- Implemented core model components in `modules.py` including various convolutional layers and normalization techniques. - Added transformation functions in `transforms.py` for piecewise rational quadratic transformations. - Created utility functions in `utils.py` for checkpoint management, logging, and hyperparameter handling. - Introduced monotonic alignment functionality with Cython optimization in `monotonic_align`. - Developed a minimal inference server in `server.py` to handle synthesis requests. - Updated requirements to include necessary dependencies for Cython and scipy.
28 lines
1.0 KiB
Docker
28 lines
1.0 KiB
Docker
# Dev/smoke-test image for the tts-gateway inference sidecar (Phase 3/4 of
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# TTS_GATEWAY_PLAN.md). NOT the polished production image - Phase 5 (deferred)
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# covers the final containerization/CI/model-artifact-distribution decisions.
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# Base image matches nik-gpu's driver 570.211.01 / CUDA 12.8.
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FROM pytorch/pytorch:2.9.1-cuda12.8-cudnn9-runtime
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RUN apt-get update && apt-get install -y --no-install-recommends \
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build-essential \
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cmake \
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&& rm -rf /var/lib/apt/lists/*
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WORKDIR /app
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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COPY . .
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# models/models.py does a module-level `import monotonic_align`, even though
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# this sidecar's infer()-only path never calls it (only the training-time
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# forward() does) - the extension still has to build for the import itself to
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# succeed. See tmp/reference/uma-tts-api/spike/FINDINGS.md for the identical
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# issue hit during the Phase 0 spike.
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RUN cd monotonic_align && python setup.py build_ext --inplace
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EXPOSE 50054
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CMD ["python", "server.py"]
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