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[CI] Add per-job uv venv isolation and upgrade CI version to Cuda 13 (#23119)

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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: Alison Shao <a.shao@wustl.edu>
Co-authored-by: Mick <mickjagger19@icloud.com>
This commit is contained in:
Baizhou Zhang
2026-04-19 05:32:36 -07:00
committed by GitHub
co-authored by Kangyan Zhou Claude Opus 4.7 Alison Shao Mick
parent 03828f4205
commit 6ecd6f84db
39 changed files with 892 additions and 239 deletions
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scripts/ci/cuda/cache_nvidia_wheels.sh
+10 -4
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@@ -21,14 +21,20 @@ NVIDIA_PIP_WHEELS="/root/.cache/nvidia-pip-wheels"
mkdir -p "$NVIDIA_WHEEL_CACHE"
for url in \
"https://pypi.nvidia.com/nvidia-cudnn-cu12/nvidia_cudnn_cu12-9.10.2.21-py3-none-manylinux_2_27_x86_64.whl" \
"https://pypi.nvidia.com/nvidia-nvshmem-cu12/nvidia_nvshmem_cu12-3.3.20-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl"; do
"https://pypi.nvidia.com/nvidia-cudnn-cu13/nvidia_cudnn_cu13-9.16.0.29-py3-none-manylinux_2_27_x86_64.whl" \
"https://pypi.nvidia.com/nvidia-nvshmem-cu13/nvidia_nvshmem_cu13-3.3.20-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl"; do
whl="$NVIDIA_WHEEL_CACHE/$(basename "$url")"
[ -f "$whl" ] && unzip -tq "$whl" &>/dev/null || curl -fL -o "$whl" "$url"
done
pip install --no-deps "$NVIDIA_WHEEL_CACHE"/nvidia_cudnn_cu12-*.whl \
"$NVIDIA_WHEEL_CACHE"/nvidia_nvshmem_cu12-*.whl 2>/dev/null || true
# Caller (ci_install_dependency.sh) sets $PIP_CMD/$PIP_INSTALL_SUFFIX to route
# installs into the active environment (venv or system). The `:-pip` fallback
# keeps the file runnable ad-hoc for debugging; in CI the caller always sets
# these. Silent failure here is deliberate — the pinned cudnn/nvshmem installs
# later in ci_install_dependency.sh are the source of truth; this is only a
# download optimization.
${PIP_CMD:-pip} install --no-deps "$NVIDIA_WHEEL_CACHE"/nvidia_cudnn_cu13-*.whl \
"$NVIDIA_WHEEL_CACHE"/nvidia_nvshmem_cu13-*.whl ${PIP_INSTALL_SUFFIX:-} 2>/dev/null || true
# If pre-cached NVIDIA pip wheels exist, tell pip to check there first.
# This avoids re-downloading ~2 GB of cublas/cufft/nvrtc/etc. every run