mindspore/model_zoo/mass/eval.py

60 lines
2.0 KiB
Python

# Copyright 2020 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""Evaluation api."""
import argparse
import pickle
from mindspore.common import dtype as mstype
from config import TransformerConfig
from src.transformer import infer, infer_ppl
from src.utils import Dictionary
from src.utils import get_score
parser = argparse.ArgumentParser(description='Evaluation MASS.')
parser.add_argument("--config", type=str, required=True,
help="Model config json file path.")
parser.add_argument("--vocab", type=str, required=True,
help="Vocabulary to use.")
parser.add_argument("--output", type=str, required=True,
help="Result file path.")
parser.add_argument("--metric", type=str, default='rouge',
help='Set eval method.')
def get_config(config):
config = TransformerConfig.from_json_file(config)
config.compute_type = mstype.float16
config.dtype = mstype.float32
return config
if __name__ == '__main__':
args, _ = parser.parse_known_args()
vocab = Dictionary.load_from_persisted_dict(args.vocab)
_config = get_config(args.config)
if args.metric == 'rouge':
result = infer(_config)
else:
result = infer_ppl(_config)
with open(args.output, "wb") as f:
pickle.dump(result, f, 1)
# get score by given metric
score = get_score(result, vocab, metric=args.metric)
print(score)