masahi commented on a change in pull request #6314:
URL: https://github.com/apache/incubator-tvm/pull/6314#discussion_r473897729
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File path: tests/python/frontend/pytorch/test_forward.py
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@@ -1428,6 +1428,48 @@ def test_forward_upsample3d():
verify_model(torch.nn.Upsample(scale_factor=2, mode='trilinear',
align_corners=True).eval(), inp)
+def test_forward_nms():
+ """dynamic Non-Maximum Suppression"""
+ torch.set_grad_enabled(False)
+ class NonMaxSupression1(Module):
+ def forward(self, *args):
+ return torchvision.ops.nms(args[0], args[1], 0.3)
+
+ class NonMaxSupression2(Module):
+ def forward(self, *args):
+ from torchvision.ops import nms
+ return torchvision.ops.nms(args[0], args[1], 0.5)
+
+ class NonMaxSupression3(Module):
+ def forward(self, *args):
+ from torchvision.ops import nms
+ return torchvision.ops.nms(args[0], args[1], 0.9)
+
+ # Generate random input data
+ def _gen_rand_inputs(num_boxes):
+ box_len = 4
+ boxes = torch.rand(num_boxes, box_len, dtype=torch.float) * 0.5
+ boxes[:, 2] += boxes[:, 0]
+ boxes[:, 3] += boxes[:, 1]
+ scores = torch.rand(num_boxes, dtype=torch.float)
+ return boxes, scores
+
+ in_boxes, in_scores = _gen_rand_inputs(10)
+ scripted_model1 = torch.jit.trace(NonMaxSupression1(), [in_boxes,
in_scores])
+ verify_script_model(scripted_model1, [in_boxes.shape, in_scores.shape],
Review comment:
Running `verify_script_model` will run `torch.jit.script` on this traced
module. Although it does no harm for this test case, running `torch.jit.script`
on an output of `torch.jit.trace` doesn't make sense.
Please refactor `verify_script_model` appropriately to use VM executor with
traced models. `script_model` means the output of `torch.jit.script`, so don't
mixup tracing and scripting usage/terminology.
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