Source code for torch_geometric.transforms.target_indegree

from typing import Optional

import torch

from import Data
from import functional_transform
from torch_geometric.transforms import BaseTransform
from torch_geometric.utils import degree

[docs]@functional_transform('target_indegree') class TargetIndegree(BaseTransform): r"""Saves the globally normalized degree of target nodes (functional name: :obj:`target_indegree`). .. math:: \mathbf{u}(i,j) = \frac{\deg(j)}{\max_{v \in \mathcal{V}} \deg(v)} in its edge attributes. Args: cat (bool, optional): Concat pseudo-coordinates to edge attributes instead of replacing them. (default: :obj:`True`) """ def __init__( self, norm: bool = True, max_value: Optional[float] = None, cat: bool = True, ) -> None: self.norm = norm self.max = max_value = cat def forward(self, data: Data) -> Data: assert data.edge_index is not None col, pseudo = data.edge_index[1], data.edge_attr deg = degree(col, data.num_nodes) if self.norm: deg = deg / (deg.max() if self.max is None else self.max) deg = deg[col] deg = deg.view(-1, 1) if pseudo is not None and pseudo = pseudo.view(-1, 1) if pseudo.dim() == 1 else pseudo data.edge_attr =[pseudo, deg.type_as(pseudo)], dim=-1) else: data.edge_attr = deg return data def __repr__(self) -> str: return (f'{self.__class__.__name__}(norm={self.norm}, ' f'max_value={self.max})')