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31
python/nx-cugraph/nx_cugraph/algorithms/bipartite/basic.py
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# Copyright (c) 2024, NVIDIA CORPORATION. | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
import cupy as cp | ||
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||
from nx_cugraph.algorithms.cluster import _triangles | ||
from nx_cugraph.convert import _to_graph | ||
from nx_cugraph.utils import networkx_algorithm | ||
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__all__ = [ | ||
"is_bipartite", | ||
] | ||
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@networkx_algorithm(plc="triangle_count", version_added="24.02") | ||
def is_bipartite(G): | ||
G = _to_graph(G) | ||
# Counting triangles may not be the fastest way to do this, but it is simple. | ||
node_ids, triangles, is_single_node = _triangles( | ||
G, None, symmetrize="union" if G.is_directed() else None | ||
) | ||
return int(cp.count_nonzero(triangles)) == 0 |
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