Files
zenml/venv/lib/python3.9/site-packages/mlflow/models/docker_utils.py
Christian Mantha 2ca0b9ef7c star
2026-03-02 19:10:52 -05:00

239 lines
8.4 KiB
Python

import logging
import os
from subprocess import Popen
from typing import Optional, Union
from urllib.parse import urlparse
from mlflow.environment_variables import MLFLOW_DOCKER_OPENJDK_VERSION
from mlflow.utils import env_manager as em
from mlflow.utils.file_utils import _copy_project
from mlflow.version import VERSION
_logger = logging.getLogger(__name__)
UBUNTU_BASE_IMAGE = "ubuntu:20.04"
PYTHON_SLIM_BASE_IMAGE = "python:{version}-slim"
SETUP_PYENV_AND_VIRTUALENV = r"""# Setup pyenv
RUN DEBIAN_FRONTEND=noninteractive TZ=Etc/UTC apt-get -y install tzdata \
libssl-dev zlib1g-dev libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm \
libncursesw5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev libffi-dev liblzma-dev
RUN git clone \
--depth 1 \
--branch $(git ls-remote --tags --sort=v:refname https://github.com/pyenv/pyenv.git | grep -o -E 'v[1-9]+(\.[1-9]+)+$' | tail -1) \
https://github.com/pyenv/pyenv.git /root/.pyenv
ENV PYENV_ROOT="/root/.pyenv"
ENV PATH="$PYENV_ROOT/bin:$PATH"
RUN apt install -y python3.9 python3.9-distutils \
&& ln -s -f $(which python3.9) /usr/bin/python \
&& wget https://bootstrap.pypa.io/get-pip.py -O /tmp/get-pip.py \
&& python /tmp/get-pip.py
RUN pip install virtualenv
""" # noqa: E501
_DOCKERFILE_TEMPLATE = """# Build an image that can serve mlflow models.
FROM {base_image}
{setup_python_venv}
{setup_java}
WORKDIR /opt/mlflow
{install_mlflow}
{install_model_and_deps}
ENV MLFLOW_DISABLE_ENV_CREATION={disable_env_creation}
ENV ENABLE_MLSERVER={enable_mlserver}
# granting read/write access and conditional execution authority to all child directories
# and files to allow for deployment to AWS Sagemaker Serverless Endpoints
# (see https://docs.aws.amazon.com/sagemaker/latest/dg/serverless-endpoints.html)
RUN chmod o+rwX /opt/mlflow/
# clean up apt cache to reduce image size
RUN rm -rf /var/lib/apt/lists/*
ENTRYPOINT ["python", "-c", "{entrypoint}"]
"""
SETUP_MINICONDA = """# Setup miniconda
RUN curl --fail -L https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh > miniconda.sh
RUN bash ./miniconda.sh -b -p /miniconda && rm ./miniconda.sh
ENV PATH="/miniconda/bin:$PATH"
""" # noqa: E501
def generate_dockerfile(
output_dir: str,
base_image: str,
model_install_steps: Optional[str],
entrypoint: str,
env_manager: Union[em.CONDA, em.LOCAL, em.VIRTUALENV],
mlflow_home: Optional[str] = None,
enable_mlserver: bool = False,
disable_env_creation_at_runtime: bool = True,
install_java: Optional[bool] = None,
):
"""
Generates a Dockerfile that can be used to build a docker image, that serves ML model
stored and tracked in MLflow.
"""
setup_java_steps = ""
setup_python_venv_steps = ""
install_mlflow_steps = _pip_mlflow_install_step(output_dir, mlflow_home)
if base_image.startswith("python:"):
if install_java:
_logger.warning(
"`install_java` option is not supported when using python base image, "
"switch to UBUNTU_BASE_IMAGE to enable java installation."
)
setup_python_venv_steps = (
"RUN apt-get -y update && apt-get install -y --no-install-recommends nginx"
)
elif base_image == UBUNTU_BASE_IMAGE:
setup_python_venv_steps = (
"RUN apt-get -y update && DEBIAN_FRONTEND=noninteractive TZ=Etc/UTC apt-get install -y "
"--no-install-recommends wget curl nginx ca-certificates bzip2 build-essential cmake "
"git-core\n\n"
)
setup_python_venv_steps += (
SETUP_MINICONDA if env_manager == em.CONDA else SETUP_PYENV_AND_VIRTUALENV
)
if install_java is not False:
jdk_ver = MLFLOW_DOCKER_OPENJDK_VERSION.get()
setup_java_steps = (
"# Setup Java\n"
f"RUN apt-get install -y --no-install-recommends openjdk-{jdk_ver}-jdk maven\n"
f"ENV JAVA_HOME=/usr/lib/jvm/java-{jdk_ver}-openjdk-amd64"
)
install_mlflow_steps += "\n\n" + _java_mlflow_install_step(mlflow_home)
with open(os.path.join(output_dir, "Dockerfile"), "w") as f:
f.write(
_DOCKERFILE_TEMPLATE.format(
base_image=base_image,
setup_python_venv=setup_python_venv_steps,
setup_java=setup_java_steps,
install_mlflow=install_mlflow_steps,
install_model_and_deps=model_install_steps,
entrypoint=entrypoint,
enable_mlserver=enable_mlserver,
disable_env_creation=disable_env_creation_at_runtime,
)
)
def _java_mlflow_install_step(mlflow_home):
maven_proxy = _get_maven_proxy()
if mlflow_home:
return (
"# Install Java mlflow-scoring from local source\n"
"RUN cd /opt/mlflow/mlflow/java/scoring && "
f"mvn --batch-mode package -DskipTests {maven_proxy} && "
"mkdir -p /opt/java/jars && "
"mv /opt/mlflow/mlflow/java/scoring/target/"
"mlflow-scoring-*-with-dependencies.jar /opt/java/jars\n"
)
else:
return (
"# Install Java mlflow-scoring from Maven Central\n"
"RUN mvn"
" --batch-mode dependency:copy"
f" -Dartifact=org.mlflow:mlflow-scoring:{VERSION}:pom"
f" -DoutputDirectory=/opt/java {maven_proxy}\n"
"RUN mvn"
" --batch-mode dependency:copy"
f" -Dartifact=org.mlflow:mlflow-scoring:{VERSION}:jar"
f" -DoutputDirectory=/opt/java/jars {maven_proxy}\n"
f"RUN cp /opt/java/mlflow-scoring-{VERSION}.pom /opt/java/pom.xml\n"
"RUN cd /opt/java && mvn "
"--batch-mode dependency:copy-dependencies "
f"-DoutputDirectory=/opt/java/jars {maven_proxy}\n"
)
def _get_maven_proxy():
http_proxy = os.getenv("http_proxy")
https_proxy = os.getenv("https_proxy")
if not http_proxy or not https_proxy:
return ""
# Expects proxies as either PROTOCOL://{USER}:{PASSWORD}@HOSTNAME:PORT
# or PROTOCOL://HOSTNAME:PORT
parsed_http_proxy = urlparse(http_proxy)
assert parsed_http_proxy.hostname is not None, "Invalid `http_proxy` hostname."
assert parsed_http_proxy.port is not None, f"Invalid proxy port: {parsed_http_proxy.port}"
parsed_https_proxy = urlparse(https_proxy)
assert parsed_https_proxy.hostname is not None, "Invalid `https_proxy` hostname."
assert parsed_https_proxy.port is not None, f"Invalid proxy port: {parsed_https_proxy.port}"
maven_proxy_options = (
"-DproxySet=true",
f"-Dhttp.proxyHost={parsed_http_proxy.hostname}",
f"-Dhttp.proxyPort={parsed_http_proxy.port}",
f"-Dhttps.proxyHost={parsed_https_proxy.hostname}",
f"-Dhttps.proxyPort={parsed_https_proxy.port}",
"-Dhttps.nonProxyHosts=repo.maven.apache.org",
)
if parsed_http_proxy.username is None or parsed_http_proxy.password is None:
return " ".join(maven_proxy_options)
return " ".join(
(
*maven_proxy_options,
f"-Dhttp.proxyUser={parsed_http_proxy.username}",
f"-Dhttp.proxyPassword={parsed_http_proxy.password}",
)
)
def _pip_mlflow_install_step(dockerfile_context_dir, mlflow_home):
"""
Get docker build commands for installing MLflow given a Docker context dir and optional source
directory
"""
if mlflow_home:
mlflow_dir = _copy_project(
src_path=os.path.abspath(mlflow_home), dst_path=dockerfile_context_dir
)
return (
"# Install MLflow from local source\n"
f"COPY {mlflow_dir} /opt/mlflow\n"
"RUN pip install /opt/mlflow"
)
else:
return f"# Install MLflow\nRUN pip install mlflow=={VERSION}"
def build_image_from_context(context_dir: str, image_name: str):
import docker
client = docker.from_env()
# In Docker < 19, `docker build` doesn't support the `--platform` option
is_platform_supported = int(client.version()["Version"].split(".")[0]) >= 19
# Enforcing the AMD64 architecture build for Apple M1 users
platform_option = ["--platform", "linux/amd64"] if is_platform_supported else []
commands = [
"docker",
"build",
"-t",
image_name,
"-f",
"Dockerfile",
*platform_option,
".",
]
proc = Popen(commands, cwd=context_dir)
if proc.wait():
raise RuntimeError("Docker build failed.")