code: def test_error_is_not_nan():
      m = ManhattanDistance()
      m.update((torch.zeros(4), torch.zeros(4)))
      assert not (
          torch.isnan(m._sum_of_errors).any()
          or torch.isinf(m._sum_of_errors).any()
      ), m._sum_of_errors
  
imports: import os
  import numpy
  import pytest
  import torch
  from sklearn.metrics import DistanceMetric
  import ignite.distributed
  from ignite.contrib.metrics.regression import ManhattanDistance
  from ignite.engine import Engine
label_desc: Use image node_id 4 for calling a global function with example usage: test_error_is_not_nan() without return types