gemini-code-assist[bot] commented on PR #18652:
URL: https://github.com/apache/tvm/pull/18652#issuecomment-3732151693

   ## Summary of Changes
   
   Hello @guan404ming, I'm Gemini Code Assist[^1]! I'm currently reviewing this 
pull request and will post my feedback shortly. In the meantime, here's a 
summary to help you and other reviewers quickly get up to speed!
   
   This pull request significantly enhances the TVM Relax ONNX frontend by 
extending its support for the ONNX `Unique` operator. Previously, only the 
primary unique values output was handled, limiting the utility of the operator 
within TVM. With these changes, the frontend can now correctly parse and 
generate Relax expressions for all optional outputs of the `Unique` operator, 
including indices, inverse indices, and counts. This improvement allows for 
more complete and accurate ONNX model conversions involving the `Unique` 
operation, enabling broader compatibility and functionality within the TVM 
ecosystem.
   
   ### Highlights
   
   * **Expanded ONNX Unique Operator Support**: The TVM ONNX frontend now fully 
supports all four optional outputs of the ONNX Unique operator: unique values, 
indices, inverse indices, and counts.
   * **Dynamic Output Generation**: The `Unique._impl_v11` converter has been 
updated to dynamically determine and generate the requested optional outputs 
based on the `num_outputs` custom attribute.
   * **Unified Output Handling**: The converter now returns a `relax.Tuple` 
containing all requested outputs, ensuring proper type and shape inference for 
each.
   * **Comprehensive Testing**: New test cases have been added to 
`test_frontend_onnx.py` to validate the correct handling of `Unique` with 
varying numbers of optional outputs (1 to 4), including different `axis` and 
`sorted` parameters.
   
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