code: def get_graph_label(self, sample_graph):
      graph_idx = sample_graph.indices[:, 1]
      graph_mask = tf.equal(graph_idx, 0)
      graph_mask = tf.cast(graph_mask, dtype=tf.int32)
      graph_mask = tf.reshape(graph_mask, [-1])
      graph_node = tf.boolean_mask(sample_graph.values, graph_mask)
      (graph_label,) = tf_euler.get_dense_feature(
          graph_node, self.params["label"], [1]
      )
      graph_label = tf.reshape(
          tf.cast(graph_label, dtype=tf.int32), [-1]
      )
      graph_label = tf.one_hot(graph_label, self.params["num_classes"])
      return graph_label
  
file_path: euler/euler_estimator/python/graph_estimator.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import tf_euler
  import numpy
  from euler_estimator.python.base_estimator import BaseEstimator
label_desc: Use image node_id 3 for calling the GraphEstimator obj's underlying member method code with example usage: obj.get_graph_label(sample_graph) and returns: graph_label