def _safe_local_path(local_path):
# NB: Since mlflow 1.0, mlflow.pyfunc.load_model expects uri instead of local path. Local paths
# work, however absolute windows path don't because the drive is parsed as scheme. Since we do
# not control the version of mlflow (the scoring server version matches the version of mlflow
# invoking the scoring command, the rest of mlflow comes from the model environment) we check
# the mlflow version at run time and convert local path to file uri to ensure platform
# independence.
from mlflow.version import VERSION
is_recent_version = VERSION.endswith("dev0") or int(
VERSION.split(".")[0]) >= 1
if is_recent_version:
from mlflow.tracking.utils import path_to_local_file_uri
return path_to_local_file_uri(local_path)
return local_path
def _create_dockerfile(output_path, mlflow_path=None):
"""
Creates a Dockerfile containing additional Docker build steps to execute
when building the Azure container image. These build steps perform the following tasks:
- Install MLflow
:param output_path: The path where the Dockerfile will be written.
:param mlflow_path: Path to a local copy of the MLflow GitHub repository. If specified, the
Dockerfile command for MLflow installation will install MLflow from this
directory. Otherwise, it will install MLflow from pip.
"""
docker_cmds = ["RUN pip install azureml-sdk"]
if mlflow_path is not None:
mlflow_install_cmd = "RUN pip install -e {mlflow_path}".format(
mlflow_path=_get_container_path(mlflow_path))
elif not mlflow_version.endswith("dev"):
mlflow_install_cmd = "RUN pip install mlflow=={mlflow_version}".format(
mlflow_version=mlflow_version)
else:
raise MlflowException(
"You are running a 'dev' version of MLflow: `{mlflow_version}` that cannot be"
" installed from pip. In order to build a container image, either specify the"
" path to a local copy of the MLflow GitHub repository using the `mlflow_home`"
" parameter or install a release version of MLflow from pip".
format(mlflow_version=mlflow_version))
docker_cmds.append(mlflow_install_cmd)
with open(output_path, "w") as f:
f.write("\n".join(docker_cmds))
