Merge branch 'PaddlePaddle:develop' into develop

paddlespeech/cli/tts/infer.py

@@ -405,8 +405,6 @@ class TTSExecutor(BaseExecutor):
         with open(self.voc_config) as f:
             self.voc_config = CfgNode(yaml.safe_load(f))
 
-        # Enter the path of model root
-
         with open(self.phones_dict, "r") as f:
             phn_id = [line.strip().split() for line in f.readlines()]
         vocab_size = len(phn_id)
@@ -501,10 +499,10 @@ class TTSExecutor(BaseExecutor):
         """
         Model inference and result stored in self.output.
         """
-        model_name = am[:am.rindex('_')]
-        dataset = am[am.rindex('_') + 1:]
+        am_name = am[:am.rindex('_')]
+        am_dataset = am[am.rindex('_') + 1:]
         get_tone_ids = False
-        if 'speedyspeech' in model_name:
+        if am_name == 'speedyspeech':
             get_tone_ids = True
         if lang == 'zh':
             input_ids = self.frontend.get_input_ids(
@@ -521,15 +519,14 @@ class TTSExecutor(BaseExecutor):
             print("lang should in {'zh', 'en'}!")
 
         # am
-        if 'speedyspeech' in model_name:
+        if am_name == 'speedyspeech':
             mel = self.am_inference(phone_ids, tone_ids)
         # fastspeech2
         else:
             # multi speaker
-            if dataset in {"aishell3", "vctk"}:
+            if am_dataset in {"aishell3", "vctk"}:
                 mel = self.am_inference(
                     phone_ids, spk_id=paddle.to_tensor(spk_id))
-
             else:
                 mel = self.am_inference(phone_ids)