title: ValueError: Error when checking : expected input_2 to have shape (162,) but got array with shape (1,)
body: <p>I have defined the following model in Keras:</p>
  
  <pre><code>init_weights = he_normal()
  main_input = Input(shape=(FEATURE_VECTOR_SIZE,)) #size 54
  aux_input = Input(shape=(AUX_FEATURE_VECTOR_SIZE,)) #size 162
  merged_input = concatenate([main_input, aux_input])
  
  shared1 = Dense(164, activation='relu', kernel_initializer=init_weights)(merged_input)
  shared2 = Dense(150, activation='relu', kernel_initializer=init_weights)(shared1)
  
  main_output = Dense(NUM_ACTIONS, activation='linear', kernel_initializer=init_weights, name='main_output')(shared2)
  aux_output = Dense(1, activation='linear', kernel_initializer=init_weights, name='aux_output')(shared2)
  
  rms = RMSprop(lr=ALPHA)
  model = Model(inputs=[main_input, aux_input], outputs=[main_output, aux_output])
  model.compile(optimizer=rms, loss='mse')
  </code></pre>
  
  <p>Later on I attempt to use it to make a prediction, as below:</p>
  
  <pre><code>aux_dummy = np.zeros(shape=(AUX_FEATURE_VECTOR_SIZE,))
  print(aux_dummy.shape)
  print(aux_dummy)
  q_vals, _ = model.predict([encode_1_hot(next_state), aux_dummy], batch_size=1)
  </code></pre>
  
  <p>However, I get an error complaining that the auxiliary input is not of the proper shape (Keras claims it should be shape (162,) and that it is actually shape (1,))</p>
  
  <p>But when I print out the shape I get exactly what it seems to be asking for (see below).</p>
  
  <pre>
  (162,)
  [0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
   0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
   0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
   0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
   0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
   0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
   0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
  Traceback (most recent call last):
    File "grid_exp.py", line 94, in 
      RL_episode(max_steps)
    File "/Users/ZerkTheMighty/Code/RL2/project/Gridworld/rl_glue.py", line 220, in RL_episode
      rl_step_result = RL_step()
    File "/Users/ZerkTheMighty/Code/RL2/project/Gridworld/rl_glue.py", line 151, in RL_step
      last_action = agent.agent_step(result['reward'],result['state'])
    File "/Users/ZerkTheMighty/Code/RL2/project/Gridworld/grid_agent.py", line 170, in agent_step
      q_vals, _ = model.predict([encode_1_hot(next_state), aux_dummy], batch_size=1)
    File "/Users/ZerkTheMighty/Code/RL2/lib/python2.7/site-packages/keras/engine/training.py", line 1817, in predict
      check_batch_axis=False)
    File "/Users/ZerkTheMighty/Code/RL2/lib/python2.7/site-packages/keras/engine/training.py", line 123, in _standardize_input_data
      str(data_shape))
  ValueError: Error when checking : expected input_2 to have shape (162,) but got array with shape (1,)
  </pre>
  
  <p>I'm at a loss as to what I should be changing in order to get this to work, but I have a suspicion that I'm overlooking something obvious. Suggestions?</p>
  
  <p>I'm using Keras 2.1.5, Theano 1.0.1, numpy 1.14.2, and python 2.7.12</p>