text: from keras.callbacks import EarlyStopping
  
  
  def early_stopper(epochs,
                    monitor='val_loss',
                    mode='moderate',
                    min_delta=None,
                    patience=None):
  
      '''EARLY STOP CALLBACK
  
      Helps prevent wasting time when loss is not becoming
      better. Offers two pre-determined settings 'moderate'
      and 'strict' and allows input of list with two values:
  
      min_delta = the limit for change at which point flag is raised
  
      patience = the number of epochs before termination from flag
  
      '''
  
      if mode == 'moderate':
          _es_out = EarlyStopping(monitor=monitor,
                                  min_delta=0,
                                  patience=int(epochs / 10),
                                  verbose=0, mode='auto')
      elif mode == 'strict':
          _es_out = EarlyStopping(monitor=monitor,
                                  min_delta=0,
                                  patience=2,
                                  verbose=0, mode='auto')
      elif isinstance(mode, list):
          _es_out = EarlyStopping(monitor=monitor,
                                  min_delta=mode[0],
                                  patience=mode[1],
                                  verbose=0, mode='auto')
      return [_es_out]
  