docstr: Increment the running number of true positives and number of elements.
docstr_tok: ["Increment","the","running","number","of","true","positives","and","number","of","elements","."]
code: def _update(self, y_pred, y_true):
      """
      Increment the running number of true positives and number of elements.
      """
      num_true_positives, total_exemples = self._compute_stats(
          y_pred, y_true
      )
      self.num_true_positives += num_true_positives
      self.total_exemples += total_exemples
      return num_true_positives, total_exemples
  
file_path: poutyne/examples/medium_post/train_with_custom_metrics.py
imports: import torch
  import torch.nn
  from torch.utils.data import random_split
  from torchvision.datasets import MNIST
  from torchvision.transforms import ToTensor
  from poutyne import Model, Metric
label_desc: Use image node_id 4 for calling the MyAccuracyMetric obj's underlying member method code with example usage: obj._update(y_pred, y_true) and returns: num_true_positives,  total_exemples