[CI][Docker] Pin manylinux2_28-builder:cuda13.0 to the release/2.13 image (#52994)
Signed-off-by: Andrey Talman <atalman@fb.com>
Andrey Talman committed
Aug 20, 2026 at 18:19 UTC
54ba80d9611d3a9cce7ba348e8719e24b5d9211c
4 files changed
+6
-6
.buildkite/image_build/image_build_torch_nightly.sh
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@@ -48,7 +48,7 @@ echo "Image not found, proceeding with build..."
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# --- CUDA 13.0 for nightly builds ---
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# Nightly CI uses CUDA 13.0 while regular CI stays on CUDA 12.9
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NIGHTLY_CUDA_VERSION="13.0.2"
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-NIGHTLY_BUILD_BASE_IMAGE="pytorch/manylinux2_28-builder:cuda13.0"
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+NIGHTLY_BUILD_BASE_IMAGE="pytorch/manylinux2_28-builder:cuda13.0-78e737ad29420ffc4800e677c51e2a852caf8359"
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NIGHTLY_FINAL_BASE_IMAGE="nvidia/cuda:${NIGHTLY_CUDA_VERSION}-base-ubuntu22.04"
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echo "--- :docker: Building torch nightly image (CUDA ${NIGHTLY_CUDA_VERSION})"
.buildkite/release-pipeline.yaml
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@@ -47,7 +47,7 @@ steps:
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agents:
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queue: cpu_queue_release
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commands:
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- - "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.2 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_X86}\" --build-arg BUILD_BASE_IMAGE=pytorch/manylinux2_28-builder:cuda13.0 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
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+ - "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.2 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_X86}\" --build-arg BUILD_BASE_IMAGE=pytorch/manylinux2_28-builder:cuda13.0-78e737ad29420ffc4800e677c51e2a852caf8359 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
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- "mkdir artifacts"
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- "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
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- "bash .buildkite/scripts/upload-nightly-wheels.sh"
@@ -234,7 +234,7 @@ steps:
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--build-arg CUDA_VERSION=13.0.2 \
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--build-arg torch_cuda_arch_list="${CUDA_ARCH_X86}" \
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--build-arg INSTALL_KV_CONNECTORS=true \
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- --build-arg BUILD_BASE_IMAGE=pytorch/manylinux2_28-builder:cuda13.0 \
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+ --build-arg BUILD_BASE_IMAGE=pytorch/manylinux2_28-builder:cuda13.0-78e737ad29420ffc4800e677c51e2a852caf8359 \
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--target vllm-openai \
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--progress plain \
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-f docker/Dockerfile .
@@ -334,7 +334,7 @@ steps:
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--build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 \
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--build-arg torch_cuda_arch_list="${CUDA_ARCH_X86}" \
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--build-arg INSTALL_KV_CONNECTORS=true \
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- --build-arg BUILD_BASE_IMAGE=pytorch/manylinux2_28-builder:cuda13.0 \
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+ --build-arg BUILD_BASE_IMAGE=pytorch/manylinux2_28-builder:cuda13.0-78e737ad29420ffc4800e677c51e2a852caf8359 \
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--target vllm-openai \
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--progress plain \
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-f docker/Dockerfile .
docker/Dockerfile
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@@ -38,7 +38,7 @@ ARG NCCL_VERSION=2.30.7
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# docker build --build-arg BUILD_BASE_IMAGE=registry.acme.org/mirror/pytorch/manylinux2_28-builder:cuda13.0
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# Build wheels against the same glibc floor as PyTorch's published wheels.
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-ARG BUILD_BASE_IMAGE=pytorch/manylinux2_28-builder:cuda13.0
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+ARG BUILD_BASE_IMAGE=pytorch/manylinux2_28-builder:cuda13.0-78e737ad29420ffc4800e677c51e2a852caf8359
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# Using cuda base image with minimal dependencies necessary for JIT compilation (FlashInfer, DeepGEMM, EP kernels)
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ARG FINAL_BASE_IMAGE=nvidia/cuda:${CUDA_VERSION}-base-ubuntu${UBUNTU_VERSION}
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docker/versions.json
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@@ -14,7 +14,7 @@
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"default": "2.30.7"
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},
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"BUILD_BASE_IMAGE": {
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- "default": "pytorch/manylinux2_28-builder:cuda13.0"
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+ "default": "pytorch/manylinux2_28-builder:cuda13.0-78e737ad29420ffc4800e677c51e2a852caf8359"
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},
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"FINAL_BASE_IMAGE": {
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"default": "nvidia/cuda:13.0.3-base-ubuntu24.04"