Reference: https://docs.astral.sh/ruff/formatter/black/#assert-statements
> Unlike Black, Ruff prefers breaking the message over breaking the assertion, similar to how both Ruff and Black prefer breaking the assignment value over breaking the assignment target:
>
> ```python
> # Input
> assert (
> len(policy_types) >= priority + num_duplicates
> ), f"This tests needs at least {priority+num_duplicates} many types."
>
>
> # Black
> assert (
> len(policy_types) >= priority + num_duplicates
> ), f"This tests needs at least {priority+num_duplicates} many types."
>
> # Ruff
> assert len(policy_types) >= priority + num_duplicates, (
> f"This tests needs at least {priority + num_duplicates} many types."
> )
> ```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/144546
Approved by: https://github.com/malfet
This is one of a series of PRs to update us to PEP585 (changing Dict -> dict, List -> list, etc). Most of the PRs were completely automated with RUFF as follows:
Since RUFF UP006 is considered an "unsafe" fix first we need to enable unsafe fixes:
```
--- a/tools/linter/adapters/ruff_linter.py
+++ b/tools/linter/adapters/ruff_linter.py
@@ -313,6 +313,7 @@
"ruff",
"check",
"--fix-only",
+ "--unsafe-fixes",
"--exit-zero",
*([f"--config={config}"] if config else []),
"--stdin-filename",
```
Then we need to tell RUFF to allow UP006 (as a final PR once all of these have landed this will be made permanent):
```
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -40,7 +40,7 @@
[tool.ruff]
-target-version = "py38"
+target-version = "py39"
line-length = 88
src = ["caffe2", "torch", "torchgen", "functorch", "test"]
@@ -87,7 +87,6 @@
"SIM116", # Disable Use a dictionary instead of consecutive `if` statements
"SIM117",
"SIM118",
- "UP006", # keep-runtime-typing
"UP007", # keep-runtime-typing
]
select = [
```
Finally running `lintrunner -a --take RUFF` will fix up the deprecated uses.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/145101
Approved by: https://github.com/bobrenjc93
Currently there are a few type annotations that falsely state that mypy doesn't support recursive types.
Recursive type support is available in mypy for a few years already. It has been officially enabled in [version 0.991](https://mypy-lang.blogspot.com/2022/11/mypy-0990-released.html). Pyright even had support for recursive types earlier (https://github.com/microsoft/pyright/issues/569), so there is probably no reason not to model these types correctly.
This PR models these types properly now. Since this has turned a few implicit `Any` into fully typed variables that are not narrowed cleanly, a small number of type ignores were necessary.
Note that regarding the `Argument` it is desirable to model it in a covariant way (i.e. using `Sequence` and `Mapping`) instead of making it invariant unnecessarily (using `List` and `Dict`). If it were modeled invariant, it would for instance mean that a `List[Node]` would not type check as `Argument`, because invariance would mean that it really has to be a `List[Argument]` (i.e., including all the branches of the union type). Since even the name of the type "argument" strongly suggest that it is semantically used as "argument", having covariance natural anyway.
There are no chances in this PR that affect runtime behavior.
CC @Skylion007
Pull Request resolved: https://github.com/pytorch/pytorch/pull/142300
Approved by: https://github.com/ezyang, https://github.com/Skylion007
This PR only adds the execution of the benchmarks on this PR and print results, following diffs will add checking out head~1 and running it and comparing.
to access results goto test pr_time_benchmarks and inspect logs:
you should see
```
+ echo 'benchmark results on current PR: '
benchmark results on current PR:
+ cat /var/lib/jenkins/workspace/test/test-reports/pr_time_benchmarks_before.txt
update_hint_regression,instruction_count,27971461254
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/131475
Approved by: https://github.com/ezyang
The `usort` config in `pyproject.toml` has no effect due to a typo. Fixing the typo make `usort` do more and generate the changes in the PR. Except `pyproject.toml`, all changes are generated by `lintrunner -a --take UFMT --all-files`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127126
Approved by: https://github.com/kit1980
The `usort` config in `pyproject.toml` has no effect due to a typo. Fixing the typo make `usort` do more and generate the changes in the PR. Except `pyproject.toml`, all changes are generated by `lintrunner -a --take UFMT --all-files`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127126
Approved by: https://github.com/kit1980
ghstack dependencies: #127122, #127123, #127124, #127125
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
This PR fixes the instruction count benchmark
1. Fix the updated import path
2. Allows building the benchmark with less compiler options (remove all "-W" options)
Test plan:
```
BENCHMARK_USE_DEV_SHM=1 python main.py --mode ci
```
Manually tested and worked on the CI machine.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/85359
Approved by: https://github.com/robieta
Summary:
This is actually something I discovered a while ago with the wall of serotonin. It was really easy for large scale runs to get bottlenecked on disk access. I have a hack in the working files of that machine to use `/dev/shm`, but I figured I should formalize and actually make a respectable utility.
I also added a param to tweak the run cadence and print when a CorePool is created; these are just to make the CI logs a bit nicer. (A printout each second on a 40 minute CI job is a bit much...)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56711
Reviewed By: agolynski
Differential Revision: D28392248
Pulled By: robieta
fbshipit-source-id: b6aa7445c488d8e4ab9d4b31ab18df4e12783d8f
Summary:
This PR add a `--mode` flag and a script to collect microbenchmarks in a single JSON file. I also added a version check since benchmarks are expected to evolve; this also turned up a determinism bug in `init_from_variants`. (`set` is not ordered, unlike `dict`)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55428
Test Plan:
Run in CI
CC: ngimel wconstab ezyang bhosmer
Reviewed By: mruberry
Differential Revision: D27775284
Pulled By: robieta
fbshipit-source-id: c8c338fedbfb2860df207fe204212a0121ecb006
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54652
This PR adds a fairly robust runner for the instruction count microbenchmarks. Key features are:
* Timeout and retry. (In rare cases, Callgrind will hang under heavy load.)
* Robust error handling and keyboard interrupt support.
* Benchmarks are pinned to cores. (Wall times still won't be great, but it's something.)
* Progress printouts, including a rough ETA.
Test Plan: Imported from OSS
Reviewed By: pbelevich
Differential Revision: D27537823
Pulled By: robieta
fbshipit-source-id: 699ac907281d28bf7ffa08594253716ca40204ba
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54651
This PR fleshes out the benchmarks to everything I could come up with. (166 individual cases when all is said and done.) If there's anything you feel warrants a spot in CI that I've missed, by all means let me know.
Test Plan: Imported from OSS
Reviewed By: pbelevich
Differential Revision: D27537824
Pulled By: robieta
fbshipit-source-id: 3819e8fec2131c6b5f29f5099cd41e79131bed90
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53296
Part 1 of the instruction count microbenchmarks. This PR is focused on benchmark definition machinery. (Though you can run `main.py` to see it in action.) A summary of the system is given in the README.
Test Plan: Imported from OSS
Reviewed By: ngimel
Differential Revision: D26907092
Pulled By: robieta
fbshipit-source-id: 0f61457b3ce89aa59a06bf1f0e7a74ccdbf17090
