class_docstr: Base class for models
class_docstr_tok: ["Base","class","for","models"]
docstr: Given feature data (in `feed_dict`), get predicted scores with current model.
  
  Args:
      sess (object): The model session object.
      feed_dict (dict): Instances to predict. This is a dictionary that maps graph elements to values.
  
  Returns:
      list: Predicted scores for the given instances.
docstr_tok: ["Given","feature","data","(","in","`","feed_dict","`",")",",","get","predicted","scores","with","current","model",".","Args",":","sess","(","object",")",":","The","model","session","object",".","feed_dict","(","dict",")",":","Instances","to","predict",".","This","is","a","dictionary","that","maps","graph","elements","to","values",".","Returns",":","list",":","Predicted","scores","for","the","given","instances","."]
code: def infer(self, sess, feed_dict):
      """Given feature data (in `feed_dict`), get predicted scores with current model.
  
      Args:
          sess (object): The model session object.
          feed_dict (dict): Instances to predict. This is a dictionary that maps graph elements to values.
  
      Returns:
          list: Predicted scores for the given instances.
      """
      feed_dict[self.layer_keeps] = self.keep_prob_test
      feed_dict[self.is_train_stage] = False
      return sess.run([self.pred], feed_dict=feed_dict)
  
imports: from os.path import join
  import abc
  import time
  import os
  import numpy
  import tensorflow
  from recommenders.models.deeprec.deeprec_utils import cal_metric
label_desc: Use image node_id 19 for calling the BaseModel obj's underlying member method code with example usage: obj.infer(sess, feed_dict) and returns: sess