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Not one of this repo's 15 workflows declared `concurrency:`, so every push
queued a complete set of runs and nothing superseded anything. A session
pushing four versions of a branch queued four complete sets, and all 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 backlog grew faster than it cleared —
0.3.31 through 0.3.34 of one branch, four full sets, when only the newest
commit's verdict was wanted.
Every workflow now groups on `${{ github.workflow }}-${{ github.ref }}` with
`cancel-in-progress: true`.
**Verified before being added here, not assumed.** An unparseable workflow
would mean no CI at all, which is a worse failure than a slow queue, and none
of the fleet's existing `concurrency:` users are on this forge — they are
GitHub-hosted, so they prove GitHub parses the key, not Forgejo. Pushed a probe
to `ci-test` on this forge (Forgejo 16.0.5) instead: runs were created, so the
key parses; and a newer push moved two older runs to `cancelled` **while they
were still queued**, which is exactly the case that matters here.
`cancel-in-progress: true` applies to `main` too. That is deliberate: main
advances by merge commits whose tree contains the commits before them, so a
newer run covers an older one's changes.
## The queue's real shape, which is worse than one busy runner
Worth recording because it decides where the next fix goes. The workspace
matrix asks for three labels:
- **`linux` — 5 workspaces** (jcp-rs, sandbox-rs, smart-byte-rs, proof-rs,
eoc-rs) → jetson-hub, which the forge reports idle and connected.
- **`linux-arm64` — 7 workspaces** (openpay, joule-code-rs, map-rs, aac-rs,
joulecontract-rs, mesh-rs, jouleclaw-rs) → the colima `txarm` VM, **on the
dev Mac**.
- **`macos` — 5 workspaces** plus the dedicated `macOS energy backends` job
→ **the dev Mac**.
So **13 of 21 contexts land on the dev Mac** through two runners, while that
same machine was carrying another session's VVC/VTM encodes at load average
132 on 18 CPUs. That is why `jcp-rs` and `eoc-rs` returned quickly — they are
the two on jetson-hub — while `mesh-rs` (linux-arm64) took 25 minutes and the
macOS job never ran at all.
Concurrency groups cut the number of queued runs, which helps every label. They
do not change the fact that one host serves 13 of 21 contexts. The structural
options are to move some `linux-arm64` workspaces onto jetson-hub's `linux`, or
to stand up a second arm64/macOS host — the Mac Studio M3 Ultra is online and
idle — and that is a fleet change rather than a repo one, so it is flagged here
rather than attempted.
No regression guard is added. A check that every workflow declares the key
would itself need a CI job on the runner this change exists to unblock, and an
unwired check is worse than none.
Co-Authored-By: Claude Opus 5 <[email protected]>
125 lines
6.6 KiB
YAML
125 lines
6.6 KiB
YAML
name: WAI neural decoders end-to-end
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# The float neural decoders (elic / mlicpp / glc / dcvc / snac) cannot make
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# WAI's cross-architecture byte-equality promise — their ONNX synthesis is
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# float, so the low bits differ by hardware (this is exactly why the
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# integer-exact int_synth path exists, and why only it is in the byte-equality
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# matrix). What they CAN be is *correct end-to-end* on a real machine: entropy
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# decode → ONNX synthesis → image assembly, reproducing a reference within ORT
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# float rounding (±4). This job proves that, with no committed model blobs:
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# the committed tool builds minimal synthetic CompressAI-compatible models +
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# bitstreams, and the Rust decoders reproduce each reference. It runs only when
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# the neural decode code or the generator changes — not on every cargo class.
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# One run per branch at a time. A push supersedes the run before it.
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#
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# There is one `macos` runner and it is the dev Mac, so every macOS job in this
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# repo queues on it. With no concurrency group, a session pushing four versions
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# of a branch queued four complete sets of runs and every one of them had to
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# drain: on 2026-10-05 a PR's 21 contexts settled none in 70 minutes behind a
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# backlog of 25 runs, and the queue grew faster than it cleared. Only the newest
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# commit's verdict is wanted, so the older runs are cancelled.
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#
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# Verified on this forge (Forgejo 16.0.5) in `ci-test` before being added here:
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# the key parses, and a newer push moves an older run to `cancelled` even while
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# it is still queued, which is the case that matters.
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#
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# `cancel-in-progress: true` also applies to `main`. That is deliberate and
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# safe here: main advances by merge commits whose tree contains the commits
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# before them, so the newer run covers the older one's changes.
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concurrency:
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group: ${{ github.workflow }}-${{ github.ref }}
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cancel-in-progress: true
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on:
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push:
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branches: [main]
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paths:
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- 'wai/wai-rs/src/neural/**'
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- 'wai/wai-rs/tests/neural_native_decode.rs'
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- 'wai/tools/wai_validate_synthetic.py'
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- '.github/workflows/wai-neural-e2e.yml'
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pull_request:
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paths:
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- 'wai/wai-rs/src/neural/**'
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- 'wai/wai-rs/tests/neural_native_decode.rs'
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- 'wai/tools/wai_validate_synthetic.py'
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- '.github/workflows/wai-neural-e2e.yml'
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jobs:
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neural-e2e:
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name: synthetic fixtures → Rust decode → reference (±4)
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runs-on: linux
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# The Rust decoders link `ort`, whose `download-binaries` feature pulls a
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# prebuilt static onnxruntime (1.28.0 for ort 2.0.0-rc.13). That library was
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# built against glibc >= 2.38 and GCC 13's libstdc++. The runner's default
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# job image, catthehacker/ubuntu:act-22.04, has glibc 2.35 and GCC 11, so the
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# test binary fails to LINK with five undefined symbols:
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# __isoc23_strtol __isoc23_strtoll __isoc23_strtoull (glibc 2.38+)
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# basic_string<char>::_M_replace_cold basic_string<wchar_t>::_M_replace_cold
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# (libstdc++, GCC 13+)
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# That link error is why this job failed at ~1 minute on every run: the
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# Python steps pass on a warm cache and the job dies at its last step. Checked
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# in both images: act-22.04 lacks all five, act-24.04 (glibc 2.39, g++ 13)
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# provides all five.
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container:
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image: catthehacker/ubuntu:act-24.04
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steps:
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- uses: actions/checkout@v5
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- uses: actions/setup-python@v5
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with:
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python-version: '3.11'
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- name: ML stack (CPU torch + torchvision + compressai + onnxruntime)
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run: |
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python -m pip install --upgrade pip
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# torch AND torchvision from the CPU index so their compiled ops match
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# (compressai imports torchvision; a mismatched build fails at
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# `torchvision::nms does not exist`).
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pip install torch torchvision --index-url https://download.pytorch.org/whl/cpu
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# `onnx` (the exporter) is separate from `onnxruntime` (the decoder).
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pip install compressai onnx onnxruntime numpy pillow
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- name: Build the synthetic fixtures (elic / mlicpp / snac / dcvc / glc)
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working-directory: wai
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run: python tools/wai_validate_synthetic.py --size 256
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# Bootstrap rustup: the docker runner image ships no Rust.
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- name: Install Rust 1.98.0
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run: |
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export PATH="$HOME/.cargo/bin:$PATH"
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command -v rustup >/dev/null 2>&1 || \
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curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --profile minimal --default-toolchain 1.98.0
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rustup toolchain install 1.98.0 --profile minimal
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rustup default 1.98.0
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echo "$HOME/.cargo/bin" >> "$GITHUB_PATH"
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- name: Each Rust decoder reproduces its reference end-to-end
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working-directory: wai/wai-rs
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# --no-default-features: the neural decoders need only `ort`, NOT the C
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# codec chain (AV1/JXL/opus), so the job needs no system codec deps.
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#
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# The grep is the assertion, not decoration. Every `*_matches_reference`
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# test opens with `if !wai.exists() || !ref.exists() || !model.exists() {
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# eprintln!("skipping ..."); return; }` — so a missing fixture makes the
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# test SKIP, and a skip is reported as a PASS. Verified by running this
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# exact command on a machine with no /tmp fixtures: it prints
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# "6 passed; 0 failed" while comparing nothing.
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#
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# That means a green `cargo test` here does NOT mean the decoders were
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# checked against their references. If the Python fixture step ever
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# succeeds while writing nothing, this job goes green having verified
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# nothing at all — the failure mode is silent and looks like success.
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# Failing on "skipping" is what makes the job's name true.
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#
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# One test is excluded by name, not tolerated as a skip:
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# `snac_real_model_matches_reference` needs real pretrained SNAC weights,
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# which this synthetic-fixture job never builds, so it would skip on every
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# run and the guard would fail a job whose five in-scope decoders all
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# match. Excluding it keeps the guard strict for everything in scope.
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run: |
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set -o pipefail
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cargo test --no-default-features --features neural --test neural_native_decode \
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-- _matches_reference --skip snac_real_model_matches_reference --nocapture \
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2>&1 | tee /tmp/neural_e2e.log
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if grep -q "skipping" /tmp/neural_e2e.log; then
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echo "::error::a reference comparison was SKIPPED — its fixtures are missing, so this job verified nothing"
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grep "skipping" /tmp/neural_e2e.log
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exit 1
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fi
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