text: Title: Multiple-Input Batched Data
  Body: I'm trying to feed a RNN+LSTM Network using the `KerasModel` layer, and in my case, I need to use 2 inputs, and get a `Dense(1)` output.
  
  ```python
  train, test, val = dataset.get('train'), dataset.get('test'), dataset.get('val')
  train_ds = BatchData(train, batch_size, use_list=True)
  test_ds = BatchData(test, batch_size, use_list=True)
  
  M = KerasModel(create_model,
                 inputs_desc=[
                      InputDesc(tf.float32, [
                          None, timesteps_val, len(features_per_timestep)], 'input_a'),
                      InputDesc(tf.float32, [
                          None, timesteps_val, 96, 96, 1], 'input_b'),
                 ],
                 targets_desc=[InputDesc(tf.float32, [None, 1], 'labels')],
                 input=QueueInput(train_ds))
  ```
  
  If I remove the `use_list=True`, I got an error saying that batched data only works in Numpy Arrays. If I remove batching, or keep the way that its above, I got:
  
  ```
  [1024 15:03:14 @input_source.py:168] ERR Exception in EnqueueThread QueueInput/input_queue:
  Traceback (most recent call last):
    File "/Users/brunoalano/.local/share/virtualenvs/research-laYaeRqi/lib/python3.6/site-packages/tensorpack/input_source/input_source.py", line 159, in run
      feed = _make_feeds(self.placehdrs, dp)
    File "/Users/brunoalano/.local/share/virtualenvs/research-laYaeRqi/lib/python3.6/site-packages/tensorpack/input_source/input_source.py", line 41, in _make_feeds
      len(datapoint), len(placeholders))
  AssertionError: Size of datapoint and placeholders are different: 2 != 3
  ```
  
  Details:
  
  - Python Version: Python 3.6.5
  - TF Version: v1.11.0-rc2-4-gc19e29306c 1.11.0
  - Tensorpack Version (from git): 0.8.9