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- # Copyright 2021 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.
- # ============================================================================
- """NAML export."""
- import numpy as np
- from mindspore import Tensor
- from mindspore.train.serialization import load_checkpoint, export
- from src.naml import NAML, NAMLWithLossCell
- from src.option import get_args
-
- if __name__ == '__main__':
-
- args = get_args("export")
- net = NAML(args)
- net.set_train(False)
- net_with_loss = NAMLWithLossCell(net)
- load_checkpoint(args.checkpoint_path, net_with_loss)
- news_encoder = net.news_encoder
- user_encoder = net.user_encoder
- bs = args.batch_size
- category = Tensor(np.zeros([bs, 1], np.int32))
- subcategory = Tensor(np.zeros([bs, 1], np.int32))
- title = Tensor(np.zeros([bs, args.n_words_title], np.int32))
- abstract = Tensor(np.zeros([bs, args.n_words_abstract], np.int32))
-
- news_input_data = [category, subcategory, title, abstract]
- export(news_encoder, *news_input_data, file_name=f"naml_news_encoder_bs_{bs}", file_format=args.file_format)
-
- browsed_news = Tensor(np.zeros([bs, args.n_browsed_news, args.n_filters], np.float32))
- export(user_encoder, browsed_news, file_name=f"naml_user_encoder_bs_{bs}", file_format=args.file_format)
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