title: the list of Numpy arrays that you are passing to your model is not the size the model expected. Expected to see 2 array(s)
body: <p>Getting that error in Keras. 
  Scenario: 
  Input:</p>
  
  <ol>
  <li>Images with train shape as (50000, 32, 32, 3)</li>
  <li>Aux input with shape (50000, 1)</li>
  <li>Ground truth: (50000, 1)</li>
  </ol>
  
  <p>This is model fit code</p>
  
  <pre><code>x_train_input = Input(shape=(32,32,3))
  
  aux_rand_input = Input(shape=(1,))
  
  out = model_inst.build_model(x_train_input, aux_rand_input)
  
  model = Model(inputs=[x_train_input, aux_rand_input], outputs=[out])
  
  model.fit(x=[x_train, aux_input], y=y_train, batch_size=batch_size, steps_per_epoch=x_train.shape[0] // batch_size, epochs=maxepoches, validation_data=(x_test, y_test), callbacks=[reduce_lr, tensorboard], verbose=2)
  </code></pre>
  
  <p>Got this error when running this. </p>
  
  <blockquote>
    <p>Error when checking model input: the list of Numpy arrays that you are
    passing to your model is not the size the model expected. Expected to
    see 2 array(s), but instead got the following list of 1 arrays:</p>
  </blockquote>
  
  <p>And this is how <code>build_model</code>'s last few layers look like. </p>
  
  <pre><code>    flatten = Flatten()(drop_5)
      # aux_input = Input(shape=(1,))
      concat = Concatenate(axis=1)([flatten, aux_input])
  
      fc1 = Dense(512, kernel_regularizer=regularizers.l2(weight_decay))(concat)
      fc1 = Activation('relu')(fc1)
      fc1 = BatchNormalization()(fc1)
  
      fc1_drop = Dropout(0.5)(fc1)
      fc2 = Dense(self.num_classes)(fc1_drop)
      out = Activation('softmax')(fc2)
      return out
  </code></pre>