websocket 2pass bugfix

游雁

2023-05-19 219c2482ab755fbd4e49dfbdee91bf1a8a4ec49a

 funasr/tasks/asr.py

@@ -132,6 +132,8 @@
        neatcontextual_paraformer=NeatContextualParaformer,
        mfcca=MFCCA,
        timestamp_prediction=TimestampPredictor,
        rnnt=TransducerModel,
        rnnt_unified=UnifiedTransducerModel,
    ),
    type_check=FunASRModel,
    default="asr",
@@ -222,6 +224,15 @@
    ),
    type_check=RNNTDecoder,
    default="rnnt",
)

joint_network_choices = ClassChoices(
    name="joint_network",
    classes=dict(
        joint_network=JointNetwork,
    ),
    default="joint_network",
    optional=True,
)

predictor_choices = ClassChoices(
@@ -353,7 +364,7 @@
            help="The keyword arguments for CTC class.",
        )
        group.add_argument(
            "--joint_net_conf",
            "--joint_network_conf",
            action=NestedDictAction,
            default=None,
            help="The keyword arguments for joint network class.",
@@ -1444,7 +1455,7 @@
        decoder_output_size = decoder.output_size

        if getattr(args, "decoder", None) is not None:
            att_decoder_class = decoder_choices.get_class(args.att_decoder)
            att_decoder_class = decoder_choices.get_class(args.decoder)

            att_decoder = att_decoder_class(
                vocab_size=vocab_size,
@@ -1462,35 +1473,23 @@
        )

        # 7. Build model
        try:
            model_class = model_choices.get_class(args.model)
        except AttributeError:
            model_class = model_choices.get_class("asr")

        if hasattr(encoder, 'unified_model_training') and encoder.unified_model_training:
            model = UnifiedTransducerModel(
                vocab_size=vocab_size,
                token_list=token_list,
                frontend=frontend,
                specaug=specaug,
                normalize=normalize,
                encoder=encoder,
                decoder=decoder,
                att_decoder=att_decoder,
                joint_network=joint_network,
                **args.model_conf,
            )

        else:
            model = TransducerModel(
                vocab_size=vocab_size,
                token_list=token_list,
                frontend=frontend,
                specaug=specaug,
                normalize=normalize,
                encoder=encoder,
                decoder=decoder,
                att_decoder=att_decoder,
                joint_network=joint_network,
                **args.model_conf,
            )

        model = model_class(
            vocab_size=vocab_size,
            token_list=token_list,
            frontend=frontend,
            specaug=specaug,
            normalize=normalize,
            encoder=encoder,
            decoder=decoder,
            att_decoder=att_decoder,
            joint_network=joint_network,
            **args.model_conf,
        )
        # 8. Initialize model
        if args.init is not None:
            raise NotImplementedError(