code: def setUp(self):
      self._metric_function = Mock(return_value="test")
      self._metric = EpochLambda(
          "test", self._metric_function, step_size=3
      )
      self._metric.reset(
          {
              torchbearer.DEVICE: "cpu",
              torchbearer.DATA_TYPE: torch.float32,
          }
      )
      self._states = [
          {
              torchbearer.BATCH: 0,
              torchbearer.Y_TRUE: torch.LongTensor([0]),
              torchbearer.Y_PRED: torch.FloatTensor([0.0]),
              torchbearer.DEVICE: "cpu",
          },
          {
              torchbearer.BATCH: 1,
              torchbearer.Y_TRUE: torch.LongTensor([1]),
              torchbearer.Y_PRED: torch.FloatTensor([0.1]),
              torchbearer.DEVICE: "cpu",
          },
          {
              torchbearer.BATCH: 2,
              torchbearer.Y_TRUE: torch.LongTensor([2]),
              torchbearer.Y_PRED: torch.FloatTensor([0.2]),
              torchbearer.DEVICE: "cpu",
          },
          {
              torchbearer.BATCH: 3,
              torchbearer.Y_TRUE: torch.LongTensor([3]),
              torchbearer.Y_PRED: torch.FloatTensor([0.3]),
              torchbearer.DEVICE: "cpu",
          },
          {
              torchbearer.BATCH: 4,
              torchbearer.Y_TRUE: torch.LongTensor([4]),
              torchbearer.Y_PRED: torch.FloatTensor([0.4]),
              torchbearer.DEVICE: "cpu",
          },
      ]
  
imports: import unittest
  import torch
  from mock import Mock, call
  from torch.autograd import Variable
  import torchbearer
  from torchbearer.metrics import Metric, BatchLambda, EpochLambda, ToDict
label_desc: Use image node_id 1 for calling the TestEpochLambda obj's underlying member method code with example usage: obj.setUp() without return types