log_vml_cpu not implemented for 'Long'

[MistSun-Chen]

Traceback (most recent call last):
File "Situation3.py", line 187, in
print("random.choice(style_dataset)",random.choice(style_dataset))
File "/home/guest/cwy/miniconda3/lib/python3.8/random.py", line 291, in choice
return seq[i]
File "/home/guest/cwy/miniconda3/lib/python3.8/site-packages/torchvision/datasets/folder.py", line 153, in getitem
sample = self.transform(sample)
File "/home/guest/cwy/miniconda3/lib/python3.8/site-packages/torchvision/transforms/transforms.py", line 67, in call
img = t(img)
File "/home/guest/cwy/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/guest/cwy/miniconda3/lib/python3.8/site-packages/torchvision/transforms/transforms.py", line 823, in forward
i, j, h, w = self.get_params(img, self.scale, self.ratio)
File "/home/guest/cwy/miniconda3/lib/python3.8/site-packages/torchvision/transforms/transforms.py", line 787, in get_params
log_ratio = torch.log(torch.tensor(ratio))
RuntimeError: log_vml_cpu not implemented for 'Long'

when I run python Situation3.py,I got this question .Does anyone has the same problem?How to solve this problem？Hope someone can reply

[Carateffee]

Change
"scale=(256/480, 1), ratio=(1, 1)"
to
"scale=(256/480, 1.0), ratio=(1.0, 1.0)"

As in the Pytorch Docs:
CLASStorchvision.transforms.RandomResizedCrop(size, scale=(0.08, 1.0), ratio=(0.75, 1.3333333333333333), interpolation=2)[SOURCE]
Crop the given image to random size and aspect ratio. The image can be a PIL Image or a Tensor, in which case it is expected to have […, H, W] shape, where … means an arbitrary number of leading dimensions

A crop of random size (default: of 0.08 to 1.0) of the original size and a random aspect ratio (default: of 3/4 to 4/3) of the original aspect ratio is made. This crop is finally resized to given size. This is popularly used to train the Inception networks.

Parameters
size (int or sequence) – expected output size of each edge. If size is an int instead of sequence like (h, w), a square output size (size, size) is made. If provided a tuple or list of length 1, it will be interpreted as (size[0], size[0]).

scale (tuple of python:float) – range of size of the origin size cropped

ratio (tuple of python:float) – range of aspect ratio of the origin aspect ratio cropped.

interpolation (int) – Desired interpolation enum defined by filters. Default is PIL.Image.BILINEAR. If input is Tensor, only PIL.Image.NEAREST, PIL.Image.BILINEAR and PIL.Image.BICUBIC are supported.