Files
pytorch/benchmarks/README.md
Xuehai Pan 4dce5b71a0 [build] modernize build-frontend: python setup.py develop/install -> [uv ]pip install --no-build-isolation [-e ]. (#156027)
Modernize the development installation:

```bash
# python setup.py develop
python -m pip install --no-build-isolation -e .

# python setup.py install
python -m pip install --no-build-isolation .
```

Now, the `python setup.py develop` is a wrapper around `python -m pip install -e .` since `setuptools>=80.0`:

- pypa/setuptools#4955

`python setup.py install` is deprecated and will emit a warning during run. The warning will become an error on October 31, 2025.

- 9c4d383631/setuptools/command/install.py (L58-L67)

> ```python
> SetuptoolsDeprecationWarning.emit(
>     "setup.py install is deprecated.",
>     """
>     Please avoid running ``setup.py`` directly.
>     Instead, use pypa/build, pypa/installer or other
>     standards-based tools.
>     """,
>     see_url="https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html",
>     due_date=(2025, 10, 31),
> )
> ```

- pypa/setuptools#3849

Additional Resource:

- [Why you shouldn't invoke setup.py directly](https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/156027
Approved by: https://github.com/ezyang
2025-07-09 11:24:27 +00:00

1.2 KiB

PyTorch Benchmarks

This folder contains scripts that produce reproducible timings of various PyTorch features.

It also provides mechanisms to compare PyTorch with other frameworks.

Setup environment

Make sure you're on a machine with CUDA, torchvision, and pytorch installed. Install in the following order:

# Install torchvision. It comes with the pytorch stable release binary
python -m pip install torch torchvision

# Install the latest pytorch master from source.
# It should supersede the installation from the release binary.
cd $PYTORCH_HOME
python -m pip install --no-build-isolation -v -e .

# Check the pytorch installation version
python -c "import torch; print(torch.__version__)"

Benchmark List

Please refer to each subfolder to discover each benchmark suite. Links are provided where descriptions exist: