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Stefy Lanza (nextime / spora ) authored
With the environment fixed, Parler got further: the venv built, the service started, the model loaded — and the first synthesis died in the DAC audio decoder's conv1d. RuntimeError: CUDNN_BACKEND_TENSOR_DESCRIPTOR cudnnFinalize failed ptrDesc->finalize() cudnn_status: CUDNN_STATUS_SUBLIBRARY_LOADING_FAILED Every cudnn sublibrary present in the venv, and the stack unable to load them: a torch 2.15 with the CUDA-13 wheels that `pip install git+…parler-tts` had resolved on its own, because nothing pinned it. requirements-parler.txt names the build now, the way every other isolated worker's file does. The health check was the deeper problem. `import parler_tts, soundfile` answered True for that venv for ever, so nothing ever rebuilt it. A venv's check has to exercise what the worker actually does: the decoder is convolutional, so the probe is one conv1d on the GPU, and a venv that imports but cannot run it is rebuilt from the pinned file. A CPU-only host passes — there is no GPU stack there to be broken. The service also latches cudnn off if it still fails there. torch has native kernels for those convolutions, the decoder is a fraction of the work, and the alternative is no speech at all. Co-Authored-By:Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014T3rZozi1Ehk96NG1WesgC
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| api | ||
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| models | ||
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| main.py | ||
| ocr_fleet_workers.py | ||
| platform_paths.py | ||
| system_app.py |