ibm_aigov_facts_client.export.export_facts_manual module

class ExportFactsManual(facts_service_client: FactsClientAdapter, **kwargs)

Bases: FactsheetServiceClientManual

Export payloads for any run tracked by manual log

export_payload_manual(run_id: str, root_directory: str = None) DetailedResponse

Export single run to factsheet when using manual logging option. Use this option when client is initiated with enable_autolog=False and external_model=True

Parameters:
  • run_id (str) – Id of run to be exported

  • root_directory (str) – (Optional) Absolute path for directory containing experiments and runs.

Returns:

A DetailedResponse containing the factsheet response result

Return type:

DetailedResponse

A way you might use me is:

>>> client.export_facts.export_payload_manual(<RUN_ID>)
prepare_model_meta(wml_client: object, meta_props: Dict[str, Any], experiment_name: str = None) Dict

Add current experiment attributes to model meta properties

Parameters:
  • wml_client (object) – Watson Machine learning client object.

  • meta_props (dict) – Current model meta properties.

  • experiment_name (str) – (Optional) Explicit name any experiment to be used.

Returns:

A Dict containing the updated meta properties.

Return type:

Dict

A way you might use me is:

>>> client.export_facts.prepare_model_meta(wml_client=<wml_client>,meta_props=<wml_model_meta_props>)