pytorch autograd_error ai_generated true

RuntimeError: shared parameter found with different gradients

ID: pytorch/parameter-sharing-error

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80%Fix Rate
84%Confidence
3Evidence
2023-01-01First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
2 active — — —

Root Cause

Parameter sharing causes gradient accumulation issues.

generic

Workarounds

  1. 88% success Use weight tying properly: decoder.weight = encoder.weight
  2. 90% success Ensure optimizer receives only unique parameters: set(model.parameters())

Dead Ends

Common approaches that don't work:

  1. Clone all shared parameters 78% fail

    Doubles memory, breaks weight tying

  2. Ignore gradient warnings 75% fail

    Incorrect gradient updates