## Summary
Add `relax.vision.get_valid_counts` and classic
`relax.vision.non_max_suppression` for object-detection post-processing
pipelines.
`get_valid_counts` performs score-based bounding box filtering and
compacts valid boxes to the front of each batch. Classic
`non_max_suppression` performs flexible IoU-based suppression on
filtered boxes, complementing existing `all_class_non_max_suppression`
for custom post-processing workflows.
This PR implements the Relax-level registration, legalization, TOPI
compute, and test coverage for both operators.
## Changes
**Relax op registration and legalization:**
- C++ op functions, FFI registration, and struct info inference for both
operators (`vision.h`, `vision.cc`)
- Python wrappers with Relax docstrings (`vision.py`)
- Legalization to `topi.vision.get_valid_counts` and
`topi.vision.non_max_suppression`
- Additional struct-info validation for `score_index`, `id_index`, and
`coord_start` when `elem_length` is statically known
**TOPI and testing:**
- Full TOPI implementation for `get_valid_counts`
- Reimplementation of classic `non_max_suppression` in TOPI
- NumPy reference implementations in `tvm.topi.testing` for both
operators
- Op-level tests for struct info inference, legalization, invalid
attribute ranges, and e2e numerical correctness
- Stronger legalization tests that verify both `relax.call_tir`
introduction and removal of the original Relax vision op
## Limitations
- Attribute range validation for `score_index`, `id_index`, and
`coord_start` is only enforced when the input `elem_length` is
statically known during struct-info inference.
- Classic `non_max_suppression` follows the existing Relax / TOPI API
shape and is intended for single-class or class-aware custom
post-processing flows, distinct from `all_class_non_max_suppression`.
## Validation
```bash
pytest tests/python/relax/test_op_vision.py -k "get_valid_counts" -v
pytest tests/python/relax/test_op_vision.py -k "test_nms_" -v
```
All related tests passed.
ConvolutedDog