gistfile1.txt

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.

import os
import glob
from datetime import datetime

from setuptools import find_packages, setup



current_date = datetime.now().strftime("%Y.%m.%d")


def read_requirements(file_path):
    with open(file_path, "r") as file:
        return file.read().splitlines()


# Determine the package name based on the presence of an environment variable
package_name = "torchao-nightly" if os.environ.get("TORCHAO_NIGHTLY") else "torchao"

# Version is year.month.date if using nightlies
version = current_date if package_name == "torchao-nightly" else "0.1"

def BuildExtension(*args, **kwargs):
    import torch
    from torch.utils.cpp_extension import BuildExtension as BE
    return BE(*args, **kwargs)

def get_extensions():
    import torch

    from torch.utils.cpp_extension import (
    CppExtension,
    CUDAExtension,
    BuildExtension,
    CUDA_HOME,
    )

    debug_mode = os.getenv('DEBUG', '0') == '1'
    if debug_mode:
        print("Compiling in debug mode")

    use_cuda = torch.cuda.is_available() and CUDA_HOME is not None
    extension = CUDAExtension if use_cuda else CppExtension

    extra_link_args = []
    extra_compile_args = {
        "cxx": [
            "-O3" if not debug_mode else "-O0",
            "-fdiagnostics-color=always",
        ],
        "nvcc": [
            "-O3" if not debug_mode else "-O0",
        ]
    }
    if debug_mode:
        extra_compile_args["cxx"].append("-g")
        extra_compile_args["nvcc"].append("-g")
        extra_link_args.extend(["-O0", "-g"])

    # this_dir = os.path.dirname(os.path.abspath(__file__))
    this_dir = os.path.dirname(os.path.curdir)
    extensions_dir = os.path.join(this_dir, "torchao", "csrc")
    sources = list(glob.glob(os.path.join(extensions_dir, "*.cpp")))

    extensions_cuda_dir = os.path.join(extensions_dir, "cuda")
    cuda_sources = list(glob.glob(os.path.join(extensions_cuda_dir, "*.cu")))

    if use_cuda:
        sources += cuda_sources

    ext_modules = [
        extension(
            "torchao._C",
            sources,
            extra_compile_args=extra_compile_args,
            extra_link_args=extra_link_args,
        )
    ]

    return ext_modules


setup(
    name=package_name,
    version=version,
    packages=find_packages(),
    include_package_data=True,
    package_data={
        "torchao.kernel.configs": ["*.pkl"],
    },
    ext_modules=get_extensions(),
    install_requires=read_requirements("requirements.txt"),
    setup_requires=['torch'],
    description="Package for applying ao techniques to GPU models",
    long_description=open("README.md").read(),
    long_description_content_type="text/markdown",
    url="https://github.com/pytorch-labs/ao",
    cmdclass={"build_ext": BuildExtension},
)