class_docstr: Caser Model
  
  :Citation:
  
      J. Tang and K. Wang, "Personalized top-n sequential recommendation via convolutional
      sequence embedding", in Proceedings of the Eleventh ACM International Conference on
      Web Search and Data Mining, ACM, 2018.
docstr: The main function to create caser model.
  
  Returns:
      object: The output of caser section.
docstr_tok: ["The","main","function","to","create","caser","model",".","Returns",":","object",":","The","output","of","caser","section","."]
code: def _build_seq_graph(self):
      """The main function to create caser model.
  
      Returns:
          object: The output of caser section.
      """
      with tf.compat.v1.variable_scope("caser"):
          cnn_output = self._caser_cnn()
          model_output = tf.concat(
              [cnn_output, self.target_item_embedding], 1
          )
          tf.compat.v1.summary.histogram("model_output", model_output)
          return model_output
  
file_path: recommenders/recommenders/models/deeprec/models/sequential/caser.py
imports: import tensorflow
  from recommenders.models.deeprec.models.sequential.sequential_base_model import SequentialBaseModel
label_desc: Use image node_id 2 for calling the CaserModel obj's underlying member method code with example usage: obj._build_seq_graph() and returns: model_output