code: def pop(self) -> TrainingExample:
      if not len(self.candidates):
          raise IndexError("No more unlabeled examples to label")
  
      prob_l = [
          learner.candidate_scores() for learner in self._learners
      ]
      probs = numpy.concatenate(prob_l, axis=1)
  
      # where do the classifers disagree?
      disagreement = numpy.std(probs > 0.5, axis=1).astype(bool)
  
      if disagreement.any():
          conflicts = disagreement.nonzero()[0]
          target = numpy.random.uniform(size=1)
          uncertain_index = conflicts[
              numpy.argmax(probs[conflicts][:, 0] - target)
          ]
      else:
          uncertain_index = numpy.std(probs, axis=1).argmax()
  
      logger.debug(
          "Classifier: %.2f, Covered: %s",
          probs[uncertain_index][0],
          bool(probs[uncertain_index][1]),
      )
  
      uncertain_pair: TrainingExample = self.candidates[uncertain_index]
      self._remove(uncertain_index)
      return uncertain_pair
  
imports: from __future__ import annotations
  import logging
  import random
  from abc import ABC, abstractmethod
  from typing import TYPE_CHECKING, overload
  from warnings import warn
  import numpy
  import numpy.typing
  import sklearn.linear_model
  import dedupe.core
  import dedupe.training
label_desc: Use image node_id 2 for calling the DisagreementLearner obj's underlying member method code with example usage: obj.pop() and returns: uncertain_pair