title: Variable length input for a simple neural network (Keras)
body: <p>Can a variable length, i.e. <code>input_dim=None</code>, be applied to a simple neural network? Specifically, the Keras Sequential model. I've been running into errors when trying to employ the same concept. I've already seen the documentation that seems to support this functionality:</p>
  
  <p><a href="https://keras.io/getting-started/functional-api-guide/" rel="nofollow noreferrer">https://keras.io/getting-started/functional-api-guide/</a></p>
  
  <p>But when I do the following...</p>
  
  <pre><code>model = Sequential()
  model.add(Dense(num_feat, input_dim = None, kernel_initializer = 'normal', activation='relu'))
  model.add(Dense(num_feat, kernel_initializer = 'normal', activation = 'relu'))
  model.add(Dropout(.2))
  model.add(Dense(num_feat, kernel_initializer = 'normal', activation = 'relu'))
  model.add(Dropout(.2))
  model.add(Dense(num_feat, kernel_initializer = 'normal', activation = 'relu'))
  model.add(Dropout(.2))
  model.add(Dense(ouput.shape[1], kernel_initializer = 'normal', activation = 'linear'))
  </code></pre>
  
  <p>...I get this error:</p>
  
  <pre><code>ValueError: ('Only Theano variables and integers are allowed in a size-tuple.', (None, 63), None)
  </code></pre>
  
  <p>Any help, ideas, or clarification would be greatly appreciated!!</p>