code: def setUp(self):
      self.predictions = torch.Tensor(
          [
              -0.45,
              -0.66,
              0.8,
              -1.65,
              0.42,
              -0.04,
              -0.99,
              -0.46,
              1.12,
              1.93,
          ]
      )
      self.label_predictions = torch.Tensor(
          [0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 1.0]
      )
      self.targets = torch.Tensor(
          [1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0]
      )
      self.binary_accuracy_none = (
          self.label_predictions == self.targets
      ).float() * 100
      self.binary_accuracy = self.binary_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 BinaryAccuracyTest obj's underlying member method code with example usage: obj.setUp() without return types