[Bug] [ONNX][FRONTEND] - Loop and NonMaximalSupression operators missing

[Mathevilg]

When converting ONNX models that contain dynamic control flow (e.g., the Loop operator) or post-processing operations such as NonMaxSuppression using TVM's Relax ONNX frontend, the conversion fails with the following error:

tvm.error.OpNotImplemented: The following operators are not supported for frontend ONNX: Loop, NonMaxSuppression

This issue prevents conversion of models such as YOLOv3/YOLOv5 that include these operators. It appears that the Relax ONNX frontend does not currently implement these operators.

Steps to Reproduce:
Export a YOLO model (or any model containing Loop and/or NonMaxSuppression) to ONNX.
Load the ONNX model using TVM's Relax ONNX frontend:

import onnx
import tvm.relax as relax

onnx_model = onnx.load("path/to/model.onnx")
shape_dict = {"input": (1, 3, 640, 640)}
mod, params = relax.frontend.from_onnx(onnx_model, shape_dict)

Expected Behavior: Either these operators should be supported by the ONNX Relax frontend, or the frontend should provide a clear message or workaround (such as lowering them to supported operators) so that users can convert their models.

Environment:

TVM Version: 19
Model: YOLO model onnx - https://github.com/onnx/models/tree/main/validated/vision/object_detection_segmentation/yolov3

Additional Info: The issue appears when converting models that rely on dynamic control flow or include post-processing operators like Loop and NonMaxSuppression.

Additional Context: This issue was encountered while attempting to convert a YOLO model to TVM Relax IR. Any guidance or workarounds on handling these operators would be greatly appreciated.

cc @KJlaccHoeUM9l