code: def _get_counts(labels):
      """Return the overall, positive, and negative counts of the labels.
  
      :param labels: the labels of the samples
      :type labels: list
      :return: a tuple containing the overall, positive, and negative counts of the labels
      :rtype: tuple of int, int, int
      """
      n = len(labels)
      n_positive = sum(labels)
      n_negative = n - n_positive
      return n, n_positive, n_negative
  
file_path: fairlearn/fairlearn/postprocessing/_tradeoff_curve_utilities.py
imports: import numpy
  import pandas
  from sklearn.utils import Bunch
  from ._constants import LABEL_KEY, P0_KEY, P1_KEY, SCORE_KEY
  from ._threshold_operation import ThresholdOperation
label_desc: Use image node_id 7 for calling a global function with example usage: _get_counts(labels) and returns: n,  n_positive,  n_negative