ReduceMax/ReduceMin over-propagates NaN — returns NaN for rows where non-NaN value should win

### What happened? ## Expected behavior For `ReduceMax([[NaN, 1.0], [2.0, NaN]], axis=1)`: - Row 0 `[NaN, 1.0]`: NaN is present → result should be NaN (per ORT) - Row 1 `[2.0, NaN]`: non-NaN value 2.0 should dominate → result should be 2.0 (per ORT) Expected: `[NaN, 2.0]` ## Actual behavior IREE returns `[NaN, NaN]` — NaN infects row 1 even though it has a valid non-NaN maximum. ``` Input: [[nan 1.] [ 2. nan]] ReduceMax(axis=1): ORT: [nan 2.] IREE: [nan nan] ReduceMin(axis=1): ORT: [nan 2.] IREE: [nan nan] ``` ## Root cause The linalg reduction lowering uses `arith.maximumf` / `arith.minimumf` with IEEE 754 NaN-propagation semantics (NaN always propagates), whereas ORT uses a semantics where the valid non-NaN value wins over NaN when NaN is not the only element. Interestingly, TVM has the **opposite** bug: TVM **under-propagates** NaN (`ReduceMax([NaN, 1.0]) → 1.0`), using `fmax` semantics where NaN is treated as missing. Both diverge from ORT, but in opposite directions. ## Note While the ONNX spec is not fully normative on NaN behavior in reductions, ONNX Runtime handles it consistently and this divergence can cause silent numerical differences when switching runtimes. ### Steps to reproduce your issue ## Reproduction ```python import numpy as np import onnx from onnx import helper, TensorProto x = np.array([[np.nan, 1.0], [2.0, np.nan]], dtype=np.float32) X = helper.make_tensor_value_info("X", TensorProto.FLOAT, [2, 2]) Y = helper.make_tensor_value_info("Y", TensorProto.FLOAT, [2]) node = helper.make_node("ReduceMax", ["X"], ["Y"], axes=[1], keepdims=0) graph = helper.make_graph([node], "main", [X], [Y]) model = helper.make_model(graph, opset_imports=[helper.make_opsetid("", 13)]) model = onnx.shape_inference.infer_shapes(model) # Run through IREE pipeline (see full reproducer script) ``` Full reproducer: `iree_bug_018_reducemax_nan.py` ### What component(s) does this issue relate to? _No response_ ### Version information ## Environment - iree-base-compiler: 3.12.0rc20260515 - iree-base-runtime: 3.12.0rc20260515 - Python: 3.11 - OS: Linux ### Additional context _No response_