Merge branch 'dev_infer' of https://github.com/alibaba/FunASR into dev_infer

funasr/bin/asr_infer.py

@@ -1581,7 +1581,7 @@ class Speech2TextTransducer:
             d = ModelDownloader()
             kwargs.update(**d.download_and_unpack(model_tag))
         
-        return Speech2Text(**kwargs)
+        return Speech2TextTransducer(**kwargs)
 
 
 class Speech2TextSAASR:

funasr/build_utils/build_asr_model.py

@@ -87,6 +87,8 @@ model_choices = ClassChoices(
         contextual_paraformer=ContextualParaformer,
         mfcca=MFCCA,
         timestamp_prediction=TimestampPredictor,
+        rnnt=TransducerModel,
+        rnnt_unified=UnifiedTransducerModel,
     ),
     default="asr",
 )
@@ -367,7 +369,7 @@ def build_asr_model(args):
             token_list=token_list,
             **args.model_conf,
         )
-    elif args.model == "rnnt":
+    elif args.model == "rnnt" or args.model == "rnnt_unified":
         # 5. Decoder
         encoder_output_size = encoder.output_size()
 
@@ -396,34 +398,21 @@ def build_asr_model(args):
             **args.joint_network_conf,
         )
 
+        model_class = model_choices.get_class(args.model)
         # 7. Build model
-        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,
-            )
+        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,
+        )
 
-        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,
-            )
     else:
         raise NotImplementedError("Not supported model: {}".format(args.model))
 

funasr/tasks/asr.py

@@ -132,6 +132,8 @@ model_choices = ClassChoices(
         neatcontextual_paraformer=NeatContextualParaformer,
         mfcca=MFCCA,
         timestamp_prediction=TimestampPredictor,
+        rnnt=TransducerModel,
+        rnnt_unified=UnifiedTransducerModel,
     ),
     type_check=FunASRModel,
     default="asr",
@@ -1453,7 +1455,7 @@ class ASRTransducerTask(ASRTask):
         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,
@@ -1471,35 +1473,23 @@ class ASRTransducerTask(ASRTask):
         )
 
         # 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(