pytorch/benchmarks/dynamo/test.py
Xuehai Pan a229b4526f [BE] Prefer dash over underscore in command-line options (#94505)
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
2023-02-09 20:16:49 +00:00

45 lines
1.2 KiB
Python

import os
import unittest
from .common import parse_args, run
from .torchbench import setup_torchbench_cwd, TorchBenchmarkRunner
try:
# fbcode only
from aiplatform.utils.sanitizer_status import is_asan_or_tsan
except ImportError:
def is_asan_or_tsan():
return False
class TestDynamoBenchmark(unittest.TestCase):
@unittest.skipIf(is_asan_or_tsan(), "ASAN/TSAN not supported")
def test_benchmark_infra_runs(self) -> None:
"""
Basic smoke test that TorchBench runs.
This test is mainly meant to check that our setup in fbcode
doesn't break.
If you see a failure here related to missing CPP headers, then
you likely need to update the resources list in:
//caffe2:inductor
"""
original_dir = setup_torchbench_cwd()
try:
args = parse_args(
[
"-dcpu",
"--inductor",
"--performance",
"--only=BERT_pytorch",
"-n1",
"--batch-size=1",
]
)
run(TorchBenchmarkRunner(), args, original_dir)
finally:
os.chdir(original_dir)