93f84bee4d0c9e082c5ef04fa5f4a0886cdad2db,openrec/recommenders/recommender.py,Recommender,_optimistic_restore,#Recommender#,460

Before Change

        
        reader = tf.train.NewCheckpointReader(save_file)
        saved_shapes = reader.get_variable_to_shape_map()
        var_names = sorted([(var.name, var.name.split(":")[0]) for var in tf.global_variables()
                if var.name.split(":")[0] in saved_shapes and len(var.shape) > 0])
        restore_vars = []
        with tf.variable_scope("", reuse=True):
            for var_name, saved_var_name in var_names:
                curr_var = tf.get_variable(saved_var_name)
                var_shape = curr_var.get_shape().as_list()
                if var_shape == saved_shapes[saved_var_name]:
                    restore_vars.append(curr_var)
        // print("... restored variables:", ",".join([var.name for var in restore_vars]))
        saver = tf.train.Saver(restore_vars)
        saver.restore(session, save_file)
            
    def build(self):

After Change

        saved_shapes = reader.get_variable_to_shape_map()
        
        restore_vars = []
        for var in tf.global_variables():
            var_name = var.name.split(":")[0]
            if var_name in saved_shapes and len(var.shape) > 0:
                if var.get_shape().as_list() == saved_shapes[var_name]:
                    restore_vars.append(var)
        
        saver = tf.train.Saver(restore_vars)
        saver.restore(session, save_file)
            
    def build(self):

Instances