def _eval_strategy_for_task(model_type: str,
task_type_for_data: TaskTypesEnum):
models_repo = ModelTypesRepository()
model_info = models_repo.model_info_by_id(model_type)
task_type_for_model = task_type_for_data
task_types_acceptable_for_model = model_info.task_type
# if the model can't be used directly for the task type from data
if task_type_for_model not in task_types_acceptable_for_model:
# search the supplementary task types, that can be included in chain which solves original task
globally_compatible_task_types = compatible_task_types(
task_type_for_model)
compatible_task_types_acceptable_for_model = list(
set(task_types_acceptable_for_model).intersection(
set(globally_compatible_task_types)))
if len(compatible_task_types_acceptable_for_model) == 0:
raise ValueError(
f'Model {model_type} can not be used as a part of {task_type_for_model}.'
)
task_type_for_model = compatible_task_types_acceptable_for_model[0]
strategy = models_repo.model_info_by_id(model_type).current_strategy(
task_type_for_model)
return strategy
def test_search_in_repository_by_id_correct():
repo = ModelTypesRepository(mocked_path())
model = repo.model_info_by_id(id='tpot')
assert model.id == 'tpot'
assert 'automl' in model.tags
