asr 统一接口，支持conformer和uniasr模型

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10964641

    * support new asr paraformer model

* support asr conformer model

* add new asr model tests

* fix format

* support new in params

* fix conflict

* type fix

* fix conflict

modelscope/pipelines/audio/asr_inference_pipeline.py

@@ -124,6 +124,15 @@ class AutomaticSpeechRecognitionPipeline(Pipeline):
             frontend_conf = None
             if 'frontend_conf' in root:
                 frontend_conf = root['frontend_conf']
+            token_num_relax = None
+            if 'token_num_relax' in root:
+                token_num_relax = root['token_num_relax']
+            decoding_ind = None
+            if 'decoding_ind' in root:
+                decoding_ind = root['decoding_ind']
+            decoding_mode = None
+            if 'decoding_mode' in root:
+                decoding_mode = root['decoding_mode']
 
             cmd['beam_size'] = root['beam_size']
             cmd['penalty'] = root['penalty']
@@ -138,6 +147,9 @@ class AutomaticSpeechRecognitionPipeline(Pipeline):
             cmd['frontend_conf'] = frontend_conf
             if frontend_conf is not None and 'fs' in frontend_conf:
                 cmd['fs']['model_fs'] = frontend_conf['fs']
+            cmd['token_num_relax'] = token_num_relax
+            cmd['decoding_ind'] = decoding_ind
+            cmd['decoding_mode'] = decoding_mode
 
         elif self.framework == Frameworks.tf:
             cmd['fs']['model_fs'] = inputs['model_config']['fs']
@@ -234,16 +246,14 @@ class AutomaticSpeechRecognitionPipeline(Pipeline):
     def run_inference(self, cmd):
         asr_result = []
         if self.framework == Frameworks.torch and cmd['code_base'] == 'funasr':
-            if cmd['mode'] == 'asr':
-                from funasr.bin import asr_inference_modelscope as asr_inference
-            else:
-                from funasr.bin import asr_inference_paraformer_modelscope as asr_inference
+            from funasr.bin import asr_inference_launch
 
-            if hasattr(asr_inference, 'set_parameters'):
-                asr_inference.set_parameters(sample_rate=cmd['fs'])
-                asr_inference.set_parameters(language=cmd['lang'])
+            if hasattr(asr_inference_launch, 'set_parameters'):
+                asr_inference_launch.set_parameters(sample_rate=cmd['fs'])
+                asr_inference_launch.set_parameters(language=cmd['lang'])
 
-            asr_result = asr_inference.asr_inference(
+            asr_result = asr_inference_launch.inference_launch(
+                mode=cmd['mode'],
                 batch_size=cmd['batch_size'],
                 maxlenratio=cmd['maxlenratio'],
                 minlenratio=cmd['minlenratio'],
@@ -253,13 +263,16 @@ class AutomaticSpeechRecognitionPipeline(Pipeline):
                 lm_weight=cmd['lm_weight'],
                 penalty=cmd['penalty'],
                 log_level=cmd['log_level'],
-                name_and_type=cmd['name_and_type'],
+                data_path_and_name_and_type=cmd['name_and_type'],
                 audio_lists=cmd['audio_in'],
                 asr_train_config=cmd['asr_train_config'],
                 asr_model_file=cmd['asr_model_file'],
                 lm_file=cmd['lm_file'],
                 lm_train_config=cmd['lm_train_config'],
-                frontend_conf=cmd['frontend_conf'])
+                frontend_conf=cmd['frontend_conf'],
+                token_num_relax=cmd['token_num_relax'],
+                decoding_ind=cmd['decoding_ind'],
+                decoding_mode=cmd['decoding_mode'])
         elif self.framework == Frameworks.torch:
             from easyasr import asr_inference_paraformer_espnet