code: def target_embed(self, n_id):
      batch_size = tf.shape(n_id)[0]
      n_id = tf.reshape(n_id, [-1])
      emb = self.target_encoder(n_id)
      emb = tf.reshape(emb, [batch_size, -1, tf.shape(emb)[-1]])
      return emb
  
file_path: euler/tf_euler/python/solution/base_unsupervise.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.solution.logits import PosNegLogits
  from tf_euler.python.solution.losses import xent_loss
label_desc: Use image node_id 2 for calling the UnsuperviseSolution obj's underlying member method code with example usage: obj.target_embed(n_id) and returns: emb