class_docstr: This prediction function calculates the prediction as the dot product between the user and item representations.
  Prediction = user_repr * item_repr
class_docstr_tok: ["This","prediction","function","calculates","the","prediction","as","the","dot","product","between","the","user","and","item","representations",".","Prediction","=","user_repr","*","item_repr"]
code: def connect_serial_prediction_graph(
      self,
      tf_user_representation,
      tf_item_representation,
      tf_x_user,
      tf_x_item,
  ):
      gathered_user_reprs = tf.gather(tf_user_representation, tf_x_user)
      gathered_item_reprs = tf.gather(tf_item_representation, tf_x_item)
      return tf.reduce_sum(
          tf.multiply(gathered_user_reprs, gathered_item_reprs), axis=1
      )
  
file_path: tensorrec/tensorrec/prediction_graphs.py
imports: import abc
  import tensorflow
  from .recommendation_graphs import relative_cosine
label_desc: Use image node_id 2 for calling the DotProductPredictionGraph obj's underlying member method code with example usage: obj.connect_serial_prediction_graph(tf_user_representation, tf_item_representation, tf_x_user, tf_x_item) and returns: tf