Issue with GPU Utilization in OfflineSpeakerDiarization (CUDA) #2054

Sanich137 · 2025-03-25T14:57:33Z

Sanich137
Mar 25, 2025

Hello!

I’m using your OfflineSpeakerDiarization tool with CUDA and encountered an issue: GPU usage drops significantly during audio processing. Could you please help me investigate this?

Environment:

CUDA 12.6, sherpa-onnx 1.11.2+cuda

Models:

pyannote-segmentation-3.0 (source: [link])

wespeaker_en_voxceleb_resnet34_LM.onnx (source: [link])

OfflineSpeakerDiarizationConfig parameters: provider="cuda", num_threads=2

Code:

diarization_model_config = sherpa_onnx.OfflineSpeakerDiarizationConfig(
    segmentation=sherpa_onnx.OfflineSpeakerSegmentationModelConfig(
        pyannote=sherpa_onnx.OfflineSpeakerSegmentationPyannoteModelConfig(
            model=segmentation_model,
        ),
        provider="cuda",
        num_threads=2,
        debug=False
    ),
    # ... other parameters
)
...
show_progress = True
if show_progress:
    sd_results = model.process(audio_array, callback=progress_callback).sort_by_start_time()
else:
    sd_results = model.process(audio_array).sort_by_start_time()

Problem:
When calling model.process(audio_array), GPU usage drops from ~90% to 0%, though GPU memory remains occupied. No errors are logged, but processing becomes noticeably slow:

A 180.0-second audio file with 3 speakers takes 48 seconds with ...resnet34_LM.onnx.

The same file takes 92.9 seconds with wespeaker_en_voxceleb_resnet152_LM.onnx.

Questions:

Is specifying provider="cuda" sufficient and correct for GPU utilization?

Are there any known limitations for CUDA support in speaker diarization?

Which parameters can be adjusted to optimize GPU usage?

Thank you in advance for your help!

csukuangfj · 2025-03-25T14:59:28Z

csukuangfj
Mar 25, 2025
Maintainer

CUDA 12.6, sherpa-onnx 1.11.2+cuda

in general, it requires cuda 11.8

Can you show complete logs?

1 reply

Sanich137 Mar 25, 2025
Author

Yes:

Logs

Using 'DEBUG' LOGGING_LEVEL
#DEBUG logging_utils.py [LINE:9] [2025-03-25 18:06:03,411] subprocess.call(['ffmpeg', '-y', '-i', 'C:\Users\kojevnikov\PycharmProjects\Vosk5_FastAPI_streaming\trash//long.mp3', '-acodec', 'pcm_s16le', '-vn', '-f', 'wav', '-'])
#DEBUG diarize.py [LINE:70] [2025-03-25 18:06:04,047] Get in work audio 180.0 sec.
#DEBUG proactor_events.py [LINE:633] [2025-03-25 18:06:04,047] Using proactor: IocpProactor
D:\a\sherpa-onnx\sherpa-onnx\sherpa-onnx\csrc\offline-speaker-segmentation-pyannote-model.cc:Init:76 onnx.quant.pre_process=onnxruntime.quant
sample_rate=16000
num_speakers=3
num_classes=7
powerset_max_classes=2
receptive_field_size=991
window_size=160000
receptive_field_shift=270
model_type=pyannote-segmentation-3.0
version=1
model_author=pyannote
maintainer=k2-fsa
url_1=https://huggingface.co/pyannote/segmentation-3.0
url_2=https://huggingface.co/csukuangfj/pyannote-models/tree/main/segmentation-3.0
license=https://huggingface.co/pyannote/segmentation-3.0/blob/main/LICENSE

#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:12,414] Diarization_progress: 0.415%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:12,631] Diarization_progress: 0.830%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:12,869] Diarization_progress: 1.245%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:13,077] Diarization_progress: 1.660%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:13,278] Diarization_progress: 2.075%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:13,459] Diarization_progress: 2.490%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:13,611] Diarization_progress: 2.905%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:13,727] Diarization_progress: 3.320%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:13,841] Diarization_progress: 3.734%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:13,927] Diarization_progress: 4.149%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:13,982] Diarization_progress: 4.564%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:14,009] Diarization_progress: 4.979%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:14,024] Diarization_progress: 5.394%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:14,065] Diarization_progress: 5.809%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:14,074] Diarization_progress: 6.224%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:14,131] Diarization_progress: 6.639%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:14,189] Diarization_progress: 7.054%
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#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:30,321] Diarization_progress: 77.593%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:30,422] Diarization_progress: 78.008%
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#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:31,433] Diarization_progress: 82.158%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:31,557] Diarization_progress: 82.573%
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#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:31,656] Diarization_progress: 83.402%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:31,798] Diarization_progress: 83.817%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:31,845] Diarization_progress: 84.232%
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#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:32,052] Diarization_progress: 85.062%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:32,234] Diarization_progress: 85.477%
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#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:35,028] Diarization_progress: 95.021%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:35,211] Diarization_progress: 95.436%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:35,269] Diarization_progress: 95.851%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:35,427] Diarization_progress: 96.266%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:35,456] Diarization_progress: 96.680%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:35,613] Diarization_progress: 97.095%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:35,797] Diarization_progress: 97.510%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:35,997] Diarization_progress: 97.925%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:36,188] Diarization_progress: 98.340%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:36,379] Diarization_progress: 98.755%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:36,570] Diarization_progress: 99.170%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:36,743] Diarization_progress: 99.585%
#DEBUG diarize.py [LINE:13] [2025-03-25 18:06:36,916] Diarization_progress: 100.000%
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,918] 2.326 -- 3.153 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 3.625 -- 7.220 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 7.895 -- 11.827 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 20.534 -- 22.559 speaker_01
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 33.646 -- 36.278 speaker_01
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 38.438 -- 39.923 speaker_01
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 42.151 -- 46.133 speaker_01
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 54.942 -- 59.482 speaker_01
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 61.253 -- 63.937 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 90.346 -- 94.767 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 97.045 -- 97.535 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 98.024 -- 98.362 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 100.775 -- 102.935 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 103.492 -- 104.926 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,919] 104.926 -- 105.652 speaker_02
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 106.175 -- 108.740 speaker_02
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 109.634 -- 112.891 speaker_02
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 114.308 -- 117.599 speaker_02
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 118.072 -- 119.624 speaker_02
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 122.341 -- 130.525 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 131.217 -- 134.710 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 134.153 -- 134.930 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 135.706 -- 138.575 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 138.170 -- 138.423 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 139.013 -- 139.283 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 139.503 -- 142.388 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 143.300 -- 144.582 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 145.038 -- 146.118 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 146.658 -- 147.130 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 147.620 -- 148.666 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 149.442 -- 152.547 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 152.024 -- 155.551 speaker_02
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,920] 153.577 -- 155.028 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,921] 155.838 -- 161.963 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,921] 161.812 -- 164.123 speaker_00
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,921] 163.887 -- 164.461 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,921] 164.950 -- 170.013 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,921] 173.101 -- 178.417 speaker_03
#DEBUG diarize.py [LINE:54] [2025-03-25 18:06:36,921] 178.838 -- 179.969 speaker_03
#DEBUG diarize.py [LINE:73] [2025-03-25 18:06:36,936] Spended 33.539054 sec.

Process finished with exit code 0

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Issue with GPU Utilization in OfflineSpeakerDiarization (CUDA) #2054

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Issue with GPU Utilization in OfflineSpeakerDiarization (CUDA) #2054

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Sanich137 Mar 25, 2025

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csukuangfj Mar 25, 2025 Maintainer

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Sanich137 Mar 25, 2025 Author

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Mar 25, 2025

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