commend get_device() on abstract function

modules/whisper/whisper_base.py

@@ -42,7 +42,7 @@ class WhisperBase(ABC):
         self.vad = SileroVAD()
 
     @abstractmethod
-    #@spaces.GPU(duration=120)
+    @spaces.GPU(duration=120)
     def transcribe(self,
                    audio: Union[str, BinaryIO, np.ndarray],
                    progress: gr.Progress,
@@ -51,7 +51,7 @@ class WhisperBase(ABC):
         pass
 
     @abstractmethod
-    #@spaces.GPU(duration=120)
+    @spaces.GPU(duration=120)
     def update_model(self,
                      model_size: str,
                      compute_type: str,
@@ -59,7 +59,7 @@ class WhisperBase(ABC):
                      ):
         pass
 
-    #@spaces.GPU(duration=120)
+    @spaces.GPU(duration=120)
     def run(self,
             audio: Union[str, BinaryIO, np.ndarray],
             progress: gr.Progress,
@@ -196,7 +196,7 @@ class WhisperBase(ABC):
             if not files:
                 self.remove_input_files([file.name for file in files])
 
-    #@spaces.GPU(duration=120)
+    @spaces.GPU(duration=120)
     def transcribe_mic(self,
                        mic_audio: str,
                        file_format: str,
@@ -249,7 +249,7 @@ class WhisperBase(ABC):
             self.release_cuda_memory()
             self.remove_input_files([mic_audio])
 
-    #@spaces.GPU(duration=120)
+    @spaces.GPU(duration=120)
     def transcribe_youtube(self,
                            youtube_link: str,
                            file_format: str,
@@ -399,18 +399,18 @@ class WhisperBase(ABC):
 
         return time_str.strip()
 
-    @staticmethod
-    #@spaces.GPU(duration=120)
-    def get_device():
-        if torch.cuda.is_available():
-            return "cuda"
-        elif torch.backends.mps.is_available():
-            return "mps"
-        else:
-            return "cpu"
+    # @staticmethod
+    # @spaces.GPU(duration=120)
+    # def get_device():
+    #     if torch.cuda.is_available():
+    #         return "cuda"
+    #     elif torch.backends.mps.is_available():
+    #         return "mps"
+    #     else:
+    #         return "cpu"
 
     @staticmethod
-    #@spaces.GPU(duration=120)
+    @spaces.GPU(duration=120)
     def release_cuda_memory():
         if torch.cuda.is_available():
             torch.cuda.empty_cache()