Every path-gated workflow begins with one small job -- `does this change touch
it`, or `which workspaces this change touches` for the standards build -- that
all of its real jobs declare in `needs`. All 55 of those gate jobs ran on
`linux-arm64`.
That is the one label the fleet cannot spare. Sampled while 267 runs were
queued, every waiting run had the same shape:
[waiting] linux-arm64 does this change touch it
[blocked] linux member · dataflow device, simulated
[blocked] macos member · dataflow device absent
237 runs, each holding a gate in the longest queue, and every real job blocked
behind it. Not only `linux` jobs: `macos`, `linux-hw`, `linux-arm64-hw` and
`macos-m3-ultra` jobs were blocked too. The measured effect was `linux-arm64`
263 deep against `linux` **zero**, with jetson-hub's 20 cores taking no job for
a full hour -- starved not for want of work but because the work could not be
unblocked. A gate waiting on the resource it is rationing is head-of-line
blocking, and it makes every other runner in the fleet idle on its behalf.
The gates move to `linux`. Nothing else changes: the diff is 55 `runs-on` lines
and no others, and every touched file still parses.
Why `linux` and not elsewhere. The gate is not free -- it compares
`BASE...HEAD`, which needs the merge base, so `fetch-depth: 0` is a full clone
rather than a ten-second script. `macos` is served by hosts on a Mac Studio
sitting at load 185; `linux` is a separate 20-core box that was measurably
empty. This moves a serialisation point to the least contended label; it does
not remove it, and the gate is still a single point of failure for its
workflow. The structural fix is an early-exit first step inside each job, which
costs one checkout per leg and is a larger change.
Follow-up, deliberately not bundled: jetson-hub runs at capacity 2 with 15 GB of
RAM, so 55 clones still serialise two at a time. Raising capacity helps gates
and hurts the heavy emulated-architecture jobs that share the label, so it wants
measuring on its own.
Co-Authored-By: Claude Opus 5 <[email protected]>
145 lines
7.4 KiB
YAML
145 lines
7.4 KiB
YAML
name: WAI neural decoders end-to-end
|
|
|
|
# The float neural decoders (elic / mlicpp / glc / dcvc / snac) cannot make
|
|
# WAI's cross-architecture byte-equality promise — their ONNX synthesis is
|
|
# float, so the low bits differ by hardware (this is exactly why the
|
|
# integer-exact int_synth path exists, and why only it is in the byte-equality
|
|
# matrix). What they CAN be is *correct end-to-end* on a real machine: entropy
|
|
# decode → ONNX synthesis → image assembly, reproducing a reference within ORT
|
|
# float rounding (±4). This job proves that, with no committed model blobs:
|
|
# the committed tool builds minimal synthetic CompressAI-compatible models +
|
|
# bitstreams, and the Rust decoders reproduce each reference. It runs only when
|
|
# the neural decode code or the generator changes — not on every cargo class.
|
|
|
|
# One run per branch at a time. A push supersedes the run before it.
|
|
#
|
|
# There is one `macos` runner and it is the dev Mac, so every macOS job in this
|
|
# repo queues on it. With no concurrency group, a session pushing four versions
|
|
# of a branch queued four complete sets of runs and every one of them had to
|
|
# drain: on 2026-10-05 a PR's 21 contexts settled none in 70 minutes behind a
|
|
# backlog of 25 runs, and the queue grew faster than it cleared. Only the newest
|
|
# commit's verdict is wanted, so the older runs are cancelled.
|
|
#
|
|
# Verified on this forge (Forgejo 16.0.5) in `ci-test` before being added here:
|
|
# the key parses, and a newer push moves an older run to `cancelled` even while
|
|
# it is still queued, which is the case that matters.
|
|
#
|
|
# `cancel-in-progress: true` also applies to `main`. That is deliberate and
|
|
# safe here: main advances by merge commits whose tree contains the commits
|
|
# before them, so the newer run covers the older one's changes.
|
|
concurrency:
|
|
group: ${{ github.workflow }}-${{ github.ref }}
|
|
cancel-in-progress: true
|
|
|
|
on:
|
|
pull_request:
|
|
paths:
|
|
- 'wai/wai-rs/src/neural/**'
|
|
- 'wai/wai-rs/tests/neural_native_decode.rs'
|
|
- 'wai/tools/wai_validate_synthetic.py'
|
|
- '.github/workflows/wai-neural-e2e.yml'
|
|
schedule:
|
|
- cron: '12 4 * * *'
|
|
|
|
jobs:
|
|
# Does this pull request's own diff touch the paths below? This forge matches a
|
|
# workflow's `paths:` against the push, so a merge of main into a branch fires the
|
|
# workflow whatever the pull request changes; every job here waits on this answer.
|
|
# A push to main, a schedule, or anything the script cannot determine answers
|
|
# `true` (scripts/pr-touches-paths.py).
|
|
relevant:
|
|
name: does this change touch it
|
|
runs-on: linux
|
|
outputs:
|
|
run: ${{ steps.gate.outputs.run }}
|
|
steps:
|
|
- uses: actions/checkout@v5
|
|
with:
|
|
fetch-depth: 0
|
|
- id: gate
|
|
run: |
|
|
set -euo pipefail
|
|
r=$(python3 scripts/pr-touches-paths.py .github/workflows/wai-neural-e2e.yml \
|
|
"${{ github.event.pull_request.base.sha }}" \
|
|
"${{ github.event.pull_request.head.sha }}")
|
|
echo "this change touches wai-neural-e2e: $r"
|
|
echo "run=$r" >> "$GITHUB_OUTPUT"
|
|
|
|
neural-e2e:
|
|
needs: relevant
|
|
if: needs.relevant.outputs.run == 'true'
|
|
name: synthetic fixtures → Rust decode → reference (±4)
|
|
runs-on: linux
|
|
# The Rust decoders link `ort`, whose `download-binaries` feature pulls a
|
|
# prebuilt static onnxruntime (1.28.0 for ort 2.0.0-rc.13). That library was
|
|
# built against glibc >= 2.38 and GCC 13's libstdc++. The runner's default
|
|
# job image, catthehacker/ubuntu:act-22.04, has glibc 2.35 and GCC 11, so the
|
|
# test binary fails to LINK with five undefined symbols:
|
|
# __isoc23_strtol __isoc23_strtoll __isoc23_strtoull (glibc 2.38+)
|
|
# basic_string<char>::_M_replace_cold basic_string<wchar_t>::_M_replace_cold
|
|
# (libstdc++, GCC 13+)
|
|
# That link error is why this job failed at ~1 minute on every run: the
|
|
# Python steps pass on a warm cache and the job dies at its last step. Checked
|
|
# in both images: act-22.04 lacks all five, act-24.04 (glibc 2.39, g++ 13)
|
|
# provides all five.
|
|
container:
|
|
image: catthehacker/ubuntu:act-24.04
|
|
steps:
|
|
- uses: actions/checkout@v5
|
|
- uses: actions/setup-python@v5
|
|
with:
|
|
python-version: '3.11'
|
|
- name: ML stack (CPU torch + torchvision + compressai + onnxruntime)
|
|
run: |
|
|
python -m pip install --upgrade pip
|
|
# torch AND torchvision from the CPU index so their compiled ops match
|
|
# (compressai imports torchvision; a mismatched build fails at
|
|
# `torchvision::nms does not exist`).
|
|
pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu
|
|
# `onnx` (the exporter) is separate from `onnxruntime` (the decoder).
|
|
pip install compressai onnx onnxruntime numpy pillow
|
|
- name: Build the synthetic fixtures (elic / mlicpp / snac / dcvc / glc)
|
|
working-directory: wai
|
|
run: python tools/wai_validate_synthetic.py --size 256
|
|
# Bootstrap rustup: the docker runner image ships no Rust.
|
|
- name: Install Rust 1.98.0
|
|
run: |
|
|
export PATH="$HOME/.cargo/bin:$PATH"
|
|
command -v rustup >/dev/null 2>&1 || \
|
|
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --profile minimal --default-toolchain 1.98.0
|
|
rustup toolchain install 1.98.0 --profile minimal
|
|
rustup default 1.98.0
|
|
echo "$HOME/.cargo/bin" >> "$GITHUB_PATH"
|
|
- name: Each Rust decoder reproduces its reference end-to-end
|
|
working-directory: wai/wai-rs
|
|
# --no-default-features: the neural decoders need only `ort`, NOT the C
|
|
# codec chain (AV1/JXL/opus), so the job needs no system codec deps.
|
|
#
|
|
# The grep is the assertion, not decoration. Every `*_matches_reference`
|
|
# test opens with `if !wai.exists() || !ref.exists() || !model.exists() {
|
|
# eprintln!("skipping ..."); return; }` — so a missing fixture makes the
|
|
# test SKIP, and a skip is reported as a PASS. Verified by running this
|
|
# exact command on a machine with no /tmp fixtures: it prints
|
|
# "6 passed; 0 failed" while comparing nothing.
|
|
#
|
|
# That means a green `cargo test` here does NOT mean the decoders were
|
|
# checked against their references. If the Python fixture step ever
|
|
# succeeds while writing nothing, this job goes green having verified
|
|
# nothing at all — the failure mode is silent and looks like success.
|
|
# Failing on "skipping" is what makes the job's name true.
|
|
#
|
|
# One test is excluded by name, not tolerated as a skip:
|
|
# `snac_real_model_matches_reference` needs real pretrained SNAC weights,
|
|
# which this synthetic-fixture job never builds, so it would skip on every
|
|
# run and the guard would fail a job whose five in-scope decoders all
|
|
# match. Excluding it keeps the guard strict for everything in scope.
|
|
run: |
|
|
set -o pipefail
|
|
cargo test --no-default-features --features neural --test neural_native_decode \
|
|
-- _matches_reference --skip snac_real_model_matches_reference --nocapture \
|
|
2>&1 | tee /tmp/neural_e2e.log
|
|
if grep -q "skipping" /tmp/neural_e2e.log; then
|
|
echo "::error::a reference comparison was SKIPPED — its fixtures are missing, so this job verified nothing"
|
|
grep "skipping" /tmp/neural_e2e.log
|
|
exit 1
|
|
fi
|