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compose.py
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compose.py
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#!/usr/bin/env python3
# Copyright 2021-2022, 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 os
import platform
import subprocess
import sys
FLAGS = None
#### helper functions
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):
print('error: {}'.format(msg), file=sys.stderr)
sys.exit(1)
def fail_if(p, msg):
if p:
fail(msg)
def start_dockerfile(ddir, images, argmap, dockerfile_name, backends):
# Set enviroment variables, set default user and install dependencies
df = '''
#
# Multistage build.
#
ARG TRITON_VERSION={}
ARG TRITON_CONTAINER_VERSION={}
FROM {} AS full
'''.format(argmap['TRITON_VERSION'], argmap['TRITON_CONTAINER_VERSION'],
images["full"])
# PyTorch, TensorFlow 1 and TensorFlow 2 backends 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) or
('tensorflow2' in backends)):
df += '''
FROM {} AS min_container
'''.format(images["gpu-min"])
df += '''
FROM {}
'''.format(images["min"])
import build
df += build.dockerfile_prepare_container_linux(argmap, backends,
FLAGS.enable_gpu,
platform.machine().lower())
# Copy over files
df += '''
WORKDIR /opt/tritonserver
COPY --chown=1000:1000 --from=full /opt/tritonserver/LICENSE .
COPY --chown=1000:1000 --from=full /opt/tritonserver/TRITON_VERSION .
COPY --chown=1000:1000 --from=full /opt/tritonserver/NVIDIA_Deep_Learning_Container_License.pdf .
COPY --chown=1000:1000 --from=full /opt/tritonserver/bin bin/
COPY --chown=1000:1000 --from=full /opt/tritonserver/lib lib/
COPY --chown=1000:1000 --from=full /opt/tritonserver/include include/
'''
with open(os.path.join(ddir, dockerfile_name), "w") as dfile:
dfile.write(df)
def add_requested_backends(ddir, dockerfile_name, backends):
df = "# Copying over backends \n"
for backend in backends:
if backend == 'openvino':
import build
ver = next(iter(build.TRITON_VERSION_MAP.values()))
backend = build.tagged_backend(backend, ver[4][0])
df += '''COPY --chown=1000:1000 --from=full /opt/tritonserver/backends/{} /opt/tritonserver/backends/{}
'''.format(backend, backend)
if len(backends) > 0:
df += '''
# Top-level /opt/tritonserver/backends not copied so need to explicitly set permissions here
RUN chown triton-server:triton-server /opt/tritonserver/backends
'''
with open(os.path.join(ddir, dockerfile_name), "a") as dfile:
dfile.write(df)
def add_requested_repoagents(ddir, dockerfile_name, repoagents):
df = "# Copying over repoagents \n"
for ra in repoagents:
df += '''COPY --chown=1000:1000 --from=full /opt/tritonserver/repoagents/{} /opt/tritonserver/repoagents/{}
'''.format(ra, ra)
if len(repoagents) > 0:
df += '''
# Top-level /opt/tritonserver/repoagents not copied so need to explicitly set permissions here
RUN chown triton-server:triton-server /opt/tritonserver/repoagents
'''
with open(os.path.join(ddir, dockerfile_name), "a") as dfile:
dfile.write(df)
def end_dockerfile(ddir, dockerfile_name, argmap):
# Install additional dependencies
df = ""
if argmap['SAGEMAKER_ENDPOINT']:
df += '''
LABEL com.amazonaws.sagemaker.capabilities.accept-bind-to-port=true
COPY --chown=1000:1000 --from=full /usr/bin/serve /usr/bin/.
'''
with open(os.path.join(ddir, dockerfile_name), "a") as dfile:
dfile.write(df)
def build_docker_image(ddir, dockerfile_name, container_name):
# Create container with docker build
p = subprocess.Popen(['docker', 'build', '-t', container_name, '-f', \
os.path.join(ddir, dockerfile_name), '.'])
p.wait()
fail_if(p.returncode != 0, 'docker build {} failed'.format(container_name))
def get_container_version_if_not_specified():
if FLAGS.container_version is None:
# Read from TRITON_VERSION file in server repo to determine version
with open('TRITON_VERSION', "r") as vfile:
version = vfile.readline().strip()
import build
_, FLAGS.container_version = build.container_versions(
version, None, FLAGS.container_version)
log('version {}'.format(version))
log('using container version {}'.format(FLAGS.container_version))
def create_argmap(images):
# Extract information from upstream build and create map other functions can
# use
full_docker_image = images["full"]
min_docker_image = images["min"]
enable_gpu = FLAGS.enable_gpu
# Docker inspect enviroment variables
base_run_args = ['docker', 'inspect', '-f']
import re # parse all PATH enviroment variables
# first pull docker images
log("pulling container:{}".format(full_docker_image))
p = subprocess.run(['docker', 'pull', full_docker_image])
fail_if(
p.returncode != 0,
'docker pull container {} failed, {}'.format(full_docker_image,
p.stderr))
if enable_gpu:
pm = subprocess.run(['docker', 'pull', min_docker_image])
fail_if(
pm.returncode != 0, 'docker pull container {} failed, {}'.format(
min_docker_image, pm.stderr))
pm_path = subprocess.run(base_run_args + [
'{{range $index, $value := .Config.Env}}{{$value}} {{end}}',
min_docker_image
],
capture_output=True,
text=True)
fail_if(
pm_path.returncode != 0,
'docker inspect to find triton enviroment variables for min container failed, {}'
.format(pm_path.stderr))
# min container needs to be GPU support enabled if the build is GPU build
vars = pm_path.stdout
e = re.search("CUDA_VERSION", vars)
gpu_enabled = False if e is None else True
fail_if(
not gpu_enabled,
'Composing container with gpu support enabled but min container provided does not have CUDA installed'
)
# Check full container enviroment variables
p_path = subprocess.run(base_run_args + [
'{{range $index, $value := .Config.Env}}{{$value}} {{end}}',
full_docker_image
],
capture_output=True,
text=True)
fail_if(
p_path.returncode != 0,
'docker inspect to find enviroment variables for full container failed, {}'
.format(p_path.stderr))
vars = p_path.stdout
log_verbose("inspect args: {}".format(vars))
e0 = re.search("TRITON_SERVER_GPU_ENABLED=([\S]{1,}) ", vars)
e1 = re.search("CUDA_VERSION", vars)
gpu_enabled = False
if (e0 != None):
gpu_enabled = e0.group(1) == "1"
elif (e1 != None):
gpu_enabled = True
fail_if(
gpu_enabled != enable_gpu,
'Error: full container provided was build with \'TRITON_SERVER_GPU_ENABLED\' as {} and you are composing container with \'TRITON_SERVER_GPU_ENABLED\' as {}'
.format(gpu_enabled, enable_gpu))
e = re.search("TRITON_SERVER_VERSION=([\S]{6,}) ", vars)
version = "" if e is None else e.group(1)
fail_if(
len(version) == 0,
'docker inspect to find triton server version failed, {}'.format(
p_path.stderr))
e = re.search("NVIDIA_TRITON_SERVER_VERSION=([\S]{5,}) ", vars)
container_version = "" if e is None else e.group(1)
fail_if(
len(container_version) == 0,
'docker inspect to find triton container version failed, {}'.format(
vars))
dcgm_ver = re.search("DCGM_VERSION=([\S]{4,}) ", vars)
dcgm_version = ""
if dcgm_ver is None:
dcgm_version = "2.2.3"
log("WARNING: DCGM version not found from image, installing the earlierst version {}"
.format(dcgm_version))
else:
dcgm_version = dcgm_ver.group(1)
fail_if(
len(dcgm_version) == 0,
'docker inspect to find DCGM version failed, {}'.format(vars))
p_sha = subprocess.run(
base_run_args +
['{{ index .Config.Labels "com.nvidia.build.ref"}}', full_docker_image],
capture_output=True,
text=True)
fail_if(
p_sha.returncode != 0,
'docker inspect of upstream docker image build sha failed, {}'.format(
p_sha.stderr))
p_build = subprocess.run(
base_run_args +
['{{ index .Config.Labels "com.nvidia.build.id"}}', full_docker_image],
capture_output=True,
text=True)
fail_if(
p_build.returncode != 0,
'docker inspect of upstream docker image build sha failed, {}'.format(
p_build.stderr))
p_find = subprocess.run(
['docker', 'run', full_docker_image, 'bash', '-c', 'ls /usr/bin/'],
capture_output=True,
text=True)
f = re.search("serve", p_find.stdout)
fail_if(p_find.returncode != 0,
"Cannot search for 'serve' in /usr/bin, {}".format(p_find.stderr))
argmap = {
'NVIDIA_BUILD_REF': p_sha.stdout.rstrip(),
'NVIDIA_BUILD_ID': p_build.stdout.rstrip(),
'TRITON_VERSION': version,
'TRITON_CONTAINER_VERSION': container_version,
'DCGM_VERSION': dcgm_version,
'SAGEMAKER_ENDPOINT': f is not None,
}
return argmap
if __name__ == '__main__':
parser = argparse.ArgumentParser()
group_qv = parser.add_mutually_exclusive_group()
group_qv.add_argument('-q',
'--quiet',
action="store_true",
required=False,
help='Disable console output.')
group_qv.add_argument('-v',
'--verbose',
action="store_true",
required=False,
help='Enable verbose output.')
parser.add_argument(
'--output-name',
type=str,
required=False,
help='Name for the generated Docker image. Default is "tritonserver".')
parser.add_argument(
'--work-dir',
type=str,
required=False,
help=
'Generated dockerfiles are placed here. Default to current directory.')
parser.add_argument(
'--container-version',
type=str,
required=False,
help=
'The version to use for the generated Docker image. If not specified the container version will be chosen automatically based on the repository branch.'
)
parser.add_argument(
'--image',
action='append',
required=False,
help=
'Use specified Docker image to generate Docker image. Specified as <image-name>,<full-image-name>. <image-name> can be "min", "gpu-min" or "full". Both "min" and "full" need to be specified at the same time. This will override "--container-version". "gpu-min" is needed for CPU-only container to copy TensorFlow and PyTorch deps.'
)
parser.add_argument('--enable-gpu',
nargs='?',
type=lambda x: (str(x).lower() == 'true'),
const=True,
default=True,
required=False,
help=argparse.SUPPRESS)
parser.add_argument(
'--backend',
action='append',
required=False,
help=
'Include <backend-name> in the generated Docker image. The flag may be specified multiple times.'
)
parser.add_argument(
'--repoagent',
action='append',
required=False,
help=
'Include <repoagent-name> in the generated Docker image. The flag may be specified multiple times.'
)
parser.add_argument(
'--dry-run',
action="store_true",
required=False,
help='Only creates Dockerfile.compose, does not build the Docker image.'
)
FLAGS = parser.parse_args()
if FLAGS.work_dir is None:
FLAGS.work_dir = "."
if FLAGS.output_name is None:
FLAGS.output_name = "tritonserver"
dockerfile_name = 'Dockerfile.compose'
if FLAGS.backend is None:
FLAGS.backend = []
if FLAGS.repoagent is None:
FLAGS.repoagent = []
# Initialize map of docker images.
images = {}
if FLAGS.image:
for img in FLAGS.image:
parts = img.split(',')
fail_if(
len(parts) != 2,
'--image must specific <image-name>,<full-image-registry>')
fail_if(
parts[0] not in ['min', 'full', 'gpu-min'],
'unsupported image-name \'{}\' for --image'.format(parts[0]))
log('image "{}": "{}"'.format(parts[0], parts[1]))
images[parts[0]] = parts[1]
else:
get_container_version_if_not_specified()
if FLAGS.enable_gpu:
images = {
"full":
"nvcr.io/nvidia/tritonserver:{}-py3".format(
FLAGS.container_version),
"min":
"nvcr.io/nvidia/tritonserver:{}-py3-min".format(
FLAGS.container_version)
}
else:
images = {
"full":
"nvcr.io/nvidia/tritonserver:{}-cpu-only-py3".format(
FLAGS.container_version),
"min":
"ubuntu:20.04"
}
fail_if(
len(images) < 2,
"Need to specify both 'full' and 'min' images if at all")
# For CPU-only image we need to copy some cuda libraries and dependencies
# since we are using PyTorch, TensorFlow 1, TensorFlow 2 containers that
# are not CPU-only.
if (('pytorch' in FLAGS.backend) or ('tensorflow1' in FLAGS.backend) or
('tensorflow2' in FLAGS.backend)) and ('gpu-min' not in images):
images["gpu-min"] = "nvcr.io/nvidia/tritonserver:{}-py3-min".format(
FLAGS.container_version)
argmap = create_argmap(images)
start_dockerfile(FLAGS.work_dir, images, argmap, dockerfile_name,
FLAGS.backend)
add_requested_backends(FLAGS.work_dir, dockerfile_name, FLAGS.backend)
add_requested_repoagents(FLAGS.work_dir, dockerfile_name, FLAGS.repoagent)
end_dockerfile(FLAGS.work_dir, dockerfile_name, argmap)
if (not FLAGS.dry_run):
build_docker_image(FLAGS.work_dir, dockerfile_name, FLAGS.output_name)