how edge_index longTensor is related to edge_index with SparseTensor?

[gebrahimi91]

In the documentation, it is mentioned:
edge_index (Tensor or SparseTensor): A :obj:torch.LongTensor or a :obj:torch_sparse.SparseTensor that defines the underlying graph connectivity/message passing flow. :obj:edge_index holds the indices of a (sparse) symmetric adjacency matrix. If :obj:edge_index is of type :obj:torch.LongTensor, its shape must be defined as :obj:[2, num_edges], where messages from nodes :obj:edge_index[0] are sent to nodes in :obj:edge_index[1] (in case :obj:flow="source_to_target"). If :obj:edge_index is of type :obj:torch_sparse.SparseTensor, its sparse indices :obj:(row, col) should relate to :obj:row = edge_index[1] and :obj:col = edge_index[0]. The major difference between both formats is that we need to input the *transposed* sparse adjacency matrix.
I get how the edge_index works when it uses LongTensor, but not sure how the sparse_version works? Can anyone give me an example of an edge_index Long Tensor and how I can convert it to the SparseTensor version?
For instance, how do you convert this to a SparseTensor?

tensor([[ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15],
        [ 0,  0,  0,  3,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0]])

[rusty1s]

You can read more about it here.