Preferring dash over underscore in command-line options. Add `--command-arg-name` to the argument parser. The old arguments with underscores `--command_arg_name` are kept for backward compatibility.
Both dashes and underscores are used in the PyTorch codebase. Some argument parsers only have dashes or only have underscores in arguments. For example, the `torchrun` utility for distributed training only accepts underscore arguments (e.g., `--master_port`). The dashes are more common in other command-line tools. And it looks to be the default choice in the Python standard library:
`argparse.BooleanOptionalAction`: 4a9dff0e5a/Lib/argparse.py (L893-L895)
```python
class BooleanOptionalAction(Action):
def __init__(...):
if option_string.startswith('--'):
option_string = '--no-' + option_string[2:]
_option_strings.append(option_string)
```
It adds `--no-argname`, not `--no_argname`. Also typing `_` need to press the shift or the caps-lock key than `-`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94505
Approved by: https://github.com/ezyang, https://github.com/seemethere
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75601
User annotations was previously pushed down to the GPU timelines but was disabled during a refactoring some time back. This patch re-enables it in PyTorch Profiler.
Test Plan: CI Tests
Reviewed By: chaekit
Differential Revision: D34591916
Pulled By: aaronenyeshi
fbshipit-source-id: 3f4d5327b391725f4ce4e3eb16740bac2cd1c618
(cherry picked from commit 4bc07174dfef8fb2ffbefba224773a4618ed203a)
Summary:
As this diff shows, currently there are a couple hundred instances of raw `noqa` in the codebase, which just ignore all errors on a given line. That isn't great, so this PR changes all existing instances of that antipattern to qualify the `noqa` with respect to a specific error code, and adds a lint to prevent more of this from happening in the future.
Interestingly, some of the examples the `noqa` lint catches are genuine attempts to qualify the `noqa` with a specific error code, such as these two:
```
test/jit/test_misc.py:27: print(f"{hello + ' ' + test}, I'm a {test}") # noqa E999
test/jit/test_misc.py:28: print(f"format blank") # noqa F541
```
However, those are still wrong because they are [missing a colon](https://flake8.pycqa.org/en/3.9.1/user/violations.html#in-line-ignoring-errors), which actually causes the error code to be completely ignored:
- If you change them to anything else, the warnings will still be suppressed.
- If you add the necessary colons then it is revealed that `E261` was also being suppressed, unintentionally:
```
test/jit/test_misc.py:27:57: E261 at least two spaces before inline comment
test/jit/test_misc.py:28:35: E261 at least two spaces before inline comment
```
I did try using [flake8-noqa](https://pypi.org/project/flake8-noqa/) instead of a custom `git grep` lint, but it didn't seem to work. This PR is definitely missing some of the functionality that flake8-noqa is supposed to provide, though, so if someone can figure out how to use it, we should do that instead.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56272
Test Plan:
CI should pass on the tip of this PR, and we know that the lint works because the following CI run (before this PR was finished) failed:
- https://github.com/pytorch/pytorch/runs/2365189927
Reviewed By: janeyx99
Differential Revision: D27830127
Pulled By: samestep
fbshipit-source-id: d6dcf4f945ebd18cd76c46a07f3b408296864fcb
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34230
This PR adds some benchmarks that we used to assess tensor expressions performance.
Differential Revision: D20251830
Test Plan: Imported from OSS
Pulled By: ZolotukhinM
fbshipit-source-id: bafd66ce32f63077e3733112d854f5c750d5b1af
Summary:
In the long string, formalstring thinks it is good to have a name.
When using dict, literal is better for readability and faster than dict constructor.
I always appreciate your efforts in creating the world's best frameworks.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/31352
Differential Revision: D19191967
Pulled By: ngimel
fbshipit-source-id: 21f063b163b67de8cf9761a4db5991f74318e991
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21502
In BenchResult, we keep name, avg_fwd, std_fwd, avg_bwd, and std_bwd. There is no information about the number of each iteration. In this diff, I am adding more info to BenchResult to include the number reported from each iteration.
Reviewed By: wanchaol
Differential Revision: D15706306
fbshipit-source-id: 3f14be4ba91f1f6da473995783bd7af1d067938d
Summary:
Sometimes at::cat gets transposed inputs and goes on a slow path. Also, make jit_premul lstm benchmark add bias to the whole input tensor to avoid separate reduction kernels in the backward pass.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18816
Differential Revision: D15013576
Pulled By: wanchaol
fbshipit-source-id: bcfa1cf44180b11b05b0f55f034707012f66281a
