requirements_transcription.txt

@@ -1,8 +1,5 @@
-pyaml
-librosa
 openai-whisper
 #https://pytorch.org/get-started/locally/
---extra-index-url https://download.pytorch.org/whl/cu128
+torch==2.5.1
-torch
+torchvision==0.20.1
-torchvision
+torchaudio==2.5.1 --index-url https://download.pytorch.org/whl/cu124
-torchaudio

transcribe_all.py

@@ -19,23 +19,6 @@ with open("transcription_config.yml", "r", encoding="utf-8") as file:
     settings = yaml.safe_load(file)
     folder_list = settings.get("folder_list")
     model_name = settings.get("model_name")
-    gpu_only = settings.get("gpu_only", False)
-
-print("PyTorch version:", torch.__version__)
-print("CUDA available?", torch.cuda.is_available())
-print("CUDA version:", torch.version.cuda)
-print("GPU count:", torch.cuda.device_count())
-if torch.cuda.is_available():
-    for i in range(torch.cuda.device_count()):
-        print(f"  Device {i}:", torch.cuda.get_device_name(i))
-
-if not folder_list or not model_name:
-    print("Error: Please check the transcription_config.yml file. It should contain 'folder_list' and 'model_name'.")
-    sys.exit(1)
-
-if gpu_only and not torch.cuda.is_available():
-    print("Error: You requested to only use GPU but it is not available. Please check your PyTorch installation.")
-    sys.exit(1)
 
 def load_audio_librosa(path: str, sr: int = 16_000) -> np.ndarray:
     audio, orig_sr = librosa.load(path, sr=sr)      # load + resample to 16 kHz