ibm_aigov_facts_client.export.export_facts_manual module
- class ExportFactsManual(facts_service_client: FactsClientAdapter, **kwargs)
Bases:
FactsheetServiceClientManualExport 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>)