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x = torch.randn(3, 4, requires_grad=True)
self.assertONNX(lambda x: torch.full(x.shape, 2), x)
+ @skipIfCI
def test_full_like(self):
x = torch.randn(3, 4, requires_grad=True)
self.assertONNX(lambda x: torch.full_like(x, 2), x)
x = torch.randn(3, 4)
self.assertONNX(torch.nn.Linear(4, 5, bias=True), x)
+ @skipIfCI
def test_zeros_like(self):
x = torch.randn(5, 8, requires_grad=True)
self.assertONNX(lambda x: torch.zeros_like(x), x)
+ @skipIfCI
def test_ones_like(self):
x = torch.randn(6, 10, requires_grad=True)
self.assertONNX(lambda x: torch.ones_like(x), x)