forked from mindspore-Ecosystem/mindspore
54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
# 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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config settings, will be used in finetune.py
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"""
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from easydict import EasyDict as edict
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import mindspore.common.dtype as mstype
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from mindspore.model_zoo.Bert_NEZHA import BertConfig
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cfg = edict({
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'task': 'NER',
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'num_labels': 41,
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'data_file': '/your/path/evaluation.tfrecord',
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'schema_file': '/your/path/schema.json',
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'finetune_ckpt': '/your/path/your.ckpt',
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'use_crf': False,
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'clue_benchmark': False,
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})
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bert_net_cfg = BertConfig(
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batch_size=16 if not cfg.clue_benchmark else 1,
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seq_length=128,
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vocab_size=21128,
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hidden_size=768,
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num_hidden_layers=12,
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num_attention_heads=12,
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intermediate_size=3072,
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hidden_act="gelu",
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hidden_dropout_prob=0.0,
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attention_probs_dropout_prob=0.0,
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max_position_embeddings=512,
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type_vocab_size=2,
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initializer_range=0.02,
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use_relative_positions=False,
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input_mask_from_dataset=True,
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token_type_ids_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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