masahi commented on a change in pull request #5075: [Torch] Add initial 3D op
support and test on Resnet 3D
URL: https://github.com/apache/incubator-tvm/pull/5075#discussion_r393317483
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File path: tests/python/frontend/pytorch/test_forward.py
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@@ -708,6 +701,31 @@ def forward(self, x):
verify_model(ToInt().eval(), torch.tensor(2.0))
+def test_adaptive_pool3d():
+ inp = torch.rand((1, 32, 16, 16, 16))
+ verify_model(torch.nn.AdaptiveMaxPool3d((1, 1, 1)).eval(), inp)
+ verify_model(torch.nn.AdaptiveMaxPool3d((2, 2, 2)).eval(), inp)
+ verify_model(torch.nn.AdaptiveAvgPool3d((1, 1, 1)).eval(), inp)
+ verify_model(torch.nn.AdaptiveAvgPool3d((2, 2, 2)).eval(), inp)
+ verify_model(torch.nn.AdaptiveAvgPool3d((4, 8, 8)).eval(), inp)
+ verify_model(torch.nn.AdaptiveMaxPool3d((7, 8, 9)).eval(), inp)
Review comment:
Added two more input shapes. Since video use case seems to be more common,
the new input shape has the depth dimension different than height/width.
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