interpret_community.mlflow package¶
Module for interaction with MLflow.
- interpret_community.mlflow.get_explanation(run_id, name)¶
Download and deserialize an explanation that has been logged to MLflow.
- interpret_community.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.
- interpret_community.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