def test_graph_store():
graph_store = MyGraphStore()
edge_index = torch.LongTensor([[0, 1], [1, 2]])
adj = SparseTensor(row=edge_index[0], col=edge_index[1])
def assert_equal_tensor_tuple(expected, actual):
assert len(expected) == len(actual)
for i in range(len(expected)):
assert torch.equal(expected[i], actual[i])
# We put all three tensor types: COO, CSR, and CSC, and we get them back
# to confirm that `GraphStore` works as intended.
coo = adj.coo()[:-1]
csr = adj.csr()[:-1]
csc = adj.csc()[-2::-1] # (row, colptr)
# Put:
graph_store['edge', EdgeLayout.COO] = coo
graph_store['edge', 'csr'] = csr
graph_store['edge', 'csc'] = csc
# Get:
assert_equal_tensor_tuple(coo, graph_store['edge', 'coo'])
assert_equal_tensor_tuple(csr, graph_store['edge', 'csr'])
assert_equal_tensor_tuple(csc, graph_store['edge', 'csc'])
# Get attrs:
edge_attrs = graph_store.get_all_edge_attrs()
assert len(edge_attrs) == 3
with pytest.raises(KeyError):
_ = graph_store['edge_2', 'coo']
def in_degree(adj: SparseTensor, bunch=None):
if bunch is None:
in_deg = adj.sum(0)
else:
N = adj.size(0)
if len(bunch) > int(0.2 * N):
in_deg = adj.sum(0)[bunch]
else:
ptr, idx, val = adj.csc()
in_deg = val.new_zeros(len(bunch))
for i, v in enumerate(bunch):
in_deg[i] = val[ptr[v] : ptr[v + 1]].sum()
return in_deg