我们需要针对50系显卡的支持 #488
Description
我在5080显卡的电脑上尝试进行安装这个项目，但是始终会提示不支持cu128或者torch的版本，然后就会自动安装cu118的版本，即使我修改了install.py文件和st.py文件，替换了支持50系显卡的一些依赖也无法解决，下面是完整的安装和错误结果，安装完成后没有启动项目，直接关闭了服务：(videolingo) D:\video\VideoLingo>streamlit run st.py
You can now view your Streamlit app in your browser.
Local URL: http://localhost:8501
Network URL: http://192.168.3.218:8501
2025-07-29 12:08:42.191 Examining the path of torch.classes raised: Tried to instantiate class 'path.path', but it does not exist! Ensure that it is registered via torch::class
🎙️ Starting audio segmentation output/audio/raw.mp3 1800 60
E:\miniconda\envs\videolingo\lib\site-packages\pyannote\audio\core\io.py:43: UserWarning: torchaudio._backend.set_audio_backend has been deprecated. This deprecation is part of a large refactoring effort to transition TorchAudio into a maintenance phase. The decoding and encoding capabilities of PyTorch for both audio and video are being consolidated into TorchCodec. Please see pytorch/audio#3902 for more information. It will be removed from the 2.9 release.
torchaudio.set_audio_backend("soundfile")
E:\miniconda\envs\videolingo\lib\site-packages\torchaudio_internal\module_utils.py:71: UserWarning: torchaudio._backend.set_audio_backend has been deprecated. With dispatcher enabled, this function is no-op. You can remove the function call.
return func(*args, **kwargs)
E:\miniconda\envs\videolingo\lib\site-packages\pyannote\audio\pipelines\speaker_verification.py:43: UserWarning: torchaudio._backend.get_audio_backend has been deprecated. This deprecation is part of a large refactoring effort to transition TorchAudio into a maintenance phase. The decoding and encoding capabilities of PyTorch for both audio and video are being consolidated into TorchCodec. Please see pytorch/audio#3902 for more information. It will be removed from the 2.9 release.
backend = torchaudio.get_audio_backend()
E:\miniconda\envs\videolingo\lib\site-packages\torchaudio_internal\module_utils.py:71: UserWarning: torchaudio._backend.get_audio_backend has been deprecated. With dispatcher enabled, this function is no-op. You can remove the function call.
return func(*args, **kwargs)
E:\miniconda\envs\videolingo\lib\site-packages\speechbrain\utils\torch_audio_backend.py:57: UserWarning: torchaudio.backend.list_audio_backends has been deprecated. This deprecation is part of a large refactoring effort to transition TorchAudio into a maintenance phase. The decoding and encoding capabilities of PyTorch for both audio and video are being consolidated into TorchCodec. Please see pytorch/audio#3902 for more information. It will be removed from the 2.9 release.
available_backends = torchaudio.list_audio_backends()
E:\miniconda\envs\videolingo\lib\site-packages\torch\backends_init.py:46: UserWarning: This API is going to be deprecated, please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at C:\actions-runner_work\pytorch\pytorch\pytorch\aten\src\ATen\Context.cpp:81.)
self.setter(val)
E:\miniconda\envs\videolingo\lib\site-packages\pyannote\audio\pipelines\speaker_verification.py:45: UserWarning: Module 'speechbrain.pretrained' was deprecated, redirecting to 'speechbrain.inference'. Please update your script. This is a change from SpeechBrain 1.0. See: https://github.com/speechbrain/speechbrain/releases/tag/v1.0.0
from speechbrain.pretrained import (
E:\miniconda\envs\videolingo\lib\site-packages\pyannote\audio\pipelines\speaker_verification.py:53: UserWarning: torchaudio._backend.set_audio_backend has been deprecated. This deprecation is part of a large refactoring effort to transition TorchAudio into a maintenance phase. The decoding and encoding capabilities of PyTorch for both audio and video are being consolidated into TorchCodec. Please see pytorch/audio#3902 for more information. It will be removed from the 2.9 release.
torchaudio.set_audio_backend(backend)
E:\miniconda\envs\videolingo\lib\site-packages\pyannote\audio\tasks\segmentation\mixins.py:37: UserWarning: torchaudio.backend.common.AudioMetaData has been moved to torchaudio.AudioMetaData. Please update the import path.
from torchaudio.backend.common import AudioMetaData
🎤 Transcribing audio with local model...
🔍 Checking HuggingFace mirrors...
✓ HF-Mirror: 0.11s
✓ ModelScope: 0.03s
✗ Official: timeout
🚀 Selected mirror: https://modelscope.cn (0.03s)
🚀 Starting WhisperX using device: cuda ...
🎮 GPU memory: 15.92 GB, 📦 Batch size: 16, ⚙️ Compute type: float16
📥 Using WHISPER model from HuggingFace: large-v3 ...
You can ignore warning of Model was trained with torch 1.10.0+cu128...
Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: pip install huggingface_hub[hf_xet] or pip install hf_xet
model.bin: 100%|█████████████████████████████████████████████████████████████████▊| 3.09G/3.10G [03:04<00:00, 16.7MB/s]
Lightning automatically upgraded your loaded checkpoint from v1.5.4 to v2.5.2. To apply the upgrade to your files permanently, run python -m pytorch_lightning.utilities.upgrade_checkpoint E:\miniconda\envs\videolingo\lib\site-packages\whisperx\assets\pytorch_model.bin
Model was trained with pyannote.audio 0.0.1, yours is 3.1.1. Bad things might happen unless you revert pyannote.audio to 0.x.
Model was trained with torch 1.10.0+cu102, yours is 2.9.0. Bad things might happen unless you revert torch to 1.x.
Note: You will see Progress if working correctly ↓
Could not locate cudnn_ops_infer64_8.dll. Please make sure it is in your library path!
(videolingo) D:\video\VideoLingo>