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@ -163,6 +163,30 @@ def get_params() -> AttributeDict:
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return params
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def decode_one_batch_greedy(
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params: AttributeDict,
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model: nn.Module,
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HLG: Optional[k2.Fsa],
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H: Optional[k2.Fsa],
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batch: dict,
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lexicon: Lexicon,
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sos_id: int,
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eos_id: int,
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token_dict: dict,
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) -> Dict[str, List[List[int]]]:
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if params.method == 'greedy-search' or params.method == 'ctc-decoding':
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batch_size = nnet_output.size(0)
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for i in range(batch_size):
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topk_log_probs, topk_indexes = nnet_output[i].topk(1)
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topk_indexes = topk_indexes.squeeze().unique_consecutive()
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topk_indexes = topk_indexes[topk_indexes != 0]
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hyp = ''
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for idx in topk_indexes:
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hyp += token_dict[idx.item()]
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print(hyp)
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def decode_one_batch(
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params: AttributeDict,
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model: nn.Module,
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