RuntimeError: parallel_for failed: cudaErrorNoKernelImageForDevice: no kernel image is available for execution on the device

Accelerated Computing CUDA CUDA Setup and Installation
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I have been trying to get whisperX to work on my GTX 970, but have been running into a myriad of problems. Please bear with me as I’m a beginner in all things programming.

To start, I have followed the github repo install instructions to the letter: GitHub - m-bain/whisperX: WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)

I then ran the following command:

whisperx.exe "C:\Users\Justin\Music\Kraft Punk Soundbites\WAV\Hey what's up_ I'm Kraft Punk.wav" --model large-v2 --device cuda --batch_size 1 --compute_type float32 --output_dir "C:\Users\Justin\Desktop\" --language en --diarize --min_speakers 1 --max_speakers 1 --hf_token XXXXXXXXXXXXXXXXX

I then ran into the following error:

[code]torchvision is not available - cannot save figures
Lightning automatically upgraded your loaded checkpoint from v1.5.4 to v2.2.3. To apply the upgrade to your files permanently, run python -m pytorch_lightning.utilities.upgrade_checkpoint C:\Users\Justin\.cache\torch\whisperx-vad-segmentation.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 2.0.0. Bad things might happen unless you revert torch to 1.x.

Performing transcription…
Traceback (most recent call last):
File “C:\Users\Justin\miniconda3\envs\whisperx\lib\runpy.py”, line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File “C:\Users\Justin\miniconda3\envs\whisperx\lib\runpy.py”, line 86, in run_code
exec(code, run_globals)
File "C:\Users\Justin\miniconda3\envs\whisperx\Scripts\whisperx.exe_main.py", line 7, in
File “C:\Users\Justin\miniconda3\envs\whisperx\lib\site-packages\whisperx\transcribe.py”, line 176, in cli
result = model.transcribe(audio, batch_size=batch_size, chunk_size=chunk_size, print_progress=print_progress)
File “C:\Users\Justin\miniconda3\envs\whisperx\lib\site-packages\whisperx\asr.py”, line 218, in transcribe
for idx, out in enumerate(self.call(data(audio, vad_segments), batch_size=batch_size, num_workers=num_workers)):
File “C:\Users\Justin\miniconda3\envs\whisperx\lib\site-packages\transformers\pipelines\pt_utils.py”, line 124, in next
item = next(self.iterator)
File “C:\Users\Justin\miniconda3\envs\whisperx\lib\site-packages\transformers\pipelines\pt_utils.py”, line 125, in next
processed = self.infer(item, **self.params)
File “C:\Users\Justin\miniconda3\envs\whisperx\lib\site-packages\transformers\pipelines\base.py”, line 1112, in forward
model_outputs = self._forward(model_inputs, **forward_params)
File “C:\Users\Justin\miniconda3\envs\whisperx\lib\site-packages\whisperx\asr.py”, line 152, in _forward
outputs = self.model.generate_segment_batched(model_inputs[‘inputs’], self.tokenizer, self.options)
File “C:\Users\Justin\miniconda3\envs\whisperx\lib\site-packages\whisperx\asr.py”, line 47, in generate_segment_batched
encoder_output = self.encode(features)
File “C:\Users\Justin\miniconda3\envs\whisperx\lib\site-packages\whisperx\asr.py”, line 86, in encode
return self.model.encode(features, to_cpu=to_cpu)
RuntimeError: parallel_for failed: cudaErrorNoKernelImageForDevice: no kernel image is available for execution on the device[/code]

I ran some basic diagnostic tests to ensure that CUDA was/is available:

[code]>>> import torch

import sys
print(‘A’, sys.version)
A 3.10.14 | packaged by Anaconda, Inc. | (main, Mar 21 2024, 16:20:14) [MSC v.1916 64 bit (AMD64)]
print(‘B’, torch.version)
B 2.3.0
print(‘C’, torch.cuda.is_available())
C True
print(‘D’, torch.backends.cudnn.enabled)
D True
device = torch.device(‘cuda’)
print(‘E’, torch.cuda.get_device_properties(device))
E _CudaDeviceProperties(name=‘NVIDIA GeForce GTX 970’, major=5, minor=2, total_memory=4095MB, multi_processor_count=13)
print(‘F’, torch.tensor([1.0, 2.0]).cuda())
F tensor([1., 2.], device=‘cuda:0’)[/code]

+-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 551.23 Driver Version: 551.23 CUDA Version: 12.4 | |-----------------------------------------+------------------------+----------------------+ | GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA GeForce GTX 970 WDDM | 00000000:01:00.0 On | N/A | | 47% 30C P2 50W / 250W | 980MiB / 4096MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+

I’m at a loss and really would appreciate some help! :)

2

One or more of the software stacks (perhaps the whisperx.exe executable) you are using have not been compiled to support a GTX 970. This isn’t a CUDA setup issue (which is what this forum is about) but rather a problem with the software stack.

3

Thanks Robert.

I will create an issue in the whisperX repo.