code: def get_input_from_id_file(self):
      def _parse_line_py(line):
          triples = line.strip().split()
          ent1 = int(triples[0])
          ent2 = int(triples[1])
          rel_type = int(triples[2])
          out = np.asarray([ent1, ent2, rel_type])
          return out
  
      def _parse_function(line):
          return tf.py_func(_parse_line_py, [line], tf.int64)
  
      dataset = tf.data.TextLineDataset(self.params["id_file"])
      dataset = dataset.map(_parse_function)
      dataset = dataset.batch(self.params["batch_size"])
      source = dataset.make_one_shot_iterator().get_next()
      return source
  
file_path: euler/euler_estimator/python/edge_estimator.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import numpy
  import tf_euler
  from euler_estimator.python.base_estimator import BaseEstimator
label_desc: Use image node_id 5 for calling the EdgeEstimator obj's underlying member method code with example usage: obj.get_input_from_id_file() and returns: source, out, tf