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Currently, pipeline_ml does not validate the input in the inference used for prediction. Since mlflow>=1.9.0, it is now possible to save the signature (=the inputs and outputs columsn name, order and types) and validate them at runtime.
Since pipeline_ml creates the MlflowPipelineModel for the KedroPipeline declared as inference argument with access to the training pipeline data, this data schema can be inferred at the same time automatically. It is both safer and a kind of minimal "auto-documentation" of the expected instance for prediction.
The text was updated successfully, but these errors were encountered:
Currently,
pipeline_ml
does not validate the input in theinference
used for prediction. Sincemlflow>=1.9.0
, it is now possible to save the signature (=the inputs and outputs columsn name, order and types) and validate them at runtime.Since
pipeline_ml
creates theMlflowPipelineModel
for theKedroPipeline
declared as inference argument with access to the training pipeline data, this data schema can be inferred at the same time automatically. It is both safer and a kind of minimal "auto-documentation" of the expected instance for prediction.The text was updated successfully, but these errors were encountered: