def create_lazy_tensor(self):
tensor = torch.randn(4, 3, 5, 2)
diag = torch.tensor([[1.0, 2.0, 4.0, 2.0, 3.0],
[2.0, 1.0, 2.0, 1.0, 4.0],
[1.0, 2.0, 2.0, 3.0, 4.0]]).repeat(4, 1, 1)
lt = LowRankRootLazyTensor(tensor).add_diag(diag)
assert isinstance(lt, LowRankRootAddedDiagLazyTensor)
return lt
def create_lazy_tensor(self):
root = torch.randn(4, 3, 5, 2)
return LowRankRootLazyTensor(root)
def create_lazy_tensor(self):
root = torch.randn(3, 1, requires_grad=True)
return LowRankRootLazyTensor(root)
def create_lazy_tensor(self):
tensor = torch.randn(5, 2)
diag = torch.tensor([1.0, 2.0, 4.0, 2.0, 3.0])
lt = LowRankRootLazyTensor(tensor).add_diag(diag)
assert isinstance(lt, LowRankRootAddedDiagLazyTensor)
return lt