It seems the current implementation will cut the tensor to min or max according to their values, which might be a problem when debugging logical errors or typos. Maybe it would be better to just throw an exception? Also it would be nice to note that in the documentation.

>>> import torch
>>> print(torch.__version__)
1.6.0
>>> a

Support Series.median()

Numpy has a way to rotate matrices by increments of 90 degrees using their rot90 method that uses transposes and flips.

There is a transpose method for Tensors, but no way of flipping the Tensor that I see.

Is there a way of properly rotating a Tensor/Dense currently, other than through manual iteration over the

The Scaladoc should be similar to numpy's API reference