Error while trying to use torch.rand_like() on a one dimensional array created using torch.arange()

[VijayV28]

Hey,
I was trying to implement the torch.rand_like() on an array generated by torch.arange() and got an error:

Array:

range1 = torch.arange(start=10, end=101, step=10)

Random function:

ten_random_numbers = torch.rand_like(input=(range1))

This threw an error as shown below:
RuntimeError: "check_uniform_bounds" not implemented for 'Long'

However, I later discovered that the dtype of the tensor generated by the torch.arange function is int64.
The rand_like() works well once I change the dtype back to float32:

range1 = torch.arange(start=10, end=101, step=10, dtype=torch.float32)

I'd really like to know why doesn't rand_like() support int64 datatype while the other tensor_like() functions do.

[mrdbourke]

Hi @VijayV28,

That's an excellent question I don't have the answer to.

I'd like to know too.

Perhaps asking in the PyTorch forums could help?

https://discuss.pytorch.org

[VijayV28]

Thanks a lot for your response. Will try your suggestion 👍