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# Copyright 2020 Huawei Technologies Co., Ltd |
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# |
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# Licensed under the Apache License, Version 2.0 (the "License"); |
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# you may not use this file except in compliance with the License. |
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# You may obtain a copy of the License at |
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# |
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# http://www.apache.org/licenses/LICENSE-2.0 |
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# |
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# Unless required by applicable law or agreed to in writing, software |
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# distributed under the License is distributed on an "AS IS" BASIS, |
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
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# See the License for the specific language governing permissions and |
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# limitations under the License. |
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# ============================================================================ |
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''' |
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Transformer hub interface for transformer large |
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''' |
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from src.transformer_model import TransformerModel |
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from src.transformer_model import TransformerConfig |
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import mindspore.common.dtype as mstype |
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transformer_net_cfg_large = TransformerConfig( |
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batch_size=96, |
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seq_length=128, |
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vocab_size=36560, |
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hidden_size=1024, |
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num_hidden_layers=6, |
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num_attention_heads=16, |
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intermediate_size=4096, |
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hidden_act="relu", |
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hidden_dropout_prob=0.2, |
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attention_probs_dropout_prob=0.2, |
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max_position_embeddings=128, |
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initializer_range=0.02, |
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label_smoothing=0.1, |
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input_mask_from_dataset=True, |
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dtype=mstype.float32, |
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compute_type=mstype.float16 |
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) |
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def create_network(name, *args, **kwargs): |
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''' |
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Create transformer network for large. |
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''' |
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if name == 'transformer_large': |
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if "seq_length" in kwargs: |
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transformer_net_cfg_large.seq_length = kwargs["seq_length"] |
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is_training = kwargs.get("is_training", False) |
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return TransformerModel(transformer_net_cfg_large, is_training, *args) |
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raise NotImplementedError(f"{name} is not implemented in the repo") |