code: def setUp(self):
      self._state = {
          torchbearer.Y_TRUE: torch.LongTensor([0, 1, 2, 2, 1]),
          torchbearer.Y_PRED: torch.FloatTensor(
              [
                  [0.9, 0.1, 0.1],  # Correct
                  [0.1, 0.9, 0.1],  # Correct
                  [0.1, 0.1, 0.9],  # Correct
                  [0.9, 0.1, 0.1],  # Incorrect
                  [0.9, 0.1, 0.1],  # Incorrect
              ]
          ),
      }
      self._state[torchbearer.Y_PRED].requires_grad = True
      self._targets = [1, 1, 1, 0, 0]
      self._metric = CategoricalAccuracy().root
  
imports: import unittest
  from mock import Mock, MagicMock, create_autospec, patch
  import torch
  import torchbearer
  from torchbearer.bases import Metric, Callback, base_closure
  from torchbearer.metrics.primitives import CategoricalAccuracy
label_desc: Use image node_id 1 for calling the TestMetric obj's underlying member method code with example usage: obj.setUp() without return types