| | |
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| | | from .utils.utils import (ONNXRuntimeError, |
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| | | OrtInferSession, get_logger, |
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| | | read_yaml) |
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| | | from .utils.utils import (TokenIDConverter, split_to_mini_sentence,code_mix_split_words) |
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| | | from .utils.utils import (TokenIDConverter, split_to_mini_sentence,code_mix_split_words,code_mix_split_words_jieba) |
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| | | logging = get_logger() |
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| | | |
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| | | |
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| | |
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| | | self.punc_list[i] = "？" |
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| | | elif self.punc_list[i] == "。": |
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| | | self.period = i |
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| | | if "seg_jieba" in config: |
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| | | self.seg_jieba = True |
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| | | self.jieba_usr_dict_path = os.path.join(model_dir, 'jieba_usr_dict') |
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| | | self.code_mix_split_words_jieba = code_mix_split_words_jieba(self.jieba_usr_dict_path) |
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| | | else: |
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| | | self.seg_jieba = False |
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| | | |
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| | | def __call__(self, text: Union[list, str], split_size=20): |
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| | | split_text = code_mix_split_words(text) |
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| | | if self.seg_jieba: |
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| | | split_text = self.code_mix_split_words_jieba(text) |
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| | | else: |
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| | | split_text = code_mix_split_words(text) |
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| | | split_text_id = self.converter.tokens2ids(split_text) |
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| | | mini_sentences = split_to_mini_sentence(split_text, split_size) |
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| | | mini_sentences_id = split_to_mini_sentence(split_text_id, split_size) |
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| | |
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| | | data = { |
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| | | "input": mini_sentence_id[None,:], |
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| | | "text_lengths": np.array([text_length], dtype='int32'), |
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| | | "vad_mask": vad_mask |
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| | | "vad_mask": vad_mask, |
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| | | "sub_masks": vad_mask |
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| | | } |
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| | | try: |
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