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fix: resolve open CodeQL alerts (float widening, workflow permissions) #22

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Merged
mstrathman merged 2 commits into from
Aug 3, 2026
Merged

fix: resolve open CodeQL alerts (float widening, workflow permissions) #22

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8c8f6ea
fix: resolve open CodeQL alerts (float widening, workflow permissions)
mstrathman Aug 2, 2026
55d6e2e
docs: narrow the changelog precision claim
mstrathman Aug 3, 2026
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5 changes: 5 additions & 0 deletions .github/workflows/wheels.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,11 @@ on:
tags: ["v*"]
workflow_dispatch:

# Default the GITHUB_TOKEN to read-only; the publish job opts into
# id-token: write for PyPI OIDC and nothing else needs write.
permissions:
contents: read

# Builds the Python wheels (`pip install sqlite-predict`). Each wheel bundles the
# zero-dependency loadable compiled for its platform. Staging runs `make
# python-src` on the host to drop the amalgamation + SQLite ext headers into the
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10 changes: 10 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -6,6 +6,16 @@ project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [Unreleased]

### Fixed

- **Forest prediction accumulates the learning-rate product in double**, matching
the trainer. The serving path multiplied the learning rate by a tree value as
`float * float` before widening to the `double` accumulator, which could
overflow to infinity (and, under x87 excess precision, differ by platform)
before the widening. The product and the forest accumulation are now computed in
double (individual tree values are still `f32`); served predictions may shift in
their least-significant digits.

## [0.2.0] - 2026-07-31

### Changed
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8 changes: 6 additions & 2 deletions predict-student.c
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Expand Up @@ -276,7 +276,10 @@ int predict0_forest_predict_row(const Forest *f, const f32 *x, f64 *scbuf, char
if (f->task == 1) {
f64 s = f->init[0];
for (int j = 0; j < f->n_trees; j++)
s += f->lr * forest_tree_value(f, j, x);
/* (f64) before the multiply: keep the product in double, matching the
* trainer (predict-train.c), so a float*float never overflows or picks up
* platform-dependent excess precision before it reaches the accumulator. */
s += (f64)f->lr * forest_tree_value(f, j, x);
*has_conf = 0;
*pred = sqlite3_mprintf("%.17g", s);
return *pred ? SQLITE_OK : SQLITE_NOMEM;
Expand All @@ -285,7 +288,8 @@ int predict0_forest_predict_row(const Forest *f, const f32 *x, f64 *scbuf, char
scbuf[c] = f->init[c];
for (int r = 0; r < f->n_rounds; r++)
for (int s = 0; s < f->n_score; s++)
scbuf[s] += f->lr * forest_tree_value(f, r * f->n_score + s, x);
/* (f64) before the multiply, as above and in the trainer */
scbuf[s] += (f64)f->lr * forest_tree_value(f, r * f->n_score + s, x);
f64 mx = scbuf[0];
int arg = 0;
for (int c = 1; c < f->n_score; c++)
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