…#17582)

Summary:
Argument dim=-1 doesn't work for torch.cross. The signature of the torch.cross has been changed to c10::optional<int64_t> dim instead of int64_t. So based on document "If dim is not given, it defaults to the first dimension found with the size 3." and if dim is specified (even negative) it will use the correspondent dim.

Fixes #17229
Pull Request resolved: pytorch/pytorch#17582

Differential Revision: D14483063

Pulled By: ifedan

fbshipit-source-id: f9699093ec401cb185fd33ca4563c8a46cdcd746

Summary:
### Create `linalg.cross`

Fixes #62810

As discussed in the corresponding issue, this PR adds `cross` to the `linalg` namespace (**Note**: There is no method variant) which is slightly different in behaviour compared to `torch.cross`.

**Note**: this is NOT an alias as suggested in mruberry's [#62810 comment](#62810 (comment)) below
> linalg.cross being consistent with the Python Array API (over NumPy) makes sense because NumPy has no linalg.cross. I also think we can implement linalg.cross without immediately deprecating torch.cross, although we should definitely refer users to linalg.cross. Deprecating torch.cross will require additional review. While it's not used often it is used, and it's unclear if users are relying on its unique behavior or not.

The current default implementation of `torch.cross` is extremely weird and confusing. This has also been reported multiple times previously. (See #17229, #39310, #41850, #50273)

- [x] Add `torch.linalg.cross` with default `dim=-1`
- [x] Add OpInfo and other tests for `torch.linalg.cross`
- [x] Add broadcasting support to `torch.cross` and `torch.linalg.cross`
- [x] Remove out skip from `torch.cross` OpInfo
- [x] Add docs for `torch.linalg.cross`. Improve docs for `torch.cross` mentioning `linalg.cross` and the difference between the two. Also adds a warning to `torch.cross`, that it may change in the future (we might want to deprecate it later)

 ---

### Additional Fixes to `torch.cross`
- [x] Fix Doc for Tensor.cross
- [x] Fix torch.cross in `torch/overridres.py`

While working on `linalg.cross` I noticed these small issues with `torch.cross` itself.

[Tensor.cross docs](https://pytorch.org/docs/stable/generated/torch.Tensor.cross.html) still mentions `dim=-1` default which is actually wrong. It should be `dim=None` after the behaviour was updated in PR #17582 but the documentation for the `method` or `function` variant wasn’t updated. Later PR #41850 updated the documentation for the `function` variant i.e `torch.cross` and also added the following warning about the weird behaviour.
> If `dim` is not given, it defaults to the first dimension found with the size 3. Note that this might be unexpected.

But still, the `Tensor.cross` docs were missed and remained outdated. I’m finally fixing that here. Also fixing `torch/overrides.py` for `torch.cross` as well now, with `dim=None`.

To verify according to the docs the default behaviour of `dim=-1` should raise, you can try the following.

```python
a = torch.randn(3, 4)
b = torch.randn(3, 4)
b.cross(a)  # this works because the implementation finds 3 in the first dimension and the default behaviour as shown in documentation is actually not true.
>>> tensor([[ 0.7171, -1.1059,  0.4162,  1.3026],
        [ 0.4320, -2.1591, -1.1423,  1.2314],
        [-0.6034, -1.6592, -0.8016,  1.6467]])

b.cross(a, dim=-1)  # this raises as expected since the last dimension doesn't have a 3
>>> RuntimeError: dimension -1 does not have size 3
```

Please take a closer look (particularly the autograd part, this is the first time I'm dealing with `derivatives.yaml`). If there is something missing, wrong or needs more explanation, please let me know. Looking forward to the feedback.

cc mruberry Lezcano IvanYashchuk rgommers

Pull Request resolved: #63285

Reviewed By: gchanan

Differential Revision: D32313346

Pulled By: mruberry

fbshipit-source-id: e68c2687c57367274e8ddb7ef28ee92dcd4c9f2c

Summary:
### Create `linalg.cross`

Fixes #62810

As discussed in the corresponding issue, this PR adds `cross` to the `linalg` namespace (**Note**: There is no method variant) which is slightly different in behaviour compared to `torch.cross`.

**Note**: this is NOT an alias as suggested in mruberry's [#62810 comment](#62810 (comment)) below
> linalg.cross being consistent with the Python Array API (over NumPy) makes sense because NumPy has no linalg.cross. I also think we can implement linalg.cross without immediately deprecating torch.cross, although we should definitely refer users to linalg.cross. Deprecating torch.cross will require additional review. While it's not used often it is used, and it's unclear if users are relying on its unique behavior or not.

The current default implementation of `torch.cross` is extremely weird and confusing. This has also been reported multiple times previously. (See #17229, #39310, #41850, #50273)

- [x] Add `torch.linalg.cross` with default `dim=-1`
- [x] Add OpInfo and other tests for `torch.linalg.cross`
- [x] Add broadcasting support to `torch.cross` and `torch.linalg.cross`
- [x] Remove out skip from `torch.cross` OpInfo
- [x] Add docs for `torch.linalg.cross`. Improve docs for `torch.cross` mentioning `linalg.cross` and the difference between the two. Also adds a warning to `torch.cross`, that it may change in the future (we might want to deprecate it later)

 ---

### Additional Fixes to `torch.cross`
- [x] Fix Doc for Tensor.cross
- [x] Fix torch.cross in `torch/overridres.py`

While working on `linalg.cross` I noticed these small issues with `torch.cross` itself.

[Tensor.cross docs](https://pytorch.org/docs/stable/generated/torch.Tensor.cross.html) still mentions `dim=-1` default which is actually wrong. It should be `dim=None` after the behaviour was updated in PR #17582 but the documentation for the `method` or `function` variant wasn’t updated. Later PR #41850 updated the documentation for the `function` variant i.e `torch.cross` and also added the following warning about the weird behaviour.
> If `dim` is not given, it defaults to the first dimension found with the size 3. Note that this might be unexpected.

But still, the `Tensor.cross` docs were missed and remained outdated. I’m finally fixing that here. Also fixing `torch/overrides.py` for `torch.cross` as well now, with `dim=None`.

To verify according to the docs the default behaviour of `dim=-1` should raise, you can try the following.

```python
a = torch.randn(3, 4)
b = torch.randn(3, 4)
b.cross(a)  # this works because the implementation finds 3 in the first dimension and the default behaviour as shown in documentation is actually not true.
>>> tensor([[ 0.7171, -1.1059,  0.4162,  1.3026],
        [ 0.4320, -2.1591, -1.1423,  1.2314],
        [-0.6034, -1.6592, -0.8016,  1.6467]])

b.cross(a, dim=-1)  # this raises as expected since the last dimension doesn't have a 3
>>> RuntimeError: dimension -1 does not have size 3
```

Please take a closer look (particularly the autograd part, this is the first time I'm dealing with `derivatives.yaml`). If there is something missing, wrong or needs more explanation, please let me know. Looking forward to the feedback.

cc mruberry Lezcano IvanYashchuk rgommers

Pull Request resolved: #63285

Reviewed By: gchanan

Differential Revision: D32313346

Pulled By: mruberry

fbshipit-source-id: e68c2687c57367274e8ddb7ef28ee92dcd4c9f2c

Summary:
### Create `linalg.cross`

Fixes #62810

As discussed in the corresponding issue, this PR adds `cross` to the `linalg` namespace (**Note**: There is no method variant) which is slightly different in behaviour compared to `torch.cross`.

**Note**: this is NOT an alias as suggested in mruberry's [#62810 comment](#62810 (comment)) below
> linalg.cross being consistent with the Python Array API (over NumPy) makes sense because NumPy has no linalg.cross. I also think we can implement linalg.cross without immediately deprecating torch.cross, although we should definitely refer users to linalg.cross. Deprecating torch.cross will require additional review. While it's not used often it is used, and it's unclear if users are relying on its unique behavior or not.

The current default implementation of `torch.cross` is extremely weird and confusing. This has also been reported multiple times previously. (See #17229, #39310, #41850, #50273)

- [x] Add `torch.linalg.cross` with default `dim=-1`
- [x] Add OpInfo and other tests for `torch.linalg.cross`
- [x] Add broadcasting support to `torch.cross` and `torch.linalg.cross`
- [x] Remove out skip from `torch.cross` OpInfo
- [x] Add docs for `torch.linalg.cross`. Improve docs for `torch.cross` mentioning `linalg.cross` and the difference between the two. Also adds a warning to `torch.cross`, that it may change in the future (we might want to deprecate it later)

 ---

### Additional Fixes to `torch.cross`
- [x] Fix Doc for Tensor.cross
- [x] Fix torch.cross in `torch/overridres.py`

While working on `linalg.cross` I noticed these small issues with `torch.cross` itself.

[Tensor.cross docs](https://pytorch.org/docs/stable/generated/torch.Tensor.cross.html) still mentions `dim=-1` default which is actually wrong. It should be `dim=None` after the behaviour was updated in PR #17582 but the documentation for the `method` or `function` variant wasn’t updated. Later PR #41850 updated the documentation for the `function` variant i.e `torch.cross` and also added the following warning about the weird behaviour.
> If `dim` is not given, it defaults to the first dimension found with the size 3. Note that this might be unexpected.

But still, the `Tensor.cross` docs were missed and remained outdated. I’m finally fixing that here. Also fixing `torch/overrides.py` for `torch.cross` as well now, with `dim=None`.

To verify according to the docs the default behaviour of `dim=-1` should raise, you can try the following.

```python
a = torch.randn(3, 4)
b = torch.randn(3, 4)
b.cross(a)  # this works because the implementation finds 3 in the first dimension and the default behaviour as shown in documentation is actually not true.
>>> tensor([[ 0.7171, -1.1059,  0.4162,  1.3026],
        [ 0.4320, -2.1591, -1.1423,  1.2314],
        [-0.6034, -1.6592, -0.8016,  1.6467]])

b.cross(a, dim=-1)  # this raises as expected since the last dimension doesn't have a 3
>>> RuntimeError: dimension -1 does not have size 3
```

Please take a closer look (particularly the autograd part, this is the first time I'm dealing with `derivatives.yaml`). If there is something missing, wrong or needs more explanation, please let me know. Looking forward to the feedback.

cc mruberry Lezcano IvanYashchuk rgommers

Pull Request resolved: #63285

Reviewed By: gchanan

Differential Revision: D32313346

Pulled By: mruberry

fbshipit-source-id: e68c2687c57367274e8ddb7ef28ee92dcd4c9f2c