code: def update(self, output: t.Tuple[t.List[np.ndarray], t.List[int]]):
      y_pred, y = output
      y_pred = np.array(y_pred).argmax(axis=1)
      y = np.array(y)
      self._correct += (y_pred == y).sum()
      self._total += y_pred.shape[0]
      super().update(output)
  
file_path: deepchecks/examples/examples_metrics_guide.py
imports: from deepchecks.tabular.checks import TrainTestPerformance
  from deepchecks.tabular.datasets.classification import adult
  from deepchecks.tabular.datasets.classification import adult
  from deepchecks.tabular.suites import model_evaluation
  from sklearn.metrics import cohen_kappa_score, fbeta_score, make_scorer
  from deepchecks.vision.checks import ClassPerformance
  from deepchecks.vision.datasets.classification import mnist_torch
  import numpy
  import typing
  from deepchecks.vision.checks import SingleDatasetPerformance
  from deepchecks.vision.metrics_utils import CustomMetric
  from deepchecks.vision.metrics import MeanDice
  from deepchecks.vision.datasets.segmentation.segmentation_coco import load_dataset, load_model
label_desc: Use image node_id 3 for calling the CustomAccuracy obj's underlying member method code with example usage: obj.update(output) without return types