tzhouam
861698f88f
- Updated Dockerfile to use a new vllm wheel version. - Modified test_put_get_inline to clarify that it always uses SHM and updated metadata assertions. - Added handling for speculative configuration in GPU model runners to delay clearing connector metadata. - Refactored payload decoding in OmniGPUModelRunner for better clarity and maintainability. Signed-off-by: tzhouam <tzhouam@connect.ust.hk>
46 lines
2.1 KiB
Docker
46 lines
2.1 KiB
Docker
ARG VLLM_BASE_IMAGE=vllm/vllm-openai
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ARG VLLM_BASE_TAG=v0.15.0
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FROM ${VLLM_BASE_IMAGE}:${VLLM_BASE_TAG}
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ARG APP_DIR=/workspace/vllm-omni
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WORKDIR ${APP_DIR}
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COPY . .
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# Install system dependencies
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RUN apt-get update && \
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apt-get install -y ffmpeg sox libsox-fmt-all && \
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apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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# Install vLLM wheel for the specific commit
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# URL format: https://wheels.vllm.ai/<commit_hash>/
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# Current vLLM wheel commit: 16f24e87975ef4cd2c12879425062913ef62f6fd
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# Note: --prerelease=allow is required because nightly/commit wheels use
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# pre-release version numbers (e.g. 2.10.0.dev...) which uv ignores by default,
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# causing it to fall back to the older stable release from PyPI.
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RUN uv pip install --system --upgrade --force-reinstall --prerelease=allow vllm --extra-index-url https://wheels.vllm.ai/ec85340531e83962877fa683e23f1d5d17cd786a
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RUN uv pip uninstall --system nvidia-cublas-cu12
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# Install vllm-omni into the same uv-managed Python environment used by the base image.
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# Use bash -c so that $(python3 -c ...) is expanded inside the container.
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RUN uv pip install --system --no-cache-dir ".[dev]"
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# pplx_kernels is optional; the base image may already ship a version.
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# Reinstall attempt may fail if no compatible wheel exists for the current
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# PyTorch/CUDA combination – allow the build to continue regardless.
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RUN pip install --upgrade --force-reinstall "pplx_kernels" || true
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RUN /bin/bash -c 'FLASHINFER_CUDA_TAG="$(python3 -c "import torch; print((torch.version.cuda or \"12.4\").replace(\".\", \"\"))")" && \
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uv pip install --system --upgrade --force-reinstall \
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"flashinfer-python==0.6.3" \
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"flashinfer-cubin==0.6.3" \
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"flashinfer-jit-cache==0.6.3" \
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--extra-index-url "https://flashinfer.ai/whl/cu${FLASHINFER_CUDA_TAG}"'
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# Pin nvidia-cublas-cu12 after vllm-omni install so dependency resolution does not overwrite it
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RUN uv pip install --system --upgrade --force-reinstall "nvidia-cublas-cu12==12.9.1.4"
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RUN uv pip install --system --upgrade --force-reinstall "numpy==2.2.6"
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RUN ln -sf /usr/bin/python3 /usr/bin/python
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ENTRYPOINT []
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