通常，我正在计算机上进行字母和数字识别，我想将项目移至Colab，但不幸的是出现了错误（您可以在下面看到错误）。经过一些调试后，我发现哪条线给了我错误。
transforms.RandomRotation(degrees=(90, -90))
以下我编写了简单的抽象代码来显示此错误。此代码在colab上不起作用，但在我自己的计算机环境下可以正常工作。问题可能与pytorch库的不同版本有关，我在计算机上的版本为1.3.1， colab使用版本1.4.0。
import torch
import torchvision
from torchvision import datasets, transforms
import matplotlib.pyplot as plt
transformOpt = transforms.Compose([
transforms.RandomRotation(degrees=(90, -90)),
transforms.ToTensor()
])
train_set = datasets.MNIST(
root='', train=True, transform=transformOpt, download=True)
test_set = datasets.MNIST(
root='', train=False, transform=transformOpt, download=True)
train_loader = torch.utils.data.DataLoader(
dataset=train_set,
batch_size=100,
shuffle=True)
test_loader = torch.utils.data.DataLoader(
dataset=test_set,
batch_size=100,
shuffle=False)
images, labels = next(iter(train_loader))
plt.imshow(images[0].view(28, 28), cmap="gray")
plt.show()
当我在Google Colab上执行上述示例代码时遇到的完整错误。
TypeError Traceback (most recent call last)
<ipython-input-1-8409db422154> in <module>()
24 shuffle=False)
25
---> 26 images, labels = next(iter(train_loader))
27 plt.imshow(images[0].view(28, 28), cmap="gray")
28 plt.show()
10 frames
/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py in __next__(self)
343
344 def __next__(self):
--> 345 data = self._next_data()
346 self._num_yielded += 1
347 if self._dataset_kind == _DatasetKind.Iterable and \
/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py in _next_data(self)
383 def _next_data(self):
384 index = self._next_index() # may raise StopIteration
--> 385 data = self._dataset_fetcher.fetch(index) # may raise StopIteration
386 if self._pin_memory:
387 data = _utils.pin_memory.pin_memory(data)
/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py in fetch(self, possibly_batched_index)
42 def fetch(self, possibly_batched_index):
43 if self.auto_collation:
---> 44 data = [self.dataset[idx] for idx in possibly_batched_index]
45 else:
46 data = self.dataset[possibly_batched_index]
/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py in <listcomp>(.0)
42 def fetch(self, possibly_batched_index):
43 if self.auto_collation:
---> 44 data = [self.dataset[idx] for idx in possibly_batched_index]
45 else:
46 data = self.dataset[possibly_batched_index]
/usr/local/lib/python3.6/dist-packages/torchvision/datasets/mnist.py in __getitem__(self, index)
95
96 if self.transform is not None:
---> 97 img = self.transform(img)
98
99 if self.target_transform is not None:
/usr/local/lib/python3.6/dist-packages/torchvision/transforms/transforms.py in __call__(self, img)
68 def __call__(self, img):
69 for t in self.transforms:
---> 70 img = t(img)
71 return img
72
/usr/local/lib/python3.6/dist-packages/torchvision/transforms/transforms.py in __call__(self, img) 1001 angle = self.get_params(self.degrees) 1002
-> 1003 return F.rotate(img, angle, self.resample, self.expand, self.center, self.fill) 1004 1005 def
__repr__(self):
/usr/local/lib/python3.6/dist-packages/torchvision/transforms/functional.py in rotate(img, angle, resample, expand, center, fill)
727 fill = tuple([fill] * 3)
728
--> 729 return img.rotate(angle, resample, expand, center, fillcolor=fill)
730
731
/usr/local/lib/python3.6/dist-packages/PIL/Image.py in rotate(self, angle, resample, expand, center, translate, fillcolor) 2003 w, h = nw, nh 2004
-> 2005 return self.transform((w, h), AFFINE, matrix, resample, fillcolor=fillcolor) 2006 2007 def save(self, fp, format=None, **params):
/usr/local/lib/python3.6/dist-packages/PIL/Image.py in transform(self, size, method, data, resample, fill, fillcolor) 2297 raise ValueError("missing method data") 2298
-> 2299 im = new(self.mode, size, fillcolor) 2300 if method == MESH: 2301 # list of quads
/usr/local/lib/python3.6/dist-packages/PIL/Image.py in new(mode, size, color) 2503 im.palette = ImagePalette.ImagePalette() 2504 color = im.palette.getcolor(color)
-> 2505 return im._new(core.fill(mode, size, color)) 2506 2507
TypeError: function takes exactly 1 argument (3 given)