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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.
- # ============================================================================
- """Generate News Crawl corpus dataset."""
- import argparse
-
- from src.utils import Dictionary
- from src.utils.preprocess import create_pre_training_dataset
-
- parser = argparse.ArgumentParser(description='Create News Crawl Pre-Training Dataset.')
- parser.add_argument("--src_folder", type=str, default="", required=True,
- help="Raw corpus folder.")
- parser.add_argument("--existed_vocab", type=str, default="", required=True,
- help="Existed vocab path.")
- parser.add_argument("--mask_ratio", type=float, default=0.4, required=True,
- help="Mask ratio.")
- parser.add_argument("--output_folder", type=str, default="", required=True,
- help="Dataset output path.")
- parser.add_argument("--max_len", type=int, default=32, required=False,
- help="Max length of sentences.")
- parser.add_argument("--suffix", type=str, default="", required=False,
- help="Add suffix to output file.")
- parser.add_argument("--processes", type=int, default=2, required=False,
- help="Size of processes pool.")
-
- if __name__ == '__main__':
- args, _ = parser.parse_known_args()
- if not (args.src_folder and args.output_folder):
- raise ValueError("Please enter required params.")
-
- if not args.existed_vocab:
- raise ValueError("`--existed_vocab` is required.")
-
- vocab = Dictionary.load_from_persisted_dict(args.existed_vocab)
-
- create_pre_training_dataset(
- folder_path=args.src_folder,
- output_folder_path=args.output_folder,
- vocabulary=vocab,
- prefix="news.20", suffix=args.suffix,
- mask_ratio=args.mask_ratio,
- min_sen_len=10,
- max_sen_len=args.max_len,
- dataset_type="tfrecord",
- cores=args.processes
- )
- print(f" | Vocabulary size: {vocab.size}.")
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