from funasr.lm.abs_model import AbsLM
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from funasr.lm.seq_rnn_lm import SequentialRNNLM
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from funasr.lm.transformer_lm import TransformerLM
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from funasr.torch_utils.initialize import initialize
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from funasr.train.class_choices import ClassChoices
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lm_choices = ClassChoices(
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"lm",
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classes=dict(
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seq_rnn=SequentialRNNLM,
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transformer=TransformerLM,
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),
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type_check=AbsLM,
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default="seq_rnn",
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)
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class_choices_list = [
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# --lm and --lm_conf
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lm_choices
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]
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|
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def build_pretrain_model(args):
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# token_list
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if args.token_list is not None:
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with open(args.token_list) as f:
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token_list = [line.rstrip() for line in f]
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args.token_list = list(token_list)
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vocab_size = len(token_list)
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logging.info(f"Vocabulary size: {vocab_size}")
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else:
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vocab_size = None
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return model
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