[英]Multiprocessing freeze_support() error in Python
我是深度學習概念的新手,到目前為止一直在使用 google colab 來運行深度學習模型。 當我對 pycharm 進行同樣的嘗試時,出現了這個錯誤。 Project_name=model,file_name=model.py
from __future__ import print_function, division
import torch
import torch.nn as nn
import torch.optim as optim
from torch.optim import lr_scheduler
import torch.backends.cudnn as cudnn
import numpy as np
import torchvision
from torchvision import datasets, models, transforms
import matplotlib.pyplot as plt
import time
import os
import copy
cudnn.benchmark = True
plt.ion() # interactive mode
data_transforms = {
'train': transforms.Compose([
transforms.RandomResizedCrop(224),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
]),
'val': transforms.Compose([
transforms.Resize(256),
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
]),
}
data_dir = '.\hymenoptera_data'
image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x),
data_transforms[x])
for x in ['train', 'val']}
dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=4,
shuffle=True, num_workers=4)
for x in ['train', 'val']}
dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'val']}
class_names = image_datasets['train'].classes
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
##visualize the model
def imshow(inp, title=None):
"""Imshow for Tensor."""
inp = inp.numpy().transpose((1, 2, 0))
mean = np.array([0.485, 0.456, 0.406])
std = np.array([0.229, 0.224, 0.225])
inp = std * inp + mean
inp = np.clip(inp, 0, 1)
plt.imshow(inp)
if title is not None:
plt.title(title)
plt.pause(0.001) # pause a bit so that plots are updated
inputs, classes = next(iter(dataloaders['train']))
out = torchvision.utils.make_grid(inputs)
imshow(out, title=[class_names[x] for x in classes])
我沒有任何主要方法,直接運行model.py,這是否合法?idk
錯誤:
(venv) PS C:\Users\prasa\PycharmProjects\model> python model.py
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "C:\python 39\lib\multiprocessing\spawn.py", line 116, in spawn_main
exitcode = _main(fd, parent_sentinel)
File "C:\python 39\lib\multiprocessing\spawn.py", line 125, in _main
prepare(preparation_data)
File "C:\python 39\lib\multiprocessing\spawn.py", line 236, in prepare
_fixup_main_from_path(data['init_main_from_path'])
File "C:\python 39\lib\multiprocessing\spawn.py", line 287, in _fixup_main_from_path
main_content = runpy.run_path(main_path,
File "C:\python 39\lib\runpy.py", line 268, in run_path
return _run_module_code(code, init_globals, run_name,
File "C:\python 39\lib\runpy.py", line 97, in _run_module_code
...
The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce an executable.
如果您的應用程序沒有main()
function 但在導入期間執行它的代碼,則multiprocessing
標准庫模塊無法正常工作。
解決方案是將代碼移動到main()
function 之類的
import ...
...
def main():
# your code here....
if __name__ == "__main__":
main()
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