch built with: - GCC 7.3 - C++ Version: 201402 - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications - Intel(R) MKL-DNN v2.1.2 (Git Hash 98be7e8afa711dc9b66c8ff3504129cb82013cdb) - OpenMP 201511 (a.k.a. OpenMP 4.5) - NNPACK is enabled - CPU capability usage: AVX2 - CUDA Runtime 11.1 - 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 8.0.5 - Magma 2.5.2 - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.9.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, TorchVision: 0.10.0+cu111 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 ------------------------------------------------------------ 2022/09/19 17:21:24 - 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=1, save_best='coco/AP', rule='greater', max_keep_ckpts=1), 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({ '/mnt/lustre/share_data/openmmlab/datasets/detection/coco/': 's3://openmmlab/datasets/detection/coco/' })) 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='SimCCLabel', input_size=(192, 256), sigma=6.0, simcc_split_ratio=2.0) 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='MobileNetV2', widen_factor=1.0, out_indices=(7, ), init_cfg=dict(type='Pretrained', checkpoint='mmcls://mobilenet_v2')), head=dict( type='SimCCHead', in_channels=1280, out_channels=17, input_size=(192, 256), in_featuremap_size=(6, 8), simcc_split_ratio=2.0, deconv_out_channels=None, loss=dict(type='KLDiscretLoss', use_target_weight=True), decoder=dict( type='SimCCLabel', input_size=(192, 256), sigma=6.0, simcc_split_ratio=2.0)), test_cfg=dict(flip_test=True, flip_mode='heatmap', shift_heatmap=True)) dataset_type = 'CocoDataset' data_mode = 'topdown' data_root = '/mnt/lustre/share_data/openmmlab/datasets/detection/coco/' train_pipeline = [ dict( type='LoadImage', file_client_args=dict( backend='petrel', path_mapping=dict({ '/mnt/lustre/share_data/openmmlab/datasets/detection/coco/': 's3://openmmlab/datasets/detection/coco/' }))), dict(type='GetBBoxCenterScale'), dict(type='RandomFlip', direction='horizontal'), dict(type='RandomHalfBody'), dict(type='RandomBBoxTransform'), dict(type='TopdownAffine', input_size=(192, 256)), dict( type='GenerateTarget', target_type='keypoint_xy_label', encoder=dict( type='SimCCLabel', input_size=(192, 256), sigma=6.0, simcc_split_ratio=2.0)), dict(type='PackPoseInputs') ] val_pipeline = [ dict(type='LoadImage', file_client_args=dict(backend='disk')), dict(type='GetBBoxCenterScale'), dict(type='TopdownAffine', input_size=(192, 256)), dict(type='PackPoseInputs') ] train_dataloader = dict( batch_size=64, num_workers=4, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='CocoDataset', data_root='/mnt/lustre/share_data/openmmlab/datasets/detection/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({ '/mnt/lustre/share_data/openmmlab/datasets/detection/coco/': 's3://openmmlab/datasets/detection/coco/' }))), dict(type='GetBBoxCenterScale'), dict(type='RandomFlip', direction='horizontal'), dict(type='RandomHalfBody'), dict(type='RandomBBoxTransform'), dict(type='TopdownAffine', input_size=(192, 256)), dict( type='GenerateTarget', target_type='keypoint_xy_label', encoder=dict( type='SimCCLabel', input_size=(192, 256), sigma=6.0, simcc_split_ratio=2.0)), 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='/mnt/lustre/share_data/openmmlab/datasets/detection/coco/', data_mode='topdown', ann_file='annotations/person_keypoints_val2017.json', bbox_file= '/mnt/lustre/share_data/openmmlab/datasets/detection/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='disk')), dict(type='GetBBoxCenterScale'), dict(type='TopdownAffine', input_size=(192, 256)), dict(type='PackPoseInputs') ])) test_dataloader = dict( batch_size=32, num_workers=2, persistent_workers=True, drop_last=False, sampler=dict(type='DefaultSampler', shuffle=False, round_up=False), dataset=dict( type='CocoDataset', data_root='/mnt/lustre/share_data/openmmlab/datasets/detection/coco/', data_mode='topdown', ann_file='annotations/person_keypoints_val2017.json', bbox_file= '/mnt/lustre/share_data/openmmlab/datasets/detection/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='disk')), dict(type='GetBBoxCenterScale'), dict(type='TopdownAffine', input_size=(192, 256)), dict(type='PackPoseInputs') ])) val_evaluator = dict( type='CocoMetric', ann_file= '/mnt/lustre/share_data/openmmlab/datasets/detection/coco/annotations/person_keypoints_val2017.json' ) test_evaluator = dict( type='CocoMetric', ann_file= '/mnt/lustre/share_data/openmmlab/datasets/detection/coco/annotations/person_keypoints_val2017.json' ) launcher = 'slurm' work_dir = '/mnt/lustre/jiangtao/experiment3/simcc_mb2_256' 2022/09/19 17:25:26 - 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. 2022/09/19 17:25:26 - 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. 2022/09/19 17:25:26 - 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. 2022/09/19 17:25:26 - 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. 2022/09/19 17:25:26 - 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. 2022/09/19 17:25:26 - 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. 2022/09/19 17:25:26 - 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. 2022/09/19 17:25:26 - 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. 2022/09/19 17:26:09 - 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. 2022/09/19 17:26:34 - 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. 2022/09/19 17:27:21 - 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. 2022/09/19 17:27:21 - 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. 2022/09/19 17:27:21 - 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([32, 3, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.conv1.bn.weight - torch.Size([32]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.conv1.bn.bias - torch.Size([32]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer1.0.conv.0.conv.weight - torch.Size([32, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer1.0.conv.0.bn.weight - torch.Size([32]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer1.0.conv.0.bn.bias - torch.Size([32]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer1.0.conv.1.conv.weight - torch.Size([16, 32, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer1.0.conv.1.bn.weight - torch.Size([16]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer1.0.conv.1.bn.bias - torch.Size([16]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.0.conv.0.conv.weight - torch.Size([96, 16, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.0.conv.0.bn.weight - torch.Size([96]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.0.conv.0.bn.bias - torch.Size([96]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.0.conv.1.conv.weight - torch.Size([96, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.0.conv.1.bn.weight - torch.Size([96]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.0.conv.1.bn.bias - torch.Size([96]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.0.conv.2.conv.weight - torch.Size([24, 96, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.0.conv.2.bn.weight - torch.Size([24]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.0.conv.2.bn.bias - torch.Size([24]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.1.conv.0.conv.weight - torch.Size([144, 24, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.1.conv.0.bn.weight - torch.Size([144]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.1.conv.0.bn.bias - torch.Size([144]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.1.conv.1.conv.weight - torch.Size([144, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.1.conv.1.bn.weight - torch.Size([144]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.1.conv.1.bn.bias - torch.Size([144]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.1.conv.2.conv.weight - torch.Size([24, 144, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.1.conv.2.bn.weight - torch.Size([24]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer2.1.conv.2.bn.bias - torch.Size([24]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.0.conv.0.conv.weight - torch.Size([144, 24, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.0.conv.0.bn.weight - torch.Size([144]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.0.conv.0.bn.bias - torch.Size([144]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.0.conv.1.conv.weight - torch.Size([144, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.0.conv.1.bn.weight - torch.Size([144]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.0.conv.1.bn.bias - torch.Size([144]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.0.conv.2.conv.weight - torch.Size([32, 144, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.0.conv.2.bn.weight - torch.Size([32]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.0.conv.2.bn.bias - torch.Size([32]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.1.conv.0.conv.weight - torch.Size([192, 32, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.1.conv.0.bn.weight - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.1.conv.0.bn.bias - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.1.conv.1.conv.weight - torch.Size([192, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.1.conv.1.bn.weight - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.1.conv.1.bn.bias - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.1.conv.2.conv.weight - torch.Size([32, 192, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.1.conv.2.bn.weight - torch.Size([32]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.1.conv.2.bn.bias - torch.Size([32]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.2.conv.0.conv.weight - torch.Size([192, 32, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.2.conv.0.bn.weight - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.2.conv.0.bn.bias - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.2.conv.1.conv.weight - torch.Size([192, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.2.conv.1.bn.weight - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.2.conv.1.bn.bias - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.2.conv.2.conv.weight - torch.Size([32, 192, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.2.conv.2.bn.weight - torch.Size([32]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer3.2.conv.2.bn.bias - torch.Size([32]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.0.conv.0.conv.weight - torch.Size([192, 32, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.0.conv.0.bn.weight - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.0.conv.0.bn.bias - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.0.conv.1.conv.weight - torch.Size([192, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.0.conv.1.bn.weight - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.0.conv.1.bn.bias - torch.Size([192]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.0.conv.2.conv.weight - torch.Size([64, 192, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.0.conv.2.bn.weight - torch.Size([64]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.0.conv.2.bn.bias - torch.Size([64]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.1.conv.0.conv.weight - torch.Size([384, 64, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.1.conv.0.bn.weight - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.1.conv.0.bn.bias - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.1.conv.1.conv.weight - torch.Size([384, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.1.conv.1.bn.weight - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.1.conv.1.bn.bias - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.1.conv.2.conv.weight - torch.Size([64, 384, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.1.conv.2.bn.weight - torch.Size([64]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.1.conv.2.bn.bias - torch.Size([64]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.2.conv.0.conv.weight - torch.Size([384, 64, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.2.conv.0.bn.weight - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.2.conv.0.bn.bias - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.2.conv.1.conv.weight - torch.Size([384, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.2.conv.1.bn.weight - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.2.conv.1.bn.bias - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.2.conv.2.conv.weight - torch.Size([64, 384, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.2.conv.2.bn.weight - torch.Size([64]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.2.conv.2.bn.bias - torch.Size([64]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.3.conv.0.conv.weight - torch.Size([384, 64, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.3.conv.0.bn.weight - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.3.conv.0.bn.bias - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.3.conv.1.conv.weight - torch.Size([384, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.3.conv.1.bn.weight - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.3.conv.1.bn.bias - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.3.conv.2.conv.weight - torch.Size([64, 384, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.3.conv.2.bn.weight - torch.Size([64]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer4.3.conv.2.bn.bias - torch.Size([64]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.0.conv.0.conv.weight - torch.Size([384, 64, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.0.conv.0.bn.weight - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.0.conv.0.bn.bias - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.0.conv.1.conv.weight - torch.Size([384, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.0.conv.1.bn.weight - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.0.conv.1.bn.bias - torch.Size([384]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.0.conv.2.conv.weight - torch.Size([96, 384, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.0.conv.2.bn.weight - torch.Size([96]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.0.conv.2.bn.bias - torch.Size([96]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.1.conv.0.conv.weight - torch.Size([576, 96, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.1.conv.0.bn.weight - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.1.conv.0.bn.bias - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.1.conv.1.conv.weight - torch.Size([576, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.1.conv.1.bn.weight - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.1.conv.1.bn.bias - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.1.conv.2.conv.weight - torch.Size([96, 576, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.1.conv.2.bn.weight - torch.Size([96]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.1.conv.2.bn.bias - torch.Size([96]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.2.conv.0.conv.weight - torch.Size([576, 96, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.2.conv.0.bn.weight - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.2.conv.0.bn.bias - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.2.conv.1.conv.weight - torch.Size([576, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.2.conv.1.bn.weight - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.2.conv.1.bn.bias - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.2.conv.2.conv.weight - torch.Size([96, 576, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.2.conv.2.bn.weight - torch.Size([96]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer5.2.conv.2.bn.bias - torch.Size([96]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.0.conv.0.conv.weight - torch.Size([576, 96, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.0.conv.0.bn.weight - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.0.conv.0.bn.bias - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.0.conv.1.conv.weight - torch.Size([576, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.0.conv.1.bn.weight - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.0.conv.1.bn.bias - torch.Size([576]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.0.conv.2.conv.weight - torch.Size([160, 576, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.0.conv.2.bn.weight - torch.Size([160]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.0.conv.2.bn.bias - torch.Size([160]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.1.conv.0.conv.weight - torch.Size([960, 160, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.1.conv.0.bn.weight - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.1.conv.0.bn.bias - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.1.conv.1.conv.weight - torch.Size([960, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.1.conv.1.bn.weight - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.1.conv.1.bn.bias - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.1.conv.2.conv.weight - torch.Size([160, 960, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.1.conv.2.bn.weight - torch.Size([160]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.1.conv.2.bn.bias - torch.Size([160]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.2.conv.0.conv.weight - torch.Size([960, 160, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.2.conv.0.bn.weight - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.2.conv.0.bn.bias - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.2.conv.1.conv.weight - torch.Size([960, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.2.conv.1.bn.weight - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.2.conv.1.bn.bias - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.2.conv.2.conv.weight - torch.Size([160, 960, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.2.conv.2.bn.weight - torch.Size([160]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer6.2.conv.2.bn.bias - torch.Size([160]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer7.0.conv.0.conv.weight - torch.Size([960, 160, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer7.0.conv.0.bn.weight - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer7.0.conv.0.bn.bias - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer7.0.conv.1.conv.weight - torch.Size([960, 1, 3, 3]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer7.0.conv.1.bn.weight - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer7.0.conv.1.bn.bias - torch.Size([960]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer7.0.conv.2.conv.weight - torch.Size([320, 960, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer7.0.conv.2.bn.weight - torch.Size([320]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.layer7.0.conv.2.bn.bias - torch.Size([320]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.conv2.conv.weight - torch.Size([1280, 320, 1, 1]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.conv2.bn.weight - torch.Size([1280]): PretrainedInit: load from mmcls://mobilenet_v2 backbone.conv2.bn.bias - torch.Size([1280]): PretrainedInit: load from mmcls://mobilenet_v2 head.final_layer.weight - torch.Size([17, 1280, 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 head.mlp_head_x.weight - torch.Size([384, 48]): NormalInit: mean=0, std=0.01, bias=0 head.mlp_head_x.bias - torch.Size([384]): NormalInit: mean=0, std=0.01, bias=0 head.mlp_head_y.weight - torch.Size([512, 48]): NormalInit: mean=0, std=0.01, bias=0 head.mlp_head_y.bias - torch.Size([512]): NormalInit: mean=0, std=0.01, bias=0 2022/09/19 17:27:21 - mmengine - INFO - Checkpoints will be saved to /mnt/lustre/jiangtao/experiment3/simcc_mb2_256 by HardDiskBackend. 2022/09/19 17:31:19 - mmengine - INFO - Epoch(train) [1][50/293] lr: 4.954910e-05 eta: 3 days, 9:16:47 time: 4.759387 data_time: 1.649016 memory: 3324 loss_kpt: 0.468156 acc_pose: 0.017312 loss: 0.468156 2022/09/19 17:34:37 - mmengine - INFO - Epoch(train) [1][100/293] lr: 9.959920e-05 eta: 3 days, 2:27:34 time: 3.967765 data_time: 1.288997 memory: 3324 loss_kpt: 0.442890 acc_pose: 0.023678 loss: 0.442890 2022/09/19 17:37:42 - mmengine - INFO - Epoch(train) [1][150/293] lr: 1.496493e-04 eta: 2 days, 22:34:05 time: 3.689532 data_time: 1.068424 memory: 3324 loss_kpt: 0.407947 acc_pose: 0.074627 loss: 0.407947 2022/09/19 17:41:19 - mmengine - INFO - Epoch(train) [1][200/293] lr: 1.996994e-04 eta: 2 days, 23:23:51 time: 4.347180 data_time: 1.146349 memory: 3324 loss_kpt: 0.365081 acc_pose: 0.131643 loss: 0.365081 2022/09/19 17:44:12 - mmengine - INFO - Epoch(train) [1][250/293] lr: 2.497495e-04 eta: 2 days, 20:49:36 time: 3.452876 data_time: 1.110123 memory: 3324 loss_kpt: 0.333576 acc_pose: 0.195880 loss: 0.333576 2022/09/19 17:46:42 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 17:46:42 - mmengine - INFO - Saving checkpoint at 1 epochs 2022/09/19 17:49:58 - mmengine - INFO - Epoch(train) [2][50/293] lr: 3.428427e-04 eta: 2 days, 10:50:07 time: 3.530144 data_time: 1.162096 memory: 3324 loss_kpt: 0.299110 acc_pose: 0.278772 loss: 0.299110 2022/09/19 17:52:46 - mmengine - INFO - Epoch(train) [2][100/293] lr: 3.928928e-04 eta: 2 days, 10:32:15 time: 3.346070 data_time: 0.948562 memory: 3324 loss_kpt: 0.285967 acc_pose: 0.326162 loss: 0.285967 2022/09/19 17:55:40 - mmengine - INFO - Epoch(train) [2][150/293] lr: 4.429429e-04 eta: 2 days, 10:34:24 time: 3.490599 data_time: 1.069263 memory: 3324 loss_kpt: 0.271778 acc_pose: 0.360462 loss: 0.271778 2022/09/19 17:58:27 - mmengine - INFO - Epoch(train) [2][200/293] lr: 4.929930e-04 eta: 2 days, 10:18:58 time: 3.330181 data_time: 1.126161 memory: 3324 loss_kpt: 0.266846 acc_pose: 0.361593 loss: 0.266846 2022/09/19 18:01:08 - mmengine - INFO - Epoch(train) [2][250/293] lr: 5.000000e-04 eta: 2 days, 9:56:17 time: 3.227738 data_time: 0.800217 memory: 3324 loss_kpt: 0.263451 acc_pose: 0.429289 loss: 0.263451 2022/09/19 18:03:40 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 18:03:40 - mmengine - INFO - Saving checkpoint at 2 epochs 2022/09/19 18:07:37 - mmengine - INFO - Epoch(train) [3][50/293] lr: 5.000000e-04 eta: 2 days, 7:01:38 time: 4.238784 data_time: 1.270877 memory: 3324 loss_kpt: 0.252087 acc_pose: 0.442660 loss: 0.252087 2022/09/19 18:10:42 - mmengine - INFO - Epoch(train) [3][100/293] lr: 5.000000e-04 eta: 2 days, 7:32:29 time: 3.707402 data_time: 1.116146 memory: 3324 loss_kpt: 0.249452 acc_pose: 0.420027 loss: 0.249452 2022/09/19 18:13:39 - mmengine - INFO - Epoch(train) [3][150/293] lr: 5.000000e-04 eta: 2 days, 7:46:26 time: 3.528588 data_time: 1.101233 memory: 3324 loss_kpt: 0.245352 acc_pose: 0.448195 loss: 0.245352 2022/09/19 18:17:08 - mmengine - INFO - Epoch(train) [3][200/293] lr: 5.000000e-04 eta: 2 days, 8:40:31 time: 4.185291 data_time: 1.904859 memory: 3324 loss_kpt: 0.239289 acc_pose: 0.437656 loss: 0.239289 2022/09/19 18:19:51 - mmengine - INFO - Epoch(train) [3][250/293] lr: 5.000000e-04 eta: 2 days, 8:31:25 time: 3.254574 data_time: 0.942635 memory: 3324 loss_kpt: 0.234137 acc_pose: 0.480564 loss: 0.234137 2022/09/19 18:22:11 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 18:22:11 - mmengine - INFO - Saving checkpoint at 3 epochs 2022/09/19 18:25:17 - mmengine - INFO - Epoch(train) [4][50/293] lr: 5.000000e-04 eta: 2 days, 5:52:29 time: 3.407837 data_time: 1.122385 memory: 3324 loss_kpt: 0.232678 acc_pose: 0.472745 loss: 0.232678 2022/09/19 18:28:04 - mmengine - INFO - Epoch(train) [4][100/293] lr: 5.000000e-04 eta: 2 days, 5:56:48 time: 3.335985 data_time: 0.911154 memory: 3324 loss_kpt: 0.226257 acc_pose: 0.438901 loss: 0.226257 2022/09/19 18:29:16 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 18:30:53 - mmengine - INFO - Epoch(train) [4][150/293] lr: 5.000000e-04 eta: 2 days, 6:02:26 time: 3.376920 data_time: 1.003980 memory: 3324 loss_kpt: 0.226694 acc_pose: 0.547468 loss: 0.226694 2022/09/19 18:33:40 - mmengine - INFO - Epoch(train) [4][200/293] lr: 5.000000e-04 eta: 2 days, 6:05:40 time: 3.342280 data_time: 1.111268 memory: 3324 loss_kpt: 0.220925 acc_pose: 0.446213 loss: 0.220925 2022/09/19 18:36:29 - mmengine - INFO - Epoch(train) [4][250/293] lr: 5.000000e-04 eta: 2 days, 6:10:03 time: 3.380016 data_time: 1.004879 memory: 3324 loss_kpt: 0.225725 acc_pose: 0.520848 loss: 0.225725 2022/09/19 18:38:29 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 18:38:29 - mmengine - INFO - Saving checkpoint at 4 epochs 2022/09/19 18:39:08 - mmengine - INFO - Epoch(train) [5][50/293] lr: 5.000000e-04 eta: 2 days, 2:28:08 time: 0.730847 data_time: 0.142494 memory: 3324 loss_kpt: 0.221083 acc_pose: 0.527871 loss: 0.221083 2022/09/19 18:39:53 - mmengine - INFO - Epoch(train) [5][100/293] lr: 5.000000e-04 eta: 2 days, 1:01:46 time: 0.888135 data_time: 0.166681 memory: 3324 loss_kpt: 0.218082 acc_pose: 0.461893 loss: 0.218082 2022/09/19 18:40:31 - mmengine - INFO - Epoch(train) [5][150/293] lr: 5.000000e-04 eta: 1 day, 23:37:00 time: 0.760100 data_time: 0.103360 memory: 3324 loss_kpt: 0.214987 acc_pose: 0.529095 loss: 0.214987 2022/09/19 18:41:16 - mmengine - INFO - Epoch(train) [5][200/293] lr: 5.000000e-04 eta: 1 day, 22:23:32 time: 0.901425 data_time: 0.324627 memory: 3324 loss_kpt: 0.216664 acc_pose: 0.519740 loss: 0.216664 2022/09/19 18:41:56 - mmengine - INFO - Epoch(train) [5][250/293] lr: 5.000000e-04 eta: 1 day, 21:11:44 time: 0.803573 data_time: 0.196632 memory: 3324 loss_kpt: 0.214622 acc_pose: 0.547301 loss: 0.214622 2022/09/19 18:42:24 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 18:42:24 - mmengine - INFO - Saving checkpoint at 5 epochs 2022/09/19 18:43:24 - mmengine - INFO - Epoch(train) [6][50/293] lr: 5.000000e-04 eta: 1 day, 18:59:06 time: 1.144448 data_time: 0.397516 memory: 3324 loss_kpt: 0.212810 acc_pose: 0.559012 loss: 0.212810 2022/09/19 18:44:21 - mmengine - INFO - Epoch(train) [6][100/293] lr: 5.000000e-04 eta: 1 day, 18:10:59 time: 1.138553 data_time: 0.207268 memory: 3324 loss_kpt: 0.210274 acc_pose: 0.550981 loss: 0.210274 2022/09/19 18:45:25 - mmengine - INFO - Epoch(train) [6][150/293] lr: 5.000000e-04 eta: 1 day, 17:30:29 time: 1.290906 data_time: 0.278723 memory: 3324 loss_kpt: 0.212733 acc_pose: 0.541264 loss: 0.212733 2022/09/19 18:46:29 - mmengine - INFO - Epoch(train) [6][200/293] lr: 5.000000e-04 eta: 1 day, 16:52:06 time: 1.282388 data_time: 0.276085 memory: 3324 loss_kpt: 0.209122 acc_pose: 0.509214 loss: 0.209122 2022/09/19 18:47:31 - mmengine - INFO - Epoch(train) [6][250/293] lr: 5.000000e-04 eta: 1 day, 16:14:30 time: 1.234347 data_time: 0.262130 memory: 3324 loss_kpt: 0.207415 acc_pose: 0.577135 loss: 0.207415 2022/09/19 18:48:25 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 18:48:25 - mmengine - INFO - Saving checkpoint at 6 epochs 2022/09/19 18:49:39 - mmengine - INFO - Epoch(train) [7][50/293] lr: 5.000000e-04 eta: 1 day, 14:43:57 time: 1.351489 data_time: 0.551045 memory: 3324 loss_kpt: 0.209143 acc_pose: 0.559529 loss: 0.209143 2022/09/19 18:50:34 - mmengine - INFO - Epoch(train) [7][100/293] lr: 5.000000e-04 eta: 1 day, 14:09:26 time: 1.117681 data_time: 0.249861 memory: 3324 loss_kpt: 0.205813 acc_pose: 0.558915 loss: 0.205813 2022/09/19 18:51:31 - mmengine - INFO - Epoch(train) [7][150/293] lr: 5.000000e-04 eta: 1 day, 13:37:04 time: 1.132938 data_time: 0.451629 memory: 3324 loss_kpt: 0.206071 acc_pose: 0.555099 loss: 0.206071 2022/09/19 18:52:15 - mmengine - INFO - Epoch(train) [7][200/293] lr: 5.000000e-04 eta: 1 day, 12:59:58 time: 0.883064 data_time: 0.350995 memory: 3324 loss_kpt: 0.206094 acc_pose: 0.581802 loss: 0.206094 2022/09/19 18:52:59 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 18:53:07 - mmengine - INFO - Epoch(train) [7][250/293] lr: 5.000000e-04 eta: 1 day, 12:28:43 time: 1.045890 data_time: 0.351581 memory: 3324 loss_kpt: 0.207327 acc_pose: 0.557591 loss: 0.207327 2022/09/19 18:53:55 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 18:53:55 - mmengine - INFO - Saving checkpoint at 7 epochs 2022/09/19 18:54:57 - mmengine - INFO - Epoch(train) [8][50/293] lr: 5.000000e-04 eta: 1 day, 11:15:42 time: 1.151401 data_time: 0.370731 memory: 3324 loss_kpt: 0.203135 acc_pose: 0.627420 loss: 0.203135 2022/09/19 18:55:51 - mmengine - INFO - Epoch(train) [8][100/293] lr: 5.000000e-04 eta: 1 day, 10:49:44 time: 1.084586 data_time: 0.335637 memory: 3324 loss_kpt: 0.199205 acc_pose: 0.587711 loss: 0.199205 2022/09/19 18:56:46 - mmengine - INFO - Epoch(train) [8][150/293] lr: 5.000000e-04 eta: 1 day, 10:25:23 time: 1.105763 data_time: 0.228802 memory: 3324 loss_kpt: 0.202974 acc_pose: 0.568078 loss: 0.202974 2022/09/19 18:57:36 - mmengine - INFO - Epoch(train) [8][200/293] lr: 5.000000e-04 eta: 1 day, 9:59:29 time: 0.988370 data_time: 0.180259 memory: 3324 loss_kpt: 0.200595 acc_pose: 0.545065 loss: 0.200595 2022/09/19 18:58:24 - mmengine - INFO - Epoch(train) [8][250/293] lr: 5.000000e-04 eta: 1 day, 9:33:59 time: 0.954990 data_time: 0.202300 memory: 3324 loss_kpt: 0.200735 acc_pose: 0.570744 loss: 0.200735 2022/09/19 18:59:05 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 18:59:05 - mmengine - INFO - Saving checkpoint at 8 epochs 2022/09/19 18:59:47 - mmengine - INFO - Epoch(train) [9][50/293] lr: 5.000000e-04 eta: 1 day, 8:28:29 time: 0.767078 data_time: 0.258047 memory: 3324 loss_kpt: 0.195742 acc_pose: 0.539684 loss: 0.195742 2022/09/19 19:00:36 - mmengine - INFO - Epoch(train) [9][100/293] lr: 5.000000e-04 eta: 1 day, 8:06:47 time: 0.981498 data_time: 0.199193 memory: 3324 loss_kpt: 0.196743 acc_pose: 0.575631 loss: 0.196743 2022/09/19 19:01:35 - mmengine - INFO - Epoch(train) [9][150/293] lr: 5.000000e-04 eta: 1 day, 7:49:56 time: 1.184643 data_time: 0.196376 memory: 3324 loss_kpt: 0.197347 acc_pose: 0.605160 loss: 0.197347 2022/09/19 19:02:29 - mmengine - INFO - Epoch(train) [9][200/293] lr: 5.000000e-04 eta: 1 day, 7:31:36 time: 1.075868 data_time: 0.154973 memory: 3324 loss_kpt: 0.201315 acc_pose: 0.557656 loss: 0.201315 2022/09/19 19:03:15 - mmengine - INFO - Epoch(train) [9][250/293] lr: 5.000000e-04 eta: 1 day, 7:10:44 time: 0.906891 data_time: 0.171130 memory: 3324 loss_kpt: 0.199369 acc_pose: 0.562767 loss: 0.199369 2022/09/19 19:03:51 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 19:03:51 - mmengine - INFO - Saving checkpoint at 9 epochs 2022/09/19 19:04:42 - mmengine - INFO - Epoch(train) [10][50/293] lr: 5.000000e-04 eta: 1 day, 6:20:14 time: 0.936744 data_time: 0.247488 memory: 3324 loss_kpt: 0.195459 acc_pose: 0.556630 loss: 0.195459 2022/09/19 19:05:38 - mmengine - INFO - Epoch(train) [10][100/293] lr: 5.000000e-04 eta: 1 day, 6:05:28 time: 1.118176 data_time: 0.289259 memory: 3324 loss_kpt: 0.195122 acc_pose: 0.563079 loss: 0.195122 2022/09/19 19:06:34 - mmengine - INFO - Epoch(train) [10][150/293] lr: 5.000000e-04 eta: 1 day, 5:51:23 time: 1.127575 data_time: 0.172879 memory: 3324 loss_kpt: 0.194593 acc_pose: 0.619332 loss: 0.194593 2022/09/19 19:07:34 - mmengine - INFO - Epoch(train) [10][200/293] lr: 5.000000e-04 eta: 1 day, 5:39:02 time: 1.202016 data_time: 0.154958 memory: 3324 loss_kpt: 0.198403 acc_pose: 0.524404 loss: 0.198403 2022/09/19 19:08:29 - mmengine - INFO - Epoch(train) [10][250/293] lr: 5.000000e-04 eta: 1 day, 5:25:19 time: 1.097721 data_time: 0.159843 memory: 3324 loss_kpt: 0.197551 acc_pose: 0.571279 loss: 0.197551 2022/09/19 19:09:15 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 19:09:15 - mmengine - INFO - Saving checkpoint at 10 epochs 2022/09/19 19:10:20 - mmengine - INFO - Epoch(val) [10][50/407] eta: 0:07:12 time: 1.212455 data_time: 1.152745 memory: 3324 2022/09/19 19:11:21 - mmengine - INFO - Epoch(val) [10][100/407] eta: 0:06:16 time: 1.225074 data_time: 1.146051 memory: 400 2022/09/19 19:12:24 - mmengine - INFO - Epoch(val) [10][150/407] eta: 0:05:22 time: 1.256423 data_time: 1.161496 memory: 400 2022/09/19 19:13:26 - mmengine - INFO - Epoch(val) [10][200/407] eta: 0:04:16 time: 1.237779 data_time: 1.164935 memory: 400 2022/09/19 19:14:27 - mmengine - INFO - Epoch(val) [10][250/407] eta: 0:03:12 time: 1.228636 data_time: 1.154441 memory: 400 2022/09/19 19:15:30 - mmengine - INFO - Epoch(val) [10][300/407] eta: 0:02:14 time: 1.255457 data_time: 1.176210 memory: 400 2022/09/19 19:16:32 - mmengine - INFO - Epoch(val) [10][350/407] eta: 0:01:10 time: 1.235562 data_time: 1.150760 memory: 400 2022/09/19 19:17:32 - mmengine - INFO - Epoch(val) [10][400/407] eta: 0:00:08 time: 1.211872 data_time: 1.123491 memory: 400 2022/09/19 19:18:40 - mmengine - INFO - Evaluating CocoMetric... 2022/09/19 19:19:02 - mmengine - INFO - Epoch(val) [10][407/407] coco/AP: 0.458751 coco/AP .5: 0.779989 coco/AP .75: 0.477813 coco/AP (M): 0.434415 coco/AP (L): 0.505481 coco/AR: 0.523174 coco/AR .5: 0.835170 coco/AR .75: 0.554314 coco/AR (M): 0.485824 coco/AR (L): 0.575474 2022/09/19 19:19:05 - mmengine - INFO - The best checkpoint with 0.4588 coco/AP at 10 epoch is saved to best_coco/AP_epoch_10.pth. 2022/09/19 19:21:07 - mmengine - INFO - Epoch(train) [11][50/293] lr: 5.000000e-04 eta: 1 day, 5:07:21 time: 2.433569 data_time: 1.299551 memory: 3324 loss_kpt: 0.195244 acc_pose: 0.620235 loss: 0.195244 2022/09/19 19:21:41 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 19:22:26 - mmengine - INFO - Epoch(train) [11][100/293] lr: 5.000000e-04 eta: 1 day, 5:02:26 time: 1.577815 data_time: 0.512648 memory: 3324 loss_kpt: 0.195013 acc_pose: 0.602279 loss: 0.195013 2022/09/19 19:23:44 - mmengine - INFO - Epoch(train) [11][150/293] lr: 5.000000e-04 eta: 1 day, 4:57:33 time: 1.572170 data_time: 0.116656 memory: 3324 loss_kpt: 0.191339 acc_pose: 0.683560 loss: 0.191339 2022/09/19 19:24:44 - mmengine - INFO - Epoch(train) [11][200/293] lr: 5.000000e-04 eta: 1 day, 4:46:55 time: 1.195628 data_time: 0.126607 memory: 3324 loss_kpt: 0.189645 acc_pose: 0.562281 loss: 0.189645 2022/09/19 19:25:50 - mmengine - INFO - Epoch(train) [11][250/293] lr: 5.000000e-04 eta: 1 day, 4:38:31 time: 1.321920 data_time: 0.112031 memory: 3324 loss_kpt: 0.195575 acc_pose: 0.598784 loss: 0.195575 2022/09/19 19:26:51 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 19:26:51 - mmengine - INFO - Saving checkpoint at 11 epochs 2022/09/19 19:28:11 - mmengine - INFO - Epoch(train) [12][50/293] lr: 5.000000e-04 eta: 1 day, 4:09:48 time: 1.535027 data_time: 0.293723 memory: 3324 loss_kpt: 0.196864 acc_pose: 0.599323 loss: 0.196864 2022/09/19 19:29:35 - mmengine - INFO - Epoch(train) [12][100/293] lr: 5.000000e-04 eta: 1 day, 4:07:29 time: 1.680986 data_time: 0.495254 memory: 3324 loss_kpt: 0.190636 acc_pose: 0.557331 loss: 0.190636 2022/09/19 19:30:50 - mmengine - INFO - Epoch(train) [12][150/293] lr: 5.000000e-04 eta: 1 day, 4:02:48 time: 1.514711 data_time: 0.166574 memory: 3324 loss_kpt: 0.189033 acc_pose: 0.620946 loss: 0.189033 2022/09/19 19:31:50 - mmengine - INFO - Epoch(train) [12][200/293] lr: 5.000000e-04 eta: 1 day, 3:53:39 time: 1.191136 data_time: 0.104375 memory: 3324 loss_kpt: 0.190904 acc_pose: 0.611689 loss: 0.190904 2022/09/19 19:32:57 - mmengine - INFO - Epoch(train) [12][250/293] lr: 5.000000e-04 eta: 1 day, 3:46:41 time: 1.331325 data_time: 0.115006 memory: 3324 loss_kpt: 0.194004 acc_pose: 0.664428 loss: 0.194004 2022/09/19 19:33:47 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 19:33:47 - mmengine - INFO - Saving checkpoint at 12 epochs 2022/09/19 19:34:46 - mmengine - INFO - Epoch(train) [13][50/293] lr: 5.000000e-04 eta: 1 day, 3:15:58 time: 1.133678 data_time: 0.496834 memory: 3324 loss_kpt: 0.192881 acc_pose: 0.612343 loss: 0.192881 2022/09/19 19:36:19 - mmengine - INFO - Epoch(train) [13][100/293] lr: 5.000000e-04 eta: 1 day, 3:16:37 time: 1.847109 data_time: 0.112183 memory: 3324 loss_kpt: 0.192290 acc_pose: 0.645160 loss: 0.192290 2022/09/19 19:37:47 - mmengine - INFO - Epoch(train) [13][150/293] lr: 5.000000e-04 eta: 1 day, 3:16:08 time: 1.767350 data_time: 0.123264 memory: 3324 loss_kpt: 0.193769 acc_pose: 0.556160 loss: 0.193769 2022/09/19 19:39:16 - mmengine - INFO - Epoch(train) [13][200/293] lr: 5.000000e-04 eta: 1 day, 3:15:42 time: 1.772214 data_time: 0.290537 memory: 3324 loss_kpt: 0.187628 acc_pose: 0.589715 loss: 0.187628 2022/09/19 19:40:40 - mmengine - INFO - Epoch(train) [13][250/293] lr: 5.000000e-04 eta: 1 day, 3:14:06 time: 1.682141 data_time: 0.272288 memory: 3324 loss_kpt: 0.187060 acc_pose: 0.609449 loss: 0.187060 2022/09/19 19:41:38 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 19:41:39 - mmengine - INFO - Saving checkpoint at 13 epochs 2022/09/19 19:42:51 - mmengine - INFO - Epoch(train) [14][50/293] lr: 5.000000e-04 eta: 1 day, 2:49:37 time: 1.402435 data_time: 0.472942 memory: 3324 loss_kpt: 0.187735 acc_pose: 0.663073 loss: 0.187735 2022/09/19 19:43:57 - mmengine - INFO - Epoch(train) [14][100/293] lr: 5.000000e-04 eta: 1 day, 2:43:40 time: 1.304820 data_time: 0.175744 memory: 3324 loss_kpt: 0.186441 acc_pose: 0.576608 loss: 0.186441 2022/09/19 19:45:13 - mmengine - INFO - Epoch(train) [14][150/293] lr: 5.000000e-04 eta: 1 day, 2:40:41 time: 1.537638 data_time: 0.454046 memory: 3324 loss_kpt: 0.191630 acc_pose: 0.581778 loss: 0.191630 2022/09/19 19:46:10 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 19:46:21 - mmengine - INFO - Epoch(train) [14][200/293] lr: 5.000000e-04 eta: 1 day, 2:35:28 time: 1.348756 data_time: 0.103319 memory: 3324 loss_kpt: 0.189433 acc_pose: 0.643166 loss: 0.189433 2022/09/19 19:47:25 - mmengine - INFO - Epoch(train) [14][250/293] lr: 5.000000e-04 eta: 1 day, 2:29:28 time: 1.273352 data_time: 0.110733 memory: 3324 loss_kpt: 0.188825 acc_pose: 0.617671 loss: 0.188825 2022/09/19 19:48:17 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 19:48:17 - mmengine - INFO - Saving checkpoint at 14 epochs 2022/09/19 19:49:21 - mmengine - INFO - Epoch(train) [15][50/293] lr: 5.000000e-04 eta: 1 day, 2:05:16 time: 1.208802 data_time: 0.210327 memory: 3324 loss_kpt: 0.185832 acc_pose: 0.636031 loss: 0.185832 2022/09/19 19:50:40 - mmengine - INFO - Epoch(train) [15][100/293] lr: 5.000000e-04 eta: 1 day, 2:03:28 time: 1.597667 data_time: 0.116585 memory: 3324 loss_kpt: 0.187551 acc_pose: 0.636308 loss: 0.187551 2022/09/19 19:52:09 - mmengine - INFO - Epoch(train) [15][150/293] lr: 5.000000e-04 eta: 1 day, 2:03:34 time: 1.766296 data_time: 0.116104 memory: 3324 loss_kpt: 0.186909 acc_pose: 0.658983 loss: 0.186909 2022/09/19 19:52:34 - mmengine - INFO - Epoch(train) [15][200/293] lr: 5.000000e-04 eta: 1 day, 1:49:39 time: 0.505812 data_time: 0.113427 memory: 3324 loss_kpt: 0.187203 acc_pose: 0.628259 loss: 0.187203 2022/09/19 19:52:58 - mmengine - INFO - Epoch(train) [15][250/293] lr: 5.000000e-04 eta: 1 day, 1:35:45 time: 0.479427 data_time: 0.112836 memory: 3324 loss_kpt: 0.186128 acc_pose: 0.660427 loss: 0.186128 2022/09/19 19:53:16 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 19:53:16 - mmengine - INFO - Saving checkpoint at 15 epochs 2022/09/19 19:54:14 - mmengine - INFO - Epoch(train) [16][50/293] lr: 5.000000e-04 eta: 1 day, 1:13:05 time: 1.113053 data_time: 0.139188 memory: 3324 loss_kpt: 0.186595 acc_pose: 0.607439 loss: 0.186595 2022/09/19 19:55:53 - mmengine - INFO - Epoch(train) [16][100/293] lr: 5.000000e-04 eta: 1 day, 1:15:52 time: 1.978707 data_time: 0.128686 memory: 3324 loss_kpt: 0.184586 acc_pose: 0.645971 loss: 0.184586 2022/09/19 19:57:05 - mmengine - INFO - Epoch(train) [16][150/293] lr: 5.000000e-04 eta: 1 day, 1:12:51 time: 1.433708 data_time: 0.118503 memory: 3324 loss_kpt: 0.185176 acc_pose: 0.699014 loss: 0.185176 2022/09/19 19:58:20 - mmengine - INFO - Epoch(train) [16][200/293] lr: 5.000000e-04 eta: 1 day, 1:10:35 time: 1.501675 data_time: 0.127945 memory: 3324 loss_kpt: 0.187313 acc_pose: 0.631009 loss: 0.187313 2022/09/19 19:59:14 - mmengine - INFO - Epoch(train) [16][250/293] lr: 5.000000e-04 eta: 1 day, 1:04:04 time: 1.082449 data_time: 0.098485 memory: 3324 loss_kpt: 0.182328 acc_pose: 0.650190 loss: 0.182328 2022/09/19 19:59:58 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 19:59:58 - mmengine - INFO - Saving checkpoint at 16 epochs 2022/09/19 20:00:47 - mmengine - INFO - Epoch(train) [17][50/293] lr: 5.000000e-04 eta: 1 day, 0:41:30 time: 0.938389 data_time: 0.174132 memory: 3324 loss_kpt: 0.184139 acc_pose: 0.586622 loss: 0.184139 2022/09/19 20:01:24 - mmengine - INFO - Epoch(train) [17][100/293] lr: 5.000000e-04 eta: 1 day, 0:31:53 time: 0.722853 data_time: 0.110972 memory: 3324 loss_kpt: 0.186967 acc_pose: 0.624548 loss: 0.186967 2022/09/19 20:02:09 - mmengine - INFO - Epoch(train) [17][150/293] lr: 5.000000e-04 eta: 1 day, 0:24:20 time: 0.916986 data_time: 0.163322 memory: 3324 loss_kpt: 0.183315 acc_pose: 0.639205 loss: 0.183315 2022/09/19 20:02:46 - mmengine - INFO - Epoch(train) [17][200/293] lr: 5.000000e-04 eta: 1 day, 0:15:09 time: 0.732322 data_time: 0.099805 memory: 3324 loss_kpt: 0.185200 acc_pose: 0.624681 loss: 0.185200 2022/09/19 20:03:25 - mmengine - INFO - Epoch(train) [17][250/293] lr: 5.000000e-04 eta: 1 day, 0:06:36 time: 0.780445 data_time: 0.102449 memory: 3324 loss_kpt: 0.180050 acc_pose: 0.589442 loss: 0.180050 2022/09/19 20:04:10 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 20:04:10 - mmengine - INFO - Saving checkpoint at 17 epochs 2022/09/19 20:04:35 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 20:05:26 - mmengine - INFO - Epoch(train) [18][50/293] lr: 5.000000e-04 eta: 23:51:14 time: 1.464097 data_time: 0.574824 memory: 3324 loss_kpt: 0.182930 acc_pose: 0.645081 loss: 0.182930 2022/09/19 20:06:14 - mmengine - INFO - Epoch(train) [18][100/293] lr: 5.000000e-04 eta: 23:44:53 time: 0.971905 data_time: 0.564112 memory: 3324 loss_kpt: 0.182619 acc_pose: 0.585779 loss: 0.182619 2022/09/19 20:07:21 - mmengine - INFO - Epoch(train) [18][150/293] lr: 5.000000e-04 eta: 23:41:58 time: 1.332654 data_time: 0.366658 memory: 3324 loss_kpt: 0.185085 acc_pose: 0.602530 loss: 0.185085 2022/09/19 20:10:18 - mmengine - INFO - Epoch(train) [18][200/293] lr: 5.000000e-04 eta: 23:59:02 time: 3.535557 data_time: 0.106135 memory: 3324 loss_kpt: 0.182502 acc_pose: 0.666037 loss: 0.182502 2022/09/19 20:11:09 - mmengine - INFO - Epoch(train) [18][250/293] lr: 5.000000e-04 eta: 23:53:08 time: 1.016955 data_time: 0.111355 memory: 3324 loss_kpt: 0.185206 acc_pose: 0.590233 loss: 0.185206 2022/09/19 20:12:13 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 20:12:13 - mmengine - INFO - Saving checkpoint at 18 epochs 2022/09/19 20:13:41 - mmengine - INFO - Epoch(train) [19][50/293] lr: 5.000000e-04 eta: 23:40:43 time: 1.697826 data_time: 0.169684 memory: 3324 loss_kpt: 0.182657 acc_pose: 0.672234 loss: 0.182657 2022/09/19 20:14:59 - mmengine - INFO - Epoch(train) [19][100/293] lr: 5.000000e-04 eta: 23:39:51 time: 1.563392 data_time: 0.163039 memory: 3324 loss_kpt: 0.182967 acc_pose: 0.601609 loss: 0.182967 2022/09/19 20:15:51 - mmengine - INFO - Epoch(train) [19][150/293] lr: 5.000000e-04 eta: 23:34:25 time: 1.032404 data_time: 0.125115 memory: 3324 loss_kpt: 0.181349 acc_pose: 0.641238 loss: 0.181349 2022/09/19 20:16:58 - mmengine - INFO - Epoch(train) [19][200/293] lr: 5.000000e-04 eta: 23:31:48 time: 1.354777 data_time: 0.432004 memory: 3324 loss_kpt: 0.183436 acc_pose: 0.628866 loss: 0.183436 2022/09/19 20:18:02 - mmengine - INFO - Epoch(train) [19][250/293] lr: 5.000000e-04 eta: 23:28:36 time: 1.280961 data_time: 0.131423 memory: 3324 loss_kpt: 0.183774 acc_pose: 0.624525 loss: 0.183774 2022/09/19 20:18:49 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 20:18:49 - mmengine - INFO - Saving checkpoint at 19 epochs 2022/09/19 20:20:17 - mmengine - INFO - Epoch(train) [20][50/293] lr: 5.000000e-04 eta: 23:17:09 time: 1.708810 data_time: 0.303757 memory: 3324 loss_kpt: 0.180290 acc_pose: 0.606045 loss: 0.180290 2022/09/19 20:21:10 - mmengine - INFO - Epoch(train) [20][100/293] lr: 5.000000e-04 eta: 23:12:18 time: 1.060918 data_time: 0.180859 memory: 3324 loss_kpt: 0.183654 acc_pose: 0.737979 loss: 0.183654 2022/09/19 20:22:15 - mmengine - INFO - Epoch(train) [20][150/293] lr: 5.000000e-04 eta: 23:09:32 time: 1.307442 data_time: 0.125354 memory: 3324 loss_kpt: 0.176707 acc_pose: 0.664032 loss: 0.176707 2022/09/19 20:23:29 - mmengine - INFO - Epoch(train) [20][200/293] lr: 5.000000e-04 eta: 23:08:08 time: 1.476245 data_time: 0.471686 memory: 3324 loss_kpt: 0.178099 acc_pose: 0.684492 loss: 0.178099 2022/09/19 20:24:27 - mmengine - INFO - Epoch(train) [20][250/293] lr: 5.000000e-04 eta: 23:04:12 time: 1.155438 data_time: 0.432045 memory: 3324 loss_kpt: 0.182735 acc_pose: 0.603278 loss: 0.182735 2022/09/19 20:25:12 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 20:25:12 - mmengine - INFO - Saving checkpoint at 20 epochs 2022/09/19 20:26:13 - mmengine - INFO - Epoch(val) [20][50/407] eta: 0:06:50 time: 1.150238 data_time: 1.098784 memory: 3324 2022/09/19 20:27:13 - mmengine - INFO - Epoch(val) [20][100/407] eta: 0:06:07 time: 1.197359 data_time: 1.126986 memory: 400 2022/09/19 20:28:11 - mmengine - INFO - Epoch(val) [20][150/407] eta: 0:04:57 time: 1.159105 data_time: 1.110640 memory: 400 2022/09/19 20:29:10 - mmengine - INFO - Epoch(val) [20][200/407] eta: 0:04:04 time: 1.181366 data_time: 1.129497 memory: 400 2022/09/19 20:30:09 - mmengine - INFO - Epoch(val) [20][250/407] eta: 0:03:05 time: 1.178962 data_time: 1.103642 memory: 400 2022/09/19 20:31:09 - mmengine - INFO - Epoch(val) [20][300/407] eta: 0:02:08 time: 1.202957 data_time: 1.132935 memory: 400 2022/09/19 20:32:08 - mmengine - INFO - Epoch(val) [20][350/407] eta: 0:01:06 time: 1.173356 data_time: 1.108936 memory: 400 2022/09/19 20:33:08 - mmengine - INFO - Epoch(val) [20][400/407] eta: 0:00:08 time: 1.194873 data_time: 1.145513 memory: 400 2022/09/19 20:34:04 - mmengine - INFO - Evaluating CocoMetric... 2022/09/19 20:34:23 - mmengine - INFO - Epoch(val) [20][407/407] coco/AP: 0.507392 coco/AP .5: 0.803575 coco/AP .75: 0.546649 coco/AP (M): 0.478965 coco/AP (L): 0.559010 coco/AR: 0.570387 coco/AR .5: 0.855793 coco/AR .75: 0.617443 coco/AR (M): 0.530675 coco/AR (L): 0.626050 2022/09/19 20:34:23 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_10.pth is removed 2022/09/19 20:34:25 - mmengine - INFO - The best checkpoint with 0.5074 coco/AP at 20 epoch is saved to best_coco/AP_epoch_20.pth. 2022/09/19 20:36:29 - mmengine - INFO - Epoch(train) [21][50/293] lr: 5.000000e-04 eta: 22:59:32 time: 2.472228 data_time: 0.483386 memory: 3324 loss_kpt: 0.182929 acc_pose: 0.616214 loss: 0.182929 2022/09/19 20:37:29 - mmengine - INFO - Epoch(train) [21][100/293] lr: 5.000000e-04 eta: 22:56:02 time: 1.198659 data_time: 0.139761 memory: 3324 loss_kpt: 0.179075 acc_pose: 0.638992 loss: 0.179075 2022/09/19 20:38:19 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 20:38:31 - mmengine - INFO - Epoch(train) [21][150/293] lr: 5.000000e-04 eta: 22:52:56 time: 1.243183 data_time: 0.528514 memory: 3324 loss_kpt: 0.180500 acc_pose: 0.628086 loss: 0.180500 2022/09/19 20:39:52 - mmengine - INFO - Epoch(train) [21][200/293] lr: 5.000000e-04 eta: 22:52:44 time: 1.620358 data_time: 0.171133 memory: 3324 loss_kpt: 0.180749 acc_pose: 0.633868 loss: 0.180749 2022/09/19 20:40:52 - mmengine - INFO - Epoch(train) [21][250/293] lr: 5.000000e-04 eta: 22:49:17 time: 1.192271 data_time: 0.262490 memory: 3324 loss_kpt: 0.175738 acc_pose: 0.633762 loss: 0.175738 2022/09/19 20:41:51 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 20:41:51 - mmengine - INFO - Saving checkpoint at 21 epochs 2022/09/19 20:42:41 - mmengine - INFO - Epoch(train) [22][50/293] lr: 5.000000e-04 eta: 22:33:30 time: 0.941161 data_time: 0.148764 memory: 3324 loss_kpt: 0.182532 acc_pose: 0.635584 loss: 0.182532 2022/09/19 20:43:44 - mmengine - INFO - Epoch(train) [22][100/293] lr: 5.000000e-04 eta: 22:30:43 time: 1.257168 data_time: 0.147570 memory: 3324 loss_kpt: 0.179759 acc_pose: 0.630492 loss: 0.179759 2022/09/19 20:44:39 - mmengine - INFO - Epoch(train) [22][150/293] lr: 5.000000e-04 eta: 22:26:52 time: 1.104942 data_time: 0.108145 memory: 3324 loss_kpt: 0.175801 acc_pose: 0.614042 loss: 0.175801 2022/09/19 20:45:24 - mmengine - INFO - Epoch(train) [22][200/293] lr: 5.000000e-04 eta: 22:21:34 time: 0.899530 data_time: 0.095730 memory: 3324 loss_kpt: 0.182250 acc_pose: 0.654427 loss: 0.182250 2022/09/19 20:46:10 - mmengine - INFO - Epoch(train) [22][250/293] lr: 5.000000e-04 eta: 22:16:33 time: 0.930752 data_time: 0.334866 memory: 3324 loss_kpt: 0.180904 acc_pose: 0.616274 loss: 0.180904 2022/09/19 20:46:46 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 20:46:46 - mmengine - INFO - Saving checkpoint at 22 epochs 2022/09/19 20:47:50 - mmengine - INFO - Epoch(train) [23][50/293] lr: 5.000000e-04 eta: 22:03:50 time: 1.222011 data_time: 0.140805 memory: 3324 loss_kpt: 0.179342 acc_pose: 0.687672 loss: 0.179342 2022/09/19 20:48:58 - mmengine - INFO - Epoch(train) [23][100/293] lr: 5.000000e-04 eta: 22:02:09 time: 1.375398 data_time: 0.110344 memory: 3324 loss_kpt: 0.176884 acc_pose: 0.616169 loss: 0.176884 2022/09/19 20:50:00 - mmengine - INFO - Epoch(train) [23][150/293] lr: 5.000000e-04 eta: 21:59:33 time: 1.242906 data_time: 0.150284 memory: 3324 loss_kpt: 0.178097 acc_pose: 0.617165 loss: 0.178097 2022/09/19 20:50:48 - mmengine - INFO - Epoch(train) [23][200/293] lr: 5.000000e-04 eta: 21:55:02 time: 0.957659 data_time: 0.247587 memory: 3324 loss_kpt: 0.177270 acc_pose: 0.671670 loss: 0.177270 2022/09/19 20:51:48 - mmengine - INFO - Epoch(train) [23][250/293] lr: 5.000000e-04 eta: 21:52:13 time: 1.202239 data_time: 0.468000 memory: 3324 loss_kpt: 0.178175 acc_pose: 0.707820 loss: 0.178175 2022/09/19 20:52:39 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 20:52:39 - mmengine - INFO - Saving checkpoint at 23 epochs 2022/09/19 20:53:28 - mmengine - INFO - Epoch(train) [24][50/293] lr: 5.000000e-04 eta: 21:38:17 time: 0.926162 data_time: 0.125852 memory: 3324 loss_kpt: 0.176412 acc_pose: 0.621209 loss: 0.176412 2022/09/19 20:54:17 - mmengine - INFO - Epoch(train) [24][100/293] lr: 5.000000e-04 eta: 21:34:03 time: 0.967129 data_time: 0.117550 memory: 3324 loss_kpt: 0.178369 acc_pose: 0.671339 loss: 0.178369 2022/09/19 20:54:53 - mmengine - INFO - Epoch(train) [24][150/293] lr: 5.000000e-04 eta: 21:28:20 time: 0.734159 data_time: 0.192231 memory: 3324 loss_kpt: 0.177131 acc_pose: 0.669608 loss: 0.177131 2022/09/19 20:55:50 - mmengine - INFO - Epoch(train) [24][200/293] lr: 5.000000e-04 eta: 21:25:17 time: 1.129383 data_time: 0.091454 memory: 3324 loss_kpt: 0.177278 acc_pose: 0.671729 loss: 0.177278 2022/09/19 20:56:37 - mmengine - INFO - Epoch(train) [24][250/293] lr: 5.000000e-04 eta: 21:21:04 time: 0.944278 data_time: 0.173251 memory: 3324 loss_kpt: 0.174830 acc_pose: 0.701408 loss: 0.174830 2022/09/19 20:56:49 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 20:57:11 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 20:57:11 - mmengine - INFO - Saving checkpoint at 24 epochs 2022/09/19 20:58:04 - mmengine - INFO - Epoch(train) [25][50/293] lr: 5.000000e-04 eta: 21:08:35 time: 1.012697 data_time: 0.237676 memory: 3324 loss_kpt: 0.176327 acc_pose: 0.634453 loss: 0.176327 2022/09/19 20:58:41 - mmengine - INFO - Epoch(train) [25][100/293] lr: 5.000000e-04 eta: 21:03:17 time: 0.749802 data_time: 0.134490 memory: 3324 loss_kpt: 0.173284 acc_pose: 0.590827 loss: 0.173284 2022/09/19 20:59:42 - mmengine - INFO - Epoch(train) [25][150/293] lr: 5.000000e-04 eta: 21:00:59 time: 1.212542 data_time: 0.089504 memory: 3324 loss_kpt: 0.177818 acc_pose: 0.547190 loss: 0.177818 2022/09/19 21:00:21 - mmengine - INFO - Epoch(train) [25][200/293] lr: 5.000000e-04 eta: 20:56:03 time: 0.787115 data_time: 0.145602 memory: 3324 loss_kpt: 0.174338 acc_pose: 0.632696 loss: 0.174338 2022/09/19 21:01:30 - mmengine - INFO - Epoch(train) [25][250/293] lr: 5.000000e-04 eta: 20:54:49 time: 1.376792 data_time: 0.095361 memory: 3324 loss_kpt: 0.176989 acc_pose: 0.644688 loss: 0.176989 2022/09/19 21:02:19 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 21:02:19 - mmengine - INFO - Saving checkpoint at 25 epochs 2022/09/19 21:03:35 - mmengine - INFO - Epoch(train) [26][50/293] lr: 5.000000e-04 eta: 20:45:46 time: 1.454031 data_time: 0.257720 memory: 3324 loss_kpt: 0.179058 acc_pose: 0.593407 loss: 0.179058 2022/09/19 21:04:49 - mmengine - INFO - Epoch(train) [26][100/293] lr: 5.000000e-04 eta: 20:45:16 time: 1.487404 data_time: 0.099384 memory: 3324 loss_kpt: 0.178237 acc_pose: 0.654223 loss: 0.178237 2022/09/19 21:05:59 - mmengine - INFO - Epoch(train) [26][150/293] lr: 5.000000e-04 eta: 20:44:16 time: 1.405210 data_time: 0.098499 memory: 3324 loss_kpt: 0.172713 acc_pose: 0.655743 loss: 0.172713 2022/09/19 21:06:58 - mmengine - INFO - Epoch(train) [26][200/293] lr: 5.000000e-04 eta: 20:41:51 time: 1.170653 data_time: 0.100492 memory: 3324 loss_kpt: 0.177556 acc_pose: 0.656654 loss: 0.177556 2022/09/19 21:07:42 - mmengine - INFO - Epoch(train) [26][250/293] lr: 5.000000e-04 eta: 20:37:46 time: 0.883833 data_time: 0.171355 memory: 3324 loss_kpt: 0.175145 acc_pose: 0.647069 loss: 0.175145 2022/09/19 21:08:21 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 21:08:21 - mmengine - INFO - Saving checkpoint at 26 epochs 2022/09/19 21:09:00 - mmengine - INFO - Epoch(train) [27][50/293] lr: 5.000000e-04 eta: 20:24:53 time: 0.723875 data_time: 0.115709 memory: 3324 loss_kpt: 0.175806 acc_pose: 0.670359 loss: 0.175806 2022/09/19 21:09:45 - mmengine - INFO - Epoch(train) [27][100/293] lr: 5.000000e-04 eta: 20:21:08 time: 0.914622 data_time: 0.229371 memory: 3324 loss_kpt: 0.175207 acc_pose: 0.664063 loss: 0.175207 2022/09/19 21:10:42 - mmengine - INFO - Epoch(train) [27][150/293] lr: 5.000000e-04 eta: 20:18:40 time: 1.130781 data_time: 0.106306 memory: 3324 loss_kpt: 0.172534 acc_pose: 0.660359 loss: 0.172534 2022/09/19 21:11:43 - mmengine - INFO - Epoch(train) [27][200/293] lr: 5.000000e-04 eta: 20:16:43 time: 1.216807 data_time: 0.107187 memory: 3324 loss_kpt: 0.175472 acc_pose: 0.673891 loss: 0.175472 2022/09/19 21:12:42 - mmengine - INFO - Epoch(train) [27][250/293] lr: 5.000000e-04 eta: 20:14:35 time: 1.184246 data_time: 0.150610 memory: 3324 loss_kpt: 0.172622 acc_pose: 0.670222 loss: 0.172622 2022/09/19 21:13:40 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 21:13:40 - mmengine - INFO - Saving checkpoint at 27 epochs 2022/09/19 21:14:35 - mmengine - INFO - Epoch(train) [28][50/293] lr: 5.000000e-04 eta: 20:04:16 time: 1.062881 data_time: 0.180107 memory: 3324 loss_kpt: 0.178881 acc_pose: 0.680848 loss: 0.178881 2022/09/19 21:15:22 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 21:15:39 - mmengine - INFO - Epoch(train) [28][100/293] lr: 5.000000e-04 eta: 20:02:40 time: 1.262128 data_time: 0.220664 memory: 3324 loss_kpt: 0.173856 acc_pose: 0.650154 loss: 0.173856 2022/09/19 21:16:36 - mmengine - INFO - Epoch(train) [28][150/293] lr: 5.000000e-04 eta: 20:00:29 time: 1.156348 data_time: 0.150672 memory: 3324 loss_kpt: 0.176041 acc_pose: 0.594761 loss: 0.176041 2022/09/19 21:17:41 - mmengine - INFO - Epoch(train) [28][200/293] lr: 5.000000e-04 eta: 19:59:02 time: 1.288680 data_time: 0.108479 memory: 3324 loss_kpt: 0.173731 acc_pose: 0.670584 loss: 0.173731 2022/09/19 21:18:35 - mmengine - INFO - Epoch(train) [28][250/293] lr: 5.000000e-04 eta: 19:56:31 time: 1.088558 data_time: 0.149503 memory: 3324 loss_kpt: 0.176915 acc_pose: 0.673642 loss: 0.176915 2022/09/19 21:19:17 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 21:19:17 - mmengine - INFO - Saving checkpoint at 28 epochs 2022/09/19 21:20:30 - mmengine - INFO - Epoch(train) [29][50/293] lr: 5.000000e-04 eta: 19:48:33 time: 1.409672 data_time: 0.473712 memory: 3324 loss_kpt: 0.174025 acc_pose: 0.642664 loss: 0.174025 2022/09/19 21:21:21 - mmengine - INFO - Epoch(train) [29][100/293] lr: 5.000000e-04 eta: 19:45:45 time: 1.024048 data_time: 0.096843 memory: 3324 loss_kpt: 0.173888 acc_pose: 0.687592 loss: 0.173888 2022/09/19 21:22:12 - mmengine - INFO - Epoch(train) [29][150/293] lr: 5.000000e-04 eta: 19:42:56 time: 1.014232 data_time: 0.188285 memory: 3324 loss_kpt: 0.171155 acc_pose: 0.662708 loss: 0.171155 2022/09/19 21:23:02 - mmengine - INFO - Epoch(train) [29][200/293] lr: 5.000000e-04 eta: 19:40:00 time: 0.991604 data_time: 0.316032 memory: 3324 loss_kpt: 0.170955 acc_pose: 0.617564 loss: 0.170955 2022/09/19 21:23:52 - mmengine - INFO - Epoch(train) [29][250/293] lr: 5.000000e-04 eta: 19:37:08 time: 0.994841 data_time: 0.164264 memory: 3324 loss_kpt: 0.174980 acc_pose: 0.594728 loss: 0.174980 2022/09/19 21:24:26 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 21:24:26 - mmengine - INFO - Saving checkpoint at 29 epochs 2022/09/19 21:25:25 - mmengine - INFO - Epoch(train) [30][50/293] lr: 5.000000e-04 eta: 19:28:07 time: 1.128474 data_time: 0.148063 memory: 3324 loss_kpt: 0.175697 acc_pose: 0.672969 loss: 0.175697 2022/09/19 21:26:12 - mmengine - INFO - Epoch(train) [30][100/293] lr: 5.000000e-04 eta: 19:25:05 time: 0.948682 data_time: 0.111298 memory: 3324 loss_kpt: 0.172659 acc_pose: 0.710180 loss: 0.172659 2022/09/19 21:27:12 - mmengine - INFO - Epoch(train) [30][150/293] lr: 5.000000e-04 eta: 19:23:21 time: 1.194049 data_time: 0.112801 memory: 3324 loss_kpt: 0.171481 acc_pose: 0.709937 loss: 0.171481 2022/09/19 21:28:06 - mmengine - INFO - Epoch(train) [30][200/293] lr: 5.000000e-04 eta: 19:21:01 time: 1.077727 data_time: 0.135451 memory: 3324 loss_kpt: 0.169875 acc_pose: 0.686721 loss: 0.169875 2022/09/19 21:29:10 - mmengine - INFO - Epoch(train) [30][250/293] lr: 5.000000e-04 eta: 19:19:42 time: 1.275066 data_time: 0.095885 memory: 3324 loss_kpt: 0.174964 acc_pose: 0.631539 loss: 0.174964 2022/09/19 21:30:03 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 21:30:03 - mmengine - INFO - Saving checkpoint at 30 epochs 2022/09/19 21:31:03 - mmengine - INFO - Epoch(val) [30][50/407] eta: 0:06:42 time: 1.127983 data_time: 1.075723 memory: 3324 2022/09/19 21:32:02 - mmengine - INFO - Epoch(val) [30][100/407] eta: 0:06:00 time: 1.175330 data_time: 1.102915 memory: 400 2022/09/19 21:33:01 - mmengine - INFO - Epoch(val) [30][150/407] eta: 0:05:03 time: 1.181273 data_time: 1.110065 memory: 400 2022/09/19 21:33:59 - mmengine - INFO - Epoch(val) [30][200/407] eta: 0:04:03 time: 1.174930 data_time: 1.103920 memory: 400 2022/09/19 21:34:58 - mmengine - INFO - Epoch(val) [30][250/407] eta: 0:03:03 time: 1.171301 data_time: 1.110316 memory: 400 2022/09/19 21:35:58 - mmengine - INFO - Epoch(val) [30][300/407] eta: 0:02:08 time: 1.198131 data_time: 1.135616 memory: 400 2022/09/19 21:36:56 - mmengine - INFO - Epoch(val) [30][350/407] eta: 0:01:05 time: 1.154744 data_time: 1.071709 memory: 400 2022/09/19 21:37:53 - mmengine - INFO - Epoch(val) [30][400/407] eta: 0:00:08 time: 1.155979 data_time: 1.080472 memory: 400 2022/09/19 21:38:49 - mmengine - INFO - Evaluating CocoMetric... 2022/09/19 21:39:07 - mmengine - INFO - Epoch(val) [30][407/407] coco/AP: 0.528249 coco/AP .5: 0.816718 coco/AP .75: 0.577152 coco/AP (M): 0.499001 coco/AP (L): 0.581975 coco/AR: 0.590680 coco/AR .5: 0.867758 coco/AR .75: 0.645309 coco/AR (M): 0.549303 coco/AR (L): 0.649052 2022/09/19 21:39:08 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_20.pth is removed 2022/09/19 21:39:10 - mmengine - INFO - The best checkpoint with 0.5282 coco/AP at 30 epoch is saved to best_coco/AP_epoch_30.pth. 2022/09/19 21:40:49 - mmengine - INFO - Epoch(train) [31][50/293] lr: 5.000000e-04 eta: 19:15:23 time: 1.993491 data_time: 0.303137 memory: 3324 loss_kpt: 0.172708 acc_pose: 0.619511 loss: 0.172708 2022/09/19 21:41:43 - mmengine - INFO - Epoch(train) [31][100/293] lr: 5.000000e-04 eta: 19:13:07 time: 1.078064 data_time: 0.109249 memory: 3324 loss_kpt: 0.173092 acc_pose: 0.627959 loss: 0.173092 2022/09/19 21:42:29 - mmengine - INFO - Epoch(train) [31][150/293] lr: 5.000000e-04 eta: 19:10:03 time: 0.914035 data_time: 0.169073 memory: 3324 loss_kpt: 0.172778 acc_pose: 0.589828 loss: 0.172778 2022/09/19 21:43:36 - mmengine - INFO - Epoch(train) [31][200/293] lr: 5.000000e-04 eta: 19:09:05 time: 1.339241 data_time: 0.096994 memory: 3324 loss_kpt: 0.172418 acc_pose: 0.683406 loss: 0.172418 2022/09/19 21:43:50 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 21:44:33 - mmengine - INFO - Epoch(train) [31][250/293] lr: 5.000000e-04 eta: 19:07:08 time: 1.133685 data_time: 0.106482 memory: 3324 loss_kpt: 0.171821 acc_pose: 0.675758 loss: 0.171821 2022/09/19 21:45:29 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 21:45:29 - mmengine - INFO - Saving checkpoint at 31 epochs 2022/09/19 21:46:25 - mmengine - INFO - Epoch(train) [32][50/293] lr: 5.000000e-04 eta: 18:58:31 time: 1.062844 data_time: 0.230346 memory: 3324 loss_kpt: 0.173292 acc_pose: 0.650956 loss: 0.173292 2022/09/19 21:47:14 - mmengine - INFO - Epoch(train) [32][100/293] lr: 5.000000e-04 eta: 18:55:56 time: 0.988756 data_time: 0.117251 memory: 3324 loss_kpt: 0.171204 acc_pose: 0.643321 loss: 0.171204 2022/09/19 21:48:16 - mmengine - INFO - Epoch(train) [32][150/293] lr: 5.000000e-04 eta: 18:54:30 time: 1.228429 data_time: 0.101862 memory: 3324 loss_kpt: 0.174795 acc_pose: 0.639171 loss: 0.174795 2022/09/19 21:49:05 - mmengine - INFO - Epoch(train) [32][200/293] lr: 5.000000e-04 eta: 18:51:59 time: 0.995317 data_time: 0.241752 memory: 3324 loss_kpt: 0.170481 acc_pose: 0.671483 loss: 0.170481 2022/09/19 21:50:03 - mmengine - INFO - Epoch(train) [32][250/293] lr: 5.000000e-04 eta: 18:50:14 time: 1.154883 data_time: 0.103123 memory: 3324 loss_kpt: 0.173594 acc_pose: 0.692150 loss: 0.173594 2022/09/19 21:50:36 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 21:50:36 - mmengine - INFO - Saving checkpoint at 32 epochs 2022/09/19 21:51:24 - mmengine - INFO - Epoch(train) [33][50/293] lr: 5.000000e-04 eta: 18:41:14 time: 0.899815 data_time: 0.366423 memory: 3324 loss_kpt: 0.170464 acc_pose: 0.730613 loss: 0.170464 2022/09/19 21:52:12 - mmengine - INFO - Epoch(train) [33][100/293] lr: 5.000000e-04 eta: 18:38:38 time: 0.959359 data_time: 0.106315 memory: 3324 loss_kpt: 0.172645 acc_pose: 0.694287 loss: 0.172645 2022/09/19 21:52:59 - mmengine - INFO - Epoch(train) [33][150/293] lr: 5.000000e-04 eta: 18:35:59 time: 0.944025 data_time: 0.251064 memory: 3324 loss_kpt: 0.171406 acc_pose: 0.624544 loss: 0.171406 2022/09/19 21:53:48 - mmengine - INFO - Epoch(train) [33][200/293] lr: 5.000000e-04 eta: 18:33:33 time: 0.985770 data_time: 0.144832 memory: 3324 loss_kpt: 0.170293 acc_pose: 0.636898 loss: 0.170293 2022/09/19 21:54:44 - mmengine - INFO - Epoch(train) [33][250/293] lr: 5.000000e-04 eta: 18:31:40 time: 1.106772 data_time: 0.097724 memory: 3324 loss_kpt: 0.171868 acc_pose: 0.644081 loss: 0.171868 2022/09/19 21:55:26 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 21:55:26 - mmengine - INFO - Saving checkpoint at 33 epochs 2022/09/19 21:56:23 - mmengine - INFO - Epoch(train) [34][50/293] lr: 5.000000e-04 eta: 18:23:52 time: 1.080831 data_time: 0.526505 memory: 3324 loss_kpt: 0.169150 acc_pose: 0.667510 loss: 0.169150 2022/09/19 21:57:14 - mmengine - INFO - Epoch(train) [34][100/293] lr: 5.000000e-04 eta: 18:21:44 time: 1.036253 data_time: 0.444801 memory: 3324 loss_kpt: 0.170352 acc_pose: 0.642759 loss: 0.170352 2022/09/19 21:58:19 - mmengine - INFO - Epoch(train) [34][150/293] lr: 5.000000e-04 eta: 18:20:42 time: 1.285349 data_time: 0.123993 memory: 3324 loss_kpt: 0.172287 acc_pose: 0.640131 loss: 0.172287 2022/09/19 21:59:07 - mmengine - INFO - Epoch(train) [34][200/293] lr: 5.000000e-04 eta: 18:18:17 time: 0.967691 data_time: 0.125094 memory: 3324 loss_kpt: 0.169992 acc_pose: 0.659521 loss: 0.169992 2022/09/19 21:59:54 - mmengine - INFO - Epoch(train) [34][250/293] lr: 5.000000e-04 eta: 18:15:44 time: 0.932862 data_time: 0.108316 memory: 3324 loss_kpt: 0.168110 acc_pose: 0.724612 loss: 0.168110 2022/09/19 22:00:31 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:00:31 - mmengine - INFO - Saving checkpoint at 34 epochs 2022/09/19 22:01:22 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:01:36 - mmengine - INFO - Epoch(train) [35][50/293] lr: 5.000000e-04 eta: 18:08:54 time: 1.236436 data_time: 0.389395 memory: 3324 loss_kpt: 0.169162 acc_pose: 0.608943 loss: 0.169162 2022/09/19 22:02:08 - mmengine - INFO - Epoch(train) [35][100/293] lr: 5.000000e-04 eta: 18:05:11 time: 0.644179 data_time: 0.103276 memory: 3324 loss_kpt: 0.167632 acc_pose: 0.628939 loss: 0.167632 2022/09/19 22:03:06 - mmengine - INFO - Epoch(train) [35][150/293] lr: 5.000000e-04 eta: 18:03:44 time: 1.169825 data_time: 0.117083 memory: 3324 loss_kpt: 0.170946 acc_pose: 0.687097 loss: 0.170946 2022/09/19 22:03:55 - mmengine - INFO - Epoch(train) [35][200/293] lr: 5.000000e-04 eta: 18:01:26 time: 0.969799 data_time: 0.141792 memory: 3324 loss_kpt: 0.170431 acc_pose: 0.651896 loss: 0.170431 2022/09/19 22:04:49 - mmengine - INFO - Epoch(train) [35][250/293] lr: 5.000000e-04 eta: 17:59:37 time: 1.081944 data_time: 0.116675 memory: 3324 loss_kpt: 0.172022 acc_pose: 0.741445 loss: 0.172022 2022/09/19 22:05:24 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:05:24 - mmengine - INFO - Saving checkpoint at 35 epochs 2022/09/19 22:06:26 - mmengine - INFO - Epoch(train) [36][50/293] lr: 5.000000e-04 eta: 17:52:53 time: 1.193111 data_time: 0.161097 memory: 3324 loss_kpt: 0.172337 acc_pose: 0.637533 loss: 0.172337 2022/09/19 22:07:09 - mmengine - INFO - Epoch(train) [36][100/293] lr: 5.000000e-04 eta: 17:50:13 time: 0.863333 data_time: 0.141819 memory: 3324 loss_kpt: 0.169082 acc_pose: 0.661605 loss: 0.169082 2022/09/19 22:08:19 - mmengine - INFO - Epoch(train) [36][150/293] lr: 5.000000e-04 eta: 17:49:45 time: 1.395260 data_time: 0.109868 memory: 3324 loss_kpt: 0.172984 acc_pose: 0.680677 loss: 0.172984 2022/09/19 22:08:54 - mmengine - INFO - Epoch(train) [36][200/293] lr: 5.000000e-04 eta: 17:46:28 time: 0.707760 data_time: 0.088979 memory: 3324 loss_kpt: 0.168263 acc_pose: 0.622655 loss: 0.168263 2022/09/19 22:09:41 - mmengine - INFO - Epoch(train) [36][250/293] lr: 5.000000e-04 eta: 17:44:07 time: 0.928461 data_time: 0.099701 memory: 3324 loss_kpt: 0.169725 acc_pose: 0.687692 loss: 0.169725 2022/09/19 22:10:30 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:10:30 - mmengine - INFO - Saving checkpoint at 36 epochs 2022/09/19 22:11:19 - mmengine - INFO - Epoch(train) [37][50/293] lr: 5.000000e-04 eta: 17:36:35 time: 0.930788 data_time: 0.150911 memory: 3324 loss_kpt: 0.168681 acc_pose: 0.686090 loss: 0.168681 2022/09/19 22:12:11 - mmengine - INFO - Epoch(train) [37][100/293] lr: 5.000000e-04 eta: 17:34:43 time: 1.036763 data_time: 0.101601 memory: 3324 loss_kpt: 0.173016 acc_pose: 0.662672 loss: 0.173016 2022/09/19 22:12:51 - mmengine - INFO - Epoch(train) [37][150/293] lr: 5.000000e-04 eta: 17:31:58 time: 0.811812 data_time: 0.102977 memory: 3324 loss_kpt: 0.170189 acc_pose: 0.679072 loss: 0.170189 2022/09/19 22:13:37 - mmengine - INFO - Epoch(train) [37][200/293] lr: 5.000000e-04 eta: 17:29:39 time: 0.915903 data_time: 0.098902 memory: 3324 loss_kpt: 0.170318 acc_pose: 0.699455 loss: 0.170318 2022/09/19 22:14:18 - mmengine - INFO - Epoch(train) [37][250/293] lr: 5.000000e-04 eta: 17:26:59 time: 0.825173 data_time: 0.137467 memory: 3324 loss_kpt: 0.168717 acc_pose: 0.690500 loss: 0.168717 2022/09/19 22:15:04 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:15:04 - mmengine - INFO - Saving checkpoint at 37 epochs 2022/09/19 22:15:47 - mmengine - INFO - Epoch(train) [38][50/293] lr: 5.000000e-04 eta: 17:19:17 time: 0.810126 data_time: 0.387642 memory: 3324 loss_kpt: 0.170195 acc_pose: 0.718552 loss: 0.170195 2022/09/19 22:16:51 - mmengine - INFO - Epoch(train) [38][100/293] lr: 5.000000e-04 eta: 17:18:25 time: 1.273276 data_time: 0.265631 memory: 3324 loss_kpt: 0.168950 acc_pose: 0.643317 loss: 0.168950 2022/09/19 22:17:47 - mmengine - INFO - Epoch(train) [38][150/293] lr: 5.000000e-04 eta: 17:16:59 time: 1.122544 data_time: 0.420043 memory: 3324 loss_kpt: 0.166660 acc_pose: 0.697356 loss: 0.166660 2022/09/19 22:17:57 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:18:28 - mmengine - INFO - Epoch(train) [38][200/293] lr: 5.000000e-04 eta: 17:14:23 time: 0.819208 data_time: 0.213164 memory: 3324 loss_kpt: 0.168426 acc_pose: 0.650717 loss: 0.168426 2022/09/19 22:19:03 - mmengine - INFO - Epoch(train) [38][250/293] lr: 5.000000e-04 eta: 17:11:21 time: 0.697641 data_time: 0.190786 memory: 3324 loss_kpt: 0.169841 acc_pose: 0.671667 loss: 0.169841 2022/09/19 22:19:39 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:19:39 - mmengine - INFO - Saving checkpoint at 38 epochs 2022/09/19 22:20:31 - mmengine - INFO - Epoch(train) [39][50/293] lr: 5.000000e-04 eta: 17:04:36 time: 0.993230 data_time: 0.629367 memory: 3324 loss_kpt: 0.169433 acc_pose: 0.664777 loss: 0.169433 2022/09/19 22:21:08 - mmengine - INFO - Epoch(train) [39][100/293] lr: 5.000000e-04 eta: 17:01:48 time: 0.740298 data_time: 0.088935 memory: 3324 loss_kpt: 0.164193 acc_pose: 0.653612 loss: 0.164193 2022/09/19 22:21:47 - mmengine - INFO - Epoch(train) [39][150/293] lr: 5.000000e-04 eta: 16:59:08 time: 0.776116 data_time: 0.096914 memory: 3324 loss_kpt: 0.169943 acc_pose: 0.668224 loss: 0.169943 2022/09/19 22:22:22 - mmengine - INFO - Epoch(train) [39][200/293] lr: 5.000000e-04 eta: 16:56:13 time: 0.699253 data_time: 0.097582 memory: 3324 loss_kpt: 0.168419 acc_pose: 0.634901 loss: 0.168419 2022/09/19 22:22:56 - mmengine - INFO - Epoch(train) [39][250/293] lr: 5.000000e-04 eta: 16:53:18 time: 0.695879 data_time: 0.095716 memory: 3324 loss_kpt: 0.170727 acc_pose: 0.640174 loss: 0.170727 2022/09/19 22:23:31 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:23:31 - mmengine - INFO - Saving checkpoint at 39 epochs 2022/09/19 22:24:25 - mmengine - INFO - Epoch(train) [40][50/293] lr: 5.000000e-04 eta: 16:46:54 time: 1.014420 data_time: 0.316943 memory: 3324 loss_kpt: 0.168713 acc_pose: 0.646694 loss: 0.168713 2022/09/19 22:25:01 - mmengine - INFO - Epoch(train) [40][100/293] lr: 5.000000e-04 eta: 16:44:07 time: 0.714735 data_time: 0.100801 memory: 3324 loss_kpt: 0.168452 acc_pose: 0.685047 loss: 0.168452 2022/09/19 22:25:38 - mmengine - INFO - Epoch(train) [40][150/293] lr: 5.000000e-04 eta: 16:41:27 time: 0.743027 data_time: 0.291160 memory: 3324 loss_kpt: 0.166960 acc_pose: 0.619784 loss: 0.166960 2022/09/19 22:26:06 - mmengine - INFO - Epoch(train) [40][200/293] lr: 5.000000e-04 eta: 16:38:12 time: 0.570489 data_time: 0.092372 memory: 3324 loss_kpt: 0.166909 acc_pose: 0.643988 loss: 0.166909 2022/09/19 22:26:53 - mmengine - INFO - Epoch(train) [40][250/293] lr: 5.000000e-04 eta: 16:36:16 time: 0.941659 data_time: 0.105468 memory: 3324 loss_kpt: 0.169493 acc_pose: 0.713480 loss: 0.169493 2022/09/19 22:27:19 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:27:19 - mmengine - INFO - Saving checkpoint at 40 epochs 2022/09/19 22:28:21 - mmengine - INFO - Epoch(val) [40][50/407] eta: 0:06:57 time: 1.168320 data_time: 1.121703 memory: 3324 2022/09/19 22:29:17 - mmengine - INFO - Epoch(val) [40][100/407] eta: 0:05:46 time: 1.128013 data_time: 1.087044 memory: 400 2022/09/19 22:30:16 - mmengine - INFO - Epoch(val) [40][150/407] eta: 0:05:01 time: 1.173949 data_time: 1.128999 memory: 400 2022/09/19 22:31:14 - mmengine - INFO - Epoch(val) [40][200/407] eta: 0:04:01 time: 1.165799 data_time: 1.112145 memory: 400 2022/09/19 22:32:13 - mmengine - INFO - Epoch(val) [40][250/407] eta: 0:03:04 time: 1.175562 data_time: 1.120817 memory: 400 2022/09/19 22:33:16 - mmengine - INFO - Epoch(val) [40][300/407] eta: 0:02:13 time: 1.251810 data_time: 1.208600 memory: 400 2022/09/19 22:34:17 - mmengine - INFO - Epoch(val) [40][350/407] eta: 0:01:09 time: 1.224108 data_time: 1.172107 memory: 400 2022/09/19 22:35:16 - mmengine - INFO - Epoch(val) [40][400/407] eta: 0:00:08 time: 1.187935 data_time: 1.138566 memory: 400 2022/09/19 22:36:13 - mmengine - INFO - Evaluating CocoMetric... 2022/09/19 22:36:31 - mmengine - INFO - Epoch(val) [40][407/407] coco/AP: 0.541588 coco/AP .5: 0.825199 coco/AP .75: 0.599298 coco/AP (M): 0.508600 coco/AP (L): 0.599329 coco/AR: 0.603889 coco/AR .5: 0.875630 coco/AR .75: 0.663885 coco/AR (M): 0.559847 coco/AR (L): 0.665478 2022/09/19 22:36:31 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_30.pth is removed 2022/09/19 22:36:33 - mmengine - INFO - The best checkpoint with 0.5416 coco/AP at 40 epoch is saved to best_coco/AP_epoch_40.pth. 2022/09/19 22:37:41 - mmengine - INFO - Epoch(train) [41][50/293] lr: 5.000000e-04 eta: 16:31:22 time: 1.364281 data_time: 0.825220 memory: 3324 loss_kpt: 0.168241 acc_pose: 0.697997 loss: 0.168241 2022/09/19 22:38:31 - mmengine - INFO - Epoch(train) [41][100/293] lr: 5.000000e-04 eta: 16:29:41 time: 1.000357 data_time: 0.090825 memory: 3324 loss_kpt: 0.166694 acc_pose: 0.712589 loss: 0.166694 2022/09/19 22:39:01 - mmengine - INFO - Epoch(train) [41][150/293] lr: 5.000000e-04 eta: 16:26:34 time: 0.586457 data_time: 0.142869 memory: 3324 loss_kpt: 0.165735 acc_pose: 0.753279 loss: 0.165735 2022/09/19 22:39:59 - mmengine - INFO - Epoch(train) [41][200/293] lr: 5.000000e-04 eta: 16:25:29 time: 1.165273 data_time: 0.240486 memory: 3324 loss_kpt: 0.167166 acc_pose: 0.652534 loss: 0.167166 2022/09/19 22:40:52 - mmengine - INFO - Epoch(train) [41][250/293] lr: 5.000000e-04 eta: 16:24:03 time: 1.066974 data_time: 0.276087 memory: 3324 loss_kpt: 0.170833 acc_pose: 0.675151 loss: 0.170833 2022/09/19 22:41:23 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:41:37 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:41:37 - mmengine - INFO - Saving checkpoint at 41 epochs 2022/09/19 22:42:34 - mmengine - INFO - Epoch(train) [42][50/293] lr: 5.000000e-04 eta: 16:18:10 time: 1.033939 data_time: 0.321202 memory: 3324 loss_kpt: 0.161884 acc_pose: 0.702564 loss: 0.161884 2022/09/19 22:43:31 - mmengine - INFO - Epoch(train) [42][100/293] lr: 5.000000e-04 eta: 16:17:02 time: 1.144618 data_time: 0.263712 memory: 3324 loss_kpt: 0.168316 acc_pose: 0.622092 loss: 0.168316 2022/09/19 22:44:29 - mmengine - INFO - Epoch(train) [42][150/293] lr: 5.000000e-04 eta: 16:15:57 time: 1.154266 data_time: 0.323642 memory: 3324 loss_kpt: 0.165908 acc_pose: 0.648612 loss: 0.165908 2022/09/19 22:45:15 - mmengine - INFO - Epoch(train) [42][200/293] lr: 5.000000e-04 eta: 16:14:04 time: 0.924471 data_time: 0.240304 memory: 3324 loss_kpt: 0.167391 acc_pose: 0.665856 loss: 0.167391 2022/09/19 22:45:56 - mmengine - INFO - Epoch(train) [42][250/293] lr: 5.000000e-04 eta: 16:11:53 time: 0.823960 data_time: 0.227505 memory: 3324 loss_kpt: 0.169484 acc_pose: 0.631817 loss: 0.169484 2022/09/19 22:46:31 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:46:31 - mmengine - INFO - Saving checkpoint at 42 epochs 2022/09/19 22:47:16 - mmengine - INFO - Epoch(train) [43][50/293] lr: 5.000000e-04 eta: 16:05:29 time: 0.826080 data_time: 0.232249 memory: 3324 loss_kpt: 0.164757 acc_pose: 0.621995 loss: 0.164757 2022/09/19 22:48:02 - mmengine - INFO - Epoch(train) [43][100/293] lr: 5.000000e-04 eta: 16:03:38 time: 0.916972 data_time: 0.198530 memory: 3324 loss_kpt: 0.167288 acc_pose: 0.655354 loss: 0.167288 2022/09/19 22:48:37 - mmengine - INFO - Epoch(train) [43][150/293] lr: 5.000000e-04 eta: 16:01:04 time: 0.691192 data_time: 0.193941 memory: 3324 loss_kpt: 0.165091 acc_pose: 0.707073 loss: 0.165091 2022/09/19 22:49:31 - mmengine - INFO - Epoch(train) [43][200/293] lr: 5.000000e-04 eta: 15:59:47 time: 1.085680 data_time: 0.248062 memory: 3324 loss_kpt: 0.165933 acc_pose: 0.644539 loss: 0.165933 2022/09/19 22:50:09 - mmengine - INFO - Epoch(train) [43][250/293] lr: 5.000000e-04 eta: 15:57:29 time: 0.765361 data_time: 0.285657 memory: 3324 loss_kpt: 0.164648 acc_pose: 0.616318 loss: 0.164648 2022/09/19 22:50:43 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:50:43 - mmengine - INFO - Saving checkpoint at 43 epochs 2022/09/19 22:51:26 - mmengine - INFO - Epoch(train) [44][50/293] lr: 5.000000e-04 eta: 15:51:11 time: 0.792328 data_time: 0.225211 memory: 3324 loss_kpt: 0.168034 acc_pose: 0.671481 loss: 0.168034 2022/09/19 22:52:08 - mmengine - INFO - Epoch(train) [44][100/293] lr: 5.000000e-04 eta: 15:49:12 time: 0.849621 data_time: 0.161914 memory: 3324 loss_kpt: 0.167936 acc_pose: 0.639315 loss: 0.167936 2022/09/19 22:52:52 - mmengine - INFO - Epoch(train) [44][150/293] lr: 5.000000e-04 eta: 15:47:17 time: 0.873436 data_time: 0.234078 memory: 3324 loss_kpt: 0.167522 acc_pose: 0.634060 loss: 0.167522 2022/09/19 22:53:39 - mmengine - INFO - Epoch(train) [44][200/293] lr: 5.000000e-04 eta: 15:45:36 time: 0.938770 data_time: 0.144897 memory: 3324 loss_kpt: 0.166799 acc_pose: 0.667222 loss: 0.166799 2022/09/19 22:54:28 - mmengine - INFO - Epoch(train) [44][250/293] lr: 5.000000e-04 eta: 15:44:01 time: 0.971130 data_time: 0.268324 memory: 3324 loss_kpt: 0.169224 acc_pose: 0.621732 loss: 0.169224 2022/09/19 22:55:01 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:55:01 - mmengine - INFO - Saving checkpoint at 44 epochs 2022/09/19 22:55:48 - mmengine - INFO - Epoch(train) [45][50/293] lr: 5.000000e-04 eta: 15:38:11 time: 0.875753 data_time: 0.243056 memory: 3324 loss_kpt: 0.165696 acc_pose: 0.725297 loss: 0.165696 2022/09/19 22:56:31 - mmengine - INFO - Epoch(train) [45][100/293] lr: 5.000000e-04 eta: 15:36:18 time: 0.860919 data_time: 0.266529 memory: 3324 loss_kpt: 0.164423 acc_pose: 0.651164 loss: 0.164423 2022/09/19 22:56:37 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:57:08 - mmengine - INFO - Epoch(train) [45][150/293] lr: 5.000000e-04 eta: 15:34:04 time: 0.750589 data_time: 0.160561 memory: 3324 loss_kpt: 0.166030 acc_pose: 0.705752 loss: 0.166030 2022/09/19 22:57:53 - mmengine - INFO - Epoch(train) [45][200/293] lr: 5.000000e-04 eta: 15:32:20 time: 0.902257 data_time: 0.251379 memory: 3324 loss_kpt: 0.166020 acc_pose: 0.715502 loss: 0.166020 2022/09/19 22:58:40 - mmengine - INFO - Epoch(train) [45][250/293] lr: 5.000000e-04 eta: 15:30:42 time: 0.936909 data_time: 0.140169 memory: 3324 loss_kpt: 0.168328 acc_pose: 0.646505 loss: 0.168328 2022/09/19 22:59:12 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 22:59:12 - mmengine - INFO - Saving checkpoint at 45 epochs 2022/09/19 22:59:53 - mmengine - INFO - Epoch(train) [46][50/293] lr: 5.000000e-04 eta: 15:24:38 time: 0.740742 data_time: 0.149650 memory: 3324 loss_kpt: 0.166522 acc_pose: 0.629150 loss: 0.166522 2022/09/19 23:00:25 - mmengine - INFO - Epoch(train) [46][100/293] lr: 5.000000e-04 eta: 15:22:08 time: 0.639884 data_time: 0.125449 memory: 3324 loss_kpt: 0.165108 acc_pose: 0.680310 loss: 0.165108 2022/09/19 23:00:49 - mmengine - INFO - Epoch(train) [46][150/293] lr: 5.000000e-04 eta: 15:19:12 time: 0.490131 data_time: 0.135037 memory: 3324 loss_kpt: 0.164360 acc_pose: 0.681222 loss: 0.164360 2022/09/19 23:01:32 - mmengine - INFO - Epoch(train) [46][200/293] lr: 5.000000e-04 eta: 15:17:25 time: 0.867209 data_time: 0.386661 memory: 3324 loss_kpt: 0.166199 acc_pose: 0.669712 loss: 0.166199 2022/09/19 23:02:11 - mmengine - INFO - Epoch(train) [46][250/293] lr: 5.000000e-04 eta: 15:15:20 time: 0.766398 data_time: 0.291442 memory: 3324 loss_kpt: 0.161463 acc_pose: 0.675052 loss: 0.161463 2022/09/19 23:02:42 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:02:42 - mmengine - INFO - Saving checkpoint at 46 epochs 2022/09/19 23:03:19 - mmengine - INFO - Epoch(train) [47][50/293] lr: 5.000000e-04 eta: 15:09:20 time: 0.692413 data_time: 0.177414 memory: 3324 loss_kpt: 0.166220 acc_pose: 0.657258 loss: 0.166220 2022/09/19 23:04:02 - mmengine - INFO - Epoch(train) [47][100/293] lr: 5.000000e-04 eta: 15:07:37 time: 0.872114 data_time: 0.309839 memory: 3324 loss_kpt: 0.165408 acc_pose: 0.602198 loss: 0.165408 2022/09/19 23:04:47 - mmengine - INFO - Epoch(train) [47][150/293] lr: 5.000000e-04 eta: 15:05:57 time: 0.889405 data_time: 0.271552 memory: 3324 loss_kpt: 0.168314 acc_pose: 0.656900 loss: 0.168314 2022/09/19 23:05:21 - mmengine - INFO - Epoch(train) [47][200/293] lr: 5.000000e-04 eta: 15:03:42 time: 0.688935 data_time: 0.206315 memory: 3324 loss_kpt: 0.168703 acc_pose: 0.706992 loss: 0.168703 2022/09/19 23:06:01 - mmengine - INFO - Epoch(train) [47][250/293] lr: 5.000000e-04 eta: 15:01:45 time: 0.788645 data_time: 0.288359 memory: 3324 loss_kpt: 0.162992 acc_pose: 0.661644 loss: 0.162992 2022/09/19 23:06:42 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:06:42 - mmengine - INFO - Saving checkpoint at 47 epochs 2022/09/19 23:07:43 - mmengine - INFO - Epoch(train) [48][50/293] lr: 5.000000e-04 eta: 14:57:16 time: 1.156057 data_time: 0.149321 memory: 3324 loss_kpt: 0.166347 acc_pose: 0.659663 loss: 0.166347 2022/09/19 23:08:37 - mmengine - INFO - Epoch(train) [48][100/293] lr: 5.000000e-04 eta: 14:56:12 time: 1.086097 data_time: 0.115369 memory: 3324 loss_kpt: 0.165207 acc_pose: 0.678114 loss: 0.165207 2022/09/19 23:09:44 - mmengine - INFO - Epoch(train) [48][150/293] lr: 5.000000e-04 eta: 14:55:51 time: 1.331265 data_time: 0.125131 memory: 3324 loss_kpt: 0.164030 acc_pose: 0.676662 loss: 0.164030 2022/09/19 23:10:20 - mmengine - INFO - Epoch(train) [48][200/293] lr: 5.000000e-04 eta: 14:53:47 time: 0.732623 data_time: 0.199269 memory: 3324 loss_kpt: 0.167378 acc_pose: 0.627709 loss: 0.167378 2022/09/19 23:10:42 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:10:56 - mmengine - INFO - Epoch(train) [48][250/293] lr: 5.000000e-04 eta: 14:51:39 time: 0.708715 data_time: 0.116517 memory: 3324 loss_kpt: 0.162677 acc_pose: 0.748303 loss: 0.162677 2022/09/19 23:11:33 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:11:33 - mmengine - INFO - Saving checkpoint at 48 epochs 2022/09/19 23:12:16 - mmengine - INFO - Epoch(train) [49][50/293] lr: 5.000000e-04 eta: 14:46:19 time: 0.811232 data_time: 0.275810 memory: 3324 loss_kpt: 0.164753 acc_pose: 0.670537 loss: 0.164753 2022/09/19 23:12:54 - mmengine - INFO - Epoch(train) [49][100/293] lr: 5.000000e-04 eta: 14:44:20 time: 0.743196 data_time: 0.136842 memory: 3324 loss_kpt: 0.166962 acc_pose: 0.684295 loss: 0.166962 2022/09/19 23:13:47 - mmengine - INFO - Epoch(train) [49][150/293] lr: 5.000000e-04 eta: 14:43:15 time: 1.067156 data_time: 0.125408 memory: 3324 loss_kpt: 0.167061 acc_pose: 0.638010 loss: 0.167061 2022/09/19 23:14:45 - mmengine - INFO - Epoch(train) [49][200/293] lr: 5.000000e-04 eta: 14:42:26 time: 1.164734 data_time: 0.128462 memory: 3324 loss_kpt: 0.162653 acc_pose: 0.744427 loss: 0.162653 2022/09/19 23:15:24 - mmengine - INFO - Epoch(train) [49][250/293] lr: 5.000000e-04 eta: 14:40:34 time: 0.775864 data_time: 0.127975 memory: 3324 loss_kpt: 0.165999 acc_pose: 0.697300 loss: 0.165999 2022/09/19 23:15:59 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:15:59 - mmengine - INFO - Saving checkpoint at 49 epochs 2022/09/19 23:16:43 - mmengine - INFO - Epoch(train) [50][50/293] lr: 5.000000e-04 eta: 14:35:23 time: 0.820211 data_time: 0.149638 memory: 3324 loss_kpt: 0.164056 acc_pose: 0.644322 loss: 0.164056 2022/09/19 23:17:26 - mmengine - INFO - Epoch(train) [50][100/293] lr: 5.000000e-04 eta: 14:33:47 time: 0.865551 data_time: 0.154982 memory: 3324 loss_kpt: 0.165284 acc_pose: 0.656169 loss: 0.165284 2022/09/19 23:18:05 - mmengine - INFO - Epoch(train) [50][150/293] lr: 5.000000e-04 eta: 14:31:57 time: 0.775892 data_time: 0.152430 memory: 3324 loss_kpt: 0.163884 acc_pose: 0.651251 loss: 0.163884 2022/09/19 23:18:43 - mmengine - INFO - Epoch(train) [50][200/293] lr: 5.000000e-04 eta: 14:30:05 time: 0.764910 data_time: 0.140990 memory: 3324 loss_kpt: 0.162049 acc_pose: 0.735991 loss: 0.162049 2022/09/19 23:19:23 - mmengine - INFO - Epoch(train) [50][250/293] lr: 5.000000e-04 eta: 14:28:18 time: 0.792996 data_time: 0.148402 memory: 3324 loss_kpt: 0.162334 acc_pose: 0.746530 loss: 0.162334 2022/09/19 23:19:46 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:19:46 - mmengine - INFO - Saving checkpoint at 50 epochs 2022/09/19 23:20:49 - mmengine - INFO - Epoch(val) [50][50/407] eta: 0:07:01 time: 1.179645 data_time: 1.128246 memory: 3324 2022/09/19 23:21:50 - mmengine - INFO - Epoch(val) [50][100/407] eta: 0:06:12 time: 1.212192 data_time: 1.135572 memory: 400 2022/09/19 23:22:50 - mmengine - INFO - Epoch(val) [50][150/407] eta: 0:05:07 time: 1.196934 data_time: 1.139344 memory: 400 2022/09/19 23:23:49 - mmengine - INFO - Epoch(val) [50][200/407] eta: 0:04:05 time: 1.184259 data_time: 1.132589 memory: 400 2022/09/19 23:24:48 - mmengine - INFO - Epoch(val) [50][250/407] eta: 0:03:05 time: 1.184159 data_time: 1.120065 memory: 400 2022/09/19 23:25:48 - mmengine - INFO - Epoch(val) [50][300/407] eta: 0:02:08 time: 1.196467 data_time: 1.133498 memory: 400 2022/09/19 23:26:47 - mmengine - INFO - Epoch(val) [50][350/407] eta: 0:01:07 time: 1.187856 data_time: 1.125111 memory: 400 2022/09/19 23:27:46 - mmengine - INFO - Epoch(val) [50][400/407] eta: 0:00:08 time: 1.176457 data_time: 1.113154 memory: 400 2022/09/19 23:28:44 - mmengine - INFO - Evaluating CocoMetric... 2022/09/19 23:29:03 - mmengine - INFO - Epoch(val) [50][407/407] coco/AP: 0.554116 coco/AP .5: 0.832160 coco/AP .75: 0.616155 coco/AP (M): 0.522054 coco/AP (L): 0.610987 coco/AR: 0.615035 coco/AR .5: 0.880825 coco/AR .75: 0.675535 coco/AR (M): 0.572166 coco/AR (L): 0.675325 2022/09/19 23:29:03 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_40.pth is removed 2022/09/19 23:29:05 - mmengine - INFO - The best checkpoint with 0.5541 coco/AP at 50 epoch is saved to best_coco/AP_epoch_50.pth. 2022/09/19 23:30:07 - mmengine - INFO - Epoch(train) [51][50/293] lr: 5.000000e-04 eta: 14:24:24 time: 1.240729 data_time: 0.441945 memory: 3324 loss_kpt: 0.164632 acc_pose: 0.762913 loss: 0.164632 2022/09/19 23:30:55 - mmengine - INFO - Epoch(train) [51][100/293] lr: 5.000000e-04 eta: 14:23:04 time: 0.953461 data_time: 0.346932 memory: 3324 loss_kpt: 0.164784 acc_pose: 0.693322 loss: 0.164784 2022/09/19 23:31:56 - mmengine - INFO - Epoch(train) [51][150/293] lr: 5.000000e-04 eta: 14:22:26 time: 1.220410 data_time: 0.123467 memory: 3324 loss_kpt: 0.168149 acc_pose: 0.722343 loss: 0.168149 2022/09/19 23:32:36 - mmengine - INFO - Epoch(train) [51][200/293] lr: 5.000000e-04 eta: 14:20:44 time: 0.809963 data_time: 0.384671 memory: 3324 loss_kpt: 0.162519 acc_pose: 0.718106 loss: 0.162519 2022/09/19 23:33:07 - mmengine - INFO - Epoch(train) [51][250/293] lr: 5.000000e-04 eta: 14:18:33 time: 0.621528 data_time: 0.106091 memory: 3324 loss_kpt: 0.164360 acc_pose: 0.682515 loss: 0.164360 2022/09/19 23:33:53 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:33:53 - mmengine - INFO - Saving checkpoint at 51 epochs 2022/09/19 23:34:28 - mmengine - INFO - Epoch(train) [52][50/293] lr: 5.000000e-04 eta: 14:13:14 time: 0.660155 data_time: 0.139240 memory: 3324 loss_kpt: 0.163837 acc_pose: 0.722703 loss: 0.163837 2022/09/19 23:34:34 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:35:05 - mmengine - INFO - Epoch(train) [52][100/293] lr: 5.000000e-04 eta: 14:11:21 time: 0.727709 data_time: 0.155142 memory: 3324 loss_kpt: 0.164662 acc_pose: 0.692690 loss: 0.164662 2022/09/19 23:35:49 - mmengine - INFO - Epoch(train) [52][150/293] lr: 5.000000e-04 eta: 14:09:53 time: 0.884074 data_time: 0.104885 memory: 3324 loss_kpt: 0.165825 acc_pose: 0.714258 loss: 0.165825 2022/09/19 23:36:27 - mmengine - INFO - Epoch(train) [52][200/293] lr: 5.000000e-04 eta: 14:08:06 time: 0.756012 data_time: 0.136706 memory: 3324 loss_kpt: 0.166650 acc_pose: 0.665448 loss: 0.166650 2022/09/19 23:37:19 - mmengine - INFO - Epoch(train) [52][250/293] lr: 5.000000e-04 eta: 14:07:02 time: 1.035802 data_time: 0.107999 memory: 3324 loss_kpt: 0.162702 acc_pose: 0.689343 loss: 0.162702 2022/09/19 23:37:56 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:37:56 - mmengine - INFO - Saving checkpoint at 52 epochs 2022/09/19 23:38:33 - mmengine - INFO - Epoch(train) [53][50/293] lr: 5.000000e-04 eta: 14:01:54 time: 0.681189 data_time: 0.154119 memory: 3324 loss_kpt: 0.163806 acc_pose: 0.642475 loss: 0.163806 2022/09/19 23:39:08 - mmengine - INFO - Epoch(train) [53][100/293] lr: 5.000000e-04 eta: 14:00:00 time: 0.698925 data_time: 0.153267 memory: 3324 loss_kpt: 0.162444 acc_pose: 0.734978 loss: 0.162444 2022/09/19 23:39:44 - mmengine - INFO - Epoch(train) [53][150/293] lr: 5.000000e-04 eta: 13:58:10 time: 0.718721 data_time: 0.107607 memory: 3324 loss_kpt: 0.164384 acc_pose: 0.695616 loss: 0.164384 2022/09/19 23:40:27 - mmengine - INFO - Epoch(train) [53][200/293] lr: 5.000000e-04 eta: 13:56:44 time: 0.877308 data_time: 0.160797 memory: 3324 loss_kpt: 0.160968 acc_pose: 0.724498 loss: 0.160968 2022/09/19 23:41:11 - mmengine - INFO - Epoch(train) [53][250/293] lr: 5.000000e-04 eta: 13:55:18 time: 0.881864 data_time: 0.104469 memory: 3324 loss_kpt: 0.166763 acc_pose: 0.681802 loss: 0.166763 2022/09/19 23:41:41 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:41:41 - mmengine - INFO - Saving checkpoint at 53 epochs 2022/09/19 23:42:26 - mmengine - INFO - Epoch(train) [54][50/293] lr: 5.000000e-04 eta: 13:50:44 time: 0.847018 data_time: 0.186924 memory: 3324 loss_kpt: 0.162733 acc_pose: 0.690270 loss: 0.162733 2022/09/19 23:42:56 - mmengine - INFO - Epoch(train) [54][100/293] lr: 5.000000e-04 eta: 13:48:39 time: 0.605614 data_time: 0.185935 memory: 3324 loss_kpt: 0.162685 acc_pose: 0.617197 loss: 0.162685 2022/09/19 23:43:32 - mmengine - INFO - Epoch(train) [54][150/293] lr: 5.000000e-04 eta: 13:46:51 time: 0.714939 data_time: 0.225100 memory: 3324 loss_kpt: 0.162305 acc_pose: 0.732749 loss: 0.162305 2022/09/19 23:44:14 - mmengine - INFO - Epoch(train) [54][200/293] lr: 5.000000e-04 eta: 13:45:22 time: 0.843675 data_time: 0.479931 memory: 3324 loss_kpt: 0.164281 acc_pose: 0.730149 loss: 0.164281 2022/09/19 23:45:02 - mmengine - INFO - Epoch(train) [54][250/293] lr: 5.000000e-04 eta: 13:44:11 time: 0.965155 data_time: 0.368766 memory: 3324 loss_kpt: 0.165089 acc_pose: 0.743108 loss: 0.165089 2022/09/19 23:45:34 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:45:34 - mmengine - INFO - Saving checkpoint at 54 epochs 2022/09/19 23:46:09 - mmengine - INFO - Epoch(train) [55][50/293] lr: 5.000000e-04 eta: 13:39:14 time: 0.644667 data_time: 0.151072 memory: 3324 loss_kpt: 0.163403 acc_pose: 0.650936 loss: 0.163403 2022/09/19 23:46:45 - mmengine - INFO - Epoch(train) [55][100/293] lr: 5.000000e-04 eta: 13:37:30 time: 0.722874 data_time: 0.319592 memory: 3324 loss_kpt: 0.165005 acc_pose: 0.634757 loss: 0.165005 2022/09/19 23:47:28 - mmengine - INFO - Epoch(train) [55][150/293] lr: 5.000000e-04 eta: 13:36:06 time: 0.866850 data_time: 0.161687 memory: 3324 loss_kpt: 0.163497 acc_pose: 0.720347 loss: 0.163497 2022/09/19 23:47:53 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:48:11 - mmengine - INFO - Epoch(train) [55][200/293] lr: 5.000000e-04 eta: 13:34:43 time: 0.866710 data_time: 0.103832 memory: 3324 loss_kpt: 0.162097 acc_pose: 0.696178 loss: 0.162097 2022/09/19 23:49:01 - mmengine - INFO - Epoch(train) [55][250/293] lr: 5.000000e-04 eta: 13:33:36 time: 0.982246 data_time: 0.110127 memory: 3324 loss_kpt: 0.161764 acc_pose: 0.706670 loss: 0.161764 2022/09/19 23:49:31 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:49:31 - mmengine - INFO - Saving checkpoint at 55 epochs 2022/09/19 23:50:08 - mmengine - INFO - Epoch(train) [56][50/293] lr: 5.000000e-04 eta: 13:28:52 time: 0.685645 data_time: 0.147193 memory: 3324 loss_kpt: 0.163522 acc_pose: 0.696911 loss: 0.163522 2022/09/19 23:51:00 - mmengine - INFO - Epoch(train) [56][100/293] lr: 5.000000e-04 eta: 13:27:54 time: 1.036214 data_time: 0.192161 memory: 3324 loss_kpt: 0.165066 acc_pose: 0.716071 loss: 0.165066 2022/09/19 23:51:52 - mmengine - INFO - Epoch(train) [56][150/293] lr: 5.000000e-04 eta: 13:26:58 time: 1.052894 data_time: 0.112059 memory: 3324 loss_kpt: 0.164769 acc_pose: 0.671054 loss: 0.164769 2022/09/19 23:52:32 - mmengine - INFO - Epoch(train) [56][200/293] lr: 5.000000e-04 eta: 13:25:26 time: 0.789728 data_time: 0.117523 memory: 3324 loss_kpt: 0.163046 acc_pose: 0.698228 loss: 0.163046 2022/09/19 23:53:00 - mmengine - INFO - Epoch(train) [56][250/293] lr: 5.000000e-04 eta: 13:23:24 time: 0.572177 data_time: 0.121810 memory: 3324 loss_kpt: 0.162129 acc_pose: 0.687267 loss: 0.162129 2022/09/19 23:54:02 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:54:02 - mmengine - INFO - Saving checkpoint at 56 epochs 2022/09/19 23:55:10 - mmengine - INFO - Epoch(train) [57][50/293] lr: 5.000000e-04 eta: 13:20:11 time: 1.298011 data_time: 0.154568 memory: 3324 loss_kpt: 0.159268 acc_pose: 0.669221 loss: 0.159268 2022/09/19 23:55:57 - mmengine - INFO - Epoch(train) [57][100/293] lr: 5.000000e-04 eta: 13:19:00 time: 0.940079 data_time: 0.410157 memory: 3324 loss_kpt: 0.161731 acc_pose: 0.607592 loss: 0.161731 2022/09/19 23:56:33 - mmengine - INFO - Epoch(train) [57][150/293] lr: 5.000000e-04 eta: 13:17:21 time: 0.723462 data_time: 0.101456 memory: 3324 loss_kpt: 0.165009 acc_pose: 0.702161 loss: 0.165009 2022/09/19 23:57:26 - mmengine - INFO - Epoch(train) [57][200/293] lr: 5.000000e-04 eta: 13:16:28 time: 1.069943 data_time: 0.130983 memory: 3324 loss_kpt: 0.160804 acc_pose: 0.739521 loss: 0.160804 2022/09/19 23:58:10 - mmengine - INFO - Epoch(train) [57][250/293] lr: 5.000000e-04 eta: 13:15:10 time: 0.874094 data_time: 0.116842 memory: 3324 loss_kpt: 0.166364 acc_pose: 0.665756 loss: 0.166364 2022/09/19 23:58:45 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/19 23:58:46 - mmengine - INFO - Saving checkpoint at 57 epochs 2022/09/19 23:59:21 - mmengine - INFO - Epoch(train) [58][50/293] lr: 5.000000e-04 eta: 13:10:35 time: 0.662789 data_time: 0.186398 memory: 3324 loss_kpt: 0.158978 acc_pose: 0.717767 loss: 0.158978 2022/09/20 00:00:14 - mmengine - INFO - Epoch(train) [58][100/293] lr: 5.000000e-04 eta: 13:09:42 time: 1.058967 data_time: 0.131940 memory: 3324 loss_kpt: 0.161258 acc_pose: 0.696431 loss: 0.161258 2022/09/20 00:00:58 - mmengine - INFO - Epoch(train) [58][150/293] lr: 5.000000e-04 eta: 13:08:25 time: 0.879585 data_time: 0.331574 memory: 3324 loss_kpt: 0.164022 acc_pose: 0.712899 loss: 0.164022 2022/09/20 00:01:36 - mmengine - INFO - Epoch(train) [58][200/293] lr: 5.000000e-04 eta: 13:06:53 time: 0.758923 data_time: 0.306369 memory: 3324 loss_kpt: 0.165773 acc_pose: 0.678306 loss: 0.165773 2022/09/20 00:02:26 - mmengine - INFO - Epoch(train) [58][250/293] lr: 5.000000e-04 eta: 13:05:53 time: 1.006543 data_time: 0.104155 memory: 3324 loss_kpt: 0.163673 acc_pose: 0.642813 loss: 0.163673 2022/09/20 00:03:00 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:03:00 - mmengine - INFO - Saving checkpoint at 58 epochs 2022/09/20 00:03:11 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:04:05 - mmengine - INFO - Epoch(train) [59][50/293] lr: 5.000000e-04 eta: 13:02:42 time: 1.255700 data_time: 0.202176 memory: 3324 loss_kpt: 0.163011 acc_pose: 0.658354 loss: 0.163011 2022/09/20 00:04:46 - mmengine - INFO - Epoch(train) [59][100/293] lr: 5.000000e-04 eta: 13:01:18 time: 0.817086 data_time: 0.107519 memory: 3324 loss_kpt: 0.160043 acc_pose: 0.658276 loss: 0.160043 2022/09/20 00:05:24 - mmengine - INFO - Epoch(train) [59][150/293] lr: 5.000000e-04 eta: 12:59:48 time: 0.770033 data_time: 0.255667 memory: 3324 loss_kpt: 0.163329 acc_pose: 0.648426 loss: 0.163329 2022/09/20 00:05:57 - mmengine - INFO - Epoch(train) [59][200/293] lr: 5.000000e-04 eta: 12:58:05 time: 0.658875 data_time: 0.127846 memory: 3324 loss_kpt: 0.162451 acc_pose: 0.657157 loss: 0.162451 2022/09/20 00:06:48 - mmengine - INFO - Epoch(train) [59][250/293] lr: 5.000000e-04 eta: 12:57:06 time: 1.005736 data_time: 0.402998 memory: 3324 loss_kpt: 0.162438 acc_pose: 0.729128 loss: 0.162438 2022/09/20 00:07:22 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:07:22 - mmengine - INFO - Saving checkpoint at 59 epochs 2022/09/20 00:08:07 - mmengine - INFO - Epoch(train) [60][50/293] lr: 5.000000e-04 eta: 12:53:07 time: 0.853009 data_time: 0.140632 memory: 3324 loss_kpt: 0.161615 acc_pose: 0.727040 loss: 0.161615 2022/09/20 00:08:47 - mmengine - INFO - Epoch(train) [60][100/293] lr: 5.000000e-04 eta: 12:51:42 time: 0.793775 data_time: 0.098867 memory: 3324 loss_kpt: 0.160013 acc_pose: 0.663621 loss: 0.160013 2022/09/20 00:09:42 - mmengine - INFO - Epoch(train) [60][150/293] lr: 5.000000e-04 eta: 12:50:58 time: 1.115916 data_time: 0.105279 memory: 3324 loss_kpt: 0.161696 acc_pose: 0.675412 loss: 0.161696 2022/09/20 00:10:40 - mmengine - INFO - Epoch(train) [60][200/293] lr: 5.000000e-04 eta: 12:50:18 time: 1.143564 data_time: 0.164594 memory: 3324 loss_kpt: 0.163573 acc_pose: 0.685339 loss: 0.163573 2022/09/20 00:11:17 - mmengine - INFO - Epoch(train) [60][250/293] lr: 5.000000e-04 eta: 12:48:49 time: 0.757801 data_time: 0.145054 memory: 3324 loss_kpt: 0.161266 acc_pose: 0.720888 loss: 0.161266 2022/09/20 00:12:03 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:12:03 - mmengine - INFO - Saving checkpoint at 60 epochs 2022/09/20 00:13:06 - mmengine - INFO - Epoch(val) [60][50/407] eta: 0:07:03 time: 1.187098 data_time: 1.139524 memory: 3324 2022/09/20 00:14:04 - mmengine - INFO - Epoch(val) [60][100/407] eta: 0:05:56 time: 1.162421 data_time: 1.105483 memory: 400 2022/09/20 00:15:02 - mmengine - INFO - Epoch(val) [60][150/407] eta: 0:04:58 time: 1.160497 data_time: 1.116536 memory: 400 2022/09/20 00:16:02 - mmengine - INFO - Epoch(val) [60][200/407] eta: 0:04:08 time: 1.200517 data_time: 1.142866 memory: 400 2022/09/20 00:17:02 - mmengine - INFO - Epoch(val) [60][250/407] eta: 0:03:07 time: 1.191219 data_time: 1.127610 memory: 400 2022/09/20 00:18:01 - mmengine - INFO - Epoch(val) [60][300/407] eta: 0:02:05 time: 1.174897 data_time: 1.098087 memory: 400 2022/09/20 00:19:00 - mmengine - INFO - Epoch(val) [60][350/407] eta: 0:01:07 time: 1.178913 data_time: 1.118940 memory: 400 2022/09/20 00:19:59 - mmengine - INFO - Epoch(val) [60][400/407] eta: 0:00:08 time: 1.192679 data_time: 1.140934 memory: 400 2022/09/20 00:20:56 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 00:21:14 - mmengine - INFO - Epoch(val) [60][407/407] coco/AP: 0.562644 coco/AP .5: 0.829403 coco/AP .75: 0.625990 coco/AP (M): 0.529791 coco/AP (L): 0.622375 coco/AR: 0.623882 coco/AR .5: 0.878621 coco/AR .75: 0.686555 coco/AR (M): 0.579896 coco/AR (L): 0.685619 2022/09/20 00:21:14 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_50.pth is removed 2022/09/20 00:21:16 - mmengine - INFO - The best checkpoint with 0.5626 coco/AP at 60 epoch is saved to best_coco/AP_epoch_60.pth. 2022/09/20 00:22:23 - mmengine - INFO - Epoch(train) [61][50/293] lr: 5.000000e-04 eta: 12:45:54 time: 1.329105 data_time: 0.271824 memory: 3324 loss_kpt: 0.163291 acc_pose: 0.739279 loss: 0.163291 2022/09/20 00:23:04 - mmengine - INFO - Epoch(train) [61][100/293] lr: 5.000000e-04 eta: 12:44:33 time: 0.819693 data_time: 0.336405 memory: 3324 loss_kpt: 0.159777 acc_pose: 0.728728 loss: 0.159777 2022/09/20 00:23:44 - mmengine - INFO - Epoch(train) [61][150/293] lr: 5.000000e-04 eta: 12:43:12 time: 0.808629 data_time: 0.114234 memory: 3324 loss_kpt: 0.159317 acc_pose: 0.746486 loss: 0.159317 2022/09/20 00:24:20 - mmengine - INFO - Epoch(train) [61][200/293] lr: 5.000000e-04 eta: 12:41:40 time: 0.728115 data_time: 0.111739 memory: 3324 loss_kpt: 0.159441 acc_pose: 0.658778 loss: 0.159441 2022/09/20 00:25:08 - mmengine - INFO - Epoch(train) [61][250/293] lr: 5.000000e-04 eta: 12:40:37 time: 0.952014 data_time: 0.253543 memory: 3324 loss_kpt: 0.160122 acc_pose: 0.701214 loss: 0.160122 2022/09/20 00:25:28 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:25:28 - mmengine - INFO - Saving checkpoint at 61 epochs 2022/09/20 00:26:16 - mmengine - INFO - Epoch(train) [62][50/293] lr: 5.000000e-04 eta: 12:36:54 time: 0.911390 data_time: 0.419530 memory: 3324 loss_kpt: 0.161233 acc_pose: 0.717147 loss: 0.161233 2022/09/20 00:27:01 - mmengine - INFO - Epoch(train) [62][100/293] lr: 5.000000e-04 eta: 12:35:44 time: 0.888971 data_time: 0.399070 memory: 3324 loss_kpt: 0.160645 acc_pose: 0.689331 loss: 0.160645 2022/09/20 00:27:26 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:27:45 - mmengine - INFO - Epoch(train) [62][150/293] lr: 5.000000e-04 eta: 12:34:34 time: 0.892982 data_time: 0.094501 memory: 3324 loss_kpt: 0.160038 acc_pose: 0.747981 loss: 0.160038 2022/09/20 00:28:32 - mmengine - INFO - Epoch(train) [62][200/293] lr: 5.000000e-04 eta: 12:33:29 time: 0.938535 data_time: 0.106469 memory: 3324 loss_kpt: 0.164394 acc_pose: 0.699206 loss: 0.164394 2022/09/20 00:29:08 - mmengine - INFO - Epoch(train) [62][250/293] lr: 5.000000e-04 eta: 12:31:57 time: 0.702728 data_time: 0.098117 memory: 3324 loss_kpt: 0.159285 acc_pose: 0.691881 loss: 0.159285 2022/09/20 00:29:58 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:29:58 - mmengine - INFO - Saving checkpoint at 62 epochs 2022/09/20 00:30:44 - mmengine - INFO - Epoch(train) [63][50/293] lr: 5.000000e-04 eta: 12:28:12 time: 0.850849 data_time: 0.162554 memory: 3324 loss_kpt: 0.161225 acc_pose: 0.661823 loss: 0.161225 2022/09/20 00:31:19 - mmengine - INFO - Epoch(train) [63][100/293] lr: 5.000000e-04 eta: 12:26:40 time: 0.698860 data_time: 0.096769 memory: 3324 loss_kpt: 0.160165 acc_pose: 0.666020 loss: 0.160165 2022/09/20 00:32:11 - mmengine - INFO - Epoch(train) [63][150/293] lr: 5.000000e-04 eta: 12:25:50 time: 1.052071 data_time: 0.341030 memory: 3324 loss_kpt: 0.159568 acc_pose: 0.706057 loss: 0.159568 2022/09/20 00:33:13 - mmengine - INFO - Epoch(train) [63][200/293] lr: 5.000000e-04 eta: 12:25:21 time: 1.228481 data_time: 0.193950 memory: 3324 loss_kpt: 0.162096 acc_pose: 0.692668 loss: 0.162096 2022/09/20 00:34:29 - mmengine - INFO - Epoch(train) [63][250/293] lr: 5.000000e-04 eta: 12:25:28 time: 1.538068 data_time: 0.379501 memory: 3324 loss_kpt: 0.166211 acc_pose: 0.698125 loss: 0.166211 2022/09/20 00:35:22 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:35:22 - mmengine - INFO - Saving checkpoint at 63 epochs 2022/09/20 00:36:17 - mmengine - INFO - Epoch(train) [64][50/293] lr: 5.000000e-04 eta: 12:22:09 time: 1.051201 data_time: 0.276048 memory: 3324 loss_kpt: 0.159052 acc_pose: 0.706066 loss: 0.159052 2022/09/20 00:36:51 - mmengine - INFO - Epoch(train) [64][100/293] lr: 5.000000e-04 eta: 12:20:35 time: 0.668101 data_time: 0.156581 memory: 3324 loss_kpt: 0.161195 acc_pose: 0.714568 loss: 0.161195 2022/09/20 00:37:41 - mmengine - INFO - Epoch(train) [64][150/293] lr: 5.000000e-04 eta: 12:19:39 time: 0.998387 data_time: 0.144716 memory: 3324 loss_kpt: 0.160291 acc_pose: 0.724840 loss: 0.160291 2022/09/20 00:38:19 - mmengine - INFO - Epoch(train) [64][200/293] lr: 5.000000e-04 eta: 12:18:17 time: 0.766255 data_time: 0.106329 memory: 3324 loss_kpt: 0.163206 acc_pose: 0.730365 loss: 0.163206 2022/09/20 00:38:59 - mmengine - INFO - Epoch(train) [64][250/293] lr: 5.000000e-04 eta: 12:16:59 time: 0.803037 data_time: 0.145639 memory: 3324 loss_kpt: 0.164381 acc_pose: 0.765354 loss: 0.164381 2022/09/20 00:39:47 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:39:47 - mmengine - INFO - Saving checkpoint at 64 epochs 2022/09/20 00:40:33 - mmengine - INFO - Epoch(train) [65][50/293] lr: 5.000000e-04 eta: 12:13:24 time: 0.872981 data_time: 0.132950 memory: 3324 loss_kpt: 0.162399 acc_pose: 0.717522 loss: 0.162399 2022/09/20 00:41:12 - mmengine - INFO - Epoch(train) [65][100/293] lr: 5.000000e-04 eta: 12:12:04 time: 0.779955 data_time: 0.141018 memory: 3324 loss_kpt: 0.160264 acc_pose: 0.719654 loss: 0.160264 2022/09/20 00:41:59 - mmengine - INFO - Epoch(train) [65][150/293] lr: 5.000000e-04 eta: 12:11:01 time: 0.928574 data_time: 0.101798 memory: 3324 loss_kpt: 0.161592 acc_pose: 0.683568 loss: 0.161592 2022/09/20 00:42:39 - mmengine - INFO - Epoch(train) [65][200/293] lr: 5.000000e-04 eta: 12:09:45 time: 0.811478 data_time: 0.105216 memory: 3324 loss_kpt: 0.160620 acc_pose: 0.714304 loss: 0.160620 2022/09/20 00:43:15 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:43:15 - mmengine - INFO - Epoch(train) [65][250/293] lr: 5.000000e-04 eta: 12:08:20 time: 0.725265 data_time: 0.099672 memory: 3324 loss_kpt: 0.160139 acc_pose: 0.722541 loss: 0.160139 2022/09/20 00:43:43 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:43:43 - mmengine - INFO - Saving checkpoint at 65 epochs 2022/09/20 00:44:39 - mmengine - INFO - Epoch(train) [66][50/293] lr: 5.000000e-04 eta: 12:05:10 time: 1.058081 data_time: 0.126072 memory: 3324 loss_kpt: 0.162364 acc_pose: 0.733140 loss: 0.162364 2022/09/20 00:45:18 - mmengine - INFO - Epoch(train) [66][100/293] lr: 5.000000e-04 eta: 12:03:52 time: 0.788982 data_time: 0.095974 memory: 3324 loss_kpt: 0.160736 acc_pose: 0.679926 loss: 0.160736 2022/09/20 00:46:03 - mmengine - INFO - Epoch(train) [66][150/293] lr: 5.000000e-04 eta: 12:02:47 time: 0.897257 data_time: 0.104260 memory: 3324 loss_kpt: 0.157450 acc_pose: 0.666775 loss: 0.157450 2022/09/20 00:46:39 - mmengine - INFO - Epoch(train) [66][200/293] lr: 5.000000e-04 eta: 12:01:23 time: 0.723406 data_time: 0.160622 memory: 3324 loss_kpt: 0.161412 acc_pose: 0.701765 loss: 0.161412 2022/09/20 00:47:13 - mmengine - INFO - Epoch(train) [66][250/293] lr: 5.000000e-04 eta: 11:59:52 time: 0.666878 data_time: 0.098965 memory: 3324 loss_kpt: 0.161439 acc_pose: 0.755683 loss: 0.161439 2022/09/20 00:47:55 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:47:55 - mmengine - INFO - Saving checkpoint at 66 epochs 2022/09/20 00:48:36 - mmengine - INFO - Epoch(train) [67][50/293] lr: 5.000000e-04 eta: 11:56:13 time: 0.761806 data_time: 0.137414 memory: 3324 loss_kpt: 0.155999 acc_pose: 0.709733 loss: 0.155999 2022/09/20 00:49:06 - mmengine - INFO - Epoch(train) [67][100/293] lr: 5.000000e-04 eta: 11:54:37 time: 0.599805 data_time: 0.103418 memory: 3324 loss_kpt: 0.159573 acc_pose: 0.746092 loss: 0.159573 2022/09/20 00:49:36 - mmengine - INFO - Epoch(train) [67][150/293] lr: 5.000000e-04 eta: 11:53:00 time: 0.597918 data_time: 0.105514 memory: 3324 loss_kpt: 0.160529 acc_pose: 0.714676 loss: 0.160529 2022/09/20 00:50:06 - mmengine - INFO - Epoch(train) [67][200/293] lr: 5.000000e-04 eta: 11:51:26 time: 0.615726 data_time: 0.133417 memory: 3324 loss_kpt: 0.159017 acc_pose: 0.692157 loss: 0.159017 2022/09/20 00:50:48 - mmengine - INFO - Epoch(train) [67][250/293] lr: 5.000000e-04 eta: 11:50:17 time: 0.839120 data_time: 0.400501 memory: 3324 loss_kpt: 0.159348 acc_pose: 0.701974 loss: 0.159348 2022/09/20 00:51:33 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:51:33 - mmengine - INFO - Saving checkpoint at 67 epochs 2022/09/20 00:52:23 - mmengine - INFO - Epoch(train) [68][50/293] lr: 5.000000e-04 eta: 11:47:02 time: 0.944477 data_time: 0.324844 memory: 3324 loss_kpt: 0.161378 acc_pose: 0.653177 loss: 0.161378 2022/09/20 00:53:03 - mmengine - INFO - Epoch(train) [68][100/293] lr: 5.000000e-04 eta: 11:45:48 time: 0.794982 data_time: 0.134627 memory: 3324 loss_kpt: 0.154863 acc_pose: 0.706168 loss: 0.154863 2022/09/20 00:53:45 - mmengine - INFO - Epoch(train) [68][150/293] lr: 5.000000e-04 eta: 11:44:39 time: 0.837920 data_time: 0.131607 memory: 3324 loss_kpt: 0.158226 acc_pose: 0.706134 loss: 0.158226 2022/09/20 00:54:24 - mmengine - INFO - Epoch(train) [68][200/293] lr: 5.000000e-04 eta: 11:43:23 time: 0.778693 data_time: 0.104652 memory: 3324 loss_kpt: 0.160072 acc_pose: 0.739589 loss: 0.160072 2022/09/20 00:54:57 - mmengine - INFO - Epoch(train) [68][250/293] lr: 5.000000e-04 eta: 11:41:57 time: 0.670118 data_time: 0.103919 memory: 3324 loss_kpt: 0.160680 acc_pose: 0.678009 loss: 0.160680 2022/09/20 00:55:31 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:55:31 - mmengine - INFO - Saving checkpoint at 68 epochs 2022/09/20 00:56:16 - mmengine - INFO - Epoch(train) [69][50/293] lr: 5.000000e-04 eta: 11:38:35 time: 0.846892 data_time: 0.130650 memory: 3324 loss_kpt: 0.156907 acc_pose: 0.714889 loss: 0.156907 2022/09/20 00:56:30 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:56:42 - mmengine - INFO - Epoch(train) [69][100/293] lr: 5.000000e-04 eta: 11:36:55 time: 0.527743 data_time: 0.106429 memory: 3324 loss_kpt: 0.158010 acc_pose: 0.627573 loss: 0.158010 2022/09/20 00:57:27 - mmengine - INFO - Epoch(train) [69][150/293] lr: 5.000000e-04 eta: 11:35:54 time: 0.902013 data_time: 0.107648 memory: 3324 loss_kpt: 0.164818 acc_pose: 0.635220 loss: 0.164818 2022/09/20 00:58:18 - mmengine - INFO - Epoch(train) [69][200/293] lr: 5.000000e-04 eta: 11:35:05 time: 1.024561 data_time: 0.226398 memory: 3324 loss_kpt: 0.159421 acc_pose: 0.640051 loss: 0.159421 2022/09/20 00:59:00 - mmengine - INFO - Epoch(train) [69][250/293] lr: 5.000000e-04 eta: 11:33:57 time: 0.835353 data_time: 0.283651 memory: 3324 loss_kpt: 0.160847 acc_pose: 0.726019 loss: 0.160847 2022/09/20 00:59:45 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 00:59:45 - mmengine - INFO - Saving checkpoint at 69 epochs 2022/09/20 01:00:22 - mmengine - INFO - Epoch(train) [70][50/293] lr: 5.000000e-04 eta: 11:30:23 time: 0.691786 data_time: 0.193457 memory: 3324 loss_kpt: 0.159036 acc_pose: 0.727050 loss: 0.159036 2022/09/20 01:01:09 - mmengine - INFO - Epoch(train) [70][100/293] lr: 5.000000e-04 eta: 11:29:27 time: 0.945261 data_time: 0.110268 memory: 3324 loss_kpt: 0.161711 acc_pose: 0.743529 loss: 0.161711 2022/09/20 01:01:55 - mmengine - INFO - Epoch(train) [70][150/293] lr: 5.000000e-04 eta: 11:28:29 time: 0.926349 data_time: 0.128326 memory: 3324 loss_kpt: 0.159478 acc_pose: 0.707650 loss: 0.159478 2022/09/20 01:02:37 - mmengine - INFO - Epoch(train) [70][200/293] lr: 5.000000e-04 eta: 11:27:21 time: 0.828963 data_time: 0.373650 memory: 3324 loss_kpt: 0.159028 acc_pose: 0.752880 loss: 0.159028 2022/09/20 01:03:16 - mmengine - INFO - Epoch(train) [70][250/293] lr: 5.000000e-04 eta: 11:26:08 time: 0.774025 data_time: 0.095257 memory: 3324 loss_kpt: 0.162234 acc_pose: 0.695758 loss: 0.162234 2022/09/20 01:03:53 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:03:53 - mmengine - INFO - Saving checkpoint at 70 epochs 2022/09/20 01:04:55 - mmengine - INFO - Epoch(val) [70][50/407] eta: 0:06:55 time: 1.165059 data_time: 1.123954 memory: 3324 2022/09/20 01:05:54 - mmengine - INFO - Epoch(val) [70][100/407] eta: 0:06:00 time: 1.174095 data_time: 1.129108 memory: 400 2022/09/20 01:06:52 - mmengine - INFO - Epoch(val) [70][150/407] eta: 0:05:01 time: 1.174659 data_time: 1.120931 memory: 400 2022/09/20 01:07:51 - mmengine - INFO - Epoch(val) [70][200/407] eta: 0:04:01 time: 1.166094 data_time: 1.100561 memory: 400 2022/09/20 01:08:50 - mmengine - INFO - Epoch(val) [70][250/407] eta: 0:03:05 time: 1.182367 data_time: 1.110513 memory: 400 2022/09/20 01:09:47 - mmengine - INFO - Epoch(val) [70][300/407] eta: 0:02:02 time: 1.142639 data_time: 1.095693 memory: 400 2022/09/20 01:10:47 - mmengine - INFO - Epoch(val) [70][350/407] eta: 0:01:08 time: 1.195765 data_time: 1.134686 memory: 400 2022/09/20 01:11:45 - mmengine - INFO - Epoch(val) [70][400/407] eta: 0:00:08 time: 1.166142 data_time: 1.116085 memory: 400 2022/09/20 01:12:41 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 01:13:00 - mmengine - INFO - Epoch(val) [70][407/407] coco/AP: 0.569959 coco/AP .5: 0.834368 coco/AP .75: 0.636671 coco/AP (M): 0.539435 coco/AP (L): 0.625243 coco/AR: 0.629723 coco/AR .5: 0.880038 coco/AR .75: 0.693325 coco/AR (M): 0.587462 coco/AR (L): 0.689223 2022/09/20 01:13:00 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_60.pth is removed 2022/09/20 01:13:02 - mmengine - INFO - The best checkpoint with 0.5700 coco/AP at 70 epoch is saved to best_coco/AP_epoch_70.pth. 2022/09/20 01:14:14 - mmengine - INFO - Epoch(train) [71][50/293] lr: 5.000000e-04 eta: 11:23:53 time: 1.437869 data_time: 0.258272 memory: 3324 loss_kpt: 0.162287 acc_pose: 0.759651 loss: 0.162287 2022/09/20 01:14:59 - mmengine - INFO - Epoch(train) [71][100/293] lr: 5.000000e-04 eta: 11:22:52 time: 0.895911 data_time: 0.104544 memory: 3324 loss_kpt: 0.158327 acc_pose: 0.670061 loss: 0.158327 2022/09/20 01:15:36 - mmengine - INFO - Epoch(train) [71][150/293] lr: 5.000000e-04 eta: 11:21:37 time: 0.746240 data_time: 0.162603 memory: 3324 loss_kpt: 0.159265 acc_pose: 0.708768 loss: 0.159265 2022/09/20 01:16:18 - mmengine - INFO - Epoch(train) [71][200/293] lr: 5.000000e-04 eta: 11:20:30 time: 0.831746 data_time: 0.096121 memory: 3324 loss_kpt: 0.156049 acc_pose: 0.728167 loss: 0.156049 2022/09/20 01:16:46 - mmengine - INFO - Epoch(train) [71][250/293] lr: 5.000000e-04 eta: 11:18:58 time: 0.568100 data_time: 0.140384 memory: 3324 loss_kpt: 0.157526 acc_pose: 0.657375 loss: 0.157526 2022/09/20 01:17:16 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:17:16 - mmengine - INFO - Saving checkpoint at 71 epochs 2022/09/20 01:17:47 - mmengine - INFO - Epoch(train) [72][50/293] lr: 5.000000e-04 eta: 11:15:19 time: 0.575416 data_time: 0.148458 memory: 3324 loss_kpt: 0.155817 acc_pose: 0.701836 loss: 0.155817 2022/09/20 01:18:20 - mmengine - INFO - Epoch(train) [72][100/293] lr: 5.000000e-04 eta: 11:13:56 time: 0.648220 data_time: 0.098100 memory: 3324 loss_kpt: 0.158831 acc_pose: 0.748028 loss: 0.158831 2022/09/20 01:19:33 - mmengine - INFO - Epoch(train) [72][150/293] lr: 5.000000e-04 eta: 11:13:52 time: 1.472632 data_time: 0.113603 memory: 3324 loss_kpt: 0.157980 acc_pose: 0.770834 loss: 0.157980 2022/09/20 01:20:37 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:20:45 - mmengine - INFO - Epoch(train) [72][200/293] lr: 5.000000e-04 eta: 11:13:45 time: 1.440316 data_time: 0.132201 memory: 3324 loss_kpt: 0.157490 acc_pose: 0.681275 loss: 0.157490 2022/09/20 01:21:53 - mmengine - INFO - Epoch(train) [72][250/293] lr: 5.000000e-04 eta: 11:13:29 time: 1.349410 data_time: 0.272700 memory: 3324 loss_kpt: 0.156311 acc_pose: 0.708891 loss: 0.156311 2022/09/20 01:22:42 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:22:43 - mmengine - INFO - Saving checkpoint at 72 epochs 2022/09/20 01:23:34 - mmengine - INFO - Epoch(train) [73][50/293] lr: 5.000000e-04 eta: 11:10:32 time: 0.972582 data_time: 0.183379 memory: 3324 loss_kpt: 0.157510 acc_pose: 0.650496 loss: 0.157510 2022/09/20 01:24:15 - mmengine - INFO - Epoch(train) [73][100/293] lr: 5.000000e-04 eta: 11:09:25 time: 0.813847 data_time: 0.170936 memory: 3324 loss_kpt: 0.156582 acc_pose: 0.685684 loss: 0.156582 2022/09/20 01:25:08 - mmengine - INFO - Epoch(train) [73][150/293] lr: 5.000000e-04 eta: 11:08:42 time: 1.071709 data_time: 0.117914 memory: 3324 loss_kpt: 0.158011 acc_pose: 0.664893 loss: 0.158011 2022/09/20 01:26:01 - mmengine - INFO - Epoch(train) [73][200/293] lr: 5.000000e-04 eta: 11:07:59 time: 1.064560 data_time: 0.106274 memory: 3324 loss_kpt: 0.157304 acc_pose: 0.697315 loss: 0.157304 2022/09/20 01:26:43 - mmengine - INFO - Epoch(train) [73][250/293] lr: 5.000000e-04 eta: 11:06:54 time: 0.837993 data_time: 0.099328 memory: 3324 loss_kpt: 0.160673 acc_pose: 0.746707 loss: 0.160673 2022/09/20 01:27:12 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:27:12 - mmengine - INFO - Saving checkpoint at 73 epochs 2022/09/20 01:27:58 - mmengine - INFO - Epoch(train) [74][50/293] lr: 5.000000e-04 eta: 11:03:49 time: 0.858011 data_time: 0.112482 memory: 3324 loss_kpt: 0.157443 acc_pose: 0.690150 loss: 0.157443 2022/09/20 01:28:36 - mmengine - INFO - Epoch(train) [74][100/293] lr: 5.000000e-04 eta: 11:02:37 time: 0.762137 data_time: 0.103874 memory: 3324 loss_kpt: 0.157638 acc_pose: 0.720544 loss: 0.157638 2022/09/20 01:29:12 - mmengine - INFO - Epoch(train) [74][150/293] lr: 5.000000e-04 eta: 11:01:23 time: 0.723462 data_time: 0.116725 memory: 3324 loss_kpt: 0.156036 acc_pose: 0.674839 loss: 0.156036 2022/09/20 01:29:45 - mmengine - INFO - Epoch(train) [74][200/293] lr: 5.000000e-04 eta: 11:00:03 time: 0.662676 data_time: 0.112783 memory: 3324 loss_kpt: 0.160654 acc_pose: 0.722377 loss: 0.160654 2022/09/20 01:30:20 - mmengine - INFO - Epoch(train) [74][250/293] lr: 5.000000e-04 eta: 10:58:46 time: 0.693056 data_time: 0.101416 memory: 3324 loss_kpt: 0.160949 acc_pose: 0.747695 loss: 0.160949 2022/09/20 01:30:48 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:30:48 - mmengine - INFO - Saving checkpoint at 74 epochs 2022/09/20 01:31:22 - mmengine - INFO - Epoch(train) [75][50/293] lr: 5.000000e-04 eta: 10:55:23 time: 0.634780 data_time: 0.163240 memory: 3324 loss_kpt: 0.157606 acc_pose: 0.667249 loss: 0.157606 2022/09/20 01:31:51 - mmengine - INFO - Epoch(train) [75][100/293] lr: 5.000000e-04 eta: 10:53:56 time: 0.575919 data_time: 0.103167 memory: 3324 loss_kpt: 0.158288 acc_pose: 0.752274 loss: 0.158288 2022/09/20 01:32:29 - mmengine - INFO - Epoch(train) [75][150/293] lr: 5.000000e-04 eta: 10:52:46 time: 0.762324 data_time: 0.101974 memory: 3324 loss_kpt: 0.155876 acc_pose: 0.737710 loss: 0.155876 2022/09/20 01:33:03 - mmengine - INFO - Epoch(train) [75][200/293] lr: 5.000000e-04 eta: 10:51:29 time: 0.686926 data_time: 0.098611 memory: 3324 loss_kpt: 0.157756 acc_pose: 0.694687 loss: 0.157756 2022/09/20 01:33:41 - mmengine - INFO - Epoch(train) [75][250/293] lr: 5.000000e-04 eta: 10:50:20 time: 0.759548 data_time: 0.102303 memory: 3324 loss_kpt: 0.157972 acc_pose: 0.662199 loss: 0.157972 2022/09/20 01:34:09 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:34:09 - mmengine - INFO - Saving checkpoint at 75 epochs 2022/09/20 01:34:30 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:34:45 - mmengine - INFO - Epoch(train) [76][50/293] lr: 5.000000e-04 eta: 10:47:04 time: 0.676445 data_time: 0.147694 memory: 3324 loss_kpt: 0.154263 acc_pose: 0.718140 loss: 0.154263 2022/09/20 01:35:33 - mmengine - INFO - Epoch(train) [76][100/293] lr: 5.000000e-04 eta: 10:46:14 time: 0.970362 data_time: 0.236529 memory: 3324 loss_kpt: 0.162178 acc_pose: 0.676306 loss: 0.162178 2022/09/20 01:36:26 - mmengine - INFO - Epoch(train) [76][150/293] lr: 5.000000e-04 eta: 10:45:31 time: 1.047582 data_time: 0.174312 memory: 3324 loss_kpt: 0.157485 acc_pose: 0.675851 loss: 0.157485 2022/09/20 01:37:21 - mmengine - INFO - Epoch(train) [76][200/293] lr: 5.000000e-04 eta: 10:44:53 time: 1.109585 data_time: 0.096884 memory: 3324 loss_kpt: 0.156686 acc_pose: 0.711764 loss: 0.156686 2022/09/20 01:38:08 - mmengine - INFO - Epoch(train) [76][250/293] lr: 5.000000e-04 eta: 10:43:59 time: 0.930346 data_time: 0.115479 memory: 3324 loss_kpt: 0.157320 acc_pose: 0.716223 loss: 0.157320 2022/09/20 01:38:40 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:38:40 - mmengine - INFO - Saving checkpoint at 76 epochs 2022/09/20 01:39:35 - mmengine - INFO - Epoch(train) [77][50/293] lr: 5.000000e-04 eta: 10:41:20 time: 1.058350 data_time: 0.545863 memory: 3324 loss_kpt: 0.158456 acc_pose: 0.701892 loss: 0.158456 2022/09/20 01:40:24 - mmengine - INFO - Epoch(train) [77][100/293] lr: 5.000000e-04 eta: 10:40:30 time: 0.971994 data_time: 0.109958 memory: 3324 loss_kpt: 0.161444 acc_pose: 0.610992 loss: 0.161444 2022/09/20 01:41:04 - mmengine - INFO - Epoch(train) [77][150/293] lr: 5.000000e-04 eta: 10:39:26 time: 0.806246 data_time: 0.354840 memory: 3324 loss_kpt: 0.159847 acc_pose: 0.704661 loss: 0.159847 2022/09/20 01:41:49 - mmengine - INFO - Epoch(train) [77][200/293] lr: 5.000000e-04 eta: 10:38:30 time: 0.904009 data_time: 0.280819 memory: 3324 loss_kpt: 0.157896 acc_pose: 0.669596 loss: 0.157896 2022/09/20 01:42:27 - mmengine - INFO - Epoch(train) [77][250/293] lr: 5.000000e-04 eta: 10:37:22 time: 0.758587 data_time: 0.095454 memory: 3324 loss_kpt: 0.159129 acc_pose: 0.697320 loss: 0.159129 2022/09/20 01:43:01 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:43:01 - mmengine - INFO - Saving checkpoint at 77 epochs 2022/09/20 01:43:49 - mmengine - INFO - Epoch(train) [78][50/293] lr: 5.000000e-04 eta: 10:34:31 time: 0.895540 data_time: 0.500786 memory: 3324 loss_kpt: 0.160859 acc_pose: 0.751028 loss: 0.160859 2022/09/20 01:44:29 - mmengine - INFO - Epoch(train) [78][100/293] lr: 5.000000e-04 eta: 10:33:27 time: 0.810593 data_time: 0.119595 memory: 3324 loss_kpt: 0.156426 acc_pose: 0.686730 loss: 0.156426 2022/09/20 01:45:12 - mmengine - INFO - Epoch(train) [78][150/293] lr: 5.000000e-04 eta: 10:32:27 time: 0.846061 data_time: 0.282255 memory: 3324 loss_kpt: 0.159239 acc_pose: 0.720962 loss: 0.159239 2022/09/20 01:45:47 - mmengine - INFO - Epoch(train) [78][200/293] lr: 5.000000e-04 eta: 10:31:15 time: 0.701371 data_time: 0.097994 memory: 3324 loss_kpt: 0.159787 acc_pose: 0.672236 loss: 0.159787 2022/09/20 01:46:16 - mmengine - INFO - Epoch(train) [78][250/293] lr: 5.000000e-04 eta: 10:29:54 time: 0.596573 data_time: 0.096330 memory: 3324 loss_kpt: 0.158387 acc_pose: 0.738754 loss: 0.158387 2022/09/20 01:46:55 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:46:55 - mmengine - INFO - Saving checkpoint at 78 epochs 2022/09/20 01:47:35 - mmengine - INFO - Epoch(train) [79][50/293] lr: 5.000000e-04 eta: 10:26:53 time: 0.748054 data_time: 0.178966 memory: 3324 loss_kpt: 0.155364 acc_pose: 0.682184 loss: 0.155364 2022/09/20 01:48:20 - mmengine - INFO - Epoch(train) [79][100/293] lr: 5.000000e-04 eta: 10:25:58 time: 0.898586 data_time: 0.103325 memory: 3324 loss_kpt: 0.156692 acc_pose: 0.683033 loss: 0.156692 2022/09/20 01:49:04 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:49:07 - mmengine - INFO - Epoch(train) [79][150/293] lr: 5.000000e-04 eta: 10:25:07 time: 0.941508 data_time: 0.132788 memory: 3324 loss_kpt: 0.158986 acc_pose: 0.711077 loss: 0.158986 2022/09/20 01:49:42 - mmengine - INFO - Epoch(train) [79][200/293] lr: 5.000000e-04 eta: 10:23:54 time: 0.688035 data_time: 0.105881 memory: 3324 loss_kpt: 0.158040 acc_pose: 0.739795 loss: 0.158040 2022/09/20 01:50:21 - mmengine - INFO - Epoch(train) [79][250/293] lr: 5.000000e-04 eta: 10:22:49 time: 0.781075 data_time: 0.152529 memory: 3324 loss_kpt: 0.156282 acc_pose: 0.700815 loss: 0.156282 2022/09/20 01:50:41 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:50:41 - mmengine - INFO - Saving checkpoint at 79 epochs 2022/09/20 01:51:32 - mmengine - INFO - Epoch(train) [80][50/293] lr: 5.000000e-04 eta: 10:20:10 time: 0.978663 data_time: 0.220877 memory: 3324 loss_kpt: 0.156918 acc_pose: 0.752552 loss: 0.156918 2022/09/20 01:52:45 - mmengine - INFO - Epoch(train) [80][100/293] lr: 5.000000e-04 eta: 10:20:01 time: 1.442623 data_time: 0.096571 memory: 3324 loss_kpt: 0.156560 acc_pose: 0.693960 loss: 0.156560 2022/09/20 01:53:45 - mmengine - INFO - Epoch(train) [80][150/293] lr: 5.000000e-04 eta: 10:19:32 time: 1.212945 data_time: 0.102474 memory: 3324 loss_kpt: 0.157884 acc_pose: 0.670695 loss: 0.157884 2022/09/20 01:54:37 - mmengine - INFO - Epoch(train) [80][200/293] lr: 5.000000e-04 eta: 10:18:48 time: 1.032826 data_time: 0.368277 memory: 3324 loss_kpt: 0.156832 acc_pose: 0.706302 loss: 0.156832 2022/09/20 01:55:04 - mmengine - INFO - Epoch(train) [80][250/293] lr: 5.000000e-04 eta: 10:17:24 time: 0.540598 data_time: 0.095239 memory: 3324 loss_kpt: 0.155568 acc_pose: 0.671867 loss: 0.155568 2022/09/20 01:55:37 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 01:55:37 - mmengine - INFO - Saving checkpoint at 80 epochs 2022/09/20 01:56:39 - mmengine - INFO - Epoch(val) [80][50/407] eta: 0:06:59 time: 1.175952 data_time: 1.127371 memory: 3324 2022/09/20 01:57:37 - mmengine - INFO - Epoch(val) [80][100/407] eta: 0:05:53 time: 1.151114 data_time: 1.097960 memory: 400 2022/09/20 01:58:36 - mmengine - INFO - Epoch(val) [80][150/407] eta: 0:05:02 time: 1.176624 data_time: 1.134133 memory: 400 2022/09/20 01:59:35 - mmengine - INFO - Epoch(val) [80][200/407] eta: 0:04:04 time: 1.181615 data_time: 1.133036 memory: 400 2022/09/20 02:00:32 - mmengine - INFO - Epoch(val) [80][250/407] eta: 0:02:59 time: 1.146178 data_time: 1.086473 memory: 400 2022/09/20 02:01:31 - mmengine - INFO - Epoch(val) [80][300/407] eta: 0:02:05 time: 1.169469 data_time: 1.119234 memory: 400 2022/09/20 02:02:28 - mmengine - INFO - Epoch(val) [80][350/407] eta: 0:01:05 time: 1.144982 data_time: 1.092592 memory: 400 2022/09/20 02:03:26 - mmengine - INFO - Epoch(val) [80][400/407] eta: 0:00:08 time: 1.159145 data_time: 1.093466 memory: 400 2022/09/20 02:04:22 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 02:04:40 - mmengine - INFO - Epoch(val) [80][407/407] coco/AP: 0.575316 coco/AP .5: 0.836368 coco/AP .75: 0.641890 coco/AP (M): 0.543390 coco/AP (L): 0.631952 coco/AR: 0.635280 coco/AR .5: 0.884603 coco/AR .75: 0.699465 coco/AR (M): 0.591833 coco/AR (L): 0.696135 2022/09/20 02:04:40 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_70.pth is removed 2022/09/20 02:04:42 - mmengine - INFO - The best checkpoint with 0.5753 coco/AP at 80 epoch is saved to best_coco/AP_epoch_80.pth. 2022/09/20 02:06:07 - mmengine - INFO - Epoch(train) [81][50/293] lr: 5.000000e-04 eta: 10:15:45 time: 1.698326 data_time: 0.497219 memory: 3324 loss_kpt: 0.158672 acc_pose: 0.736964 loss: 0.158672 2022/09/20 02:06:54 - mmengine - INFO - Epoch(train) [81][100/293] lr: 5.000000e-04 eta: 10:14:53 time: 0.927971 data_time: 0.095379 memory: 3324 loss_kpt: 0.155891 acc_pose: 0.662514 loss: 0.155891 2022/09/20 02:07:31 - mmengine - INFO - Epoch(train) [81][150/293] lr: 5.000000e-04 eta: 10:13:47 time: 0.751295 data_time: 0.091894 memory: 3324 loss_kpt: 0.154647 acc_pose: 0.747702 loss: 0.154647 2022/09/20 02:08:30 - mmengine - INFO - Epoch(train) [81][200/293] lr: 5.000000e-04 eta: 10:13:14 time: 1.167364 data_time: 0.097390 memory: 3324 loss_kpt: 0.154836 acc_pose: 0.723106 loss: 0.154836 2022/09/20 02:09:21 - mmengine - INFO - Epoch(train) [81][250/293] lr: 5.000000e-04 eta: 10:12:30 time: 1.018495 data_time: 0.152907 memory: 3324 loss_kpt: 0.157875 acc_pose: 0.721354 loss: 0.157875 2022/09/20 02:10:07 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:10:07 - mmengine - INFO - Saving checkpoint at 81 epochs 2022/09/20 02:10:45 - mmengine - INFO - Epoch(train) [82][50/293] lr: 5.000000e-04 eta: 10:09:32 time: 0.710144 data_time: 0.300863 memory: 3324 loss_kpt: 0.153933 acc_pose: 0.682219 loss: 0.153933 2022/09/20 02:11:17 - mmengine - INFO - Epoch(train) [82][100/293] lr: 5.000000e-04 eta: 10:08:17 time: 0.631396 data_time: 0.182319 memory: 3324 loss_kpt: 0.154112 acc_pose: 0.678075 loss: 0.154112 2022/09/20 02:11:43 - mmengine - INFO - Epoch(train) [82][150/293] lr: 5.000000e-04 eta: 10:06:54 time: 0.524760 data_time: 0.095585 memory: 3324 loss_kpt: 0.155129 acc_pose: 0.673690 loss: 0.155129 2022/09/20 02:12:24 - mmengine - INFO - Epoch(train) [82][200/293] lr: 5.000000e-04 eta: 10:05:54 time: 0.823922 data_time: 0.097859 memory: 3324 loss_kpt: 0.159447 acc_pose: 0.709004 loss: 0.159447 2022/09/20 02:13:16 - mmengine - INFO - Epoch(train) [82][250/293] lr: 5.000000e-04 eta: 10:05:11 time: 1.033227 data_time: 0.279547 memory: 3324 loss_kpt: 0.160052 acc_pose: 0.712006 loss: 0.160052 2022/09/20 02:13:33 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:13:45 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:13:45 - mmengine - INFO - Saving checkpoint at 82 epochs 2022/09/20 02:14:18 - mmengine - INFO - Epoch(train) [83][50/293] lr: 5.000000e-04 eta: 10:02:09 time: 0.610927 data_time: 0.120241 memory: 3324 loss_kpt: 0.156844 acc_pose: 0.702421 loss: 0.156844 2022/09/20 02:14:46 - mmengine - INFO - Epoch(train) [83][100/293] lr: 5.000000e-04 eta: 10:00:49 time: 0.564689 data_time: 0.117971 memory: 3324 loss_kpt: 0.155662 acc_pose: 0.733175 loss: 0.155662 2022/09/20 02:15:29 - mmengine - INFO - Epoch(train) [83][150/293] lr: 5.000000e-04 eta: 9:59:53 time: 0.854585 data_time: 0.092870 memory: 3324 loss_kpt: 0.159185 acc_pose: 0.648264 loss: 0.159185 2022/09/20 02:16:07 - mmengine - INFO - Epoch(train) [83][200/293] lr: 5.000000e-04 eta: 9:58:49 time: 0.762938 data_time: 0.192734 memory: 3324 loss_kpt: 0.155561 acc_pose: 0.706818 loss: 0.155561 2022/09/20 02:16:55 - mmengine - INFO - Epoch(train) [83][250/293] lr: 5.000000e-04 eta: 9:58:00 time: 0.951210 data_time: 0.132950 memory: 3324 loss_kpt: 0.157630 acc_pose: 0.687709 loss: 0.157630 2022/09/20 02:17:36 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:17:36 - mmengine - INFO - Saving checkpoint at 83 epochs 2022/09/20 02:18:08 - mmengine - INFO - Epoch(train) [84][50/293] lr: 5.000000e-04 eta: 9:54:59 time: 0.594933 data_time: 0.181856 memory: 3324 loss_kpt: 0.155604 acc_pose: 0.760910 loss: 0.155604 2022/09/20 02:19:00 - mmengine - INFO - Epoch(train) [84][100/293] lr: 5.000000e-04 eta: 9:54:18 time: 1.043735 data_time: 0.281222 memory: 3324 loss_kpt: 0.155219 acc_pose: 0.703748 loss: 0.155219 2022/09/20 02:19:52 - mmengine - INFO - Epoch(train) [84][150/293] lr: 5.000000e-04 eta: 9:53:35 time: 1.034479 data_time: 0.298819 memory: 3324 loss_kpt: 0.155722 acc_pose: 0.750106 loss: 0.155722 2022/09/20 02:20:28 - mmengine - INFO - Epoch(train) [84][200/293] lr: 5.000000e-04 eta: 9:52:29 time: 0.717696 data_time: 0.093032 memory: 3324 loss_kpt: 0.154749 acc_pose: 0.682426 loss: 0.154749 2022/09/20 02:21:08 - mmengine - INFO - Epoch(train) [84][250/293] lr: 5.000000e-04 eta: 9:51:28 time: 0.798020 data_time: 0.244998 memory: 3324 loss_kpt: 0.159553 acc_pose: 0.693691 loss: 0.159553 2022/09/20 02:21:34 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:21:34 - mmengine - INFO - Saving checkpoint at 84 epochs 2022/09/20 02:22:02 - mmengine - INFO - Epoch(train) [85][50/293] lr: 5.000000e-04 eta: 9:48:24 time: 0.518613 data_time: 0.113631 memory: 3324 loss_kpt: 0.155468 acc_pose: 0.698144 loss: 0.155468 2022/09/20 02:22:46 - mmengine - INFO - Epoch(train) [85][100/293] lr: 5.000000e-04 eta: 9:47:30 time: 0.873591 data_time: 0.102424 memory: 3324 loss_kpt: 0.155631 acc_pose: 0.676932 loss: 0.155631 2022/09/20 02:23:38 - mmengine - INFO - Epoch(train) [85][150/293] lr: 5.000000e-04 eta: 9:46:48 time: 1.031094 data_time: 0.092639 memory: 3324 loss_kpt: 0.155615 acc_pose: 0.688581 loss: 0.155615 2022/09/20 02:24:10 - mmengine - INFO - Epoch(train) [85][200/293] lr: 5.000000e-04 eta: 9:45:37 time: 0.647775 data_time: 0.093807 memory: 3324 loss_kpt: 0.155520 acc_pose: 0.727741 loss: 0.155520 2022/09/20 02:24:48 - mmengine - INFO - Epoch(train) [85][250/293] lr: 5.000000e-04 eta: 9:44:35 time: 0.761459 data_time: 0.174891 memory: 3324 loss_kpt: 0.157903 acc_pose: 0.679051 loss: 0.157903 2022/09/20 02:25:13 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:25:13 - mmengine - INFO - Saving checkpoint at 85 epochs 2022/09/20 02:25:51 - mmengine - INFO - Epoch(train) [86][50/293] lr: 5.000000e-04 eta: 9:41:47 time: 0.708804 data_time: 0.155710 memory: 3324 loss_kpt: 0.154217 acc_pose: 0.662595 loss: 0.154217 2022/09/20 02:26:27 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:26:37 - mmengine - INFO - Epoch(train) [86][100/293] lr: 5.000000e-04 eta: 9:40:57 time: 0.922428 data_time: 0.218764 memory: 3324 loss_kpt: 0.154270 acc_pose: 0.730519 loss: 0.154270 2022/09/20 02:27:17 - mmengine - INFO - Epoch(train) [86][150/293] lr: 5.000000e-04 eta: 9:39:59 time: 0.802383 data_time: 0.100640 memory: 3324 loss_kpt: 0.157037 acc_pose: 0.696537 loss: 0.157037 2022/09/20 02:27:55 - mmengine - INFO - Epoch(train) [86][200/293] lr: 5.000000e-04 eta: 9:38:57 time: 0.757814 data_time: 0.093250 memory: 3324 loss_kpt: 0.154251 acc_pose: 0.700666 loss: 0.154251 2022/09/20 02:28:25 - mmengine - INFO - Epoch(train) [86][250/293] lr: 5.000000e-04 eta: 9:37:42 time: 0.587109 data_time: 0.095152 memory: 3324 loss_kpt: 0.155553 acc_pose: 0.632348 loss: 0.155553 2022/09/20 02:29:01 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:29:01 - mmengine - INFO - Saving checkpoint at 86 epochs 2022/09/20 02:29:42 - mmengine - INFO - Epoch(train) [87][50/293] lr: 5.000000e-04 eta: 9:35:01 time: 0.758929 data_time: 0.154815 memory: 3324 loss_kpt: 0.157990 acc_pose: 0.685093 loss: 0.157990 2022/09/20 02:30:21 - mmengine - INFO - Epoch(train) [87][100/293] lr: 5.000000e-04 eta: 9:34:02 time: 0.785280 data_time: 0.086465 memory: 3324 loss_kpt: 0.152610 acc_pose: 0.701469 loss: 0.152610 2022/09/20 02:30:54 - mmengine - INFO - Epoch(train) [87][150/293] lr: 5.000000e-04 eta: 9:32:53 time: 0.658517 data_time: 0.092897 memory: 3324 loss_kpt: 0.157382 acc_pose: 0.718501 loss: 0.157382 2022/09/20 02:31:18 - mmengine - INFO - Epoch(train) [87][200/293] lr: 5.000000e-04 eta: 9:31:33 time: 0.489120 data_time: 0.133615 memory: 3324 loss_kpt: 0.154066 acc_pose: 0.661575 loss: 0.154066 2022/09/20 02:32:06 - mmengine - INFO - Epoch(train) [87][250/293] lr: 5.000000e-04 eta: 9:30:46 time: 0.955150 data_time: 0.091572 memory: 3324 loss_kpt: 0.155883 acc_pose: 0.700120 loss: 0.155883 2022/09/20 02:32:39 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:32:39 - mmengine - INFO - Saving checkpoint at 87 epochs 2022/09/20 02:33:31 - mmengine - INFO - Epoch(train) [88][50/293] lr: 5.000000e-04 eta: 9:28:23 time: 0.991400 data_time: 0.142375 memory: 3324 loss_kpt: 0.157115 acc_pose: 0.753485 loss: 0.157115 2022/09/20 02:34:05 - mmengine - INFO - Epoch(train) [88][100/293] lr: 5.000000e-04 eta: 9:27:17 time: 0.683841 data_time: 0.092103 memory: 3324 loss_kpt: 0.156341 acc_pose: 0.699275 loss: 0.156341 2022/09/20 02:34:40 - mmengine - INFO - Epoch(train) [88][150/293] lr: 5.000000e-04 eta: 9:26:13 time: 0.700045 data_time: 0.105368 memory: 3324 loss_kpt: 0.156179 acc_pose: 0.673266 loss: 0.156179 2022/09/20 02:35:16 - mmengine - INFO - Epoch(train) [88][200/293] lr: 5.000000e-04 eta: 9:25:09 time: 0.710342 data_time: 0.212613 memory: 3324 loss_kpt: 0.152506 acc_pose: 0.748317 loss: 0.152506 2022/09/20 02:35:58 - mmengine - INFO - Epoch(train) [88][250/293] lr: 5.000000e-04 eta: 9:24:15 time: 0.853514 data_time: 0.302810 memory: 3324 loss_kpt: 0.153060 acc_pose: 0.735467 loss: 0.153060 2022/09/20 02:36:35 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:36:35 - mmengine - INFO - Saving checkpoint at 88 epochs 2022/09/20 02:37:12 - mmengine - INFO - Epoch(train) [89][50/293] lr: 5.000000e-04 eta: 9:21:32 time: 0.680723 data_time: 0.213238 memory: 3324 loss_kpt: 0.155563 acc_pose: 0.712547 loss: 0.155563 2022/09/20 02:37:50 - mmengine - INFO - Epoch(train) [89][100/293] lr: 5.000000e-04 eta: 9:20:33 time: 0.763740 data_time: 0.167922 memory: 3324 loss_kpt: 0.154912 acc_pose: 0.644960 loss: 0.154912 2022/09/20 02:38:31 - mmengine - INFO - Epoch(train) [89][150/293] lr: 5.000000e-04 eta: 9:19:38 time: 0.826367 data_time: 0.178221 memory: 3324 loss_kpt: 0.155480 acc_pose: 0.726482 loss: 0.155480 2022/09/20 02:39:09 - mmengine - INFO - Epoch(train) [89][200/293] lr: 5.000000e-04 eta: 9:18:37 time: 0.748676 data_time: 0.100079 memory: 3324 loss_kpt: 0.153872 acc_pose: 0.692388 loss: 0.153872 2022/09/20 02:39:18 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:39:43 - mmengine - INFO - Epoch(train) [89][250/293] lr: 5.000000e-04 eta: 9:17:33 time: 0.694596 data_time: 0.109725 memory: 3324 loss_kpt: 0.159188 acc_pose: 0.722749 loss: 0.159188 2022/09/20 02:40:05 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:40:05 - mmengine - INFO - Saving checkpoint at 89 epochs 2022/09/20 02:40:32 - mmengine - INFO - Epoch(train) [90][50/293] lr: 5.000000e-04 eta: 9:14:39 time: 0.484382 data_time: 0.159969 memory: 3324 loss_kpt: 0.154528 acc_pose: 0.684586 loss: 0.154528 2022/09/20 02:40:59 - mmengine - INFO - Epoch(train) [90][100/293] lr: 5.000000e-04 eta: 9:13:25 time: 0.536640 data_time: 0.139608 memory: 3324 loss_kpt: 0.155956 acc_pose: 0.714722 loss: 0.155956 2022/09/20 02:41:42 - mmengine - INFO - Epoch(train) [90][150/293] lr: 5.000000e-04 eta: 9:12:34 time: 0.872332 data_time: 0.098266 memory: 3324 loss_kpt: 0.159098 acc_pose: 0.694374 loss: 0.159098 2022/09/20 02:42:21 - mmengine - INFO - Epoch(train) [90][200/293] lr: 5.000000e-04 eta: 9:11:36 time: 0.775734 data_time: 0.259040 memory: 3324 loss_kpt: 0.155505 acc_pose: 0.710600 loss: 0.155505 2022/09/20 02:43:00 - mmengine - INFO - Epoch(train) [90][250/293] lr: 5.000000e-04 eta: 9:10:38 time: 0.770351 data_time: 0.299018 memory: 3324 loss_kpt: 0.155734 acc_pose: 0.669669 loss: 0.155734 2022/09/20 02:43:31 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:43:31 - mmengine - INFO - Saving checkpoint at 90 epochs 2022/09/20 02:44:34 - mmengine - INFO - Epoch(val) [90][50/407] eta: 0:07:04 time: 1.189437 data_time: 1.133920 memory: 3324 2022/09/20 02:45:32 - mmengine - INFO - Epoch(val) [90][100/407] eta: 0:05:55 time: 1.159056 data_time: 1.111436 memory: 400 2022/09/20 02:46:31 - mmengine - INFO - Epoch(val) [90][150/407] eta: 0:05:05 time: 1.187248 data_time: 1.127852 memory: 400 2022/09/20 02:47:29 - mmengine - INFO - Epoch(val) [90][200/407] eta: 0:03:59 time: 1.158931 data_time: 1.121375 memory: 400 2022/09/20 02:48:29 - mmengine - INFO - Epoch(val) [90][250/407] eta: 0:03:06 time: 1.189303 data_time: 1.141236 memory: 400 2022/09/20 02:49:28 - mmengine - INFO - Epoch(val) [90][300/407] eta: 0:02:06 time: 1.186454 data_time: 1.135763 memory: 400 2022/09/20 02:50:27 - mmengine - INFO - Epoch(val) [90][350/407] eta: 0:01:07 time: 1.181297 data_time: 1.130892 memory: 400 2022/09/20 02:51:26 - mmengine - INFO - Epoch(val) [90][400/407] eta: 0:00:08 time: 1.181827 data_time: 1.135409 memory: 400 2022/09/20 02:52:22 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 02:52:40 - mmengine - INFO - Epoch(val) [90][407/407] coco/AP: 0.579177 coco/AP .5: 0.838672 coco/AP .75: 0.646455 coco/AP (M): 0.548606 coco/AP (L): 0.635751 coco/AR: 0.640302 coco/AR .5: 0.886492 coco/AR .75: 0.702613 coco/AR (M): 0.598634 coco/AR (L): 0.699368 2022/09/20 02:52:40 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_80.pth is removed 2022/09/20 02:52:42 - mmengine - INFO - The best checkpoint with 0.5792 coco/AP at 90 epoch is saved to best_coco/AP_epoch_90.pth. 2022/09/20 02:54:08 - mmengine - INFO - Epoch(train) [91][50/293] lr: 5.000000e-04 eta: 9:09:08 time: 1.710273 data_time: 0.317971 memory: 3324 loss_kpt: 0.154219 acc_pose: 0.730985 loss: 0.154219 2022/09/20 02:54:58 - mmengine - INFO - Epoch(train) [91][100/293] lr: 5.000000e-04 eta: 9:08:26 time: 1.010541 data_time: 0.187933 memory: 3324 loss_kpt: 0.152883 acc_pose: 0.692356 loss: 0.152883 2022/09/20 02:55:34 - mmengine - INFO - Epoch(train) [91][150/293] lr: 5.000000e-04 eta: 9:07:25 time: 0.720491 data_time: 0.197750 memory: 3324 loss_kpt: 0.154332 acc_pose: 0.679390 loss: 0.154332 2022/09/20 02:56:15 - mmengine - INFO - Epoch(train) [91][200/293] lr: 5.000000e-04 eta: 9:06:29 time: 0.802612 data_time: 0.175690 memory: 3324 loss_kpt: 0.154989 acc_pose: 0.717268 loss: 0.154989 2022/09/20 02:56:56 - mmengine - INFO - Epoch(train) [91][250/293] lr: 5.000000e-04 eta: 9:05:34 time: 0.822272 data_time: 0.099702 memory: 3324 loss_kpt: 0.157766 acc_pose: 0.689007 loss: 0.157766 2022/09/20 02:57:21 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 02:57:21 - mmengine - INFO - Saving checkpoint at 91 epochs 2022/09/20 02:58:16 - mmengine - INFO - Epoch(train) [92][50/293] lr: 5.000000e-04 eta: 9:03:21 time: 1.038044 data_time: 0.138709 memory: 3324 loss_kpt: 0.157515 acc_pose: 0.727501 loss: 0.157515 2022/09/20 02:58:52 - mmengine - INFO - Epoch(train) [92][100/293] lr: 5.000000e-04 eta: 9:02:21 time: 0.731247 data_time: 0.145016 memory: 3324 loss_kpt: 0.156312 acc_pose: 0.718471 loss: 0.156312 2022/09/20 02:59:25 - mmengine - INFO - Epoch(train) [92][150/293] lr: 5.000000e-04 eta: 9:01:16 time: 0.656181 data_time: 0.107504 memory: 3324 loss_kpt: 0.154263 acc_pose: 0.695971 loss: 0.154263 2022/09/20 03:00:04 - mmengine - INFO - Epoch(train) [92][200/293] lr: 5.000000e-04 eta: 9:00:19 time: 0.785165 data_time: 0.106928 memory: 3324 loss_kpt: 0.159415 acc_pose: 0.739876 loss: 0.159415 2022/09/20 03:00:34 - mmengine - INFO - Epoch(train) [92][250/293] lr: 5.000000e-04 eta: 8:59:11 time: 0.592270 data_time: 0.173548 memory: 3324 loss_kpt: 0.155402 acc_pose: 0.731591 loss: 0.155402 2022/09/20 03:01:07 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 03:01:07 - mmengine - INFO - Saving checkpoint at 92 epochs 2022/09/20 03:01:38 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 03:01:43 - mmengine - INFO - Epoch(train) [93][50/293] lr: 5.000000e-04 eta: 8:56:36 time: 0.673901 data_time: 0.129473 memory: 3324 loss_kpt: 0.156702 acc_pose: 0.737849 loss: 0.156702 2022/09/20 03:02:36 - mmengine - INFO - Epoch(train) [93][100/293] lr: 5.000000e-04 eta: 8:55:57 time: 1.051553 data_time: 0.138883 memory: 3324 loss_kpt: 0.155901 acc_pose: 0.701863 loss: 0.155901 2022/09/20 03:03:11 - mmengine - INFO - Epoch(train) [93][150/293] lr: 5.000000e-04 eta: 8:54:55 time: 0.695917 data_time: 0.105539 memory: 3324 loss_kpt: 0.157226 acc_pose: 0.692818 loss: 0.157226 2022/09/20 03:03:37 - mmengine - INFO - Epoch(train) [93][200/293] lr: 5.000000e-04 eta: 8:53:42 time: 0.522453 data_time: 0.104789 memory: 3324 loss_kpt: 0.154861 acc_pose: 0.708911 loss: 0.154861 2022/09/20 03:04:19 - mmengine - INFO - Epoch(train) [93][250/293] lr: 5.000000e-04 eta: 8:52:50 time: 0.835569 data_time: 0.288008 memory: 3324 loss_kpt: 0.157306 acc_pose: 0.682773 loss: 0.157306 2022/09/20 03:05:08 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 03:05:08 - mmengine - INFO - Saving checkpoint at 93 epochs 2022/09/20 03:07:56 - mmengine - INFO - Epoch(train) [94][50/293] lr: 5.000000e-04 eta: 8:52:41 time: 2.977818 data_time: 0.834895 memory: 3324 loss_kpt: 0.155898 acc_pose: 0.712129 loss: 0.155898 2022/09/20 03:10:51 - mmengine - INFO - Epoch(train) [94][100/293] lr: 5.000000e-04 eta: 8:54:35 time: 3.494550 data_time: 1.145288 memory: 3324 loss_kpt: 0.159000 acc_pose: 0.623637 loss: 0.159000 2022/09/20 03:13:26 - mmengine - INFO - Epoch(train) [94][150/293] lr: 5.000000e-04 eta: 8:56:02 time: 3.097752 data_time: 0.842875 memory: 3324 loss_kpt: 0.154984 acc_pose: 0.744190 loss: 0.154984 2022/09/20 03:15:50 - mmengine - INFO - Epoch(train) [94][200/293] lr: 5.000000e-04 eta: 8:57:15 time: 2.879257 data_time: 0.955042 memory: 3324 loss_kpt: 0.155633 acc_pose: 0.753973 loss: 0.155633 2022/09/20 03:18:15 - mmengine - INFO - Epoch(train) [94][250/293] lr: 5.000000e-04 eta: 8:58:30 time: 2.911443 data_time: 0.996343 memory: 3324 loss_kpt: 0.156833 acc_pose: 0.741559 loss: 0.156833 2022/09/20 03:20:21 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 03:20:21 - mmengine - INFO - Saving checkpoint at 94 epochs 2022/09/20 03:23:21 - mmengine - INFO - Epoch(train) [95][50/293] lr: 5.000000e-04 eta: 8:58:32 time: 3.243567 data_time: 0.927945 memory: 3324 loss_kpt: 0.156843 acc_pose: 0.741518 loss: 0.156843 2022/09/20 03:25:45 - mmengine - INFO - Epoch(train) [95][100/293] lr: 5.000000e-04 eta: 8:59:42 time: 2.872323 data_time: 0.817591 memory: 3324 loss_kpt: 0.155184 acc_pose: 0.707670 loss: 0.155184 2022/09/20 03:28:18 - mmengine - INFO - Epoch(train) [95][150/293] lr: 5.000000e-04 eta: 9:01:03 time: 3.065648 data_time: 0.777301 memory: 3324 loss_kpt: 0.155257 acc_pose: 0.670188 loss: 0.155257 2022/09/20 03:31:06 - mmengine - INFO - Epoch(train) [95][200/293] lr: 5.000000e-04 eta: 9:02:41 time: 3.356409 data_time: 1.069304 memory: 3324 loss_kpt: 0.156199 acc_pose: 0.705163 loss: 0.156199 2022/09/20 03:33:25 - mmengine - INFO - Epoch(train) [95][250/293] lr: 5.000000e-04 eta: 9:03:43 time: 2.775881 data_time: 0.919734 memory: 3324 loss_kpt: 0.157538 acc_pose: 0.716193 loss: 0.157538 2022/09/20 03:35:20 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 03:35:20 - mmengine - INFO - Saving checkpoint at 95 epochs 2022/09/20 03:38:12 - mmengine - INFO - Epoch(train) [96][50/293] lr: 5.000000e-04 eta: 9:03:33 time: 3.113786 data_time: 0.991014 memory: 3324 loss_kpt: 0.155034 acc_pose: 0.738575 loss: 0.155034 2022/09/20 03:40:51 - mmengine - INFO - Epoch(train) [96][100/293] lr: 5.000000e-04 eta: 9:04:57 time: 3.178904 data_time: 0.690911 memory: 3324 loss_kpt: 0.152745 acc_pose: 0.675533 loss: 0.152745 2022/09/20 03:43:11 - mmengine - INFO - Epoch(train) [96][150/293] lr: 5.000000e-04 eta: 9:05:57 time: 2.786521 data_time: 0.861937 memory: 3324 loss_kpt: 0.157169 acc_pose: 0.676513 loss: 0.157169 2022/09/20 03:43:51 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 03:45:44 - mmengine - INFO - Epoch(train) [96][200/293] lr: 5.000000e-04 eta: 9:07:13 time: 3.059180 data_time: 0.944101 memory: 3324 loss_kpt: 0.154482 acc_pose: 0.708731 loss: 0.154482 2022/09/20 03:48:24 - mmengine - INFO - Epoch(train) [96][250/293] lr: 5.000000e-04 eta: 9:08:36 time: 3.207226 data_time: 0.865750 memory: 3324 loss_kpt: 0.155238 acc_pose: 0.714538 loss: 0.155238 2022/09/20 03:50:33 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 03:50:33 - mmengine - INFO - Saving checkpoint at 96 epochs 2022/09/20 03:54:14 - mmengine - INFO - Epoch(train) [97][50/293] lr: 5.000000e-04 eta: 9:09:10 time: 3.951436 data_time: 1.239933 memory: 3324 loss_kpt: 0.158193 acc_pose: 0.752034 loss: 0.158193 2022/09/20 03:57:21 - mmengine - INFO - Epoch(train) [97][100/293] lr: 5.000000e-04 eta: 9:11:03 time: 3.743033 data_time: 1.099506 memory: 3324 loss_kpt: 0.154361 acc_pose: 0.743348 loss: 0.154361 2022/09/20 04:00:16 - mmengine - INFO - Epoch(train) [97][150/293] lr: 5.000000e-04 eta: 9:12:42 time: 3.507029 data_time: 0.974318 memory: 3324 loss_kpt: 0.154101 acc_pose: 0.693642 loss: 0.154101 2022/09/20 04:02:49 - mmengine - INFO - Epoch(train) [97][200/293] lr: 5.000000e-04 eta: 9:13:52 time: 3.054860 data_time: 1.017349 memory: 3324 loss_kpt: 0.155926 acc_pose: 0.713024 loss: 0.155926 2022/09/20 04:05:14 - mmengine - INFO - Epoch(train) [97][250/293] lr: 5.000000e-04 eta: 9:14:52 time: 2.887819 data_time: 0.963491 memory: 3324 loss_kpt: 0.156921 acc_pose: 0.706390 loss: 0.156921 2022/09/20 04:07:19 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 04:07:19 - mmengine - INFO - Saving checkpoint at 97 epochs 2022/09/20 04:10:25 - mmengine - INFO - Epoch(train) [98][50/293] lr: 5.000000e-04 eta: 9:14:37 time: 3.217447 data_time: 1.016541 memory: 3324 loss_kpt: 0.152485 acc_pose: 0.687884 loss: 0.152485 2022/09/20 04:12:53 - mmengine - INFO - Epoch(train) [98][100/293] lr: 5.000000e-04 eta: 9:15:41 time: 2.971320 data_time: 0.775615 memory: 3324 loss_kpt: 0.154662 acc_pose: 0.679774 loss: 0.154662 2022/09/20 04:15:36 - mmengine - INFO - Epoch(train) [98][150/293] lr: 5.000000e-04 eta: 9:17:00 time: 3.258690 data_time: 1.091756 memory: 3324 loss_kpt: 0.156852 acc_pose: 0.713887 loss: 0.156852 2022/09/20 04:18:16 - mmengine - INFO - Epoch(train) [98][200/293] lr: 5.000000e-04 eta: 9:18:15 time: 3.199451 data_time: 1.080268 memory: 3324 loss_kpt: 0.154122 acc_pose: 0.759787 loss: 0.154122 2022/09/20 04:21:00 - mmengine - INFO - Epoch(train) [98][250/293] lr: 5.000000e-04 eta: 9:19:33 time: 3.271313 data_time: 1.090136 memory: 3324 loss_kpt: 0.152842 acc_pose: 0.714149 loss: 0.152842 2022/09/20 04:23:05 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 04:23:05 - mmengine - INFO - Saving checkpoint at 98 epochs 2022/09/20 04:26:18 - mmengine - INFO - Epoch(train) [99][50/293] lr: 5.000000e-04 eta: 9:19:24 time: 3.412310 data_time: 0.924173 memory: 3324 loss_kpt: 0.153033 acc_pose: 0.714903 loss: 0.153033 2022/09/20 04:28:59 - mmengine - INFO - Epoch(train) [99][100/293] lr: 5.000000e-04 eta: 9:20:37 time: 3.209326 data_time: 1.020717 memory: 3324 loss_kpt: 0.158018 acc_pose: 0.708022 loss: 0.158018 2022/09/20 04:31:43 - mmengine - INFO - Epoch(train) [99][150/293] lr: 5.000000e-04 eta: 9:21:53 time: 3.278774 data_time: 0.931221 memory: 3324 loss_kpt: 0.152531 acc_pose: 0.784902 loss: 0.152531 2022/09/20 04:34:19 - mmengine - INFO - Epoch(train) [99][200/293] lr: 5.000000e-04 eta: 9:22:59 time: 3.122556 data_time: 1.050537 memory: 3324 loss_kpt: 0.151697 acc_pose: 0.697286 loss: 0.151697 2022/09/20 04:36:52 - mmengine - INFO - Epoch(train) [99][250/293] lr: 5.000000e-04 eta: 9:24:01 time: 3.050529 data_time: 0.925457 memory: 3324 loss_kpt: 0.154042 acc_pose: 0.734174 loss: 0.154042 2022/09/20 04:38:45 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 04:39:03 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 04:39:03 - mmengine - INFO - Saving checkpoint at 99 epochs 2022/09/20 04:42:18 - mmengine - INFO - Epoch(train) [100][50/293] lr: 5.000000e-04 eta: 9:23:48 time: 3.428508 data_time: 1.175991 memory: 3324 loss_kpt: 0.154327 acc_pose: 0.613913 loss: 0.154327 2022/09/20 04:45:08 - mmengine - INFO - Epoch(train) [100][100/293] lr: 5.000000e-04 eta: 9:25:07 time: 3.394291 data_time: 0.965323 memory: 3324 loss_kpt: 0.153398 acc_pose: 0.734897 loss: 0.153398 2022/09/20 04:47:50 - mmengine - INFO - Epoch(train) [100][150/293] lr: 5.000000e-04 eta: 9:26:16 time: 3.242863 data_time: 0.958706 memory: 3324 loss_kpt: 0.154047 acc_pose: 0.660485 loss: 0.154047 2022/09/20 04:50:22 - mmengine - INFO - Epoch(train) [100][200/293] lr: 5.000000e-04 eta: 9:27:14 time: 3.034979 data_time: 1.020721 memory: 3324 loss_kpt: 0.154025 acc_pose: 0.759826 loss: 0.154025 2022/09/20 04:52:56 - mmengine - INFO - Epoch(train) [100][250/293] lr: 5.000000e-04 eta: 9:28:13 time: 3.086035 data_time: 1.017829 memory: 3324 loss_kpt: 0.156133 acc_pose: 0.748826 loss: 0.156133 2022/09/20 04:55:07 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 04:55:07 - mmengine - INFO - Saving checkpoint at 100 epochs 2022/09/20 04:56:50 - mmengine - INFO - Epoch(val) [100][50/407] eta: 0:10:02 time: 1.687414 data_time: 1.134231 memory: 3324 2022/09/20 04:58:18 - mmengine - INFO - Epoch(val) [100][100/407] eta: 0:08:57 time: 1.750181 data_time: 1.220965 memory: 400 2022/09/20 04:59:39 - mmengine - INFO - Epoch(val) [100][150/407] eta: 0:06:58 time: 1.627295 data_time: 1.107658 memory: 400 2022/09/20 05:00:57 - mmengine - INFO - Epoch(val) [100][200/407] eta: 0:05:20 time: 1.550413 data_time: 1.028745 memory: 400 2022/09/20 05:02:15 - mmengine - INFO - Epoch(val) [100][250/407] eta: 0:04:06 time: 1.567502 data_time: 0.993809 memory: 400 2022/09/20 05:03:40 - mmengine - INFO - Epoch(val) [100][300/407] eta: 0:03:01 time: 1.694468 data_time: 1.211371 memory: 400 2022/09/20 05:04:59 - mmengine - INFO - Epoch(val) [100][350/407] eta: 0:01:29 time: 1.576801 data_time: 1.105934 memory: 400 2022/09/20 05:06:10 - mmengine - INFO - Epoch(val) [100][400/407] eta: 0:00:10 time: 1.435096 data_time: 0.996958 memory: 400 2022/09/20 05:12:43 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 05:15:08 - mmengine - INFO - Epoch(val) [100][407/407] coco/AP: 0.578961 coco/AP .5: 0.838194 coco/AP .75: 0.646036 coco/AP (M): 0.545995 coco/AP (L): 0.637875 coco/AR: 0.640995 coco/AR .5: 0.887909 coco/AR .75: 0.703873 coco/AR (M): 0.596831 coco/AR (L): 0.703084 2022/09/20 05:17:41 - mmengine - INFO - Epoch(train) [101][50/293] lr: 5.000000e-04 eta: 9:27:35 time: 3.059605 data_time: 0.740365 memory: 3324 loss_kpt: 0.156459 acc_pose: 0.707089 loss: 0.156459 2022/09/20 05:20:10 - mmengine - INFO - Epoch(train) [101][100/293] lr: 5.000000e-04 eta: 9:28:27 time: 2.971828 data_time: 0.907680 memory: 3324 loss_kpt: 0.153202 acc_pose: 0.690020 loss: 0.153202 2022/09/20 05:22:28 - mmengine - INFO - Epoch(train) [101][150/293] lr: 5.000000e-04 eta: 9:29:07 time: 2.772017 data_time: 0.886306 memory: 3324 loss_kpt: 0.154127 acc_pose: 0.705109 loss: 0.154127 2022/09/20 05:24:37 - mmengine - INFO - Epoch(train) [101][200/293] lr: 5.000000e-04 eta: 9:29:36 time: 2.583593 data_time: 0.844401 memory: 3324 loss_kpt: 0.152566 acc_pose: 0.754227 loss: 0.152566 2022/09/20 05:27:00 - mmengine - INFO - Epoch(train) [101][250/293] lr: 5.000000e-04 eta: 9:30:19 time: 2.841728 data_time: 0.996352 memory: 3324 loss_kpt: 0.157503 acc_pose: 0.710727 loss: 0.157503 2022/09/20 05:28:55 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 05:28:55 - mmengine - INFO - Saving checkpoint at 101 epochs 2022/09/20 05:32:02 - mmengine - INFO - Epoch(train) [102][50/293] lr: 5.000000e-04 eta: 9:29:45 time: 3.208865 data_time: 1.072771 memory: 3324 loss_kpt: 0.156719 acc_pose: 0.676789 loss: 0.156719 2022/09/20 05:34:32 - mmengine - INFO - Epoch(train) [102][100/293] lr: 5.000000e-04 eta: 9:30:34 time: 2.996197 data_time: 0.779879 memory: 3324 loss_kpt: 0.153661 acc_pose: 0.729183 loss: 0.153661 2022/09/20 05:36:44 - mmengine - INFO - Epoch(train) [102][150/293] lr: 5.000000e-04 eta: 9:31:04 time: 2.640187 data_time: 0.781640 memory: 3324 loss_kpt: 0.151558 acc_pose: 0.698314 loss: 0.151558 2022/09/20 05:39:15 - mmengine - INFO - Epoch(train) [102][200/293] lr: 5.000000e-04 eta: 9:31:54 time: 3.024703 data_time: 0.849805 memory: 3324 loss_kpt: 0.154157 acc_pose: 0.720110 loss: 0.154157 2022/09/20 05:41:32 - mmengine - INFO - Epoch(train) [102][250/293] lr: 5.000000e-04 eta: 9:32:27 time: 2.731490 data_time: 0.881184 memory: 3324 loss_kpt: 0.151378 acc_pose: 0.741636 loss: 0.151378 2022/09/20 05:43:27 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 05:43:27 - mmengine - INFO - Saving checkpoint at 102 epochs 2022/09/20 05:45:54 - mmengine - INFO - Epoch(train) [103][50/293] lr: 5.000000e-04 eta: 9:31:18 time: 2.618326 data_time: 0.859357 memory: 3324 loss_kpt: 0.154745 acc_pose: 0.675829 loss: 0.154745 2022/09/20 05:48:14 - mmengine - INFO - Epoch(train) [103][100/293] lr: 5.000000e-04 eta: 9:31:54 time: 2.798691 data_time: 0.758898 memory: 3324 loss_kpt: 0.157724 acc_pose: 0.708476 loss: 0.157724 2022/09/20 05:48:48 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 05:50:13 - mmengine - INFO - Epoch(train) [103][150/293] lr: 5.000000e-04 eta: 9:32:08 time: 2.380026 data_time: 0.888459 memory: 3324 loss_kpt: 0.155384 acc_pose: 0.743586 loss: 0.155384 2022/09/20 05:52:28 - mmengine - INFO - Epoch(train) [103][200/293] lr: 5.000000e-04 eta: 9:32:37 time: 2.688167 data_time: 0.758504 memory: 3324 loss_kpt: 0.154098 acc_pose: 0.711432 loss: 0.154098 2022/09/20 05:54:42 - mmengine - INFO - Epoch(train) [103][250/293] lr: 5.000000e-04 eta: 9:33:05 time: 2.678479 data_time: 0.821174 memory: 3324 loss_kpt: 0.157490 acc_pose: 0.631713 loss: 0.157490 2022/09/20 05:56:33 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 05:56:33 - mmengine - INFO - Saving checkpoint at 103 epochs 2022/09/20 05:59:07 - mmengine - INFO - Epoch(train) [104][50/293] lr: 5.000000e-04 eta: 9:31:48 time: 2.529915 data_time: 0.793928 memory: 3324 loss_kpt: 0.152826 acc_pose: 0.704662 loss: 0.152826 2022/09/20 06:01:09 - mmengine - INFO - Epoch(train) [104][100/293] lr: 5.000000e-04 eta: 9:32:03 time: 2.444560 data_time: 0.768111 memory: 3324 loss_kpt: 0.150932 acc_pose: 0.777374 loss: 0.150932 2022/09/20 06:03:34 - mmengine - INFO - Epoch(train) [104][150/293] lr: 5.000000e-04 eta: 9:32:41 time: 2.908133 data_time: 1.023592 memory: 3324 loss_kpt: 0.156709 acc_pose: 0.712137 loss: 0.156709 2022/09/20 06:05:42 - mmengine - INFO - Epoch(train) [104][200/293] lr: 5.000000e-04 eta: 9:33:01 time: 2.552468 data_time: 0.786219 memory: 3324 loss_kpt: 0.152814 acc_pose: 0.663213 loss: 0.152814 2022/09/20 06:07:42 - mmengine - INFO - Epoch(train) [104][250/293] lr: 5.000000e-04 eta: 9:33:12 time: 2.399131 data_time: 0.640625 memory: 3324 loss_kpt: 0.153697 acc_pose: 0.778968 loss: 0.153697 2022/09/20 06:09:20 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 06:09:20 - mmengine - INFO - Saving checkpoint at 104 epochs 2022/09/20 06:11:44 - mmengine - INFO - Epoch(train) [105][50/293] lr: 5.000000e-04 eta: 9:31:45 time: 2.380049 data_time: 0.774915 memory: 3324 loss_kpt: 0.152942 acc_pose: 0.678309 loss: 0.152942 2022/09/20 06:13:26 - mmengine - INFO - Epoch(train) [105][100/293] lr: 5.000000e-04 eta: 9:31:38 time: 2.049473 data_time: 0.614837 memory: 3324 loss_kpt: 0.153421 acc_pose: 0.751204 loss: 0.153421 2022/09/20 06:15:22 - mmengine - INFO - Epoch(train) [105][150/293] lr: 5.000000e-04 eta: 9:31:43 time: 2.305809 data_time: 0.622463 memory: 3324 loss_kpt: 0.152173 acc_pose: 0.651946 loss: 0.152173 2022/09/20 06:17:12 - mmengine - INFO - Epoch(train) [105][200/293] lr: 5.000000e-04 eta: 9:31:42 time: 2.206523 data_time: 0.674335 memory: 3324 loss_kpt: 0.155654 acc_pose: 0.722836 loss: 0.155654 2022/09/20 06:18:52 - mmengine - INFO - Epoch(train) [105][250/293] lr: 5.000000e-04 eta: 9:31:31 time: 1.996307 data_time: 0.665419 memory: 3324 loss_kpt: 0.150880 acc_pose: 0.690471 loss: 0.150880 2022/09/20 06:20:35 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 06:20:35 - mmengine - INFO - Saving checkpoint at 105 epochs 2022/09/20 06:23:08 - mmengine - INFO - Epoch(train) [106][50/293] lr: 5.000000e-04 eta: 9:30:16 time: 2.646022 data_time: 0.827865 memory: 3324 loss_kpt: 0.152837 acc_pose: 0.684724 loss: 0.152837 2022/09/20 06:25:01 - mmengine - INFO - Epoch(train) [106][100/293] lr: 5.000000e-04 eta: 9:30:17 time: 2.255959 data_time: 0.805470 memory: 3324 loss_kpt: 0.151175 acc_pose: 0.694547 loss: 0.151175 2022/09/20 06:26:51 - mmengine - INFO - Epoch(train) [106][150/293] lr: 5.000000e-04 eta: 9:30:15 time: 2.188962 data_time: 0.674421 memory: 3324 loss_kpt: 0.155170 acc_pose: 0.729553 loss: 0.155170 2022/09/20 06:28:42 - mmengine - INFO - Epoch(train) [106][200/293] lr: 5.000000e-04 eta: 9:30:13 time: 2.210575 data_time: 0.790897 memory: 3324 loss_kpt: 0.154328 acc_pose: 0.686094 loss: 0.154328 2022/09/20 06:29:56 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 06:30:23 - mmengine - INFO - Epoch(train) [106][250/293] lr: 5.000000e-04 eta: 9:30:02 time: 2.034131 data_time: 0.701730 memory: 3324 loss_kpt: 0.152088 acc_pose: 0.716570 loss: 0.152088 2022/09/20 06:31:46 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 06:31:46 - mmengine - INFO - Saving checkpoint at 106 epochs 2022/09/20 06:34:11 - mmengine - INFO - Epoch(train) [107][50/293] lr: 5.000000e-04 eta: 9:28:42 time: 2.584473 data_time: 0.782855 memory: 3324 loss_kpt: 0.153734 acc_pose: 0.736165 loss: 0.153734 2022/09/20 06:36:02 - mmengine - INFO - Epoch(train) [107][100/293] lr: 5.000000e-04 eta: 9:28:40 time: 2.227481 data_time: 0.677654 memory: 3324 loss_kpt: 0.154819 acc_pose: 0.721821 loss: 0.154819 2022/09/20 06:37:53 - mmengine - INFO - Epoch(train) [107][150/293] lr: 5.000000e-04 eta: 9:28:36 time: 2.211828 data_time: 0.717443 memory: 3324 loss_kpt: 0.155603 acc_pose: 0.724566 loss: 0.155603 2022/09/20 06:39:45 - mmengine - INFO - Epoch(train) [107][200/293] lr: 5.000000e-04 eta: 9:28:35 time: 2.250993 data_time: 0.676256 memory: 3324 loss_kpt: 0.152727 acc_pose: 0.736257 loss: 0.152727 2022/09/20 06:41:43 - mmengine - INFO - Epoch(train) [107][250/293] lr: 5.000000e-04 eta: 9:28:38 time: 2.355558 data_time: 0.628599 memory: 3324 loss_kpt: 0.151736 acc_pose: 0.750965 loss: 0.151736 2022/09/20 06:43:06 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 06:43:06 - mmengine - INFO - Saving checkpoint at 107 epochs 2022/09/20 06:45:22 - mmengine - INFO - Epoch(train) [108][50/293] lr: 5.000000e-04 eta: 9:27:05 time: 2.365432 data_time: 0.758782 memory: 3324 loss_kpt: 0.151760 acc_pose: 0.743344 loss: 0.151760 2022/09/20 06:47:07 - mmengine - INFO - Epoch(train) [108][100/293] lr: 5.000000e-04 eta: 9:26:55 time: 2.091907 data_time: 0.626152 memory: 3324 loss_kpt: 0.154882 acc_pose: 0.703150 loss: 0.154882 2022/09/20 06:48:47 - mmengine - INFO - Epoch(train) [108][150/293] lr: 5.000000e-04 eta: 9:26:40 time: 1.994159 data_time: 0.644566 memory: 3324 loss_kpt: 0.152971 acc_pose: 0.744126 loss: 0.152971 2022/09/20 06:50:18 - mmengine - INFO - Epoch(train) [108][200/293] lr: 5.000000e-04 eta: 9:26:16 time: 1.823454 data_time: 0.628928 memory: 3324 loss_kpt: 0.153747 acc_pose: 0.740765 loss: 0.153747 2022/09/20 06:51:50 - mmengine - INFO - Epoch(train) [108][250/293] lr: 5.000000e-04 eta: 9:25:53 time: 1.840357 data_time: 0.642009 memory: 3324 loss_kpt: 0.151051 acc_pose: 0.752392 loss: 0.151051 2022/09/20 06:53:16 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 06:53:16 - mmengine - INFO - Saving checkpoint at 108 epochs 2022/09/20 06:55:14 - mmengine - INFO - Epoch(train) [109][50/293] lr: 5.000000e-04 eta: 9:24:07 time: 2.097685 data_time: 0.717755 memory: 3324 loss_kpt: 0.152365 acc_pose: 0.768314 loss: 0.152365 2022/09/20 06:56:46 - mmengine - INFO - Epoch(train) [109][100/293] lr: 5.000000e-04 eta: 9:23:43 time: 1.847331 data_time: 0.656835 memory: 3324 loss_kpt: 0.153270 acc_pose: 0.680816 loss: 0.153270 2022/09/20 06:58:14 - mmengine - INFO - Epoch(train) [109][150/293] lr: 5.000000e-04 eta: 9:23:16 time: 1.763646 data_time: 0.593311 memory: 3324 loss_kpt: 0.155345 acc_pose: 0.723585 loss: 0.155345 2022/09/20 06:59:46 - mmengine - INFO - Epoch(train) [109][200/293] lr: 5.000000e-04 eta: 9:22:51 time: 1.819766 data_time: 0.617199 memory: 3324 loss_kpt: 0.151506 acc_pose: 0.692188 loss: 0.151506 2022/09/20 07:01:19 - mmengine - INFO - Epoch(train) [109][250/293] lr: 5.000000e-04 eta: 9:22:28 time: 1.875099 data_time: 0.636688 memory: 3324 loss_kpt: 0.153469 acc_pose: 0.704236 loss: 0.153469 2022/09/20 07:02:42 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 07:02:42 - mmengine - INFO - Saving checkpoint at 109 epochs 2022/09/20 07:04:45 - mmengine - INFO - Epoch(train) [110][50/293] lr: 5.000000e-04 eta: 9:20:45 time: 2.182284 data_time: 0.648912 memory: 3324 loss_kpt: 0.152641 acc_pose: 0.705507 loss: 0.152641 2022/09/20 07:05:07 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 07:06:17 - mmengine - INFO - Epoch(train) [110][100/293] lr: 5.000000e-04 eta: 9:20:20 time: 1.835127 data_time: 0.633788 memory: 3324 loss_kpt: 0.151829 acc_pose: 0.662232 loss: 0.151829 2022/09/20 07:07:44 - mmengine - INFO - Epoch(train) [110][150/293] lr: 5.000000e-04 eta: 9:19:51 time: 1.748985 data_time: 0.619011 memory: 3324 loss_kpt: 0.152037 acc_pose: 0.702648 loss: 0.152037 2022/09/20 07:09:20 - mmengine - INFO - Epoch(train) [110][200/293] lr: 5.000000e-04 eta: 9:19:30 time: 1.913259 data_time: 0.581665 memory: 3324 loss_kpt: 0.152491 acc_pose: 0.666483 loss: 0.152491 2022/09/20 07:10:55 - mmengine - INFO - Epoch(train) [110][250/293] lr: 5.000000e-04 eta: 9:19:07 time: 1.903907 data_time: 0.620773 memory: 3324 loss_kpt: 0.153446 acc_pose: 0.723080 loss: 0.153446 2022/09/20 07:12:16 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 07:12:16 - mmengine - INFO - Saving checkpoint at 110 epochs 2022/09/20 07:13:42 - mmengine - INFO - Epoch(val) [110][50/407] eta: 0:08:43 time: 1.467499 data_time: 1.148061 memory: 3324 2022/09/20 07:14:57 - mmengine - INFO - Epoch(val) [110][100/407] eta: 0:07:44 time: 1.513002 data_time: 1.154798 memory: 400 2022/09/20 07:16:12 - mmengine - INFO - Epoch(val) [110][150/407] eta: 0:06:26 time: 1.503933 data_time: 1.195022 memory: 400 2022/09/20 07:17:27 - mmengine - INFO - Epoch(val) [110][200/407] eta: 0:05:07 time: 1.485701 data_time: 1.127392 memory: 400 2022/09/20 07:18:41 - mmengine - INFO - Epoch(val) [110][250/407] eta: 0:03:51 time: 1.477223 data_time: 1.106497 memory: 400 2022/09/20 07:19:51 - mmengine - INFO - Epoch(val) [110][300/407] eta: 0:02:31 time: 1.415229 data_time: 1.050435 memory: 400 2022/09/20 07:21:09 - mmengine - INFO - Epoch(val) [110][350/407] eta: 0:01:28 time: 1.549136 data_time: 1.239027 memory: 400 2022/09/20 07:21:58 - mmengine - INFO - Epoch(val) [110][400/407] eta: 0:00:06 time: 0.987493 data_time: 0.580648 memory: 400 2022/09/20 07:26:55 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 07:28:35 - mmengine - INFO - Epoch(val) [110][407/407] coco/AP: 0.582539 coco/AP .5: 0.837521 coco/AP .75: 0.651935 coco/AP (M): 0.548924 coco/AP (L): 0.642948 coco/AR: 0.642412 coco/AR .5: 0.884288 coco/AR .75: 0.705605 coco/AR (M): 0.597487 coco/AR (L): 0.706243 2022/09/20 07:28:36 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_90.pth is removed 2022/09/20 07:28:50 - mmengine - INFO - The best checkpoint with 0.5825 coco/AP at 110 epoch is saved to best_coco/AP_epoch_110.pth. 2022/09/20 07:30:41 - mmengine - INFO - Epoch(train) [111][50/293] lr: 5.000000e-04 eta: 9:17:25 time: 2.221367 data_time: 0.666524 memory: 3324 loss_kpt: 0.151050 acc_pose: 0.736455 loss: 0.151050 2022/09/20 07:32:29 - mmengine - INFO - Epoch(train) [111][100/293] lr: 5.000000e-04 eta: 9:17:13 time: 2.146088 data_time: 0.645991 memory: 3324 loss_kpt: 0.151671 acc_pose: 0.692217 loss: 0.151671 2022/09/20 07:34:06 - mmengine - INFO - Epoch(train) [111][150/293] lr: 5.000000e-04 eta: 9:16:52 time: 1.935090 data_time: 0.645999 memory: 3324 loss_kpt: 0.154301 acc_pose: 0.664889 loss: 0.154301 2022/09/20 07:35:50 - mmengine - INFO - Epoch(train) [111][200/293] lr: 5.000000e-04 eta: 9:16:37 time: 2.097709 data_time: 0.717490 memory: 3324 loss_kpt: 0.152136 acc_pose: 0.705081 loss: 0.152136 2022/09/20 07:37:28 - mmengine - INFO - Epoch(train) [111][250/293] lr: 5.000000e-04 eta: 9:16:16 time: 1.954928 data_time: 0.685171 memory: 3324 loss_kpt: 0.152460 acc_pose: 0.784547 loss: 0.152460 2022/09/20 07:38:55 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 07:38:55 - mmengine - INFO - Saving checkpoint at 111 epochs 2022/09/20 07:40:47 - mmengine - INFO - Epoch(train) [112][50/293] lr: 5.000000e-04 eta: 9:14:29 time: 2.149270 data_time: 0.696233 memory: 3324 loss_kpt: 0.153328 acc_pose: 0.702816 loss: 0.153328 2022/09/20 07:42:24 - mmengine - INFO - Epoch(train) [112][100/293] lr: 5.000000e-04 eta: 9:14:07 time: 1.935038 data_time: 0.638040 memory: 3324 loss_kpt: 0.151670 acc_pose: 0.702500 loss: 0.151670 2022/09/20 07:43:58 - mmengine - INFO - Epoch(train) [112][150/293] lr: 5.000000e-04 eta: 9:13:42 time: 1.887596 data_time: 0.672198 memory: 3324 loss_kpt: 0.149493 acc_pose: 0.737390 loss: 0.149493 2022/09/20 07:45:37 - mmengine - INFO - Epoch(train) [112][200/293] lr: 5.000000e-04 eta: 9:13:21 time: 1.985045 data_time: 0.637106 memory: 3324 loss_kpt: 0.153537 acc_pose: 0.718379 loss: 0.153537 2022/09/20 07:47:09 - mmengine - INFO - Epoch(train) [112][250/293] lr: 5.000000e-04 eta: 9:12:53 time: 1.829459 data_time: 0.630657 memory: 3324 loss_kpt: 0.154404 acc_pose: 0.696616 loss: 0.154404 2022/09/20 07:48:27 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 07:48:27 - mmengine - INFO - Saving checkpoint at 112 epochs 2022/09/20 07:50:33 - mmengine - INFO - Epoch(train) [113][50/293] lr: 5.000000e-04 eta: 9:11:06 time: 2.150663 data_time: 0.631626 memory: 3324 loss_kpt: 0.150823 acc_pose: 0.755711 loss: 0.150823 2022/09/20 07:52:12 - mmengine - INFO - Epoch(train) [113][100/293] lr: 5.000000e-04 eta: 9:10:44 time: 1.975547 data_time: 0.596684 memory: 3324 loss_kpt: 0.151227 acc_pose: 0.709531 loss: 0.151227 2022/09/20 07:53:44 - mmengine - INFO - Epoch(train) [113][150/293] lr: 5.000000e-04 eta: 9:10:16 time: 1.838170 data_time: 0.536500 memory: 3324 loss_kpt: 0.150605 acc_pose: 0.740166 loss: 0.150605 2022/09/20 07:54:51 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 07:55:23 - mmengine - INFO - Epoch(train) [113][200/293] lr: 5.000000e-04 eta: 9:09:54 time: 1.980579 data_time: 0.624129 memory: 3324 loss_kpt: 0.151375 acc_pose: 0.695802 loss: 0.151375 2022/09/20 07:56:54 - mmengine - INFO - Epoch(train) [113][250/293] lr: 5.000000e-04 eta: 9:09:24 time: 1.822054 data_time: 0.611089 memory: 3324 loss_kpt: 0.154218 acc_pose: 0.703431 loss: 0.154218 2022/09/20 07:58:14 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 07:58:14 - mmengine - INFO - Saving checkpoint at 113 epochs 2022/09/20 08:00:26 - mmengine - INFO - Epoch(train) [114][50/293] lr: 5.000000e-04 eta: 9:07:43 time: 2.303470 data_time: 0.735785 memory: 3324 loss_kpt: 0.152850 acc_pose: 0.724676 loss: 0.152850 2022/09/20 08:02:05 - mmengine - INFO - Epoch(train) [114][100/293] lr: 5.000000e-04 eta: 9:07:20 time: 1.973113 data_time: 0.655243 memory: 3324 loss_kpt: 0.149733 acc_pose: 0.699203 loss: 0.149733 2022/09/20 08:03:30 - mmengine - INFO - Epoch(train) [114][150/293] lr: 5.000000e-04 eta: 9:06:45 time: 1.705621 data_time: 0.558528 memory: 3324 loss_kpt: 0.151067 acc_pose: 0.698133 loss: 0.151067 2022/09/20 08:05:04 - mmengine - INFO - Epoch(train) [114][200/293] lr: 5.000000e-04 eta: 9:06:18 time: 1.881260 data_time: 0.610790 memory: 3324 loss_kpt: 0.151957 acc_pose: 0.695561 loss: 0.151957 2022/09/20 08:06:43 - mmengine - INFO - Epoch(train) [114][250/293] lr: 5.000000e-04 eta: 9:05:54 time: 1.984813 data_time: 0.696734 memory: 3324 loss_kpt: 0.154543 acc_pose: 0.655009 loss: 0.154543 2022/09/20 08:08:06 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 08:08:06 - mmengine - INFO - Saving checkpoint at 114 epochs 2022/09/20 08:10:00 - mmengine - INFO - Epoch(train) [115][50/293] lr: 5.000000e-04 eta: 9:04:03 time: 2.076351 data_time: 0.697326 memory: 3324 loss_kpt: 0.152539 acc_pose: 0.728353 loss: 0.152539 2022/09/20 08:11:34 - mmengine - INFO - Epoch(train) [115][100/293] lr: 5.000000e-04 eta: 9:03:35 time: 1.878756 data_time: 0.615945 memory: 3324 loss_kpt: 0.156114 acc_pose: 0.669312 loss: 0.156114 2022/09/20 08:12:56 - mmengine - INFO - Epoch(train) [115][150/293] lr: 5.000000e-04 eta: 9:02:57 time: 1.650947 data_time: 0.613360 memory: 3324 loss_kpt: 0.153451 acc_pose: 0.730417 loss: 0.153451 2022/09/20 08:14:23 - mmengine - INFO - Epoch(train) [115][200/293] lr: 5.000000e-04 eta: 9:02:22 time: 1.730317 data_time: 0.554295 memory: 3324 loss_kpt: 0.153005 acc_pose: 0.673851 loss: 0.153005 2022/09/20 08:15:54 - mmengine - INFO - Epoch(train) [115][250/293] lr: 5.000000e-04 eta: 9:01:51 time: 1.816006 data_time: 0.578667 memory: 3324 loss_kpt: 0.155621 acc_pose: 0.735863 loss: 0.155621 2022/09/20 08:17:01 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 08:17:01 - mmengine - INFO - Saving checkpoint at 115 epochs 2022/09/20 08:18:44 - mmengine - INFO - Epoch(train) [116][50/293] lr: 5.000000e-04 eta: 8:59:49 time: 1.852104 data_time: 0.645467 memory: 3324 loss_kpt: 0.153502 acc_pose: 0.750891 loss: 0.153502 2022/09/20 08:20:14 - mmengine - INFO - Epoch(train) [116][100/293] lr: 5.000000e-04 eta: 8:59:17 time: 1.800545 data_time: 0.583853 memory: 3324 loss_kpt: 0.155473 acc_pose: 0.749719 loss: 0.155473 2022/09/20 08:21:53 - mmengine - INFO - Epoch(train) [116][150/293] lr: 5.000000e-04 eta: 8:58:51 time: 1.970335 data_time: 0.635620 memory: 3324 loss_kpt: 0.151397 acc_pose: 0.720865 loss: 0.151397 2022/09/20 08:23:29 - mmengine - INFO - Epoch(train) [116][200/293] lr: 5.000000e-04 eta: 8:58:24 time: 1.916405 data_time: 0.560374 memory: 3324 loss_kpt: 0.149936 acc_pose: 0.744470 loss: 0.149936 2022/09/20 08:25:12 - mmengine - INFO - Epoch(train) [116][250/293] lr: 5.000000e-04 eta: 8:58:02 time: 2.067356 data_time: 0.646408 memory: 3324 loss_kpt: 0.153947 acc_pose: 0.705346 loss: 0.153947 2022/09/20 08:26:32 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 08:26:32 - mmengine - INFO - Saving checkpoint at 116 epochs 2022/09/20 08:27:20 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 08:28:38 - mmengine - INFO - Epoch(train) [117][50/293] lr: 5.000000e-04 eta: 8:56:12 time: 2.154489 data_time: 0.660079 memory: 3324 loss_kpt: 0.150775 acc_pose: 0.724489 loss: 0.150775 2022/09/20 08:30:18 - mmengine - INFO - Epoch(train) [117][100/293] lr: 5.000000e-04 eta: 8:55:47 time: 1.996446 data_time: 0.689229 memory: 3324 loss_kpt: 0.151080 acc_pose: 0.704657 loss: 0.151080 2022/09/20 08:31:52 - mmengine - INFO - Epoch(train) [117][150/293] lr: 5.000000e-04 eta: 8:55:16 time: 1.875631 data_time: 0.623198 memory: 3324 loss_kpt: 0.152104 acc_pose: 0.742391 loss: 0.152104 2022/09/20 08:33:19 - mmengine - INFO - Epoch(train) [117][200/293] lr: 5.000000e-04 eta: 8:54:41 time: 1.744344 data_time: 0.552910 memory: 3324 loss_kpt: 0.152502 acc_pose: 0.636197 loss: 0.152502 2022/09/20 08:34:43 - mmengine - INFO - Epoch(train) [117][250/293] lr: 5.000000e-04 eta: 8:54:02 time: 1.679303 data_time: 0.437772 memory: 3324 loss_kpt: 0.150218 acc_pose: 0.727762 loss: 0.150218 2022/09/20 08:36:00 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 08:36:00 - mmengine - INFO - Saving checkpoint at 117 epochs 2022/09/20 08:38:02 - mmengine - INFO - Epoch(train) [118][50/293] lr: 5.000000e-04 eta: 8:52:14 time: 2.222307 data_time: 0.700312 memory: 3324 loss_kpt: 0.152666 acc_pose: 0.752773 loss: 0.152666 2022/09/20 08:39:34 - mmengine - INFO - Epoch(train) [118][100/293] lr: 5.000000e-04 eta: 8:51:42 time: 1.831895 data_time: 0.605651 memory: 3324 loss_kpt: 0.154005 acc_pose: 0.694307 loss: 0.154005 2022/09/20 08:40:55 - mmengine - INFO - Epoch(train) [118][150/293] lr: 5.000000e-04 eta: 8:51:01 time: 1.625699 data_time: 0.532817 memory: 3324 loss_kpt: 0.152766 acc_pose: 0.759093 loss: 0.152766 2022/09/20 08:42:31 - mmengine - INFO - Epoch(train) [118][200/293] lr: 5.000000e-04 eta: 8:50:31 time: 1.912774 data_time: 0.557541 memory: 3324 loss_kpt: 0.153216 acc_pose: 0.719113 loss: 0.153216 2022/09/20 08:44:03 - mmengine - INFO - Epoch(train) [118][250/293] lr: 5.000000e-04 eta: 8:49:58 time: 1.836789 data_time: 0.601061 memory: 3324 loss_kpt: 0.150802 acc_pose: 0.682977 loss: 0.150802 2022/09/20 08:45:27 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 08:45:28 - mmengine - INFO - Saving checkpoint at 118 epochs 2022/09/20 08:47:33 - mmengine - INFO - Epoch(train) [119][50/293] lr: 5.000000e-04 eta: 8:48:07 time: 2.167804 data_time: 0.774842 memory: 3324 loss_kpt: 0.150793 acc_pose: 0.725762 loss: 0.150793 2022/09/20 08:49:07 - mmengine - INFO - Epoch(train) [119][100/293] lr: 5.000000e-04 eta: 8:47:36 time: 1.881714 data_time: 0.574396 memory: 3324 loss_kpt: 0.149874 acc_pose: 0.639469 loss: 0.149874 2022/09/20 08:50:39 - mmengine - INFO - Epoch(train) [119][150/293] lr: 5.000000e-04 eta: 8:47:02 time: 1.843470 data_time: 0.594964 memory: 3324 loss_kpt: 0.152052 acc_pose: 0.731626 loss: 0.152052 2022/09/20 08:52:05 - mmengine - INFO - Epoch(train) [119][200/293] lr: 5.000000e-04 eta: 8:46:24 time: 1.714460 data_time: 0.530597 memory: 3324 loss_kpt: 0.151648 acc_pose: 0.806755 loss: 0.151648 2022/09/20 08:53:44 - mmengine - INFO - Epoch(train) [119][250/293] lr: 5.000000e-04 eta: 8:45:55 time: 1.967985 data_time: 0.569931 memory: 3324 loss_kpt: 0.154408 acc_pose: 0.716104 loss: 0.154408 2022/09/20 08:55:04 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 08:55:04 - mmengine - INFO - Saving checkpoint at 119 epochs 2022/09/20 08:57:00 - mmengine - INFO - Epoch(train) [120][50/293] lr: 5.000000e-04 eta: 8:43:59 time: 2.030363 data_time: 0.684900 memory: 3324 loss_kpt: 0.150378 acc_pose: 0.723294 loss: 0.150378 2022/09/20 08:58:36 - mmengine - INFO - Epoch(train) [120][100/293] lr: 5.000000e-04 eta: 8:43:28 time: 1.920032 data_time: 0.652509 memory: 3324 loss_kpt: 0.151798 acc_pose: 0.728365 loss: 0.151798 2022/09/20 08:59:39 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 09:00:11 - mmengine - INFO - Epoch(train) [120][150/293] lr: 5.000000e-04 eta: 8:42:56 time: 1.904863 data_time: 0.668532 memory: 3324 loss_kpt: 0.149181 acc_pose: 0.746835 loss: 0.149181 2022/09/20 09:01:44 - mmengine - INFO - Epoch(train) [120][200/293] lr: 5.000000e-04 eta: 8:42:23 time: 1.861460 data_time: 0.634024 memory: 3324 loss_kpt: 0.154635 acc_pose: 0.701137 loss: 0.154635 2022/09/20 09:03:13 - mmengine - INFO - Epoch(train) [120][250/293] lr: 5.000000e-04 eta: 8:41:45 time: 1.773859 data_time: 0.599804 memory: 3324 loss_kpt: 0.152777 acc_pose: 0.737456 loss: 0.152777 2022/09/20 09:04:28 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 09:04:28 - mmengine - INFO - Saving checkpoint at 120 epochs 2022/09/20 09:05:59 - mmengine - INFO - Epoch(val) [120][50/407] eta: 0:09:08 time: 1.537390 data_time: 1.235934 memory: 3324 2022/09/20 09:07:11 - mmengine - INFO - Epoch(val) [120][100/407] eta: 0:07:20 time: 1.433376 data_time: 1.124882 memory: 400 2022/09/20 09:08:27 - mmengine - INFO - Epoch(val) [120][150/407] eta: 0:06:35 time: 1.538708 data_time: 1.257021 memory: 400 2022/09/20 09:09:39 - mmengine - INFO - Epoch(val) [120][200/407] eta: 0:04:53 time: 1.416181 data_time: 1.076359 memory: 400 2022/09/20 09:10:52 - mmengine - INFO - Epoch(val) [120][250/407] eta: 0:03:49 time: 1.464276 data_time: 1.164033 memory: 400 2022/09/20 09:12:02 - mmengine - INFO - Epoch(val) [120][300/407] eta: 0:02:29 time: 1.395514 data_time: 1.069246 memory: 400 2022/09/20 09:13:14 - mmengine - INFO - Epoch(val) [120][350/407] eta: 0:01:23 time: 1.459285 data_time: 1.146721 memory: 400 2022/09/20 09:14:01 - mmengine - INFO - Epoch(val) [120][400/407] eta: 0:00:06 time: 0.924615 data_time: 0.595342 memory: 400 2022/09/20 09:18:35 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 09:20:03 - mmengine - INFO - Epoch(val) [120][407/407] coco/AP: 0.588803 coco/AP .5: 0.841753 coco/AP .75: 0.657869 coco/AP (M): 0.555286 coco/AP (L): 0.648372 coco/AR: 0.648504 coco/AR .5: 0.888854 coco/AR .75: 0.712531 coco/AR (M): 0.603824 coco/AR (L): 0.711446 2022/09/20 09:20:03 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_110.pth is removed 2022/09/20 09:20:12 - mmengine - INFO - The best checkpoint with 0.5888 coco/AP at 120 epoch is saved to best_coco/AP_epoch_120.pth. 2022/09/20 09:22:17 - mmengine - INFO - Epoch(train) [121][50/293] lr: 5.000000e-04 eta: 8:40:07 time: 2.510559 data_time: 0.752823 memory: 3324 loss_kpt: 0.152008 acc_pose: 0.659176 loss: 0.152008 2022/09/20 09:24:07 - mmengine - INFO - Epoch(train) [121][100/293] lr: 5.000000e-04 eta: 8:39:45 time: 2.198360 data_time: 0.657106 memory: 3324 loss_kpt: 0.153358 acc_pose: 0.738136 loss: 0.153358 2022/09/20 09:25:48 - mmengine - INFO - Epoch(train) [121][150/293] lr: 5.000000e-04 eta: 8:39:17 time: 2.017110 data_time: 0.607789 memory: 3324 loss_kpt: 0.151754 acc_pose: 0.760732 loss: 0.151754 2022/09/20 09:27:31 - mmengine - INFO - Epoch(train) [121][200/293] lr: 5.000000e-04 eta: 8:38:49 time: 2.052278 data_time: 0.603855 memory: 3324 loss_kpt: 0.152766 acc_pose: 0.714490 loss: 0.152766 2022/09/20 09:29:20 - mmengine - INFO - Epoch(train) [121][250/293] lr: 5.000000e-04 eta: 8:38:27 time: 2.192314 data_time: 0.564025 memory: 3324 loss_kpt: 0.152015 acc_pose: 0.683876 loss: 0.152015 2022/09/20 09:30:41 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 09:30:41 - mmengine - INFO - Saving checkpoint at 121 epochs 2022/09/20 09:32:53 - mmengine - INFO - Epoch(train) [122][50/293] lr: 5.000000e-04 eta: 8:36:37 time: 2.252925 data_time: 0.673398 memory: 3324 loss_kpt: 0.151889 acc_pose: 0.771253 loss: 0.151889 2022/09/20 09:34:27 - mmengine - INFO - Epoch(train) [122][100/293] lr: 5.000000e-04 eta: 8:36:03 time: 1.882584 data_time: 0.612981 memory: 3324 loss_kpt: 0.150404 acc_pose: 0.754564 loss: 0.150404 2022/09/20 09:36:02 - mmengine - INFO - Epoch(train) [122][150/293] lr: 5.000000e-04 eta: 8:35:29 time: 1.900422 data_time: 0.641097 memory: 3324 loss_kpt: 0.152025 acc_pose: 0.635037 loss: 0.152025 2022/09/20 09:37:50 - mmengine - INFO - Epoch(train) [122][200/293] lr: 5.000000e-04 eta: 8:35:05 time: 2.166957 data_time: 0.635478 memory: 3324 loss_kpt: 0.152852 acc_pose: 0.749569 loss: 0.152852 2022/09/20 09:39:23 - mmengine - INFO - Epoch(train) [122][250/293] lr: 5.000000e-04 eta: 8:34:29 time: 1.862072 data_time: 0.606896 memory: 3324 loss_kpt: 0.151337 acc_pose: 0.752913 loss: 0.151337 2022/09/20 09:40:39 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 09:40:39 - mmengine - INFO - Saving checkpoint at 122 epochs 2022/09/20 09:42:19 - mmengine - INFO - Epoch(train) [123][50/293] lr: 5.000000e-04 eta: 8:32:23 time: 1.792238 data_time: 0.654130 memory: 3324 loss_kpt: 0.153406 acc_pose: 0.732362 loss: 0.153406 2022/09/20 09:43:55 - mmengine - INFO - Epoch(train) [123][100/293] lr: 5.000000e-04 eta: 8:31:49 time: 1.924091 data_time: 0.596367 memory: 3324 loss_kpt: 0.151848 acc_pose: 0.741183 loss: 0.151848 2022/09/20 09:45:41 - mmengine - INFO - Epoch(train) [123][150/293] lr: 5.000000e-04 eta: 8:31:22 time: 2.115168 data_time: 0.641632 memory: 3324 loss_kpt: 0.152188 acc_pose: 0.724543 loss: 0.152188 2022/09/20 09:47:13 - mmengine - INFO - Epoch(train) [123][200/293] lr: 5.000000e-04 eta: 8:30:45 time: 1.842330 data_time: 0.601326 memory: 3324 loss_kpt: 0.152849 acc_pose: 0.720884 loss: 0.152849 2022/09/20 09:48:46 - mmengine - INFO - Epoch(train) [123][250/293] lr: 5.000000e-04 eta: 8:30:09 time: 1.858319 data_time: 0.700241 memory: 3324 loss_kpt: 0.151259 acc_pose: 0.722537 loss: 0.151259 2022/09/20 09:48:54 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 09:50:09 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 09:50:09 - mmengine - INFO - Saving checkpoint at 123 epochs 2022/09/20 09:52:11 - mmengine - INFO - Epoch(train) [124][50/293] lr: 5.000000e-04 eta: 8:28:18 time: 2.237173 data_time: 0.698825 memory: 3324 loss_kpt: 0.151904 acc_pose: 0.660827 loss: 0.151904 2022/09/20 09:53:41 - mmengine - INFO - Epoch(train) [124][100/293] lr: 5.000000e-04 eta: 8:27:39 time: 1.802198 data_time: 0.565869 memory: 3324 loss_kpt: 0.152054 acc_pose: 0.744671 loss: 0.152054 2022/09/20 09:55:27 - mmengine - INFO - Epoch(train) [124][150/293] lr: 5.000000e-04 eta: 8:27:11 time: 2.107878 data_time: 0.616543 memory: 3324 loss_kpt: 0.152184 acc_pose: 0.716205 loss: 0.152184 2022/09/20 09:57:03 - mmengine - INFO - Epoch(train) [124][200/293] lr: 5.000000e-04 eta: 8:26:36 time: 1.931580 data_time: 0.509486 memory: 3324 loss_kpt: 0.154900 acc_pose: 0.658247 loss: 0.154900 2022/09/20 09:58:46 - mmengine - INFO - Epoch(train) [124][250/293] lr: 5.000000e-04 eta: 8:26:06 time: 2.052077 data_time: 0.566505 memory: 3324 loss_kpt: 0.152361 acc_pose: 0.741805 loss: 0.152361 2022/09/20 10:00:02 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 10:00:02 - mmengine - INFO - Saving checkpoint at 124 epochs 2022/09/20 10:02:10 - mmengine - INFO - Epoch(train) [125][50/293] lr: 5.000000e-04 eta: 8:24:15 time: 2.269012 data_time: 0.692587 memory: 3324 loss_kpt: 0.152235 acc_pose: 0.800361 loss: 0.152235 2022/09/20 10:03:54 - mmengine - INFO - Epoch(train) [125][100/293] lr: 5.000000e-04 eta: 8:23:44 time: 2.061217 data_time: 0.568963 memory: 3324 loss_kpt: 0.150411 acc_pose: 0.745063 loss: 0.150411 2022/09/20 10:05:31 - mmengine - INFO - Epoch(train) [125][150/293] lr: 5.000000e-04 eta: 8:23:10 time: 1.954509 data_time: 0.572305 memory: 3324 loss_kpt: 0.150336 acc_pose: 0.675024 loss: 0.150336 2022/09/20 10:07:15 - mmengine - INFO - Epoch(train) [125][200/293] lr: 5.000000e-04 eta: 8:22:39 time: 2.080210 data_time: 0.591528 memory: 3324 loss_kpt: 0.150790 acc_pose: 0.724750 loss: 0.150790 2022/09/20 10:08:56 - mmengine - INFO - Epoch(train) [125][250/293] lr: 5.000000e-04 eta: 8:22:07 time: 2.012371 data_time: 0.682941 memory: 3324 loss_kpt: 0.153378 acc_pose: 0.707564 loss: 0.153378 2022/09/20 10:10:13 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 10:10:13 - mmengine - INFO - Saving checkpoint at 125 epochs 2022/09/20 10:12:21 - mmengine - INFO - Epoch(train) [126][50/293] lr: 5.000000e-04 eta: 8:20:16 time: 2.301978 data_time: 0.751480 memory: 3324 loss_kpt: 0.153247 acc_pose: 0.794040 loss: 0.153247 2022/09/20 10:14:02 - mmengine - INFO - Epoch(train) [126][100/293] lr: 5.000000e-04 eta: 8:19:43 time: 2.028227 data_time: 0.630079 memory: 3324 loss_kpt: 0.153160 acc_pose: 0.661034 loss: 0.153160 2022/09/20 10:15:42 - mmengine - INFO - Epoch(train) [126][150/293] lr: 5.000000e-04 eta: 8:19:09 time: 1.992366 data_time: 0.561437 memory: 3324 loss_kpt: 0.150051 acc_pose: 0.619487 loss: 0.150051 2022/09/20 10:17:23 - mmengine - INFO - Epoch(train) [126][200/293] lr: 5.000000e-04 eta: 8:18:36 time: 2.028608 data_time: 0.624255 memory: 3324 loss_kpt: 0.151524 acc_pose: 0.684676 loss: 0.151524 2022/09/20 10:19:17 - mmengine - INFO - Epoch(train) [126][250/293] lr: 5.000000e-04 eta: 8:18:11 time: 2.271114 data_time: 0.690464 memory: 3324 loss_kpt: 0.151548 acc_pose: 0.712074 loss: 0.151548 2022/09/20 10:20:43 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 10:20:43 - mmengine - INFO - Saving checkpoint at 126 epochs 2022/09/20 10:22:54 - mmengine - INFO - Epoch(train) [127][50/293] lr: 5.000000e-04 eta: 8:16:19 time: 2.257341 data_time: 0.625055 memory: 3324 loss_kpt: 0.150274 acc_pose: 0.734355 loss: 0.150274 2022/09/20 10:23:54 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 10:24:34 - mmengine - INFO - Epoch(train) [127][100/293] lr: 5.000000e-04 eta: 8:15:44 time: 1.999311 data_time: 0.647189 memory: 3324 loss_kpt: 0.151781 acc_pose: 0.761460 loss: 0.151781 2022/09/20 10:26:14 - mmengine - INFO - Epoch(train) [127][150/293] lr: 5.000000e-04 eta: 8:15:09 time: 1.997896 data_time: 0.603953 memory: 3324 loss_kpt: 0.150691 acc_pose: 0.750014 loss: 0.150691 2022/09/20 10:28:10 - mmengine - INFO - Epoch(train) [127][200/293] lr: 5.000000e-04 eta: 8:14:45 time: 2.324876 data_time: 0.581521 memory: 3324 loss_kpt: 0.151188 acc_pose: 0.694360 loss: 0.151188 2022/09/20 10:29:53 - mmengine - INFO - Epoch(train) [127][250/293] lr: 5.000000e-04 eta: 8:14:12 time: 2.069509 data_time: 0.665521 memory: 3324 loss_kpt: 0.150204 acc_pose: 0.705435 loss: 0.150204 2022/09/20 10:31:19 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 10:31:19 - mmengine - INFO - Saving checkpoint at 127 epochs 2022/09/20 10:33:21 - mmengine - INFO - Epoch(train) [128][50/293] lr: 5.000000e-04 eta: 8:12:15 time: 2.151089 data_time: 0.631749 memory: 3324 loss_kpt: 0.147890 acc_pose: 0.743870 loss: 0.147890 2022/09/20 10:35:01 - mmengine - INFO - Epoch(train) [128][100/293] lr: 5.000000e-04 eta: 8:11:40 time: 1.993246 data_time: 0.535335 memory: 3324 loss_kpt: 0.155258 acc_pose: 0.712699 loss: 0.155258 2022/09/20 10:36:37 - mmengine - INFO - Epoch(train) [128][150/293] lr: 5.000000e-04 eta: 8:11:02 time: 1.924399 data_time: 0.562485 memory: 3324 loss_kpt: 0.151954 acc_pose: 0.725487 loss: 0.151954 2022/09/20 10:38:22 - mmengine - INFO - Epoch(train) [128][200/293] lr: 5.000000e-04 eta: 8:10:29 time: 2.090551 data_time: 0.612032 memory: 3324 loss_kpt: 0.152426 acc_pose: 0.732729 loss: 0.152426 2022/09/20 10:40:01 - mmengine - INFO - Epoch(train) [128][250/293] lr: 5.000000e-04 eta: 8:09:53 time: 1.994405 data_time: 0.690347 memory: 3324 loss_kpt: 0.149666 acc_pose: 0.706953 loss: 0.149666 2022/09/20 10:41:20 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 10:41:21 - mmengine - INFO - Saving checkpoint at 128 epochs 2022/09/20 10:43:24 - mmengine - INFO - Epoch(train) [129][50/293] lr: 5.000000e-04 eta: 8:07:58 time: 2.224803 data_time: 0.710790 memory: 3324 loss_kpt: 0.150811 acc_pose: 0.721759 loss: 0.150811 2022/09/20 10:45:04 - mmengine - INFO - Epoch(train) [129][100/293] lr: 5.000000e-04 eta: 8:07:21 time: 1.994279 data_time: 0.636410 memory: 3324 loss_kpt: 0.148654 acc_pose: 0.729537 loss: 0.148654 2022/09/20 10:46:46 - mmengine - INFO - Epoch(train) [129][150/293] lr: 5.000000e-04 eta: 8:06:46 time: 2.034114 data_time: 0.608159 memory: 3324 loss_kpt: 0.153410 acc_pose: 0.706248 loss: 0.153410 2022/09/20 10:48:24 - mmengine - INFO - Epoch(train) [129][200/293] lr: 5.000000e-04 eta: 8:06:08 time: 1.979487 data_time: 0.643064 memory: 3324 loss_kpt: 0.154944 acc_pose: 0.723288 loss: 0.154944 2022/09/20 10:50:00 - mmengine - INFO - Epoch(train) [129][250/293] lr: 5.000000e-04 eta: 8:05:29 time: 1.903109 data_time: 0.655848 memory: 3324 loss_kpt: 0.149510 acc_pose: 0.726175 loss: 0.149510 2022/09/20 10:51:21 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 10:51:21 - mmengine - INFO - Saving checkpoint at 129 epochs 2022/09/20 10:53:20 - mmengine - INFO - Epoch(train) [130][50/293] lr: 5.000000e-04 eta: 8:03:30 time: 2.119822 data_time: 0.614739 memory: 3324 loss_kpt: 0.150846 acc_pose: 0.709713 loss: 0.150846 2022/09/20 10:55:07 - mmengine - INFO - Epoch(train) [130][100/293] lr: 5.000000e-04 eta: 8:02:57 time: 2.146025 data_time: 0.647040 memory: 3324 loss_kpt: 0.149584 acc_pose: 0.720063 loss: 0.149584 2022/09/20 10:56:46 - mmengine - INFO - Epoch(train) [130][150/293] lr: 5.000000e-04 eta: 8:02:19 time: 1.978675 data_time: 0.592358 memory: 3324 loss_kpt: 0.149860 acc_pose: 0.693340 loss: 0.149860 2022/09/20 10:58:25 - mmengine - INFO - Epoch(train) [130][200/293] lr: 5.000000e-04 eta: 8:01:41 time: 1.981008 data_time: 0.586217 memory: 3324 loss_kpt: 0.148734 acc_pose: 0.720050 loss: 0.148734 2022/09/20 10:58:30 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 10:59:57 - mmengine - INFO - Epoch(train) [130][250/293] lr: 5.000000e-04 eta: 8:00:59 time: 1.836730 data_time: 0.599758 memory: 3324 loss_kpt: 0.151325 acc_pose: 0.738270 loss: 0.151325 2022/09/20 11:01:23 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 11:01:23 - mmengine - INFO - Saving checkpoint at 130 epochs 2022/09/20 11:02:51 - mmengine - INFO - Epoch(val) [130][50/407] eta: 0:08:42 time: 1.462921 data_time: 1.166866 memory: 3324 2022/09/20 11:04:02 - mmengine - INFO - Epoch(val) [130][100/407] eta: 0:07:12 time: 1.409042 data_time: 1.095341 memory: 400 2022/09/20 11:05:13 - mmengine - INFO - Epoch(val) [130][150/407] eta: 0:06:07 time: 1.431829 data_time: 1.110454 memory: 400 2022/09/20 11:06:26 - mmengine - INFO - Epoch(val) [130][200/407] eta: 0:05:00 time: 1.451149 data_time: 1.118744 memory: 400 2022/09/20 11:07:39 - mmengine - INFO - Epoch(val) [130][250/407] eta: 0:03:48 time: 1.455054 data_time: 1.179207 memory: 400 2022/09/20 11:08:50 - mmengine - INFO - Epoch(val) [130][300/407] eta: 0:02:30 time: 1.409924 data_time: 1.112087 memory: 400 2022/09/20 11:10:02 - mmengine - INFO - Epoch(val) [130][350/407] eta: 0:01:22 time: 1.451710 data_time: 1.154727 memory: 400 2022/09/20 11:10:47 - mmengine - INFO - Epoch(val) [130][400/407] eta: 0:00:06 time: 0.904374 data_time: 0.590009 memory: 400 2022/09/20 11:15:08 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 11:16:53 - mmengine - INFO - Epoch(val) [130][407/407] coco/AP: 0.591545 coco/AP .5: 0.846288 coco/AP .75: 0.664555 coco/AP (M): 0.557176 coco/AP (L): 0.653088 coco/AR: 0.652157 coco/AR .5: 0.894679 coco/AR .75: 0.719301 coco/AR (M): 0.607047 coco/AR (L): 0.715570 2022/09/20 11:16:53 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_120.pth is removed 2022/09/20 11:17:05 - mmengine - INFO - The best checkpoint with 0.5915 coco/AP at 130 epoch is saved to best_coco/AP_epoch_130.pth. 2022/09/20 11:19:09 - mmengine - INFO - Epoch(train) [131][50/293] lr: 5.000000e-04 eta: 7:59:10 time: 2.467876 data_time: 0.753191 memory: 3324 loss_kpt: 0.150483 acc_pose: 0.706471 loss: 0.150483 2022/09/20 11:20:56 - mmengine - INFO - Epoch(train) [131][100/293] lr: 5.000000e-04 eta: 7:58:36 time: 2.136933 data_time: 0.639372 memory: 3324 loss_kpt: 0.149962 acc_pose: 0.755479 loss: 0.149962 2022/09/20 11:22:32 - mmengine - INFO - Epoch(train) [131][150/293] lr: 5.000000e-04 eta: 7:57:56 time: 1.924147 data_time: 0.659889 memory: 3324 loss_kpt: 0.149046 acc_pose: 0.662676 loss: 0.149046 2022/09/20 11:24:13 - mmengine - INFO - Epoch(train) [131][200/293] lr: 5.000000e-04 eta: 7:57:18 time: 2.017247 data_time: 0.736840 memory: 3324 loss_kpt: 0.151535 acc_pose: 0.701937 loss: 0.151535 2022/09/20 11:25:43 - mmengine - INFO - Epoch(train) [131][250/293] lr: 5.000000e-04 eta: 7:56:33 time: 1.795722 data_time: 0.520145 memory: 3324 loss_kpt: 0.152667 acc_pose: 0.752659 loss: 0.152667 2022/09/20 11:27:28 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 11:27:28 - mmengine - INFO - Saving checkpoint at 131 epochs 2022/09/20 11:29:31 - mmengine - INFO - Epoch(train) [132][50/293] lr: 5.000000e-04 eta: 7:54:34 time: 2.149759 data_time: 0.765089 memory: 3324 loss_kpt: 0.151966 acc_pose: 0.699588 loss: 0.151966 2022/09/20 11:31:08 - mmengine - INFO - Epoch(train) [132][100/293] lr: 5.000000e-04 eta: 7:53:54 time: 1.936162 data_time: 0.659353 memory: 3324 loss_kpt: 0.150665 acc_pose: 0.774139 loss: 0.150665 2022/09/20 11:32:31 - mmengine - INFO - Epoch(train) [132][150/293] lr: 5.000000e-04 eta: 7:53:05 time: 1.658764 data_time: 0.553455 memory: 3324 loss_kpt: 0.150585 acc_pose: 0.706153 loss: 0.150585 2022/09/20 11:34:14 - mmengine - INFO - Epoch(train) [132][200/293] lr: 5.000000e-04 eta: 7:52:27 time: 2.047444 data_time: 0.612492 memory: 3324 loss_kpt: 0.154665 acc_pose: 0.688229 loss: 0.154665 2022/09/20 11:36:00 - mmengine - INFO - Epoch(train) [132][250/293] lr: 5.000000e-04 eta: 7:51:52 time: 2.122886 data_time: 0.596544 memory: 3324 loss_kpt: 0.149747 acc_pose: 0.687601 loss: 0.149747 2022/09/20 11:37:26 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 11:37:26 - mmengine - INFO - Saving checkpoint at 132 epochs 2022/09/20 11:39:31 - mmengine - INFO - Epoch(train) [133][50/293] lr: 5.000000e-04 eta: 7:49:52 time: 2.149825 data_time: 0.701462 memory: 3324 loss_kpt: 0.152013 acc_pose: 0.717917 loss: 0.152013 2022/09/20 11:41:10 - mmengine - INFO - Epoch(train) [133][100/293] lr: 5.000000e-04 eta: 7:49:13 time: 1.983780 data_time: 0.708243 memory: 3324 loss_kpt: 0.149602 acc_pose: 0.763674 loss: 0.149602 2022/09/20 11:42:55 - mmengine - INFO - Epoch(train) [133][150/293] lr: 5.000000e-04 eta: 7:48:36 time: 2.109425 data_time: 0.719183 memory: 3324 loss_kpt: 0.149317 acc_pose: 0.765005 loss: 0.149317 2022/09/20 11:44:47 - mmengine - INFO - Epoch(train) [133][200/293] lr: 5.000000e-04 eta: 7:48:03 time: 2.222474 data_time: 0.712693 memory: 3324 loss_kpt: 0.150508 acc_pose: 0.738285 loss: 0.150508 2022/09/20 11:46:24 - mmengine - INFO - Epoch(train) [133][250/293] lr: 5.000000e-04 eta: 7:47:22 time: 1.948078 data_time: 0.617653 memory: 3324 loss_kpt: 0.147614 acc_pose: 0.691849 loss: 0.147614 2022/09/20 11:47:47 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 11:47:47 - mmengine - INFO - Saving checkpoint at 133 epochs 2022/09/20 11:49:20 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 11:49:53 - mmengine - INFO - Epoch(train) [134][50/293] lr: 5.000000e-04 eta: 7:45:22 time: 2.178570 data_time: 0.670359 memory: 3324 loss_kpt: 0.148069 acc_pose: 0.689459 loss: 0.148069 2022/09/20 11:50:23 - mmengine - INFO - Epoch(train) [134][100/293] lr: 5.000000e-04 eta: 7:44:02 time: 0.590748 data_time: 0.252058 memory: 3324 loss_kpt: 0.152522 acc_pose: 0.673059 loss: 0.152522 2022/09/20 11:51:06 - mmengine - INFO - Epoch(train) [134][150/293] lr: 5.000000e-04 eta: 7:42:49 time: 0.876095 data_time: 0.256340 memory: 3324 loss_kpt: 0.151042 acc_pose: 0.738255 loss: 0.151042 2022/09/20 11:52:06 - mmengine - INFO - Epoch(train) [134][200/293] lr: 5.000000e-04 eta: 7:41:46 time: 1.203252 data_time: 0.111769 memory: 3324 loss_kpt: 0.154266 acc_pose: 0.705054 loss: 0.154266 2022/09/20 11:52:51 - mmengine - INFO - Epoch(train) [134][250/293] lr: 5.000000e-04 eta: 7:40:35 time: 0.894844 data_time: 0.106463 memory: 3324 loss_kpt: 0.150626 acc_pose: 0.705941 loss: 0.150626 2022/09/20 11:53:30 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 11:53:31 - mmengine - INFO - Saving checkpoint at 134 epochs 2022/09/20 11:54:05 - mmengine - INFO - Epoch(train) [135][50/293] lr: 5.000000e-04 eta: 7:37:53 time: 0.641586 data_time: 0.185615 memory: 3324 loss_kpt: 0.151666 acc_pose: 0.663390 loss: 0.151666 2022/09/20 11:54:49 - mmengine - INFO - Epoch(train) [135][100/293] lr: 5.000000e-04 eta: 7:36:41 time: 0.887408 data_time: 0.099127 memory: 3324 loss_kpt: 0.150737 acc_pose: 0.755943 loss: 0.150737 2022/09/20 11:55:25 - mmengine - INFO - Epoch(train) [135][150/293] lr: 5.000000e-04 eta: 7:35:24 time: 0.709369 data_time: 0.237899 memory: 3324 loss_kpt: 0.147764 acc_pose: 0.746092 loss: 0.147764 2022/09/20 11:56:19 - mmengine - INFO - Epoch(train) [135][200/293] lr: 5.000000e-04 eta: 7:34:18 time: 1.086441 data_time: 0.102155 memory: 3324 loss_kpt: 0.145905 acc_pose: 0.735226 loss: 0.145905 2022/09/20 11:57:03 - mmengine - INFO - Epoch(train) [135][250/293] lr: 5.000000e-04 eta: 7:33:07 time: 0.881332 data_time: 0.099551 memory: 3324 loss_kpt: 0.148915 acc_pose: 0.671479 loss: 0.148915 2022/09/20 11:57:31 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 11:57:31 - mmengine - INFO - Saving checkpoint at 135 epochs 2022/09/20 11:58:12 - mmengine - INFO - Epoch(train) [136][50/293] lr: 5.000000e-04 eta: 7:30:29 time: 0.761849 data_time: 0.371790 memory: 3324 loss_kpt: 0.149561 acc_pose: 0.724496 loss: 0.149561 2022/09/20 11:58:51 - mmengine - INFO - Epoch(train) [136][100/293] lr: 5.000000e-04 eta: 7:29:15 time: 0.779119 data_time: 0.458283 memory: 3324 loss_kpt: 0.151921 acc_pose: 0.734786 loss: 0.151921 2022/09/20 11:59:36 - mmengine - INFO - Epoch(train) [136][150/293] lr: 5.000000e-04 eta: 7:28:05 time: 0.912567 data_time: 0.414129 memory: 3324 loss_kpt: 0.149896 acc_pose: 0.639367 loss: 0.149896 2022/09/20 12:00:13 - mmengine - INFO - Epoch(train) [136][200/293] lr: 5.000000e-04 eta: 7:26:50 time: 0.741202 data_time: 0.322584 memory: 3324 loss_kpt: 0.155141 acc_pose: 0.718503 loss: 0.155141 2022/09/20 12:01:01 - mmengine - INFO - Epoch(train) [136][250/293] lr: 5.000000e-04 eta: 7:25:41 time: 0.956989 data_time: 0.672514 memory: 3324 loss_kpt: 0.148883 acc_pose: 0.743222 loss: 0.148883 2022/09/20 12:01:53 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:01:53 - mmengine - INFO - Saving checkpoint at 136 epochs 2022/09/20 12:02:41 - mmengine - INFO - Epoch(train) [137][50/293] lr: 5.000000e-04 eta: 7:23:09 time: 0.905369 data_time: 0.179560 memory: 3324 loss_kpt: 0.150409 acc_pose: 0.733363 loss: 0.150409 2022/09/20 12:03:36 - mmengine - INFO - Epoch(train) [137][100/293] lr: 5.000000e-04 eta: 7:22:04 time: 1.100950 data_time: 0.312141 memory: 3324 loss_kpt: 0.149127 acc_pose: 0.748052 loss: 0.149127 2022/09/20 12:04:26 - mmengine - INFO - Epoch(train) [137][150/293] lr: 5.000000e-04 eta: 7:20:56 time: 1.004408 data_time: 0.247356 memory: 3324 loss_kpt: 0.152978 acc_pose: 0.723983 loss: 0.152978 2022/09/20 12:04:29 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:05:15 - mmengine - INFO - Epoch(train) [137][200/293] lr: 5.000000e-04 eta: 7:19:48 time: 0.982103 data_time: 0.102379 memory: 3324 loss_kpt: 0.149907 acc_pose: 0.697483 loss: 0.149907 2022/09/20 12:06:09 - mmengine - INFO - Epoch(train) [137][250/293] lr: 5.000000e-04 eta: 7:18:43 time: 1.078849 data_time: 0.103501 memory: 3324 loss_kpt: 0.153318 acc_pose: 0.751751 loss: 0.153318 2022/09/20 12:06:56 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:06:56 - mmengine - INFO - Saving checkpoint at 137 epochs 2022/09/20 12:07:47 - mmengine - INFO - Epoch(train) [138][50/293] lr: 5.000000e-04 eta: 7:16:14 time: 0.976476 data_time: 0.125572 memory: 3324 loss_kpt: 0.147932 acc_pose: 0.803588 loss: 0.147932 2022/09/20 12:08:22 - mmengine - INFO - Epoch(train) [138][100/293] lr: 5.000000e-04 eta: 7:14:58 time: 0.689150 data_time: 0.099145 memory: 3324 loss_kpt: 0.147855 acc_pose: 0.749185 loss: 0.147855 2022/09/20 12:09:09 - mmengine - INFO - Epoch(train) [138][150/293] lr: 5.000000e-04 eta: 7:13:50 time: 0.944928 data_time: 0.107994 memory: 3324 loss_kpt: 0.152242 acc_pose: 0.698171 loss: 0.152242 2022/09/20 12:09:52 - mmengine - INFO - Epoch(train) [138][200/293] lr: 5.000000e-04 eta: 7:12:39 time: 0.858531 data_time: 0.112255 memory: 3324 loss_kpt: 0.149092 acc_pose: 0.750978 loss: 0.149092 2022/09/20 12:10:38 - mmengine - INFO - Epoch(train) [138][250/293] lr: 5.000000e-04 eta: 7:11:30 time: 0.922066 data_time: 0.103283 memory: 3324 loss_kpt: 0.151064 acc_pose: 0.751583 loss: 0.151064 2022/09/20 12:11:13 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:11:13 - mmengine - INFO - Saving checkpoint at 138 epochs 2022/09/20 12:12:04 - mmengine - INFO - Epoch(train) [139][50/293] lr: 5.000000e-04 eta: 7:09:01 time: 0.959622 data_time: 0.120678 memory: 3324 loss_kpt: 0.150952 acc_pose: 0.693038 loss: 0.150952 2022/09/20 12:12:55 - mmengine - INFO - Epoch(train) [139][100/293] lr: 5.000000e-04 eta: 7:07:55 time: 1.021675 data_time: 0.101017 memory: 3324 loss_kpt: 0.152384 acc_pose: 0.733611 loss: 0.152384 2022/09/20 12:13:54 - mmengine - INFO - Epoch(train) [139][150/293] lr: 5.000000e-04 eta: 7:06:53 time: 1.182758 data_time: 0.103022 memory: 3324 loss_kpt: 0.152045 acc_pose: 0.725828 loss: 0.152045 2022/09/20 12:14:27 - mmengine - INFO - Epoch(train) [139][200/293] lr: 5.000000e-04 eta: 7:05:37 time: 0.651056 data_time: 0.147240 memory: 3324 loss_kpt: 0.152362 acc_pose: 0.729407 loss: 0.152362 2022/09/20 12:14:53 - mmengine - INFO - Epoch(train) [139][250/293] lr: 5.000000e-04 eta: 7:04:18 time: 0.522540 data_time: 0.102421 memory: 3324 loss_kpt: 0.151437 acc_pose: 0.754019 loss: 0.151437 2022/09/20 12:15:28 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:15:28 - mmengine - INFO - Saving checkpoint at 139 epochs 2022/09/20 12:16:15 - mmengine - INFO - Epoch(train) [140][50/293] lr: 5.000000e-04 eta: 7:01:49 time: 0.893591 data_time: 0.346340 memory: 3324 loss_kpt: 0.148354 acc_pose: 0.782039 loss: 0.148354 2022/09/20 12:17:11 - mmengine - INFO - Epoch(train) [140][100/293] lr: 5.000000e-04 eta: 7:00:46 time: 1.107726 data_time: 0.165552 memory: 3324 loss_kpt: 0.151798 acc_pose: 0.693282 loss: 0.151798 2022/09/20 12:18:02 - mmengine - INFO - Epoch(train) [140][150/293] lr: 5.000000e-04 eta: 6:59:40 time: 1.024100 data_time: 0.127554 memory: 3324 loss_kpt: 0.154030 acc_pose: 0.682188 loss: 0.154030 2022/09/20 12:18:46 - mmengine - INFO - Epoch(train) [140][200/293] lr: 5.000000e-04 eta: 6:58:30 time: 0.885296 data_time: 0.358870 memory: 3324 loss_kpt: 0.152673 acc_pose: 0.727035 loss: 0.152673 2022/09/20 12:19:30 - mmengine - INFO - Epoch(train) [140][250/293] lr: 5.000000e-04 eta: 6:57:21 time: 0.878204 data_time: 0.135177 memory: 3324 loss_kpt: 0.151478 acc_pose: 0.691159 loss: 0.151478 2022/09/20 12:19:50 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:20:02 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:20:02 - mmengine - INFO - Saving checkpoint at 140 epochs 2022/09/20 12:21:04 - mmengine - INFO - Epoch(val) [140][50/407] eta: 0:07:02 time: 1.182649 data_time: 1.150565 memory: 3324 2022/09/20 12:22:03 - mmengine - INFO - Epoch(val) [140][100/407] eta: 0:05:58 time: 1.168422 data_time: 1.121079 memory: 400 2022/09/20 12:23:02 - mmengine - INFO - Epoch(val) [140][150/407] eta: 0:05:03 time: 1.179109 data_time: 1.129213 memory: 400 2022/09/20 12:24:01 - mmengine - INFO - Epoch(val) [140][200/407] eta: 0:04:04 time: 1.180093 data_time: 1.138110 memory: 400 2022/09/20 12:25:00 - mmengine - INFO - Epoch(val) [140][250/407] eta: 0:03:04 time: 1.174615 data_time: 1.142441 memory: 400 2022/09/20 12:26:00 - mmengine - INFO - Epoch(val) [140][300/407] eta: 0:02:08 time: 1.198629 data_time: 1.144256 memory: 400 2022/09/20 12:26:58 - mmengine - INFO - Epoch(val) [140][350/407] eta: 0:01:06 time: 1.162079 data_time: 1.106694 memory: 400 2022/09/20 12:27:56 - mmengine - INFO - Epoch(val) [140][400/407] eta: 0:00:08 time: 1.176479 data_time: 1.126935 memory: 400 2022/09/20 12:28:51 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 12:29:09 - mmengine - INFO - Epoch(val) [140][407/407] coco/AP: 0.589840 coco/AP .5: 0.838846 coco/AP .75: 0.661050 coco/AP (M): 0.557612 coco/AP (L): 0.649716 coco/AR: 0.648882 coco/AR .5: 0.887122 coco/AR .75: 0.713791 coco/AR (M): 0.605053 coco/AR (L): 0.710962 2022/09/20 12:30:46 - mmengine - INFO - Epoch(train) [141][50/293] lr: 5.000000e-04 eta: 6:55:19 time: 1.933295 data_time: 0.154009 memory: 3324 loss_kpt: 0.151624 acc_pose: 0.672478 loss: 0.151624 2022/09/20 12:31:31 - mmengine - INFO - Epoch(train) [141][100/293] lr: 5.000000e-04 eta: 6:54:10 time: 0.895742 data_time: 0.098222 memory: 3324 loss_kpt: 0.152833 acc_pose: 0.705198 loss: 0.152833 2022/09/20 12:32:05 - mmengine - INFO - Epoch(train) [141][150/293] lr: 5.000000e-04 eta: 6:52:56 time: 0.675224 data_time: 0.139358 memory: 3324 loss_kpt: 0.150923 acc_pose: 0.708229 loss: 0.150923 2022/09/20 12:32:38 - mmengine - INFO - Epoch(train) [141][200/293] lr: 5.000000e-04 eta: 6:51:42 time: 0.676881 data_time: 0.104767 memory: 3324 loss_kpt: 0.149316 acc_pose: 0.658889 loss: 0.149316 2022/09/20 12:33:26 - mmengine - INFO - Epoch(train) [141][250/293] lr: 5.000000e-04 eta: 6:50:34 time: 0.948719 data_time: 0.104736 memory: 3324 loss_kpt: 0.152387 acc_pose: 0.656076 loss: 0.152387 2022/09/20 12:34:04 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:34:04 - mmengine - INFO - Saving checkpoint at 141 epochs 2022/09/20 12:34:48 - mmengine - INFO - Epoch(train) [142][50/293] lr: 5.000000e-04 eta: 6:48:06 time: 0.824253 data_time: 0.435357 memory: 3324 loss_kpt: 0.149789 acc_pose: 0.733224 loss: 0.149789 2022/09/20 12:35:46 - mmengine - INFO - Epoch(train) [142][100/293] lr: 5.000000e-04 eta: 6:47:04 time: 1.151494 data_time: 0.404312 memory: 3324 loss_kpt: 0.150632 acc_pose: 0.766501 loss: 0.150632 2022/09/20 12:36:27 - mmengine - INFO - Epoch(train) [142][150/293] lr: 5.000000e-04 eta: 6:45:54 time: 0.821651 data_time: 0.095055 memory: 3324 loss_kpt: 0.151135 acc_pose: 0.738278 loss: 0.151135 2022/09/20 12:37:17 - mmengine - INFO - Epoch(train) [142][200/293] lr: 5.000000e-04 eta: 6:44:48 time: 1.002458 data_time: 0.112525 memory: 3324 loss_kpt: 0.153735 acc_pose: 0.730845 loss: 0.153735 2022/09/20 12:37:49 - mmengine - INFO - Epoch(train) [142][250/293] lr: 5.000000e-04 eta: 6:43:34 time: 0.634601 data_time: 0.201510 memory: 3324 loss_kpt: 0.150043 acc_pose: 0.773318 loss: 0.150043 2022/09/20 12:38:11 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:38:12 - mmengine - INFO - Saving checkpoint at 142 epochs 2022/09/20 12:39:26 - mmengine - INFO - Epoch(train) [143][50/293] lr: 5.000000e-04 eta: 6:41:21 time: 1.444814 data_time: 0.301018 memory: 3324 loss_kpt: 0.149817 acc_pose: 0.705452 loss: 0.149817 2022/09/20 12:40:12 - mmengine - INFO - Epoch(train) [143][100/293] lr: 5.000000e-04 eta: 6:40:14 time: 0.907024 data_time: 0.097535 memory: 3324 loss_kpt: 0.149780 acc_pose: 0.671511 loss: 0.149780 2022/09/20 12:40:54 - mmengine - INFO - Epoch(train) [143][150/293] lr: 5.000000e-04 eta: 6:39:04 time: 0.847600 data_time: 0.197741 memory: 3324 loss_kpt: 0.149884 acc_pose: 0.745803 loss: 0.149884 2022/09/20 12:41:24 - mmengine - INFO - Epoch(train) [143][200/293] lr: 5.000000e-04 eta: 6:37:49 time: 0.598950 data_time: 0.103189 memory: 3324 loss_kpt: 0.147678 acc_pose: 0.716803 loss: 0.147678 2022/09/20 12:42:14 - mmengine - INFO - Epoch(train) [143][250/293] lr: 5.000000e-04 eta: 6:36:44 time: 1.010600 data_time: 0.162733 memory: 3324 loss_kpt: 0.153047 acc_pose: 0.715803 loss: 0.153047 2022/09/20 12:42:53 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:42:53 - mmengine - INFO - Saving checkpoint at 143 epochs 2022/09/20 12:43:37 - mmengine - INFO - Epoch(train) [144][50/293] lr: 5.000000e-04 eta: 6:34:18 time: 0.826942 data_time: 0.172569 memory: 3324 loss_kpt: 0.153844 acc_pose: 0.681833 loss: 0.153844 2022/09/20 12:44:14 - mmengine - INFO - Epoch(train) [144][100/293] lr: 5.000000e-04 eta: 6:33:07 time: 0.740909 data_time: 0.116929 memory: 3324 loss_kpt: 0.149440 acc_pose: 0.712234 loss: 0.149440 2022/09/20 12:44:15 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:44:40 - mmengine - INFO - Epoch(train) [144][150/293] lr: 5.000000e-04 eta: 6:31:51 time: 0.521671 data_time: 0.115103 memory: 3324 loss_kpt: 0.150931 acc_pose: 0.756252 loss: 0.150931 2022/09/20 12:45:22 - mmengine - INFO - Epoch(train) [144][200/293] lr: 5.000000e-04 eta: 6:30:42 time: 0.834726 data_time: 0.161284 memory: 3324 loss_kpt: 0.150097 acc_pose: 0.687508 loss: 0.150097 2022/09/20 12:46:04 - mmengine - INFO - Epoch(train) [144][250/293] lr: 5.000000e-04 eta: 6:29:33 time: 0.847495 data_time: 0.349316 memory: 3324 loss_kpt: 0.149844 acc_pose: 0.745629 loss: 0.149844 2022/09/20 12:46:31 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:46:31 - mmengine - INFO - Saving checkpoint at 144 epochs 2022/09/20 12:47:06 - mmengine - INFO - Epoch(train) [145][50/293] lr: 5.000000e-04 eta: 6:27:04 time: 0.628816 data_time: 0.177932 memory: 3324 loss_kpt: 0.148695 acc_pose: 0.742360 loss: 0.148695 2022/09/20 12:47:35 - mmengine - INFO - Epoch(train) [145][100/293] lr: 5.000000e-04 eta: 6:25:50 time: 0.587557 data_time: 0.115094 memory: 3324 loss_kpt: 0.151442 acc_pose: 0.733748 loss: 0.151442 2022/09/20 12:48:12 - mmengine - INFO - Epoch(train) [145][150/293] lr: 5.000000e-04 eta: 6:24:39 time: 0.731386 data_time: 0.108056 memory: 3324 loss_kpt: 0.150365 acc_pose: 0.754762 loss: 0.150365 2022/09/20 12:49:00 - mmengine - INFO - Epoch(train) [145][200/293] lr: 5.000000e-04 eta: 6:23:34 time: 0.972907 data_time: 0.440453 memory: 3324 loss_kpt: 0.152009 acc_pose: 0.749565 loss: 0.152009 2022/09/20 12:49:40 - mmengine - INFO - Epoch(train) [145][250/293] lr: 5.000000e-04 eta: 6:22:25 time: 0.792562 data_time: 0.429835 memory: 3324 loss_kpt: 0.150731 acc_pose: 0.750036 loss: 0.150731 2022/09/20 12:50:08 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:50:08 - mmengine - INFO - Saving checkpoint at 145 epochs 2022/09/20 12:50:51 - mmengine - INFO - Epoch(train) [146][50/293] lr: 5.000000e-04 eta: 6:20:01 time: 0.807827 data_time: 0.306595 memory: 3324 loss_kpt: 0.149434 acc_pose: 0.812490 loss: 0.149434 2022/09/20 12:51:15 - mmengine - INFO - Epoch(train) [146][100/293] lr: 5.000000e-04 eta: 6:18:45 time: 0.489094 data_time: 0.146197 memory: 3324 loss_kpt: 0.150227 acc_pose: 0.686949 loss: 0.150227 2022/09/20 12:51:54 - mmengine - INFO - Epoch(train) [146][150/293] lr: 5.000000e-04 eta: 6:17:36 time: 0.769362 data_time: 0.259959 memory: 3324 loss_kpt: 0.151992 acc_pose: 0.741298 loss: 0.151992 2022/09/20 12:52:25 - mmengine - INFO - Epoch(train) [146][200/293] lr: 5.000000e-04 eta: 6:16:23 time: 0.630257 data_time: 0.101015 memory: 3324 loss_kpt: 0.147238 acc_pose: 0.751285 loss: 0.147238 2022/09/20 12:53:08 - mmengine - INFO - Epoch(train) [146][250/293] lr: 5.000000e-04 eta: 6:15:15 time: 0.848711 data_time: 0.170060 memory: 3324 loss_kpt: 0.149653 acc_pose: 0.797934 loss: 0.149653 2022/09/20 12:53:39 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:53:39 - mmengine - INFO - Saving checkpoint at 146 epochs 2022/09/20 12:54:13 - mmengine - INFO - Epoch(train) [147][50/293] lr: 5.000000e-04 eta: 6:12:49 time: 0.632847 data_time: 0.119813 memory: 3324 loss_kpt: 0.147940 acc_pose: 0.739225 loss: 0.147940 2022/09/20 12:54:53 - mmengine - INFO - Epoch(train) [147][100/293] lr: 5.000000e-04 eta: 6:11:41 time: 0.804339 data_time: 0.107982 memory: 3324 loss_kpt: 0.150690 acc_pose: 0.739653 loss: 0.150690 2022/09/20 12:55:28 - mmengine - INFO - Epoch(train) [147][150/293] lr: 5.000000e-04 eta: 6:10:30 time: 0.703794 data_time: 0.096315 memory: 3324 loss_kpt: 0.147710 acc_pose: 0.675544 loss: 0.147710 2022/09/20 12:56:24 - mmengine - INFO - Epoch(train) [147][200/293] lr: 5.000000e-04 eta: 6:09:29 time: 1.116205 data_time: 0.133016 memory: 3324 loss_kpt: 0.148386 acc_pose: 0.753469 loss: 0.148386 2022/09/20 12:56:43 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:56:58 - mmengine - INFO - Epoch(train) [147][250/293] lr: 5.000000e-04 eta: 6:08:18 time: 0.679269 data_time: 0.099314 memory: 3324 loss_kpt: 0.151554 acc_pose: 0.706880 loss: 0.151554 2022/09/20 12:57:28 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 12:57:28 - mmengine - INFO - Saving checkpoint at 147 epochs 2022/09/20 12:58:16 - mmengine - INFO - Epoch(train) [148][50/293] lr: 5.000000e-04 eta: 6:05:59 time: 0.891279 data_time: 0.130803 memory: 3324 loss_kpt: 0.150420 acc_pose: 0.718267 loss: 0.150420 2022/09/20 12:58:54 - mmengine - INFO - Epoch(train) [148][100/293] lr: 5.000000e-04 eta: 6:04:50 time: 0.759995 data_time: 0.147206 memory: 3324 loss_kpt: 0.149666 acc_pose: 0.706829 loss: 0.149666 2022/09/20 12:59:25 - mmengine - INFO - Epoch(train) [148][150/293] lr: 5.000000e-04 eta: 6:03:38 time: 0.620307 data_time: 0.216134 memory: 3324 loss_kpt: 0.149323 acc_pose: 0.693134 loss: 0.149323 2022/09/20 13:00:14 - mmengine - INFO - Epoch(train) [148][200/293] lr: 5.000000e-04 eta: 6:02:34 time: 0.984160 data_time: 0.554070 memory: 3324 loss_kpt: 0.146563 acc_pose: 0.682903 loss: 0.146563 2022/09/20 13:01:00 - mmengine - INFO - Epoch(train) [148][250/293] lr: 5.000000e-04 eta: 6:01:29 time: 0.915565 data_time: 0.530811 memory: 3324 loss_kpt: 0.148034 acc_pose: 0.699861 loss: 0.148034 2022/09/20 13:01:30 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:01:30 - mmengine - INFO - Saving checkpoint at 148 epochs 2022/09/20 13:02:10 - mmengine - INFO - Epoch(train) [149][50/293] lr: 5.000000e-04 eta: 5:59:08 time: 0.758535 data_time: 0.217838 memory: 3324 loss_kpt: 0.151684 acc_pose: 0.696549 loss: 0.151684 2022/09/20 13:02:44 - mmengine - INFO - Epoch(train) [149][100/293] lr: 5.000000e-04 eta: 5:57:57 time: 0.671170 data_time: 0.093159 memory: 3324 loss_kpt: 0.147449 acc_pose: 0.756083 loss: 0.147449 2022/09/20 13:03:17 - mmengine - INFO - Epoch(train) [149][150/293] lr: 5.000000e-04 eta: 5:56:47 time: 0.655075 data_time: 0.105228 memory: 3324 loss_kpt: 0.145492 acc_pose: 0.717377 loss: 0.145492 2022/09/20 13:03:43 - mmengine - INFO - Epoch(train) [149][200/293] lr: 5.000000e-04 eta: 5:55:34 time: 0.521944 data_time: 0.095403 memory: 3324 loss_kpt: 0.146213 acc_pose: 0.688747 loss: 0.146213 2022/09/20 13:04:20 - mmengine - INFO - Epoch(train) [149][250/293] lr: 5.000000e-04 eta: 5:54:25 time: 0.735257 data_time: 0.106931 memory: 3324 loss_kpt: 0.149298 acc_pose: 0.717660 loss: 0.149298 2022/09/20 13:04:49 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:04:49 - mmengine - INFO - Saving checkpoint at 149 epochs 2022/09/20 13:05:27 - mmengine - INFO - Epoch(train) [150][50/293] lr: 5.000000e-04 eta: 5:52:04 time: 0.712175 data_time: 0.175116 memory: 3324 loss_kpt: 0.146921 acc_pose: 0.683243 loss: 0.146921 2022/09/20 13:06:04 - mmengine - INFO - Epoch(train) [150][100/293] lr: 5.000000e-04 eta: 5:50:56 time: 0.735267 data_time: 0.104759 memory: 3324 loss_kpt: 0.148650 acc_pose: 0.710955 loss: 0.148650 2022/09/20 13:06:49 - mmengine - INFO - Epoch(train) [150][150/293] lr: 5.000000e-04 eta: 5:49:51 time: 0.906404 data_time: 0.113345 memory: 3324 loss_kpt: 0.150675 acc_pose: 0.682465 loss: 0.150675 2022/09/20 13:07:38 - mmengine - INFO - Epoch(train) [150][200/293] lr: 5.000000e-04 eta: 5:48:48 time: 0.979549 data_time: 0.094029 memory: 3324 loss_kpt: 0.150278 acc_pose: 0.711934 loss: 0.150278 2022/09/20 13:08:21 - mmengine - INFO - Epoch(train) [150][250/293] lr: 5.000000e-04 eta: 5:47:42 time: 0.861359 data_time: 0.205797 memory: 3324 loss_kpt: 0.151016 acc_pose: 0.730365 loss: 0.151016 2022/09/20 13:08:55 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:08:55 - mmengine - INFO - Saving checkpoint at 150 epochs 2022/09/20 13:09:55 - mmengine - INFO - Epoch(val) [150][50/407] eta: 0:06:39 time: 1.118701 data_time: 1.076958 memory: 3324 2022/09/20 13:10:53 - mmengine - INFO - Epoch(val) [150][100/407] eta: 0:05:59 time: 1.170273 data_time: 1.130151 memory: 400 2022/09/20 13:11:51 - mmengine - INFO - Epoch(val) [150][150/407] eta: 0:04:57 time: 1.157373 data_time: 1.097371 memory: 400 2022/09/20 13:12:49 - mmengine - INFO - Epoch(val) [150][200/407] eta: 0:04:02 time: 1.170376 data_time: 1.101178 memory: 400 2022/09/20 13:13:45 - mmengine - INFO - Epoch(val) [150][250/407] eta: 0:02:55 time: 1.114982 data_time: 1.057638 memory: 400 2022/09/20 13:14:44 - mmengine - INFO - Epoch(val) [150][300/407] eta: 0:02:05 time: 1.169605 data_time: 1.101862 memory: 400 2022/09/20 13:15:41 - mmengine - INFO - Epoch(val) [150][350/407] eta: 0:01:05 time: 1.141481 data_time: 1.083504 memory: 400 2022/09/20 13:16:38 - mmengine - INFO - Epoch(val) [150][400/407] eta: 0:00:07 time: 1.141036 data_time: 1.094827 memory: 400 2022/09/20 13:17:34 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 13:17:52 - mmengine - INFO - Epoch(val) [150][407/407] coco/AP: 0.594480 coco/AP .5: 0.845871 coco/AP .75: 0.663136 coco/AP (M): 0.559801 coco/AP (L): 0.655780 coco/AR: 0.653574 coco/AR .5: 0.892160 coco/AR .75: 0.717569 coco/AR (M): 0.607621 coco/AR (L): 0.718618 2022/09/20 13:17:52 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_130.pth is removed 2022/09/20 13:17:55 - mmengine - INFO - The best checkpoint with 0.5945 coco/AP at 150 epoch is saved to best_coco/AP_epoch_150.pth. 2022/09/20 13:19:17 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:19:17 - mmengine - INFO - Epoch(train) [151][50/293] lr: 5.000000e-04 eta: 5:45:41 time: 1.649013 data_time: 0.132376 memory: 3324 loss_kpt: 0.149816 acc_pose: 0.689492 loss: 0.149816 2022/09/20 13:19:55 - mmengine - INFO - Epoch(train) [151][100/293] lr: 5.000000e-04 eta: 5:44:33 time: 0.757283 data_time: 0.202394 memory: 3324 loss_kpt: 0.151634 acc_pose: 0.802540 loss: 0.151634 2022/09/20 13:20:50 - mmengine - INFO - Epoch(train) [151][150/293] lr: 5.000000e-04 eta: 5:43:32 time: 1.093015 data_time: 0.105349 memory: 3324 loss_kpt: 0.148736 acc_pose: 0.727919 loss: 0.148736 2022/09/20 13:21:29 - mmengine - INFO - Epoch(train) [151][200/293] lr: 5.000000e-04 eta: 5:42:26 time: 0.797922 data_time: 0.195209 memory: 3324 loss_kpt: 0.149796 acc_pose: 0.746994 loss: 0.149796 2022/09/20 13:22:13 - mmengine - INFO - Epoch(train) [151][250/293] lr: 5.000000e-04 eta: 5:41:20 time: 0.862711 data_time: 0.099276 memory: 3324 loss_kpt: 0.149474 acc_pose: 0.753868 loss: 0.149474 2022/09/20 13:22:54 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:22:54 - mmengine - INFO - Saving checkpoint at 151 epochs 2022/09/20 13:23:25 - mmengine - INFO - Epoch(train) [152][50/293] lr: 5.000000e-04 eta: 5:38:58 time: 0.563187 data_time: 0.152376 memory: 3324 loss_kpt: 0.145922 acc_pose: 0.749620 loss: 0.145922 2022/09/20 13:24:03 - mmengine - INFO - Epoch(train) [152][100/293] lr: 5.000000e-04 eta: 5:37:51 time: 0.755356 data_time: 0.230771 memory: 3324 loss_kpt: 0.147961 acc_pose: 0.669627 loss: 0.147961 2022/09/20 13:24:42 - mmengine - INFO - Epoch(train) [152][150/293] lr: 5.000000e-04 eta: 5:36:45 time: 0.789071 data_time: 0.120999 memory: 3324 loss_kpt: 0.146400 acc_pose: 0.756685 loss: 0.146400 2022/09/20 13:25:18 - mmengine - INFO - Epoch(train) [152][200/293] lr: 5.000000e-04 eta: 5:35:37 time: 0.710928 data_time: 0.125267 memory: 3324 loss_kpt: 0.149295 acc_pose: 0.750699 loss: 0.149295 2022/09/20 13:26:00 - mmengine - INFO - Epoch(train) [152][250/293] lr: 5.000000e-04 eta: 5:34:32 time: 0.850518 data_time: 0.422053 memory: 3324 loss_kpt: 0.150444 acc_pose: 0.750882 loss: 0.150444 2022/09/20 13:26:34 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:26:34 - mmengine - INFO - Saving checkpoint at 152 epochs 2022/09/20 13:27:28 - mmengine - INFO - Epoch(train) [153][50/293] lr: 5.000000e-04 eta: 5:32:20 time: 1.026728 data_time: 0.470831 memory: 3324 loss_kpt: 0.147346 acc_pose: 0.765071 loss: 0.147346 2022/09/20 13:28:14 - mmengine - INFO - Epoch(train) [153][100/293] lr: 5.000000e-04 eta: 5:31:16 time: 0.919709 data_time: 0.108829 memory: 3324 loss_kpt: 0.148809 acc_pose: 0.732716 loss: 0.148809 2022/09/20 13:28:58 - mmengine - INFO - Epoch(train) [153][150/293] lr: 5.000000e-04 eta: 5:30:12 time: 0.889104 data_time: 0.301595 memory: 3324 loss_kpt: 0.147516 acc_pose: 0.698049 loss: 0.147516 2022/09/20 13:29:37 - mmengine - INFO - Epoch(train) [153][200/293] lr: 5.000000e-04 eta: 5:29:06 time: 0.788876 data_time: 0.111349 memory: 3324 loss_kpt: 0.148970 acc_pose: 0.693103 loss: 0.148970 2022/09/20 13:30:10 - mmengine - INFO - Epoch(train) [153][250/293] lr: 5.000000e-04 eta: 5:27:57 time: 0.642200 data_time: 0.125867 memory: 3324 loss_kpt: 0.146757 acc_pose: 0.735884 loss: 0.146757 2022/09/20 13:30:59 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:30:59 - mmengine - INFO - Saving checkpoint at 153 epochs 2022/09/20 13:31:39 - mmengine - INFO - Epoch(train) [154][50/293] lr: 5.000000e-04 eta: 5:25:41 time: 0.761183 data_time: 0.124505 memory: 3324 loss_kpt: 0.147670 acc_pose: 0.728521 loss: 0.147670 2022/09/20 13:32:37 - mmengine - INFO - Epoch(train) [154][100/293] lr: 5.000000e-04 eta: 5:24:42 time: 1.148556 data_time: 0.098390 memory: 3324 loss_kpt: 0.149398 acc_pose: 0.706632 loss: 0.149398 2022/09/20 13:33:24 - mmengine - INFO - Epoch(train) [154][150/293] lr: 5.000000e-04 eta: 5:23:39 time: 0.945592 data_time: 0.101839 memory: 3324 loss_kpt: 0.144707 acc_pose: 0.704703 loss: 0.144707 2022/09/20 13:33:44 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:34:14 - mmengine - INFO - Epoch(train) [154][200/293] lr: 5.000000e-04 eta: 5:22:38 time: 1.004068 data_time: 0.362181 memory: 3324 loss_kpt: 0.151326 acc_pose: 0.772756 loss: 0.151326 2022/09/20 13:34:47 - mmengine - INFO - Epoch(train) [154][250/293] lr: 5.000000e-04 eta: 5:21:29 time: 0.654913 data_time: 0.103543 memory: 3324 loss_kpt: 0.149084 acc_pose: 0.735110 loss: 0.149084 2022/09/20 13:35:30 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:35:30 - mmengine - INFO - Saving checkpoint at 154 epochs 2022/09/20 13:36:14 - mmengine - INFO - Epoch(train) [155][50/293] lr: 5.000000e-04 eta: 5:19:16 time: 0.827699 data_time: 0.177853 memory: 3324 loss_kpt: 0.149693 acc_pose: 0.722181 loss: 0.149693 2022/09/20 13:36:42 - mmengine - INFO - Epoch(train) [155][100/293] lr: 5.000000e-04 eta: 5:18:07 time: 0.576373 data_time: 0.109166 memory: 3324 loss_kpt: 0.147380 acc_pose: 0.686315 loss: 0.147380 2022/09/20 13:37:32 - mmengine - INFO - Epoch(train) [155][150/293] lr: 5.000000e-04 eta: 5:17:05 time: 0.981623 data_time: 0.247994 memory: 3324 loss_kpt: 0.151076 acc_pose: 0.712310 loss: 0.151076 2022/09/20 13:38:17 - mmengine - INFO - Epoch(train) [155][200/293] lr: 5.000000e-04 eta: 5:16:01 time: 0.903032 data_time: 0.142520 memory: 3324 loss_kpt: 0.147080 acc_pose: 0.719193 loss: 0.147080 2022/09/20 13:38:48 - mmengine - INFO - Epoch(train) [155][250/293] lr: 5.000000e-04 eta: 5:14:53 time: 0.626914 data_time: 0.137001 memory: 3324 loss_kpt: 0.148357 acc_pose: 0.740714 loss: 0.148357 2022/09/20 13:39:27 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:39:27 - mmengine - INFO - Saving checkpoint at 155 epochs 2022/09/20 13:40:13 - mmengine - INFO - Epoch(train) [156][50/293] lr: 5.000000e-04 eta: 5:12:41 time: 0.855327 data_time: 0.392449 memory: 3324 loss_kpt: 0.148506 acc_pose: 0.731795 loss: 0.148506 2022/09/20 13:41:02 - mmengine - INFO - Epoch(train) [156][100/293] lr: 5.000000e-04 eta: 5:11:40 time: 0.994727 data_time: 0.103586 memory: 3324 loss_kpt: 0.151216 acc_pose: 0.722335 loss: 0.151216 2022/09/20 13:41:39 - mmengine - INFO - Epoch(train) [156][150/293] lr: 5.000000e-04 eta: 5:10:34 time: 0.739549 data_time: 0.105266 memory: 3324 loss_kpt: 0.148040 acc_pose: 0.747655 loss: 0.148040 2022/09/20 13:42:28 - mmengine - INFO - Epoch(train) [156][200/293] lr: 5.000000e-04 eta: 5:09:32 time: 0.973913 data_time: 0.124389 memory: 3324 loss_kpt: 0.149166 acc_pose: 0.730012 loss: 0.149166 2022/09/20 13:42:58 - mmengine - INFO - Epoch(train) [156][250/293] lr: 5.000000e-04 eta: 5:08:24 time: 0.599317 data_time: 0.099145 memory: 3324 loss_kpt: 0.151622 acc_pose: 0.708523 loss: 0.151622 2022/09/20 13:43:45 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:43:45 - mmengine - INFO - Saving checkpoint at 156 epochs 2022/09/20 13:44:33 - mmengine - INFO - Epoch(train) [157][50/293] lr: 5.000000e-04 eta: 5:06:14 time: 0.924613 data_time: 0.331579 memory: 3324 loss_kpt: 0.146985 acc_pose: 0.721518 loss: 0.146985 2022/09/20 13:45:08 - mmengine - INFO - Epoch(train) [157][100/293] lr: 5.000000e-04 eta: 5:05:08 time: 0.692782 data_time: 0.096836 memory: 3324 loss_kpt: 0.145768 acc_pose: 0.747715 loss: 0.145768 2022/09/20 13:45:59 - mmengine - INFO - Epoch(train) [157][150/293] lr: 5.000000e-04 eta: 5:04:07 time: 1.021100 data_time: 0.101971 memory: 3324 loss_kpt: 0.147689 acc_pose: 0.751945 loss: 0.147689 2022/09/20 13:46:47 - mmengine - INFO - Epoch(train) [157][200/293] lr: 5.000000e-04 eta: 5:03:05 time: 0.949996 data_time: 0.099565 memory: 3324 loss_kpt: 0.148765 acc_pose: 0.686853 loss: 0.148765 2022/09/20 13:47:27 - mmengine - INFO - Epoch(train) [157][250/293] lr: 5.000000e-04 eta: 5:02:01 time: 0.806767 data_time: 0.166732 memory: 3324 loss_kpt: 0.147316 acc_pose: 0.710306 loss: 0.147316 2022/09/20 13:47:56 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:47:56 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:47:56 - mmengine - INFO - Saving checkpoint at 157 epochs 2022/09/20 13:48:37 - mmengine - INFO - Epoch(train) [158][50/293] lr: 5.000000e-04 eta: 4:59:49 time: 0.769128 data_time: 0.153223 memory: 3324 loss_kpt: 0.149707 acc_pose: 0.786939 loss: 0.149707 2022/09/20 13:49:18 - mmengine - INFO - Epoch(train) [158][100/293] lr: 5.000000e-04 eta: 4:58:45 time: 0.807756 data_time: 0.118160 memory: 3324 loss_kpt: 0.146515 acc_pose: 0.707476 loss: 0.146515 2022/09/20 13:49:55 - mmengine - INFO - Epoch(train) [158][150/293] lr: 5.000000e-04 eta: 4:57:40 time: 0.739723 data_time: 0.091084 memory: 3324 loss_kpt: 0.148807 acc_pose: 0.710738 loss: 0.148807 2022/09/20 13:50:33 - mmengine - INFO - Epoch(train) [158][200/293] lr: 5.000000e-04 eta: 4:56:35 time: 0.770492 data_time: 0.101395 memory: 3324 loss_kpt: 0.150593 acc_pose: 0.752042 loss: 0.150593 2022/09/20 13:51:16 - mmengine - INFO - Epoch(train) [158][250/293] lr: 5.000000e-04 eta: 4:55:32 time: 0.846299 data_time: 0.150331 memory: 3324 loss_kpt: 0.149868 acc_pose: 0.740695 loss: 0.149868 2022/09/20 13:51:58 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:51:58 - mmengine - INFO - Saving checkpoint at 158 epochs 2022/09/20 13:52:43 - mmengine - INFO - Epoch(train) [159][50/293] lr: 5.000000e-04 eta: 4:53:23 time: 0.850003 data_time: 0.144548 memory: 3324 loss_kpt: 0.147424 acc_pose: 0.749675 loss: 0.147424 2022/09/20 13:53:29 - mmengine - INFO - Epoch(train) [159][100/293] lr: 5.000000e-04 eta: 4:52:21 time: 0.926655 data_time: 0.102607 memory: 3324 loss_kpt: 0.148525 acc_pose: 0.747276 loss: 0.148525 2022/09/20 13:54:24 - mmengine - INFO - Epoch(train) [159][150/293] lr: 5.000000e-04 eta: 4:51:22 time: 1.086425 data_time: 0.168782 memory: 3324 loss_kpt: 0.148731 acc_pose: 0.717166 loss: 0.148731 2022/09/20 13:55:06 - mmengine - INFO - Epoch(train) [159][200/293] lr: 5.000000e-04 eta: 4:50:19 time: 0.849551 data_time: 0.109470 memory: 3324 loss_kpt: 0.148558 acc_pose: 0.752100 loss: 0.148558 2022/09/20 13:55:44 - mmengine - INFO - Epoch(train) [159][250/293] lr: 5.000000e-04 eta: 4:49:15 time: 0.756321 data_time: 0.190592 memory: 3324 loss_kpt: 0.149895 acc_pose: 0.738388 loss: 0.149895 2022/09/20 13:56:23 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 13:56:23 - mmengine - INFO - Saving checkpoint at 159 epochs 2022/09/20 13:57:10 - mmengine - INFO - Epoch(train) [160][50/293] lr: 5.000000e-04 eta: 4:47:07 time: 0.885024 data_time: 0.143943 memory: 3324 loss_kpt: 0.147336 acc_pose: 0.772357 loss: 0.147336 2022/09/20 13:57:43 - mmengine - INFO - Epoch(train) [160][100/293] lr: 5.000000e-04 eta: 4:46:01 time: 0.655654 data_time: 0.122751 memory: 3324 loss_kpt: 0.147822 acc_pose: 0.715851 loss: 0.147822 2022/09/20 13:58:21 - mmengine - INFO - Epoch(train) [160][150/293] lr: 5.000000e-04 eta: 4:44:57 time: 0.753552 data_time: 0.112941 memory: 3324 loss_kpt: 0.148035 acc_pose: 0.707981 loss: 0.148035 2022/09/20 13:59:15 - mmengine - INFO - Epoch(train) [160][200/293] lr: 5.000000e-04 eta: 4:43:58 time: 1.083749 data_time: 0.108829 memory: 3324 loss_kpt: 0.147188 acc_pose: 0.690599 loss: 0.147188 2022/09/20 13:59:55 - mmengine - INFO - Epoch(train) [160][250/293] lr: 5.000000e-04 eta: 4:42:54 time: 0.802555 data_time: 0.101927 memory: 3324 loss_kpt: 0.148095 acc_pose: 0.738910 loss: 0.148095 2022/09/20 14:00:24 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:00:24 - mmengine - INFO - Saving checkpoint at 160 epochs 2022/09/20 14:01:28 - mmengine - INFO - Epoch(val) [160][50/407] eta: 0:07:07 time: 1.196280 data_time: 1.164033 memory: 3324 2022/09/20 14:02:26 - mmengine - INFO - Epoch(val) [160][100/407] eta: 0:05:57 time: 1.165710 data_time: 1.128317 memory: 400 2022/09/20 14:03:26 - mmengine - INFO - Epoch(val) [160][150/407] eta: 0:05:07 time: 1.196422 data_time: 1.143492 memory: 400 2022/09/20 14:04:24 - mmengine - INFO - Epoch(val) [160][200/407] eta: 0:04:02 time: 1.170873 data_time: 1.131639 memory: 400 2022/09/20 14:05:23 - mmengine - INFO - Epoch(val) [160][250/407] eta: 0:03:05 time: 1.179903 data_time: 1.144242 memory: 400 2022/09/20 14:06:23 - mmengine - INFO - Epoch(val) [160][300/407] eta: 0:02:06 time: 1.185514 data_time: 1.145673 memory: 400 2022/09/20 14:07:20 - mmengine - INFO - Epoch(val) [160][350/407] eta: 0:01:05 time: 1.146846 data_time: 1.090388 memory: 400 2022/09/20 14:08:19 - mmengine - INFO - Epoch(val) [160][400/407] eta: 0:00:08 time: 1.185293 data_time: 1.133093 memory: 400 2022/09/20 14:09:15 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 14:09:34 - mmengine - INFO - Epoch(val) [160][407/407] coco/AP: 0.599704 coco/AP .5: 0.848278 coco/AP .75: 0.672332 coco/AP (M): 0.565967 coco/AP (L): 0.658714 coco/AR: 0.658186 coco/AR .5: 0.894994 coco/AR .75: 0.725126 coco/AR (M): 0.614313 coco/AR (L): 0.720253 2022/09/20 14:09:34 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_150.pth is removed 2022/09/20 14:09:36 - mmengine - INFO - The best checkpoint with 0.5997 coco/AP at 160 epoch is saved to best_coco/AP_epoch_160.pth. 2022/09/20 14:10:50 - mmengine - INFO - Epoch(train) [161][50/293] lr: 5.000000e-04 eta: 4:40:56 time: 1.464974 data_time: 0.427753 memory: 3324 loss_kpt: 0.147830 acc_pose: 0.742522 loss: 0.147830 2022/09/20 14:11:25 - mmengine - INFO - Epoch(train) [161][100/293] lr: 5.000000e-04 eta: 4:39:52 time: 0.700204 data_time: 0.100523 memory: 3324 loss_kpt: 0.150749 acc_pose: 0.706904 loss: 0.150749 2022/09/20 14:11:40 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:12:06 - mmengine - INFO - Epoch(train) [161][150/293] lr: 5.000000e-04 eta: 4:38:49 time: 0.823005 data_time: 0.283333 memory: 3324 loss_kpt: 0.148721 acc_pose: 0.652418 loss: 0.148721 2022/09/20 14:12:49 - mmengine - INFO - Epoch(train) [161][200/293] lr: 5.000000e-04 eta: 4:37:47 time: 0.859916 data_time: 0.187507 memory: 3324 loss_kpt: 0.149698 acc_pose: 0.705353 loss: 0.149698 2022/09/20 14:13:34 - mmengine - INFO - Epoch(train) [161][250/293] lr: 5.000000e-04 eta: 4:36:45 time: 0.904315 data_time: 0.414669 memory: 3324 loss_kpt: 0.149707 acc_pose: 0.728432 loss: 0.149707 2022/09/20 14:14:23 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:14:23 - mmengine - INFO - Saving checkpoint at 161 epochs 2022/09/20 14:14:59 - mmengine - INFO - Epoch(train) [162][50/293] lr: 5.000000e-04 eta: 4:34:35 time: 0.667941 data_time: 0.130000 memory: 3324 loss_kpt: 0.147856 acc_pose: 0.717224 loss: 0.147856 2022/09/20 14:15:32 - mmengine - INFO - Epoch(train) [162][100/293] lr: 5.000000e-04 eta: 4:33:31 time: 0.666019 data_time: 0.118727 memory: 3324 loss_kpt: 0.147172 acc_pose: 0.742839 loss: 0.147172 2022/09/20 14:16:08 - mmengine - INFO - Epoch(train) [162][150/293] lr: 5.000000e-04 eta: 4:32:26 time: 0.713799 data_time: 0.109552 memory: 3324 loss_kpt: 0.151263 acc_pose: 0.729120 loss: 0.151263 2022/09/20 14:16:49 - mmengine - INFO - Epoch(train) [162][200/293] lr: 5.000000e-04 eta: 4:31:24 time: 0.832477 data_time: 0.139434 memory: 3324 loss_kpt: 0.150821 acc_pose: 0.767891 loss: 0.150821 2022/09/20 14:17:23 - mmengine - INFO - Epoch(train) [162][250/293] lr: 5.000000e-04 eta: 4:30:20 time: 0.676558 data_time: 0.108088 memory: 3324 loss_kpt: 0.146133 acc_pose: 0.719846 loss: 0.146133 2022/09/20 14:17:51 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:17:51 - mmengine - INFO - Saving checkpoint at 162 epochs 2022/09/20 14:18:28 - mmengine - INFO - Epoch(train) [163][50/293] lr: 5.000000e-04 eta: 4:28:11 time: 0.676461 data_time: 0.194727 memory: 3324 loss_kpt: 0.149730 acc_pose: 0.733507 loss: 0.149730 2022/09/20 14:18:53 - mmengine - INFO - Epoch(train) [163][100/293] lr: 5.000000e-04 eta: 4:27:04 time: 0.507482 data_time: 0.117891 memory: 3324 loss_kpt: 0.146594 acc_pose: 0.773307 loss: 0.146594 2022/09/20 14:19:31 - mmengine - INFO - Epoch(train) [163][150/293] lr: 5.000000e-04 eta: 4:26:01 time: 0.768322 data_time: 0.125564 memory: 3324 loss_kpt: 0.150054 acc_pose: 0.654990 loss: 0.150054 2022/09/20 14:20:03 - mmengine - INFO - Epoch(train) [163][200/293] lr: 5.000000e-04 eta: 4:24:57 time: 0.634369 data_time: 0.108511 memory: 3324 loss_kpt: 0.151835 acc_pose: 0.726853 loss: 0.151835 2022/09/20 14:20:35 - mmengine - INFO - Epoch(train) [163][250/293] lr: 5.000000e-04 eta: 4:23:52 time: 0.631576 data_time: 0.115225 memory: 3324 loss_kpt: 0.150592 acc_pose: 0.763828 loss: 0.150592 2022/09/20 14:21:00 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:21:00 - mmengine - INFO - Saving checkpoint at 163 epochs 2022/09/20 14:21:32 - mmengine - INFO - Epoch(train) [164][50/293] lr: 5.000000e-04 eta: 4:21:43 time: 0.598198 data_time: 0.144335 memory: 3324 loss_kpt: 0.146243 acc_pose: 0.778848 loss: 0.146243 2022/09/20 14:22:04 - mmengine - INFO - Epoch(train) [164][100/293] lr: 5.000000e-04 eta: 4:20:39 time: 0.629565 data_time: 0.115237 memory: 3324 loss_kpt: 0.145891 acc_pose: 0.739253 loss: 0.145891 2022/09/20 14:22:44 - mmengine - INFO - Epoch(train) [164][150/293] lr: 5.000000e-04 eta: 4:19:37 time: 0.810818 data_time: 0.100499 memory: 3324 loss_kpt: 0.146075 acc_pose: 0.650146 loss: 0.146075 2022/09/20 14:23:21 - mmengine - INFO - Epoch(train) [164][200/293] lr: 5.000000e-04 eta: 4:18:34 time: 0.737981 data_time: 0.129940 memory: 3324 loss_kpt: 0.150179 acc_pose: 0.776449 loss: 0.150179 2022/09/20 14:23:53 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:24:02 - mmengine - INFO - Epoch(train) [164][250/293] lr: 5.000000e-04 eta: 4:17:32 time: 0.812039 data_time: 0.132311 memory: 3324 loss_kpt: 0.147776 acc_pose: 0.728871 loss: 0.147776 2022/09/20 14:24:44 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:24:44 - mmengine - INFO - Saving checkpoint at 164 epochs 2022/09/20 14:25:30 - mmengine - INFO - Epoch(train) [165][50/293] lr: 5.000000e-04 eta: 4:15:28 time: 0.878505 data_time: 0.120862 memory: 3324 loss_kpt: 0.148816 acc_pose: 0.672439 loss: 0.148816 2022/09/20 14:26:11 - mmengine - INFO - Epoch(train) [165][100/293] lr: 5.000000e-04 eta: 4:14:27 time: 0.810089 data_time: 0.104186 memory: 3324 loss_kpt: 0.144955 acc_pose: 0.749734 loss: 0.144955 2022/09/20 14:26:56 - mmengine - INFO - Epoch(train) [165][150/293] lr: 5.000000e-04 eta: 4:13:26 time: 0.895988 data_time: 0.108036 memory: 3324 loss_kpt: 0.148445 acc_pose: 0.794088 loss: 0.148445 2022/09/20 14:27:33 - mmengine - INFO - Epoch(train) [165][200/293] lr: 5.000000e-04 eta: 4:12:24 time: 0.754944 data_time: 0.102776 memory: 3324 loss_kpt: 0.150660 acc_pose: 0.730921 loss: 0.150660 2022/09/20 14:28:15 - mmengine - INFO - Epoch(train) [165][250/293] lr: 5.000000e-04 eta: 4:11:23 time: 0.839545 data_time: 0.105112 memory: 3324 loss_kpt: 0.151157 acc_pose: 0.704727 loss: 0.151157 2022/09/20 14:28:47 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:28:47 - mmengine - INFO - Saving checkpoint at 165 epochs 2022/09/20 14:29:40 - mmengine - INFO - Epoch(train) [166][50/293] lr: 5.000000e-04 eta: 4:09:21 time: 0.995440 data_time: 0.134565 memory: 3324 loss_kpt: 0.146954 acc_pose: 0.743749 loss: 0.146954 2022/09/20 14:30:33 - mmengine - INFO - Epoch(train) [166][100/293] lr: 5.000000e-04 eta: 4:08:23 time: 1.063023 data_time: 0.571681 memory: 3324 loss_kpt: 0.147361 acc_pose: 0.767642 loss: 0.147361 2022/09/20 14:31:11 - mmengine - INFO - Epoch(train) [166][150/293] lr: 5.000000e-04 eta: 4:07:21 time: 0.766656 data_time: 0.355860 memory: 3324 loss_kpt: 0.151500 acc_pose: 0.737955 loss: 0.151500 2022/09/20 14:31:43 - mmengine - INFO - Epoch(train) [166][200/293] lr: 5.000000e-04 eta: 4:06:18 time: 0.634887 data_time: 0.165138 memory: 3324 loss_kpt: 0.149438 acc_pose: 0.705144 loss: 0.149438 2022/09/20 14:32:38 - mmengine - INFO - Epoch(train) [166][250/293] lr: 5.000000e-04 eta: 4:05:20 time: 1.094428 data_time: 0.103753 memory: 3324 loss_kpt: 0.146647 acc_pose: 0.740504 loss: 0.146647 2022/09/20 14:33:09 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:33:09 - mmengine - INFO - Saving checkpoint at 166 epochs 2022/09/20 14:33:39 - mmengine - INFO - Epoch(train) [167][50/293] lr: 5.000000e-04 eta: 4:03:14 time: 0.546447 data_time: 0.181301 memory: 3324 loss_kpt: 0.150764 acc_pose: 0.699491 loss: 0.150764 2022/09/20 14:34:16 - mmengine - INFO - Epoch(train) [167][100/293] lr: 5.000000e-04 eta: 4:02:12 time: 0.741982 data_time: 0.104385 memory: 3324 loss_kpt: 0.150403 acc_pose: 0.772120 loss: 0.150403 2022/09/20 14:34:53 - mmengine - INFO - Epoch(train) [167][150/293] lr: 5.000000e-04 eta: 4:01:10 time: 0.738810 data_time: 0.100199 memory: 3324 loss_kpt: 0.148027 acc_pose: 0.690998 loss: 0.148027 2022/09/20 14:35:29 - mmengine - INFO - Epoch(train) [167][200/293] lr: 5.000000e-04 eta: 4:00:07 time: 0.720545 data_time: 0.100908 memory: 3324 loss_kpt: 0.147792 acc_pose: 0.723866 loss: 0.147792 2022/09/20 14:36:08 - mmengine - INFO - Epoch(train) [167][250/293] lr: 5.000000e-04 eta: 3:59:06 time: 0.789467 data_time: 0.096669 memory: 3324 loss_kpt: 0.145274 acc_pose: 0.751687 loss: 0.145274 2022/09/20 14:36:48 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:36:48 - mmengine - INFO - Saving checkpoint at 167 epochs 2022/09/20 14:37:19 - mmengine - INFO - Epoch(train) [168][50/293] lr: 5.000000e-04 eta: 3:57:01 time: 0.568782 data_time: 0.108602 memory: 3324 loss_kpt: 0.149421 acc_pose: 0.769293 loss: 0.149421 2022/09/20 14:37:43 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:38:01 - mmengine - INFO - Epoch(train) [168][100/293] lr: 5.000000e-04 eta: 3:56:01 time: 0.836166 data_time: 0.111654 memory: 3324 loss_kpt: 0.147295 acc_pose: 0.734222 loss: 0.147295 2022/09/20 14:38:47 - mmengine - INFO - Epoch(train) [168][150/293] lr: 5.000000e-04 eta: 3:55:01 time: 0.914325 data_time: 0.100179 memory: 3324 loss_kpt: 0.144225 acc_pose: 0.695882 loss: 0.144225 2022/09/20 14:39:21 - mmengine - INFO - Epoch(train) [168][200/293] lr: 5.000000e-04 eta: 3:53:59 time: 0.670799 data_time: 0.115294 memory: 3324 loss_kpt: 0.148238 acc_pose: 0.687552 loss: 0.148238 2022/09/20 14:40:03 - mmengine - INFO - Epoch(train) [168][250/293] lr: 5.000000e-04 eta: 3:52:59 time: 0.857424 data_time: 0.109824 memory: 3324 loss_kpt: 0.146652 acc_pose: 0.718023 loss: 0.146652 2022/09/20 14:40:29 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:40:29 - mmengine - INFO - Saving checkpoint at 168 epochs 2022/09/20 14:41:10 - mmengine - INFO - Epoch(train) [169][50/293] lr: 5.000000e-04 eta: 3:50:57 time: 0.764440 data_time: 0.151552 memory: 3324 loss_kpt: 0.149815 acc_pose: 0.752120 loss: 0.149815 2022/09/20 14:41:45 - mmengine - INFO - Epoch(train) [169][100/293] lr: 5.000000e-04 eta: 3:49:55 time: 0.708832 data_time: 0.118678 memory: 3324 loss_kpt: 0.151251 acc_pose: 0.728421 loss: 0.151251 2022/09/20 14:42:15 - mmengine - INFO - Epoch(train) [169][150/293] lr: 5.000000e-04 eta: 3:48:52 time: 0.588582 data_time: 0.114723 memory: 3324 loss_kpt: 0.144246 acc_pose: 0.698068 loss: 0.144246 2022/09/20 14:42:51 - mmengine - INFO - Epoch(train) [169][200/293] lr: 5.000000e-04 eta: 3:47:50 time: 0.728600 data_time: 0.109226 memory: 3324 loss_kpt: 0.148876 acc_pose: 0.668098 loss: 0.148876 2022/09/20 14:43:28 - mmengine - INFO - Epoch(train) [169][250/293] lr: 5.000000e-04 eta: 3:46:49 time: 0.726587 data_time: 0.097910 memory: 3324 loss_kpt: 0.146474 acc_pose: 0.735882 loss: 0.146474 2022/09/20 14:43:52 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:43:52 - mmengine - INFO - Saving checkpoint at 169 epochs 2022/09/20 14:44:31 - mmengine - INFO - Epoch(train) [170][50/293] lr: 5.000000e-04 eta: 3:44:47 time: 0.734107 data_time: 0.296843 memory: 3324 loss_kpt: 0.145291 acc_pose: 0.739357 loss: 0.145291 2022/09/20 14:45:33 - mmengine - INFO - Epoch(train) [170][100/293] lr: 5.000000e-04 eta: 3:43:52 time: 1.236096 data_time: 0.226112 memory: 3324 loss_kpt: 0.146268 acc_pose: 0.705228 loss: 0.146268 2022/09/20 14:46:14 - mmengine - INFO - Epoch(train) [170][150/293] lr: 5.000000e-04 eta: 3:42:52 time: 0.825161 data_time: 0.134806 memory: 3324 loss_kpt: 0.147070 acc_pose: 0.745094 loss: 0.147070 2022/09/20 14:47:17 - mmengine - INFO - Epoch(train) [170][200/293] lr: 5.000000e-04 eta: 3:41:57 time: 1.250951 data_time: 0.105376 memory: 3324 loss_kpt: 0.145220 acc_pose: 0.717232 loss: 0.145220 2022/09/20 14:48:02 - mmengine - INFO - Epoch(train) [170][250/293] lr: 5.000000e-04 eta: 3:40:59 time: 0.912267 data_time: 0.190885 memory: 3324 loss_kpt: 0.149850 acc_pose: 0.749914 loss: 0.149850 2022/09/20 14:48:33 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 14:48:33 - mmengine - INFO - Saving checkpoint at 170 epochs 2022/09/20 14:49:36 - mmengine - INFO - Epoch(val) [170][50/407] eta: 0:07:05 time: 1.190622 data_time: 1.128702 memory: 3324 2022/09/20 14:50:36 - mmengine - INFO - Epoch(val) [170][100/407] eta: 0:06:04 time: 1.187190 data_time: 1.146864 memory: 400 2022/09/20 14:51:34 - mmengine - INFO - Epoch(val) [170][150/407] eta: 0:05:01 time: 1.171317 data_time: 1.133788 memory: 400 2022/09/20 14:52:33 - mmengine - INFO - Epoch(val) [170][200/407] eta: 0:04:02 time: 1.173283 data_time: 1.125656 memory: 400 2022/09/20 14:53:32 - mmengine - INFO - Epoch(val) [170][250/407] eta: 0:03:07 time: 1.192132 data_time: 1.153647 memory: 400 2022/09/20 14:54:33 - mmengine - INFO - Epoch(val) [170][300/407] eta: 0:02:09 time: 1.210084 data_time: 1.161092 memory: 400 2022/09/20 14:55:34 - mmengine - INFO - Epoch(val) [170][350/407] eta: 0:01:09 time: 1.221018 data_time: 1.188683 memory: 400 2022/09/20 14:56:33 - mmengine - INFO - Epoch(val) [170][400/407] eta: 0:00:08 time: 1.173527 data_time: 1.114110 memory: 400 2022/09/20 14:57:29 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 14:57:48 - mmengine - INFO - Epoch(val) [170][407/407] coco/AP: 0.597032 coco/AP .5: 0.842766 coco/AP .75: 0.668856 coco/AP (M): 0.562014 coco/AP (L): 0.658567 coco/AR: 0.656329 coco/AR .5: 0.889484 coco/AR .75: 0.723079 coco/AR (M): 0.610407 coco/AR (L): 0.720736 2022/09/20 14:59:14 - mmengine - INFO - Epoch(train) [171][50/293] lr: 5.000000e-05 eta: 3:39:09 time: 1.727787 data_time: 0.578274 memory: 3324 loss_kpt: 0.148267 acc_pose: 0.756708 loss: 0.148267 2022/09/20 14:59:54 - mmengine - INFO - Epoch(train) [171][100/293] lr: 5.000000e-05 eta: 3:38:09 time: 0.788868 data_time: 0.097391 memory: 3324 loss_kpt: 0.146945 acc_pose: 0.738464 loss: 0.146945 2022/09/20 15:00:17 - mmengine - INFO - Epoch(train) [171][150/293] lr: 5.000000e-05 eta: 3:37:05 time: 0.470571 data_time: 0.123521 memory: 3324 loss_kpt: 0.144296 acc_pose: 0.801706 loss: 0.144296 2022/09/20 15:00:50 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:00:55 - mmengine - INFO - Epoch(train) [171][200/293] lr: 5.000000e-05 eta: 3:36:05 time: 0.753192 data_time: 0.108952 memory: 3324 loss_kpt: 0.142783 acc_pose: 0.686724 loss: 0.142783 2022/09/20 15:01:37 - mmengine - INFO - Epoch(train) [171][250/293] lr: 5.000000e-05 eta: 3:35:05 time: 0.849266 data_time: 0.100570 memory: 3324 loss_kpt: 0.143205 acc_pose: 0.713195 loss: 0.143205 2022/09/20 15:02:20 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:02:20 - mmengine - INFO - Saving checkpoint at 171 epochs 2022/09/20 15:03:14 - mmengine - INFO - Epoch(train) [172][50/293] lr: 5.000000e-05 eta: 3:33:08 time: 1.015621 data_time: 0.152618 memory: 3324 loss_kpt: 0.144222 acc_pose: 0.674540 loss: 0.144222 2022/09/20 15:03:46 - mmengine - INFO - Epoch(train) [172][100/293] lr: 5.000000e-05 eta: 3:32:07 time: 0.654884 data_time: 0.101098 memory: 3324 loss_kpt: 0.142191 acc_pose: 0.748099 loss: 0.142191 2022/09/20 15:04:25 - mmengine - INFO - Epoch(train) [172][150/293] lr: 5.000000e-05 eta: 3:31:07 time: 0.763205 data_time: 0.099351 memory: 3324 loss_kpt: 0.142318 acc_pose: 0.742975 loss: 0.142318 2022/09/20 15:04:56 - mmengine - INFO - Epoch(train) [172][200/293] lr: 5.000000e-05 eta: 3:30:05 time: 0.634035 data_time: 0.120351 memory: 3324 loss_kpt: 0.143466 acc_pose: 0.749064 loss: 0.143466 2022/09/20 15:05:41 - mmengine - INFO - Epoch(train) [172][250/293] lr: 5.000000e-05 eta: 3:29:06 time: 0.898247 data_time: 0.093072 memory: 3324 loss_kpt: 0.142090 acc_pose: 0.676995 loss: 0.142090 2022/09/20 15:06:10 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:06:10 - mmengine - INFO - Saving checkpoint at 172 epochs 2022/09/20 15:06:42 - mmengine - INFO - Epoch(train) [173][50/293] lr: 5.000000e-05 eta: 3:27:06 time: 0.593241 data_time: 0.228035 memory: 3324 loss_kpt: 0.141476 acc_pose: 0.789474 loss: 0.141476 2022/09/20 15:07:18 - mmengine - INFO - Epoch(train) [173][100/293] lr: 5.000000e-05 eta: 3:26:05 time: 0.721615 data_time: 0.122009 memory: 3324 loss_kpt: 0.141941 acc_pose: 0.771001 loss: 0.141941 2022/09/20 15:08:02 - mmengine - INFO - Epoch(train) [173][150/293] lr: 5.000000e-05 eta: 3:25:06 time: 0.880024 data_time: 0.105450 memory: 3324 loss_kpt: 0.141419 acc_pose: 0.773185 loss: 0.141419 2022/09/20 15:08:44 - mmengine - INFO - Epoch(train) [173][200/293] lr: 5.000000e-05 eta: 3:24:07 time: 0.828268 data_time: 0.303886 memory: 3324 loss_kpt: 0.143195 acc_pose: 0.667462 loss: 0.143195 2022/09/20 15:09:31 - mmengine - INFO - Epoch(train) [173][250/293] lr: 5.000000e-05 eta: 3:23:09 time: 0.949508 data_time: 0.181976 memory: 3324 loss_kpt: 0.142435 acc_pose: 0.709664 loss: 0.142435 2022/09/20 15:09:53 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:09:53 - mmengine - INFO - Saving checkpoint at 173 epochs 2022/09/20 15:10:42 - mmengine - INFO - Epoch(train) [174][50/293] lr: 5.000000e-05 eta: 3:21:13 time: 0.925639 data_time: 0.221961 memory: 3324 loss_kpt: 0.143627 acc_pose: 0.754992 loss: 0.143627 2022/09/20 15:11:21 - mmengine - INFO - Epoch(train) [174][100/293] lr: 5.000000e-05 eta: 3:20:13 time: 0.773183 data_time: 0.093029 memory: 3324 loss_kpt: 0.139153 acc_pose: 0.696907 loss: 0.139153 2022/09/20 15:11:51 - mmengine - INFO - Epoch(train) [174][150/293] lr: 5.000000e-05 eta: 3:19:12 time: 0.610493 data_time: 0.112888 memory: 3324 loss_kpt: 0.141720 acc_pose: 0.760926 loss: 0.141720 2022/09/20 15:12:25 - mmengine - INFO - Epoch(train) [174][200/293] lr: 5.000000e-05 eta: 3:18:12 time: 0.676882 data_time: 0.129154 memory: 3324 loss_kpt: 0.141134 acc_pose: 0.737489 loss: 0.141134 2022/09/20 15:13:00 - mmengine - INFO - Epoch(train) [174][250/293] lr: 5.000000e-05 eta: 3:17:11 time: 0.687809 data_time: 0.106313 memory: 3324 loss_kpt: 0.140782 acc_pose: 0.764059 loss: 0.140782 2022/09/20 15:13:41 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:13:41 - mmengine - INFO - Saving checkpoint at 174 epochs 2022/09/20 15:13:56 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:14:22 - mmengine - INFO - Epoch(train) [175][50/293] lr: 5.000000e-05 eta: 3:15:14 time: 0.752511 data_time: 0.142192 memory: 3324 loss_kpt: 0.145228 acc_pose: 0.705284 loss: 0.145228 2022/09/20 15:15:00 - mmengine - INFO - Epoch(train) [175][100/293] lr: 5.000000e-05 eta: 3:14:14 time: 0.775862 data_time: 0.104695 memory: 3324 loss_kpt: 0.142382 acc_pose: 0.737381 loss: 0.142382 2022/09/20 15:15:38 - mmengine - INFO - Epoch(train) [175][150/293] lr: 5.000000e-05 eta: 3:13:15 time: 0.752546 data_time: 0.258461 memory: 3324 loss_kpt: 0.139722 acc_pose: 0.745385 loss: 0.139722 2022/09/20 15:16:04 - mmengine - INFO - Epoch(train) [175][200/293] lr: 5.000000e-05 eta: 3:12:13 time: 0.530390 data_time: 0.118652 memory: 3324 loss_kpt: 0.139991 acc_pose: 0.703196 loss: 0.139991 2022/09/20 15:16:46 - mmengine - INFO - Epoch(train) [175][250/293] lr: 5.000000e-05 eta: 3:11:15 time: 0.839461 data_time: 0.247441 memory: 3324 loss_kpt: 0.143067 acc_pose: 0.749945 loss: 0.143067 2022/09/20 15:17:28 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:17:28 - mmengine - INFO - Saving checkpoint at 175 epochs 2022/09/20 15:18:03 - mmengine - INFO - Epoch(train) [176][50/293] lr: 5.000000e-05 eta: 3:09:17 time: 0.643558 data_time: 0.166966 memory: 3324 loss_kpt: 0.139598 acc_pose: 0.766798 loss: 0.139598 2022/09/20 15:18:31 - mmengine - INFO - Epoch(train) [176][100/293] lr: 5.000000e-05 eta: 3:08:16 time: 0.571744 data_time: 0.088071 memory: 3324 loss_kpt: 0.143122 acc_pose: 0.714525 loss: 0.143122 2022/09/20 15:19:08 - mmengine - INFO - Epoch(train) [176][150/293] lr: 5.000000e-05 eta: 3:07:17 time: 0.734076 data_time: 0.139088 memory: 3324 loss_kpt: 0.141144 acc_pose: 0.743660 loss: 0.141144 2022/09/20 15:19:54 - mmengine - INFO - Epoch(train) [176][200/293] lr: 5.000000e-05 eta: 3:06:19 time: 0.919790 data_time: 0.327363 memory: 3324 loss_kpt: 0.139464 acc_pose: 0.707058 loss: 0.139464 2022/09/20 15:20:35 - mmengine - INFO - Epoch(train) [176][250/293] lr: 5.000000e-05 eta: 3:05:21 time: 0.826815 data_time: 0.291872 memory: 3324 loss_kpt: 0.146567 acc_pose: 0.783319 loss: 0.146567 2022/09/20 15:20:55 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:20:55 - mmengine - INFO - Saving checkpoint at 176 epochs 2022/09/20 15:21:25 - mmengine - INFO - Epoch(train) [177][50/293] lr: 5.000000e-05 eta: 3:03:23 time: 0.529496 data_time: 0.118874 memory: 3324 loss_kpt: 0.139708 acc_pose: 0.753517 loss: 0.139708 2022/09/20 15:22:04 - mmengine - INFO - Epoch(train) [177][100/293] lr: 5.000000e-05 eta: 3:02:24 time: 0.790953 data_time: 0.196964 memory: 3324 loss_kpt: 0.141966 acc_pose: 0.758155 loss: 0.141966 2022/09/20 15:22:35 - mmengine - INFO - Epoch(train) [177][150/293] lr: 5.000000e-05 eta: 3:01:24 time: 0.611571 data_time: 0.109880 memory: 3324 loss_kpt: 0.140446 acc_pose: 0.761613 loss: 0.140446 2022/09/20 15:23:17 - mmengine - INFO - Epoch(train) [177][200/293] lr: 5.000000e-05 eta: 3:00:26 time: 0.856110 data_time: 0.096374 memory: 3324 loss_kpt: 0.143060 acc_pose: 0.733486 loss: 0.143060 2022/09/20 15:23:49 - mmengine - INFO - Epoch(train) [177][250/293] lr: 5.000000e-05 eta: 2:59:26 time: 0.621383 data_time: 0.177151 memory: 3324 loss_kpt: 0.141605 acc_pose: 0.761394 loss: 0.141605 2022/09/20 15:24:26 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:24:26 - mmengine - INFO - Saving checkpoint at 177 epochs 2022/09/20 15:25:04 - mmengine - INFO - Epoch(train) [178][50/293] lr: 5.000000e-05 eta: 2:57:30 time: 0.702164 data_time: 0.143765 memory: 3324 loss_kpt: 0.143289 acc_pose: 0.775368 loss: 0.143289 2022/09/20 15:25:36 - mmengine - INFO - Epoch(train) [178][100/293] lr: 5.000000e-05 eta: 2:56:31 time: 0.647124 data_time: 0.094821 memory: 3324 loss_kpt: 0.141505 acc_pose: 0.766803 loss: 0.141505 2022/09/20 15:26:04 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:26:14 - mmengine - INFO - Epoch(train) [178][150/293] lr: 5.000000e-05 eta: 2:55:32 time: 0.757320 data_time: 0.095288 memory: 3324 loss_kpt: 0.140603 acc_pose: 0.784702 loss: 0.140603 2022/09/20 15:26:59 - mmengine - INFO - Epoch(train) [178][200/293] lr: 5.000000e-05 eta: 2:54:35 time: 0.907304 data_time: 0.251842 memory: 3324 loss_kpt: 0.139264 acc_pose: 0.721559 loss: 0.139264 2022/09/20 15:27:59 - mmengine - INFO - Epoch(train) [178][250/293] lr: 5.000000e-05 eta: 2:53:41 time: 1.203670 data_time: 0.100807 memory: 3324 loss_kpt: 0.140579 acc_pose: 0.703524 loss: 0.140579 2022/09/20 15:28:30 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:28:30 - mmengine - INFO - Saving checkpoint at 178 epochs 2022/09/20 15:28:59 - mmengine - INFO - Epoch(train) [179][50/293] lr: 5.000000e-05 eta: 2:51:44 time: 0.530843 data_time: 0.116538 memory: 3324 loss_kpt: 0.138198 acc_pose: 0.769528 loss: 0.138198 2022/09/20 15:29:45 - mmengine - INFO - Epoch(train) [179][100/293] lr: 5.000000e-05 eta: 2:50:47 time: 0.920049 data_time: 0.127902 memory: 3324 loss_kpt: 0.143810 acc_pose: 0.727866 loss: 0.143810 2022/09/20 15:30:30 - mmengine - INFO - Epoch(train) [179][150/293] lr: 5.000000e-05 eta: 2:49:50 time: 0.907138 data_time: 0.403392 memory: 3324 loss_kpt: 0.139525 acc_pose: 0.708190 loss: 0.139525 2022/09/20 15:31:28 - mmengine - INFO - Epoch(train) [179][200/293] lr: 5.000000e-05 eta: 2:48:55 time: 1.148679 data_time: 0.097245 memory: 3324 loss_kpt: 0.140956 acc_pose: 0.743374 loss: 0.140956 2022/09/20 15:31:57 - mmengine - INFO - Epoch(train) [179][250/293] lr: 5.000000e-05 eta: 2:47:56 time: 0.576537 data_time: 0.097774 memory: 3324 loss_kpt: 0.139547 acc_pose: 0.757184 loss: 0.139547 2022/09/20 15:32:28 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:32:28 - mmengine - INFO - Saving checkpoint at 179 epochs 2022/09/20 15:33:21 - mmengine - INFO - Epoch(train) [180][50/293] lr: 5.000000e-05 eta: 2:46:04 time: 1.011968 data_time: 0.400816 memory: 3324 loss_kpt: 0.141091 acc_pose: 0.746385 loss: 0.141091 2022/09/20 15:34:10 - mmengine - INFO - Epoch(train) [180][100/293] lr: 5.000000e-05 eta: 2:45:08 time: 0.986033 data_time: 0.101612 memory: 3324 loss_kpt: 0.142438 acc_pose: 0.728023 loss: 0.142438 2022/09/20 15:34:55 - mmengine - INFO - Epoch(train) [180][150/293] lr: 5.000000e-05 eta: 2:44:11 time: 0.898782 data_time: 0.096808 memory: 3324 loss_kpt: 0.142630 acc_pose: 0.754715 loss: 0.142630 2022/09/20 15:35:39 - mmengine - INFO - Epoch(train) [180][200/293] lr: 5.000000e-05 eta: 2:43:14 time: 0.877316 data_time: 0.101314 memory: 3324 loss_kpt: 0.138131 acc_pose: 0.736949 loss: 0.138131 2022/09/20 15:36:26 - mmengine - INFO - Epoch(train) [180][250/293] lr: 5.000000e-05 eta: 2:42:17 time: 0.939598 data_time: 0.116969 memory: 3324 loss_kpt: 0.141721 acc_pose: 0.713109 loss: 0.141721 2022/09/20 15:37:00 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:37:00 - mmengine - INFO - Saving checkpoint at 180 epochs 2022/09/20 15:38:03 - mmengine - INFO - Epoch(val) [180][50/407] eta: 0:07:03 time: 1.186903 data_time: 1.141614 memory: 3324 2022/09/20 15:39:03 - mmengine - INFO - Epoch(val) [180][100/407] eta: 0:06:03 time: 1.183347 data_time: 1.141225 memory: 400 2022/09/20 15:40:03 - mmengine - INFO - Epoch(val) [180][150/407] eta: 0:05:09 time: 1.202458 data_time: 1.165375 memory: 400 2022/09/20 15:41:02 - mmengine - INFO - Epoch(val) [180][200/407] eta: 0:04:03 time: 1.176825 data_time: 1.139533 memory: 400 2022/09/20 15:42:02 - mmengine - INFO - Epoch(val) [180][250/407] eta: 0:03:08 time: 1.200151 data_time: 1.166084 memory: 400 2022/09/20 15:43:01 - mmengine - INFO - Epoch(val) [180][300/407] eta: 0:02:07 time: 1.189631 data_time: 1.148198 memory: 400 2022/09/20 15:44:00 - mmengine - INFO - Epoch(val) [180][350/407] eta: 0:01:07 time: 1.187098 data_time: 1.144303 memory: 400 2022/09/20 15:45:01 - mmengine - INFO - Epoch(val) [180][400/407] eta: 0:00:08 time: 1.205759 data_time: 1.165351 memory: 400 2022/09/20 15:45:56 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 15:46:15 - mmengine - INFO - Epoch(val) [180][407/407] coco/AP: 0.616737 coco/AP .5: 0.855752 coco/AP .75: 0.694197 coco/AP (M): 0.581882 coco/AP (L): 0.677811 coco/AR: 0.674764 coco/AR .5: 0.900976 coco/AR .75: 0.742916 coco/AR (M): 0.630374 coco/AR (L): 0.737681 2022/09/20 15:46:15 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_160.pth is removed 2022/09/20 15:46:17 - mmengine - INFO - The best checkpoint with 0.6167 coco/AP at 180 epoch is saved to best_coco/AP_epoch_180.pth. 2022/09/20 15:47:30 - mmengine - INFO - Epoch(train) [181][50/293] lr: 5.000000e-05 eta: 2:40:30 time: 1.460652 data_time: 0.314093 memory: 3324 loss_kpt: 0.139749 acc_pose: 0.760232 loss: 0.139749 2022/09/20 15:48:14 - mmengine - INFO - Epoch(train) [181][100/293] lr: 5.000000e-05 eta: 2:39:33 time: 0.874036 data_time: 0.225629 memory: 3324 loss_kpt: 0.138904 acc_pose: 0.804251 loss: 0.138904 2022/09/20 15:49:10 - mmengine - INFO - Epoch(train) [181][150/293] lr: 5.000000e-05 eta: 2:38:38 time: 1.126058 data_time: 0.148715 memory: 3324 loss_kpt: 0.140981 acc_pose: 0.694394 loss: 0.140981 2022/09/20 15:50:07 - mmengine - INFO - Epoch(train) [181][200/293] lr: 5.000000e-05 eta: 2:37:43 time: 1.135556 data_time: 0.096049 memory: 3324 loss_kpt: 0.140286 acc_pose: 0.707589 loss: 0.140286 2022/09/20 15:50:52 - mmengine - INFO - Epoch(train) [181][250/293] lr: 5.000000e-05 eta: 2:36:47 time: 0.899713 data_time: 0.184261 memory: 3324 loss_kpt: 0.141492 acc_pose: 0.786282 loss: 0.141492 2022/09/20 15:50:58 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:51:21 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:51:21 - mmengine - INFO - Saving checkpoint at 181 epochs 2022/09/20 15:51:57 - mmengine - INFO - Epoch(train) [182][50/293] lr: 5.000000e-05 eta: 2:34:53 time: 0.667624 data_time: 0.204309 memory: 3324 loss_kpt: 0.141613 acc_pose: 0.811616 loss: 0.141613 2022/09/20 15:52:42 - mmengine - INFO - Epoch(train) [182][100/293] lr: 5.000000e-05 eta: 2:33:57 time: 0.897185 data_time: 0.119664 memory: 3324 loss_kpt: 0.139073 acc_pose: 0.796941 loss: 0.139073 2022/09/20 15:53:42 - mmengine - INFO - Epoch(train) [182][150/293] lr: 5.000000e-05 eta: 2:33:02 time: 1.212883 data_time: 0.290064 memory: 3324 loss_kpt: 0.143786 acc_pose: 0.738390 loss: 0.143786 2022/09/20 15:54:21 - mmengine - INFO - Epoch(train) [182][200/293] lr: 5.000000e-05 eta: 2:32:05 time: 0.767889 data_time: 0.101621 memory: 3324 loss_kpt: 0.140420 acc_pose: 0.781157 loss: 0.140420 2022/09/20 15:55:05 - mmengine - INFO - Epoch(train) [182][250/293] lr: 5.000000e-05 eta: 2:31:08 time: 0.878602 data_time: 0.198635 memory: 3324 loss_kpt: 0.139594 acc_pose: 0.787851 loss: 0.139594 2022/09/20 15:55:37 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:55:37 - mmengine - INFO - Saving checkpoint at 182 epochs 2022/09/20 15:56:25 - mmengine - INFO - Epoch(train) [183][50/293] lr: 5.000000e-05 eta: 2:29:17 time: 0.910895 data_time: 0.182066 memory: 3324 loss_kpt: 0.142120 acc_pose: 0.726899 loss: 0.142120 2022/09/20 15:57:16 - mmengine - INFO - Epoch(train) [183][100/293] lr: 5.000000e-05 eta: 2:28:22 time: 1.021430 data_time: 0.096656 memory: 3324 loss_kpt: 0.141921 acc_pose: 0.725629 loss: 0.141921 2022/09/20 15:58:09 - mmengine - INFO - Epoch(train) [183][150/293] lr: 5.000000e-05 eta: 2:27:26 time: 1.054730 data_time: 0.098031 memory: 3324 loss_kpt: 0.144182 acc_pose: 0.748355 loss: 0.144182 2022/09/20 15:58:44 - mmengine - INFO - Epoch(train) [183][200/293] lr: 5.000000e-05 eta: 2:26:28 time: 0.688854 data_time: 0.258545 memory: 3324 loss_kpt: 0.140522 acc_pose: 0.744192 loss: 0.140522 2022/09/20 15:59:14 - mmengine - INFO - Epoch(train) [183][250/293] lr: 5.000000e-05 eta: 2:25:30 time: 0.607962 data_time: 0.188276 memory: 3324 loss_kpt: 0.141069 acc_pose: 0.664220 loss: 0.141069 2022/09/20 15:59:55 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 15:59:55 - mmengine - INFO - Saving checkpoint at 183 epochs 2022/09/20 16:00:35 - mmengine - INFO - Epoch(train) [184][50/293] lr: 5.000000e-05 eta: 2:23:38 time: 0.755136 data_time: 0.224593 memory: 3324 loss_kpt: 0.140660 acc_pose: 0.768343 loss: 0.140660 2022/09/20 16:01:08 - mmengine - INFO - Epoch(train) [184][100/293] lr: 5.000000e-05 eta: 2:22:40 time: 0.648856 data_time: 0.129179 memory: 3324 loss_kpt: 0.137345 acc_pose: 0.738106 loss: 0.137345 2022/09/20 16:01:50 - mmengine - INFO - Epoch(train) [184][150/293] lr: 5.000000e-05 eta: 2:21:44 time: 0.853861 data_time: 0.151748 memory: 3324 loss_kpt: 0.141456 acc_pose: 0.758436 loss: 0.141456 2022/09/20 16:02:42 - mmengine - INFO - Epoch(train) [184][200/293] lr: 5.000000e-05 eta: 2:20:49 time: 1.031729 data_time: 0.133791 memory: 3324 loss_kpt: 0.140326 acc_pose: 0.763436 loss: 0.140326 2022/09/20 16:03:13 - mmengine - INFO - Epoch(train) [184][250/293] lr: 5.000000e-05 eta: 2:19:50 time: 0.621434 data_time: 0.094873 memory: 3324 loss_kpt: 0.141319 acc_pose: 0.752553 loss: 0.141319 2022/09/20 16:03:59 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:03:59 - mmengine - INFO - Saving checkpoint at 184 epochs 2022/09/20 16:04:37 - mmengine - INFO - Epoch(train) [185][50/293] lr: 5.000000e-05 eta: 2:17:59 time: 0.721761 data_time: 0.128950 memory: 3324 loss_kpt: 0.135531 acc_pose: 0.766259 loss: 0.135531 2022/09/20 16:05:08 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:05:22 - mmengine - INFO - Epoch(train) [185][100/293] lr: 5.000000e-05 eta: 2:17:03 time: 0.892856 data_time: 0.218949 memory: 3324 loss_kpt: 0.141485 acc_pose: 0.751233 loss: 0.141485 2022/09/20 16:06:06 - mmengine - INFO - Epoch(train) [185][150/293] lr: 5.000000e-05 eta: 2:16:07 time: 0.886519 data_time: 0.087111 memory: 3324 loss_kpt: 0.140875 acc_pose: 0.728084 loss: 0.140875 2022/09/20 16:06:48 - mmengine - INFO - Epoch(train) [185][200/293] lr: 5.000000e-05 eta: 2:15:11 time: 0.837991 data_time: 0.120912 memory: 3324 loss_kpt: 0.138353 acc_pose: 0.718117 loss: 0.138353 2022/09/20 16:07:22 - mmengine - INFO - Epoch(train) [185][250/293] lr: 5.000000e-05 eta: 2:14:13 time: 0.669101 data_time: 0.085553 memory: 3324 loss_kpt: 0.138837 acc_pose: 0.745460 loss: 0.138837 2022/09/20 16:07:56 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:07:56 - mmengine - INFO - Saving checkpoint at 185 epochs 2022/09/20 16:08:40 - mmengine - INFO - Epoch(train) [186][50/293] lr: 5.000000e-05 eta: 2:12:23 time: 0.831063 data_time: 0.303300 memory: 3324 loss_kpt: 0.141914 acc_pose: 0.710007 loss: 0.141914 2022/09/20 16:09:15 - mmengine - INFO - Epoch(train) [186][100/293] lr: 5.000000e-05 eta: 2:11:26 time: 0.691881 data_time: 0.123034 memory: 3324 loss_kpt: 0.140638 acc_pose: 0.740260 loss: 0.140638 2022/09/20 16:09:45 - mmengine - INFO - Epoch(train) [186][150/293] lr: 5.000000e-05 eta: 2:10:28 time: 0.590145 data_time: 0.192100 memory: 3324 loss_kpt: 0.138899 acc_pose: 0.779767 loss: 0.138899 2022/09/20 16:10:33 - mmengine - INFO - Epoch(train) [186][200/293] lr: 5.000000e-05 eta: 2:09:33 time: 0.971270 data_time: 0.284430 memory: 3324 loss_kpt: 0.141239 acc_pose: 0.758073 loss: 0.141239 2022/09/20 16:11:18 - mmengine - INFO - Epoch(train) [186][250/293] lr: 5.000000e-05 eta: 2:08:37 time: 0.893033 data_time: 0.175752 memory: 3324 loss_kpt: 0.140363 acc_pose: 0.717049 loss: 0.140363 2022/09/20 16:11:52 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:11:52 - mmengine - INFO - Saving checkpoint at 186 epochs 2022/09/20 16:12:37 - mmengine - INFO - Epoch(train) [187][50/293] lr: 5.000000e-05 eta: 2:06:48 time: 0.850307 data_time: 0.159672 memory: 3324 loss_kpt: 0.141176 acc_pose: 0.759409 loss: 0.141176 2022/09/20 16:13:14 - mmengine - INFO - Epoch(train) [187][100/293] lr: 5.000000e-05 eta: 2:05:51 time: 0.745109 data_time: 0.221659 memory: 3324 loss_kpt: 0.140085 acc_pose: 0.742820 loss: 0.140085 2022/09/20 16:13:48 - mmengine - INFO - Epoch(train) [187][150/293] lr: 5.000000e-05 eta: 2:04:54 time: 0.680533 data_time: 0.346030 memory: 3324 loss_kpt: 0.140383 acc_pose: 0.746074 loss: 0.140383 2022/09/20 16:14:24 - mmengine - INFO - Epoch(train) [187][200/293] lr: 5.000000e-05 eta: 2:03:58 time: 0.723351 data_time: 0.162457 memory: 3324 loss_kpt: 0.141258 acc_pose: 0.804866 loss: 0.141258 2022/09/20 16:14:51 - mmengine - INFO - Epoch(train) [187][250/293] lr: 5.000000e-05 eta: 2:03:00 time: 0.532514 data_time: 0.098253 memory: 3324 loss_kpt: 0.139604 acc_pose: 0.753965 loss: 0.139604 2022/09/20 16:15:12 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:15:12 - mmengine - INFO - Saving checkpoint at 187 epochs 2022/09/20 16:15:49 - mmengine - INFO - Epoch(train) [188][50/293] lr: 5.000000e-05 eta: 2:01:10 time: 0.673362 data_time: 0.133901 memory: 3324 loss_kpt: 0.143204 acc_pose: 0.756740 loss: 0.143204 2022/09/20 16:16:12 - mmengine - INFO - Epoch(train) [188][100/293] lr: 5.000000e-05 eta: 2:00:12 time: 0.470512 data_time: 0.126946 memory: 3324 loss_kpt: 0.139995 acc_pose: 0.803790 loss: 0.139995 2022/09/20 16:16:42 - mmengine - INFO - Epoch(train) [188][150/293] lr: 5.000000e-05 eta: 1:59:15 time: 0.599710 data_time: 0.258567 memory: 3324 loss_kpt: 0.143414 acc_pose: 0.756964 loss: 0.143414 2022/09/20 16:17:10 - mmengine - INFO - Epoch(train) [188][200/293] lr: 5.000000e-05 eta: 1:58:18 time: 0.561972 data_time: 0.126801 memory: 3324 loss_kpt: 0.140815 acc_pose: 0.725580 loss: 0.140815 2022/09/20 16:17:18 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:18:02 - mmengine - INFO - Epoch(train) [188][250/293] lr: 5.000000e-05 eta: 1:57:23 time: 1.025071 data_time: 0.102585 memory: 3324 loss_kpt: 0.143134 acc_pose: 0.722322 loss: 0.143134 2022/09/20 16:18:54 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:18:54 - mmengine - INFO - Saving checkpoint at 188 epochs 2022/09/20 16:19:43 - mmengine - INFO - Epoch(train) [189][50/293] lr: 5.000000e-05 eta: 1:55:36 time: 0.932776 data_time: 0.222410 memory: 3324 loss_kpt: 0.143119 acc_pose: 0.830325 loss: 0.143119 2022/09/20 16:20:28 - mmengine - INFO - Epoch(train) [189][100/293] lr: 5.000000e-05 eta: 1:54:40 time: 0.902876 data_time: 0.096136 memory: 3324 loss_kpt: 0.142262 acc_pose: 0.757053 loss: 0.142262 2022/09/20 16:21:29 - mmengine - INFO - Epoch(train) [189][150/293] lr: 5.000000e-05 eta: 1:53:47 time: 1.212900 data_time: 0.097096 memory: 3324 loss_kpt: 0.139409 acc_pose: 0.772369 loss: 0.139409 2022/09/20 16:22:06 - mmengine - INFO - Epoch(train) [189][200/293] lr: 5.000000e-05 eta: 1:52:51 time: 0.749355 data_time: 0.122315 memory: 3324 loss_kpt: 0.141452 acc_pose: 0.723399 loss: 0.141452 2022/09/20 16:22:36 - mmengine - INFO - Epoch(train) [189][250/293] lr: 5.000000e-05 eta: 1:51:54 time: 0.591768 data_time: 0.096129 memory: 3324 loss_kpt: 0.142828 acc_pose: 0.744501 loss: 0.142828 2022/09/20 16:23:02 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:23:02 - mmengine - INFO - Saving checkpoint at 189 epochs 2022/09/20 16:23:24 - mmengine - INFO - Epoch(train) [190][50/293] lr: 5.000000e-05 eta: 1:50:04 time: 0.402279 data_time: 0.111348 memory: 3324 loss_kpt: 0.143006 acc_pose: 0.721508 loss: 0.143006 2022/09/20 16:23:41 - mmengine - INFO - Epoch(train) [190][100/293] lr: 5.000000e-05 eta: 1:49:06 time: 0.343281 data_time: 0.105111 memory: 3324 loss_kpt: 0.141545 acc_pose: 0.772091 loss: 0.141545 2022/09/20 16:23:59 - mmengine - INFO - Epoch(train) [190][150/293] lr: 5.000000e-05 eta: 1:48:08 time: 0.351198 data_time: 0.105464 memory: 3324 loss_kpt: 0.142728 acc_pose: 0.783744 loss: 0.142728 2022/09/20 16:24:18 - mmengine - INFO - Epoch(train) [190][200/293] lr: 5.000000e-05 eta: 1:47:10 time: 0.382431 data_time: 0.101404 memory: 3324 loss_kpt: 0.140332 acc_pose: 0.712094 loss: 0.140332 2022/09/20 16:24:36 - mmengine - INFO - Epoch(train) [190][250/293] lr: 5.000000e-05 eta: 1:46:12 time: 0.348550 data_time: 0.100762 memory: 3324 loss_kpt: 0.141281 acc_pose: 0.731113 loss: 0.141281 2022/09/20 16:24:50 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:24:50 - mmengine - INFO - Saving checkpoint at 190 epochs 2022/09/20 16:25:53 - mmengine - INFO - Epoch(val) [190][50/407] eta: 0:07:04 time: 1.189156 data_time: 1.147245 memory: 3324 2022/09/20 16:26:52 - mmengine - INFO - Epoch(val) [190][100/407] eta: 0:06:00 time: 1.173272 data_time: 1.127683 memory: 400 2022/09/20 16:27:49 - mmengine - INFO - Epoch(val) [190][150/407] eta: 0:04:56 time: 1.153374 data_time: 1.101806 memory: 400 2022/09/20 16:28:49 - mmengine - INFO - Epoch(val) [190][200/407] eta: 0:04:07 time: 1.196839 data_time: 1.145379 memory: 400 2022/09/20 16:29:48 - mmengine - INFO - Epoch(val) [190][250/407] eta: 0:03:04 time: 1.176811 data_time: 1.135233 memory: 400 2022/09/20 16:30:49 - mmengine - INFO - Epoch(val) [190][300/407] eta: 0:02:10 time: 1.219068 data_time: 1.169802 memory: 400 2022/09/20 16:31:48 - mmengine - INFO - Epoch(val) [190][350/407] eta: 0:01:07 time: 1.178752 data_time: 1.131303 memory: 400 2022/09/20 16:32:46 - mmengine - INFO - Epoch(val) [190][400/407] eta: 0:00:08 time: 1.169099 data_time: 1.117499 memory: 400 2022/09/20 16:33:42 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 16:33:59 - mmengine - INFO - Epoch(val) [190][407/407] coco/AP: 0.619120 coco/AP .5: 0.856370 coco/AP .75: 0.696019 coco/AP (M): 0.584398 coco/AP (L): 0.680103 coco/AR: 0.676496 coco/AR .5: 0.900819 coco/AR .75: 0.744805 coco/AR (M): 0.632232 coco/AR (L): 0.739576 2022/09/20 16:34:00 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_180.pth is removed 2022/09/20 16:34:02 - mmengine - INFO - The best checkpoint with 0.6191 coco/AP at 190 epoch is saved to best_coco/AP_epoch_190.pth. 2022/09/20 16:34:21 - mmengine - INFO - Epoch(train) [191][50/293] lr: 5.000000e-05 eta: 1:44:23 time: 0.379354 data_time: 0.116506 memory: 3324 loss_kpt: 0.140517 acc_pose: 0.670343 loss: 0.140517 2022/09/20 16:34:40 - mmengine - INFO - Epoch(train) [191][100/293] lr: 5.000000e-05 eta: 1:43:26 time: 0.377130 data_time: 0.100722 memory: 3324 loss_kpt: 0.138557 acc_pose: 0.755227 loss: 0.138557 2022/09/20 16:34:58 - mmengine - INFO - Epoch(train) [191][150/293] lr: 5.000000e-05 eta: 1:42:28 time: 0.358006 data_time: 0.110190 memory: 3324 loss_kpt: 0.139937 acc_pose: 0.724034 loss: 0.139937 2022/09/20 16:35:16 - mmengine - INFO - Epoch(train) [191][200/293] lr: 5.000000e-05 eta: 1:41:31 time: 0.362196 data_time: 0.102169 memory: 3324 loss_kpt: 0.141009 acc_pose: 0.711766 loss: 0.141009 2022/09/20 16:35:33 - mmengine - INFO - Epoch(train) [191][250/293] lr: 5.000000e-05 eta: 1:40:33 time: 0.352075 data_time: 0.109325 memory: 3324 loss_kpt: 0.141186 acc_pose: 0.721664 loss: 0.141186 2022/09/20 16:35:48 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:35:48 - mmengine - INFO - Saving checkpoint at 191 epochs 2022/09/20 16:36:04 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:36:09 - mmengine - INFO - Epoch(train) [192][50/293] lr: 5.000000e-05 eta: 1:38:45 time: 0.366378 data_time: 0.113056 memory: 3324 loss_kpt: 0.140108 acc_pose: 0.734440 loss: 0.140108 2022/09/20 16:36:25 - mmengine - INFO - Epoch(train) [192][100/293] lr: 5.000000e-05 eta: 1:37:48 time: 0.333532 data_time: 0.108392 memory: 3324 loss_kpt: 0.140110 acc_pose: 0.724612 loss: 0.140110 2022/09/20 16:36:42 - mmengine - INFO - Epoch(train) [192][150/293] lr: 5.000000e-05 eta: 1:36:51 time: 0.337901 data_time: 0.112348 memory: 3324 loss_kpt: 0.137560 acc_pose: 0.710384 loss: 0.137560 2022/09/20 16:36:59 - mmengine - INFO - Epoch(train) [192][200/293] lr: 5.000000e-05 eta: 1:35:54 time: 0.344265 data_time: 0.099797 memory: 3324 loss_kpt: 0.138106 acc_pose: 0.790091 loss: 0.138106 2022/09/20 16:37:16 - mmengine - INFO - Epoch(train) [192][250/293] lr: 5.000000e-05 eta: 1:34:57 time: 0.330854 data_time: 0.101843 memory: 3324 loss_kpt: 0.142472 acc_pose: 0.776063 loss: 0.142472 2022/09/20 16:37:29 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:37:29 - mmengine - INFO - Saving checkpoint at 192 epochs 2022/09/20 16:37:50 - mmengine - INFO - Epoch(train) [193][50/293] lr: 5.000000e-05 eta: 1:33:09 time: 0.357173 data_time: 0.113227 memory: 3324 loss_kpt: 0.140282 acc_pose: 0.765385 loss: 0.140282 2022/09/20 16:38:07 - mmengine - INFO - Epoch(train) [193][100/293] lr: 5.000000e-05 eta: 1:32:12 time: 0.340611 data_time: 0.106552 memory: 3324 loss_kpt: 0.138056 acc_pose: 0.737364 loss: 0.138056 2022/09/20 16:38:24 - mmengine - INFO - Epoch(train) [193][150/293] lr: 5.000000e-05 eta: 1:31:16 time: 0.349348 data_time: 0.106205 memory: 3324 loss_kpt: 0.139608 acc_pose: 0.750546 loss: 0.139608 2022/09/20 16:38:41 - mmengine - INFO - Epoch(train) [193][200/293] lr: 5.000000e-05 eta: 1:30:19 time: 0.342137 data_time: 0.107752 memory: 3324 loss_kpt: 0.139310 acc_pose: 0.754941 loss: 0.139310 2022/09/20 16:38:59 - mmengine - INFO - Epoch(train) [193][250/293] lr: 5.000000e-05 eta: 1:29:22 time: 0.341334 data_time: 0.106139 memory: 3324 loss_kpt: 0.141566 acc_pose: 0.769542 loss: 0.141566 2022/09/20 16:39:12 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:39:12 - mmengine - INFO - Saving checkpoint at 193 epochs 2022/09/20 16:39:33 - mmengine - INFO - Epoch(train) [194][50/293] lr: 5.000000e-05 eta: 1:27:36 time: 0.372878 data_time: 0.117586 memory: 3324 loss_kpt: 0.139721 acc_pose: 0.802185 loss: 0.139721 2022/09/20 16:39:51 - mmengine - INFO - Epoch(train) [194][100/293] lr: 5.000000e-05 eta: 1:26:40 time: 0.361442 data_time: 0.101829 memory: 3324 loss_kpt: 0.139493 acc_pose: 0.733293 loss: 0.139493 2022/09/20 16:40:09 - mmengine - INFO - Epoch(train) [194][150/293] lr: 5.000000e-05 eta: 1:25:43 time: 0.346333 data_time: 0.108705 memory: 3324 loss_kpt: 0.139381 acc_pose: 0.726571 loss: 0.139381 2022/09/20 16:40:26 - mmengine - INFO - Epoch(train) [194][200/293] lr: 5.000000e-05 eta: 1:24:47 time: 0.347559 data_time: 0.101852 memory: 3324 loss_kpt: 0.140755 acc_pose: 0.733290 loss: 0.140755 2022/09/20 16:40:44 - mmengine - INFO - Epoch(train) [194][250/293] lr: 5.000000e-05 eta: 1:23:51 time: 0.355576 data_time: 0.106806 memory: 3324 loss_kpt: 0.142993 acc_pose: 0.745337 loss: 0.142993 2022/09/20 16:40:59 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:40:59 - mmengine - INFO - Saving checkpoint at 194 epochs 2022/09/20 16:41:21 - mmengine - INFO - Epoch(train) [195][50/293] lr: 5.000000e-05 eta: 1:22:06 time: 0.386651 data_time: 0.114185 memory: 3324 loss_kpt: 0.137124 acc_pose: 0.763376 loss: 0.137124 2022/09/20 16:41:39 - mmengine - INFO - Epoch(train) [195][100/293] lr: 5.000000e-05 eta: 1:21:10 time: 0.365331 data_time: 0.108815 memory: 3324 loss_kpt: 0.139608 acc_pose: 0.780636 loss: 0.139608 2022/09/20 16:41:58 - mmengine - INFO - Epoch(train) [195][150/293] lr: 5.000000e-05 eta: 1:20:14 time: 0.369182 data_time: 0.108079 memory: 3324 loss_kpt: 0.141385 acc_pose: 0.742965 loss: 0.141385 2022/09/20 16:42:00 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:42:15 - mmengine - INFO - Epoch(train) [195][200/293] lr: 5.000000e-05 eta: 1:19:18 time: 0.358947 data_time: 0.103868 memory: 3324 loss_kpt: 0.140657 acc_pose: 0.777632 loss: 0.140657 2022/09/20 16:42:33 - mmengine - INFO - Epoch(train) [195][250/293] lr: 5.000000e-05 eta: 1:18:22 time: 0.347708 data_time: 0.113233 memory: 3324 loss_kpt: 0.139501 acc_pose: 0.734396 loss: 0.139501 2022/09/20 16:42:47 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:42:47 - mmengine - INFO - Saving checkpoint at 195 epochs 2022/09/20 16:43:07 - mmengine - INFO - Epoch(train) [196][50/293] lr: 5.000000e-05 eta: 1:16:38 time: 0.360939 data_time: 0.114758 memory: 3324 loss_kpt: 0.138494 acc_pose: 0.748901 loss: 0.138494 2022/09/20 16:43:25 - mmengine - INFO - Epoch(train) [196][100/293] lr: 5.000000e-05 eta: 1:15:42 time: 0.343999 data_time: 0.107652 memory: 3324 loss_kpt: 0.138803 acc_pose: 0.739437 loss: 0.138803 2022/09/20 16:43:42 - mmengine - INFO - Epoch(train) [196][150/293] lr: 5.000000e-05 eta: 1:14:47 time: 0.346067 data_time: 0.104905 memory: 3324 loss_kpt: 0.141895 acc_pose: 0.763892 loss: 0.141895 2022/09/20 16:43:59 - mmengine - INFO - Epoch(train) [196][200/293] lr: 5.000000e-05 eta: 1:13:51 time: 0.342899 data_time: 0.108269 memory: 3324 loss_kpt: 0.136972 acc_pose: 0.763789 loss: 0.136972 2022/09/20 16:44:16 - mmengine - INFO - Epoch(train) [196][250/293] lr: 5.000000e-05 eta: 1:12:56 time: 0.330686 data_time: 0.104210 memory: 3324 loss_kpt: 0.142003 acc_pose: 0.738868 loss: 0.142003 2022/09/20 16:44:29 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:44:29 - mmengine - INFO - Saving checkpoint at 196 epochs 2022/09/20 16:44:51 - mmengine - INFO - Epoch(train) [197][50/293] lr: 5.000000e-05 eta: 1:11:12 time: 0.381868 data_time: 0.114535 memory: 3324 loss_kpt: 0.139129 acc_pose: 0.790826 loss: 0.139129 2022/09/20 16:45:09 - mmengine - INFO - Epoch(train) [197][100/293] lr: 5.000000e-05 eta: 1:10:17 time: 0.363958 data_time: 0.113645 memory: 3324 loss_kpt: 0.141910 acc_pose: 0.758212 loss: 0.141910 2022/09/20 16:45:27 - mmengine - INFO - Epoch(train) [197][150/293] lr: 5.000000e-05 eta: 1:09:22 time: 0.366355 data_time: 0.112512 memory: 3324 loss_kpt: 0.139228 acc_pose: 0.750278 loss: 0.139228 2022/09/20 16:45:45 - mmengine - INFO - Epoch(train) [197][200/293] lr: 5.000000e-05 eta: 1:08:27 time: 0.355381 data_time: 0.112234 memory: 3324 loss_kpt: 0.141163 acc_pose: 0.713764 loss: 0.141163 2022/09/20 16:46:02 - mmengine - INFO - Epoch(train) [197][250/293] lr: 5.000000e-05 eta: 1:07:32 time: 0.345249 data_time: 0.105378 memory: 3324 loss_kpt: 0.139711 acc_pose: 0.767087 loss: 0.139711 2022/09/20 16:46:17 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:46:17 - mmengine - INFO - Saving checkpoint at 197 epochs 2022/09/20 16:46:38 - mmengine - INFO - Epoch(train) [198][50/293] lr: 5.000000e-05 eta: 1:05:49 time: 0.369349 data_time: 0.122412 memory: 3324 loss_kpt: 0.137556 acc_pose: 0.780823 loss: 0.137556 2022/09/20 16:46:57 - mmengine - INFO - Epoch(train) [198][100/293] lr: 5.000000e-05 eta: 1:04:54 time: 0.370467 data_time: 0.112545 memory: 3324 loss_kpt: 0.138345 acc_pose: 0.785480 loss: 0.138345 2022/09/20 16:47:16 - mmengine - INFO - Epoch(train) [198][150/293] lr: 5.000000e-05 eta: 1:03:59 time: 0.387043 data_time: 0.105553 memory: 3324 loss_kpt: 0.139797 acc_pose: 0.771256 loss: 0.139797 2022/09/20 16:47:35 - mmengine - INFO - Epoch(train) [198][200/293] lr: 5.000000e-05 eta: 1:03:05 time: 0.377967 data_time: 0.107152 memory: 3324 loss_kpt: 0.139849 acc_pose: 0.782794 loss: 0.139849 2022/09/20 16:47:54 - mmengine - INFO - Epoch(train) [198][250/293] lr: 5.000000e-05 eta: 1:02:10 time: 0.376210 data_time: 0.113808 memory: 3324 loss_kpt: 0.139960 acc_pose: 0.747961 loss: 0.139960 2022/09/20 16:48:04 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:48:09 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:48:09 - mmengine - INFO - Saving checkpoint at 198 epochs 2022/09/20 16:48:29 - mmengine - INFO - Epoch(train) [199][50/293] lr: 5.000000e-05 eta: 1:00:28 time: 0.352520 data_time: 0.108563 memory: 3324 loss_kpt: 0.140532 acc_pose: 0.772930 loss: 0.140532 2022/09/20 16:48:46 - mmengine - INFO - Epoch(train) [199][100/293] lr: 5.000000e-05 eta: 0:59:34 time: 0.344988 data_time: 0.101167 memory: 3324 loss_kpt: 0.136729 acc_pose: 0.738979 loss: 0.136729 2022/09/20 16:49:04 - mmengine - INFO - Epoch(train) [199][150/293] lr: 5.000000e-05 eta: 0:58:39 time: 0.351359 data_time: 0.105291 memory: 3324 loss_kpt: 0.143296 acc_pose: 0.739897 loss: 0.143296 2022/09/20 16:49:21 - mmengine - INFO - Epoch(train) [199][200/293] lr: 5.000000e-05 eta: 0:57:45 time: 0.337282 data_time: 0.101278 memory: 3324 loss_kpt: 0.139109 acc_pose: 0.710310 loss: 0.139109 2022/09/20 16:49:38 - mmengine - INFO - Epoch(train) [199][250/293] lr: 5.000000e-05 eta: 0:56:51 time: 0.354232 data_time: 0.107656 memory: 3324 loss_kpt: 0.140850 acc_pose: 0.757760 loss: 0.140850 2022/09/20 16:49:52 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:49:52 - mmengine - INFO - Saving checkpoint at 199 epochs 2022/09/20 16:50:13 - mmengine - INFO - Epoch(train) [200][50/293] lr: 5.000000e-05 eta: 0:55:09 time: 0.360270 data_time: 0.112481 memory: 3324 loss_kpt: 0.141201 acc_pose: 0.731089 loss: 0.141201 2022/09/20 16:50:30 - mmengine - INFO - Epoch(train) [200][100/293] lr: 5.000000e-05 eta: 0:54:15 time: 0.345067 data_time: 0.103865 memory: 3324 loss_kpt: 0.138101 acc_pose: 0.761546 loss: 0.138101 2022/09/20 16:50:48 - mmengine - INFO - Epoch(train) [200][150/293] lr: 5.000000e-05 eta: 0:53:21 time: 0.353499 data_time: 0.109564 memory: 3324 loss_kpt: 0.138822 acc_pose: 0.752205 loss: 0.138822 2022/09/20 16:51:05 - mmengine - INFO - Epoch(train) [200][200/293] lr: 5.000000e-05 eta: 0:52:28 time: 0.347349 data_time: 0.101251 memory: 3324 loss_kpt: 0.140238 acc_pose: 0.675945 loss: 0.140238 2022/09/20 16:51:23 - mmengine - INFO - Epoch(train) [200][250/293] lr: 5.000000e-05 eta: 0:51:34 time: 0.353024 data_time: 0.102920 memory: 3324 loss_kpt: 0.137678 acc_pose: 0.757213 loss: 0.137678 2022/09/20 16:51:37 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 16:51:37 - mmengine - INFO - Saving checkpoint at 200 epochs 2022/09/20 16:52:40 - mmengine - INFO - Epoch(val) [200][50/407] eta: 0:07:00 time: 1.179212 data_time: 1.127767 memory: 3324 2022/09/20 16:53:39 - mmengine - INFO - Epoch(val) [200][100/407] eta: 0:06:00 time: 1.173783 data_time: 1.122733 memory: 400 2022/09/20 16:54:37 - mmengine - INFO - Epoch(val) [200][150/407] eta: 0:04:57 time: 1.155850 data_time: 1.122129 memory: 400 2022/09/20 16:55:36 - mmengine - INFO - Epoch(val) [200][200/407] eta: 0:04:06 time: 1.188568 data_time: 1.152786 memory: 400 2022/09/20 16:56:35 - mmengine - INFO - Epoch(val) [200][250/407] eta: 0:03:04 time: 1.177643 data_time: 1.128839 memory: 400 2022/09/20 16:57:35 - mmengine - INFO - Epoch(val) [200][300/407] eta: 0:02:08 time: 1.199241 data_time: 1.153940 memory: 400 2022/09/20 16:58:35 - mmengine - INFO - Epoch(val) [200][350/407] eta: 0:01:08 time: 1.194104 data_time: 1.153994 memory: 400 2022/09/20 16:59:33 - mmengine - INFO - Epoch(val) [200][400/407] eta: 0:00:08 time: 1.173341 data_time: 1.123281 memory: 400 2022/09/20 17:00:28 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 17:00:46 - mmengine - INFO - Epoch(val) [200][407/407] coco/AP: 0.620055 coco/AP .5: 0.856042 coco/AP .75: 0.694369 coco/AP (M): 0.585115 coco/AP (L): 0.681020 coco/AR: 0.678133 coco/AR .5: 0.901921 coco/AR .75: 0.745592 coco/AR (M): 0.633625 coco/AR (L): 0.740877 2022/09/20 17:00:46 - mmengine - INFO - The previous best checkpoint /mnt/lustre/jiangtao/experiment3/simcc_mb2_256/best_coco/AP_epoch_190.pth is removed 2022/09/20 17:00:48 - mmengine - INFO - The best checkpoint with 0.6201 coco/AP at 200 epoch is saved to best_coco/AP_epoch_200.pth. 2022/09/20 17:01:07 - mmengine - INFO - Epoch(train) [201][50/293] lr: 5.000000e-06 eta: 0:49:53 time: 0.383346 data_time: 0.118923 memory: 3324 loss_kpt: 0.139630 acc_pose: 0.819136 loss: 0.139630 2022/09/20 17:01:25 - mmengine - INFO - Epoch(train) [201][100/293] lr: 5.000000e-06 eta: 0:48:59 time: 0.356564 data_time: 0.105905 memory: 3324 loss_kpt: 0.140831 acc_pose: 0.736729 loss: 0.140831 2022/09/20 17:01:43 - mmengine - INFO - Epoch(train) [201][150/293] lr: 5.000000e-06 eta: 0:48:06 time: 0.363010 data_time: 0.109263 memory: 3324 loss_kpt: 0.138597 acc_pose: 0.776457 loss: 0.138597 2022/09/20 17:02:00 - mmengine - INFO - Epoch(train) [201][200/293] lr: 5.000000e-06 eta: 0:47:12 time: 0.323925 data_time: 0.104212 memory: 3324 loss_kpt: 0.138705 acc_pose: 0.753451 loss: 0.138705 2022/09/20 17:02:16 - mmengine - INFO - Epoch(train) [201][250/293] lr: 5.000000e-06 eta: 0:46:19 time: 0.325726 data_time: 0.102958 memory: 3324 loss_kpt: 0.141029 acc_pose: 0.745344 loss: 0.141029 2022/09/20 17:02:30 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:02:30 - mmengine - INFO - Saving checkpoint at 201 epochs 2022/09/20 17:02:49 - mmengine - INFO - Epoch(train) [202][50/293] lr: 5.000000e-06 eta: 0:44:39 time: 0.333107 data_time: 0.118777 memory: 3324 loss_kpt: 0.138527 acc_pose: 0.744437 loss: 0.138527 2022/09/20 17:03:06 - mmengine - INFO - Epoch(train) [202][100/293] lr: 5.000000e-06 eta: 0:43:46 time: 0.326119 data_time: 0.110710 memory: 3324 loss_kpt: 0.139471 acc_pose: 0.767431 loss: 0.139471 2022/09/20 17:03:08 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:03:22 - mmengine - INFO - Epoch(train) [202][150/293] lr: 5.000000e-06 eta: 0:42:52 time: 0.323018 data_time: 0.104227 memory: 3324 loss_kpt: 0.139007 acc_pose: 0.789994 loss: 0.139007 2022/09/20 17:03:38 - mmengine - INFO - Epoch(train) [202][200/293] lr: 5.000000e-06 eta: 0:41:59 time: 0.317210 data_time: 0.103910 memory: 3324 loss_kpt: 0.135310 acc_pose: 0.754926 loss: 0.135310 2022/09/20 17:03:54 - mmengine - INFO - Epoch(train) [202][250/293] lr: 5.000000e-06 eta: 0:41:06 time: 0.322246 data_time: 0.102089 memory: 3324 loss_kpt: 0.139723 acc_pose: 0.687877 loss: 0.139723 2022/09/20 17:04:07 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:04:07 - mmengine - INFO - Saving checkpoint at 202 epochs 2022/09/20 17:04:28 - mmengine - INFO - Epoch(train) [203][50/293] lr: 5.000000e-06 eta: 0:39:27 time: 0.369713 data_time: 0.120322 memory: 3324 loss_kpt: 0.140272 acc_pose: 0.759264 loss: 0.140272 2022/09/20 17:04:45 - mmengine - INFO - Epoch(train) [203][100/293] lr: 5.000000e-06 eta: 0:38:34 time: 0.346587 data_time: 0.107141 memory: 3324 loss_kpt: 0.137027 acc_pose: 0.737010 loss: 0.137027 2022/09/20 17:05:03 - mmengine - INFO - Epoch(train) [203][150/293] lr: 5.000000e-06 eta: 0:37:41 time: 0.359658 data_time: 0.113473 memory: 3324 loss_kpt: 0.142547 acc_pose: 0.797136 loss: 0.142547 2022/09/20 17:05:21 - mmengine - INFO - Epoch(train) [203][200/293] lr: 5.000000e-06 eta: 0:36:48 time: 0.347144 data_time: 0.109903 memory: 3324 loss_kpt: 0.136299 acc_pose: 0.735341 loss: 0.136299 2022/09/20 17:05:38 - mmengine - INFO - Epoch(train) [203][250/293] lr: 5.000000e-06 eta: 0:35:56 time: 0.344881 data_time: 0.105854 memory: 3324 loss_kpt: 0.141024 acc_pose: 0.778550 loss: 0.141024 2022/09/20 17:05:53 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:05:53 - mmengine - INFO - Saving checkpoint at 203 epochs 2022/09/20 17:06:13 - mmengine - INFO - Epoch(train) [204][50/293] lr: 5.000000e-06 eta: 0:34:17 time: 0.357320 data_time: 0.112477 memory: 3324 loss_kpt: 0.139223 acc_pose: 0.813539 loss: 0.139223 2022/09/20 17:06:29 - mmengine - INFO - Epoch(train) [204][100/293] lr: 5.000000e-06 eta: 0:33:25 time: 0.320400 data_time: 0.100152 memory: 3324 loss_kpt: 0.137624 acc_pose: 0.804922 loss: 0.137624 2022/09/20 17:06:46 - mmengine - INFO - Epoch(train) [204][150/293] lr: 5.000000e-06 eta: 0:32:32 time: 0.340887 data_time: 0.105088 memory: 3324 loss_kpt: 0.137685 acc_pose: 0.776597 loss: 0.137685 2022/09/20 17:07:03 - mmengine - INFO - Epoch(train) [204][200/293] lr: 5.000000e-06 eta: 0:31:40 time: 0.332816 data_time: 0.111728 memory: 3324 loss_kpt: 0.137677 acc_pose: 0.732589 loss: 0.137677 2022/09/20 17:07:20 - mmengine - INFO - Epoch(train) [204][250/293] lr: 5.000000e-06 eta: 0:30:47 time: 0.337367 data_time: 0.105861 memory: 3324 loss_kpt: 0.139873 acc_pose: 0.738986 loss: 0.139873 2022/09/20 17:07:34 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:07:34 - mmengine - INFO - Saving checkpoint at 204 epochs 2022/09/20 17:07:54 - mmengine - INFO - Epoch(train) [205][50/293] lr: 5.000000e-06 eta: 0:29:10 time: 0.351477 data_time: 0.113561 memory: 3324 loss_kpt: 0.137019 acc_pose: 0.738492 loss: 0.137019 2022/09/20 17:08:11 - mmengine - INFO - Epoch(train) [205][100/293] lr: 5.000000e-06 eta: 0:28:18 time: 0.335883 data_time: 0.108681 memory: 3324 loss_kpt: 0.139284 acc_pose: 0.734553 loss: 0.139284 2022/09/20 17:08:28 - mmengine - INFO - Epoch(train) [205][150/293] lr: 5.000000e-06 eta: 0:27:25 time: 0.330123 data_time: 0.104413 memory: 3324 loss_kpt: 0.136653 acc_pose: 0.708950 loss: 0.136653 2022/09/20 17:08:44 - mmengine - INFO - Epoch(train) [205][200/293] lr: 5.000000e-06 eta: 0:26:33 time: 0.328506 data_time: 0.099751 memory: 3324 loss_kpt: 0.138865 acc_pose: 0.770084 loss: 0.138865 2022/09/20 17:08:53 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:09:01 - mmengine - INFO - Epoch(train) [205][250/293] lr: 5.000000e-06 eta: 0:25:41 time: 0.329909 data_time: 0.104222 memory: 3324 loss_kpt: 0.137295 acc_pose: 0.827038 loss: 0.137295 2022/09/20 17:09:14 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:09:14 - mmengine - INFO - Saving checkpoint at 205 epochs 2022/09/20 17:09:36 - mmengine - INFO - Epoch(train) [206][50/293] lr: 5.000000e-06 eta: 0:24:04 time: 0.377741 data_time: 0.111379 memory: 3324 loss_kpt: 0.139364 acc_pose: 0.733622 loss: 0.139364 2022/09/20 17:09:54 - mmengine - INFO - Epoch(train) [206][100/293] lr: 5.000000e-06 eta: 0:23:13 time: 0.366624 data_time: 0.104189 memory: 3324 loss_kpt: 0.136746 acc_pose: 0.749332 loss: 0.136746 2022/09/20 17:10:12 - mmengine - INFO - Epoch(train) [206][150/293] lr: 5.000000e-06 eta: 0:22:21 time: 0.358289 data_time: 0.109887 memory: 3324 loss_kpt: 0.140360 acc_pose: 0.710406 loss: 0.140360 2022/09/20 17:10:29 - mmengine - INFO - Epoch(train) [206][200/293] lr: 5.000000e-06 eta: 0:21:29 time: 0.335175 data_time: 0.099105 memory: 3324 loss_kpt: 0.141079 acc_pose: 0.787366 loss: 0.141079 2022/09/20 17:10:46 - mmengine - INFO - Epoch(train) [206][250/293] lr: 5.000000e-06 eta: 0:20:38 time: 0.347099 data_time: 0.106520 memory: 3324 loss_kpt: 0.138602 acc_pose: 0.731941 loss: 0.138602 2022/09/20 17:11:01 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:11:01 - mmengine - INFO - Saving checkpoint at 206 epochs 2022/09/20 17:11:21 - mmengine - INFO - Epoch(train) [207][50/293] lr: 5.000000e-06 eta: 0:19:01 time: 0.360739 data_time: 0.115578 memory: 3324 loss_kpt: 0.139548 acc_pose: 0.731013 loss: 0.139548 2022/09/20 17:11:39 - mmengine - INFO - Epoch(train) [207][100/293] lr: 5.000000e-06 eta: 0:18:10 time: 0.346979 data_time: 0.115151 memory: 3324 loss_kpt: 0.138820 acc_pose: 0.761083 loss: 0.138820 2022/09/20 17:11:56 - mmengine - INFO - Epoch(train) [207][150/293] lr: 5.000000e-06 eta: 0:17:18 time: 0.350333 data_time: 0.112219 memory: 3324 loss_kpt: 0.137005 acc_pose: 0.774513 loss: 0.137005 2022/09/20 17:12:14 - mmengine - INFO - Epoch(train) [207][200/293] lr: 5.000000e-06 eta: 0:16:27 time: 0.347431 data_time: 0.112665 memory: 3324 loss_kpt: 0.138200 acc_pose: 0.788721 loss: 0.138200 2022/09/20 17:12:32 - mmengine - INFO - Epoch(train) [207][250/293] lr: 5.000000e-06 eta: 0:15:36 time: 0.362703 data_time: 0.110233 memory: 3324 loss_kpt: 0.143118 acc_pose: 0.770538 loss: 0.143118 2022/09/20 17:12:46 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:12:46 - mmengine - INFO - Saving checkpoint at 207 epochs 2022/09/20 17:13:08 - mmengine - INFO - Epoch(train) [208][50/293] lr: 5.000000e-06 eta: 0:14:00 time: 0.386582 data_time: 0.116799 memory: 3324 loss_kpt: 0.138401 acc_pose: 0.750739 loss: 0.138401 2022/09/20 17:13:27 - mmengine - INFO - Epoch(train) [208][100/293] lr: 5.000000e-06 eta: 0:13:09 time: 0.372774 data_time: 0.104417 memory: 3324 loss_kpt: 0.141207 acc_pose: 0.724707 loss: 0.141207 2022/09/20 17:13:45 - mmengine - INFO - Epoch(train) [208][150/293] lr: 5.000000e-06 eta: 0:12:18 time: 0.369167 data_time: 0.102649 memory: 3324 loss_kpt: 0.136973 acc_pose: 0.762664 loss: 0.136973 2022/09/20 17:14:03 - mmengine - INFO - Epoch(train) [208][200/293] lr: 5.000000e-06 eta: 0:11:27 time: 0.367212 data_time: 0.102110 memory: 3324 loss_kpt: 0.138502 acc_pose: 0.732861 loss: 0.138502 2022/09/20 17:14:21 - mmengine - INFO - Epoch(train) [208][250/293] lr: 5.000000e-06 eta: 0:10:36 time: 0.347403 data_time: 0.104094 memory: 3324 loss_kpt: 0.137710 acc_pose: 0.743318 loss: 0.137710 2022/09/20 17:14:35 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:14:35 - mmengine - INFO - Saving checkpoint at 208 epochs 2022/09/20 17:14:57 - mmengine - INFO - Epoch(train) [209][50/293] lr: 5.000000e-06 eta: 0:09:01 time: 0.388408 data_time: 0.125097 memory: 3324 loss_kpt: 0.138105 acc_pose: 0.727376 loss: 0.138105 2022/09/20 17:14:59 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:15:15 - mmengine - INFO - Epoch(train) [209][100/293] lr: 5.000000e-06 eta: 0:08:11 time: 0.372689 data_time: 0.107266 memory: 3324 loss_kpt: 0.136716 acc_pose: 0.720068 loss: 0.136716 2022/09/20 17:15:34 - mmengine - INFO - Epoch(train) [209][150/293] lr: 5.000000e-06 eta: 0:07:20 time: 0.369457 data_time: 0.116356 memory: 3324 loss_kpt: 0.142072 acc_pose: 0.761526 loss: 0.142072 2022/09/20 17:15:52 - mmengine - INFO - Epoch(train) [209][200/293] lr: 5.000000e-06 eta: 0:06:29 time: 0.373366 data_time: 0.109358 memory: 3324 loss_kpt: 0.140089 acc_pose: 0.748110 loss: 0.140089 2022/09/20 17:16:11 - mmengine - INFO - Epoch(train) [209][250/293] lr: 5.000000e-06 eta: 0:05:38 time: 0.369487 data_time: 0.114084 memory: 3324 loss_kpt: 0.138828 acc_pose: 0.762517 loss: 0.138828 2022/09/20 17:16:26 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:16:26 - mmengine - INFO - Saving checkpoint at 209 epochs 2022/09/20 17:16:48 - mmengine - INFO - Epoch(train) [210][50/293] lr: 5.000000e-06 eta: 0:04:04 time: 0.374928 data_time: 0.123785 memory: 3324 loss_kpt: 0.140217 acc_pose: 0.789792 loss: 0.140217 2022/09/20 17:17:06 - mmengine - INFO - Epoch(train) [210][100/293] lr: 5.000000e-06 eta: 0:03:14 time: 0.368871 data_time: 0.108900 memory: 3324 loss_kpt: 0.138995 acc_pose: 0.831142 loss: 0.138995 2022/09/20 17:17:24 - mmengine - INFO - Epoch(train) [210][150/293] lr: 5.000000e-06 eta: 0:02:23 time: 0.362952 data_time: 0.116061 memory: 3324 loss_kpt: 0.138392 acc_pose: 0.710535 loss: 0.138392 2022/09/20 17:17:41 - mmengine - INFO - Epoch(train) [210][200/293] lr: 5.000000e-06 eta: 0:01:33 time: 0.332161 data_time: 0.106763 memory: 3324 loss_kpt: 0.138985 acc_pose: 0.739028 loss: 0.138985 2022/09/20 17:17:58 - mmengine - INFO - Epoch(train) [210][250/293] lr: 5.000000e-06 eta: 0:00:43 time: 0.337232 data_time: 0.113725 memory: 3324 loss_kpt: 0.141597 acc_pose: 0.731627 loss: 0.141597 2022/09/20 17:18:13 - mmengine - INFO - Exp name: simcc_mobilenetv2_wo-deconv-8xb64-210e_coco-256x192_20220919_171943 2022/09/20 17:18:13 - mmengine - INFO - Saving checkpoint at 210 epochs 2022/09/20 17:19:15 - mmengine - INFO - Epoch(val) [210][50/407] eta: 0:06:58 time: 1.170933 data_time: 1.104692 memory: 3324 2022/09/20 17:20:14 - mmengine - INFO - Epoch(val) [210][100/407] eta: 0:06:01 time: 1.179112 data_time: 1.138899 memory: 400 2022/09/20 17:21:13 - mmengine - INFO - Epoch(val) [210][150/407] eta: 0:05:03 time: 1.181731 data_time: 1.135203 memory: 400 2022/09/20 17:22:12 - mmengine - INFO - Epoch(val) [210][200/407] eta: 0:04:02 time: 1.171880 data_time: 1.121835 memory: 400 2022/09/20 17:23:11 - mmengine - INFO - Epoch(val) [210][250/407] eta: 0:03:05 time: 1.178497 data_time: 1.132052 memory: 400 2022/09/20 17:24:11 - mmengine - INFO - Epoch(val) [210][300/407] eta: 0:02:09 time: 1.208192 data_time: 1.165576 memory: 400 2022/09/20 17:25:09 - mmengine - INFO - Epoch(val) [210][350/407] eta: 0:01:06 time: 1.167996 data_time: 1.114746 memory: 400 2022/09/20 17:26:08 - mmengine - INFO - Epoch(val) [210][400/407] eta: 0:00:08 time: 1.180229 data_time: 1.124676 memory: 400 2022/09/20 17:27:04 - mmengine - INFO - Evaluating CocoMetric... 2022/09/20 17:27:22 - mmengine - INFO - Epoch(val) [210][407/407] coco/AP: 0.619720 coco/AP .5: 0.855415 coco/AP .75: 0.696597 coco/AP (M): 0.584318 coco/AP (L): 0.680749 coco/AR: 0.678149 coco/AR .5: 0.901921 coco/AR .75: 0.747009 coco/AR (M): 0.633515 coco/AR (L): 0.741286