code: def early_stop(self, validation_loss: float) -> bool:
      if validation_loss < self.min_validation_loss:
          self.min_validation_loss = validation_loss
          self.counter = 0
      elif validation_loss > (
          self.min_validation_loss + self.min_delta
      ):
          self.counter += 1
          if self.counter >= self.patience:
              return True
      return False
  
file_path: doctr/references/recognition/utils.py
imports: import math
  import matplotlib.pyplot
  import numpy
label_desc: Use image node_id 2 for calling the EarlyStopper obj's underlying member method code with example usage: obj.early_stop(validation_loss) and returns: False, True