code: def __init__(self, var_list, dtype=tf.float32):
      assigns = []
      shapes = list(map(var_shape, var_list))
      total_size = np.sum([intprod(shape) for shape in shapes])
  
      self.theta = theta = tf.placeholder(dtype, [total_size])
      start = 0
      assigns = []
      for shape, v in zip(shapes, var_list):
          size = intprod(shape)
          assigns.append(
              tf.assign(
                  v, tf.reshape(theta[start : start + size], shape)
              )
          )
          start += size
      self.op = tf.group(*assigns)
  
imports: import numpy
  import tensorflow
  import copy
  import os
  import functools
  import collections
  import multiprocessing
label_desc: Use image node_id 1 to create a new SetFromFlat object from inherited base classes: object with example: obj = SetFromFlat(var_list, dtype)