masahi commented on a change in pull request #4961: [Torch] Upsampling op
support and enable registering a user defined op conversion map
URL: https://github.com/apache/incubator-tvm/pull/4961#discussion_r385946326
##########
File path: tests/python/frontend/pytorch/test_forward.py
##########
@@ -677,9 +666,29 @@ def forward(self, *args):
chunks = args[0].chunk(7, 2)
return torch.cat(chunks, 2)
- with torch.no_grad():
- input_data = torch.rand(input_shape).float()
- verify_model(Chunk1().float().eval(), input_data=input_data)
+ input_data = torch.rand(input_shape).float()
+ verify_model(Chunk1().float().eval(), input_data=input_data)
+
+def test_upsample():
+ class Upsample(nn.Module):
+ def __init__(self, size=None, scale=None,
+ mode="nearest", align_corners=None):
+ super().__init__()
+ self.size = size
+ self.scale = scale
+ self.mode = mode
+ self.align_corners = align_corners
+
+ def forward(self, x):
+ return nn.functional.interpolate(x, size=self.size,
+ scale_factor=self.scale,
+ mode=self.mode,
+ align_corners=self.align_corners)
+ inp = torch.rand((1, 3, 32, 32))
+ verify_model(Upsample(size=(64, 64), mode="nearest"), inp)
+ verify_model(Upsample(scale=2, mode="nearest"), inp)
+ verify_model(Upsample(size=(64, 64), mode="bilinear", align_corners=True),
inp)
+ verify_model(Upsample(scale=2, mode="bilinear", align_corners=True), inp)
Review comment:
added
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