# Copyright (c) Alibaba, Inc. and its affiliates.
[docs]def generate_best_metric_name(evaluate_type, dataset_name, metric_names):
"""
Generate best metric name for different evaluator / different dataset / different metric_names
evaluate_type: str
dataset_name: None or str
metric_names: None str or list[str] or tuple(str)
Return:
list[str]
"""
base_name = evaluate_type
if dataset_name is not None:
base_name = base_name + '_' + dataset_name
return_name = []
if metric_names is None:
return_name = [base_name]
elif type(metric_names) == str:
return_name = [base_name + '_' + metric_names]
elif type(metric_names) == list or type(metric_names) == tuple:
if len(metric_names) == 0:
return_name = [base_name]
for k in metric_names:
assert (type(k) == str)
return_name.append(base_name + '_' + k)
return return_name