code: def get_y_true_y_pred():
      # Generate an image with labels 0 (background), 1, 2
      # 3 classes:
      y_true = np.zeros((30, 30), dtype=np.int32)
      y_true[1:11, 1:11] = 1
      y_true[15:25, 15:25] = 2
  
      y_pred = np.zeros((30, 30), dtype=np.int32)
      y_pred[5:15, 1:11] = 1
      y_pred[20:30, 20:30] = 2
      return y_true, y_pred
  
imports: import os
  import numpy
  import pytest
  import torch
  from sklearn.metrics import accuracy_score, confusion_matrix, precision_score, recall_score
  import ignite.distributed
  from ignite.exceptions import NotComputableError
  from ignite.metrics import ConfusionMatrix, IoU, JaccardIndex, mIoU
  from ignite.metrics.confusion_matrix import cmAccuracy, cmPrecision, cmRecall, DiceCoefficient
label_desc: Use image node_id 7 for calling a global function with example usage: get_y_true_y_pred() and returns: y_true,  y_pred