Joshua Shay Kricheli NeuroSymbolic AI
v2 v1

Release · v3.11.9

Gate FD-gradient check on magnitude, not…

test(tpp): gate FD-gradient check on magnitude, not non-portable bit-exactness

test v3.11.9 July 7, 2026 Claude 66c4ced

Details

Wiring the TPP suite into CI surfaced a portability gap in the pre-existing
"FD gradient + objective are bit-exact vs scipy" test: it asserted all-but-one
bit-identical gradient components, but the runner's libm differs from the
machine the goldens were captured on, and the 2-point finite-difference quotient
amplifies each V8-vs-glibc `pow` ULP difference (16/20 exact on the CI runner vs
19/20 locally). The magnitude bounds (objective ≤1e-15, gradient ≤1e-4 relative)
are the portable correctness guarantee and still hold everywhere, so assert
those and log the bit-exact counts for insight instead of asserting them.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Dqq3yLFbZnaCYwTcZZEZRU

Files changed (1)

frontend/client/tests/tpp-core.test.mjs +9 −5