sub:assertion {
  sub:_LinguisticSystem a schema:ComputerLanguage ;
    rdfs:label "python" ;
    rdfs:seeAlso <https://www.wikidata.org/wiki/Q28865> ;
    owl:versionInfo "3.9.15.final.0" .
  sub:_hyper_params a pplan:Variable ;
    rdfs:comment "None" ;
    rdfs:label "hyper_params" .
  sub:_model a pplan:Variable ;
    rdfs:comment "None" ;
    rdfs:label "model" .
  sub:_out1 a pplan:Variable ;
    rdfs:comment "str" ;
    rdfs:label "out1" .
  sub:_path a pplan:Variable ;
    rdfs:comment "None" ;
    rdfs:label "path" .
  sub:_sample_data a pplan:Variable ;
    rdfs:comment "None" ;
    rdfs:label "sample_data" .
  sub:_scores a pplan:Variable ;
    rdfs:comment "None" ;
    rdfs:label "scores" .
  sub:_step dc1:description """@is_fairstep(label='Save a model')
def save(
    model,
    path,
    sample_data,
    scores = None,
    hyper_params = None,
    # model: Any,
    # path: str,
    # sample_data: Any,
    # scores: Optional[Dict] = None,
    # hyper_params: Optional[Dict] = None,
) -> str:
    model_name = path.rsplit('/', 1)[-1]
    # print(os.path.isabs(path))
    # if not os.path.isabs(path):
    #     path = os.path.join(os.getcwd(), path)
    log.info(f\"💾 Saving model in {path}\")

    # mlem_model = MlemModel.from_obj(model, sample_data=sample_data)
    # mlem_model.dump(path)
    # print(mlem_model)
    mlem.save(model, path, sample_data=sample_data)

    g = get_run_metadata(scores, sample_data, hyper_params, model_name)
    g.serialize(f\"{path}.ttl\", format='ttl')
    # os.chmod(f\"{path}.ttl\", 0o644)
    # os.chmod(f\"{path}.mlem\", 0o644)

    # TODO: generate and store RDF metadata
    return path
""" ;
    dc1:language sub:_LinguisticSystem ;
    pplan:hasInputVar sub:_hyper_params , sub:_model , sub:_path , sub:_sample_data , sub:_scores ;
    pplan:hasOutputVar sub:_out1 ;
    a bpmn:ScriptTask , pplan:Step ;
    rdfs:label "Save a model" .
}