code: def good_predictor(x: np.ndarray) -> np.ndarray:
      """
      A dummy predictor returning a vector of random binary target labels.
      """
      return np.random.randint(low=0, high=2, size=x.shape[0])
  
file_path: alibi/alibi/explainers/tests/test_anchor_tabular.py
imports: from collections import OrderedDict, defaultdict
  from copy import deepcopy
  import numpy
  import pytest
  from pytest_lazyfixture import lazy_fixture
  from alibi.api.defaults import DEFAULT_META_ANCHOR, DEFAULT_DATA_ANCHOR
  from alibi.exceptions import NotFittedError, PredictorCallError, PredictorReturnTypeError
  from alibi.explainers import AnchorTabular, DistributedAnchorTabular
  from alibi.explainers.tests.utils import predict_fcn
label_desc: Use image node_id 7 for calling a global function with example usage: good_predictor(x) and returns: np