How to concatenate list of pytorch tensors?

Suppose I have a list tensors in the same size. Is there any unified function to merge all these like np.array(array_list) in case you have list or numpy arrays.

This is my current solution

 data = th.zeros([len(imgs), imgs[0].size()[0], imgs[0].size()[1], imgs[0].size()[2]])
 for i, img in enumerate(imgs): 
       print(img.size())
       print(img.type())
       data[i] = img
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You can use torch.cat or torch.stack

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just in case you were wondering about the difference:


stack

Concatenates sequence of tensors along a new dimension.

cat

Concatenates the given sequence of seq tensors in the given dimension.

So if A and B are of shape (3, 4), torch.cat([A, B], dim=0) will be of shape (6, 4) and torch.stack([A, B], dim=0) will be of shape (2, 3, 4).

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What if A is of shape (1,3,4) and B is (3,4)?

I want the result to be (2,3,4). How do I do this?

a = torch.rand(1, 3, 4)
print(a.shape)
b = torch.rand(3, 4)
print(b.shape)
b = b.unsqueeze(0)
print(b.shape)
c = torch.cat([a, b], dim=0)
print(c.shape)
3 Likes

Thank you, it works.