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[DeprecationWarning]: Resolving warning: conversion of an array with ndim > 0 to a scalar. #7834

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[DeprecationWarning]: Resolving warning: conversion of an array with ndim > 0 to a scalar. #7834

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2 changes: 1 addition & 1 deletion python/dgl/data/tu.py
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Original file line number Diff line number Diff line change
Expand Up @@ -406,7 +406,7 @@ def process(self):
int
)
)
self.num_labels = int(max(DS_graph_labels) + 1)
self.num_labels = int(max(DS_graph_labels)[0] + 1)
self.graph_labels = F.tensor(DS_graph_labels)
elif os.path.exists(self._file_path("graph_attributes")):
DS_graph_labels = loadtxt(
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4 changes: 2 additions & 2 deletions python/dgl/utils/data.py
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Original file line number Diff line number Diff line change
Expand Up @@ -94,7 +94,7 @@ def networkx2tensor(nx_graph, idtype, edge_id_attr_name=None):
src = [0] * num_edges
dst = [0] * num_edges
for u, v, attr in nx_graph.edges(data=True):
eid = int(attr[edge_id_attr_name])
eid = int(attr[edge_id_attr_name][0])
if eid < 0 or eid >= nx_graph.number_of_edges():
raise DGLError(
"Expect edge IDs to be a non-negative integer smaller than {:d}, "
Expand Down Expand Up @@ -278,7 +278,7 @@ def networkxbipartite2tensors(
"Expect the node {} to have attribute bipartite=1 "
"with edge {}".format(v, (u, v))
)
eid = int(attr[edge_id_attr_name])
eid = int(attr[edge_id_attr_name][0])
if eid < 0 or eid >= nx_graph.number_of_edges():
raise DGLError(
"Expect edge IDs to be a non-negative integer smaller than {:d}, "
Expand Down
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