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support integer types in fast_tanh and fast_exp#18768

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tlopex merged 3 commits into
apache:mainfrom
jikechao:main
Feb 20, 2026
Merged

support integer types in fast_tanh and fast_exp#18768
tlopex merged 3 commits into
apache:mainfrom
jikechao:main

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@jikechao

@jikechao jikechao commented Feb 12, 2026

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Fix #18767.

This PR fixes the issue by adding explicit type casting in fast_tanh and fast_exp to convert integer inputs to float32.

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Summary of Changes

Hello @jikechao, I'm Gemini Code Assist1! 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 enhances the fast_tanh function by introducing a mechanism to automatically convert integer input tensors to float32. This change addresses a reported bug where the function failed to process integer types correctly, thereby broadening its compatibility and ensuring reliable operation across various numerical inputs without requiring manual type conversion from the user.

Highlights

  • Integer Type Support: Added explicit type casting within the fast_tanh function to convert integer (int and uint) input tensors to float32.
  • Bug Fix: Resolved an issue where fast_tanh did not correctly handle integer input types, preventing potential errors and improving function robustness.

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Changelog
  • python/tvm/topi/math.py
    • Added explicit type casting for integer and unsigned integer inputs to float32 in the fast_tanh function.
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  • No specific activity (comments, reviews, progress updates) has been recorded for this pull request yet.
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Code Review

The pull request correctly adds support for integer types in fast_tanh by casting them to float32, which aligns with the behavior of other mathematical functions in the library. The implementation is sound. I have a minor suggestion to improve the conciseness of the code.

Comment thread python/tvm/topi/math.py Outdated
y : tvm.te.Tensor
The result.
"""
if x.dtype.startswith('int') or x.dtype.startswith('uint'):

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medium

This condition can be made more concise. The startswith method can accept a tuple of strings to check for multiple prefixes.

Suggested change
if x.dtype.startswith('int') or x.dtype.startswith('uint'):
if x.dtype.startswith(('int', 'uint')):

Cast input tensor to float32 if its dtype is int or uint.
@jikechao jikechao changed the title support integer types in fast_tanh support integer types in fast_tanh and fast_exp Feb 12, 2026
@tlopex

tlopex commented Feb 19, 2026

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Could you fix the lint issue?

@jikechao

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Could you fix the lint issue?

I have fixed it. Could you help me review it again? Thanks a lot!

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LGTM Thanks!

@tlopex tlopex merged commit 9752557 into apache:main Feb 20, 2026
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Successfully merging this pull request may close these issues.

[Bug] Code generation fails when compiling topi.fast_tanh for int16 dtype with LLVM target

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