Cleanup commented code

models/whisper.py

@@ -20,39 +20,4 @@ def get_prediction_with_timelines(pipe, sample):
     return pipe(sample, batch_size=8, return_timestamps=True)["chunks"]
 
 def get_prediction(pipe, sample):
-    return pipe(sample, batch_size=8)["text"]
-
-
-# audio_file = open("movie.mp3", "rb")
-# sample = audio_file.read()
-# prediction = pipe(sample, batch_size=8, return_timestamps=True)["chunks"]
-
-
-# def main():
-#     print("# Extracting audio from video")
-#     # audio = get_audio_from_video("movie.mp4", "movie.mp3")
-#     print("# Splitting audio into chunks")
-#     split_audio("movie.mp3", "movie_parts", 30)
-#     print("# Gettin Device")
-#     device = get_device()
-#     print("# Getting Pipeline")
-#     pipe = get_pipe(device)
-#     print("# Getting Predictions")
-#     for file in os.listdir("movie_parts"):
-#         print(f"Processing {file}")
-#         audio_file = open(os.path.join("movie_parts", file), "rb")
-#         sample = audio_file.read()
-#         print(f"# Getting Prediction for file {file}")
-#         prediction = get_prediction(pipe, sample)
-#         print(f"# Saving Subtitles for file {file}")
-#         save_subtitles(prediction, file.replace(".mp3", ".srt"))
-#     # Aggregating subtitles into one file
-#     print("# Aggregating subtitles into one file")
-#     with open("movie.srt", "w") as f:
-#         for file in os.listdir("movie_parts"):
-#             with open(os.path.join("movie_parts", file), "r") as f2:
-#                 f.write(f2.read())
-#     print("# Done")
-
-# if __name__ == "__main__":
-#     main()
+    return pipe(sample, batch_size=8)["text"]