Migration guide

This page explains how to migrate between versions with breaking changes, if you had an existing kedro project.

Migration from 0.3.0 to 0.4.0

Catalog entries

Replace the follwoing entries:

old	new
kedro_mlflow.io.MlflowArtifactDataSet	kedro_mlflow.io.artifacts.MlflowArtifactDataSet
kedro_mlflow.io.MlflowMetricsDataSet	kedro_mlflow.io.metrics.MlflowMetricsDataSet

Hooks

Hooks are now auto-registered if you use kedro>=0.16.4. You can remove the following entry from your run.py:

    hooks = (
        MlflowPipelineHook(),
        MlflowNodeHook()
    )

KedroPipelineModel

Be aware that if you had trained saved a pipeline as a mlflow model with pipeline_ml_factory, retraining this pipeline with kedro-mlflow==0.4.0 will lead to a new behaviour. Let assume the name of your output in the DataCatalog was predictions, the output of a registered model will be modified from:

{
    predictions:
        {
            <your model-predictions>
        }
}

to:

{
    <your model-predictions>
}

Thus, parsing the predictions of this model must be updated accordingly.