[BugFix][Arith] Reject padded IterMapSimplify fallback

[zupengwang]

Fixes #19524.

Problem

When predicate-aware iter-map detection fails, IterMapSimplify retries detection without the predicate. The retry can introduce iterator padding, but the API returns only simplified expressions and drops the fallback's padding_predicate.

FlattenBuffer can therefore consume a non-equivalent flattened index. In the conv2d_transpose reproducer from #19524, scheduled TIR contains (index - 1) // 2, while the affected path generated a shifted CUDA address and silently read out of bounds.

Change

• Accept the predicate-free fallback only when it requires no iterator padding.
• Preserve the original expression when the fallback would need a padding predicate.
• Cover both sides of the decision: an unpadded fallback still simplifies, while a padded fallback is rejected.

Validation

Base: apache/tvm@4e9a099d154d7c4644a40a1a9c00b8873226468e

Environment: NVIDIA RTX 3090 (SM86), CUDA 13.0 (nvcc 13.0.48), GCC 11.5.0, CMake 4.4.2, TVM 0.26.dev0.

• CUDA-enabled build: 589/589 targets built.
• python -m pytest tests/python/arith/test_arith_iter_affine_map.py -q: 44 passed.
• python -m pytest tests/python/relax/test_transform_legalize_ops_nn.py::test_conv2d_transpose tests/python/relax/test_op_nn_convolution.py::test_conv2d_transpose_wrong_output_padding -q: 2 passed.
• Scoped pre-commit checks on both changed files: all passed, including Ruff and clang-format 20.1.8.
• git diff --check: passed.

GPU correctness experiment used 14 conv2d_transpose cases (H=4..10, output_padding in {0, 1}), with PyTorch F.conv_transpose2d as the oracle:

Revision	Failing cases	Worst max absolute error
Base	5 / 14	0.3841745257
This change	0 / 14	7.4505806e-08

Risk

For predicates that iter-map detection cannot parse, padded fallback mappings now retain their original expressions instead of being simplified. This is deliberately conservative and may reduce simplification in those cases; unpadded fallbacks keep the existing behavior.

Not run locally

The full upstream arm, cpu, docker, gpu, and wasm CI matrices were not run locally.