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build.py
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executable file
·2081 lines (1828 loc) · 77.9 KB
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#!/usr/bin/env python3
# Copyright 2020-2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import argparse
import logging
import os.path
import multiprocessing
import pathlib
import platform
import shutil
import subprocess
import sys
import traceback
from distutils.dir_util import copy_tree
from inspect import getsourcefile
#
# Build Triton Inference Server.
#
# By default build.py builds the Triton container. The TRITON_VERSION
# file indicates the Triton version and TRITON_VERSION_MAP is used to
# determine the corresponding container version and upstream container
# version (upstream containers are dependencies required by
# Triton). These versions may be overridden. See docs/build.md for
# more information.
# Map from Triton version to corresponding container and component versions.
#
# triton version ->
# (triton container version,
# upstream container version,
# ORT version,
# ORT OpenVINO version (use None to disable OpenVINO in ORT),
# Standalone OpenVINO version,
# DCGM version
# )
#
# Currently the OpenVINO versions used in ORT and standalone must
# match because of the way dlopen works with loading the backends. If
# different versions are used then one backend or the other will
# incorrectly load the other version of the openvino libraries.
#
# The standalone openVINO describes multiple versions where each version
# is a pair of openVINO version and openVINO package version. When openVINO
# package version is specified, then backend will be built with pre-built
# openVINO release from Intel. If the package version is specified as None,
# then openVINO for the backend is built from source with openMP support.
# By default, only the first version is built. To build the all the versions
# in list use --build-multiple-openvino. Triton will use the first version
# for inference by default. In order to use different version, Triton should
# be invoked with appropriate backend configuration:
# (--backend-config=openvino,version=<version_str>)
# The version string can be obtained as follows:
# <major_version>_<minor_version>[_pre]
# Append '_pre' only if the openVINO backend was built with prebuilt openVINO
# library. In other words, when the second element of the pair is not None.
# To use ('2021.4', None) version_str should be `2021_4'.
# To use ('2021.4', '2021.4.582') version_str should be `2021_4_pre'.
# User can also build openvino backend from specific commit sha of openVINO
# repository. The pair should be (`SPECIFIC`, <commit_sha_of_ov_repo>).
# Note: Not all sha ids would successfuly compile and work.
#
TRITON_VERSION_MAP = {
'2.21.0': (
'22.04', # triton container
'22.04', # upstream container
'1.10.0', # ORT
'2021.4.582', # ORT OpenVINO
(('2021.4', None), ('2021.4', '2021.4.582'),
('SPECIFIC', 'f2f281e6')), # Standalone OpenVINO
'2.2.9') # DCGM version
}
EXAMPLE_BACKENDS = ['identity', 'square', 'repeat']
CORE_BACKENDS = ['ensemble']
NONCORE_BACKENDS = [
'tensorflow1', 'tensorflow2', 'onnxruntime', 'python', 'dali', 'pytorch',
'openvino', 'fil', 'fastertransformer', 'tensorrt', 'armnn_tflite'
]
EXAMPLE_REPOAGENTS = ['checksum']
FLAGS = None
EXTRA_CORE_CMAKE_FLAGS = {}
OVERRIDE_CORE_CMAKE_FLAGS = {}
EXTRA_BACKEND_CMAKE_FLAGS = {}
OVERRIDE_BACKEND_CMAKE_FLAGS = {}
SCRIPT_DIR = os.path.dirname(os.path.abspath(getsourcefile(lambda: 0)))
def log(msg, force=False):
if force or not FLAGS.quiet:
try:
print(msg, file=sys.stderr)
except Exception:
print('<failed to log>', file=sys.stderr)
def log_verbose(msg):
if FLAGS.verbose:
log(msg, force=True)
def fail(msg):
fail_if(True, msg)
def target_platform():
if FLAGS.target_platform is not None:
return FLAGS.target_platform
return platform.system().lower()
def target_machine():
if FLAGS.target_machine is not None:
return FLAGS.target_machine
return platform.machine().lower()
def fail_if(p, msg):
if p:
print('error: {}'.format(msg), file=sys.stderr)
sys.exit(1)
def mkdir(path):
log_verbose('mkdir: {}'.format(path))
pathlib.Path(path).mkdir(parents=True, exist_ok=True)
def rmdir(path):
log_verbose('rmdir: {}'.format(path))
shutil.rmtree(path, ignore_errors=True)
def cpdir(src, dest):
log_verbose('cpdir: {} -> {}'.format(src, dest))
copy_tree(src, dest, preserve_symlinks=1)
def untar(targetdir, tarfile):
log_verbose('untar {} into {}'.format(tarfile, targetdir))
p = subprocess.Popen(['tar', '--strip-components=1', '-xf', tarfile],
cwd=targetdir)
p.wait()
fail_if(p.returncode != 0,
'untar {} into {} failed'.format(tarfile, targetdir))
def gitclone(cwd, repo, tag, subdir, org):
# If 'tag' starts with "pull/" then it must be of form
# "pull/<pr>/head". We just clone at "main" and then fetch the
# reference onto a new branch we name "tritonbuildref".
clone_dir = cwd + '/' + subdir
if tag.startswith("pull/"):
log_verbose('git clone of repo "{}" at ref "{}"'.format(repo, tag))
if os.path.exists(clone_dir) and not FLAGS.no_force_clone:
rmdir(clone_dir)
if not os.path.exists(clone_dir):
p = subprocess.Popen([
'git', 'clone', '--recursive', '--depth=1', '{}/{}.git'.format(
org, repo), subdir
],
cwd=cwd)
p.wait()
fail_if(
p.returncode != 0,
'git clone of repo "{}" at branch "main" failed'.format(repo))
log_verbose('git fetch of ref "{}"'.format(tag))
p = subprocess.Popen(
['git', 'fetch', 'origin', '{}:tritonbuildref'.format(tag)],
cwd=os.path.join(cwd, subdir))
p.wait()
fail_if(p.returncode != 0,
'git fetch of ref "{}" failed'.format(tag))
log_verbose('git checkout of tritonbuildref')
p = subprocess.Popen(['git', 'checkout', 'tritonbuildref'],
cwd=os.path.join(cwd, subdir))
p.wait()
fail_if(p.returncode != 0,
'git checkout of branch "tritonbuildref" failed')
else:
log_verbose('git clone of repo "{}" at tag "{}"'.format(repo, tag))
if os.path.exists(clone_dir) and not FLAGS.no_force_clone:
rmdir(clone_dir)
if not os.path.exists(clone_dir):
p = subprocess.Popen([
'git', 'clone', '--recursive', '--single-branch', '--depth=1',
'-b', tag, '{}/{}.git'.format(org, repo), subdir
],
cwd=cwd)
p.wait()
fail_if(
p.returncode != 0,
'git clone of repo "{}" at tag "{}" failed'.format(repo, tag))
def prebuild_command():
p = subprocess.Popen(FLAGS.container_prebuild_command.split())
p.wait()
fail_if(p.returncode != 0, 'container prebuild cmd failed')
def cmake(cwd, args):
log_verbose('cmake {}'.format(args))
p = subprocess.Popen([
'cmake',
] + args, cwd=cwd)
p.wait()
fail_if(p.returncode != 0, 'cmake failed')
def makeinstall(cwd, target='install'):
log_verbose('make {}'.format(target))
if target_platform() == 'windows':
verbose_flag = '' if FLAGS.verbose else '-clp:ErrorsOnly'
buildtype_flag = '-p:Configuration={}'.format(FLAGS.build_type)
p = subprocess.Popen([
'msbuild.exe', '-m:{}'.format(str(FLAGS.build_parallel)),
verbose_flag, buildtype_flag, '{}.vcxproj'.format(target)
],
cwd=cwd)
else:
verbose_flag = 'VERBOSE=1' if FLAGS.verbose else 'VERBOSE=0'
p = subprocess.Popen(
['make', '-j',
str(FLAGS.build_parallel), verbose_flag, target],
cwd=cwd)
p.wait()
fail_if(p.returncode != 0, 'make {} failed'.format(target))
def cmake_core_arg(name, type, value):
# Return cmake -D setting to set name=value for core build. Use
# command-line specified value if one is given.
if name in OVERRIDE_CORE_CMAKE_FLAGS:
value = OVERRIDE_CORE_CMAKE_FLAGS[name]
if type is None:
type = ''
else:
type = ':{}'.format(type)
return '-D{}{}={}'.format(name, type, value)
def cmake_core_enable(name, flag):
# Return cmake -D setting to set name=flag?ON:OFF for core
# build. Use command-line specified value for 'flag' if one is
# given.
if name in OVERRIDE_CORE_CMAKE_FLAGS:
value = OVERRIDE_CORE_CMAKE_FLAGS[name]
else:
value = 'ON' if flag else 'OFF'
return '-D{}:BOOL={}'.format(name, value)
def cmake_core_extra_args():
args = []
for k, v in EXTRA_CORE_CMAKE_FLAGS.items():
args.append('-D{}={}'.format(k, v))
return args
def cmake_backend_arg(backend, name, type, value):
# Return cmake -D setting to set name=value for backend build. Use
# command-line specified value if one is given.
if backend in OVERRIDE_BACKEND_CMAKE_FLAGS:
if name in OVERRIDE_BACKEND_CMAKE_FLAGS[backend]:
value = OVERRIDE_BACKEND_CMAKE_FLAGS[backend][name]
if type is None:
type = ''
else:
type = ':{}'.format(type)
return '-D{}{}={}'.format(name, type, value)
def cmake_backend_enable(backend, name, flag):
# Return cmake -D setting to set name=flag?ON:OFF for backend
# build. Use command-line specified value for 'flag' if one is
# given.
value = None
if backend in OVERRIDE_BACKEND_CMAKE_FLAGS:
if name in OVERRIDE_BACKEND_CMAKE_FLAGS[backend]:
value = OVERRIDE_BACKEND_CMAKE_FLAGS[backend][name]
if value is None:
value = 'ON' if flag else 'OFF'
return '-D{}:BOOL={}'.format(name, value)
def cmake_backend_extra_args(backend):
args = []
if backend in EXTRA_BACKEND_CMAKE_FLAGS:
for k, v in EXTRA_BACKEND_CMAKE_FLAGS[backend].items():
args.append('-D{}={}'.format(k, v))
return args
def cmake_repoagent_arg(name, type, value):
# For now there is no override for repo-agents
if type is None:
type = ''
else:
type = ':{}'.format(type)
return '-D{}{}={}'.format(name, type, value)
def cmake_repoagent_enable(name, flag):
# For now there is no override for repo-agents
value = 'ON' if flag else 'OFF'
return '-D{}:BOOL={}'.format(name, value)
def cmake_repoagent_extra_args():
# For now there is no extra args for repo-agents
args = []
return args
def core_cmake_args(components, backends, install_dir):
cargs = [
cmake_core_arg('CMAKE_BUILD_TYPE', None, FLAGS.build_type),
cmake_core_arg('CMAKE_INSTALL_PREFIX', 'PATH', install_dir),
cmake_core_arg('TRITON_VERSION', 'STRING', FLAGS.version),
cmake_core_arg('TRITON_COMMON_REPO_TAG', 'STRING',
components['common']),
cmake_core_arg('TRITON_CORE_REPO_TAG', 'STRING', components['core']),
cmake_core_arg('TRITON_BACKEND_REPO_TAG', 'STRING',
components['backend']),
cmake_core_arg('TRITON_THIRD_PARTY_REPO_TAG', 'STRING',
components['thirdparty'])
]
cargs.append(
cmake_core_enable('TRITON_ENABLE_LOGGING', FLAGS.enable_logging))
cargs.append(cmake_core_enable('TRITON_ENABLE_STATS', FLAGS.enable_stats))
cargs.append(
cmake_core_enable('TRITON_ENABLE_METRICS', FLAGS.enable_metrics))
cargs.append(
cmake_core_enable('TRITON_ENABLE_METRICS_GPU',
FLAGS.enable_gpu_metrics))
cargs.append(
cmake_core_enable('TRITON_ENABLE_TRACING', FLAGS.enable_tracing))
cargs.append(cmake_core_enable('TRITON_ENABLE_NVTX', FLAGS.enable_nvtx))
cargs.append(cmake_core_enable('TRITON_ENABLE_GPU', FLAGS.enable_gpu))
cargs.append(
cmake_core_arg('TRITON_MIN_COMPUTE_CAPABILITY', None,
FLAGS.min_compute_capability))
cargs.append(
cmake_core_enable('TRITON_ENABLE_MALI_GPU', FLAGS.enable_mali_gpu))
cargs.append(
cmake_core_enable('TRITON_ENABLE_GRPC', 'grpc' in FLAGS.endpoint))
cargs.append(
cmake_core_enable('TRITON_ENABLE_HTTP', 'http' in FLAGS.endpoint))
cargs.append(
cmake_core_enable('TRITON_ENABLE_SAGEMAKER', 'sagemaker'
in FLAGS.endpoint))
cargs.append(
cmake_core_enable('TRITON_ENABLE_VERTEX_AI', 'vertex-ai'
in FLAGS.endpoint))
cargs.append(
cmake_core_enable('TRITON_ENABLE_GCS', 'gcs' in FLAGS.filesystem))
cargs.append(cmake_core_enable('TRITON_ENABLE_S3', 's3'
in FLAGS.filesystem))
cargs.append(
cmake_core_enable('TRITON_ENABLE_AZURE_STORAGE', 'azure_storage'
in FLAGS.filesystem))
cargs.append(
cmake_core_enable('TRITON_ENABLE_ENSEMBLE', 'ensemble' in backends))
cargs.append(
cmake_core_enable('TRITON_ENABLE_TENSORRT', 'tensorrt' in backends))
# If TRITONBUILD_* is defined in the env then we use it to set
# corresponding cmake value.
for evar, eval in os.environ.items():
if evar.startswith('TRITONBUILD_'):
cargs.append(cmake_core_arg(evar[len('TRITONBUILD_'):], None, eval))
cargs += cmake_core_extra_args()
cargs.append(FLAGS.cmake_dir)
return cargs
def repoagent_repo(ra):
return '{}_repository_agent'.format(ra)
def repoagent_cmake_args(images, components, ra, install_dir):
if ra in EXAMPLE_REPOAGENTS:
args = []
else:
fail('unknown agent {}'.format(ra))
cargs = args + [
cmake_repoagent_arg('CMAKE_BUILD_TYPE', None, FLAGS.build_type),
cmake_repoagent_arg('CMAKE_INSTALL_PREFIX', 'PATH', install_dir),
cmake_repoagent_arg('TRITON_COMMON_REPO_TAG', 'STRING',
components['common']),
cmake_repoagent_arg('TRITON_CORE_REPO_TAG', 'STRING',
components['core'])
]
cargs.append(cmake_repoagent_enable('TRITON_ENABLE_GPU', FLAGS.enable_gpu))
# If TRITONBUILD_* is defined in the env then we use it to set
# corresponding cmake value.
for evar, eval in os.environ.items():
if evar.startswith('TRITONBUILD_'):
cargs.append(
cmake_repoagent_arg(evar[len('TRITONBUILD_'):], None, eval))
cargs += cmake_repoagent_extra_args()
cargs.append('..')
return cargs
def backend_repo(be):
if (be == 'tensorflow1') or (be == 'tensorflow2'):
return 'tensorflow_backend'
if be.startswith("openvino"):
return 'openvino_backend'
return '{}_backend'.format(be)
def backend_cmake_args(images, components, be, install_dir, library_paths,
variant_index):
if be == 'onnxruntime':
args = onnxruntime_cmake_args(images, library_paths)
elif be.startswith('openvino'):
args = openvino_cmake_args(be, variant_index)
elif be == 'tensorflow1':
args = tensorflow_cmake_args(1, images, library_paths)
elif be == 'tensorflow2':
args = tensorflow_cmake_args(2, images, library_paths)
elif be == 'python':
args = []
elif be == 'dali':
args = dali_cmake_args()
elif be == 'pytorch':
args = pytorch_cmake_args(images)
elif be == 'armnn_tflite':
args = armnn_tflite_cmake_args()
elif be == 'fil':
args = fil_cmake_args(images)
elif be == 'fastertransformer':
args = []
elif be == 'tensorrt':
args = tensorrt_cmake_args()
elif be in EXAMPLE_BACKENDS:
args = []
else:
fail('unknown backend {}'.format(be))
cargs = args + [
cmake_backend_arg(be, 'CMAKE_BUILD_TYPE', None, FLAGS.build_type),
cmake_backend_arg(be, 'CMAKE_INSTALL_PREFIX', 'PATH', install_dir),
cmake_backend_arg(be, 'TRITON_COMMON_REPO_TAG', 'STRING',
components['common']),
cmake_backend_arg(be, 'TRITON_CORE_REPO_TAG', 'STRING',
components['core']),
cmake_backend_arg(be, 'TRITON_BACKEND_REPO_TAG', 'STRING',
components['backend'])
]
cargs.append(cmake_backend_enable(be, 'TRITON_ENABLE_GPU',
FLAGS.enable_gpu))
cargs.append(
cmake_backend_enable(be, 'TRITON_ENABLE_MALI_GPU',
FLAGS.enable_mali_gpu))
cargs.append(
cmake_backend_enable(be, 'TRITON_ENABLE_STATS', FLAGS.enable_stats))
# If TRITONBUILD_* is defined in the env then we use it to set
# corresponding cmake value.
for evar, eval in os.environ.items():
if evar.startswith('TRITONBUILD_'):
cargs.append(
cmake_backend_arg(be, evar[len('TRITONBUILD_'):], None, eval))
cargs += cmake_backend_extra_args(be)
cargs.append('..')
return cargs
def pytorch_cmake_args(images):
# If platform is jetpack do not use docker based build
if target_platform() == 'jetpack':
if 'pytorch' not in library_paths:
raise Exception(
"Must specify library path for pytorch using --library-paths=pytorch:<path_to_pytorch>"
)
pt_lib_path = library_paths['pytorch'] + "/lib"
pt_include_paths = ""
for suffix in [
'include/torch', 'include/torch/torch/csrc/api/include',
'include/torchvision'
]:
pt_include_paths += library_paths['pytorch'] + '/' + suffix + ';'
cargs = [
cmake_backend_arg('pytorch', 'TRITON_PYTORCH_INCLUDE_PATHS', None,
pt_include_paths),
cmake_backend_arg('pytorch', 'TRITON_PYTORCH_LIB_PATHS', None,
pt_lib_path),
]
else:
if "pytorch" in images:
image = images["pytorch"]
else:
image = 'nvcr.io/nvidia/pytorch:{}-py3'.format(
FLAGS.upstream_container_version)
cargs = [
cmake_backend_arg('pytorch', 'TRITON_PYTORCH_DOCKER_IMAGE', None,
image),
]
if FLAGS.enable_gpu:
cargs.append(
cmake_backend_enable('pytorch',
'TRITON_PYTORCH_ENABLE_TORCHTRT', True))
return cargs
def onnxruntime_cmake_args(images, library_paths):
cargs = [
cmake_backend_arg('onnxruntime', 'TRITON_BUILD_ONNXRUNTIME_VERSION',
None, TRITON_VERSION_MAP[FLAGS.version][2])
]
# TRITON_ENABLE_GPU is already set for all backends in backend_cmake_args()
if FLAGS.enable_gpu:
cargs.append(
cmake_backend_enable('onnxruntime',
'TRITON_ENABLE_ONNXRUNTIME_TENSORRT', True))
# If platform is jetpack do not use docker based build
if target_platform() == 'jetpack':
if 'onnxruntime' not in library_paths:
raise Exception(
"Must specify library path for onnxruntime using --library-paths=onnxruntime:<path_to_onnxruntime>"
)
ort_lib_path = library_paths['onnxruntime'] + "/lib"
ort_include_path = library_paths['onnxruntime'] + "/include"
cargs += [
cmake_backend_arg('onnxruntime', 'TRITON_ONNXRUNTIME_INCLUDE_PATHS',
None, ort_include_path),
cmake_backend_arg('onnxruntime', 'TRITON_ONNXRUNTIME_LIB_PATHS',
None, ort_lib_path),
cmake_backend_enable('onnxruntime',
'TRITON_ENABLE_ONNXRUNTIME_OPENVINO', False)
]
else:
if target_platform() == 'windows':
if 'base' in images:
cargs.append(
cmake_backend_arg('onnxruntime', 'TRITON_BUILD_CONTAINER',
None, images['base']))
else:
if 'base' in images:
cargs.append(
cmake_backend_arg('onnxruntime', 'TRITON_BUILD_CONTAINER',
None, images['base']))
else:
cargs.append(
cmake_backend_arg('onnxruntime',
'TRITON_BUILD_CONTAINER_VERSION', None,
TRITON_VERSION_MAP[FLAGS.version][1]))
if ((target_machine() != 'aarch64') and
(TRITON_VERSION_MAP[FLAGS.version][3] is not None)):
cargs.append(
cmake_backend_enable('onnxruntime',
'TRITON_ENABLE_ONNXRUNTIME_OPENVINO',
True))
cargs.append(
cmake_backend_arg(
'onnxruntime',
'TRITON_BUILD_ONNXRUNTIME_OPENVINO_VERSION', None,
TRITON_VERSION_MAP[FLAGS.version][3]))
return cargs
def openvino_cmake_args(be, variant_index):
using_specific_commit_sha = False
if TRITON_VERSION_MAP[FLAGS.version][4][variant_index][0] == 'SPECIFIC':
using_specific_commit_sha = True
ov_version = TRITON_VERSION_MAP[FLAGS.version][4][variant_index][1]
if ov_version:
if using_specific_commit_sha:
use_prebuilt_ov = False
else:
use_prebuilt_ov = True
else:
# If the OV package version is None, then we are not using prebuilt package
ov_version = TRITON_VERSION_MAP[FLAGS.version][4][variant_index][0]
use_prebuilt_ov = False
if using_specific_commit_sha:
cargs = [
cmake_backend_arg(be, 'TRITON_BUILD_OPENVINO_COMMIT_SHA', None,
ov_version),
]
else:
cargs = [
cmake_backend_arg(be, 'TRITON_BUILD_OPENVINO_VERSION', None,
ov_version),
]
cargs.append(
cmake_backend_arg(be, 'TRITON_OPENVINO_BACKEND_INSTALLDIR', None, be))
if target_platform() == 'windows':
if 'base' in images:
cargs.append(
cmake_backend_arg(be, 'TRITON_BUILD_CONTAINER', None,
images['base']))
else:
if 'base' in images:
cargs.append(
cmake_backend_arg(be, 'TRITON_BUILD_CONTAINER', None,
images['base']))
else:
cargs.append(
cmake_backend_arg(be, 'TRITON_BUILD_CONTAINER_VERSION', None,
TRITON_VERSION_MAP[FLAGS.version][1]))
cargs.append(
cmake_backend_enable(be, 'TRITON_BUILD_USE_PREBUILT_OPENVINO',
use_prebuilt_ov))
return cargs
def tensorrt_cmake_args():
cargs = [
cmake_backend_enable('tensorrt', 'TRITON_ENABLE_NVTX',
FLAGS.enable_nvtx),
]
if target_platform() == 'windows':
cargs.append(
cmake_backend_arg('tensorrt', 'TRITON_TENSORRT_INCLUDE_PATHS', None,
'c:/TensorRT/include'))
return cargs
def tensorflow_cmake_args(ver, images, library_paths):
backend_name = "tensorflow{}".format(ver)
# If platform is jetpack do not use docker images
extra_args = []
if target_platform() == 'jetpack':
if backend_name in library_paths:
extra_args = [
cmake_backend_arg(backend_name, 'TRITON_TENSORFLOW_LIB_PATHS',
None, library_paths[backend_name])
]
else:
raise Exception(
f"Must specify library path for {backend_name} using --library-paths={backend_name}:<path_to_{backend_name}>"
)
else:
# If a specific TF image is specified use it, otherwise pull from NGC.
if backend_name in images:
image = images[backend_name]
else:
image = 'nvcr.io/nvidia/tensorflow:{}-tf{}-py3'.format(
FLAGS.upstream_container_version, ver)
extra_args = [
cmake_backend_arg(backend_name, 'TRITON_TENSORFLOW_DOCKER_IMAGE',
None, image)
]
return [
cmake_backend_arg(backend_name, 'TRITON_TENSORFLOW_VERSION', None, ver)
] + extra_args
def dali_cmake_args():
return [
cmake_backend_enable('dali', 'TRITON_DALI_SKIP_DOWNLOAD', False),
]
def fil_cmake_args(images):
cargs = [cmake_backend_enable('fil', 'TRITON_FIL_DOCKER_BUILD', True)]
if 'base' in images:
cargs.append(
cmake_backend_arg('fil', 'TRITON_BUILD_CONTAINER', None,
images['base']))
else:
cargs.append(
cmake_backend_arg('fil', 'TRITON_BUILD_CONTAINER_VERSION', None,
TRITON_VERSION_MAP[FLAGS.version][1]))
return cargs
def armnn_tflite_cmake_args():
return [
cmake_backend_arg('armnn_tflite', 'JOBS', None,
multiprocessing.cpu_count()),
]
def install_dcgm_libraries(dcgm_version, target_machine):
if dcgm_version == '':
fail(
'unable to determine default repo-tag, DCGM version not known for {}'
.format(FLAGS.version))
return ''
else:
if target_machine == 'aarch64':
return '''
ENV DCGM_VERSION {}
# Install DCGM. Steps from https://developer.nvidia.com/dcgm#Downloads
RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/sbsa/cuda-ubuntu2004.pin && \
mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600 && \
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/sbsa/7fa2af80.pub && \
add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/sbsa/ /" && \
apt-get update && apt-get install -y datacenter-gpu-manager=1:{}
'''.format(dcgm_version, dcgm_version)
else:
return '''
ENV DCGM_VERSION {}
# Install DCGM. Steps from https://developer.nvidia.com/dcgm#Downloads
RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin && \
mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600 && \
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/7fa2af80.pub && \
add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ /" && \
apt-get update && apt-get install -y datacenter-gpu-manager=1:{}
'''.format(dcgm_version, dcgm_version)
def get_container_versions(version, container_version,
upstream_container_version):
if container_version is None:
if version not in TRITON_VERSION_MAP:
fail('container version not known for {}'.format(version))
container_version = TRITON_VERSION_MAP[version][0]
if upstream_container_version is None:
if version not in TRITON_VERSION_MAP:
fail('upstream container version not known for {}'.format(version))
upstream_container_version = TRITON_VERSION_MAP[version][1]
return container_version, upstream_container_version
def create_dockerfile_buildbase(ddir, dockerfile_name, argmap):
df = '''
ARG TRITON_VERSION={}
ARG TRITON_CONTAINER_VERSION={}
ARG BASE_IMAGE={}
'''.format(argmap['TRITON_VERSION'], argmap['TRITON_CONTAINER_VERSION'],
argmap['BASE_IMAGE'])
df += '''
FROM ${BASE_IMAGE}
ARG TRITON_VERSION
ARG TRITON_CONTAINER_VERSION
'''
# Install the windows- or linux-specific buildbase dependencies
if target_platform() == 'windows':
df += '''
SHELL ["cmd", "/S", "/C"]
'''
else:
df += '''
# Ensure apt-get won't prompt for selecting options
ENV DEBIAN_FRONTEND=noninteractive
# libcurl4-openSSL-dev is needed for GCS
# python3-dev is needed by Torchvision
# python3-pip and libarchive-dev is needed by python backend
# uuid-dev and pkg-config is needed for Azure Storage
# scons is needed for armnn_tflite backend build dep
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates \
autoconf \
automake \
build-essential \
docker.io \
git \
libre2-dev \
libssl-dev \
libtool \
libboost-dev \
libcurl4-openssl-dev \
libb64-dev \
patchelf \
python3-dev \
python3-pip \
python3-setuptools \
rapidjson-dev \
scons \
software-properties-common \
unzip \
wget \
zlib1g-dev \
libarchive-dev \
pkg-config \
uuid-dev \
libnuma-dev && \
rm -rf /var/lib/apt/lists/*
RUN pip3 install --upgrade pip && \
pip3 install --upgrade wheel setuptools docker
# Server build requires recent version of CMake (FetchContent required)
RUN wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc 2>/dev/null | \
gpg --dearmor - | \
tee /etc/apt/trusted.gpg.d/kitware.gpg >/dev/null && \
apt-add-repository 'deb https://apt.kitware.com/ubuntu/ focal main' && \
apt-get update && \
apt-get install -y --no-install-recommends \
cmake-data=3.21.1-0kitware1ubuntu20.04.1 cmake=3.21.1-0kitware1ubuntu20.04.1
'''
# Copy in the triton source. We remove existing contents first in
# case the FROM container has something there already.
if target_platform() == 'windows':
df += '''
WORKDIR /workspace
RUN rmdir /S/Q * || exit 0
COPY . .
'''
else:
df += '''
WORKDIR /workspace
RUN rm -fr *
COPY . .
ENTRYPOINT []
'''
if FLAGS.enable_gpu:
df += install_dcgm_libraries(argmap['DCGM_VERSION'],
target_machine())
df += '''
ENV TRITON_SERVER_VERSION ${TRITON_VERSION}
ENV NVIDIA_TRITON_SERVER_VERSION ${TRITON_CONTAINER_VERSION}
'''
mkdir(ddir)
with open(os.path.join(ddir, dockerfile_name), "w") as dfile:
dfile.write(df)
def create_dockerfile_build(ddir, dockerfile_name, backends, build_dir):
df = '''
FROM tritonserver_builder_image AS build
FROM tritonserver_buildbase
COPY --from=build {0} {0}
'''.format(build_dir)
# If requested, package the source code for all OSS used to build
# Triton Windows is not delivered as a container (and tar not
# available) so skip for windows platform.
if target_platform() != 'windows':
if not FLAGS.no_core_build and not FLAGS.no_container_source:
df += '''
RUN mkdir -p {0}/install/third-party-src && \
(cd {0}/tritonserver/build && \
tar zcf {0}/install/third-party-src/src.tar.gz third-party-src)
COPY --from=build /workspace/docker/README.third-party-src {0}/install/third-party-src/README
'''.format(build_dir)
if 'onnxruntime' in backends:
if target_platform() != 'windows':
df += '''
# Copy ONNX custom op library and model (needed for testing)
RUN if [ -d {0}/onnxruntime ]; then \
cp {0}/onnxruntime/install/test/libcustom_op_library.so /workspace/qa/L0_custom_ops/.; \
cp {0}/onnxruntime/install/test/custom_op_test.onnx /workspace/qa/L0_custom_ops/.; \
fi
'''.format(build_dir)
mkdir(ddir)
with open(os.path.join(ddir, dockerfile_name), "w") as dfile:
dfile.write(df)
def create_dockerfile_linux(ddir, dockerfile_name, argmap, backends, repoagents,
endpoints, build_dir):
df = '''
#
# Multistage build.
#
ARG TRITON_VERSION={}
ARG TRITON_CONTAINER_VERSION={}
ARG BASE_IMAGE={}
ARG BUILD_IMAGE=tritonserver_build
############################################################################
## Build image
############################################################################
FROM ${{BUILD_IMAGE}} AS tritonserver_build
'''.format(argmap['TRITON_VERSION'], argmap['TRITON_CONTAINER_VERSION'],
argmap['BASE_IMAGE'])
# PyTorch and TensorFlow1 backend need extra CUDA and other dependencies
# during runtime that are missing in the CPU only base container. These
# dependencies must be copied from the Triton Min image
if not FLAGS.enable_gpu and \
(('pytorch' in backends) or ('tensorflow1' in backends)):
df += '''
############################################################################
## Triton Min image
############################################################################
FROM {} AS min_container
'''.format(argmap['GPU_BASE_IMAGE'])
df += '''
############################################################################
## Production stage: Create container with just inference server executable
############################################################################
FROM ${BASE_IMAGE}
'''
df += dockerfile_prepare_container_linux(argmap, backends, FLAGS.enable_gpu,
target_machine())
df += '''
WORKDIR /opt/tritonserver
COPY --chown=1000:1000 LICENSE .
COPY --chown=1000:1000 TRITON_VERSION .
COPY --chown=1000:1000 NVIDIA_Deep_Learning_Container_License.pdf .
'''
if not FLAGS.no_core_build:
df += '''
COPY --chown=1000:1000 --from=tritonserver_build {0}/install/bin/tritonserver bin/
COPY --chown=1000:1000 --from=tritonserver_build {0}/install/lib/libtritonserver.so lib/
COPY --chown=1000:1000 --from=tritonserver_build {0}/install/include/triton/core include/triton/core
# Top-level include/core not copied so --chown does not set it correctly,
# so explicit set on all of include
RUN chown -R triton-server:triton-server include
'''.format(build_dir)
# If requested, include the source code for all OSS used to build Triton
if not FLAGS.no_container_source:
df += '''
COPY --chown=1000:1000 --from=tritonserver_build {0}/install/third-party-src third-party-src
'''.format(build_dir)
# Add feature labels for SageMaker endpoint
if 'sagemaker' in endpoints:
df += '''
LABEL com.amazonaws.sagemaker.capabilities.accept-bind-to-port=true
COPY --chown=1000:1000 --from=tritonserver_build /workspace/docker/sagemaker/serve /usr/bin/.
'''
for noncore in NONCORE_BACKENDS:
if noncore in backends:
df += '''
COPY --chown=1000:1000 --from=tritonserver_build {0}/install/backends backends
'''.format(build_dir)
break
# This is required since libcublasLt.so is not present during the build
# stage of the PyTorch backend
if not FLAGS.enable_gpu and ('pytorch' in backends):
df += '''
RUN patchelf --add-needed /usr/local/cuda/lib64/stubs/libcublasLt.so.11 backends/pytorch/libtorch_cuda.so