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import torch
from torch_geometric.data import Data
from torch_geometric.datasets.motif_generator import CustomMotif
class GridMotif(CustomMotif):
r"""Generates the grid-structured motif from the
`"GNNExplainer: Generating Explanations for Graph Neural Networks"
<https://arxiv.org/abs/1903.03894>`__ paper.
"""
def __init__(self) -> None:
edge_indices = [
[0, 1],
[0, 3],
[1, 4],
[3, 4],
[1, 2],
[2, 5],
[4, 5],
[3, 6],
[6, 7],
[4, 7],
[5, 8],
[7, 8],
[1, 0],
[3, 0],
[4, 1],
[4, 3],
[2, 1],
[5, 2],
[5, 4],
[6, 3],
[7, 6],
[7, 4],
[8, 5],
[8, 7],
]
structure = Data(
num_nodes=9,
edge_index=torch.tensor(edge_indices).t().contiguous(),
y=torch.tensor([0, 1, 0, 1, 2, 1, 0, 1, 0]),
)
super().__init__(structure)
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