tzhouamandClaude Opus 4.8
b5c6a30d4e
Three regressions surfaced only on dev/vllm-align in Buildkite build 2520 (26 failing jobs vs 5 on main); ~15 of the 19 align-unique failures trace to these: 1. numpy 2.5 vs numba: Dockerfile.ci pinned numpy==2.2.6 before the flashinfer and torch cu130 reinstalls, which resolved numpy back to 2.5 and broke 'import numba' (needs numpy <= 2.4). Re-pin numpy as the final dependency op. 2. libnvJitLink.so.13 not found: the CUDA-13 JIT linker lives in the nvidia-cuda-nvjitlink-cu13 wheel, not /usr/local/cuda (CUDA 12) as the old LD_LIBRARY_PATH assumed; bitsandbytes/torch.compile subprocesses could not dlopen it (broke Entrypoint L4, a multi-GPU diffusion job, both Quantization jobs via hang/timeout). Install the wheel and register its lib dir via ldconfig. 3. transformers >= 5.5 AutoProcessor.register now requires the config class, not a model_type string; processing_gr00t_n1d7.py passed "Gr00tN1d7" -> AttributeError 'str' object has no attribute '__module__' -> pytest collection errors (exit 2). Pass Gr00tN1d7Config, matching AutoModel.register in modeling/gr00t_n1d7.py. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
80 lines
3.7 KiB
Docker
80 lines
3.7 KiB
Docker
# Target vllm version: v0.24.0 (releases/v0.24.0 branch).
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# The pinned VLLM_PRECOMPILED_WHEEL_COMMIT and VLLM_BASE_TAG below must
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# be updated on every rebase to match the new upstream vllm commit/tag.
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ARG VLLM_BASE_IMAGE=vllm/vllm-openai
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ARG VLLM_BASE_TAG=v0.24.0
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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 ${APP_DIR}
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COPY . .
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# Install system dependencies
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RUN apt-get update && \
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apt-get install -y espeak-ng git jq && \
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apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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# Install vLLM (CUDA 13.0 build) from precompiled wheel at the selected commit.
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# Must use direct URL because the wheel has a PEP 440 local version identifier
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# (e.g. +gaeee7ef93.cu130) which pip/uv refuse to install from a PEP 503 package index.
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# The cu130 wheel index lives at /<commit>/cu130/vllm/ but the actual wheel files
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# are stored at the top level /<commit>/<wheel>.
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ENV VLLM_PRECOMPILED_WHEEL_COMMIT=2dfaae752b4db0d43cfc0715c780e33be030d0f1
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# Keep the base image's CUDA-12 toolkit libs on the loader path. NOTE: this does
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# NOT resolve libnvJitLink.so.13 (that CUDA-13 lib is not in /usr/local/cuda here) —
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# the .so.13 JIT linker is handled separately via ldconfig after the cu130 wheels
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# are installed (see the nvidia-cuda-nvjitlink-cu13 step below).
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ENV LD_LIBRARY_PATH=/usr/local/cuda/targets/x86_64-linux/lib:${LD_LIBRARY_PATH}
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RUN VLLM_WHEEL_URL=$(python3 -c "import urllib.request,re; \
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from urllib.parse import urljoin, quote; \
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index_url='https://wheels.vllm.ai/${VLLM_PRECOMPILED_WHEEL_COMMIT}/cu130/vllm/'; \
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html=urllib.request.urlopen(index_url).read().decode(); \
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m=re.search(r'href=\"([^\"]*x86_64\.whl)\"',html); \
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assert m, f'No x86_64 vLLM wheel found at {index_url}'; \
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print(quote(urljoin(index_url,m.group(1)), safe=':/+%'))") && \
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echo "Installing vLLM from: ${VLLM_WHEEL_URL}" && \
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uv pip install --system --force-reinstall "${VLLM_WHEEL_URL}"
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RUN uv pip install --system ".[dev]"
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RUN uv pip install --system --upgrade \
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"flashinfer-python==0.6.13" \
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"flashinfer-cubin==0.6.13"
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RUN uv pip install --system --upgrade \
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"flashinfer-jit-cache==0.6.13" \
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--index-url https://flashinfer.ai/whl/cu130
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# Force-reinstall torch AFTER flashinfer, because flashinfer --upgrade pulls in
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# a newer torch (2.12.x) whose libtorch_cuda.so lacks
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# at::cuda::getCurrentCUDABlasHandle, causing "undefined symbol" at import time.
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RUN uv pip install --system --force-reinstall \
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"torch==2.11.0" "torchaudio==2.11.0" "torchvision==0.26.0" \
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--torch-backend cu130
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# CUDA 13 JIT linker: libnvJitLink.so.13 ships only in the nvidia-cuda-nvjitlink-cu13
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# pip wheel (the v0.24.0 base image's /usr/local/cuda toolkit is CUDA 12, so the
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# LD_LIBRARY_PATH above never resolves the .so.13). The cu130 torch/vllm wheels pull
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# this package into site-packages, but its lib dir is not on the dynamic-loader path,
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# so bitsandbytes / torch.compile worker subprocesses fail to dlopen it. Register the
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# actual lib dir with ldconfig (system-wide, survives subprocess env resets).
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RUN uv pip install --system "nvidia-cuda-nvjitlink-cu13" && \
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NVJITLINK_LIB="$(find / -name 'libnvJitLink.so.13*' 2>/dev/null | head -1)" && \
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test -n "$NVJITLINK_LIB" && \
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dirname "$NVJITLINK_LIB" > /etc/ld.so.conf.d/nvjitlink-cu13.conf && \
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ldconfig && \
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echo "Registered ${NVJITLINK_LIB} with ldconfig"
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# Re-pin numpy LAST. numba requires numpy <= 2.4, but the flashinfer and torch cu130
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# reinstalls above resolve numpy back up to 2.5, which breaks `import numba` at test
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# time ("Numba needs NumPy 2.4 or less"). This must be the final dependency op so
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# nothing can clobber it again.
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RUN uv pip install --system "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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