viiccwen opened a new issue, #19974:
URL: https://github.com/apache/tvm/issues/19974

   ### Expected behavior
   
   The Relax ONNX frontend should preserve ONNX integer `Div` semantics. ONNX 
defines
   integer `Div` as truncating division, rounding toward zero.
   
   This behavior should hold both for constant tensors and for shape-derived 
scalar
   values represented as Relax/TIR primitive expressions.
   
   ### Actual behavior
   
   When an ONNX `Div` has integer inputs and one input is a shape-derived 
`PrimExpr`,
   the importer can fold it through NumPy floating-point division. This 
produces a
   floating-point TIR value such as `T.float64(128.67676767)` instead of an
   integer value such as `T.int64(128)`.
   
   If that result is then used as a slice bound or another index value, Relax 
import
   can fail because the downstream operator expects an integer primitive 
expression.
   
   One failing pattern is:
   
   ```text
   Shape -> Gather -> Div -> Slice
   ```
   
   where the `Div` result is used as the `end` argument of `Slice`.
   
   ### Environment
   
   - Component: Relax ONNX frontend
   - Affected file: `python/tvm/relax/frontend/onnx/onnx_frontend.py`
   - Reproduced with a local TVM checkout using the Python ONNX frontend tests
   
   ### Steps to reproduce
   
   Create a graph where `Shape(x)[0]` is divided by an `int64` constant and 
used as a
   `Slice` bound:
   
   ```text
   x: float32[386]
   Shape(x) -> Gather(axis=0) -> Div(3) -> Slice(x, starts=[0], ends=[Div 
result])
   ```
   
   The importer may fail with an error similar to:
   
   ```text
   relax.strided_slice requires the end argument to be a tuple of int64 
PrimExpr values
   ...
   the end argument (T.float64(128.66666666666666),) has type T.Tuple(T.float64)
   ```
   
   ### Triage
   
   * needs-triage
   * type: bug
   * relax
   * frontend: onnx


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