title: Load Tensorflow v1 model weights into a Tensorflow Core 2.0 alpha model (which is a tf.keras.Model)
body: <p>I have a checkpoint that was created with tf.train.Saver(). I am currently updating my codebase to Tensorflow v2.0 that uses eager execution and I am trying to load this checkpoint into a tf.keras.Model. </p>
  
  <pre><code>    model = MyModel()
      model.load_weights(checkpoint_path)
  </code></pre>
  
  <p>However, this throws the following error:</p>
  
  <p>NotImplementedError: Streaming restore not supported from name-based checkpoints. File a feature request if this limitation bothers you.</p>
  
  <p>I also tried to use CheckpointManager without much success.</p>
  
  <pre><code>    ckpt = tf.train.Checkpoint(net=model)
      manager = tf.train.CheckpointManager(ckpt, "path/to/checkpoint_dir", max_to_keep=3)
      ckpt.restore(manager.latest_checkpoint) 
  </code></pre>
  
  <p>Is there a way to use TF v1 model weights in TF v2 ?</p>
  
  <p>It is really time consuming to retrain models on ImageNet from scratch.</p>