load_model#

load_model(model_uri, dst_path=None)[source]#

Load a sktime model from a local file or a run.

Parameters:
model_uristr

The location, in URI format, of the MLflow model. For example:

  • /Users/me/path/to/local/model

  • relative/path/to/local/model

  • s3://my_bucket/path/to/model

  • runs:/<mlflow_run_id>/run-relative/path/to/model

  • mlflow-artifacts:/path/to/model

For more information about supported URI schemes, see Referencing Artifacts.

dst_pathstr, optional (default=None)

The local filesystem path to which to download the model artifact.This directory must already exist. If unspecified, a local output path will be created.

Returns:
A sktime model instance.

References

[1]

https://www.mlflow.org/docs/latest/python_api/mlflow.models.html#mlflow.models.Model.load

Examples

>>> from sktime.datasets import load_airline
>>> from sktime.forecasting.arima import ARIMA
>>> from sktime.utils import mlflow_sktime  
>>> y = load_airline()  
>>> forecaster = ARIMA(  
...     order=(1, 1, 0),
...     seasonal_order=(0, 1, 0, 12),
...     suppress_warnings=True)
>>> forecaster.fit(y)  
ARIMA(...)
>>> model_path = "model"  
>>> mlflow_sktime.save_model(  
...     sktime_model=forecaster,
...     path=model_path)
>>> loaded_model = mlflow_sktime.load_model(model_uri=model_path)