code: def setUp(self):
      self.predictions = torch.Tensor(
          [
              [0.35, 0.25, 0.1, 0.1, 0.2],
              [0.1, 0.6, 0.1, 0.2, 0.0],
              [0.1, 0.6, 0.1, 0.2, 0.0],
              [0.1, 0.5, 0.1, 0.2, 0.0],
              [0.1, 0.2, 0.1, 0.7, 0.0],
              [0.1, 0.6, 0.1, 0.2, 0.0],
          ]
      )
      self.label_predictions = torch.Tensor([0, 1, 1, 1, 3, 1])
      self.targets = torch.Tensor([0, 4, 1, 0, 3, 0])
      self.accuracy_none = (
          self.label_predictions == self.targets
      ).float() * 100
      self.accuracy = self.accuracy_none.mean()
  
imports: from unittest import TestCase, skipIf
  import numpy
  import torch
  from poutyne import Accuracy, BinaryAccuracy, TopKAccuracy, acc, bin_acc, topk
label_desc: Use image node_id 1 for calling the AccuracyTest obj's underlying member method code with example usage: obj.setUp() without return types