bhetherman
44a10667c2
- Added environment variables to prevent CPU thread pools from busy-waiting. - Deferred loading of video models until first use to reduce VRAM footprint. - Implemented streaming of speaking clips for improved responsiveness. - Introduced a queue for managing speaking clips to handle multiple requests smoothly. - Updated video playback logic to ensure proper handling of clip generation.
21 lines
578 B
Python
21 lines
578 B
Python
import os
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import torch
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import uvicorn
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# Cap CPU thread pools so PyTorch/OpenMP don't spin-wait on every core at idle.
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# Models run on GPU; the CPU thread pool is only needed for small ops.
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os.environ.setdefault("OMP_WAIT_POLICY", "PASSIVE")
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os.environ.setdefault("MKL_WAIT_POLICY", "PASSIVE")
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os.environ.setdefault("TOKENIZERS_PARALLELISM", "false")
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torch.set_num_threads(2)
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torch.set_num_interop_threads(2)
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if __name__ == "__main__":
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uvicorn.run(
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"server.main:app",
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host="0.0.0.0",
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port=8000,
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reload=False,
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log_level="info",
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)
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