对自己的数据集进行moco自监督训练时，报错提示not enough values to unpack，请问如何解决

[ratcat1232]

请问是不是数据集格式的问题？
2021-12-25 15:33:39,456 - mmselfsup - INFO - workflow: [('train', 1)], max: 200 epochs
2021-12-25 15:33:39,457 - mmselfsup - INFO - Checkpoints will be saved to /home/sipl/zy/mmselfsup/work_dirs/imagelist_test by HardDiskBackend.
/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/utils/registry.py:251: UserWarning: The old API of register_module(module, force=False) is deprecated and will be removed, please use the new API register_module(name=None, force=False, module=None) instead.
warnings.warn(
/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/utils/registry.py:251: UserWarning: The old API of register_module(module, force=False) is deprecated and will be removed, please use the new API register_module(name=None, force=False, module=None) instead.
warnings.warn(
/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/utils/registry.py:251: UserWarning: The old API of register_module(module, force=False) is deprecated and will be removed, please use the new API register_module(name=None, force=False, module=None) instead.
warnings.warn(
/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/utils/registry.py:251: UserWarning: The old API of register_module(module, force=False) is deprecated and will be removed, please use the new API register_module(name=None, force=False, module=None) instead.
warnings.warn(
2021-12-25 15:33:52,377 - mmcv - INFO - Reducer buckets have been rebuilt in this iteration.
Exception in thread Thread-1:
Traceback (most recent call last):
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/threading.py", line 932, in _bootstrap_inner
self.run()
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/threading.py", line 870, in run
self._target(*self._args, **self._kwargs)
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/torch/utils/data/_utils/pin_memory.py", line 28, in _pin_memory_loop
idx, data = r
ValueError: not enough values to unpack (expected 2, got 0)
Traceback (most recent call last):
File "tools/train.py", line 158, in
main()
File "tools/train.py", line 148, in main
train_model(
File "/home/sipl/zy/mmselfsup/mmselfsup/apis/train.py", line 186, in train_model
runner.run(data_loaders, cfg.workflow)
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 127, in run
epoch_runner(data_loaders[i], **kwargs)
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 47, in train
for i, data_batch in enumerate(self.data_loader):
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 349, in iter
self._iterator._reset(self)
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 852, in _reset
data = self._get_data()
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1029, in _get_data
raise RuntimeError('Pin memory thread exited unexpectedly')
RuntimeError: Pin memory thread exited unexpectedly
Traceback (most recent call last):
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/torch/distributed/launch.py", line 260, in
main()
File "/home/sipl/anaconda3/envs/mmdet/lib/python3.8/site-packages/torch/distributed/launch.py", line 255, in main
raise subprocess.CalledProcessError(returncode=process.returncode,
subprocess.CalledProcessError: Command '['/home/sipl/anaconda3/envs/mmdet/bin/python', '-u', 'tools/train.py', '--local_rank=0', 'configs/selfsup/densecl/densecl_resnet50.py', '--seed', '0', '--launcher', 'pytorch', '--work_dir', 'work_dirs/imagelist_test/']' returned non-zero exit status 1.

1. I have searched related issues but cannot get the expected help.
2. I have read the FAQ documentation but cannot get the expected help.

[fangyixiao18]

could you please provide your env_info and the format of your own dataset?

[ratcat1232]

could you please provide your env_info and the format of your own dataset?

感谢您的回复,以下是我的env_info和数据集格式信息:

PyTorch version: 1.7.1
Is debug build: False
CUDA used to build PyTorch: 9.2
ROCM used to build PyTorch: N/A

OS: Ubuntu 16.04.6 LTS (x86_64)
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609
Clang version: Could not collect
CMake version: Could not collect

Python version: 3.8 (64-bit runtime)
Is CUDA available: True
CUDA runtime version: 9.2.148
GPU models and configuration: GPU 0: TITAN X (Pascal)
Nvidia driver version: 418.43
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.20.2
[pip3] torch==1.7.1
[pip3] torch-tb-profiler==0.2.1
[pip3] torchaudio==0.7.0a0+a853dff
[pip3] torchvision==0.8.2
[conda] blas 1.0 mkl https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
[conda] cudatoolkit 9.2 0 defaults
[conda] mkl 2021.2.0 h06a4308_296 defaults
[conda] mkl-service 2.3.0 py38h27cfd23_1 defaults
[conda] mkl_fft 1.3.0 py38h42c9631_2 defaults
[conda] mkl_random 1.2.1 py38ha9443f7_2 defaults
[conda] numpy 1.20.2 py38h2d18471_0 defaults
[conda] numpy-base 1.20.2 py38hfae3a4d_0 defaults
[conda] pytorch 1.7.1 py3.8_cuda9.2.148_cudnn7.6.3_0 pytorch
[conda] torch-tb-profiler 0.2.1
[conda] torchaudio 0.7.2 py38 pytorch
[conda] torchvision 0.8.2 py38_cu92 pytorch
Pillow (6.2.2)

数据集的结构和imagenet一样
train文件夹存放图片,meta包括一个标注了图片名的txt文件--train.txt.
这个txt文件只标注了文件名称,没有标签信息.

顺便一提,我更换了以前版本(就是需要mmcv=1.0.3的版本)的openselfsup,成功调通了代码.

[fangyixiao18]

你的 data config 里 data_source 是用的 ImageNet 还是 ImageList 呢？

[ratcat1232]

你的 data config 里 data_source 是用的 ImageNet 还是 ImageList 呢？

您好，我是用的是imagelist

[fangyixiao18]

应该是版本问题，我们在 datasets/builder.py 里 pytorch 版本检查地方写的有点小问题，我们会改成 1.8 来避免一下。pytorch 1.7 中 pin_memory 和 persistent_worker 不能一起使用， 之前 mmcls 也有类似问题。open-mmlab/mmpretrain#472