code: def _build_wide_columns(user_ids, item_ids, hash_bucket_size=1000):
      """Build wide feature (crossed) columns. `user_ids` * `item_ids` are hashed into `hash_bucket_size`
  
      Args:
          user_ids (tf.feature_column.categorical_column_with_vocabulary_list): User ids.
          item_ids (tf.feature_column.categorical_column_with_vocabulary_list): Item ids.
          hash_bucket_size (int): Hash bucket size.
  
      Returns:
          list: Wide feature columns.
      """
      # Including the original features in addition to the crossed one is recommended to address hash collision problem.
      return [
          user_ids,
          item_ids,
          tf.feature_column.crossed_column(
              [user_ids, item_ids], hash_bucket_size=hash_bucket_size
          ),
      ]
  
imports: import tensorflow
  from recommenders.utils.constants import DEFAULT_USER_COL, DEFAULT_ITEM_COL
  from recommenders.utils.tf_utils import MODEL_DIR
label_desc: Use image node_id 2 for calling a global function with example usage: _build_wide_columns(user_ids, item_ids, hash_bucket_size) and returns: list