ci(sgl-kernel-build): actually reclaim disk in the wheel-build cleanup step (#25206)
Co-authored-by: Claude <noreply@anthropic.com>
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@@ -83,21 +83,24 @@ jobs:
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- name: Free Docker disk space
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run: |
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set -x
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# build.sh retags sgl-kernel-deps:cuda${CUDA_VERSION}-${PY_TAG}-${ARCH}
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# on every run, leaving the previous image as a dangling <none>:<none>
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# entry (~16-23 GB each). Prune them before building so the runner
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# doesn't fill up. The local buildx cache at ~/.cache/sgl-kernel/buildx
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# and the tagged sgl-kernel-deps image are not affected.
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# `until=12h` avoids racing with a sibling matrix cell (cuda 12.9 vs
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# 13.0) that may have just orphaned an image seconds ago.
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docker image prune -f --filter "until=12h"
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# Drop orphaned buildx builder volumes from past `docker buildx create`
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# invocations. The active `sgl-kernel-builder` volume is held open and
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# would fail to remove anyway, but skip it explicitly for clarity.
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for v in $(docker volume ls -q | grep '^buildx_buildkit_' | grep -v '^buildx_buildkit_sgl-kernel-builder' || true); do
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echo "Removing orphan buildx volume: $v"
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docker volume rm "$v" || true
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# `-f` only (no `-a`): drops dangling <none>:<none> layers from
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# prior runs but keeps the tagged sgl-kernel-deps:* base images.
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docker image prune -f
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# Reap orphan buildx builders from interrupted prior runs. Must
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# `buildx rm` (not `volume rm`) — the volume is held open by the
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# buildkit helper container; removing the builder frees both.
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# `sgl-kernel-builder` and `default` are skipped on purpose.
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for b in $(docker buildx ls --format '{{.Name}}' | grep -E '^builder-' || true); do
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echo "Removing orphan buildx builder: $b"
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docker buildx rm "$b" || true
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done
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# Trim the persistent local buildx cache (--cache-to mode=max grows
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# unbounded). Cache-hit imports rewrite the blob, so mtime tracks
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# "last carried forward by a build" — 14d is well past the freshest
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# CI cycle.
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if [ -d "$HOME/.cache/sgl-kernel/buildx/blobs" ]; then
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find "$HOME/.cache/sgl-kernel/buildx/blobs" -type f -mtime +14 -delete
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fi
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df -h /
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- name: Build wheel for Python ${{ matrix.python-version }} and CUDA ${{ matrix.cuda-version }}
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