Files
ruvnet--RuView/.github/workflows/verify-pipeline.yml
T
ruv 2d2b16a458 diag(proof): make hash precision configurable + CI cross-microarch sweep
verify.py's HASH_QUANTIZATION_DECIMALS is now overridable via
PROOF_HASH_DECIMALS. Finding: the determinism divergence is NOT
Windows-vs-Linux — Windows and a second Linux box (ruvultra, same
numpy/scipy) produce identical hashes at every precision, including
ca58956c at 6 decimals. Only the GitHub Azure CI runner diverges
(667eb054), i.e. a CPU-microarchitecture pocketfft/BLAS reordering
(the #560 Skylake-vs-Cascade-Lake class).

Temporary diagnostic sweep step prints the CI runner's hash at decimals
6..2 so we can pick the coarsest precision that collapses the
microarch divergence to the common hash. Both the sweep step and the
PROOF_HASH_DECIMALS plumbing are removed/finalized in the follow-up.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-05-31 11:58:24 -04:00

139 lines
5.2 KiB
YAML

name: Verify Pipeline Determinism
on:
push:
branches: [ main, master, 'claude/**' ]
paths:
- 'archive/v1/src/core/**'
- 'archive/v1/src/hardware/**'
- 'archive/v1/data/proof/**'
- 'archive/v1/requirements-lock.txt'
- '.github/workflows/verify-pipeline.yml'
pull_request:
branches: [ main, master ]
paths:
- 'archive/v1/src/core/**'
- 'archive/v1/src/hardware/**'
- 'archive/v1/data/proof/**'
- 'archive/v1/requirements-lock.txt'
- '.github/workflows/verify-pipeline.yml'
workflow_dispatch:
jobs:
verify-determinism:
name: Verify Pipeline Determinism
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.11']
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v6
with:
python-version: ${{ matrix.python-version }}
- name: Install pinned dependencies
run: |
python -m pip install --upgrade pip
pip install -r archive/v1/requirements-lock.txt
- name: Verify reference signal is reproducible
run: |
echo "=== Regenerating reference signal ==="
python archive/v1/data/proof/generate_reference_signal.py
echo ""
echo "=== Checking data file matches committed version ==="
# The regenerated file should be identical to the committed one
# (We compare the metadata file since data file is large)
python -c "
import json, hashlib
with open('archive/v1/data/proof/sample_csi_meta.json') as f:
meta = json.load(f)
assert meta['is_synthetic'] == True, 'Metadata must mark signal as synthetic'
assert meta['numpy_seed'] == 42, 'Seed must be 42'
print('Reference signal metadata validated.')
"
- name: Quantization sweep (diagnostic — cross-microarch precision)
working-directory: archive/v1
env:
OMP_NUM_THREADS: "1"
OPENBLAS_NUM_THREADS: "1"
MKL_NUM_THREADS: "1"
VECLIB_MAXIMUM_THREADS: "1"
NUMEXPR_NUM_THREADS: "1"
run: |
for d in 6 5 4 3 2; do
h=$(PROOF_HASH_DECIMALS=$d python data/proof/verify.py --generate-hash 2>/dev/null | grep -i 'Computed:' | sed 's/.*Computed:[[:space:]]*//')
echo "SWEEP d=$d $h"
done
- name: Run pipeline verification
working-directory: archive/v1
env:
# Pin thread count for scipy.fft / BLAS — multi-threaded reduction
# order is otherwise non-deterministic across CI runs (issue #560
# follow-up: 9- and 6-decimal quantization were not enough because
# the divergence is from threading order, not SIMD reordering).
# Single-threaded keeps the proof reproducible at a ~2-3x slowdown.
OMP_NUM_THREADS: "1"
OPENBLAS_NUM_THREADS: "1"
MKL_NUM_THREADS: "1"
VECLIB_MAXIMUM_THREADS: "1"
NUMEXPR_NUM_THREADS: "1"
run: |
echo "=== Running pipeline verification ==="
python data/proof/verify.py
echo ""
echo "Pipeline verification PASSED."
- name: Run verification twice to confirm determinism
working-directory: archive/v1
env:
OMP_NUM_THREADS: "1"
OPENBLAS_NUM_THREADS: "1"
MKL_NUM_THREADS: "1"
VECLIB_MAXIMUM_THREADS: "1"
NUMEXPR_NUM_THREADS: "1"
run: |
echo "=== Second run for determinism confirmation ==="
python data/proof/verify.py
echo "Determinism confirmed across multiple runs."
- name: Check for unseeded np.random in production code
run: |
echo "=== Scanning for unseeded np.random usage in production code ==="
# Search for np.random calls without a seed in production code
# Exclude test files, proof data generators, and known parser placeholders
VIOLATIONS=$(grep -rn "np\.random\." archive/v1/src/ \
--include="*.py" \
--exclude-dir="__pycache__" \
| grep -v "np\.random\.RandomState" \
| grep -v "np\.random\.seed" \
| grep -v "np\.random\.default_rng" \
| grep -v "# placeholder" \
| grep -v "# mock" \
| grep -v "# test" \
|| true)
if [ -n "$VIOLATIONS" ]; then
echo ""
echo "WARNING: Found potential unseeded np.random usage in production code:"
echo "$VIOLATIONS"
echo ""
echo "Each np.random call should either:"
echo " 1. Use np.random.RandomState(seed) or np.random.default_rng(seed)"
echo " 2. Be in a test/mock context (add '# placeholder' comment)"
echo ""
# Note: This is a warning, not a failure, because some existing
# placeholder code in parsers uses np.random for mock data.
# Once hardware integration is complete, these should be removed.
echo "WARNING: Review the above usages. Existing parser placeholders are expected."
else
echo "No unseeded np.random usage found in production code."
fi