ValuerError regarding dimensions when declaring PyTorch tensor

Question

I'm currently trying to convert a list of values into a PyTorch tensor and am facing some difficulties.

The exact code that's causing the error is:

input_tensor = torch.cuda.FloatTensor(data)

Here, data is a list with two elements: The first element is another list of NumPy arrays and the second element is a list of tuples. The sizes of both lists differ, and I believe this is causing the following error:

*** ValueError: expected sequence of length x at dim 2 (got y)

Usually y is larger than x. I've tried playing around with an IPython terminal to see what's wrong, and it appears that trying to convert data of this format directly into PyTorch tensors doesn't work. Taking each individual element of the data list and converting those into tensors works, though.

Does anybody know why this doesn't work and perhaps also be able to provide some feedback on how to achieve my original goal? Thanks in advance.

Answer 1

Let's say that the first sublist of data contains n 1D arrays, each of size m, and the second sublist contains k tuples, each of size p.

When calling torch.FloatTensor(data) each sublist is converted to a 2D tensor, of shape (n, m) and of shape (k, p) respectively; then they are stack together to form a 3D tensor. This is possible only if n=k and m=p -- think of a 3D tensor as a cuboid.

This is quite obvious I think, so I guess you have m = p and want to create a 2D tensor of shape (n+k, m) by simply concatenating the two sublists:

torch.FloatTensor(np.concatenate(data))