def hyperopt()

in ludwig/hyperopt_cli.py [0:0]

• 36 lines of code
• 1 McCabe index (conditional complexity)

def hyperopt(
        model_definition=None,
        model_definition_file=None,
        data_df=None,
        data_train_df=None,
        data_validation_df=None,
        data_test_df=None,
        data_csv=None,
        data_train_csv=None,
        data_validation_csv=None,
        data_test_csv=None,
        data_hdf5=None,
        data_train_hdf5=None,
        data_validation_hdf5=None,
        data_test_hdf5=None,
        train_set_metadata_json=None,
        experiment_name="hyperopt",
        model_name="run",
        # model_load_path=None,
        # model_resume_path=None,
        skip_save_training_description=True,
        skip_save_training_statistics=True,
        skip_save_model=True,
        skip_save_progress=True,
        skip_save_log=True,
        skip_save_processed_input=True,
        skip_save_unprocessed_output=True,
        skip_save_test_predictions=True,
        skip_save_test_statistics=True,
        skip_save_hyperopt_statistics=False,
        output_directory="results",
        gpus=None,
        gpu_memory_limit=None,
        allow_parallel_threads=True,
        use_horovod=False,
        random_seed=default_random_seed,
        debug=False,
        **kwargs,