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[CI/Build] Use uv in the Dockerfile (#13566)

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Michael Goin 2025-02-20 02:05:44 -05:00 committed by GitHub
parent 3738e6fa80
commit 497bc83124
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1 changed files with 19 additions and 13 deletions
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@ -27,6 +27,9 @@ RUN echo 'tzdata tzdata/Areas select America' | debconf-set-selections \
&& ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
&& curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION} \
&& python3 --version && python3 -m pip --version
# Install uv for faster pip installs
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install uv
# Upgrade to GCC 10 to avoid https://gcc.gnu.org/bugzilla/show_bug.cgi?id=92519
# as it was causing spam when compiling the CUTLASS kernels
@ -52,13 +55,13 @@ WORKDIR /workspace
# after this step
RUN --mount=type=cache,target=/root/.cache/pip \
if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
python3 -m pip install --index-url https://download.pytorch.org/whl/nightly/cu126 "torch==2.7.0.dev20250121+cu126" "torchvision==0.22.0.dev20250121"; \
uv pip install --system --index-url https://download.pytorch.org/whl/nightly/cu126 "torch==2.7.0.dev20250121+cu126" "torchvision==0.22.0.dev20250121"; \
fi
COPY requirements-common.txt requirements-common.txt
COPY requirements-cuda.txt requirements-cuda.txt
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install -r requirements-cuda.txt
uv pip install --system -r requirements-cuda.txt
# cuda arch list used by torch
# can be useful for both `dev` and `test`
@ -79,7 +82,7 @@ ARG TARGETPLATFORM
COPY requirements-build.txt requirements-build.txt
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install -r requirements-build.txt
uv pip install --system -r requirements-build.txt
COPY . .
ARG GIT_REPO_CHECK=0
@ -144,7 +147,7 @@ COPY requirements-lint.txt requirements-lint.txt
COPY requirements-test.txt requirements-test.txt
COPY requirements-dev.txt requirements-dev.txt
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install -r requirements-dev.txt
uv pip install --system -r requirements-dev.txt
#################### DEV IMAGE ####################
#################### vLLM installation IMAGE ####################
@ -174,6 +177,9 @@ RUN echo 'tzdata tzdata/Areas select America' | debconf-set-selections \
&& ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
&& curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION} \
&& python3 --version && python3 -m pip --version
# Install uv for faster pip installs
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install uv
# Workaround for https://github.com/openai/triton/issues/2507 and
# https://github.com/pytorch/pytorch/issues/107960 -- hopefully
@ -187,13 +193,13 @@ RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/
# after this step
RUN --mount=type=cache,target=/root/.cache/pip \
if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
python3 -m pip install --index-url https://download.pytorch.org/whl/nightly/cu124 "torch==2.6.0.dev20241210+cu124" "torchvision==0.22.0.dev20241215"; \
uv pip install --system --index-url https://download.pytorch.org/whl/nightly/cu124 "torch==2.6.0.dev20241210+cu124" "torchvision==0.22.0.dev20241215"; \
fi
# Install vllm wheel first, so that torch etc will be installed.
RUN --mount=type=bind,from=build,src=/workspace/dist,target=/vllm-workspace/dist \
--mount=type=cache,target=/root/.cache/pip \
python3 -m pip install dist/*.whl --verbose
uv pip install --system dist/*.whl --verbose
# If we need to build FlashInfer wheel before its release:
# $ export FLASHINFER_ENABLE_AOT=1
@ -210,7 +216,7 @@ RUN --mount=type=bind,from=build,src=/workspace/dist,target=/vllm-workspace/dist
RUN --mount=type=cache,target=/root/.cache/pip \
. /etc/environment && \
if [ "$TARGETPLATFORM" != "linux/arm64" ]; then \
python3 -m pip install https://github.com/flashinfer-ai/flashinfer/releases/download/v0.2.1.post1/flashinfer_python-0.2.1.post1+cu124torch2.5-cp38-abi3-linux_x86_64.whl ; \
uv pip install --system https://github.com/flashinfer-ai/flashinfer/releases/download/v0.2.1.post1/flashinfer_python-0.2.1.post1+cu124torch2.5-cp38-abi3-linux_x86_64.whl ; \
fi
COPY examples examples
@ -220,7 +226,7 @@ COPY examples examples
# TODO: Remove this once FlashInfer AOT wheel is fixed
COPY requirements-build.txt requirements-build.txt
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install -r requirements-build.txt
uv pip install --system -r requirements-build.txt
#################### vLLM installation IMAGE ####################
@ -233,15 +239,15 @@ ADD . /vllm-workspace/
# install development dependencies (for testing)
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install -r requirements-dev.txt
uv pip install --system -r requirements-dev.txt
# install development dependencies (for testing)
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install -e tests/vllm_test_utils
uv pip install --system -e tests/vllm_test_utils
# enable fast downloads from hf (for testing)
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install hf_transfer
uv pip install --system hf_transfer
ENV HF_HUB_ENABLE_HF_TRANSFER 1
# Copy in the v1 package for testing (it isn't distributed yet)
@ -262,9 +268,9 @@ FROM vllm-base AS vllm-openai-base
# install additional dependencies for openai api server
RUN --mount=type=cache,target=/root/.cache/pip \
if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
pip install accelerate hf_transfer 'modelscope!=1.15.0' 'bitsandbytes>=0.42.0' 'timm==0.9.10' boto3 runai-model-streamer runai-model-streamer[s3]; \
uv pip install --system accelerate hf_transfer 'modelscope!=1.15.0' 'bitsandbytes>=0.42.0' 'timm==0.9.10' boto3 runai-model-streamer runai-model-streamer[s3]; \
else \
pip install accelerate hf_transfer 'modelscope!=1.15.0' 'bitsandbytes>=0.45.0' 'timm==0.9.10' boto3 runai-model-streamer runai-model-streamer[s3]; \
uv pip install --system accelerate hf_transfer 'modelscope!=1.15.0' 'bitsandbytes>=0.45.0' 'timm==0.9.10' boto3 runai-model-streamer runai-model-streamer[s3]; \
fi
ENV VLLM_USAGE_SOURCE production-docker-image