python/FunASR-XL.git

			@@ -28,7 +28,7 @@
			from funasr.models.decoder.transformer_decoder import (
			DynamicConvolution2DTransformerDecoder, # noqa: H301
			)
			from funasr.models.decoder.transformer_decoder_sa_asr import SAAsrTransformerDecoder
			from funasr.models.decoder.transformer_decoder import SAAsrTransformerDecoder
			from funasr.models.decoder.transformer_decoder import DynamicConvolutionTransformerDecoder
			from funasr.models.decoder.transformer_decoder import (
			LightweightConvolution2DTransformerDecoder, # noqa: H301
			@@ -39,7 +39,7 @@
			from funasr.models.decoder.transformer_decoder import ParaformerDecoderSAN
			from funasr.models.decoder.transformer_decoder import TransformerDecoder
			from funasr.models.decoder.contextual_decoder import ContextualParaformerDecoder
			from funasr.models.e2e_sa_asr import ESPnetASRModel
			from funasr.models.e2e_sa_asr import SAASRModel
			from funasr.models.e2e_asr_paraformer import Paraformer, ParaformerBert, BiCifParaformer, ContextualParaformer
			from funasr.models.e2e_tp import TimestampPredictor
			from funasr.models.e2e_asr_mfcca import MFCCA
			@@ -70,11 +70,11 @@
			from funasr.models.specaug.abs_specaug import AbsSpecAug
			from funasr.models.specaug.specaug import SpecAug
			from funasr.models.specaug.specaug import SpecAugLFR
			from funasr.models.base_model import FunASRModel
			from funasr.modules.subsampling import Conv1dSubsampling
			from funasr.tasks.abs_task import AbsTask
			from funasr.text.phoneme_tokenizer import g2p_choices
			from funasr.torch_utils.initialize import initialize
			from funasr.train.abs_espnet_model import AbsESPnetModel
			from funasr.train.class_choices import ClassChoices
			from funasr.train.trainer import Trainer
			from funasr.utils.get_default_kwargs import get_default_kwargs
			@@ -120,7 +120,7 @@
			model_choices = ClassChoices(
			"model",
			classes=dict(
			asr=ESPnetASRModel,
			asr=SAASRModel,
			uniasr=UniASR,
			paraformer=Paraformer,
			paraformer_bert=ParaformerBert,
			@@ -129,7 +129,7 @@
			mfcca=MFCCA,
			timestamp_prediction=TimestampPredictor,
			),
			type_check=AbsESPnetModel,
			type_check=FunASRModel,
			default="asr",
			)
			preencoder_choices = ClassChoices(
			@@ -620,4 +620,4 @@
			initialize(model, args.init)

			assert check_return_type(model)
			return model
			return model