code: def test_numeric_transformation_registry(
      transformation, backend, ray_cluster_2cpu
  ):
      data_df, proc_df = get_test_data(backend)
      backend = initialize_backend(backend)
  
      feature_meta = NumberFeatureMixin.get_feature_meta(
          {},
          data_df["x"],
          {"normalization": transformation},
          backend,
          True,
      )
  
      num_feature = number_feature()
  
      NumberFeatureMixin.add_feature_data(
          feature_config=num_feature,
          input_df=data_df,
          proc_df=proc_df,
          metadata={num_feature[NAME]: feature_meta},
          preprocessing_parameters={"normalization": transformation},
          backend=backend,
          skip_save_processed_input=False,
      )
  
file_path: ludwig/tests/ludwig/utils/test_normalization.py
imports: from typing import Tuple
  import numpy
  import pandas
  import pytest
  from ludwig.backend import initialize_backend
  from ludwig.constants import COLUMN, NAME, PROC_COLUMN
  from ludwig.features.feature_utils import compute_feature_hash
  from ludwig.features.number_feature import NumberFeatureMixin, numeric_transformation_registry
  from ludwig.utils.types import DataFrame
label_desc: Use image node_id 4 for calling a global function with example usage: test_numeric_transformation_registry(transformation, backend, ray_cluster_2cpu) without return types