Improvement of calculation time

Dear all,

I am generating a Graph with the following command:


for i in range(1, 3352):
    for j in range(1, 3352):
        # row = LL[i,:]
        # column = LL[1,:]
        print(i)
        print(j)

        # a = np.array([i, j])

        # c = np.concatenate((c[i,:], a[i,:]), axis=1)

        edge_index_temp = torch.tensor([[i, j]], dtype=torch.long)
        edge_index = torch.cat((edge_index, edge_index_temp))

        x_temp = torch.tensor([[counter]], dtype=torch.float)
        x = torch.cat((x, x_temp))
        counter = counter + 1

        corr_value = LL[i, j]

        edge_attr_temp = torch.tensor([[corr_value]], dtype=torch.float)
        edge_attr = torch.cat((edge_attr, edge_attr_temp))

but loops are super slow. How can I speed that up?

Best,