#2760
84%
main: 84%

Ran 07 Aug 2026 02:48AM UTC

Jobs 1

Files 39

Run time 1min

Badge

Embed ▾

Committed 07 Aug 2026 02:42AM UTC coverage: 83.571%. First build

Build # #2760

Build Type

Pull #866

github

Committed by

khatchad

Commit Message

Add the implicitly-cast NumPy argument fixture and probe scaffold

Reduces [linear_regression from #861 Case 1](https://github.com/ponder-lab/Hybridize-Functions-Refactoring/issues/861): a float32 module-scope variable combined with a float64 NumPy call-site argument. All three subject behaviors reproduce on the reduction under TF 2.9.3: undecorated runs (float32), a bare decorator raises the Mul dtype TypeError, and a signature pinned to the variable's dtype runs and matches eager. The scaffold test asserts candidacy only; its assertions harden when the eager-effective dtype detector lands. The analysis currently types the parameter float64 with shape [10] while the scalar-initialized variables stay dtype-unknown ([wala/ML#827](https://github.com/wala/ML/issues/827) tracks the initializer derivation).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01AM8pvSeP5UqDyyTn9h5E2P

Pull Request Pull Request #866: Pin or decline on eager-effective dtype for NumPy arguments

Coverage Stats

3052 of 3652 relevant lines covered (83.57%)

0.84 hits per line

Jobs

ID	Job ID	Ran	Files	Coverage
1	#2760.1	07 Aug 2026 02:48AM UTC	39	83.57

ponder-lab / Hybridize-Functions-Refactoring / #2760
84%
main: 84%

README BADGES
x

Markdown

Textile

RDoc

HTML

Rst

Jobs

Source Files on build #2760

ponder-lab / Hybridize-Functions-Refactoring / #2760 84% main: 84%

README BADGES x

Markdown

Textile

RDoc

HTML

Rst

Jobs

Source Files on build #2760

ponder-lab / Hybridize-Functions-Refactoring / #2760
84%
main: 84%

README BADGES
x