Check if at least one element in tensor is nonzero

1

I want to check if a tensor contains nonzero elements. It does not matter to me how many nonzero elements there are. I currently do the following which is very inefficient for large tensors:

T.abs().sum().item() == 0

Is there a better way to do this in PyTorch? Like a function that stops iterating through the tensor as soon as it finds the first nonzero element?

2

Not too sure on that, but I do believe that this:

T.abs().sum().item() == 0

will be much faster than

a function that stops iterating through the tensor as soon as it finds the first nonzero element?

as loops/iterators are very very slow :open_mouth:

3

Also this might be of interest: .nonzero()

image

You can check some_tensor.nonzero() and check for empty results (i.e. tensor([])

1 Like
4

tensorName.type(t.uint8).any()

5

I guess tensor_name.any() should work fine. Why the type() call?

6

Without typecasting, I get this error:
RuntimeError: all only supports torch.uint8 and torch.bool dtypes
At least with pytorch version 1.7.1