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_r393317839
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File path: tests/python/frontend/pytorch/test_forward.py
##########
@@ -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)
+
+
+def test_conv3d():
+ inp = torch.rand((1, 32, 16, 16, 16))
+ verify_model(torch.nn.Conv3d(32, 16, (3, 3, 3),
+ padding=(1, 1, 1)).eval(),
+ inp),
+ verify_model(torch.nn.Conv3d(32, 16, (5, 5, 5),
+ padding=(2, 2, 2)).eval(),
+ inp),
+ verify_model(torch.nn.Conv3d(32, 16, kernel_size=1).eval(),
+ inp)
+ # downsample
+ verify_model(torch.nn.Conv3d(32, 16, kernel_size=1, stride=2).eval(),
Review comment:
added more tests
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