software-engineering/spark-vllm-docker
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Merge remote-tracking branch 'upstream/main'

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# Conflicts:
#	Dockerfile
This commit is contained in:
Drew Botwinick
2026-03-24 15:41:09 -05:00
parent d6e76f8e2f 9e089acf2b
commit 8298c3d7f8
3 changed files with 29 additions and 46 deletions
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@@ -4,9 +4,9 @@
ARG BUILD_JOBS=16
# =========================================================
# STAGE 1: Base Image (Installs Dependencies)
# STAGE 1: Base Build Image
# =========================================================
FROM nvcr.io/nvidia/pytorch:26.01-py3 AS base
FROM nvidia/cuda:13.2.0-devel-ubuntu24.04 AS base
# Build parallemism
ARG BUILD_JOBS
@@ -35,10 +35,18 @@ ENV VLLM_BASE_DIR=/workspace/vllm
# Added ccache to enable incremental compilation caching
RUN apt update && \
apt install -y --no-install-recommends \
curl vim ninja-build git \
curl vim cmake build-essential ninja-build \
libcudnn9-cuda-13 libcudnn9-dev-cuda-13 \
python3-dev python3-pip git wget \
libnccl-dev libnccl2 libibverbs1 libibverbs-dev rdma-core \
ccache \
&& rm -rf /var/lib/apt/lists/* \
&& pip install uv && pip uninstall -y flash-attn
&& pip install uv
# Additional deps
RUN --mount=type=cache,id=uv-cache,target=/root/.cache/uv \
uv pip install torch torchvision torchaudio triton --index-url https://download.pytorch.org/whl/nightly/cu130 && \
uv pip install nvidia-nvshmem-cu13 "apache-tvm-ffi<0.2" filelock pynvml requests tqdm
# Configure Ccache for CUDA/C++
ENV PATH=/usr/lib/ccache:$PATH
@@ -73,9 +81,6 @@ ARG FLASHINFER_REF=main
# Change this argument to force a re-download of FlashInfer
ARG CACHEBUST_FLASHINFER=1
RUN --mount=type=cache,id=uv-cache,target=/root/.cache/uv \
uv pip install nvidia-nvshmem-cu13 "apache-tvm-ffi<0.2"
# Smart Git Clone (Fetch changes instead of full re-clone)
RUN --mount=type=cache,id=repo-cache,target=/repo-cache \
cd /repo-cache && \
@@ -132,9 +137,6 @@ ARG TORCH_CUDA_ARCH_LIST="12.1a"
ENV TORCH_CUDA_ARCH_LIST=${TORCH_CUDA_ARCH_LIST}
WORKDIR $VLLM_BASE_DIR
RUN --mount=type=cache,id=uv-cache,target=/root/.cache/uv \
uv pip install nvidia-nvshmem-cu13 "apache-tvm-ffi<0.2"
# --- VLLM SOURCE CACHE BUSTER ---
ARG CACHEBUST_VLLM=1
@@ -211,7 +213,7 @@ COPY --from=vllm-builder /workspace/wheels /
# =========================================================
# STAGE 6: Runner (Installs wheels from host ./wheels/)
# =========================================================
FROM nvcr.io/nvidia/pytorch:26.01-py3 AS runner
FROM nvidia/cuda:13.2.0-devel-ubuntu24.04 AS runner
# Transferring build settings from build image because of ptxas/jit compilation during vLLM startup
# Build parallemism
@@ -235,10 +237,12 @@ ENV UV_LINK_MODE=copy
# Install runtime dependencies
RUN apt update && \
apt install -y --no-install-recommends \
curl vim git \
python3 python3-pip python3-dev vim curl git wget \
libcudnn9-cuda-13 \
libnccl-dev libnccl2 libibverbs1 libibverbs-dev rdma-core \
libxcb1 \
&& rm -rf /var/lib/apt/lists/* \
&& pip install uv && pip uninstall -y flash-attn # triton-kernels pytorch-triton
&& pip install uv
# Set final working directory
WORKDIR $VLLM_BASE_DIR
@@ -250,6 +254,11 @@ RUN mkdir -p tiktoken_encodings && \
ARG PRE_TRANSFORMERS=0
# Install deps
RUN --mount=type=cache,id=uv-cache,target=/root/.cache/uv \
uv pip install torch torchvision torchaudio triton --index-url https://download.pytorch.org/whl/nightly/cu130 && \
uv pip install nvidia-nvshmem-cu13 "apache-tvm-ffi<0.2"
# Install wheels from host ./wheels/ (bind-mounted from build context — no layer bloat)
# With --tf5: override vLLM's transformers<5 constraint to get transformers>=5
RUN --mount=type=bind,source=wheels,target=/workspace/wheels \
@@ -273,24 +282,7 @@ ENV PATH=$VLLM_BASE_DIR:$PATH
# Final extra deps
RUN --mount=type=cache,id=uv-cache,target=/root/.cache/uv \
uv pip install ray[default] fastsafetensors nvidia-nvshmem-cu13
uv pip install ray[default] fastsafetensors
# Build metadata (generated by build-and-copy.sh)
COPY build-metadata.yaml /workspace/build-metadata.yaml
# Cleanup
# Keeping it here for reference - this won't work as is without squashing layers
# RUN uv pip uninstall absl-py apex argon2-cffi \
# argon2-cffi-bindings arrow asttokens astunparse async-lru audioread babel beautifulsoup4 \
# black bleach comm contourpy cycler datasets debugpy decorator defusedxml dllist dm-tree \
# execnet executing expecttest fastjsonschema fonttools fqdn gast hypothesis \
# ipykernel ipython ipython_pygments_lexers isoduration isort jedi joblib jupyter-events \
# jupyter-lsp jupyter_client jupyter_core jupyter_server jupyter_server_terminals jupyterlab \
# jupyterlab_code_formatter jupyterlab_code_formatter jupyterlab_pygments jupyterlab_server \
# jupyterlab_tensorboard_pro jupytext kiwisolver matplotlib matplotlib-inline matplotlib-inline \
# mistune ml_dtypes mock nbclient nbconvert nbformat nest-asyncio notebook notebook_shim \
# opt_einsum optree outlines_core overrides pandas pandocfilters parso pexpect polygraphy pooch \
# pyarrow pycocotools pytest-flakefinder pytest-rerunfailures pytest-shard pytest-xdist \
# scikit-learn scipy Send2Trash soundfile soupsieve soxr spin stack-data \
# wcwidth webcolors xdoctest Werkzeug
COPY build-metadata.yaml /workspace/build-metadata.yaml