code: def get_row_col_values(
      X,
      context,
      row_gather,
      col_gather,
      bos_id,
      eos_id,
      table_position_type,
      max_row_col_embedding,
  ):
      """
      Applys gather_tables on rows and columns and returns the output as a nested dict
      with keys "row" and "col"
      """
      return {
          "row": gather_tables(
              X,
              row_gather,
              context,
              bos_id=tf.constant(bos_id),
              eos_id=tf.constant(eos_id),
              table_position_type=table_position_type,
              max_row_col_embedding=max_row_col_embedding,
          ),
          "col": gather_tables(
              X,
              col_gather,
              context,
              bos_id=tf.constant(bos_id),
              eos_id=tf.constant(eos_id),
              table_position_type=table_position_type,
              max_row_col_embedding=max_row_col_embedding,
          ),
      }
  
file_path: finetune/finetune/base_models/bert/table_utils.py
imports: import tensorflow
  from finetune.base_models.bert.modeling import gelu
label_desc: Use image node_id 7 for calling a global function with example usage: get_row_col_values(X, context, row_gather, col_gather, bos_id, eos_id, table_position_type, max_row_col_embedding) and returns: dict