code: def _mutIndividual(individual, up, indpb, gene_type=None):
      for i, up, rn in zip(
          range(len(up)), up, [random.random() for _ in range(len(up))]
      ):
          if rn < indpb:
              individual[i] = random.randint(0, up)
      return (individual,)
  
imports: from __future__ import division
  import os
  import warnings
  import numpy
  import random
  from deap import base, creator, tools, algorithms
  from collections import defaultdict
  from sklearn.base import clone, is_classifier
  from sklearn.model_selection._validation import _fit_and_score
  from sklearn.model_selection._search import BaseSearchCV, check_cv, _check_param_grid
  from sklearn.metrics import check_scoring
  from sklearn.utils.validation import _num_samples, indexable
label_desc: Use image node_id 4 for calling a global function with example usage: _mutIndividual(individual, up, indpb, gene_type) and returns: individual