class_docstr: Random node selection.
code: def rank(
      self, edge_index: numpy.ndarray
  ) -> numpy.ndarray:  # noqa: D102
      return self.generator.permutation(edge_index.max())
  
imports: import logging
  from abc import ABC, abstractmethod
  from typing import Iterable, Optional, Sequence, Union
  import numpy
  import torch
  from class_resolver import ClassResolver, HintOrType, OptionalKwargs
  from torch_ppr import page_rank
  from ...triples.splitting import get_absolute_split_sizes, normalize_ratios
  from ...typing import OneOrSequence
  from ...utils import ExtraReprMixin
label_desc: Use image node_id 2 for calling the RandomAnchorSelection obj's underlying member method code with example usage: obj.rank(edge_index) and returns: self