code: def test_number_feature_zscore_normalization_error():
      input_features = [
          number_feature(
              name="num_input",
              preprocessing={"normalization": "zscore"},
          )
      ]
      output_features = [number_feature(name="num_output")]
  
      df = pd.read_csv(generate_data(input_features, output_features))
  
      # Override input number feature to have a constant value
      df["num_input"] = 1
  
      config = {
          "input_features": input_features,
          "output_features": output_features,
      }
  
      model = LudwigModel(config, backend="local")
  
      with pytest.raises(RuntimeError):
          model.preprocess(dataset=df)
  
imports: import pandas
  import pytest
  from ludwig.api import LudwigModel
  from tests.integration_tests.utils import generate_data, number_feature
label_desc: Use image node_id 1 for calling a global function with example usage: test_number_feature_zscore_normalization_error() without return types