class_docstr: Random node selection.
docstr: Initialize the selection stragegy.
  
  :param num_anchors:
      the number of anchors to select
  :param random_seed:
      the random seed to use.
code: def __init__(
      self,
      num_anchors: int = 32,
      random_seed: Optional[int] = None,
  ) -> None:
      """
      Initialize the selection stragegy.
  
      :param num_anchors:
          the number of anchors to select
      :param random_seed:
          the random seed to use.
      """
      super().__init__(num_anchors=num_anchors)
      self.generator: numpy.random.Generator = numpy.random.default_rng(
          random_seed
      )
  
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 RandomAnchorSelection object from inherited base classes: SingleSelection with example: obj = RandomAnchorSelection(num_anchors, random_seed)