PyTorch问题

Question

嗨，伙计们，我遇到了一个问题，

 import torchvision.datasets
from torch import nn
from torch.nn import Conv2d
from torch.utils.data import DataLoader

dataset = torchvision.datasets.CIFAR10("./data", train=False, transform=torchvision.transforms.ToTensor, download=True)

dataloader = DataLoader(dataset, batch_size=64)


class MyCnn(nn.Module):
    def __init__(self):
        super(MyCnn, self).__init__()
        self.conv1 = Conv2d(in_channels=3, out_channels=6, kernel_size=3, stride=1, padding=0)

    def forward(self, x):
        x = self.conv1(x)
        return x

myCnn = MyCnn()
print(myCnn)

for data in dataloader:
    imgs, targets = data
    output = myCnn(imgs)
    print(imgs.shape)
    print(output.shape)

它不起作用：

MyCnn(
  (conv1): Conv2d(3, 6, kernel_size=(3, 3), stride=(1, 1))
)
Traceback (most recent call last):
  File "D:/myWork/python/python_study/py/pytorch/nn_conv2d.py", line 33, in <module>
    for data in dataloader:
  File "C:\Users\guy78\anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 530, in __next__
    data = self._next_data()
  File "C:\Users\guy78\anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 570, in _next_data
    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
  File "C:\Users\guy78\anaconda3\lib\site-packages\torch\utils\data\_utils\fetch.py", line 49, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "C:\Users\guy78\anaconda3\lib\site-packages\torch\utils\data\_utils\fetch.py", line 49, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "C:\Users\guy78\anaconda3\lib\site-packages\torchvision\datasets\cifar.py", line 118, in __getitem__
    img = self.transform(img)
KeyboardInterrupt

帮助

Answer 1

这将打印出数据。

dataset = torchvision.datasets.CIFAR10("./data", train=False, transform=torchvision.transforms.ToTensor(), download=True)

这是我在科拉布的Cifar的链接。

https://colab.research.google.com/drive/1lboZmvaTAIWdma9CdUrZbFrrr4gPeZ6t?usp=sharing