我正在尝试运行代码的PyTorch实现,该代码应该适用于SBD数据集。
训练标签最初以 .bin 文件形式提供,然后转换为 HDF5 (.h5) 文件。
运行算法时,出现错误:“TypeError: h5py 对象无法被腌制”
我认为该错误源于 torch.utils.data.DataLoader。
知道我是否在这里遗漏了任何概念吗?我读到,pickling 通常不是首选,但截至目前,我的数据集仅采用 HDF5 格式。
供您参考,错误的堆栈跟踪如下:
File "G:\My Drive\Debvrat - shared\Codes\CASENet PyTorch Implementations\SBD-lijiaman\main.py", line 130, in <module>
main()
File "G:\My Drive\Debvrat - shared\Codes\CASENet PyTorch Implementations\SBD-lijiaman\main.py", line 85, in main
win_feats5, win_fusion, viz, global_step)
File "G:\My Drive\Debvrat - shared\Codes\CASENet PyTorch Implementations\SBD-lijiaman\train_val\model_play.py", line 31, in train
for i, (img, target) in enumerate(train_loader):
File "C:\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 819, in __iter__
return _DataLoaderIter(self)
File "C:\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 560, in __init__
w.start()
File "C:\Anaconda3\lib\multiprocessing\process.py", line 112, in start
self._popen = self._Popen(self)
File "C:\Anaconda3\lib\multiprocessing\context.py", line 223, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "C:\Anaconda3\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "C:\Anaconda3\lib\multiprocessing\popen_spawn_win32.py", line 89, in __init__
reduction.dump(process_obj, to_child)
File "C:\Anaconda3\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj)
File "C:\Anaconda3\lib\site-packages\h5py\_hl\base.py", line 308, in __getnewargs__
raise TypeError("h5py objects cannot be pickled")
TypeError: h5py objects cannot be pickled
我正在使用 Conda 版本 4.8.2、Python 3.7.4、PyTorch 1.0.0 和 Cuda 10.2.89
谢谢,
设置 num_workers=0 为我解决这个问题
我更喜欢使用 h5pickle 作为包装器来读取 h5 文件。 详细信息请参阅:https://github.com/DaanVanVugt/h5pickle