title: Unable to save model with tensorflow 2.0
body: <p>When saving a model, in my case, HRNet, i met the following error:
  ValueError: Unable to save the object ListWrapper([ListWrapper([None])]) </p>
  
  <p>Some of my layer looks like(Full version: <a href="https://github.com/zheLim/auto-face-parsing/blob/master/lib/model/hrnet_blocks.py" rel="nofollow noreferrer">https://github.com/zheLim/auto-face-parsing/blob/master/lib/model/hrnet_blocks.py</a>):</p>
  
  <pre><code>class MultiResolutionLayer(layers.Layer):
  def __init__(self, n_channels_list, bn_momentum=0.01, activation='relu'):
      """
      fuse feature from different branch with adding
      :param n_branches:
      :param n_channels:
      :param multi_scale_output:
      """
      super(MultiResolutionLayer, self).__init__()
      self.n_branches = len(n_channels_list)
      self.fuse_layers = [[] for branch_i in range(self.n_branches)]
      for branch_i in range(self.n_branches):
          layer = []
          for branch_j in range(self.n_branches):
              if branch_i &lt; branch_j:
                  # resolution of branch i is greater than branch_j
                  # branch_j will be upsample with nearest resize
                  layer.append(keras.Sequential(
                      [layers.Conv2D(filters=n_channels_list[branch_i], kernel_size=1, strides=1, padding='same',
                                     use_bias=False, activation=activation),
                       layers.BatchNormalization(momentum=bn_momentum)]))
              elif branch_i == branch_j:
                  # branch i is branch_j
                  layer.append(None)
  </code></pre>
  
  <p>The error message suggest that "If you don't need this list checkpointed, wrap it in a tf.contrib.checkpoint.NoDependency object; it will be automatically un-wrapped and subsequently ignored." However, tf 2.0 has no contri module.
  Any one knows how to solve this problem?</p>