code: def test_replace_inf_values(divide_by_zero_es):
      div_by_scalar = DivideNumericScalar(value=0)
      div_by_feature = DivideByFeature(value=1)
      div_by_feature_neg = DivideByFeature(value=-1)
      for primitive in [
          "divide_numeric",
          div_by_scalar,
          div_by_feature,
          div_by_feature_neg,
      ]:
          fm, _ = dfs(
              entityset=divide_by_zero_es,
              target_dataframe_name="zero",
              trans_primitives=[primitive],
              max_depth=1,
          )
          assert (
              np.inf in to_pandas(fm).values
              or -np.inf in to_pandas(fm).values
          )
          replaced_fm = replace_inf_values(fm)
          replaced_fm = to_pandas(replaced_fm)
          assert np.inf not in replaced_fm.values
          assert -np.inf not in replaced_fm.values
  
          custom_value_fm = replace_inf_values(
              fm, replacement_value="custom_val"
          )
          custom_value_fm = to_pandas(custom_value_fm)
          assert np.inf not in custom_value_fm.values
          assert -np.inf not in replaced_fm.values
          assert "custom_val" in custom_value_fm.values
  
imports: import numpy
  from featuretools import dfs
  from featuretools.computational_backends import replace_inf_values
  from featuretools.primitives import DivideByFeature, DivideNumericScalar
  from featuretools.tests.testing_utils import to_pandas
label_desc: Use image node_id 1 for calling a global function with example usage: test_replace_inf_values(divide_by_zero_es) without return types