LudovicoYIN commented on PR #19634:
URL: https://github.com/apache/tvm/pull/19634#issuecomment-4571344781

   Thanks for the detailed review. I updated the sequence recurrent converters 
to address the correctness issues you pointed out.
   
   1. For both sequence LSTM converters, the fused activation is now applied on 
the internal cell path rather than as a post-activation on the final hidden 
state. I also fixed the `time_major=True` layout handling so the output 
preserves `[time, batch, ...]`.
   
   2. For unsupported optional inputs, the converters now explicitly raise 
`OpNotImplemented` instead of silently ignoring peephole / projection / 
layer-norm / aux-input variants.
   
   I also strengthened the tests:
   - `BIDIRECTIONAL_SEQUENCE_RNN` now uses the full 12-input form
   - `BIDIRECTIONAL_SEQUENCE_LSTM` now uses the full 48-input form
   - added `time_major=True` regression coverage
   - added unsupported-input rejection tests
   - added stronger equation/activation-level checks for the recurrent lowering


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