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Long-form audio speaker diarization OOM in clustering #7912
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Thanks for raising this issue, could you please attach full log here. |
Attached the log from running NeuralDiarizer. |
I'm also having this issue, hangs at this step, similar settings as op. Versions: Nemo 1.21.0, python 3.10
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@remenberl |
This worked for me after building from source, and setting num_workers to 0 |
This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days. |
This issue was closed because it has been inactive for 7 days since being marked as stale. |
Hi,
Thanks for the recent development of long-form audio speaker diarization in #7737. Recently I encounter a 4-hour-long audio and observe OOM on RAM (not VRAM).
Steps/Code to reproduce bug
It can be reproduced by using audio https://podwise-hh.s3.us-west-1.amazonaws.com/0ef8d4f5beb504fae9f12272a83db030ab29c92f4e033eb86bfefe3d1668c7cf.m4a
My telephonic config file is just the default, with the clustering/msdd part pasted below:
Expected behavior
The job stops after my screen prints the last iteration of "Extracting embeddings for Diarization" and the program quickly consumes close to 64GB memory from 20GB- in previous steps. FYI, here are the last lines of prints before being killed.
Environment overview (please complete the following information)
python -m pip install git+https://github.com/NVIDIA/NeMo.git@main#egg=nemo_toolkit[asr]
docker pull
&docker run
commands usedEnvironment details
If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:
Additional context
Add any other context about the problem here.
Example: GPU model
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