This attention code runs clean with correct shapes—yet one bug silently breaks what the model learns
cneuralnetwork · x · 2026-10-30
A spot-the-bug challenge: an attention implementation runs without errors and produces correct output shapes, but hides a single bug that completely changes what the model learns. The author challenges readers to find it—an example of the most dangerous class of deep learning bugs: silent, non-crashing mistakes that quietly invalidate training results.
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