Commit Graph

5 Commits

Author SHA1 Message Date
Sam Estep
5bcbbf5373 Lint trailing newlines (#54737)
Summary:
*Context:* https://github.com/pytorch/pytorch/issues/53406 added a lint for trailing whitespace at the ends of lines. However, in order to pass FB-internal lints, that PR also had to normalize the trailing newlines in four of the files it touched. This PR adds an OSS lint to normalize trailing newlines.

The changes to the following files (made in 54847d0adb9be71be4979cead3d9d4c02160e4cd) are the only manually-written parts of this PR:

- `.github/workflows/lint.yml`
- `mypy-strict.ini`
- `tools/README.md`
- `tools/test/test_trailing_newlines.py`
- `tools/trailing_newlines.py`

I would have liked to make this just a shell one-liner like the other three similar lints, but nothing I could find quite fit the bill. Specifically, all the answers I tried from the following Stack Overflow questions were far too slow (at least a minute and a half to run on this entire repository):

- [How to detect file ends in newline?](https://stackoverflow.com/q/38746)
- [How do I find files that do not end with a newline/linefeed?](https://stackoverflow.com/q/4631068)
- [How to list all files in the Git index without newline at end of file](https://stackoverflow.com/q/27624800)
- [Linux - check if there is an empty line at the end of a file [duplicate]](https://stackoverflow.com/q/34943632)
- [git ensure newline at end of each file](https://stackoverflow.com/q/57770972)

To avoid giving false positives during the few days after this PR is merged, we should probably only merge it after https://github.com/pytorch/pytorch/issues/54967.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/54737

Test Plan:
Running the shell script from the "Ensure correct trailing newlines" step in the `quick-checks` job of `.github/workflows/lint.yml` should print no output and exit in a fraction of a second with a status of 0. That was not the case prior to this PR, as shown by this failing GHA workflow run on an earlier draft of this PR:

- https://github.com/pytorch/pytorch/runs/2197446987?check_suite_focus=true

In contrast, this run (after correcting the trailing newlines in this PR) succeeded:

- https://github.com/pytorch/pytorch/pull/54737/checks?check_run_id=2197553241

To unit-test `tools/trailing_newlines.py` itself (this is run as part of our "Test tools" GitHub Actions workflow):
```
python tools/test/test_trailing_newlines.py
```

Reviewed By: malfet

Differential Revision: D27409736

Pulled By: samestep

fbshipit-source-id: 46f565227046b39f68349bbd5633105b2d2e9b19
2021-03-30 13:09:52 -07:00
Neha Shah
5ad885b823 [Caffe2][Pruning] Make the caffe2 Sum operator support long types (#40379)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/40379

The current sum operator doesn't support Long .. hence modify the code

Test Plan: Write a test case

Reviewed By: jspark1105, yinghai

Differential Revision: D21917365

fbshipit-source-id: b37d2c100c70d17d2f89c309e40360ddfab584ee
2020-06-23 14:18:29 -07:00
Duke Vijitbenjaronk
d684112ec9 Output sequence probability with CTC beam search, optional multiple output sequences (#21927)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21927

Add `OUTPUT_PROB` output to CTCBeamSearchDecoderOp to return a probability for each sequence.

Add argument to output top-k instead of top-1 decoded sequences.

Reviewed By: SuperIRabbit

Differential Revision: D15797371

fbshipit-source-id: 737ca5cc4f90a0bcc3660ac9f58519a175977b69
2019-07-02 17:29:13 -07:00
Xiaomeng Yang
54b33503ec Optimize channel_stats_op (#16243)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16243

Optimize channel_stats_op and add NHWC impl

Reviewed By: takatosp1

Differential Revision: D13775515

fbshipit-source-id: decb889e646f5316d4afefdf9f9b6bc6343613cd
2019-03-12 12:08:00 -07:00
Ansha Yu
e3e6ca1102 operator serialized test coverage summary document (#13703)
Summary:
Add a markdown document summarizing the coverage of serialized operator tests. This currently only takes into account what has been covered by the tests with respect to the entire registry of c2 operators.

Next, we will break down the coverage by which operators have unit tests associated with them, which have hypothesis tests, and which have tests more specifically calling assertReferenceChecks.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13703

Reviewed By: dzhulgakov

Differential Revision: D12970810

Pulled By: ajyu

fbshipit-source-id: 4f0cd057b1cf734371333e24d26cbab630a170e1
2018-11-09 15:04:08 -08:00