fix spaces bug

modules/translation/nllb_inference.py

@@ -21,14 +21,14 @@ class NLLBInference(TranslationBase):
         self.available_target_langs = list(NLLB_AVAILABLE_LANGS.keys())
         self.pipeline = None
 
-    @spaces.GPU
+    @spaces.GPU(duration=120)
     def translate(self,
                   text: str
                   ):
         result = self.pipeline(text)
         return result[0]['translation_text']
 
-    @spaces.GPU
+    @spaces.GPU(duration=120)
     def update_model(self,
                      model_size: str,
                      src_lang: str,

modules/translation/translation_base.py

@@ -24,12 +24,14 @@ class TranslationBase(ABC):
         self.device = self.get_device()
 
     @abstractmethod
+    @spaces.GPU(duration=120)
     def translate(self,
                   text: str
                   ):
         pass
 
     @abstractmethod
+    @spaces.GPU(duration=120)
     def update_model(self,
                      model_size: str,
                      src_lang: str,
@@ -38,6 +40,7 @@ class TranslationBase(ABC):
                      ):
         pass
 
+    @spaces.GPU(duration=120)
     def translate_file(self,
                        fileobjs: list,
                        model_size: str,
@@ -128,7 +131,7 @@ class TranslationBase(ABC):
             self.remove_input_files([fileobj.name for fileobj in fileobjs])
 
     @staticmethod
-    @spaces.GPU
+    @spaces.GPU(duration=120)
     def get_device():
         if torch.cuda.is_available():
             return "cuda"
@@ -138,7 +141,7 @@ class TranslationBase(ABC):
             return "cpu"
 
     @staticmethod
-    @spaces.GPU
+    @spaces.GPU(duration=120)
     def release_cuda_memory():
         if torch.cuda.is_available():
             torch.cuda.empty_cache()

modules/whisper/faster_whisper_inference.py

@@ -31,7 +31,7 @@ class FasterWhisperInference(WhisperBase):
         self.available_models = self.model_paths.keys()
         self.available_compute_types = self.get_available_compute_type()
 
-    @spaces.GPU
+    @spaces.GPU(duration=120)
     def transcribe(self,
                    audio: Union[str, BinaryIO, np.ndarray],
                    progress: gr.Progress,
@@ -89,7 +89,7 @@ class FasterWhisperInference(WhisperBase):
         elapsed_time = time.time() - start_time
         return segments_result, elapsed_time
 
-    @spaces.GPU
+    @spaces.GPU(duration=120)
     def update_model(self,
                      model_size: str,
                      compute_type: str,
@@ -149,7 +149,7 @@ class FasterWhisperInference(WhisperBase):
         return ['int16', 'float32', 'int8', 'int8_float32']
 
     @staticmethod
-    @spaces.GPU
+    @spaces.GPU(duration=120)
     def get_device():
         if torch.cuda.is_available():
             return "cuda"

modules/whisper/whisper_base.py

@@ -42,7 +42,7 @@ class WhisperBase(ABC):
         self.vad = SileroVAD()
 
     @abstractmethod
-    @spaces.GPU
+    @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
+    @spaces.GPU(duration=120)
     def update_model(self,
                      model_size: str,
                      compute_type: str,
@@ -59,7 +59,7 @@ class WhisperBase(ABC):
                      ):
         pass
 
-    @spaces.GPU
+    @spaces.GPU(duration=120)
     def run(self,
             audio: Union[str, BinaryIO, np.ndarray],
             progress: gr.Progress,
@@ -125,7 +125,7 @@ class WhisperBase(ABC):
             elapsed_time += elapsed_time_diarization
         return result, elapsed_time
 
-    @spaces.GPU
+    @spaces.GPU(duration=120)
     def transcribe_file(self,
                         files: list,
                         file_format: str,
@@ -196,7 +196,7 @@ class WhisperBase(ABC):
             if not files:
                 self.remove_input_files([file.name for file in files])
 
-    @spaces.GPU
+    @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
+    @spaces.GPU(duration=120)
     def transcribe_youtube(self,
                            youtube_link: str,
                            file_format: str,
@@ -400,7 +400,7 @@ class WhisperBase(ABC):
         return time_str.strip()
 
     @staticmethod
-    @spaces.GPU
+    @spaces.GPU(duration=120)
     def get_device():
         if torch.cuda.is_available():
             return "cuda"
@@ -410,7 +410,7 @@ class WhisperBase(ABC):
             return "cpu"
 
     @staticmethod
-    @spaces.GPU
+    @spaces.GPU(duration=120)
     def release_cuda_memory():
         if torch.cuda.is_available():
             torch.cuda.empty_cache()