code: def get_y_true_y_pred():
      # Generate an image with labels 0 (background), 1, 2
      # 3 classes:
      y_true = np.zeros((1, 3, 30, 30), dtype=np.int64)
      y_true[0, 0, 5:17, 7:11] = 1
      y_true[0, 1, 1:11, 1:11] = 1
      y_true[0, 2, 15:25, 15:25] = 1
  
      y_pred = np.zeros((1, 3, 30, 30), dtype=np.int64)
      y_pred[0, 0, 0:7, 8:15] = 1
      y_pred[0, 1, 5:15, 1:11] = 1
      y_pred[0, 2, 20:30, 20:30] = 1
      return y_true, y_pred
  
file_path: ignite/tests/ignite/metrics/test_multilabel_confusion_matrix.py
imports: import numpy
  import pytest
  import torch
  from sklearn.metrics import multilabel_confusion_matrix
  import ignite.distributed
  from ignite.exceptions import NotComputableError
  from ignite.metrics.multilabel_confusion_matrix import MultiLabelConfusionMatrix
label_desc: Use image node_id 4 for calling a global function with example usage: get_y_true_y_pred() and returns: y_true,  y_pred