[英]Pytorch transforms.RandomRotation() does not work on Google Colab
Normally i was working on letter&digit recognition on my computer and I wanted to move my project to Colab but unfortunately there was an error (you can see the error below).通常,我正在计算机上进行字母和数字识别,我想将我的项目移至 Colab,但不幸的是出现错误(您可以在下面看到错误)。 after some debugging i found which line is giving me error.
经过一些调试后,我发现哪一行给了我错误。
transforms.RandomRotation(degrees=(90, -90))
below i wrote simple abstract code to show this error.This code does not work on colab but it works fine at my own computer environment.Problem might be about the different versions of pytorch library i have version 1.3.1 on my computer and colab uses version 1.4.0.下面我写了简单的抽象代码来显示这个错误。这段代码在 colab 上不起作用,但它在我自己的计算机环境中工作正常。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()
The full error I got when I execute this sample code above on Google Colab.
我在 Google Colab 上执行上面的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)
You're absolutely correct.你是完全正确的。 torchvision 0.5 has a bug in
RandomRotation()
in the fill
argument probably due to incompatible Pillow version. torchvision 0.5 在
fill
参数中的RandomRotation()
有一个错误,可能是由于枕头版本不兼容。 This issue has now been fixed ( PR#1760 ) and will be resolved in the next release.此问题现已修复 ( PR#1760 ),并将在下一个版本中解决。
Temporarily, you add fill=(0,)
to RandomRotation
transform to fix it.暂时,您将
fill=(0,)
添加到RandomRotation
变换以修复它。
transforms.RandomRotation(degrees=(90, -90), fill=(0,))
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