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improve stability of test_nms_cuda #2044

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11 changes: 10 additions & 1 deletion test/test_ops.py
Original file line number Diff line number Diff line change
Expand Up @@ -374,10 +374,14 @@ def _create_tensors_with_iou(self, N, iou_thresh):
# let b0 be [x0, y0, x1, y1], and b1 be [x0, y0, x1 + d, y1],
# then, in order to satisfy ops.iou(b0, b1) == iou_thresh,
# we need to have d = (x1 - x0) * (1 - iou_thresh) / iou_thresh
# Adjust the threshold upward a bit with the intent of creating
# at least one box that exceeds (barely) the threshold and so
# should be suppressed.
boxes = torch.rand(N, 4) * 100
boxes[:, 2:] += boxes[:, :2]
boxes[-1, :] = boxes[0, :]
x0, y0, x1, y1 = boxes[-1].tolist()
iou_thresh += 1e-5
boxes[-1, 2] += (x1 - x0) * (1 - iou_thresh) / iou_thresh
scores = torch.rand(N)
return boxes, scores
Expand All @@ -399,7 +403,12 @@ def test_nms_cuda(self):
r_cpu = ops.nms(boxes, scores, iou)
r_cuda = ops.nms(boxes.cuda(), scores.cuda(), iou)

self.assertTrue(torch.allclose(r_cpu, r_cuda.cpu()), err_msg.format(iou))
is_eq = torch.allclose(r_cpu, r_cuda.cpu())
if not is_eq:
# if the indices are not the same, ensure that it's because the scores
# are duplicate
is_eq = torch.allclose(scores[r_cpu], scores[r_cuda.cpu()])
self.assertTrue(is_eq, err_msg.format(iou))


class NewEmptyTensorTester(unittest.TestCase):
Expand Down