code: def __call__(self, inputs):
      batch_size = tf.shape(inputs)[0]
      neg_nodes_group = []
      for n_type in self.neg_type:
          neg_node = tf_euler.sample_node(
              batch_size * self.num_negs, n_type
          )
          neg_node = tf.reshape(neg_node, [batch_size, self.num_negs])
          neg_nodes_group.append(neg_node)
      if len(self.neg_type) == 1:
          return neg_nodes_group[0]
      else:
          return neg_nodes_group
  
file_path: euler/tf_euler/python/solution/samplers.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import tf_euler
label_desc: Use image node_id 2 for calling the SampleNegWithTypes obj's underlying member method code with example usage: obj.__call__(inputs) and returns: neg_nodes_group, neg_nodes_group