PyTorchAbout 4 min read
Diagnose missing gradients and unchanged parameters
Separate registration, graph participation, gradient accumulation, and optimizer membership before changing a learning rate.
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PyTorch โ Technical solutions
Find a clear diagnosis before you change anything. Each guide explains the symptoms, likely causes, a contextual solution and how to verify the result.
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PyTorchAbout 3 min read
Trace shape, broadcasting, and attention-mask errors
Inspect unreduced dimensions and allowed dependencies before trusting a plausible scalar loss or attention output.
Read solutionPyTorchAbout 3 min read
Investigate restored-model state and mode disagreement
Trace named state, snapshots, input meaning, and evaluation mode before trusting a successful load.
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