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Short sequences work fine.Longer sequences cause GPU crashes.No code changes were made.Only input size increased.
Records update repeatedly without obvious loops. I want to understand why recursion happens.
Nothing changed in the code logic.Only the ML framework version was upgraded.Yet predictions shifted slightly.This caused unexpected regressions?
My model gives great accuracy on my laptop.When deployed on a server, predictions become inconsistent.The same input sometimes produces different outputs.Nothing crashes, but the behavior is unreliable.
