compose.py

#!/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:
        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)