docstr: Get the parameters as a flat vector
  
  :param var_list: ([TensorFlow Tensor]) the variables
  :param sess: (TensorFlow Session)
code: def __init__(self, var_list, sess=None):
      """
      Get the parameters as a flat vector
  
      :param var_list: ([TensorFlow Tensor]) the variables
      :param sess: (TensorFlow Session)
      """
      self.operation = tf.concat(
          axis=0, values=[tf.reshape(v, [numel(v)]) for v in var_list]
      )
      self.sess = sess
  
imports: import os
  import collections
  import functools
  import multiprocessing
  from typing import Set
  import numpy
  import tensorflow
label_desc: Use image node_id 1 to create a new GetFlat object from inherited base classes: object with example: obj = GetFlat(var_list, sess)