我刚开始使用PyTorch进行PyTorch-Tutorial 深度学习：60分钟闪电战我应该补充一点，我之前没有编写过任何python（但其他语言如Java）。
现在，我的代码看起来像
import torch
import torchvision
import torchvision.transforms as transforms
import matplotlib.pyplot as plt
import numpy as np
print("\n-------------------Backpropagation-------------------\n")
transform = transforms.Compose(
[transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])
trainset = torchvision.datasets.CIFAR10(root='./data', train=True,download=True, transform=transform)
trainloader = torch.utils.data.DataLoader(trainset, batch_size=4, shuffle=True, num_workers=2)
testset = torchvision.datasets.CIFAR10(root='./data', train=False, download=True, transform=transform)
testloader = torch.utils.data.DataLoader(testset, batch_size=4, shuffle=False, num_workers=2)
classes = ('plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck')
dataiter = iter(trainloader)
images, labels = dataiter.next()
def imshow(img):
img = img / 2 + 0.5
npimg = img.numpy()
plt.imshow(np.transpose(npimg, (1, 2, 0)))
imshow(torchvision.utils.make_grid(images))
print(' '.join('%5s' % classes[labels[j]] for j in range(4)))
应该与教程一致。 如果我执行此操作，我将收到以下错误：
"C:\Program Files\Anaconda3\python.exe" C:/MA/pytorch/deepLearningWithPytorchTutorial/trainingClassifier.py
-------------------Backpropagation-------------------
Files already downloaded and verified
Files already downloaded and verified
-------------------Backpropagation-------------------
Files already downloaded and verified
Files already downloaded and verified
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "C:\Program Files\Anaconda3\lib\multiprocessing\spawn.py", line 105, in spawn_main
exitcode = _main(fd)
File "C:\Program Files\Anaconda3\lib\multiprocessing\spawn.py", line 114, in _main
prepare(preparation_data)
File "C:\Program Files\Anaconda3\lib\multiprocessing\spawn.py", line 225, in prepare
_fixup_main_from_path(data['init_main_from_path'])
File "C:\Program Files\Anaconda3\lib\multiprocessing\spawn.py", line 277, in _fixup_main_from_path
run_name="__mp_main__")
File "C:\Program Files\Anaconda3\lib\runpy.py", line 263, in run_path
pkg_name=pkg_name, script_name=fname)
File "C:\Program Files\Anaconda3\lib\runpy.py", line 96, in _run_module_code
mod_name, mod_spec, pkg_name, script_name)
File "C:\Program Files\Anaconda3\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "C:\MA\pytorch\deepLearningWithPytorchTutorial\trainingClassifier.py", line 23, in <module>
dataiter = iter(trainloader)
File "C:\Program Files\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 451, in __iter__
return _DataLoaderIter(self)
File "C:\Program Files\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 239, in __init__
w.start()
File "C:\Program Files\Anaconda3\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "C:\Program Files\Anaconda3\lib\multiprocessing\context.py", line 223, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "C:\Program Files\Anaconda3\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "C:\Program Files\Anaconda3\lib\multiprocessing\popen_spawn_win32.py", line 33, in __init__
prep_data = spawn.get_preparation_data(process_obj._name)
File "C:\Program Files\Anaconda3\lib\multiprocessing\spawn.py", line 143, in get_preparation_data
_check_not_importing_main()
File "C:\Program Files\Anaconda3\lib\multiprocessing\spawn.py", line 136, in _check_not_importing_main
is not going to be frozen to produce an executable.''')
RuntimeError:
An attempt has been made to start a new process before the
current process has finished its bootstrapping phase.
This probably means that you are not using fork to start your
child processes and you have forgotten to use the proper idiom
in the main module:
if __name__ == '__main__':
freeze_support()
...
The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce an executable.
Traceback (most recent call last):
File "C:/MA/pytorch/deepLearningWithPytorchTutorial/trainingClassifier.py", line 23, in <module>
dataiter = iter(trainloader)
File "C:\Program Files\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 451, in __iter__
return _DataLoaderIter(self)
File "C:\Program Files\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 239, in __init__
w.start()
File "C:\Program Files\Anaconda3\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "C:\Program Files\Anaconda3\lib\multiprocessing\context.py", line 223, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "C:\Program Files\Anaconda3\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "C:\Program Files\Anaconda3\lib\multiprocessing\popen_spawn_win32.py", line 65, in __init__
reduction.dump(process_obj, to_child)
File "C:\Program Files\Anaconda3\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj)
BrokenPipeError: [Errno 32] Broken pipe
Process finished with exit code 1
我已经下载了 *。py 和 * .ipynb 。 使用jupyter运行 * .ipynb 工作正常（但我不想在juniper web界面中编程，我更喜欢pyCharm）而 * .py 在控制台（Anaconda提示符和cmd）失败并出现相同的错误。
有谁知道如何解决这个问题？ （我使用的是Python 3.6.5（来自Anaconda）和pyCharm，操作系统：Win10 64位）
谢谢！ 好处
更新
如果它是相关的，我只需将num_workers=2设置为num_workers=0（两者），然后它就会工作..。
答案 0 :(得分：1)
由于Windows中multiprocessing的实现方式不同，您需要使用此块包装主代码：
if __name__ == '__main__':
有关详情，请查看the official PyTorch Windows notes。
答案 1 :(得分：1)
查看Windows multiprocessing: programming guidelines的文档。您应该将所有操作包装在函数中，然后在if __name__ == '__main__'子句中调用它们：
# required imports
def load_datasets(...):
# Code to load the datasets with multiple workers
def train(...):
# Code to train the model
if __name__ == '__main__':
load_datasets()
train()
简而言之，这里的想法是将示例代码包装在if __name__ == '__main__'语句中。