code: def parse_graph_file(
      file_dir, total_label, graph_name, fea_len, train_num
  ):
      content_file = os.path.join(
          file_dir, "data", graph_name + ".NODE.paper.tab"
      )
      cite_file = os.path.join(
          file_dir, "data", graph_name + ".DIRECTED.cites.tab"
      )
      node_map = gen_node_map(cite_file)
      edge_src, edge_dst, edge_type = gen_edge(
          cite_file, node_map, train_num
      )
      node_ids, node_type, node_label, node_feature = gen_node(
          content_file, node_map, total_label, fea_len, train_num
      )
      return (
          node_ids,
          node_type,
          node_label,
          node_feature,
          edge_src,
          edge_dst,
          edge_type,
      )
  
file_path: euler/tf_euler/python/dataset/pubmed_utils.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: parse_graph_file(file_dir, total_label, graph_name, fea_len, train_num) and returns: node_ids,  node_type,  node_label,  node_feature,  edge_src,  edge_dst,  edge_type