title: How to use Merge layer (concat function) on Keras 2.0.0?
body: <p>I am trying to reproduce the entity embedding models using Keras. Here is the <a href="https://github.com/entron/entity-embedding-rossmann" rel="noreferrer">github link</a> and use the <code>kaggle</code> branch. There is one python file <code>models.py</code> and the <code>Merge</code> layer is used.</p>
  
  <p><code>
  from keras.layers.core import Dense, Dropout, Activation, Merge, Reshape
  ......<br>
  self.model.add(Merge(models, mode='concat'))
  </code></p>
  
  <p>This code should be fine for old-version of Keras,  but using Keras 2.0.0 using tensorflow 1.0.0 as the backend (python 2.7), there will be wrong information:
  <code>
  Using TensorFlow backend.
  Traceback (most recent call last):
    File "/Users/pengjuzhao/Udacity/MLND/entity-embedding-rossmann/test_model.py", line 2, in &lt;module&gt;
      from models import NN_with_EntityEmbedding
    File "/Users/pengjuzhao/Udacity/MLND/entity-embedding-rossmann/models.py", line 8, in &lt;module&gt;
      from keras.layers.core import Dense, Dropout, Activation, Merge, Reshape
  ImportError: cannot import name Merge
  [Finished in 1.8s with exit code 1]
  [shell_cmd: python -u "/Users/pengjuzhao/Udacity/MLND/entity-embedding-rossmann/test_model.py"]
  [dir: /Users/pengjuzhao/Udacity/MLND/entity-embedding-rossmann]
  [path: /usr/bin:/bin:/usr/sbin:/sbin]
  </code></p>
  
  <p>Is there anyone who knows how to reach the same target(<code>self.model.add(Merge(models, mode='concat'))</code>)or how to use the merge/Merge layer  using Keras 2.0.0 ?
  Thank you in advance. </p>