code: def test_fbeta_binary_zero_dim_pred(self):
      fbeta = FBeta(
          average="binary", make_deterministic=self.make_deterministic
      )
      fbeta.update(
          self.predictions[:, 1] - self.predictions[:, 0], self.targets
      )
  
      # check state
      numpy.testing.assert_almost_equal(
          fbeta._pred_sum.tolist(), self.pred_sum
      )
      numpy.testing.assert_almost_equal(
          fbeta._true_sum.tolist(), self.true_sum
      )
      numpy.testing.assert_almost_equal(
          fbeta._true_positive_sum.tolist(), self.true_positive_sum
      )
      numpy.testing.assert_almost_equal(
          fbeta._total_sum.tolist(), self.total_sum
      )
      numpy.testing.assert_almost_equal(fbeta.compute(), self.output)
  
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 4 for calling the BaseFBetaBinaryTest obj's underlying member method code with example usage: obj.test_fbeta_binary_zero_dim_pred() without return types