code: def to_sample(self, inputs):
      batch_size = tf.size(inputs)
      path = tf_euler.random_walk(
          inputs,
          [self.edge_type] * self.walk_len,
          p=self.walk_p,
          q=self.walk_q,
          default_node=self.max_id + 1,
      )
      pair = tf_euler.gen_pair(
          path, self.left_win_size, self.right_win_size
      )
      num_pairs = pair.shape[1]
      src, pos = tf.split(pair, [1, 1], axis=-1)
      src = tf.reshape(src, [batch_size * num_pairs, 1])
      pos = tf.reshape(pos, [batch_size * num_pairs, 1])
      negs = tf_euler.sample_node(
          batch_size * num_pairs * self.num_negs,
          self.node_type,
          condition=self.neg_condition,
      )
      negs = tf.reshape(negs, [batch_size * num_pairs, self.num_negs])
      return src, pos, negs
  
file_path: euler/examples/deepwalk/deepwalk.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import tf_euler
  from tf_euler.python.mp_utils.base_gnn import BaseGNNNet
  from tf_euler.python.mp_utils.base import SuperviseModel, UnsuperviseModel
label_desc: Use image node_id 2 for calling the BaseNode2Vec obj's underlying member method code with example usage: obj.to_sample(inputs) and returns: src,  pos,  negs