Converting numpy array to tensor on GPU

import torch
from skimage import io

img = io.imread('input.png')

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
print(device)

img =torch.tensor(img, device=device).float()
print(img.device)

Output

cuda:0
cpu

I am not able to convert a numpy array into a torch tensor on GPU. What is the right way to do this?

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You should transform numpy arrays to PyTorch tensors with torch.from_numpy.
Otherwise some weird issues might occur.

img = torch.from_numpy(img).float().to(device)
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That works. Thanks! :smile:

Thank you man this was helpful

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How to achieve this in Pytorch version 0.3.0?

You should use .cpu() or .cuda() instead of the .to(device) method. The others should also exist in 0.3.0.

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