This page explains how to migrate between versions with breaking changes, if you had an existing kedro project.
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 are now auto-registered if you use kedro>=0.16.4
. You can remove the following entry from your run.py
:
hooks = (
MlflowPipelineHook(),
MlflowNodeHook()
)
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.