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[Dependency] Upgrade to Torch 2.11.0 (#21247)

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Co-authored-by: Kangyan Zhou <zky314343421@gmail.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-authored-by: Baizhou Zhang <sobereddiezhang@gmail.com>
Co-authored-by: b8zhong <b8zhong@users.noreply.github.com>
Co-authored-by: Mick <mickjagger19@icloud.com>
This commit is contained in:
Brayden Zhong
2026-05-02 12:25:36 -07:00
committed by GitHub
co-authored by Kangyan Zhou Claude Opus 4.7 Baizhou Zhang b8zhong Mick
parent 24a6b3084d
commit 88bb5dffe4
21 changed files with 658 additions and 211 deletions
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scripts/ci/cuda/ci_install_dependency.sh
+5 -45
View File
@@ -34,9 +34,6 @@ configure_environment() {
CU_STRIP="${CU_VERSION#cu}"
CU_MAJOR="${CU_STRIP:0:2}"
# Nvidia package versions we pin (torch ships older versions).
NVIDIA_CUDNN_VERSION="9.16.0.29"
NVIDIA_NVSHMEM_VERSION="3.4.5"
OPTIONAL_DEPS="${1:-}"
# Whether to create a uv venv (set USE_VENV=1). Default: 0.
@@ -288,19 +285,11 @@ install_sglang_kernel() {
$PIP_CMD install "torch==${TORCH_VER}" "torchaudio==${TORCHAUDIO_VER}" "torchvision==${TORCHVISION_VER}" --index-url "https://download.pytorch.org/whl/${CU_VERSION}" --force-reinstall --no-deps $PIP_INSTALL_SUFFIX
fi
# Reinstall sglang-kernel with matching CUDA version if needed
SGL_KERNEL_FULL_VER=$(pip show sglang-kernel 2>/dev/null | grep "^Version:" | awk '{print $2}' || echo "")
SGL_KERNEL_CUDA_VER=$(printf '%s' "$SGL_KERNEL_FULL_VER" | sed -n 's/.*+//p')
echo "Detected sglang-kernel version: ${SGL_KERNEL_FULL_VER} (CUDA tag: ${SGL_KERNEL_CUDA_VER:-none})"
if [ -n "$SGL_KERNEL_CUDA_VER" ] && [ "$SGL_KERNEL_CUDA_VER" != "$CU_VERSION" ]; then
SGL_KERNEL_VER="${SGL_KERNEL_FULL_VER%+*}"
echo "Reinstalling sglang-kernel==${SGL_KERNEL_VER} from ${CU_VERSION} index to match torch..."
if [ "$CU_MAJOR" = "13" ]; then
$PIP_CMD install "sglang-kernel==${SGL_KERNEL_VER}" --index-url "https://docs.sglang.ai/whl/${CU_VERSION}/" --force-reinstall --no-deps $PIP_INSTALL_SUFFIX
else
$PIP_CMD install "sglang-kernel==${SGL_KERNEL_VER}" --force-reinstall --no-deps $PIP_INSTALL_SUFFIX
fi
fi
# install_sglang above pulls sglang-kernel from PyPI, whose default wheel
# tracks one CUDA version (currently cu130). Force-reinstall from the
# CU_VERSION-matched sglang wheel index so runners on a different CUDA
# (e.g. h20 / cu129) get a wheel linked against the right libnvrtc.
$PIP_CMD install "sglang-kernel==${SGL_KERNEL_VERSION_FROM_SRT}" --index-url "https://docs.sglang.ai/whl/${CU_VERSION}/" --force-reinstall --no-deps $PIP_INSTALL_SUFFIX
mark_step_done "${FUNCNAME[0]}"
}
@@ -407,34 +396,6 @@ install_extra_deps() {
mark_step_done "${FUNCNAME[0]}"
}
fix_nvidia_deps() {
if [ "$CU_MAJOR" = "13" ]; then
NVSHMEM_PKG="nvidia-nvshmem-cu13"
CUDNN_PKG="nvidia-cudnn-cu13"
else
NVSHMEM_PKG="nvidia-nvshmem-cu12"
CUDNN_PKG="nvidia-cudnn-cu12"
fi
# DeepEP depends on nvshmem 3.4.5
INSTALLED_NVSHMEM=$(pip show ${NVSHMEM_PKG} 2>/dev/null | grep "^Version:" | awk '{print $2}' || echo "")
if [ "$INSTALLED_NVSHMEM" = "$NVIDIA_NVSHMEM_VERSION" ]; then
echo "${NVSHMEM_PKG}==${NVIDIA_NVSHMEM_VERSION} already installed, skipping reinstall"
else
$PIP_CMD install ${NVSHMEM_PKG}==${NVIDIA_NVSHMEM_VERSION} $PIP_INSTALL_SUFFIX
fi
# cudnn < 9.16.0.29 causes Conv3D performance regression
INSTALLED_CUDNN=$(pip show ${CUDNN_PKG} 2>/dev/null | grep "^Version:" | awk '{print $2}' || echo "")
if [ "$INSTALLED_CUDNN" = "$NVIDIA_CUDNN_VERSION" ]; then
echo "${CUDNN_PKG}==${NVIDIA_CUDNN_VERSION} already installed, skipping reinstall"
else
$PIP_CMD install ${CUDNN_PKG}==${NVIDIA_CUDNN_VERSION} $PIP_INSTALL_SUFFIX
fi
mark_step_done "${FUNCNAME[0]}"
}
install_test_tools() {
# Download kernels from kernels community
kernels download python || true
@@ -506,7 +467,6 @@ main() {
download_flashinfer_cache
stabilize_flashinfer_jit_paths
install_extra_deps
fix_nvidia_deps
install_test_tools
prepare_runner
setup_ld_library_path