code: def example_feature_columns():
      """Returns the example feature columns."""
      feature_names = [
          "custom_features_{}".format(i + 1)
          for i in range(FLAGS.num_features)
      ]
  
      def log1p_cutoff(t):
          return tf.clip_by_value(
              tf.math.log1p(tf.abs(t)) * tf.sign(t), -_CUTOFF, _CUTOFF
          )
  
      example_feature_columns_ = {}
      for name in feature_names:
          example_feature_columns_[
              name
          ] = tf.feature_column.numeric_column(
              name,
              shape=(1,),
              default_value=0.0,
              normalizer_fn=log1p_cutoff,
          )
  
      return example_feature_columns_
  
file_path: ranking/tensorflow_ranking/research/dasalc.py
imports: from absl import flags
  import tensorflow
  from tensorflow import estimator
  from tensorflow.python.estimator.canned import optimizers
  import tensorflow_ranking
label_desc: Use image node_id 2 for calling a global function with example usage: example_feature_columns() and returns: example_feature_columns_, tf