class_docstr: Object which carries out genetic search and returns top performing model
  upon completion.
code: def _handle_broken_model(self, model, error):
      del model
  
      n = self.genome_handler.n_classes
      loss = log_loss(
          np.concatenate(([1], np.zeros(n - 1))), np.ones(n) / n
      )
      accuracy = 1 / n
      gc.collect()
  
      if K.backend() == "tensorflow":
          K.clear_session()
          tf.reset_default_graph()
  
      print("An error occurred and the model could not train:")
      print(error)
      print(
          (
              "Model assigned poor score. Please ensure that your model"
              "constraints live within your computational resources."
          )
      )
      return loss, accuracy
  
imports: from __future__ import print_function
  import random
  import csv
  import operator
  import gc
  import os
  from datetime import datetime
  from keras.callbacks import EarlyStopping
  from keras.models import load_model
  import keras.backend
  from sklearn.metrics import log_loss
  import numpy
label_desc: Use image node_id 7 for calling the DEvol obj's underlying member method code with example usage: obj._handle_broken_model(model, error) and returns: loss,  accuracy