class_docstr: Base class for crossovers.
  
  A crossover operation is used by :class:`~optuna.samplers.NSGAIISampler`
  to create new parameter combination from parameters of ``n`` parent individuals.
  
  .. note::
      Concrete implementations of this class are expected to only accept parameters
      from numerical distributions. At the moment, only crossover operation for categorical
      parameters (uniform crossover) is built-in into :class:`~optuna.samplers.NSGAIISampler`.
docstr: Number of parent individuals required to perform crossover.
docstr_tok: ["Number","of","parent","individuals","required","to","perform","crossover","."]
code: def n_parents(self) -> int:
      """Number of parent individuals required to perform crossover."""
  
      raise NotImplementedError
  
file_path: optuna/optuna/samplers/nsgaii/_crossovers/_base.py
imports: import abc
  import numpy
  from optuna.study import Study
label_desc: Use image node_id 2 for calling the BaseCrossover obj's underlying member method code with example usage: obj.n_parents() without return types