Error when I use resume_from

[tarv33]

Once I use 'resume_from' in config, mmaction2 will report error.

2021-05-19 01:08:48,176 - mmaction - INFO - Environment info:
------------------------------------------------------------
sys.platform: linux
Python: 3.7.7 (default, May  7 2020, 21:25:33) [GCC 7.3.0]
CUDA available: True
GPU 0,1,2,3: Tesla V100-PCIE-16GB
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 10.1, V10.1.243
GCC: gcc (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0
PyTorch: 1.6.0
PyTorch compiling details: PyTorch built with:
  - GCC 7.3
  - C++ Version: 201402
  - Intel(R) Math Kernel Library Version 2020.0.1 Product Build 20200208 for Intel(R) 64 architecture applications
  - Intel(R) MKL-DNN v1.5.0 (Git Hash e2ac1fac44c5078ca927cb9b90e1b3066a0b2ed0)
  - OpenMP 201511 (a.k.a. OpenMP 4.5)
  - NNPACK is enabled
  - CPU capability usage: AVX2
  - CUDA Runtime 10.1
  - 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_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_37,code=compute_37
  - CuDNN 7.6.3
  - Magma 2.5.2
  - Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -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-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, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=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_STATIC_DISPATCH=OFF, 

TorchVision: 0.7.0
OpenCV: 4.5.1
MMCV: 1.3.0
MMCV Compiler: GCC 7.3
MMCV CUDA Compiler: 10.1
MMAction2: 0.13.0+6a252b8
------------------------------------------------------------

2021-05-19 01:08:48,176 - mmaction - INFO - Distributed training: False
2021-05-19 01:08:48,176 - mmaction - INFO - Config: /mmaction2/configs/recognition/tin/tin_r50_1x1x8_40e_sthv2_rgb.py
checkpoint_config = dict(interval=1)
log_config = dict(
    interval=20,
    hooks=[
        dict(type='TextLoggerHook'),
        # dict(type='TensorboardLoggerHook'),
    ])
# runtime settings
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = None
resume_from = None
workflow = [('train', 1)]


# model settings
model = dict(
    type='Recognizer2D',
    backbone=dict(
        type='ResNetTIN',
        pretrained='torchvision://resnet50',
        depth=50,
        norm_eval=False,
        shift_div=4),
    cls_head=dict(
        type='TSMHead',
        num_classes=174,
        in_channels=2048,
        spatial_type='avg',
        consensus=dict(type='AvgConsensus', dim=1),
        dropout_ratio=0.8,
        init_std=0.001,
        is_shift=False),
    # model training and testing settings
    train_cfg=None,
    test_cfg=dict(average_clips=None))


# dataset settings
dataset_type = 'RawframeDataset'
data_root = 'data/sthv2/rawframes'
data_root_val = 'data/sthv2/rawframes'
ann_file_train = 'data/sthv2/sthv2_train_list_rawframes.txt'
ann_file_val = 'data/sthv2/sthv2_val_list_rawframes.txt'
ann_file_test = 'data/sthv2/sthv2_val_list_rawframes.txt'
img_norm_cfg = dict(
    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_bgr=False)
train_pipeline = [
    dict(type='SampleFrames', clip_len=1, frame_interval=1, num_clips=8),
    dict(type='RawFrameDecode'),
    dict(type='Resize', scale=(-1, 256)),
    dict(
        type='MultiScaleCrop',
        input_size=224,
        scales=(1, 0.875, 0.75, 0.66),
        random_crop=False,
        max_wh_scale_gap=1),
    dict(type='Resize', scale=(224, 224), keep_ratio=False),
    dict(type='Normalize', **img_norm_cfg),
    dict(type='FormatShape', input_format='NCHW'),
    dict(type='Collect', keys=['imgs', 'label'], meta_keys=[]),
    dict(type='ToTensor', keys=['imgs', 'label'])
]
val_pipeline = [
    dict(
        type='SampleFrames',
        clip_len=1,
        frame_interval=1,
        num_clips=8,
        test_mode=True),
    dict(type='RawFrameDecode'),
    dict(type='Resize', scale=(-1, 256)),
    dict(type='CenterCrop', crop_size=224),
    dict(type='Normalize', **img_norm_cfg),
    dict(type='FormatShape', input_format='NCHW'),
    dict(type='Collect', keys=['imgs', 'label'], meta_keys=[]),
    dict(type='ToTensor', keys=['imgs'])
]
test_pipeline = [
    dict(
        type='SampleFrames',
        clip_len=1,
        frame_interval=1,
        num_clips=8,
        test_mode=True),
    dict(type='RawFrameDecode'),
    dict(type='Resize', scale=(-1, 256)),
    dict(type='CenterCrop', crop_size=224),
    dict(type='Normalize', **img_norm_cfg),
    dict(type='FormatShape', input_format='NCHW'),
    dict(type='Collect', keys=['imgs', 'label'], meta_keys=[]),
    dict(type='ToTensor', keys=['imgs'])
]
data = dict(
    videos_per_gpu=12, #6,
    workers_per_gpu=4,
    train=dict(
        type=dataset_type,
        ann_file=ann_file_train,
        data_prefix=data_root,
        pipeline=train_pipeline),
    val=dict(
        type=dataset_type,
        ann_file=ann_file_val,
        data_prefix=data_root_val,
        pipeline=val_pipeline),
    test=dict(
        type=dataset_type,
        ann_file=ann_file_test,
        data_prefix=data_root_val,
        pipeline=test_pipeline))
evaluation = dict(
    interval=2, metrics=['top_k_accuracy', 'mean_class_accuracy'])

# optimizer
optimizer = dict(
    type='SGD',
    constructor='TSMOptimizerConstructor',
    paramwise_cfg=dict(fc_lr5=True),
    lr=0.02,  # this lr is used for 8 gpus
    momentum=0.9,
    weight_decay=0.0005)
optimizer_config = dict(grad_clip=dict(max_norm=20, norm_type=2))
# learning policy
lr_config = dict(
    policy='CosineAnnealing',
    by_epoch=False,
    warmup='linear',
    warmup_iters=1,
    warmup_by_epoch=True,
    min_lr=0)
total_epochs = 40

# runtime settings
work_dir = './work_dirs/tin_r50_1x1x8_40e_sthv2_rgb/'
resume_from = './work_dirs/tin_r50_1x1x8_40e_sthv2_rgb/epoch_29.pth'

Use load_from_torchvision loader
2021-05-19 01:08:49,657 - mmaction - INFO - These parameters in pretrained checkpoint are not loaded: {'fc.weight', 'fc.bias'}
2021-05-19 01:08:55,979 - mmaction - INFO - load checkpoint from ./work_dirs/tin_r50_1x1x8_40e_sthv2_rgb/epoch_29.pth
2021-05-19 01:08:55,979 - mmaction - INFO - Use load_from_local loader
Traceback (most recent call last):
  File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/config.py", line 96, in _validate_py_syntax
    ast.parse(content)
  File "/opt/conda/lib/python3.7/ast.py", line 35, in parse
    return compile(source, filename, mode, PyCF_ONLY_AST)
  File "<unknown>", line 1
    /mmaction2/configs/_base_/models/tin_r50.py
    ^
SyntaxError: invalid syntax

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "tools/train.py", line 197, in <module>
    main()
  File "tools/train.py", line 193, in main
    meta=meta)
  File "/mmaction2/mmaction/apis/train.py", line 157, in train_model
    runner.resume(cfg.resume_from)
  File "/opt/conda/lib/python3.7/site-packages/mmcv/runner/base_runner.py", line 347, in resume
    checkpoint['meta']['config'], file_format='.py')
  File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/config.py", line 279, in fromstring
    cfg = Config.fromfile(temp_file.name)
  File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/config.py", line 252, in fromfile
    use_predefined_variables)
  File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/config.py", line 145, in _file2dict
    Config._validate_py_syntax(filename)
  File "/opt/conda/lib/python3.7/site-packages/mmcv/utils/config.py", line 98, in _validate_py_syntax
    raise SyntaxError('There are syntax errors in config '
SyntaxError: There are syntax errors in config file /tmp/tmpkq2pesx0.py: invalid syntax (<unknown>, line 1)
Exception ignored in: <function _TemporaryFileCloser.__del__ at 0x7f1f26907830>
Traceback (most recent call last):
  File "/opt/conda/lib/python3.7/tempfile.py", line 448, in __del__
    self.close()
  File "/opt/conda/lib/python3.7/tempfile.py", line 444, in close
    unlink(self.name)
FileNotFoundError: [Errno 2] No such file or directory: '/tmp/tmpenshl8j0/tmp0er7xxxe.py'

[innerlee]

This is fixed in #820

[tarv33]

Thanks