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[Deps] Retire the CUDA 12 lane (#38404)

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Co-authored-by: Mohammad Angkad <mohammad.angkad@radixark.ai>
This commit is contained in:
Mohammad Miadh Angkad
2026-09-10 16:58:09 -07:00
committed by GitHub
co-authored by Mohammad Angkad
parent fae8cd84cb
commit 52c191da52
38 changed files with 170 additions and 737 deletions
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docker/Dockerfile
+15 -77
View File
@@ -6,7 +6,6 @@ ARG BUILD_TYPE=all
ARG BRANCH_TYPE=remote
ARG SGL_KERNEL_VERSION=0.4.6.post1
ARG SGL_VERSION
ARG SGL_DEEP_GEMM_VERSION=0.1.7
ARG USE_LATEST_SGLANG=0
ARG GDRCOPY_VERSION=2.5.1
ARG SGL_NCCL_VERSION=2.30.7
@@ -185,25 +184,11 @@ RUN curl --proto '=https' --tlsv1.2 --retry 3 --retry-delay 2 -sSf https://sh.ru
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install --upgrade pip setuptools wheel html5lib six \
&& case "$CUDA_VERSION" in \
12.6.3) CUINDEX=126 ;; \
12.9.2) CUINDEX=129 ;; \
13.0.3) CUINDEX=130 ;; \
13.0.3) ;; \
*) echo "Unsupported CUDA version: $CUDA_VERSION" && exit 1 ;; \
esac \
&& if [ "$CUDA_VERSION" = "12.6.3" ]; then \
python3 -m pip install https://${GITHUB_ARTIFACTORY}/sgl-project/whl/releases/download/v${SGL_KERNEL_VERSION}/sglang_kernel-${SGL_KERNEL_VERSION}+cu124-cp310-abi3-manylinux2014_$(uname -m).whl --force-reinstall --no-deps \
; \
elif [ "$CUDA_VERSION" = "12.9.2" ]; then \
python3 -m pip install https://${GITHUB_ARTIFACTORY}/sgl-project/whl/releases/download/v${SGL_KERNEL_VERSION}/sglang_kernel-${SGL_KERNEL_VERSION}+cu129-cp310-abi3-manylinux2014_$(uname -m).whl --force-reinstall --no-deps \
; \
elif [ "$CUDA_VERSION" = "13.0.3" ]; then \
# --no-deps prevents pip from pulling torch from default PyPI
python3 -m pip install sglang-kernel==${SGL_KERNEL_VERSION} --force-reinstall --no-deps \
; \
else \
echo "Unsupported CUDA version: $CUDA_VERSION" && exit 1 \
; \
fi
# --no-deps prevents pip from pulling torch from default PyPI
&& python3 -m pip install sglang-kernel==${SGL_KERNEL_VERSION} --force-reinstall --no-deps
# Copy dep spec + Rust crate source + proto files. setuptools-rust compiles the
# Rust extension during the stub wheel build; the crate's build.rs references
@@ -214,15 +199,11 @@ COPY rust/sglang-grpc /tmp/sglang_deps/rust/sglang-grpc
COPY rust/sglang-mm /tmp/sglang_deps/rust/sglang-mm
COPY proto /tmp/sglang_deps/proto
# Install sglang dependencies (torch, transformers, etc.). CUDA 12 DeepEP
# wheels live only on the SGLang index, so preinstall the local-version wheel;
# it satisfies the public-version pyproject pin during the full dependency solve.
# Install sglang dependencies (torch, transformers, etc.).
# Generate constraints.txt to prevent reinstalling these deps in later stages.
RUN --mount=type=cache,target=/root/.cache/pip \
--mount=type=cache,target=/root/.cargo/registry \
case "$CUDA_VERSION" in \
12.6.3) CUINDEX=126 ;; \
12.9.2) CUINDEX=129 ;; \
13.0.3) CUINDEX=130 ;; \
*) echo "Unsupported CUDA version: $CUDA_VERSION" && exit 1 ;; \
esac \
@@ -232,27 +213,7 @@ RUN --mount=type=cache,target=/root/.cache/pip \
&& echo '__version__ = "0.0.0"' > sglang/version.py \
&& touch README.md \
&& touch LICENSE \
&& SGL_DEEP_EP_VERSION="$(sed -n 's/^[[:space:]]*"sgl-deep-ep==\([^"]*\)",/\1/p' pyproject.toml)" \
&& test -n "${SGL_DEEP_EP_VERSION}" \
&& if [ "${CUDA_VERSION%%.*}" = "12" ]; then \
python3 -m pip install \
"sgl-deep-ep==${SGL_DEEP_EP_VERSION}+cu129" \
--index-url "https://docs.sglang.ai/whl/cu129/" \
--no-deps; \
fi \
&& if [ "${CUDA_VERSION%%.*}" = "12" ]; then \
sed -i 's/cuda-python>=13\.0/cuda-python>=12,<13/' pyproject.toml && \
sed -i 's/flashinfer_python\[cu13\]/flashinfer_python[cu12]/' pyproject.toml && \
sed -i 's/nvidia-cutlass-dsl\[cu13\]/nvidia-cutlass-dsl/' pyproject.toml; \
fi \
&& python3 -m pip install --extra-index-url https://download.pytorch.org/whl/cu${CUINDEX} ".[${BUILD_TYPE}]" \
&& if [ "${CUDA_VERSION%%.*}" = "12" ]; then \
pip list --format=freeze | awk -F'==' '/-cu13(==|$)/ {print $1}' \
| xargs -r python3 -m pip uninstall -y && \
python3 -m pip install --index-url https://download.pytorch.org/whl/cu${CUINDEX} \
torch==2.13.0 torchvision==0.28.0 torchaudio==2.11.0 --force-reinstall; \
python3 -m pip install https://github.com/sgl-project/whl/releases/download/v${SGL_DEEP_GEMM_VERSION}/sgl_deep_gemm-${SGL_DEEP_GEMM_VERSION}+cu129-py3-none-manylinux2014_$(uname -m).whl --force-reinstall; \
fi \
&& cd /sgl-workspace \
&& rm -rf /tmp/sglang_deps \
&& pip freeze | grep -v "^sglang==" > /sgl-workspace/constraints.txt
@@ -315,8 +276,6 @@ ARG FLASHINFER_VERSION
# Stage jit-cache/cubin artifacts into /flashinfer_jit_output for clean COPY later
RUN --mount=type=cache,target=/root/.cache/pip \
case "$CUDA_VERSION" in \
12.6.3) CUINDEX=126 ;; \
12.9.2) CUINDEX=129 ;; \
13.0.3) CUINDEX=130 ;; \
*) echo "Unsupported CUDA version: $CUDA_VERSION" && exit 1 ;; \
esac \
@@ -503,21 +462,12 @@ RUN --mount=type=cache,target=/var/cache/apt,id=framework-apt \
# Install Mooncake
RUN --mount=type=cache,target=/root/.cache/pip \
CUDA_MAJOR="${CUDA_VERSION%%.*}" && \
if [ "$CUDA_MAJOR" -ge 13 ]; then \
python3 -m pip install mooncake-transfer-engine-cuda13==${MOONCAKE_VERSION}; \
else \
python3 -m pip install mooncake-transfer-engine==${MOONCAKE_VERSION}; \
fi
python3 -m pip install mooncake-transfer-engine-cuda13==${MOONCAKE_VERSION}
# Install MSCCL++ Python dependencies and package (builds extension via CMake through pip)
RUN --mount=type=cache,target=/root/.cache/pip \
git clone --depth=1 --branch ${MSCCLPP_VERSION} https://${GITHUB_ARTIFACTORY}/microsoft/mscclpp.git /tmp/mscclpp \
&& case "${CUDA_VERSION}" in \
12.*) \
CMAKE_ARGS="-DMSCCLPP_BYPASS_GPU_CHECK=ON -DMSCCLPP_USE_CUDA=ON -DMSCCLPP_GPU_ARCHS=80,90,100,100a,103,103a" \
python3 -m pip install "/tmp/mscclpp[cuda12]"; \
;; \
13.*) \
CMAKE_ARGS="-DMSCCLPP_BYPASS_GPU_CHECK=ON -DMSCCLPP_USE_CUDA=ON -DMSCCLPP_GPU_ARCHS=80,90,100,100a,103,103a" \
python3 -m pip install "/tmp/mscclpp[cuda13]"; \
@@ -553,22 +503,15 @@ RUN --mount=type=cache,target=/root/.cache/pip \
# resolving dependencies and generating constraints.txt. DeepEP needs 2.30.7
# at runtime; apply the override only after the constrained dependency solve.
RUN --mount=type=cache,target=/root/.cache/pip \
if [ "${CUDA_VERSION%%.*}" = "13" ]; then \
python3 -m pip install --force-reinstall --no-deps \
"nvidia-nccl-cu13==${SGL_NCCL_VERSION}"; \
fi
python3 -m pip install --force-reinstall --no-deps \
"nvidia-nccl-cu13==${SGL_NCCL_VERSION}"
# Per-CUDA-major package installs. The `nixl` stub package is needed (it owns
# the `nixl` import path) but unconditionally requires nixl-cu12, so we install
# it with --no-deps and pair it with the matching nixl-cu12 / nixl-cu13 binary
# to avoid shipping wrong-CUDA libs on cu13 images.
RUN --mount=type=cache,target=/root/.cache/pip if [ "${CUDA_VERSION%%.*}" = "12" ]; then \
python3 -m pip install nixl nixl-cu12 --no-deps ; \
python3 -m pip install "cuda-python>=12,<13" ; \
elif [ "${CUDA_VERSION%%.*}" = "13" ]; then \
python3 -m pip install nixl nixl-cu13 --no-deps ; \
python3 -m pip install "cuda-python>=13,<14" ; \
fi
# The `nixl` stub package is needed (it owns the `nixl` import path) but
# unconditionally requires nixl-cu12, so install it with --no-deps and pair it
# with the nixl-cu13 binary to avoid shipping wrong-CUDA libs.
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install nixl nixl-cu13 --no-deps \
&& python3 -m pip install "cuda-python>=13,<14"
# Install the latest available AI Dynamo prerelease from NVIDIA's package index.
RUN --mount=type=cache,target=/root/.cache/pip \
@@ -638,11 +581,6 @@ RUN if [ "$BRANCH_TYPE" = "local" ]; then \
# Clean up __pycache__/tests/pyc in same RUN to avoid writing ~28k files to layer
RUN --mount=type=cache,target=/root/.cache/pip \
cd /sgl-workspace/sglang \
&& if [ "${CUDA_VERSION%%.*}" = "12" ]; then \
sed -i 's/cuda-python>=13\.0/cuda-python>=12,<13/' python/pyproject.toml && \
sed -i 's/flashinfer_python\[cu13\]/flashinfer_python[cu12]/' python/pyproject.toml && \
sed -i 's/nvidia-cutlass-dsl\[cu13\]/nvidia-cutlass-dsl/' python/pyproject.toml; \
fi \
&& python3 -m pip install --no-deps -e "python[${BUILD_TYPE}]" \
&& kernels lock python \
&& ( success=0; \
@@ -659,8 +597,8 @@ RUN --mount=type=cache,target=/root/.cache/pip \
echo "sgl-kernel cubin download failed, retrying in 30s..." && sleep 30; \
done; \
# x86: if no prebuilt sgl-flash-attn3 variant matches this torch+CUDA \
# combo (e.g. cu129 publishes no torch>=2.10 cubin), fall back to \
# runtime JIT instead of failing the build, mirroring the aarch64 branch. \
# combo, fall back to runtime JIT instead of failing the build, \
# mirroring the aarch64 branch. \
if [ "$success" != "1" ]; then \
echo "WARNING: no matching sgl-flash-attn3 cubin variant for this torch+CUDA; kernels will be JIT-compiled at runtime"; \
success=1; \
docker/Dockerfile.cu134
+13 -68
View File
@@ -493,19 +493,11 @@ RUN curl --proto '=https' --tlsv1.2 --retry 3 --retry-delay 2 -sSf https://sh.ru
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install --upgrade pip setuptools wheel html5lib six \
&& case "$CUDA_VERSION" in \
12.6.3) CUINDEX=126 ;; \
12.9.2) CUINDEX=129 ;; \
13.0.3) CUINDEX=130 ;; \
13.4.0) CUINDEX=134 ;; \
*) echo "Unsupported CUDA version: $CUDA_VERSION" && exit 1 ;; \
esac \
&& if [ "$CUDA_VERSION" = "12.6.3" ]; then \
python3 -m pip install https://${GITHUB_ARTIFACTORY}/sgl-project/whl/releases/download/v${SGL_KERNEL_VERSION}/sglang_kernel-${SGL_KERNEL_VERSION}+cu124-cp310-abi3-manylinux2014_$(uname -m).whl --force-reinstall --no-deps \
; \
elif [ "$CUDA_VERSION" = "12.9.2" ]; then \
python3 -m pip install https://${GITHUB_ARTIFACTORY}/sgl-project/whl/releases/download/v${SGL_KERNEL_VERSION}/sglang_kernel-${SGL_KERNEL_VERSION}+cu129-cp310-abi3-manylinux2014_$(uname -m).whl --force-reinstall --no-deps \
; \
elif [ "$CUDA_VERSION" = "13.0.3" ]; then \
&& if [ "$CUDA_VERSION" = "13.0.3" ]; then \
# --no-deps prevents pip from pulling torch from default PyPI
python3 -m pip install sglang-kernel==${SGL_KERNEL_VERSION} --force-reinstall --no-deps \
; \
@@ -527,15 +519,11 @@ COPY rust/sglang-grpc /tmp/sglang_deps/rust/sglang-grpc
COPY rust/sglang-mm /tmp/sglang_deps/rust/sglang-mm
COPY proto /tmp/sglang_deps/proto
# Install sglang dependencies (torch, transformers, etc.). CUDA 12 DeepEP
# wheels live only on the SGLang index, so preinstall the local-version wheel;
# it satisfies the public-version pyproject pin during the full dependency solve.
# Install sglang dependencies (torch, transformers, etc.).
# Generate constraints.txt to prevent reinstalling these deps in later stages.
RUN --mount=type=cache,target=/root/.cache/pip \
--mount=type=cache,target=/root/.cargo/registry \
case "$CUDA_VERSION" in \
12.6.3) CUINDEX=126 ;; \
12.9.2) CUINDEX=129 ;; \
13.0.3) CUINDEX=130 ;; \
13.4.0) CUINDEX=134 ;; \
*) echo "Unsupported CUDA version: $CUDA_VERSION" && exit 1 ;; \
@@ -546,19 +534,6 @@ RUN --mount=type=cache,target=/root/.cache/pip \
&& echo '__version__ = "0.0.0"' > sglang/version.py \
&& touch README.md \
&& touch LICENSE \
&& SGL_DEEP_EP_VERSION="$(sed -n 's/^[[:space:]]*"sgl-deep-ep==\([^"]*\)",/\1/p' pyproject.toml)" \
&& test -n "${SGL_DEEP_EP_VERSION}" \
&& if [ "${CUDA_VERSION%%.*}" = "12" ]; then \
python3 -m pip install \
"sgl-deep-ep==${SGL_DEEP_EP_VERSION}+cu129" \
--index-url "https://docs.sglang.ai/whl/cu129/" \
--no-deps; \
fi \
&& if [ "${CUDA_VERSION%%.*}" = "12" ]; then \
sed -i 's/cuda-python>=13\.0/cuda-python>=12,<13/' pyproject.toml && \
sed -i 's/flashinfer_python\[cu13\]/flashinfer_python[cu12]/' pyproject.toml && \
sed -i 's/nvidia-cutlass-dsl\[cu13\]/nvidia-cutlass-dsl/' pyproject.toml; \
fi \
&& if [ "$CUDA_VERSION" = "13.4.0" ]; then \
sed -i "s|^ \"flashinfer_python\[cu13\]==.*| \"flashinfer_python[cu13]==${FLASHINFER_VERSION}\",|" pyproject.toml; \
fi \
@@ -579,17 +554,8 @@ RUN --mount=type=cache,target=/root/.cache/pip \
TORCH_INDEX="https://download.pytorch.org/whl/cu${CUINDEX}"; \
fi \
&& python3 -m pip install --extra-index-url "${TORCH_INDEX}" ".[${BUILD_TYPE}]" \
&& if [ "${CUDA_VERSION%%.*}" = "13" ]; then \
python3 -m pip install --force-reinstall --no-deps \
"nvidia-nccl-cu13==${NCCL_VERSION}"; \
fi \
&& if [ "${CUDA_VERSION%%.*}" = "12" ]; then \
pip list --format=freeze | awk -F'==' '/-cu13(==|$)/ {print $1}' \
| xargs -r python3 -m pip uninstall -y && \
python3 -m pip install --index-url https://download.pytorch.org/whl/cu${CUINDEX} \
torch==2.13.0 torchvision==0.28.0 torchaudio==2.11.0 --force-reinstall; \
python3 -m pip install https://github.com/sgl-project/whl/releases/download/v${SGL_DEEP_GEMM_VERSION}/sgl_deep_gemm-${SGL_DEEP_GEMM_VERSION}+cu129-py3-none-manylinux2014_$(uname -m).whl --force-reinstall; \
fi \
&& python3 -m pip install --force-reinstall --no-deps \
"nvidia-nccl-cu13==${NCCL_VERSION}" \
&& if [ "$CUDA_VERSION" = "13.4.0" ]; then \
python3 -m pip install --force-reinstall --no-deps /tmp/cu134_wheels/*.whl; \
fi \
@@ -643,8 +609,6 @@ ARG FLASHINFER_VERSION
# Stage jit-cache/cubin artifacts into /flashinfer_jit_output for clean COPY later
RUN --mount=type=cache,target=/root/.cache/pip \
case "$CUDA_VERSION" in \
12.6.3) CUINDEX=126 ;; \
12.9.2) CUINDEX=129 ;; \
13.0.3) CUINDEX=130 ;; \
13.4.0) CUINDEX=134 ;; \
*) echo "Unsupported CUDA version: $CUDA_VERSION" && exit 1 ;; \
@@ -830,21 +794,12 @@ RUN --mount=type=cache,target=/var/cache/apt,id=framework-apt \
# Install Mooncake
RUN --mount=type=cache,target=/root/.cache/pip \
CUDA_MAJOR="${CUDA_VERSION%%.*}" && \
if [ "$CUDA_MAJOR" -ge 13 ]; then \
python3 -m pip install mooncake-transfer-engine-cuda13==${MOONCAKE_VERSION}; \
else \
python3 -m pip install mooncake-transfer-engine==${MOONCAKE_VERSION}; \
fi
python3 -m pip install mooncake-transfer-engine-cuda13==${MOONCAKE_VERSION}
# Install MSCCL++ Python dependencies and package (builds extension via CMake through pip)
RUN --mount=type=cache,target=/root/.cache/pip \
git clone --depth=1 --branch ${MSCCLPP_VERSION} https://${GITHUB_ARTIFACTORY}/microsoft/mscclpp.git /tmp/mscclpp \
&& case "${CUDA_VERSION}" in \
12.*) \
CMAKE_ARGS="-DMSCCLPP_BYPASS_GPU_CHECK=ON -DMSCCLPP_USE_CUDA=ON -DMSCCLPP_GPU_ARCHS=80,90,100,100a,103,103a" \
python3 -m pip install "/tmp/mscclpp[cuda12]"; \
;; \
13.*) \
CMAKE_ARGS="-DMSCCLPP_BYPASS_GPU_CHECK=ON -DMSCCLPP_USE_CUDA=ON -DMSCCLPP_GPU_ARCHS=80,90,100,100a,103,103a" \
python3 -m pip install "/tmp/mscclpp[cuda13]"; \
@@ -882,17 +837,12 @@ RUN --mount=type=cache,target=/root/.cache/pip \
termplotlib \
"runai-model-streamer[s3,gcs,azure]>=0.15.7"
# Per-CUDA-major package installs. The `nixl` stub package is needed (it owns
# the `nixl` import path) but unconditionally requires nixl-cu12, so we install
# it with --no-deps and pair it with the matching nixl-cu12 / nixl-cu13 binary
# to avoid shipping wrong-CUDA libs on cu13 images.
RUN --mount=type=cache,target=/root/.cache/pip if [ "${CUDA_VERSION%%.*}" = "12" ]; then \
python3 -m pip install nixl nixl-cu12 --no-deps ; \
python3 -m pip install "cuda-python>=12,<13" ; \
elif [ "${CUDA_VERSION%%.*}" = "13" ]; then \
python3 -m pip install nixl nixl-cu13 --no-deps ; \
python3 -m pip install "cuda-python>=13,<14" ; \
fi
# The `nixl` stub package is needed (it owns the `nixl` import path) but
# unconditionally requires nixl-cu12, so install it with --no-deps and pair it
# with the nixl-cu13 binary to avoid shipping wrong-CUDA libs.
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install nixl nixl-cu13 --no-deps \
&& python3 -m pip install "cuda-python>=13,<14"
# Install the latest available AI Dynamo prerelease from NVIDIA's package index.
RUN --mount=type=cache,target=/root/.cache/pip \
@@ -965,11 +915,6 @@ RUN if [ "$BRANCH_TYPE" = "local" ]; then \
# Clean up __pycache__/tests/pyc in same RUN to avoid writing ~28k files to layer
RUN --mount=type=cache,target=/root/.cache/pip \
cd /sgl-workspace/sglang \
&& if [ "${CUDA_VERSION%%.*}" = "12" ]; then \
sed -i 's/cuda-python>=13\.0/cuda-python>=12,<13/' python/pyproject.toml && \
sed -i 's/flashinfer_python\[cu13\]/flashinfer_python[cu12]/' python/pyproject.toml && \
sed -i 's/nvidia-cutlass-dsl\[cu13\]/nvidia-cutlass-dsl/' python/pyproject.toml; \
fi \
&& if [ "$CUDA_VERSION" = "13.4.0" ]; then \
sed -i "s|^ \"flashinfer_python\[cu13\]==.*| \"flashinfer_python[cu13]==${FLASHINFER_VERSION}\",|" python/pyproject.toml; \
fi \
@@ -989,8 +934,8 @@ RUN --mount=type=cache,target=/root/.cache/pip \
echo "sgl-kernel cubin download failed, retrying in 30s..." && sleep 30; \
done; \
# x86: if no prebuilt sgl-flash-attn3 variant matches this torch+CUDA \
# combo (e.g. cu129 publishes no torch>=2.10 cubin), fall back to \
# runtime JIT instead of failing the build, mirroring the aarch64 branch. \
# combo, fall back to runtime JIT instead of failing the build, \
# mirroring the aarch64 branch. \
if [ "$success" != "1" ]; then \
echo "WARNING: no matching sgl-flash-attn3 cubin variant for this torch+CUDA; kernels will be JIT-compiled at runtime"; \
success=1; \
docker/sgl-deep-ep.Dockerfile
+2 -18
View File
@@ -6,7 +6,6 @@ FROM ${BASE_IMAGE}:cuda${CUDA_VERSION}
ARG ARCHITECTURE=x86_64
ARG CUDA_TAG=cu130
ARG CUDA_VERSION=13.0
ARG GDRCOPY_VERSION=2.5.1
ARG NCCL_VERSION=2.30.7
ARG PYTHON_TAG=cp312-cp312
ARG TORCH_VERSION=2.13.0
@@ -49,19 +48,6 @@ RUN set -eux; \
ln -sf "${cuda_stub}" /usr/lib64/libcuda.so; \
ln -sf "${cuda_stub}" "/usr/lib/${ARCHITECTURE}-linux-gnu/libcuda.so"
# DeepEP v2 uses NCCL Gin on CUDA 13. Keep GDRCopy only for the CUDA 12
# legacy NVSHMEM/IBGDA build.
RUN set -eux; \
if [ "${CUDA_TAG}" = cu129 ]; then \
git clone --depth 1 --branch "v${GDRCOPY_VERSION}" \
https://github.com/NVIDIA/gdrcopy.git /opt/gdrcopy; \
make -C /opt/gdrcopy CUDA="${CUDA_HOME}" prefix=/usr/local lib_install; \
printf '%s\n' /usr/local/lib > /etc/ld.so.conf.d/gdrcopy.conf; \
ldconfig; \
test -f /usr/local/include/gdrapi.h; \
ldconfig -p | grep -q libgdrapi; \
fi
RUN --mount=type=cache,id=sgl-deep-ep-pip-${CUDA_TAG}-${PYTHON_TAG}-${ARCHITECTURE},target=/root/.cache/pip \
set -eux; \
"${PYTHON_BIN}" -m pip uninstall -y deep-ep sgl-deep-ep || true; \
@@ -69,10 +55,8 @@ RUN --mount=type=cache,id=sgl-deep-ep-pip-${CUDA_TAG}-${PYTHON_TAG}-${ARCHITECTU
"${PYTHON_BIN}" -m pip install --force-reinstall \
"torch==${TORCH_VERSION}" \
--index-url "https://download.pytorch.org/whl/${CUDA_TAG}"; \
if [ "${CUDA_TAG}" = cu130 ]; then \
"${PYTHON_BIN}" -m pip install --force-reinstall --no-deps \
"nvidia-nccl-cu13==${NCCL_VERSION}"; \
fi; \
"${PYTHON_BIN}" -m pip install --force-reinstall --no-deps \
"nvidia-nccl-cu13==${NCCL_VERSION}"; \
"${PYTHON_BIN}" -m pip install \
"auditwheel>=6.0" \
build \
docker/sgl-deep-gemm.Dockerfile
+1 -2
View File
@@ -27,8 +27,7 @@ RUN --mount=type=cache,id=sgl-deep-gemm-pip,target=/root/.cache/pip \
set -eux; \
case "${CUDA_VERSION}" in \
13.0) CU_TAG=cu130 ;; \
12.9) CU_TAG=cu129 ;; \
*) CU_TAG=cu130 ;; \
*) echo "Unsupported CUDA version: ${CUDA_VERSION}" && exit 1 ;; \
esac; \
${PYTHON_ROOT_PATH}/bin/pip install torch==${TORCH_VER} --index-url https://${PYTORCH_MIRROR}/whl/${CU_TAG}; \
${PYTHON_ROOT_PATH}/bin/pip install --index-url ${PIP_DEFAULT_INDEX} \