gemini-code-assist[bot] commented on code in PR #19626:
URL: https://github.com/apache/tvm/pull/19626#discussion_r3312057314
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python/tvm/relax/frontend/onnx/onnx_frontend.py:
##########
@@ -1104,6 +1104,20 @@ def _impl_v13(cls, bb, inputs, attr, params):
return relax.const(output, to_type)
if isinstance(inputs[0], relax.PrimValue):
return relax.PrimValue(inputs[0].value.astype(to_type))
+
+ try:
+ np_dst = _np.dtype(str(to_type))
+ except Exception:
+ return relax.op.astype(inputs[0], to_type)
+
+ if np_dst.kind in ("i", "u"):
+ src = inputs[0]
+ src_dtype = getattr(getattr(src, "struct_info", None), "dtype",
None) or getattr(src, "dtype", None)
+ if src_dtype is not None and
_relax_dtype_is_floating_point(src_dtype):
+ bad = relax.op.logical_or(relax.op.isnan(src),
relax.op.isinf(src))
Review Comment:
We can simplify the check for non-finite values (NaN and Inf) by using
`relax.op.logical_not(relax.op.isfinite(src))`. This avoids one extra operator
call (`logical_or` of `isnan` and `isinf`) and simplifies the generated Relax
graph.
```suggestion
bad = relax.op.logical_not(relax.op.isfinite(src))
```
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