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new 1c27ccf531 [CI] Drop redundant cmake/ninja install from the Linux
wheel CUDA sidecar (#19761)
1c27ccf531 is described below
commit 1c27ccf5313f9d09e084e023bb01ff042e0090cc
Author: Shushi Hong <[email protected]>
AuthorDate: Sun Jun 14 07:46:42 2026 -0400
[CI] Drop redundant cmake/ninja install from the Linux wheel CUDA sidecar
(#19761)
This pr is the follow-up pr of #19754. It removes the redundant `pip
install -U pip cmake ninja` (since those are already installed in
docker) and the unused python_bin variable, and update the comment to
match: the image provides the build tools, and PATH only needs the
bundled CPython (for the configure) plus the CUDA toolchain (for nvcc).
Also fixs a stale comment in the Windows sidecar: it claimed the conda
13.0.2 pin matched the Linux hook, but the Linux side is now CUDA 13.1
(from the image). The win-64 nvidia channel still caps at 13.0.x, so
Windows stays on 13.0.2 -- slightly behind Linux but harmless, since the
sidecar has no device code and links the CUDA runtime by soname only.
The Windows pip install is kept: that build uses the Ninja generator and
runs on a runner without the prebuilt CUDA image.
---
ci/scripts/package/README.md | 6 ++++--
ci/scripts/package/manylinux_build_libtvm_runtime_cuda.sh | 8 ++++----
ci/scripts/package/windows_build_libtvm_runtime_cuda.bat | 9 +++++----
3 files changed, 13 insertions(+), 10 deletions(-)
diff --git a/ci/scripts/package/README.md b/ci/scripts/package/README.md
index f123fd1383..972c315309 100644
--- a/ci/scripts/package/README.md
+++ b/ci/scripts/package/README.md
@@ -23,7 +23,9 @@ and `[tool.scikit-build]`). This directory holds the few
helper scripts that flo
invokes:
- `manylinux_build_libtvm_runtime_cuda.sh` — run by the `build_cuda_runtime` CI
- stage; builds the `libtvm_runtime_cuda.so` sidecar inside the manylinux
container.
+ stage; builds the `libtvm_runtime_cuda.so` sidecar inside the prebuilt
+ `quay.io/manylinux_cuda` image (CUDA toolkit preinstalled).
- `windows_build_libtvm_runtime_cuda.bat` — the Windows equivalent (run with
- `shell: cmd`), building `tvm_runtime_cuda.dll`.
+ `shell: cmd`); installs the CUDA toolkit via conda and builds
+ `tvm_runtime_cuda.dll`.
- `build-environment.yaml` — conda environment for building the wheel.
diff --git a/ci/scripts/package/manylinux_build_libtvm_runtime_cuda.sh
b/ci/scripts/package/manylinux_build_libtvm_runtime_cuda.sh
index 66e3d787b4..ea9e563046 100755
--- a/ci/scripts/package/manylinux_build_libtvm_runtime_cuda.sh
+++ b/ci/scripts/package/manylinux_build_libtvm_runtime_cuda.sh
@@ -27,14 +27,14 @@ set -euxo pipefail
repo_root="$(cd "$(dirname "${BASH_SOURCE[0]}")/../../.." && pwd)"
build_dir="${repo_root}/build-wheel-cuda"
-python_bin="/opt/python/cp310-cp310/bin/python"
parallel="$(getconf _NPROCESSORS_ONLN 2>/dev/null || echo 4)"
# Build the CUDA runtime sidecar with CUDA on and LLVM off, so it does not need
-# the LLVM prefix; the main CPU wheel links LLVM statically. pip-install
-# cmake/ninja rather than relying on whatever the image ships.
+# the LLVM prefix; the main CPU wheel links LLVM statically. The manylinux CUDA
+# image already ships cmake and make, and the build uses the default Makefiles
+# generator (no Ninja), so no build tools are installed here. Put the bundled
+# CPython and CUDA toolchain on PATH for the CMake configure and nvcc.
export PATH="/opt/python/cp310-cp310/bin:/usr/local/cuda/bin:${PATH}"
-"${python_bin}" -m pip install -U pip cmake ninja
nvcc --version
rm -rf "${build_dir}"
diff --git a/ci/scripts/package/windows_build_libtvm_runtime_cuda.bat
b/ci/scripts/package/windows_build_libtvm_runtime_cuda.bat
index 20523394ee..4864c18a80 100644
--- a/ci/scripts/package/windows_build_libtvm_runtime_cuda.bat
+++ b/ci/scripts/package/windows_build_libtvm_runtime_cuda.bat
@@ -36,10 +36,11 @@ set "conda_exe=conda"
where conda >nul 2>nul || set "conda_exe=%CONDA%\Scripts\conda.exe"
rem Install the pinned CUDA toolkit via conda from the nvidia channel,
mirroring the
-rem LLVM-via-conda install used elsewhere. The win-64 channel caps at 13.0.x,
matching
-rem the Linux hook's CUDA 13.0.2. The nvidia CDN occasionally returns a
transient
-rem HTTP 5xx, so retry once; a half-finished first attempt can leave the prefix
-rem partially populated, so wipe it before retrying.
+rem LLVM-via-conda install used elsewhere. The win-64 channel caps at 13.0.x,
so this
+rem pins 13.0.2 -- slightly behind the Linux image's CUDA 13.1, which is
harmless: the
+rem sidecar has no device code and links the CUDA runtime by soname only. The
nvidia
+rem CDN occasionally returns a transient HTTP 5xx, so retry once; a
half-finished first
+rem attempt can leave the prefix partially populated, so wipe it before
retrying.
if not exist "%cuda_prefix%\Library\bin\nvcc.exe" (
call "%conda_exe%" create -q -p "%cuda_prefix%" -c nvidia/label/cuda-13.0.2
cuda-toolkit -y
if errorlevel 1 (
