docstr: Checks if the training should be stopped early. The decision is made based on
  the masured values of one or more quantitative metrics over time.
  
  Parameters
  ----------
  epoch : int
      The number of the current epoch. Multiple checks per epoch are allowed.
  measure_values : dict of str to float
      A dictionary of measured values.
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code: def check_early_stop(self, epoch, measured_values):
      """Checks if the training should be stopped early. The decision is made based on
      the masured values of one or more quantitative metrics over time.
  
      Parameters
      ----------
      epoch : int
          The number of the current epoch. Multiple checks per epoch are allowed.
      measure_values : dict of str to float
          A dictionary of measured values.
      """
      pass
  
imports: import logging
  import numpy
  from abc import ABC
label_desc: Use image node_id 1 for calling the EarlyStoppingHandler obj's underlying member method code with example usage: obj.check_early_stop(epoch, measured_values) without return types