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- # 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 os
- import argparse
- import pickle
-
- from mindspore.common import dtype as mstype
- from mindspore import context
-
- 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.')
- parser.add_argument("--platform", type=str, required=True,
- help="model working platform.")
-
-
- def get_config(config):
- config = TransformerConfig.from_json_file(config)
- config.compute_type = mstype.float32
- config.dtype = mstype.float32
- return config
-
-
- if __name__ == '__main__':
- args, _ = parser.parse_known_args()
- if args.vocab.endswith("bin"):
- vocab = Dictionary.load_from_persisted_dict(args.vocab)
- else:
- vocab = Dictionary.load_from_text([args.vocab])
- _config = get_config(args.config)
-
- device_id = os.getenv('DEVICE_ID', None)
- if device_id is None:
- device_id = 0
- device_id = int(device_id)
- context.set_context(
- #mode=context.GRAPH_MODE,
- mode=context.PYNATIVE_MODE,
- device_target=args.platform,
- reserve_class_name_in_scope=False,
- device_id=device_id)
-
- 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)
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