title: How to write a net with a Memory Data Layer using pycaffe?
body: <p>It is possible to write a caffe prototxt in pycaffe with a hdf5 data layer from the following lines:</p>
  
  <pre><code>import caffe
  from caffe import layers as L
  
  def logreg(hdf5, batch_size):
      n = caffe.NetSpec()
      n.data, n.label = L.HDF5Data(batch_size = batch_size, source = hdf5, ntop = 2)
      n.ip1 = L.InnerProduct(n.data, num_output = 2, weight_filler = dict(type='xavier'))
      n.accuracy = L.Accuracy(n.ip1, n.label)
      n.loss = L.SoftmaxWithLoss(n.ip1, n.label)
      return n.to_proto()
  
  with open('models/logreg_auto_train.prototxt', 'w') as f:
      f.write(str(logreg('data/train.txt', chunck_size)))
  </code></pre>
  
  <p>Is it possible to use a similar method to write a prototxt that has a Memory Data Layer?</p>