gemini-code-assist[bot] commented on PR #18390:
URL: https://github.com/apache/tvm/pull/18390#issuecomment-3441440982

   ## Summary of Changes
   
   Hello @jikechao, 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 introduces a crucial enhancement to the `tvm.tir.exp` 
operator, enabling it to seamlessly process integer input types. Previously, 
attempting to use integer inputs with `tir.exp` would lead to an 
`InternalError` during LLVM code generation due to the underlying `llvm.exp` 
intrinsic expecting floating-point values. The implemented solution 
automatically casts integer inputs to `float64`, ensuring robust and consistent 
behavior, and bringing `tir.exp`'s functionality in line with established deep 
learning frameworks.
   
   ### Highlights
   
   * **Integer Type Support for tir.exp**: The `tvm.tir.exp` operator now 
correctly handles integer input types, resolving an `InternalError` during LLVM 
code generation.
   * **Automatic Type Conversion**: Integer inputs are implicitly converted to 
`float64` before the exponential operation, ensuring compatibility with the 
underlying `llvm.exp` intrinsic.
   * **Behavior Alignment**: This change aligns `tir.exp`'s behavior with other 
popular libraries like PyTorch and NumPy, which also perform implicit type 
conversion for exponential functions.
   
   
   
   
   
   
   
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