class_docstr: Select entities according to their page rank.
  
  .. seealso::
      http://web.stanford.edu/class/cs224w/slides/04-pagerank.pdf
docstr: Initialize the selection strategy.
  
  :param num_anchors:
      the number of anchors to select
  :param kwargs:
      additional keyword-based parameters passed to :func:`page_rank`.
code: def __init__(
      self,
      num_anchors: int = 32,
      **kwargs,
  ) -> None:
      """
      Initialize the selection strategy.
  
      :param num_anchors:
          the number of anchors to select
      :param kwargs:
          additional keyword-based parameters passed to :func:`page_rank`.
      """
      super().__init__(num_anchors=num_anchors)
      self.kwargs = kwargs
  
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 1 to create a new PageRankAnchorSelection object from inherited base classes: SingleSelection with example: obj = PageRankAnchorSelection(num_anchors)