rename function

app.py

@@ -149,7 +149,7 @@ class App:
                                                        hf_token=tb_hf_token)
 
                     btn_run.click(fn=self.whisper_inf.transcribe_file,
-                                  inputs=params + whisper_params.to_list(),
+                                  inputs=params + whisper_params.as_list(),
                                   outputs=[tb_indicator, files_subtitles])
                     btn_openfolder.click(fn=lambda: self.open_folder("outputs"), inputs=None, outputs=None)
                     dd_model.change(fn=self.on_change_models, inputs=[dd_model], outputs=[cb_translate])
@@ -231,7 +231,7 @@ class App:
                                                        hf_token=tb_hf_token)
 
                     btn_run.click(fn=self.whisper_inf.transcribe_youtube,
-                                  inputs=params + whisper_params.to_list(),
+                                  inputs=params + whisper_params.as_list(),
                                   outputs=[tb_indicator, files_subtitles])
                     tb_youtubelink.change(get_ytmetas, inputs=[tb_youtubelink],
                                           outputs=[img_thumbnail, tb_title, tb_description])
@@ -305,7 +305,7 @@ class App:
                                                        hf_token=tb_hf_token)
 
                     btn_run.click(fn=self.whisper_inf.transcribe_mic,
-                                  inputs=params + whisper_params.to_list(),
+                                  inputs=params + whisper_params.as_list(),
                                   outputs=[tb_indicator, files_subtitles])
                     btn_openfolder.click(fn=lambda: self.open_folder("outputs"), inputs=None, outputs=None)
                     dd_model.change(fn=self.on_change_models, inputs=[dd_model], outputs=[cb_translate])

modules/faster_whisper_inference.py

@@ -52,7 +52,7 @@ class FasterWhisperInference(WhisperBase):
         """
         start_time = time.time()
 
-        params = WhisperParameters.post_process(*whisper_params)
+        params = WhisperParameters.as_value(*whisper_params)
 
         if params.model_size != self.current_model_size or self.model is None or self.current_compute_type != params.compute_type:
             self.update_model(params.model_size, params.compute_type, progress)

modules/insanely_fast_whisper_inference.py

@@ -53,7 +53,7 @@ class InsanelyFastWhisperInference(WhisperBase):
             elapsed time for transcription
         """
         start_time = time.time()
-        params = WhisperParameters.post_process(*whisper_params)
+        params = WhisperParameters.as_value(*whisper_params)
 
         if params.model_size != self.current_model_size or self.model is None or self.current_compute_type != params.compute_type:
             self.update_model(params.model_size, params.compute_type, progress)

modules/whisper_Inference.py

@@ -45,7 +45,7 @@ class WhisperInference(WhisperBase):
             elapsed time for transcription
         """
         start_time = time.time()
-        params = WhisperParameters.post_process(*whisper_params)
+        params = WhisperParameters.as_value(*whisper_params)
 
         if params.model_size != self.current_model_size or self.model is None or self.current_compute_type != params.compute_type:
             self.update_model(params.model_size, params.compute_type, progress)

modules/whisper_parameter.py

@@ -133,7 +133,7 @@ class WhisperParameters:
         Read more about : https://huggingface.co/pyannote/speaker-diarization-3.1#requirements
     """
 
-    def to_list(self) -> list:
+    def as_list(self) -> list:
         """
         Converts the data class attributes into a list, Use in Gradio UI before Gradio pre-processing.
         See more about Gradio pre-processing: : https://www.gradio.app/docs/components
@@ -145,7 +145,7 @@ class WhisperParameters:
         return [getattr(self, f.name) for f in fields(self)]
 
     @staticmethod
-    def post_process(*args) -> 'WhisperValues':
+    def as_value(*args) -> 'WhisperValues':
         """
         To use Whisper parameters in function after Gradio post-processing.
         See more about Gradio post-processing: : https://www.gradio.app/docs/components