class_docstr: This suite was built using the checklist process with the self.editor
  suggestions. Users are encouraged to add/modify as they see fit.
  
  Note: `editor.suggest(...)` can be slow as it runs a language model.
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docstr: These arguments are expected by `checklist.expect.Expect.pairwise` function.
  We only use `orig_conf` and `conf` in this case.
  
  `orig_conf` is the confidence score of the first example in a test's input data pair.
  
  A `bool` output indicates whether the test passed the expectation (always
  `True` in this function's case).
  
  A `float` output indicates the magnitude of the failure.
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code: def _diff_up(
      self,
      orig_pred: int,
      pred: int,
      orig_conf: np.ndarray,
      conf: np.ndarray,
      labels: Optional[int] = None,
      meta: Optional[List] = None,
  ) -> Union[bool, float]:
      """
      These arguments are expected by `checklist.expect.Expect.pairwise` function.
      We only use `orig_conf` and `conf` in this case.
  
      `orig_conf` is the confidence score of the first example in a test's input data pair.
  
      A `bool` output indicates whether the test passed the expectation (always
      `True` in this function's case).
  
      A `float` output indicates the magnitude of the failure.
      """
      tolerance = 0.1
      change = self._positive_change(orig_conf, conf)
      if change + tolerance >= 0:
          return True
      else:
          return change + tolerance
  
imports: from typing import Optional, Iterable, List, Union, Tuple
  import numpy
  from checklist.test_suite import TestSuite
  from checklist.test_types import MFT, INV, DIR, Expect
  from checklist.perturb import Perturb
  from allennlp.confidence_checks.task_checklists.task_suite import TaskSuite
  from allennlp.confidence_checks.task_checklists import utils
  from allennlp.data.instance import Instance
  from allennlp.predictors import Predictor
label_desc: Use image node_id 13 for calling the SentimentAnalysisSuite obj's underlying member method code with example usage: obj._diff_up(orig_pred, pred, orig_conf, conf, labels, meta) and returns: True, unknown