gemini-code-assist[bot] commented on PR #18421:
URL: https://github.com/apache/tvm/pull/18421#issuecomment-3489649231

   ## Summary of Changes
   
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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 `step` attribute to the `ForNode` in TVM's 
Tensor IR (TIR), enabling the representation and generation of loops with 
non-unit iteration steps. This foundational change impacts various components, 
from the core IR definition and Python scripting interface to code generation 
backends and scheduling primitives, ensuring that loops with custom steps are 
correctly parsed, lowered, and compiled across TVM.
   
   ### Highlights
   
   * **New `step` attribute for `ForNode`**: Introduced an optional `step` 
attribute to the `ForNode` in TVM's Tensor IR (TIR), allowing loops to iterate 
with non-unit steps (e.g., `for i in range(0, 100, 3)`).
   * **Python API and Scripting Support**: Updated the Python 
`tvm.script.ir_builder.tir` module to accept `step` arguments for `serial`, 
`parallel`, `vectorized`, and `unroll` loop types. The `tvm.script.parser.tir` 
now handles Python's `range` sugar with a `step` argument, mapping it to the 
new TIR `step` attribute.
   * **Code Generation Updates**: Modified various code generation backends 
(LLVM, C, WebGPU, SPIRV) to correctly interpret and generate code for loops 
that include a custom `step` value. This ensures that the new loop semantics 
are respected during compilation.
   * **TIR Schedule and Transform Compatibility**: Adjusted numerous TIR 
scheduling primitives and transformation passes to either propagate the new 
`step` attribute or utilize the newly introduced `For::ForSimple` constructor, 
which implicitly assumes a trivial (unit) step. This maintains compatibility 
and correctness across the TIR pipeline.
   * **New Utility and Tests**: Added a `HasTrivialStep()` method to `ForNode` 
for easier checking of unit steps. New test cases were introduced in 
`test_tir_nodes.py` and `test_tvmscript_parser_tir.py` to validate the 
functionality of loops with custom steps.
   
   
   
   
   
   
   
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