mlflow.models module provides an API for saving machine learning models in
“flavors” that can be understood by different downstream tools.
The built-in flavors are:
For details, see MLflow Models.
Model(artifact_path=None, run_id=None, utc_time_created=datetime.datetime(2019, 1, 30, 22, 33, 56, 74277), flavors=None)
An MLflow Model that can support multiple model flavors.
log(artifact_path, flavor, **kwargs)
Log model using supplied flavor module.
- artifact_path – Run relative path identifying the model.
- flavor – Flavor module to save the model with. The module must have
save_modelfunction that will persist the model as a valid MLflow model.
- kwargs – Extra args passed to the model flavor.