def create_lazy_tensor(self):
mat1 = make_random_mat(40, rank=5, batch_size=2)
mat2 = make_random_mat(40, rank=5, batch_size=2)
mat3 = make_random_mat(40, rank=5, batch_size=2)
mat4 = make_random_mat(40, rank=5, batch_size=2)
mat5 = make_random_mat(40, rank=5, batch_size=2)
res = MulLazyTensor(RootLazyTensor(mat1), RootLazyTensor(mat2),
RootLazyTensor(mat3), RootLazyTensor(mat4),
RootLazyTensor(mat5))
return res.add_diag(torch.tensor(0.5))
def create_lazy_tensor(self):
mat1 = make_random_mat(30, 3)
mat2 = make_random_mat(30, 3)
mat3 = make_random_mat(30, 3)
mat4 = make_random_mat(30, 3)
mat5 = make_random_mat(30, 3)
res = MulLazyTensor(RootLazyTensor(mat1), RootLazyTensor(mat2),
RootLazyTensor(mat3), RootLazyTensor(mat4),
RootLazyTensor(mat5))
return res.add_diag(torch.tensor(1.0))
def create_lazy_tensor(self):
mat1 = make_random_mat(6, rank=5, batch_size=2)
mat2 = make_random_mat(6, rank=5, batch_size=2)
res = MulLazyTensor(RootLazyTensor(mat1), RootLazyTensor(mat2))
return res.add_diag(torch.tensor(2.0))
def create_lazy_tensor(self):
mat1 = make_random_mat(6, 3)
mat2 = make_random_mat(6, 3)
res = MulLazyTensor(RootLazyTensor(mat1), RootLazyTensor(mat2))
return res.add_diag(torch.tensor(2.))