Summary:
Context: https://github.com/pytorch/pytorch/pull/53299#discussion_r587882857
These are the only hand-written parts of this diff:
- the addition to `.github/workflows/lint.yml`
- the file endings changed in these four files (to appease FB-internal land-blocking lints):
- `GLOSSARY.md`
- `aten/src/ATen/core/op_registration/README.md`
- `scripts/README.md`
- `torch/csrc/jit/codegen/fuser/README.md`
The rest was generated by running this command (on macOS):
```
git grep -I -l ' $' -- . ':(exclude)**/contrib/**' ':(exclude)third_party' | xargs gsed -i 's/ *$//'
```
I looked over the auto-generated changes and didn't see anything that looked problematic.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53406
Test Plan:
This run (after adding the lint but before removing existing trailing spaces) failed:
- https://github.com/pytorch/pytorch/runs/2043032377
This run (on the tip of this PR) succeeded:
- https://github.com/pytorch/pytorch/runs/2043296348
Reviewed By: walterddr, seemethere
Differential Revision: D26856620
Pulled By: samestep
fbshipit-source-id: 3f0de7f7c2e4b0f1c089eac9b5085a58dd7e0d97
Summary:
Fixes https://github.com/pytorch/pytorch/issues/49034
Pull Request resolved: https://github.com/pytorch/pytorch/pull/49035
Test Plan:
Imported from GitHub, without a `Test Plan:` line.
Force rebased to deal with merge conflicts
Reviewed By: zhangguanheng66
Differential Revision: D25767065
Pulled By: walterddr
fbshipit-source-id: ffb904e449f137825824e3f43f3775a55e9b011b
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/38211
Just because the annotations are inline doesn't mean the files type
check; most of the newly annotated files have type errors and I
added exclusions for them in mypy.ini. The payoff of moving
all of these modules inline is I can delete the relevant code
generation logic for the pyi files (which was added ignore
annotations that weren't actually relevant anymore.)
For the most part the translation was completely mechanical, but there
were two hairy issues. First, I needed to work around a Python 3.6 and
earlier bug where Generic has a nontrivial metaclass. This fix is in
torch/jit/__init__.py. Second, module.py, we need to apply the same
fix for avoiding contravariance checks that the pyi file used to have;
this is done by declaring forward as a variable (rather than a
function), which appears to be sufficient enough to get mypy to not
contravariantly check input arguments.
Because we aren't actually typechecking these modules in most
cases, it is inevitable that some of these type annotations are wrong.
I slavishly copied the old annotations from the pyi files unless there
was an obvious correction I could make. These annotations will probably
need fixing up later.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Test Plan: Imported from OSS
Differential Revision: D21497397
Pulled By: ezyang
fbshipit-source-id: 2b08bacc152c48f074e7edc4ee5dce1b77d83702
Summary:
xref gh-32838, gh-34032
This is a major refactor of parts of the documentation to split it up using sphinx's `autosummary` feature which will build out `autofuction` and `autoclass` stub files and link to them. The end result is that the top module pages like torch.nn.rst and torch.rst are now more like table-of-contents to the actual single-class or single-function documentations pages.
Along the way, I modified many of the docstrings to eliminate sphinx warnings when building. I think the only thing I changed from a non-documentation perspective is to add names to `__all__` when adding them to `globals()` in `torch.__init__.py`
I do not know the CI system: are the documentation build artifacts available after the build, so reviewers can preview before merging?
Pull Request resolved: https://github.com/pytorch/pytorch/pull/37419
Differential Revision: D21337640
Pulled By: ezyang
fbshipit-source-id: d4ad198780c3ae7a96a9f22651e00ff2d31a0c0f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/32745
Some parameters (like `bias` in conv) are optional. To achieve this
previously, you had to add `bias` as a constant, which would invoke some
pretty weird behavior in the frontend, summarized as:
```
if bias is not None:
add it as a parameter normally
else: # bias is None
add it as a constant with the value None
```
There are several things bad about this:
1. Bias is not a constant. Marking it `__constants__` is confusing.
2. It basically relies on an implementation detail (the frontend
processes parameters before constants) to work.
Okay, whatever. I don't even know why we did this originally, but
getting rid of it doesn't break anything, so I assume improved NoneType
refinement has made this a non-issue.
Note on perf: this will make no difference; if bias was `None` it's still
folded out today, if bias is a Tensor it would be added as a parameter
both before and after this change
Test Plan: Imported from OSS
Differential Revision: D19628634
Pulled By: suo
fbshipit-source-id: d9128a09c5d096b938fcf567b8c23b09ac9ab37f
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/25339
This is to get rid of backend-specific dispatch in modules; this autograd function is no longer backend specific so
doesn't need to be in a backend specific location.
Test Plan: Imported from OSS
Differential Revision: D17101576
Pulled By: gchanan
fbshipit-source-id: f4f0bd3ecc2d4dbd8cdfedbaabcadb8c603d2507
Summary:
We are planning to put up a deprecation warning for legacy autograd function in 1.2: https://github.com/pytorch/pytorch/pull/22922. This PR removes all usage of legacy function in PyTorch core and test suite, to prepare for the eventual removal of legacy function.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22925
Differential Revision: D16344834
Pulled By: yf225
fbshipit-source-id: 8bf4cca740398835a08b7a290f3058c3e46781ba
Summary:
* Deletes all weak script decorators / associated data structures / methods
* In order to keep supporting the standard library in script, this enables recursive script on any function defined in `torch.nn`
* Most changes in `torch/nn` are the result of `ag -Q "weak" torch/nn/ -l | xargs sed -i '/weak/d'`, only `rnn.py` needed manual editing to use the `ignore` and `export` to continue supporting the overloaded `forward` methods
* `Sequential`/`ModuleList` no longer need to be added to constants since they are compiled on demand
This should also fix https://github.com/pytorch/pytorch/issues/22212
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22212
Differential Revision: D15988346
Pulled By: driazati
fbshipit-source-id: af223e3ad0580be895377312949997a70e988e4f
Summary:
A bunch of modules were missing entries for `__constants__` which was making their `__repr__`s not work. Others had `__constants__` that were not necessary since it was provided by some parent class instead.
Fixes#20978
](https://our.intern.facebook.com/intern/diff/15539518/)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21071
Pulled By: driazati
Differential Revision: D15539518
fbshipit-source-id: 24bdd1ef41ef636eefd5d2bad4ab2d79646ed4f0
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18598
ghimport-source-id: c74597e5e7437e94a43c163cee0639b20d0d0c6a
Stack from [ghstack](https://github.com/ezyang/ghstack):
* **#18598 Turn on F401: Unused import warning.**
This was requested by someone at Facebook; this lint is turned
on for Facebook by default. "Sure, why not."
I had to noqa a number of imports in __init__. Hypothetically
we're supposed to use __all__ in this case, but I was too lazy
to fix it. Left for future work.
Be careful! flake8-2 and flake8-3 behave differently with
respect to import resolution for # type: comments. flake8-3 will
report an import unused; flake8-2 will not. For now, I just
noqa'd all these sites.
All the changes were done by hand.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Differential Revision: D14687478
fbshipit-source-id: 30d532381e914091aadfa0d2a5a89404819663e3
Summary:
PR to update the shape notation for all of the torch.nn modules to take a unified form. The goal is to make these definitions machine-readable and those checkable by unifying the style across all of the different modules.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15741
Differential Revision: D13709601
Pulled By: ezyang
fbshipit-source-id: fb89a03903fdf0cd0dcf76f3e469b8582b2f3634
Summary:
This PR:
1. Handle None value attr in the WeakScriptModuleProxy
2. add back module tests that now passing
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14715
Differential Revision: D13313573
Pulled By: wanchaol
fbshipit-source-id: a6b7892707350290a6d69b6f6270ad089bfc954b
Summary:
Commits:
1. In extension doc, get rid of all references of `Variable` s (Closes#6947 )
+ also add minor improvements
+ also added a section with links to cpp extension :) goldsborough
+ removed mentions of `autograd.Function.requires_grad` as it's not used anywhere and hardcoded to `return_Py_True`.
2. Fix several sphinx warnings
3. Change `*` in equations in `module/conv.py` to `\times`
4. Fix docs for `Fold` and `Unfold`.
+ Added better shape check for `Fold` (it previously may give bogus result when there are not enough blocks). Added test for the checks.
5. Fix doc saying `trtrs` not available for CUDA (#9247 )
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9239
Reviewed By: soumith
Differential Revision: D8762492
Pulled By: SsnL
fbshipit-source-id: 13cd91128981a94493d5efdf250c40465f84346a
This PR enables users to print extra information of their subclassed nn.Module.
Now I simply insert the user-defined string at the ending of module name, which should be discussed in this PR.
Before this PR, users should redefine the __repr__ and copy&paste the source code from Module.
* Add support for extra information on Module
* Rewrite the repr method of Module
* Fix flake8
* Change the __repr__ to get_extra_repr in Linear
* Fix extra new-line for empty line
* Add test for __repr__ method
* Fix bug of block string indent
* Add indent for multi-line repr test.
* Address review comments
* Update tutorial for creating nn.Module
* Fix flake8, add extra_repr of bilinear
* Refactor DropoutNd
* Change to extra_repr in some Modules
* Fix flake8
* Refactor padding modules
* Refactor pooling module
* Fix typo
* Change to extra_repr
* Fix bug for GroupNorm
* Fix bug for LayerNorm
* Fix some minor errors in existing docs.
* Fix Convolution and Pooling docs in torch.nn.functional
* Cleaned up torch.nn.functional docs
* Address @SsnL 's comments
* Add multiplication sign missing in docs
* Fix more typos, and clear some warnings
* Change infinity symbol in LPPool2d
* Revert some changes in torch.nn.functional
* Few more minor changes
* Improvize documentation
1. Add formula for erf, erfinv
2. Make exp, expm1 similar to log, log1p
3. Symbol change in ge, le, ne, isnan
* Fix minor nit in the docstring
* More doc improvements
1. Added some formulae
2. Complete scanning till "Other Operations" in Tensor docs
* Add more changes
1. Modify all torch.Tensor wherever required
* Fix Conv docs
1. Fix minor nits in the references for LAPACK routines
* Improve Pooling docs
1. Fix lint error
* Improve docs for RNN, Normalization and Padding
1. Fix flake8 error for pooling
* Final fixes for torch.nn.* docs.
1. Improve Loss Function documentation
2. Improve Vision Layers documentation
* Fix lint error
* Improve docstrings in torch.nn.init
* Fix lint error
* Fix minor error in torch.nn.init.sparse
* Fix Activation and Utils Docs
1. Fix Math Errors
2. Add explicit clean to Makefile in docs to prevent running graph generation script
while cleaning
3. Fix utils docs
* Make PYCMD a Makefile argument, clear up prints in the build_activation_images.py
* Fix batch norm doc error
The nn.* counterpart of #5443 . Mostly removed Variable wrapper. Also added doc for nn.RReLU.
Notice that torch.randn(*, requires_grad=True) isn't documented until #5462 is done.
* at::maybe_data_ptr and Check.h => TensorUtils.h
* THNN support for optional BN running_*
* ATen support for optional BN running_*
* Python nn.* support for optional BN running_*; Improve IN and BN doc
* Add tests for IN and BN new option
* Layer Norm
* Fix LRN doc
* functional interface for LN and IN
* Layer norm tests
* fix BN double backward returning undefined tensors
* fix jit test using wrong dim inputs for BN
* add/improve BN, IN and LN GPU tests with half type
* Udpate docs to be consistent with Conv notation
Fix onnx
Clarified onnx symbokic wrapper
* fix typo
* Address comments
* Fix LaTex rendering in CosineAnnealingLR
Backslashes were interpreted by Python as escapes in the string, so \frac
turned into frac, which is not a valid LaTex command.
This could be fixed with double backslashes, but the easiest solution is to
just use a raw (r) docstring.
* Fix sphinx warnings for LRN doc headings
* Move LRN docstring from __init__ to class level
The docstring was not rendered by sphinx at
http://pytorch.org/docs/master/nn.html#torch.nn.LocalResponseNorm
because it was in the constructor.
* Remove superfluous backticks from LRN formula
Here's the command I used to invoke autopep8 (in parallel!):
git ls-files | grep '\.py$' | xargs -n1 -P`nproc` autopep8 -i
Several rules are ignored in setup.cfg. The goal is to let autopep8
handle everything which it can handle safely, and to disable any rules
which are tricky or controversial to address. We may want to come back
and re-enable some of these rules later, but I'm trying to make this
patch as safe as possible.
Also configures flake8 to match pep8's behavior.
Also configures TravisCI to check the whole project for lint.
Uses the assignment syntax to get deterministic ordering of parameters.
The ordering of parameters using the constructor syntax is
non-deterministic because kwargs use dict() in Python 3.5 and earlier.
