NMS discards box when IoU == iou_threshold

🐛 Describe the bug

According to the doc of NMS [1], it discards all overlapping boxes with IoU > iou_threshold, so the box with IoU == iou_threshold should be kept. However, according to the following code snippet, it's not the case.

input_boxes = torch.tensor([[1., 1., 2., 3.], [0., 0., 2. , 2.]])
input_scores = torch.tensor([3., 2.])
# Two boxes should both be kept, but only one get kept.
torchvision.ops.nms(input_boxes, input_scores, iou_threshold=0.2)
# Verify the IoU is same as iou_threshold.
torchvision.ops.box_iou(torch.tensor([[1., 1., 2., 3.]]), torch.tensor([[0., 0., 2., 2.]]))

[1] https://pytorch.org/vision/main/generated/torchvision.ops.nms.html

Versions

Versions of relevant libraries:
[pip3] numpy==1.21.0
[pip3] torch==1.13.1
[pip3] torchvision==0.14.1
[conda] numpy 1.21.0 pypi_0 pypi
[conda] torch 1.13.1 pypi_0 pypi
[conda] torchvision 0.14.1 pypi_0 pypi

Start by reproducing the example with torchvision.ops.nms and torchvision.ops.box_iou using the versions listed in the issue. Trace the NMS behavior for an IoU exactly equal to iou_threshold and compare it with the documented strict-greater-than rule. Done means the boundary case keeps both boxes, with verification covering this example.