wehub-resource-sync
44 lines
1.8 KiB
Docker
44 lines
1.8 KiB
Docker
# Lightweight ROCm image: latest LMCache release on top of vLLM-ROCm.
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# No NIXL, no Prefill-Decode Disaggregation.
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# For AMD Instinct GPUs (MI300X/MI325X, MI350X/MI355X).
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#
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# Note: lmcache is built from source with HIP extensions using
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# --no-build-isolation to link against the ROCm torch in the base image.
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FROM vllm/vllm-openai-rocm:latest
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# ROCm GPU architectures — required during build (no GPU present)
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ARG PYTORCH_ROCM_ARCH="gfx942,gfx950"
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ENV PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}
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# Build LMCache from source with HIP extensions.
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# PyPI lmcache>=0.4 ships only binary wheels (no sdist), so `--no-binary`
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# cannot force a source build. Cloning the repo ensures HIP extensions
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# are compiled against the ROCm torch already present in the base image.
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# Build deps are installed from the cloned source to stay version-consistent.
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ARG max_jobs=2
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ENV MAX_JOBS=${max_jobs}
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ARG LMCACHE_VERSION=dev
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RUN git clone --depth 1 -b ${LMCACHE_VERSION} https://github.com/LMCache/LMCache.git /tmp/lmcache && \
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cd /tmp/lmcache && \
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uv pip install --system --no-cache -r requirements/build.txt && \
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BUILD_WITH_HIP=1 CXX=hipcc \
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uv pip install --system --no-cache --no-build-isolation . && \
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rm -rf /tmp/lmcache
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# Build (no repo context needed — everything is cloned from git):
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# docker build -f docker/Dockerfile.rocm-lightweight -t 'lmcache/vllm-openai-rocm:light' docker/
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# Run:
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# export HF_TOKEN=<your_huggingface_token>
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# docker run --device /dev/kfd --device /dev/dri --group-add video \
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# -v ~/.cache/huggingface:/root/.cache/huggingface \
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# --env "HF_TOKEN=$HF_TOKEN" \
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# -p 8000:8000 \
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# --ipc=host \
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# lmcache/vllm-openai-rocm:light \
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# --model Qwen/Qwen3-0.6B \
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# --kv-transfer-config \
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# '{"kv_connector":"LMCacheConnectorV1","kv_role":"kv_both"}'
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