code: def test_fbeta_with_return_batch_value(self):
      targets = self.targets.clone()
      targets[-1] = -100
      mask = torch.Tensor([1, 1, 1, 1, 0, 1])
  
      fbeta = FBeta(make_deterministic=self.make_deterministic)
      batch_value = fbeta(self.predictions, (targets, mask))
      epoch_value = fbeta.compute()
  
      self.assertEqual(batch_value, epoch_value)
  
imports: from unittest import TestCase
  import numpy
  import torch
  import torch.nn
  from poutyne import F1, BinaryF1, FBeta, Model
label_desc: Use image node_id 14 for calling the BaseFBetaTest obj's underlying member method code with example usage: obj.test_fbeta_with_return_batch_value() without return types