class_docstr: AbstractModel which returns random values on a call to `fit`.
code: def _train(self, X: np.ndarray, Y: np.ndarray) -> RandomModel:
      if not isinstance(X, np.ndarray):
          raise NotImplementedError("X has to be of type np.ndarray.")
      if not isinstance(Y, np.ndarray):
          raise NotImplementedError("Y has to be of type np.ndarray.")
  
      logger.debug("(Pseudo) fit model to data.")
      return self
  
imports: from __future__ import annotations
  import numpy
  from smac.model.abstract_model import AbstractModel
  from smac.utils.logging import get_logger
label_desc: Use image node_id 1 for calling the RandomModel obj's underlying member method code with example usage: obj._train(X, Y) and returns: self