wucong.lyb
2023-07-04 6b840d51437d3b23854bd9bed84cfb0d8976d079
funasr/build_utils/build_asr_model.py
@@ -26,6 +26,7 @@
from funasr.models.e2e_asr_mfcca import MFCCA
from funasr.models.e2e_asr_transducer import TransducerModel, UnifiedTransducerModel
from funasr.models.e2e_asr_bat import BATModel
from funasr.models.e2e_sa_asr import SAASRModel
from funasr.models.e2e_asr_paraformer import Paraformer, ParaformerOnline, ParaformerBert, BiCifParaformer, ContextualParaformer
@@ -46,7 +47,7 @@
from funasr.models.frontend.wav_frontend import WavFrontend
from funasr.models.frontend.windowing import SlidingWindow
from funasr.models.joint_net.joint_network import JointNetwork
from funasr.models.predictor.cif import CifPredictor, CifPredictorV2, CifPredictorV3
from funasr.models.predictor.cif import CifPredictor, CifPredictorV2, CifPredictorV3, BATPredictor
from funasr.models.specaug.specaug import SpecAug
from funasr.models.specaug.specaug import SpecAugLFR
from funasr.modules.subsampling import Conv1dSubsampling
@@ -99,7 +100,7 @@
        rnnt=TransducerModel,
        rnnt_unified=UnifiedTransducerModel,
        sa_asr=SAASRModel,
        bat=BATModel,
    ),
    default="asr",
)
@@ -188,6 +189,7 @@
        ctc_predictor=None,
        cif_predictor_v2=CifPredictorV2,
        cif_predictor_v3=CifPredictorV3,
        bat_predictor=BATPredictor,
    ),
    default="cif_predictor",
    optional=True,
@@ -313,12 +315,15 @@
    encoder = encoder_class(input_size=input_size, **args.encoder_conf)
    # decoder
    decoder_class = decoder_choices.get_class(args.decoder)
    decoder = decoder_class(
        vocab_size=vocab_size,
        encoder_output_size=encoder.output_size(),
        **args.decoder_conf,
    )
    if hasattr(args, "decoder") and args.decoder is not None:
        decoder_class = decoder_choices.get_class(args.decoder)
        decoder = decoder_class(
            vocab_size=vocab_size,
            encoder_output_size=encoder.output_size(),
            **args.decoder_conf,
        )
    else:
        decoder = None
    # ctc
    ctc = CTC(
@@ -463,6 +468,53 @@
            joint_network=joint_network,
            **args.model_conf,
        )
    elif args.model == "bat":
        # 5. Decoder
        encoder_output_size = encoder.output_size()
        rnnt_decoder_class = rnnt_decoder_choices.get_class(args.rnnt_decoder)
        decoder = rnnt_decoder_class(
            vocab_size,
            **args.rnnt_decoder_conf,
        )
        decoder_output_size = decoder.output_size
        if getattr(args, "decoder", None) is not None:
            att_decoder_class = decoder_choices.get_class(args.decoder)
            att_decoder = att_decoder_class(
                vocab_size=vocab_size,
                encoder_output_size=encoder_output_size,
                **args.decoder_conf,
            )
        else:
            att_decoder = None
        # 6. Joint Network
        joint_network = JointNetwork(
            vocab_size,
            encoder_output_size,
            decoder_output_size,
            **args.joint_network_conf,
        )
        predictor_class = predictor_choices.get_class(args.predictor)
        predictor = predictor_class(**args.predictor_conf)
        model_class = model_choices.get_class(args.model)
        # 7. Build model
        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,
            predictor=predictor,
            **args.model_conf,
        )
    elif args.model == "sa_asr":
        asr_encoder_class = asr_encoder_choices.get_class(args.asr_encoder)
        asr_encoder = asr_encoder_class(input_size=input_size, **args.asr_encoder_conf)