lezcano 61a5c779bf Make l1_loss composite ...

Fixing the forward AD for `sgn` in the next PR of this stack uncovered a
number of issues with the derivatives of `l1_loss`. Upon inspection,
`l1_loss` was just implemented as a composite function, but it was not
differentiable. This PR makes it a fully differentiable function.

As a side note, `l1_loss_out` was incorrect in a number of ways. Even
more, it is not exposed to the public as `F.l1_loss` does not accept an
`out=` parameter. As such it is not even tested. I wonder how useful is
to have `out=` variants for loss functions if we don't expose them at
all. Even more, I wonder how useful is to have `_out` variants  for loss
functions, given that their most normal use case is to return just a
real number cc jbschlosser

Pull Request resolved: https://github.com/pytorch/pytorch/pull/78257

Approved by: https://github.com/jbschlosser

2022-06-16 00:03:22 +00:00

..

_internal

Make l1_loss composite

2022-06-16 00:03:22 +00:00

__init__.py

cleanup torch.testing namespace (#72708)

2022-02-25 06:30:31 +00:00

_comparison.py

move MPS compat into common comparison machinery (#77836)

2022-06-08 08:09:18 +00:00

_creation.py

[chalf] div, eq, masked_fill, index_put (#77479)

2022-05-18 17:01:08 +00:00

_deprecated.py

promote torch.testing to stable (#73348)

2022-02-25 06:30:31 +00:00

_legacy.py

[complex32] real and imag (also remove unused real and imag kernels)

2022-05-05 04:36:58 +00:00