open-standards/.github/workflows/wai-neural-e2e.yml
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ci: thirteen WAI workflows run only when the pull request's own diff touches them
The forge matches a workflow's paths: against the push, not the pull request,
so merging main into a branch fired every path-filtered workflow whatever the
pull request changed. wai-pack and wai-web-reach already guarded against this
with scripts/pr-touches-paths.py; wai-conformance, wai-formal-verification,
wai-vector, wai-ops, wai-quantum-webgpu, conformance, wai-energy-receipts,
wai-byte-equality, wai-jpegai-e2e, wai-neural-e2e, wai-sota-vectors,
wai-neural-gates and wai-web-wasm now do too: a light job on linux-arm64
answers whether the pull request's diff touches the workflow's paths, and every
other job waits on it. A push to main, a schedule, or anything the script
cannot determine answers true.

Co-Authored-By: Claude Opus 5.5 <[email protected]>
2026-10-14 03:41:49 -04:00

150 lines
7.6 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:
push:
branches: [main]
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'
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'
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-arm64
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