As usage increased, we started seeing more UNABLE_TO_LOCK_ROW errors. These rarely occurred earlier but are now fairly common during updates and integrations. The logic hasn’t changed much. I want to understand why locking becomes more frequent over time.
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Feature distributions look stable.But prediction quality is declining.Simple drift metrics don’t explain it.Something deeper seems wrong.
As more features are added, previously stable tests begin failing. These failures seem unrelated to recent changes. Maintaining tests now takes significant effort. I want to understand why this happens.
My GAN generates faces.But many look distorted or unnatural.Eyes and mouths appear in wrong positions.The training seems stable, but outputs are flawed.
The model produces grammatically correct text.But it keeps repeating the same phrases.The output never moves forward.It feels stuck in a loop?
unexpected truncation