build_pytorch_libs.py

from __future__ import annotations

import os
import platform
from glob import glob

from setuptools import distutils  # type: ignore[import]

from .setup_helpers.cmake import CMake, USE_NINJA
from .setup_helpers.env import check_negative_env_flag, IS_64BIT, IS_WINDOWS


def _overlay_windows_vcvars(env: dict[str, str]) -> dict[str, str]:
    vc_arch = "x64" if IS_64BIT else "x86"

    if platform.machine() == "ARM64":
        vc_arch = "x64_arm64"

        # First Win11 Windows on Arm build version that supports x64 emulation
        # is 10.0.22000.
        win11_1st_version = (10, 0, 22000)
        current_win_version = tuple(
            int(version_part) for version_part in platform.version().split(".")
        )
        if current_win_version < win11_1st_version:
            vc_arch = "x86_arm64"
            print(
                "Warning: 32-bit toolchain will be used, but 64-bit linker "
                "is recommended to avoid out-of-memory linker error!"
            )
            print(
                "Warning: Please consider upgrading to Win11, where x64 "
                "emulation is enabled!"
            )

    vc_env: dict[str, str] = distutils._msvccompiler._get_vc_env(vc_arch)
    # Keys in `_get_vc_env` are always lowercase.
    # We turn them into uppercase before overlaying vcvars
    # because OS environ keys are always uppercase on Windows.
    # https://stackoverflow.com/a/7797329
    vc_env = {k.upper(): v for k, v in vc_env.items()}
    for k, v in env.items():
        uk = k.upper()
        if uk not in vc_env:
            vc_env[uk] = v
    return vc_env


def _create_build_env() -> dict[str, str]:
    # XXX - our cmake file sometimes looks at the system environment
    # and not cmake flags!
    # you should NEVER add something to this list. It is bad practice to
    # have cmake read the environment
    my_env = os.environ.copy()
    if (
        "CUDA_HOME" in my_env
    ):  # Keep CUDA_HOME. This env variable is still used in other part.
        my_env["CUDA_BIN_PATH"] = my_env["CUDA_HOME"]
    elif IS_WINDOWS:  # we should eventually make this as part of FindCUDA.
        cuda_win = glob("C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v*.*")
        if len(cuda_win) > 0:
            my_env["CUDA_BIN_PATH"] = cuda_win[0]

    if IS_WINDOWS and USE_NINJA:
        # When using Ninja under Windows, the gcc toolchain will be chosen as
        # default. But it should be set to MSVC as the user's first choice.
        my_env = _overlay_windows_vcvars(my_env)
        my_env.setdefault("CC", "cl")
        my_env.setdefault("CXX", "cl")
    return my_env


def build_pytorch(
    version: str | None,
    cmake_python_library: str | None,
    build_python: bool,
    rerun_cmake: bool,
    cmake_only: bool,
    cmake: CMake,
) -> None:
    my_env = _create_build_env()
    build_test = not check_negative_env_flag("BUILD_TEST")
    cmake.generate(
        version, cmake_python_library, build_python, build_test, my_env, rerun_cmake
    )
    if cmake_only:
        return
    cmake.build(my_env)