Register a pipeline to mlflow with KedroPipelineModel
custom mlflow model
You can log a Kedro Pipeline
to mlflow as a custom model through the CLI with modelify
command:
kedro mlflow modelify --pipeline=<your-pipeline> --input-name <name-in-catalog-of-input-data>
This command will create a new run with an artifact named model
. Open the user interface with kedro mlflow ui
to check the result. You can also:
specify the run id in which you want to log the pipeline with the
--run-id
argumentpass almost all arguments accepted by
mlflow.pyfunc.log_model
, see the list of all accepted arguments in the API documentation