mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
797 lines
30 KiB
Python
Executable File
797 lines
30 KiB
Python
Executable File
#!/usr/bin/env python3
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# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import platform
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import sys
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import sysconfig
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import warnings
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from argparse import ArgumentParser
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from contextlib import contextmanager
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from functools import partial
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from multiprocessing import cpu_count
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from pathlib import Path
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from shutil import copy, copytree, rmtree
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from subprocess import DEVNULL, CalledProcessError, check_output, run
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from textwrap import dedent
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from typing import List
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try:
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from packaging.requirements import Requirement
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except (ImportError, ModuleNotFoundError):
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from pip._vendor.packaging.requirements import Requirement
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build_run = partial(run, shell=True, check=True)
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@contextmanager
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def working_directory(path):
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"""Changes working directory and returns to previous on exit."""
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prev_cwd = Path.cwd()
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os.chdir(path)
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try:
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yield
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finally:
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os.chdir(prev_cwd)
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def get_project_dir():
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return Path(__file__).parent.resolve().parent
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def get_source_dir():
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return get_project_dir() / "cpp"
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def get_build_dir(build_dir, build_type):
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if build_dir is None:
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build_dir = get_source_dir() / ("build" if build_type == "Release" else
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f"build_{build_type}")
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else:
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build_dir = Path(build_dir).resolve()
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return build_dir
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def clear_folder(folder_path):
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for item in os.listdir(folder_path):
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item_path = os.path.join(folder_path, item)
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if os.path.isdir(item_path) and not os.path.islink(item_path):
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rmtree(item_path)
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else:
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os.remove(item_path)
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def sysconfig_scheme(override_vars=None):
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# Backported 'venv' scheme from Python 3.11+
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if os.name == 'nt':
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scheme = {
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'purelib': '{base}/Lib/site-packages',
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'scripts': '{base}/Scripts',
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}
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else:
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scheme = {
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'purelib': '{base}/lib/python{py_version_short}/site-packages',
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'scripts': '{base}/bin',
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}
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vars_ = sysconfig.get_config_vars()
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if override_vars:
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vars_.update(override_vars)
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return {key: value.format(**vars_) for key, value in scheme.items()}
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def create_venv(project_dir: Path):
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py_major = sys.version_info.major
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py_minor = sys.version_info.minor
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venv_prefix = project_dir / f".venv-{py_major}.{py_minor}"
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print(
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f"-- Using virtual environment at: {venv_prefix} (Python {py_major}.{py_minor})"
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)
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# Ensure compatible virtualenv version is installed (>=20.29.1, <22.0)
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print("-- Ensuring virtualenv version >=20.29.1,<22.0 is installed...")
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build_run(f'"{sys.executable}" -m pip install "virtualenv>=20.29.1,<22.0"')
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# Create venv if it doesn't exist
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if not venv_prefix.exists():
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print(f"-- Creating virtual environment in {venv_prefix}...")
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build_run(
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f'"{sys.executable}" -m virtualenv --system-site-packages "{venv_prefix}"'
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)
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else:
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print("-- Virtual environment already exists.")
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return venv_prefix
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def setup_venv(project_dir: Path, requirements_file: Path, no_venv: bool):
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"""Creates/updates a venv and installs requirements.
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Args:
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project_dir: The root directory of the project.
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requirements_file: Path to the requirements file.
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no_venv: Use current Python environment as is.
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Returns:
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Tuple[Path, Path]: Paths to the python and conan executables in the venv.
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"""
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if no_venv or sys.prefix != sys.base_prefix:
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reason = "Explicitly requested by user" if no_venv else "Already inside virtual environment"
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print(f"-- {reason}, using environment {sys.prefix} as is.")
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venv_prefix = Path(sys.prefix)
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else:
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venv_prefix = create_venv(project_dir)
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scheme = sysconfig_scheme({'base': venv_prefix})
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# Determine venv executable paths
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scripts_dir = Path(scheme["scripts"])
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venv_python = venv_prefix / sys.executable.removeprefix(sys.prefix)[1:]
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if os.environ.get("NVIDIA_PYTORCH_VERSION"):
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# Ensure PyPI PyTorch is not installed in the venv
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purelib_dir = Path(scheme["purelib"])
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pytorch_package_dir = purelib_dir / "torch"
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if venv_prefix != sys.base_prefix and pytorch_package_dir.exists():
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warnings.warn(
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f"Using the NVIDIA PyTorch container with PyPI distributed PyTorch may lead to compatibility issues.\n"
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f"If you encounter any problems, please delete the environment at `{venv_prefix}` so that "
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f"`build_wheel.py` can recreate the virtual environment correctly."
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)
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print("^^^^^^^^^^ IMPORTANT WARNING ^^^^^^^^^^", file=sys.stderr)
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input("Press Ctrl+C to stop, any key to continue...\n")
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# Ensure inherited PyTorch version is compatible
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try:
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info = check_output(
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[str(venv_python), "-m", "pip", "show", "torch"])
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except CalledProcessError:
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raise RuntimeError(
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"NVIDIA PyTorch container detected, but cannot find PyTorch installation. "
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"The environment is corrupted. Please recreate your container.")
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version_installed = next(
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line.removeprefix("Version: ")
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for line in info.decode().splitlines()
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if line.startswith("Version: "))
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version_required = None
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try:
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with open(requirements_file) as fp:
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for line in fp:
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if line.startswith("torch"):
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version_required = Requirement(line)
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break
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except FileNotFoundError:
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pass
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if version_required is not None:
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if version_installed not in version_required.specifier:
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raise RuntimeError(
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f"Incompatible NVIDIA PyTorch container detected. "
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f"The container provides PyTorch version {version_installed}, "
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f"but current revision requires {version_required}. "
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f"Please recreate your container using image specified in .devcontainer/docker-compose.yml. "
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f"NOTE: Please don't try install PyTorch using pip. "
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f"Using the NVIDIA PyTorch container with PyPI distributed PyTorch may lead to compatibility issues."
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)
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# Install/update requirements
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print(
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f"-- Installing requirements from {requirements_file} into {venv_prefix}..."
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)
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build_run(f'"{venv_python}" -m pip install -r "{requirements_file}"')
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venv_conan = setup_conan(scripts_dir, venv_python)
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return venv_python, venv_conan
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def setup_conan(scripts_dir, venv_python):
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build_run(f'"{venv_python}" -m pip install conan==2.14.0')
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# Determine the path to the conan executable within the venv
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venv_conan = scripts_dir / "conan"
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if not venv_conan.exists():
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# Attempt to find it using shutil.which as a fallback, in case it's already installed in the system
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try:
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result = build_run(
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f'''{venv_python} -c "import shutil; print(shutil.which('conan'))" ''',
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capture_output=True,
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text=True)
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conan_path_str = result.stdout.strip()
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if conan_path_str:
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venv_conan = Path(conan_path_str)
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print(
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f"-- Found conan executable via PATH search at: {venv_conan}"
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)
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else:
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raise RuntimeError(
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f"Failed to locate conan executable in virtual environment {scripts_dir} or system PATH."
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)
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except CalledProcessError as e:
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print(f"Fallback search command output: {e.stdout}",
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file=sys.stderr)
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print(f"Fallback search command error: {e.stderr}", file=sys.stderr)
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raise RuntimeError(
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f"Failed to locate conan executable in virtual environment {scripts_dir} or system PATH."
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)
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else:
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print(f"-- Found conan executable at: {venv_conan}")
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# Create default profile
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build_run(f'"{venv_conan}" profile detect -f')
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# Add the tensorrt-llm remote if it doesn't exist
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build_run(
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f'"{venv_conan}" remote add --force tensorrt-llm https://edge.urm.nvidia.com/artifactory/api/conan/sw-tensorrt-llm-conan',
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stdout=DEVNULL,
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stderr=DEVNULL)
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return venv_conan
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def generate_fmha_cu(project_dir, venv_python):
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fmha_v2_cu_dir = project_dir / "cpp/tensorrt_llm/kernels/contextFusedMultiHeadAttention/fmha_v2_cu"
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fmha_v2_cu_dir.mkdir(parents=True, exist_ok=True)
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fmha_v2_dir = project_dir / "cpp/kernels/fmha_v2"
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os.chdir(fmha_v2_dir)
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env = os.environ.copy()
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env.update({
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"TORCH_CUDA_ARCH_LIST": "9.0",
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"ENABLE_SM89_QMMA": "1",
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"ENABLE_HMMA_FP32": "1",
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"GENERATE_CUBIN": "1",
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"SCHEDULING_MODE": "1",
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"ENABLE_SM100": "1",
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"ENABLE_SM120": "1",
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"GENERATE_CU_TRTLLM": "true"
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})
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build_run("rm -rf generated")
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build_run("rm -rf temp")
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build_run("rm -rf obj")
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build_run("python3 setup.py", env=env)
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# Copy generated header file when cu path is active and cubins are deleted.
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cubin_dir = project_dir / "cpp/tensorrt_llm/kernels/contextFusedMultiHeadAttention/cubin"
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build_run(f"mv generated/fmha_cubin.h {cubin_dir}")
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for cu_file in (fmha_v2_dir / "generated").glob("*sm*.cu"):
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build_run(f"mv {cu_file} {fmha_v2_cu_dir}")
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os.chdir(project_dir)
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def main(*,
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build_type: str = "Release",
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generator: str = "",
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build_dir: Path = None,
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dist_dir: Path = None,
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cuda_architectures: str = None,
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job_count: int = None,
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extra_cmake_vars: List[str] = list(),
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extra_make_targets: str = "",
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trt_root: str = '/usr/local/tensorrt',
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nccl_root: str = None,
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nixl_root: str = None,
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internal_cutlass_kernels_root: str = None,
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clean: bool = False,
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clean_wheel: bool = False,
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configure_cmake: bool = False,
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use_ccache: bool = False,
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fast_build: bool = False,
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cpp_only: bool = False,
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install: bool = False,
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skip_building_wheel: bool = False,
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linking_install_binary: bool = False,
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python_bindings: bool = True,
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benchmarks: bool = False,
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micro_benchmarks: bool = False,
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nvtx: bool = False,
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skip_stubs: bool = False,
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generate_fmha: bool = False,
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no_venv: bool = False):
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if clean:
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clean_wheel = True
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project_dir = get_project_dir()
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os.chdir(project_dir)
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# Get all submodules and check their folder exists. If not,
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# invoke git submodule update
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with open(project_dir / ".gitmodules", "r") as submodules_f:
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submodules = [
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l.split("=")[1].strip() for l in submodules_f.readlines()
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if "path = " in l
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]
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if any(not (project_dir / submodule / ".git").exists()
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for submodule in submodules):
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build_run('git submodule update --init --recursive')
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on_windows = platform.system() == "Windows"
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requirements_filename = "requirements-dev-windows.txt" if on_windows else "requirements-dev.txt"
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# Setup venv and install requirements
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venv_python, venv_conan = setup_venv(project_dir,
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project_dir / requirements_filename,
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no_venv)
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# Ensure base TRT is installed (check inside the venv)
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try:
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check_output([str(venv_python), "-m", "pip", "show", "tensorrt"])
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except CalledProcessError:
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error_msg = "TensorRT was not installed properly."
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if on_windows:
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error_msg += (
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" Please download the TensorRT zip file manually,"
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" install it and relaunch build_wheel.py."
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" See https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html#installing-zip for more details."
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)
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else:
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error_msg += f" Please install tensorrt into the venv using \"`{venv_python}` -m pip install tensorrt\" and relaunch build_wheel.py"
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raise RuntimeError(error_msg)
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if cuda_architectures is not None:
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if "70-real" in cuda_architectures:
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raise RuntimeError("Volta architecture is deprecated support.")
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cmake_cuda_architectures = (
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f'"-DCMAKE_CUDA_ARCHITECTURES={cuda_architectures}"'
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if cuda_architectures is not None else "")
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cmake_def_args = []
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cmake_generator = ""
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if on_windows:
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# Windows does not support multi-device currently.
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extra_cmake_vars.extend(["ENABLE_MULTI_DEVICE=0"])
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# The Ninja CMake generator is used for our Windows build
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# (Easier than MSBuild to make compatible with our Docker image)
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if generator:
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cmake_generator = "-G" + generator
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if job_count is None:
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job_count = cpu_count()
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if len(extra_cmake_vars):
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# Backwards compatibility, we also support semicolon expansion for each value.
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# However, it is best to use flag multiple-times due to issues with spaces in CLI.
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expanded_args = []
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for var in extra_cmake_vars:
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expanded_args += var.split(";")
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extra_cmake_vars = ["\"-D{}\"".format(var) for var in expanded_args]
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# Don't include duplicate conditions
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cmake_def_args.extend(set(extra_cmake_vars))
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if trt_root is not None:
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cmake_def_args.append(f"-DTensorRT_ROOT={trt_root}")
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if nccl_root is not None:
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cmake_def_args.append(f"-DNCCL_ROOT={nccl_root}")
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if nixl_root is not None:
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cmake_def_args.append(f"-DNIXL_ROOT={nixl_root}")
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build_dir = get_build_dir(build_dir, build_type)
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first_build = not Path(build_dir, "CMakeFiles").exists()
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if clean and build_dir.exists():
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clear_folder(build_dir) # Keep the folder in case it is mounted.
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build_dir.mkdir(parents=True, exist_ok=True)
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if use_ccache:
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cmake_def_args.append(
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f"-DCMAKE_CXX_COMPILER_LAUNCHER=ccache -DCMAKE_CUDA_COMPILER_LAUNCHER=ccache"
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)
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if fast_build:
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cmake_def_args.append(f"-DFAST_BUILD=ON")
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targets = ["tensorrt_llm", "nvinfer_plugin_tensorrt_llm"]
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if cpp_only:
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build_pyt = "OFF"
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build_pybind = "OFF"
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else:
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targets.extend(["bindings", "th_common"])
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build_pyt = "ON"
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build_pybind = "ON"
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if benchmarks:
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targets.append("benchmarks")
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if micro_benchmarks:
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targets.append("micro_benchmarks")
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build_micro_benchmarks = "ON"
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else:
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build_micro_benchmarks = "OFF"
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disable_nvtx = "OFF" if nvtx else "ON"
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if not on_windows:
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targets.append("executorWorker")
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source_dir = get_source_dir()
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fmha_v2_cu_dir = project_dir / "cpp/tensorrt_llm/kernels/contextFusedMultiHeadAttention/fmha_v2_cu"
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if clean or generate_fmha:
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build_run(f"rm -rf {fmha_v2_cu_dir}")
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generate_fmha_cu(project_dir, venv_python)
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elif not fmha_v2_cu_dir.exists():
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generate_fmha_cu(project_dir, venv_python)
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with working_directory(build_dir):
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if clean or first_build or configure_cmake:
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build_run(
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f"\"{venv_conan}\" install --build=missing --remote=tensorrt-llm --output-folder={build_dir}/conan -s 'build_type={build_type}' {source_dir}"
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)
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cmake_def_args.append(
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f"-DCMAKE_TOOLCHAIN_FILE={build_dir}/conan/conan_toolchain.cmake"
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)
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if internal_cutlass_kernels_root:
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cmake_def_args.append(
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f"-DINTERNAL_CUTLASS_KERNELS_PATH={internal_cutlass_kernels_root}"
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)
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cmake_def_args = " ".join(cmake_def_args)
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cmake_configure_command = (
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f'cmake -DCMAKE_BUILD_TYPE="{build_type}" -DBUILD_PYT="{build_pyt}" -DBUILD_PYBIND="{build_pybind}"'
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f' -DNVTX_DISABLE="{disable_nvtx}" -DBUILD_MICRO_BENCHMARKS={build_micro_benchmarks}'
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f' -DBUILD_WHEEL_TARGETS="{";".join(targets)}"'
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f' -DPython_EXECUTABLE={venv_python} -DPython3_EXECUTABLE={venv_python}'
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f' {cmake_cuda_architectures} {cmake_def_args} {cmake_generator} -S "{source_dir}"'
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)
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print("CMake Configure command: ")
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print(cmake_configure_command)
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build_run(cmake_configure_command)
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cmake_build_command = (
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f'cmake --build . --config {build_type} --parallel {job_count} '
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f'--target build_wheel_targets {" ".join(extra_make_targets)}')
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print("CMake Build command: ")
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print(cmake_build_command)
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build_run(cmake_build_command)
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|
|
if cpp_only:
|
|
assert not install, "Installing is not supported for cpp_only builds"
|
|
return
|
|
|
|
pkg_dir = project_dir / "tensorrt_llm"
|
|
assert pkg_dir.is_dir(), f"{pkg_dir} is not a directory"
|
|
lib_dir = pkg_dir / "libs"
|
|
include_dir = pkg_dir / "include"
|
|
if lib_dir.exists():
|
|
clear_folder(lib_dir)
|
|
if include_dir.exists():
|
|
clear_folder(include_dir)
|
|
|
|
cache_dir = os.getenv("TRTLLM_DG_CACHE_DIR")
|
|
if cache_dir is not None:
|
|
cache_dir = Path(cache_dir)
|
|
elif on_windows:
|
|
if os.getenv("APPDATA") is not None:
|
|
cache_dir = Path(os.getenv("APPDATA")) / "tensorrt_llm"
|
|
else:
|
|
cache_dir = Path(os.getenv("TEMP")) / "tensorrt_llm"
|
|
else:
|
|
if os.getenv("HOME") is not None:
|
|
cache_dir = Path(os.getenv("HOME")) / ".tensorrt_llm"
|
|
else:
|
|
cache_dir = Path(os.getenv("TEMP"), "/tmp") / "tensorrt_llm"
|
|
if cache_dir.exists():
|
|
clear_folder(cache_dir)
|
|
|
|
install_file = copy
|
|
install_tree = copytree
|
|
if skip_building_wheel and linking_install_binary:
|
|
|
|
def symlink_remove_dst(src, dst):
|
|
src = os.path.abspath(src)
|
|
dst = os.path.abspath(dst)
|
|
if os.path.isdir(dst):
|
|
dst = os.path.join(dst, os.path.basename(src))
|
|
if os.path.exists(dst):
|
|
os.remove(dst)
|
|
os.symlink(src, dst)
|
|
|
|
install_file = symlink_remove_dst
|
|
|
|
def symlink_remove_dst_tree(src, dst, dirs_exist_ok=True):
|
|
src = os.path.abspath(src)
|
|
dst = os.path.abspath(dst)
|
|
if dirs_exist_ok and os.path.exists(dst):
|
|
os.remove(dst)
|
|
os.symlink(src, dst)
|
|
|
|
install_tree = symlink_remove_dst_tree
|
|
|
|
lib_dir.mkdir(parents=True, exist_ok=True)
|
|
include_dir.mkdir(parents=True, exist_ok=True)
|
|
install_tree(get_source_dir() / "include" / "tensorrt_llm" / "deep_gemm",
|
|
include_dir / "deep_gemm",
|
|
dirs_exist_ok=True)
|
|
required_cuda_headers = [
|
|
"cuda_fp16.h", "cuda_fp16.hpp", "cuda_bf16.h", "cuda_bf16.hpp",
|
|
"cuda_fp8.h", "cuda_fp8.hpp"
|
|
]
|
|
if os.getenv("CUDA_HOME") is not None:
|
|
cuda_include_dir = Path(os.getenv("CUDA_HOME")) / "include"
|
|
elif os.getenv("CUDA_PATH") is not None:
|
|
cuda_include_dir = Path(os.getenv("CUDA_PATH")) / "include"
|
|
elif not on_windows:
|
|
cuda_include_dir = Path("/usr/local/cuda/include")
|
|
else:
|
|
cuda_include_dir = None
|
|
|
|
if cuda_include_dir is None or not cuda_include_dir.exists():
|
|
print(
|
|
"CUDA_HOME or CUDA_PATH should be set to enable DeepGEMM JIT compilation"
|
|
)
|
|
else:
|
|
cuda_include_target_dir = include_dir / "cuda" / "include"
|
|
cuda_include_target_dir.mkdir(parents=True, exist_ok=True)
|
|
for header in required_cuda_headers:
|
|
install_file(cuda_include_dir / header, include_dir / header)
|
|
|
|
if on_windows:
|
|
install_file(build_dir / "tensorrt_llm/tensorrt_llm.dll",
|
|
lib_dir / "tensorrt_llm.dll")
|
|
install_file(build_dir / f"tensorrt_llm/thop/th_common.dll",
|
|
lib_dir / "th_common.dll")
|
|
install_file(
|
|
build_dir / f"tensorrt_llm/plugins/nvinfer_plugin_tensorrt_llm.dll",
|
|
lib_dir / "nvinfer_plugin_tensorrt_llm.dll")
|
|
else:
|
|
install_file(build_dir / "tensorrt_llm/libtensorrt_llm.so",
|
|
lib_dir / "libtensorrt_llm.so")
|
|
install_file(build_dir / "tensorrt_llm/thop/libth_common.so",
|
|
lib_dir / "libth_common.so")
|
|
install_file(
|
|
build_dir /
|
|
"tensorrt_llm/plugins/libnvinfer_plugin_tensorrt_llm.so",
|
|
lib_dir / "libnvinfer_plugin_tensorrt_llm.so")
|
|
if os.path.exists(
|
|
build_dir /
|
|
"tensorrt_llm/executor/cache_transmission/ucx_utils/libtensorrt_llm_ucx_wrapper.so"
|
|
):
|
|
install_file(
|
|
build_dir /
|
|
"tensorrt_llm/executor/cache_transmission/ucx_utils/libtensorrt_llm_ucx_wrapper.so",
|
|
lib_dir / "libtensorrt_llm_ucx_wrapper.so")
|
|
if os.path.exists(
|
|
build_dir /
|
|
"tensorrt_llm/executor/cache_transmission/nixl_utils/libtensorrt_llm_nixl_wrapper.so"
|
|
):
|
|
install_file(
|
|
build_dir /
|
|
"tensorrt_llm/executor/cache_transmission/nixl_utils/libtensorrt_llm_nixl_wrapper.so",
|
|
lib_dir / "libtensorrt_llm_nixl_wrapper.so")
|
|
install_file(
|
|
build_dir /
|
|
"tensorrt_llm/kernels/decoderMaskedMultiheadAttention/libdecoder_attention_0.so",
|
|
lib_dir / "libdecoder_attention_0.so")
|
|
install_file(
|
|
build_dir /
|
|
"tensorrt_llm/kernels/decoderMaskedMultiheadAttention/libdecoder_attention_1.so",
|
|
lib_dir / "libdecoder_attention_1.so")
|
|
|
|
bin_dir = pkg_dir / "bin"
|
|
if bin_dir.exists():
|
|
clear_folder(bin_dir)
|
|
bin_dir.mkdir(parents=True, exist_ok=True)
|
|
|
|
if not on_windows:
|
|
install_file(build_dir / "tensorrt_llm/executor_worker/executorWorker",
|
|
bin_dir / "executorWorker")
|
|
|
|
if not cpp_only:
|
|
|
|
def get_pybind_lib():
|
|
pybind_build_dir = (build_dir / "tensorrt_llm" / "pybind")
|
|
if on_windows:
|
|
pybind_lib = list(pybind_build_dir.glob("bindings.*.pyd"))
|
|
else:
|
|
pybind_lib = list(pybind_build_dir.glob("bindings.*.so"))
|
|
|
|
assert len(
|
|
pybind_lib
|
|
) == 1, f"Exactly one pybind library should be present: {pybind_lib}"
|
|
return pybind_lib[0]
|
|
|
|
install_file(get_pybind_lib(), pkg_dir)
|
|
if not skip_stubs:
|
|
with working_directory(project_dir):
|
|
build_run(f"\"{venv_python}\" -m pip install pybind11-stubgen")
|
|
with working_directory(pkg_dir):
|
|
if on_windows:
|
|
stubgen = "stubgen.py"
|
|
stubgen_contents = """
|
|
# Loading torch, trt before bindings is required to avoid import errors on windows.
|
|
# isort: off
|
|
import torch
|
|
import tensorrt as trt
|
|
# isort: on
|
|
import os
|
|
import platform
|
|
|
|
from pybind11_stubgen import main
|
|
|
|
if __name__ == "__main__":
|
|
# Load dlls from `libs` directory before launching bindings.
|
|
if platform.system() == "Windows":
|
|
os.add_dll_directory(r\"{lib_dir}\")
|
|
main()
|
|
""".format(lib_dir=lib_dir)
|
|
(pkg_dir / stubgen).write_text(dedent(stubgen_contents))
|
|
build_run(f"\"{venv_python}\" {stubgen} -o . bindings")
|
|
(pkg_dir / stubgen).unlink()
|
|
else:
|
|
env_ld = os.environ.copy()
|
|
|
|
new_library_path = "/usr/local/cuda/compat:/usr/local/cuda/compat/lib:/usr/local/cuda/compat/lib.real"
|
|
if 'LD_LIBRARY_PATH' in env_ld:
|
|
new_library_path += f":{env_ld['LD_LIBRARY_PATH']}"
|
|
env_ld["LD_LIBRARY_PATH"] = new_library_path
|
|
try:
|
|
build_run(
|
|
f"\"{venv_python}\" -m pybind11_stubgen -o . bindings --exit-code",
|
|
env=env_ld)
|
|
except CalledProcessError as ex:
|
|
print(f"Failed to build pybind11 stubgen: {ex}",
|
|
file=sys.stderr)
|
|
exit(1)
|
|
|
|
if not skip_building_wheel:
|
|
if dist_dir is None:
|
|
dist_dir = project_dir / "build"
|
|
else:
|
|
dist_dir = Path(dist_dir)
|
|
|
|
if not dist_dir.exists():
|
|
dist_dir.mkdir(parents=True)
|
|
|
|
if clean_wheel:
|
|
# For incremental build, the python build module adds
|
|
# the new files but does not remove the deleted files.
|
|
#
|
|
# This breaks the Windows CI/CD pipeline when building
|
|
# and validating python changes in the whl.
|
|
clear_folder(dist_dir)
|
|
|
|
build_run(
|
|
f'\"{venv_python}\" -m build {project_dir} --skip-dependency-check --no-isolation --wheel --outdir "{dist_dir}"'
|
|
)
|
|
|
|
if install:
|
|
build_run(f"\"{sys.executable}\" -m pip install -e .[devel]")
|
|
|
|
|
|
def add_arguments(parser: ArgumentParser):
|
|
parser.add_argument("--build_type",
|
|
"-b",
|
|
default="Release",
|
|
choices=["Release", "RelWithDebInfo", "Debug"])
|
|
parser.add_argument("--generator", "-G", default="")
|
|
parser.add_argument("--cuda_architectures", "-a")
|
|
parser.add_argument("--install", "-i", action="store_true")
|
|
parser.add_argument("--clean", "-c", action="store_true")
|
|
parser.add_argument("--clean_wheel",
|
|
action="store_true",
|
|
help="Clear dist_dir folder creating wheel")
|
|
parser.add_argument("--configure_cmake",
|
|
action="store_true",
|
|
help="Always configure cmake before building")
|
|
parser.add_argument("--use_ccache",
|
|
"-ccache",
|
|
default=False,
|
|
action="store_true",
|
|
help="Use ccache compiler driver")
|
|
parser.add_argument(
|
|
"--fast_build",
|
|
"-f",
|
|
default=False,
|
|
action="store_true",
|
|
help=
|
|
"Skip compiling some kernels to accelerate compilation -- for development only"
|
|
)
|
|
parser.add_argument("--job_count",
|
|
"-j",
|
|
const=cpu_count(),
|
|
nargs="?",
|
|
help="Parallel job count")
|
|
parser.add_argument(
|
|
"--cpp_only",
|
|
"-l",
|
|
action="store_true",
|
|
help="Only build the C++ library without Python dependencies")
|
|
parser.add_argument(
|
|
"--extra-cmake-vars",
|
|
"-D",
|
|
action="append",
|
|
help=
|
|
"Extra cmake variable definition which can be specified multiple times, example: -D \"key1=value1\" -D \"key2=value2\"",
|
|
default=[])
|
|
parser.add_argument(
|
|
"--extra-make-targets",
|
|
help="A list of additional make targets, example: \"target_1 target_2\"",
|
|
nargs="+",
|
|
default=[])
|
|
parser.add_argument("--trt_root",
|
|
default="/usr/local/tensorrt",
|
|
help="Directory to find TensorRT headers/libs")
|
|
parser.add_argument("--nccl_root",
|
|
help="Directory to find NCCL headers/libs")
|
|
parser.add_argument("--nixl_root",
|
|
help="Directory to find NIXL headers/libs")
|
|
parser.add_argument(
|
|
"--internal-cutlass-kernels-root",
|
|
default="",
|
|
help=
|
|
"Directory to the internal_cutlass_kernels sources. If specified, the internal_cutlass_kernels and NVRTC wrapper libraries will be built from source."
|
|
)
|
|
parser.add_argument("--build_dir",
|
|
type=Path,
|
|
help="Directory where cpp sources are built")
|
|
parser.add_argument("--dist_dir",
|
|
type=Path,
|
|
help="Directory where python wheels are built")
|
|
parser.add_argument(
|
|
"--skip_building_wheel",
|
|
"-s",
|
|
action="store_true",
|
|
help=
|
|
"Do not build the *.whl files (they are only needed for distribution).")
|
|
parser.add_argument(
|
|
"--linking_install_binary",
|
|
action="store_true",
|
|
help="Install the built binary by symbolic linking instead of copying.")
|
|
parser.add_argument(
|
|
"--python_bindings",
|
|
"-p",
|
|
action="store_true",
|
|
help="(deprecated) Build the python bindings for the C++ runtime.")
|
|
parser.add_argument("--benchmarks",
|
|
action="store_true",
|
|
help="Build the benchmarks for the C++ runtime.")
|
|
parser.add_argument("--micro_benchmarks",
|
|
action="store_true",
|
|
help="Build the micro benchmarks for C++ components.")
|
|
parser.add_argument("--nvtx",
|
|
action="store_true",
|
|
help="Enable NVTX features.")
|
|
parser.add_argument("--skip-stubs",
|
|
action="store_true",
|
|
help="Skip building python stubs")
|
|
parser.add_argument("--generate_fmha",
|
|
action="store_true",
|
|
help="Generate the FMHA cu files.")
|
|
parser.add_argument(
|
|
"--no-venv",
|
|
action="store_true",
|
|
help=
|
|
"Use the current Python interpreter without creating a virtual environment."
|
|
)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
parser = ArgumentParser()
|
|
add_arguments(parser)
|
|
args = parser.parse_args()
|
|
main(**vars(args))
|