interpret_community.mlflow.mlflow module¶
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interpret_community.mlflow.mlflow.
get_explanation
(run_id, name)¶ Download and deserialize an explanation that has been logged to MLflow.
Parameters: Returns: The rehydrated explanation.
Return type: Explanation
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interpret_community.mlflow.mlflow.
log_explanation
(name, explanation)¶ Log the explanation to MLflow using MLflow model logging.
Parameters: - name (str) – The name of the explanation. Will be used as a directory name.
- explanation (Explanation) – The explanation object to log.
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interpret_community.mlflow.mlflow.
save_model
(path, loader_module=None, data_path=None, conda_env=None, mlflow_model=None, **kwargs)¶ Save the explanation locally using the MLflow model format.
This function is necessary for log_explanation to work properly.
Parameters: - path (str) – The destination path for the saved explanation.
- loader_module (str) – The package that will be used to reload a serialized explanation. In this case, always interpret_community.mlflow.
- data_path (str) – The path to the serialized explanation files.
- conda_env (str) – The path to a YAML file with basic Python environment information.
- mlflow_model (None) – In our case, always None.
Returns: The MLflow model representation of the explanation.
Return type: mlflow.models.Model