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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/ci_install_deepep.sh
+43 -10
View File
@@ -2,7 +2,23 @@
# Install the dependency in CI.
set -euxo pipefail
bash scripts/ci/cuda/ci_install_dependency.sh
# Source (not bash) so that venv activation, $PIP_CMD, $CU_VERSION, $NVCC_VER, and
# $PIP_INSTALL_SUFFIX all propagate into this shell. Without sourcing, the subshell
# exits and this script would fall back to system Python.
#
# Note: any `exit N` or `set -e` trip inside the sourced script terminates *this*
# script too (bash runs sourced commands in the current shell, so `exit` is not
# caught by `if`/`||`). The real error message appears upstream in the log.
# shellcheck disable=SC1091
source scripts/ci/cuda/ci_install_dependency.sh
# In venv mode, PIP_CMD must be set by the sourced script. If it isn't, the
# source chain is broken and we'd silently fall back to system `pip` below —
# exactly the split-install bug the migration is meant to prevent.
if [ -z "${PIP_CMD:-}" ]; then
echo "FATAL:PIP_CMD is unset after sourcing ci_install_dependency.sh"
exit 1
fi
export GDRCOPY_HOME=/usr/src/gdrdrv-2.5.1/
export CUDA_HOME=/usr/local/cuda
@@ -96,24 +112,41 @@ fi
cd ${DEEPEP_DIR}
if [ "$GRACE_BLACKWELL" = "1" ]; then
CUDA_VERSION=$(nvidia-smi | grep "CUDA Version" | head -n1 | awk '{print $9}')
# Resolve the toolkit CUDA version. Preference order:
# 1. $NVCC_VER inherited from the sourced ci_install_dependency.sh
# (both scripts agree on the detected value, no re-detection cost).
# 2. Local `nvcc --version` (authoritative — container toolkit).
# 3. `nvidia-smi` (host driver; last resort).
if [ -n "${NVCC_VER:-}" ]; then
CUDA_VERSION="$NVCC_VER"
elif command -v nvcc >/dev/null 2>&1; then
CUDA_VERSION=$(nvcc --version | grep -oP 'release \K[0-9]+\.[0-9]+')
else
CUDA_VERSION=$(nvidia-smi | grep "CUDA Version" | head -n1 | awk '{print $9}' || true)
fi
if [ -z "${CUDA_VERSION:-}" ]; then
echo "FATAL: could not determine CUDA toolkit version (NVCC_VER unset, nvcc missing, nvidia-smi empty)"
exit 1
fi
if [ "$CUDA_VERSION" = "12.8" ]; then
CHOSEN_TORCH_CUDA_ARCH_LIST='10.0'
elif awk -v ver="$CUDA_VERSION" 'BEGIN {exit !(ver > 12.8)}'; then
# With cuda > 12.8, the compiler supports 10.3, so we should use
# CHOSEN_TORCH_CUDA_ARCH_LIST='10.0;10.3'
#
# However, our CI machine has a weird setup and nvidia-smi reports wrong CUDA version in the container.
# The container is actually cuda 12.8, but nvidia-smi reports 13.0, leading to compilation errors. so we
# drop 10.3.
CHOSEN_TORCH_CUDA_ARCH_LIST='10.0'
# CUDA > 12.8 supports sm_103 (Blackwell)
CHOSEN_TORCH_CUDA_ARCH_LIST='10.0;10.3'
else
echo "Unsupported CUDA version for Grace Blackwell: $CUDA_VERSION" && exit 1
fi && \
if [ "${CUDA_VERSION%%.*}" = "13" ]; then \
sed -i "/^ include_dirs = \['csrc\/'\]/a\ include_dirs.append('${CUDA_HOME}/include/cccl')" setup.py; \
fi
TORCH_CUDA_ARCH_LIST="${CHOSEN_TORCH_CUDA_ARCH_LIST}" pip install --no-build-isolation .
TORCH_CUDA_ARCH_LIST="${CHOSEN_TORCH_CUDA_ARCH_LIST}" ${PIP_CMD:-pip} install --no-build-isolation . ${PIP_INSTALL_SUFFIX:-}
else
# CUDA 13.0 puts CCCL headers in /usr/local/cuda/include/cccl/ but nvshmem
# includes them as <cuda/__cccl_config> expecting /usr/local/cuda/include/cuda/.
# Add the cccl path to setup.py include_dirs so the compiler finds them.
NVCC_MAJOR=$(nvcc --version 2>/dev/null | grep -oP 'release \K[0-9]+' || echo "0")
if [ "$NVCC_MAJOR" = "13" ]; then
sed -i "/^ include_dirs = \['csrc\/'\]/a\ include_dirs.append('${CUDA_HOME:-/usr/local/cuda}/include/cccl')" setup.py
fi
python3 setup.py install
fi