mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
539 lines
20 KiB
Python
Executable File
539 lines
20 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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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 CalledProcessError, check_output, run
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from textwrap import dedent
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from typing import List
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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 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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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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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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build_run = partial(run, shell=True, check=True)
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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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build_run(f"\"{sys.executable}\" -m pip install -r {requirements_filename}")
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# Ensure TRT is installed on windows to prevent surprises.
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reqs = check_output([sys.executable, "-m", "pip", "freeze"])
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installed_packages = [r.decode().split("==")[0] for r in reqs.split()]
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if "tensorrt" not in installed_packages:
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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 += " Please run `pip install tensorrt` manually 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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build_dir = get_build_dir(build_dir, build_type)
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first_build = not build_dir.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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with working_directory(build_dir):
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cmake_def_args = " ".join(cmake_def_args)
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if clean or first_build or configure_cmake:
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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' {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:
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assert not install, "Installing is not supported for cpp_only builds"
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return
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pkg_dir = project_dir / "tensorrt_llm"
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assert pkg_dir.is_dir(), f"{pkg_dir} is not a directory"
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lib_dir = pkg_dir / "libs"
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include_dir = pkg_dir / "include"
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if lib_dir.exists():
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clear_folder(lib_dir)
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if include_dir.exists():
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clear_folder(include_dir)
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cache_dir = os.getenv("TRTLLM_DG_CACHE_DIR")
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if cache_dir is not None:
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cache_dir = Path(cache_dir)
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elif on_windows:
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if os.getenv("APPDATA") is not None:
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cache_dir = Path(os.getenv("APPDATA")) / "tensorrt_llm"
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else:
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cache_dir = Path(os.getenv("TEMP")) / "tensorrt_llm"
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else:
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if os.getenv("HOME") is not None:
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cache_dir = Path(os.getenv("HOME")) / ".tensorrt_llm"
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else:
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cache_dir = Path(os.getenv("TEMP"), "/tmp") / "tensorrt_llm"
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if cache_dir.exists():
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clear_folder(cache_dir)
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install_file = copy
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install_tree = copytree
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if skip_building_wheel and linking_install_binary:
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def symlink_remove_dst(src, dst):
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src = os.path.abspath(src)
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dst = os.path.abspath(dst)
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if os.path.isdir(dst):
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dst = os.path.join(dst, os.path.basename(src))
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if os.path.exists(dst):
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os.remove(dst)
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os.symlink(src, dst)
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install_file = symlink_remove_dst
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def symlink_remove_dst_tree(src, dst, dirs_exist_ok=True):
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src = os.path.abspath(src)
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dst = os.path.abspath(dst)
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if dirs_exist_ok and os.path.exists(dst):
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os.remove(dst)
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os.symlink(src, dst)
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install_tree = symlink_remove_dst_tree
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lib_dir.mkdir(parents=True, exist_ok=True)
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include_dir.mkdir(parents=True, exist_ok=True)
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install_tree(get_source_dir() / "include" / "tensorrt_llm" / "deep_gemm",
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include_dir / "deep_gemm",
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dirs_exist_ok=True)
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required_cuda_headers = [
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"cuda_fp16.h", "cuda_fp16.hpp", "cuda_bf16.h", "cuda_bf16.hpp",
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"cuda_fp8.h", "cuda_fp8.hpp"
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]
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if os.getenv("CUDA_HOME") is not None:
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cuda_include_dir = Path(os.getenv("CUDA_HOME")) / "include"
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elif os.getenv("CUDA_PATH") is not None:
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cuda_include_dir = Path(os.getenv("CUDA_PATH")) / "include"
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elif not on_windows:
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cuda_include_dir = Path("/usr/local/cuda/include")
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else:
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cuda_include_dir = None
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if cuda_include_dir is None or not cuda_include_dir.exists():
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print(
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"CUDA_HOME or CUDA_PATH should be set to enable DeepGEMM JIT compilation"
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)
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else:
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cuda_include_target_dir = include_dir / "cuda" / "include"
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cuda_include_target_dir.mkdir(parents=True, exist_ok=True)
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for header in required_cuda_headers:
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install_file(cuda_include_dir / header, include_dir / header)
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if on_windows:
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install_file(build_dir / "tensorrt_llm/tensorrt_llm.dll",
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lib_dir / "tensorrt_llm.dll")
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install_file(build_dir / f"tensorrt_llm/thop/th_common.dll",
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lib_dir / "th_common.dll")
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install_file(
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build_dir / f"tensorrt_llm/plugins/nvinfer_plugin_tensorrt_llm.dll",
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lib_dir / "nvinfer_plugin_tensorrt_llm.dll")
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install_file(
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build_dir /
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"tensorrt_llm/kernels/decoderMaskedMultiheadAttention/decoderXQAImplJIT/nvrtcWrapper/tensorrt_llm_nvrtc_wrapper.dll",
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lib_dir / "tensorrt_llm_nvrtc_wrapper.dll")
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else:
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install_file(build_dir / "tensorrt_llm/libtensorrt_llm.so",
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lib_dir / "libtensorrt_llm.so")
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install_file(build_dir / "tensorrt_llm/thop/libth_common.so",
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lib_dir / "libth_common.so")
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install_file(
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build_dir /
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"tensorrt_llm/plugins/libnvinfer_plugin_tensorrt_llm.so",
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lib_dir / "libnvinfer_plugin_tensorrt_llm.so")
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install_file(
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build_dir /
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"tensorrt_llm/kernels/decoderMaskedMultiheadAttention/decoderXQAImplJIT/nvrtcWrapper/libtensorrt_llm_nvrtc_wrapper.so",
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lib_dir / "libtensorrt_llm_nvrtc_wrapper.so")
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if os.path.exists(
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build_dir /
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"tensorrt_llm/executor/cache_transmission/ucx_utils/libtensorrt_llm_ucx_wrapper.so"
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):
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install_file(
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build_dir /
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"tensorrt_llm/executor/cache_transmission/ucx_utils/libtensorrt_llm_ucx_wrapper.so",
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lib_dir / "libtensorrt_llm_ucx_wrapper.so")
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install_file(
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build_dir /
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"tensorrt_llm/kernels/decoderMaskedMultiheadAttention/libdecoder_attention_0.so",
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lib_dir / "libdecoder_attention_0.so")
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install_file(
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build_dir /
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"tensorrt_llm/kernels/decoderMaskedMultiheadAttention/libdecoder_attention_1.so",
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lib_dir / "libdecoder_attention_1.so")
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bin_dir = pkg_dir / "bin"
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if bin_dir.exists():
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clear_folder(bin_dir)
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bin_dir.mkdir(parents=True, exist_ok=True)
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if not on_windows:
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install_file(build_dir / "tensorrt_llm/executor_worker/executorWorker",
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bin_dir / "executorWorker")
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if not cpp_only:
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def get_pybind_lib():
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pybind_build_dir = (build_dir / "tensorrt_llm" / "pybind")
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if on_windows:
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pybind_lib = list(pybind_build_dir.glob("bindings.*.pyd"))
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else:
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pybind_lib = list(pybind_build_dir.glob("bindings.*.so"))
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assert len(
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pybind_lib
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) == 1, f"Exactly one pybind library should be present: {pybind_lib}"
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return pybind_lib[0]
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install_file(get_pybind_lib(), pkg_dir)
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if not skip_stubs:
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with working_directory(project_dir):
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build_run(
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f"\"{sys.executable}\" -m pip install pybind11-stubgen")
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with working_directory(pkg_dir):
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if on_windows:
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stubgen = "stubgen.py"
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stubgen_contents = """
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# Loading torch, trt before bindings is required to avoid import errors on windows.
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# isort: off
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import torch
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import tensorrt as trt
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# isort: on
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import os
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import platform
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from pybind11_stubgen import main
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if __name__ == "__main__":
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# Load dlls from `libs` directory before launching bindings.
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if platform.system() == "Windows":
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os.add_dll_directory(r\"{lib_dir}\")
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main()
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""".format(lib_dir=lib_dir)
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(pkg_dir / stubgen).write_text(dedent(stubgen_contents))
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build_run(f"\"{sys.executable}\" {stubgen} -o . bindings")
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(pkg_dir / stubgen).unlink()
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else:
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env_ld = os.environ.copy()
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new_library_path = "/usr/local/cuda/compat/lib.real"
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if 'LD_LIBRARY_PATH' in env_ld:
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new_library_path += f":{env_ld['LD_LIBRARY_PATH']}"
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env_ld["LD_LIBRARY_PATH"] = new_library_path
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try:
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build_run(
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f"\"{sys.executable}\" -m pybind11_stubgen -o . bindings --exit-code",
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env=env_ld)
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except CalledProcessError as ex:
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print(f"Failed to build pybind11 stubgen: {ex}",
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file=sys.stderr)
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exit(1)
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if not skip_building_wheel:
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if dist_dir is None:
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dist_dir = project_dir / "build"
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else:
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dist_dir = Path(dist_dir)
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if not dist_dir.exists():
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dist_dir.mkdir(parents=True)
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if clean_wheel:
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# For incremental build, the python build module adds
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# the new files but does not remove the deleted files.
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#
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# This breaks the Windows CI/CD pipeline when building
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# and validating python changes in the whl.
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clear_folder(dist_dir)
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build_run(
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f'\"{sys.executable}\" -m build {project_dir} --skip-dependency-check --no-isolation --wheel --outdir "{dist_dir}"'
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)
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if install:
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build_run(f"\"{sys.executable}\" -m pip install -e .[devel]")
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def add_arguments(parser: ArgumentParser):
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parser.add_argument("--build_type",
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"-b",
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default="Release",
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choices=["Release", "RelWithDebInfo", "Debug"])
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parser.add_argument("--generator", "-G", default="")
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parser.add_argument("--cuda_architectures", "-a")
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parser.add_argument("--install", "-i", action="store_true")
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parser.add_argument("--clean", "-c", action="store_true")
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parser.add_argument("--clean_wheel",
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action="store_true",
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help="Clear dist_dir folder creating wheel")
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parser.add_argument("--configure_cmake",
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action="store_true",
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help="Always configure cmake before building")
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parser.add_argument("--use_ccache",
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"-ccache",
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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("--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")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
parser = ArgumentParser()
|
|
add_arguments(parser)
|
|
args = parser.parse_args()
|
|
main(**vars(args))
|