code: def __check_init_num_samples(num_samples, required_num_samples):
      if num_samples != required_num_samples:
          raise ValueError(
              "The provided initialization contains a different number "
              "of points (%d) than the data provided (%d)."
              % (num_samples, required_num_samples)
          )
  
imports: import inspect
  import logging
  import multiprocessing
  from collections.abc import Iterable
  from types import SimpleNamespace
  from time import time
  import numpy
  from sklearn.base import BaseEstimator
  from openTSNE import _tsne
  from openTSNE import initialization
  from openTSNE.affinity import Affinities, MultiscaleMixture
  from openTSNE.quad_tree import QuadTree
  from openTSNE import utils
label_desc: Use image node_id 3 for calling a global function with example usage: __check_init_num_samples(num_samples, required_num_samples) without return types