Sentry_image_models
/
resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1
/20230605_201824
/20230605_201824.log
| 2023/06/05 20:18:27 - mmengine - INFO - | |
| ------------------------------------------------------------ | |
| System environment: | |
| sys.platform: linux | |
| Python: 3.10.9 (main, Mar 8 2023, 10:47:38) [GCC 11.2.0] | |
| CUDA available: True | |
| numpy_random_seed: 829172272 | |
| GPU 0,1: NVIDIA A100-SXM4-80GB | |
| CUDA_HOME: /mnt/petrelfs/share/cuda-11.6 | |
| NVCC: Cuda compilation tools, release 11.6, V11.6.124 | |
| GCC: gcc (GCC) 7.5.0 | |
| PyTorch: 1.13.1 | |
| PyTorch compiling details: PyTorch built with: | |
| - GCC 9.3 | |
| - C++ Version: 201402 | |
| - Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 for Intel(R) 64 architecture applications | |
| - Intel(R) MKL-DNN v2.6.0 (Git Hash 52b5f107dd9cf10910aaa19cb47f3abf9b349815) | |
| - OpenMP 201511 (a.k.a. OpenMP 4.5) | |
| - LAPACK is enabled (usually provided by MKL) | |
| - NNPACK is enabled | |
| - CPU capability usage: AVX2 | |
| - CUDA Runtime 11.6 | |
| - 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_61,code=sm_61;-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;-gencode;arch=compute_37,code=compute_37 | |
| - CuDNN 8.3.2 (built against CUDA 11.5) | |
| - Magma 2.6.1 | |
| - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.6, CUDNN_VERSION=8.3.2, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.13.1, 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, USE_ROCM=OFF, | |
| TorchVision: 0.14.1 | |
| OpenCV: 4.7.0 | |
| MMEngine: 0.7.3 | |
| Runtime environment: | |
| cudnn_benchmark: True | |
| mp_cfg: {'mp_start_method': 'fork', 'opencv_num_threads': 0} | |
| dist_cfg: {'backend': 'nccl'} | |
| seed: None | |
| deterministic: False | |
| Distributed launcher: slurm | |
| Distributed training: True | |
| GPU number: 2 | |
| ------------------------------------------------------------ | |
| 2023/06/05 20:18:32 - mmengine - INFO - Config: | |
| optim_wrapper = dict( | |
| optimizer=dict( | |
| type='SGD', | |
| lr=0.0005, | |
| momentum=0.9, | |
| weight_decay=0.0001, | |
| _scope_='mmpretrain'), | |
| clip_grad=None) | |
| param_scheduler = [ | |
| dict(type='CosineAnnealingLR', eta_min=1e-05, by_epoch=False, begin=0) | |
| ] | |
| train_cfg = dict(by_epoch=True, max_epochs=10, val_interval=1) | |
| val_cfg = dict() | |
| test_cfg = dict() | |
| auto_scale_lr = dict(base_batch_size=512) | |
| model = dict( | |
| type='ImageClassifier', | |
| backbone=dict( | |
| frozen_stages=2, | |
| type='ResNet', | |
| depth=50, | |
| num_stages=4, | |
| out_indices=(3, ), | |
| style='pytorch', | |
| init_cfg=dict( | |
| type='Pretrained', | |
| checkpoint= | |
| 'https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth', | |
| prefix='backbone')), | |
| neck=dict(type='GlobalAveragePooling'), | |
| head=dict( | |
| type='LinearClsHead', | |
| num_classes=2, | |
| in_channels=2048, | |
| loss=dict(type='CrossEntropyLoss', loss_weight=1.0), | |
| topk=1)) | |
| dataset_type = 'CustomDataset' | |
| data_preprocessor = dict( | |
| num_classes=2, | |
| mean=[123.675, 116.28, 103.53], | |
| std=[58.395, 57.12, 57.375], | |
| to_rgb=True) | |
| bgr_mean = [103.53, 116.28, 123.675] | |
| bgr_std = [57.375, 57.12, 58.395] | |
| train_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='RandomResizedCrop', | |
| scale=224, | |
| backend='pillow', | |
| interpolation='bicubic'), | |
| dict(type='RandomFlip', prob=0.5, direction='horizontal'), | |
| dict(type='JPEG', compress_val=65, prob=0.1), | |
| dict(type='GaussianBlur', radius=1.5, prob=0.1), | |
| dict(type='PackInputs') | |
| ] | |
| test_pipeline = [ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='ResizeEdge', | |
| scale=256, | |
| edge='short', | |
| backend='pillow', | |
| interpolation='bicubic'), | |
| dict(type='CenterCrop', crop_size=224), | |
| dict(type='PackInputs') | |
| ] | |
| train_dataloader = dict( | |
| pin_memory=True, | |
| persistent_workers=True, | |
| collate_fn=dict(type='default_collate'), | |
| batch_size=256, | |
| num_workers=10, | |
| dataset=dict( | |
| type='ConcatDataset', | |
| datasets=[ | |
| dict( | |
| type='CustomDataset', | |
| data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset', | |
| ann_file= | |
| '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/stylegan3fake8w.csv', | |
| pipeline=[ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='RandomResizedCrop', | |
| scale=224, | |
| backend='pillow', | |
| interpolation='bicubic'), | |
| dict(type='RandomFlip', prob=0.5, direction='horizontal'), | |
| dict(type='JPEG', compress_val=65, prob=0.1), | |
| dict(type='GaussianBlur', radius=1.5, prob=0.1), | |
| dict(type='PackInputs') | |
| ]), | |
| dict( | |
| type='CustomDataset', | |
| data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset', | |
| ann_file= | |
| '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/stylegan3real8w.csv', | |
| pipeline=[ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='RandomResizedCrop', | |
| scale=224, | |
| backend='pillow', | |
| interpolation='bicubic'), | |
| dict(type='RandomFlip', prob=0.5, direction='horizontal'), | |
| dict(type='JPEG', compress_val=65, prob=0.1), | |
| dict(type='GaussianBlur', radius=1.5, prob=0.1), | |
| dict(type='PackInputs') | |
| ]) | |
| ]), | |
| sampler=dict(type='DefaultSampler', shuffle=True)) | |
| val_dataloader = dict( | |
| pin_memory=True, | |
| persistent_workers=True, | |
| collate_fn=dict(type='default_collate'), | |
| batch_size=256, | |
| num_workers=10, | |
| dataset=dict( | |
| type='ConcatDataset', | |
| datasets=[ | |
| dict( | |
| type='CustomDataset', | |
| data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset', | |
| ann_file= | |
| '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/stylegan3fake8w.csv', | |
| pipeline=[ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='RandomResizedCrop', | |
| scale=224, | |
| backend='pillow', | |
| interpolation='bicubic'), | |
| dict(type='RandomFlip', prob=0.5, direction='horizontal'), | |
| dict(type='JPEG', compress_val=65, prob=0.1), | |
| dict(type='GaussianBlur', radius=1.5, prob=0.1), | |
| dict(type='PackInputs') | |
| ]), | |
| dict( | |
| type='CustomDataset', | |
| data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset', | |
| ann_file= | |
| '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/stylegan3real8w.csv', | |
| pipeline=[ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='RandomResizedCrop', | |
| scale=224, | |
| backend='pillow', | |
| interpolation='bicubic'), | |
| dict(type='RandomFlip', prob=0.5, direction='horizontal'), | |
| dict(type='JPEG', compress_val=65, prob=0.1), | |
| dict(type='GaussianBlur', radius=1.5, prob=0.1), | |
| dict(type='PackInputs') | |
| ]) | |
| ]), | |
| sampler=dict(type='DefaultSampler', shuffle=False)) | |
| val_evaluator = dict(type='Accuracy', topk=1) | |
| test_dataloader = dict( | |
| pin_memory=True, | |
| persistent_workers=True, | |
| collate_fn=dict(type='default_collate'), | |
| batch_size=256, | |
| num_workers=10, | |
| dataset=dict( | |
| type='ConcatDataset', | |
| datasets=[ | |
| dict( | |
| type='CustomDataset', | |
| data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset', | |
| ann_file= | |
| '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/stylegan3fake8w.csv', | |
| pipeline=[ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='RandomResizedCrop', | |
| scale=224, | |
| backend='pillow', | |
| interpolation='bicubic'), | |
| dict(type='RandomFlip', prob=0.5, direction='horizontal'), | |
| dict(type='JPEG', compress_val=65, prob=0.1), | |
| dict(type='GaussianBlur', radius=1.5, prob=0.1), | |
| dict(type='PackInputs') | |
| ]), | |
| dict( | |
| type='CustomDataset', | |
| data_root='/mnt/petrelfs/luzeyu/workspace/fakebench/dataset', | |
| ann_file= | |
| '/mnt/petrelfs/luzeyu/workspace/fakebench/dataset/meta/train/stylegan3real8w.csv', | |
| pipeline=[ | |
| dict(type='LoadImageFromFile'), | |
| dict( | |
| type='RandomResizedCrop', | |
| scale=224, | |
| backend='pillow', | |
| interpolation='bicubic'), | |
| dict(type='RandomFlip', prob=0.5, direction='horizontal'), | |
| dict(type='JPEG', compress_val=65, prob=0.1), | |
| dict(type='GaussianBlur', radius=1.5, prob=0.1), | |
| dict(type='PackInputs') | |
| ]) | |
| ]), | |
| sampler=dict(type='DefaultSampler', shuffle=False)) | |
| test_evaluator = dict(type='Accuracy', topk=1) | |
| custom_hooks = [dict(type='EMAHook', momentum=0.0001, priority='ABOVE_NORMAL')] | |
| default_scope = 'mmpretrain' | |
| default_hooks = dict( | |
| timer=dict(type='IterTimerHook'), | |
| logger=dict(type='LoggerHook', interval=100), | |
| param_scheduler=dict(type='ParamSchedulerHook'), | |
| checkpoint=dict(type='CheckpointHook', interval=1), | |
| sampler_seed=dict(type='DistSamplerSeedHook'), | |
| visualization=dict(type='VisualizationHook', enable=True)) | |
| env_cfg = dict( | |
| cudnn_benchmark=True, | |
| mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0), | |
| dist_cfg=dict(backend='nccl')) | |
| vis_backends = [dict(type='LocalVisBackend')] | |
| visualizer = dict( | |
| type='UniversalVisualizer', | |
| vis_backends=[ | |
| dict(type='LocalVisBackend'), | |
| dict(type='TensorboardVisBackend') | |
| ]) | |
| log_level = 'INFO' | |
| load_from = None | |
| resume = False | |
| randomness = dict(seed=None, deterministic=False) | |
| launcher = 'slurm' | |
| work_dir = 'workdir/resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1' | |
| 2023/06/05 20:18:43 - mmengine - INFO - Hooks will be executed in the following order: | |
| before_run: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (ABOVE_NORMAL) EMAHook | |
| (BELOW_NORMAL) LoggerHook | |
| -------------------- | |
| after_load_checkpoint: | |
| (ABOVE_NORMAL) EMAHook | |
| -------------------- | |
| before_train: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (ABOVE_NORMAL) EMAHook | |
| (NORMAL ) IterTimerHook | |
| (VERY_LOW ) CheckpointHook | |
| -------------------- | |
| before_train_epoch: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) DistSamplerSeedHook | |
| -------------------- | |
| before_train_iter: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (NORMAL ) IterTimerHook | |
| -------------------- | |
| after_train_iter: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (ABOVE_NORMAL) EMAHook | |
| (NORMAL ) IterTimerHook | |
| (BELOW_NORMAL) LoggerHook | |
| (LOW ) ParamSchedulerHook | |
| (VERY_LOW ) CheckpointHook | |
| -------------------- | |
| after_train_epoch: | |
| (NORMAL ) IterTimerHook | |
| (LOW ) ParamSchedulerHook | |
| (VERY_LOW ) CheckpointHook | |
| -------------------- | |
| before_val_epoch: | |
| (ABOVE_NORMAL) EMAHook | |
| (NORMAL ) IterTimerHook | |
| -------------------- | |
| before_val_iter: | |
| (NORMAL ) IterTimerHook | |
| -------------------- | |
| after_val_iter: | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) VisualizationHook | |
| (BELOW_NORMAL) LoggerHook | |
| -------------------- | |
| after_val_epoch: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (ABOVE_NORMAL) EMAHook | |
| (NORMAL ) IterTimerHook | |
| (BELOW_NORMAL) LoggerHook | |
| (LOW ) ParamSchedulerHook | |
| (VERY_LOW ) CheckpointHook | |
| -------------------- | |
| before_save_checkpoint: | |
| (ABOVE_NORMAL) EMAHook | |
| -------------------- | |
| after_train: | |
| (VERY_LOW ) CheckpointHook | |
| -------------------- | |
| before_test_epoch: | |
| (ABOVE_NORMAL) EMAHook | |
| (NORMAL ) IterTimerHook | |
| -------------------- | |
| before_test_iter: | |
| (NORMAL ) IterTimerHook | |
| -------------------- | |
| after_test_iter: | |
| (NORMAL ) IterTimerHook | |
| (NORMAL ) VisualizationHook | |
| (BELOW_NORMAL) LoggerHook | |
| -------------------- | |
| after_test_epoch: | |
| (VERY_HIGH ) RuntimeInfoHook | |
| (ABOVE_NORMAL) EMAHook | |
| (NORMAL ) IterTimerHook | |
| (BELOW_NORMAL) LoggerHook | |
| -------------------- | |
| after_run: | |
| (BELOW_NORMAL) LoggerHook | |
| -------------------- | |
| 2023/06/05 20:18:54 - mmengine - INFO - load backbone in model from: https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| Name of parameter - Initialization information | |
| backbone.conv1.weight - torch.Size([64, 3, 7, 7]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.bn1.weight - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.bn1.bias - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.conv1.weight - torch.Size([64, 64, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.bn1.weight - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.bn1.bias - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.conv2.weight - torch.Size([64, 64, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.bn2.weight - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.bn2.bias - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.conv3.weight - torch.Size([256, 64, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.bn3.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.bn3.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.downsample.0.weight - torch.Size([256, 64, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.downsample.1.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.0.downsample.1.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.1.conv1.weight - torch.Size([64, 256, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.1.bn1.weight - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.1.bn1.bias - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.1.conv2.weight - torch.Size([64, 64, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.1.bn2.weight - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.1.bn2.bias - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.1.conv3.weight - torch.Size([256, 64, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.1.bn3.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.1.bn3.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.2.conv1.weight - torch.Size([64, 256, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.2.bn1.weight - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.2.bn1.bias - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.2.conv2.weight - torch.Size([64, 64, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.2.bn2.weight - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.2.bn2.bias - torch.Size([64]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.2.conv3.weight - torch.Size([256, 64, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.2.bn3.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer1.2.bn3.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.conv1.weight - torch.Size([128, 256, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.bn1.weight - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.bn1.bias - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.conv2.weight - torch.Size([128, 128, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.bn2.weight - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.bn2.bias - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.conv3.weight - torch.Size([512, 128, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.bn3.weight - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.bn3.bias - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.downsample.0.weight - torch.Size([512, 256, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.downsample.1.weight - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.0.downsample.1.bias - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.1.conv1.weight - torch.Size([128, 512, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.1.bn1.weight - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.1.bn1.bias - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.1.conv2.weight - torch.Size([128, 128, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.1.bn2.weight - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.1.bn2.bias - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.1.conv3.weight - torch.Size([512, 128, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.1.bn3.weight - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.1.bn3.bias - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.2.conv1.weight - torch.Size([128, 512, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.2.bn1.weight - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.2.bn1.bias - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.2.conv2.weight - torch.Size([128, 128, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.2.bn2.weight - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.2.bn2.bias - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.2.conv3.weight - torch.Size([512, 128, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.2.bn3.weight - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.2.bn3.bias - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.3.conv1.weight - torch.Size([128, 512, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.3.bn1.weight - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.3.bn1.bias - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.3.conv2.weight - torch.Size([128, 128, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.3.bn2.weight - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.3.bn2.bias - torch.Size([128]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.3.conv3.weight - torch.Size([512, 128, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.3.bn3.weight - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer2.3.bn3.bias - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.conv1.weight - torch.Size([256, 512, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.bn1.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.bn1.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.conv2.weight - torch.Size([256, 256, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.bn2.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.bn2.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.conv3.weight - torch.Size([1024, 256, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.bn3.weight - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.bn3.bias - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.downsample.0.weight - torch.Size([1024, 512, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.downsample.1.weight - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.0.downsample.1.bias - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.1.conv1.weight - torch.Size([256, 1024, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.1.bn1.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.1.bn1.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.1.conv2.weight - torch.Size([256, 256, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.1.bn2.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.1.bn2.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.1.conv3.weight - torch.Size([1024, 256, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.1.bn3.weight - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.1.bn3.bias - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.2.conv1.weight - torch.Size([256, 1024, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.2.bn1.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.2.bn1.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.2.conv2.weight - torch.Size([256, 256, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.2.bn2.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.2.bn2.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.2.conv3.weight - torch.Size([1024, 256, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.2.bn3.weight - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.2.bn3.bias - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.3.conv1.weight - torch.Size([256, 1024, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.3.bn1.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.3.bn1.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.3.conv2.weight - torch.Size([256, 256, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.3.bn2.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.3.bn2.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.3.conv3.weight - torch.Size([1024, 256, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.3.bn3.weight - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.3.bn3.bias - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.4.conv1.weight - torch.Size([256, 1024, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.4.bn1.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.4.bn1.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.4.conv2.weight - torch.Size([256, 256, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.4.bn2.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.4.bn2.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.4.conv3.weight - torch.Size([1024, 256, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.4.bn3.weight - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.4.bn3.bias - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.5.conv1.weight - torch.Size([256, 1024, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.5.bn1.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.5.bn1.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.5.conv2.weight - torch.Size([256, 256, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.5.bn2.weight - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.5.bn2.bias - torch.Size([256]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.5.conv3.weight - torch.Size([1024, 256, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.5.bn3.weight - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer3.5.bn3.bias - torch.Size([1024]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.conv1.weight - torch.Size([512, 1024, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.bn1.weight - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.bn1.bias - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.conv2.weight - torch.Size([512, 512, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.bn2.weight - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.bn2.bias - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.conv3.weight - torch.Size([2048, 512, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.bn3.weight - torch.Size([2048]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.bn3.bias - torch.Size([2048]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.downsample.0.weight - torch.Size([2048, 1024, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.downsample.1.weight - torch.Size([2048]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.0.downsample.1.bias - torch.Size([2048]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.1.conv1.weight - torch.Size([512, 2048, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.1.bn1.weight - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.1.bn1.bias - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.1.conv2.weight - torch.Size([512, 512, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.1.bn2.weight - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.1.bn2.bias - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.1.conv3.weight - torch.Size([2048, 512, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.1.bn3.weight - torch.Size([2048]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.1.bn3.bias - torch.Size([2048]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.2.conv1.weight - torch.Size([512, 2048, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.2.bn1.weight - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.2.bn1.bias - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.2.conv2.weight - torch.Size([512, 512, 3, 3]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.2.bn2.weight - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.2.bn2.bias - torch.Size([512]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.2.conv3.weight - torch.Size([2048, 512, 1, 1]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.2.bn3.weight - torch.Size([2048]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| backbone.layer4.2.bn3.bias - torch.Size([2048]): | |
| PretrainedInit: load from https://download.openmmlab.com/mmclassification/v0/resnet/resnet50_8xb32_in1k_20210831-ea4938fc.pth | |
| head.fc.weight - torch.Size([2, 2048]): | |
| NormalInit: mean=0, std=0.01, bias=0 | |
| head.fc.bias - torch.Size([2]): | |
| NormalInit: mean=0, std=0.01, bias=0 | |
| 2023/06/05 20:18:54 - mmengine - WARNING - "FileClient" will be deprecated in future. Please use io functions in https://mmengine.readthedocs.io/en/latest/api/fileio.html#file-io | |
| 2023/06/05 20:18:54 - mmengine - WARNING - "HardDiskBackend" is the alias of "LocalBackend" and the former will be deprecated in future. | |
| 2023/06/05 20:18:54 - mmengine - INFO - Checkpoints will be saved to /mnt/petrelfs/luzeyu/workspace/fakebench/mmpretrain/workdir/resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1. | |
| 2023/06/05 20:20:55 - mmengine - INFO - Epoch(train) [1][100/342] lr: 4.9899e-04 eta: 1:07:02 time: 1.2894 data_time: 0.0462 memory: 9436 loss: 0.6466 | |
| 2023/06/05 20:22:52 - mmengine - INFO - Epoch(train) [1][200/342] lr: 4.9592e-04 eta: 1:04:00 time: 1.1408 data_time: 0.0374 memory: 6319 loss: 0.5994 | |
| 2023/06/05 20:24:48 - mmengine - INFO - Epoch(train) [1][300/342] lr: 4.9082e-04 eta: 1:01:19 time: 1.1450 data_time: 0.0338 memory: 6319 loss: 0.5529 | |
| 2023/06/05 20:25:33 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 20:25:33 - mmengine - INFO - Saving checkpoint at 1 epochs | |
| 2023/06/05 20:27:32 - mmengine - INFO - Epoch(val) [1][100/342] eta: 0:04:35 time: 0.3524 data_time: 0.2598 memory: 6319 | |
| 2023/06/05 20:29:08 - mmengine - INFO - Epoch(val) [1][200/342] eta: 0:02:29 time: 0.2520 data_time: 0.1639 memory: 3133 | |
| 2023/06/05 20:31:17 - mmengine - INFO - Epoch(val) [1][300/342] eta: 0:00:47 time: 1.2765 data_time: 1.1885 memory: 3133 | |
| 2023/06/05 20:33:48 - mmengine - INFO - Epoch(val) [1][342/342] accuracy/top1: 52.5023 data_time: 1.2363 time: 1.3259 | |
| 2023/06/05 20:35:48 - mmengine - INFO - Epoch(train) [2][100/342] lr: 4.8017e-04 eta: 0:58:13 time: 1.1271 data_time: 0.3758 memory: 6319 loss: 0.4926 | |
| 2023/06/05 20:37:58 - mmengine - INFO - Epoch(train) [2][200/342] lr: 4.7036e-04 eta: 0:57:23 time: 1.2324 data_time: 0.0280 memory: 6319 loss: 0.4379 | |
| 2023/06/05 20:39:51 - mmengine - INFO - Epoch(train) [2][300/342] lr: 4.5874e-04 eta: 0:54:58 time: 1.1658 data_time: 0.0007 memory: 6319 loss: 0.4117 | |
| 2023/06/05 20:40:38 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 20:40:38 - mmengine - INFO - Saving checkpoint at 2 epochs | |
| 2023/06/05 20:42:34 - mmengine - INFO - Epoch(val) [2][100/342] eta: 0:04:25 time: 0.3601 data_time: 0.2723 memory: 6319 | |
| 2023/06/05 20:44:11 - mmengine - INFO - Epoch(val) [2][200/342] eta: 0:02:26 time: 0.2166 data_time: 0.1296 memory: 3133 | |
| 2023/06/05 20:46:18 - mmengine - INFO - Epoch(val) [2][300/342] eta: 0:00:46 time: 1.1879 data_time: 1.0999 memory: 3133 | |
| 2023/06/05 20:48:49 - mmengine - INFO - Epoch(val) [2][342/342] accuracy/top1: 54.9073 data_time: 1.2266 time: 1.3162 | |
| 2023/06/05 20:50:50 - mmengine - INFO - Epoch(train) [3][100/342] lr: 4.3931e-04 eta: 0:52:07 time: 1.2552 data_time: 0.5291 memory: 6319 loss: 0.3391 | |
| 2023/06/05 20:53:01 - mmengine - INFO - Epoch(train) [3][200/342] lr: 4.2373e-04 eta: 0:50:45 time: 1.1545 data_time: 0.5126 memory: 6319 loss: 0.3379 | |
| 2023/06/05 20:54:56 - mmengine - INFO - Epoch(train) [3][300/342] lr: 4.0672e-04 eta: 0:48:33 time: 1.0924 data_time: 0.5283 memory: 6319 loss: 0.3355 | |
| 2023/06/05 20:55:20 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 20:55:43 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 20:55:43 - mmengine - INFO - Saving checkpoint at 3 epochs | |
| 2023/06/05 20:57:40 - mmengine - INFO - Epoch(val) [3][100/342] eta: 0:04:28 time: 0.3432 data_time: 0.2546 memory: 6319 | |
| 2023/06/05 20:59:18 - mmengine - INFO - Epoch(val) [3][200/342] eta: 0:02:28 time: 0.2374 data_time: 0.1503 memory: 3133 | |
| 2023/06/05 21:01:23 - mmengine - INFO - Epoch(val) [3][300/342] eta: 0:00:46 time: 1.1826 data_time: 1.0944 memory: 3133 | |
| 2023/06/05 21:04:00 - mmengine - INFO - Epoch(val) [3][342/342] accuracy/top1: 56.8017 data_time: 1.2417 time: 1.3311 | |
| 2023/06/05 21:05:59 - mmengine - INFO - Epoch(train) [4][100/342] lr: 3.8041e-04 eta: 0:45:34 time: 1.1012 data_time: 0.6531 memory: 6319 loss: 0.2856 | |
| 2023/06/05 21:07:53 - mmengine - INFO - Epoch(train) [4][200/342] lr: 3.6058e-04 eta: 0:43:27 time: 1.1526 data_time: 0.0985 memory: 6319 loss: 0.2939 | |
| 2023/06/05 21:09:56 - mmengine - INFO - Epoch(train) [4][300/342] lr: 3.3985e-04 eta: 0:41:35 time: 1.1228 data_time: 0.1639 memory: 6319 loss: 0.2874 | |
| 2023/06/05 21:10:41 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 21:10:41 - mmengine - INFO - Saving checkpoint at 4 epochs | |
| 2023/06/05 21:12:34 - mmengine - INFO - Epoch(val) [4][100/342] eta: 0:04:20 time: 0.3319 data_time: 0.2435 memory: 6319 | |
| 2023/06/05 21:14:11 - mmengine - INFO - Epoch(val) [4][200/342] eta: 0:02:25 time: 0.2262 data_time: 0.1397 memory: 3133 | |
| 2023/06/05 21:16:16 - mmengine - INFO - Epoch(val) [4][300/342] eta: 0:00:46 time: 1.1651 data_time: 1.0761 memory: 3133 | |
| 2023/06/05 21:18:53 - mmengine - INFO - Epoch(val) [4][342/342] accuracy/top1: 58.0077 data_time: 1.2350 time: 1.3242 | |
| 2023/06/05 21:21:25 - mmengine - INFO - Epoch(train) [5][100/342] lr: 3.0924e-04 eta: 0:39:22 time: 1.0484 data_time: 0.0007 memory: 6319 loss: 0.2582 | |
| 2023/06/05 21:23:20 - mmengine - INFO - Epoch(train) [5][200/342] lr: 2.8709e-04 eta: 0:37:13 time: 1.1158 data_time: 0.0008 memory: 6319 loss: 0.2382 | |
| 2023/06/05 21:25:14 - mmengine - INFO - Epoch(train) [5][300/342] lr: 2.6467e-04 eta: 0:35:06 time: 1.2034 data_time: 0.0032 memory: 6319 loss: 0.2546 | |
| 2023/06/05 21:25:58 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 21:25:58 - mmengine - INFO - Saving checkpoint at 5 epochs | |
| 2023/06/05 21:27:51 - mmengine - INFO - Epoch(val) [5][100/342] eta: 0:04:20 time: 0.3397 data_time: 0.2517 memory: 6319 | |
| 2023/06/05 21:29:28 - mmengine - INFO - Epoch(val) [5][200/342] eta: 0:02:24 time: 0.2111 data_time: 0.1246 memory: 3133 | |
| 2023/06/05 21:31:31 - mmengine - INFO - Epoch(val) [5][300/342] eta: 0:00:45 time: 1.2263 data_time: 1.1381 memory: 3133 | |
| 2023/06/05 21:34:04 - mmengine - INFO - Epoch(val) [5][342/342] accuracy/top1: 58.4781 data_time: 1.2147 time: 1.3046 | |
| 2023/06/05 21:36:03 - mmengine - INFO - Epoch(train) [6][100/342] lr: 2.3275e-04 eta: 0:32:08 time: 1.2094 data_time: 0.0141 memory: 6319 loss: 0.2229 | |
| 2023/06/05 21:37:57 - mmengine - INFO - Epoch(train) [6][200/342] lr: 2.1046e-04 eta: 0:30:04 time: 1.1259 data_time: 0.0032 memory: 6319 loss: 0.2249 | |
| 2023/06/05 21:39:40 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 21:39:51 - mmengine - INFO - Epoch(train) [6][300/342] lr: 1.8855e-04 eta: 0:28:01 time: 1.1113 data_time: 0.0009 memory: 6319 loss: 0.2035 | |
| 2023/06/05 21:40:36 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 21:40:36 - mmengine - INFO - Saving checkpoint at 6 epochs | |
| 2023/06/05 21:42:29 - mmengine - INFO - Epoch(val) [6][100/342] eta: 0:04:20 time: 0.3264 data_time: 0.2388 memory: 6319 | |
| 2023/06/05 21:44:05 - mmengine - INFO - Epoch(val) [6][200/342] eta: 0:02:24 time: 0.2174 data_time: 0.1302 memory: 3133 | |
| 2023/06/05 21:46:08 - mmengine - INFO - Epoch(val) [6][300/342] eta: 0:00:45 time: 1.1842 data_time: 1.0961 memory: 3133 | |
| 2023/06/05 21:48:58 - mmengine - INFO - Epoch(val) [6][342/342] accuracy/top1: 58.6636 data_time: 1.2616 time: 1.3514 | |
| 2023/06/05 21:50:54 - mmengine - INFO - Epoch(train) [7][100/342] lr: 1.5844e-04 eta: 0:25:06 time: 1.1492 data_time: 0.5207 memory: 6319 loss: 0.2196 | |
| 2023/06/05 21:52:48 - mmengine - INFO - Epoch(train) [7][200/342] lr: 1.3820e-04 eta: 0:23:05 time: 1.2282 data_time: 0.2014 memory: 6319 loss: 0.2140 | |
| 2023/06/05 21:54:57 - mmengine - INFO - Epoch(train) [7][300/342] lr: 1.1893e-04 eta: 0:21:11 time: 1.1372 data_time: 0.0008 memory: 6319 loss: 0.2145 | |
| 2023/06/05 21:55:43 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 21:55:43 - mmengine - INFO - Saving checkpoint at 7 epochs | |
| 2023/06/05 21:57:37 - mmengine - INFO - Epoch(val) [7][100/342] eta: 0:04:21 time: 0.3393 data_time: 0.2504 memory: 6319 | |
| 2023/06/05 21:59:15 - mmengine - INFO - Epoch(val) [7][200/342] eta: 0:02:25 time: 0.2251 data_time: 0.1374 memory: 3133 | |
| 2023/06/05 22:01:14 - mmengine - INFO - Epoch(val) [7][300/342] eta: 0:00:45 time: 1.1680 data_time: 1.0796 memory: 3133 | |
| 2023/06/05 22:03:49 - mmengine - INFO - Epoch(val) [7][342/342] accuracy/top1: 57.8239 data_time: 1.2072 time: 1.2968 | |
| 2023/06/05 22:05:46 - mmengine - INFO - Epoch(train) [8][100/342] lr: 9.3587e-05 eta: 0:18:20 time: 1.0941 data_time: 0.0016 memory: 6319 loss: 0.2031 | |
| 2023/06/05 22:07:44 - mmengine - INFO - Epoch(train) [8][200/342] lr: 7.7361e-05 eta: 0:16:21 time: 1.1903 data_time: 0.0012 memory: 6319 loss: 0.2023 | |
| 2023/06/05 22:09:39 - mmengine - INFO - Epoch(train) [8][300/342] lr: 6.2632e-05 eta: 0:14:21 time: 1.2062 data_time: 0.0015 memory: 6319 loss: 0.2108 | |
| 2023/06/05 22:10:25 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 22:10:25 - mmengine - INFO - Saving checkpoint at 8 epochs | |
| 2023/06/05 22:12:20 - mmengine - INFO - Epoch(val) [8][100/342] eta: 0:04:23 time: 0.3376 data_time: 0.2488 memory: 6319 | |
| 2023/06/05 22:13:59 - mmengine - INFO - Epoch(val) [8][200/342] eta: 0:02:27 time: 0.2099 data_time: 0.1225 memory: 3133 | |
| 2023/06/05 22:16:02 - mmengine - INFO - Epoch(val) [8][300/342] eta: 0:00:46 time: 1.1863 data_time: 1.0969 memory: 3133 | |
| 2023/06/05 22:18:34 - mmengine - INFO - Epoch(val) [8][342/342] accuracy/top1: 57.4348 data_time: 1.2203 time: 1.3109 | |
| 2023/06/05 22:20:30 - mmengine - INFO - Epoch(train) [9][100/342] lr: 4.4532e-05 eta: 0:11:31 time: 1.1255 data_time: 0.2349 memory: 6319 loss: 0.2043 | |
| 2023/06/05 22:22:29 - mmengine - INFO - Epoch(train) [9][200/342] lr: 3.3915e-05 eta: 0:09:33 time: 1.1331 data_time: 0.0008 memory: 6319 loss: 0.2061 | |
| 2023/06/05 22:23:44 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 22:24:22 - mmengine - INFO - Epoch(train) [9][300/342] lr: 2.5163e-05 eta: 0:07:34 time: 1.2186 data_time: 0.0009 memory: 6319 loss: 0.1880 | |
| 2023/06/05 22:25:10 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 22:25:10 - mmengine - INFO - Saving checkpoint at 9 epochs | |
| 2023/06/05 22:27:03 - mmengine - INFO - Epoch(val) [9][100/342] eta: 0:04:20 time: 0.3659 data_time: 0.2787 memory: 6319 | |
| 2023/06/05 22:28:40 - mmengine - INFO - Epoch(val) [9][200/342] eta: 0:02:25 time: 0.2184 data_time: 0.1318 memory: 3133 | |
| 2023/06/05 22:30:43 - mmengine - INFO - Epoch(val) [9][300/342] eta: 0:00:45 time: 1.2018 data_time: 1.1051 memory: 3133 | |
| 2023/06/05 22:33:16 - mmengine - INFO - Epoch(val) [9][342/342] accuracy/top1: 57.2224 data_time: 1.2147 time: 1.3041 | |
| 2023/06/05 22:35:11 - mmengine - INFO - Epoch(train) [10][100/342] lr: 1.6078e-05 eta: 0:04:45 time: 1.1201 data_time: 0.1549 memory: 6319 loss: 0.1912 | |
| 2023/06/05 22:37:04 - mmengine - INFO - Epoch(train) [10][200/342] lr: 1.2111e-05 eta: 0:02:47 time: 1.1655 data_time: 0.0007 memory: 6319 loss: 0.2117 | |
| 2023/06/05 22:38:57 - mmengine - INFO - Epoch(train) [10][300/342] lr: 1.0191e-05 eta: 0:00:49 time: 1.0937 data_time: 0.0011 memory: 6319 loss: 0.1982 | |
| 2023/06/05 22:39:49 - mmengine - INFO - Exp name: resnet50_2xb256_stylegan3_1m_lr5e-4_aug_1e-1_20230605_201824 | |
| 2023/06/05 22:39:49 - mmengine - INFO - Saving checkpoint at 10 epochs | |
| 2023/06/05 22:41:43 - mmengine - INFO - Epoch(val) [10][100/342] eta: 0:04:22 time: 0.3482 data_time: 0.2601 memory: 6319 | |
| 2023/06/05 22:43:21 - mmengine - INFO - Epoch(val) [10][200/342] eta: 0:02:26 time: 0.2168 data_time: 0.1303 memory: 3133 | |
| 2023/06/05 22:45:24 - mmengine - INFO - Epoch(val) [10][300/342] eta: 0:00:46 time: 1.2010 data_time: 1.1128 memory: 3133 | |
| 2023/06/05 22:47:58 - mmengine - INFO - Epoch(val) [10][342/342] accuracy/top1: 56.7966 data_time: 1.2155 time: 1.3052 | |