code: def create_network():
      init = GlorotUniform()
      layers = [
          Conv(
              (3, 3, 128),
              init=init,
              activation=Rectlin(),
              strides=dict(str_h=1, str_w=2),
          ),
          Conv(
              (3, 3, 256),
              init=init,
              batch_norm=True,
              activation=Rectlin(),
          ),
          Pooling(2, strides=2),
          Conv(
              (2, 2, 512),
              init=init,
              batch_norm=True,
              activation=Rectlin(),
          ),
          DeepBiRNN(
              256,
              init=init,
              activation=Rectlin(),
              reset_cells=True,
              depth=3,
          ),
          RecurrentLast(),
          Affine(32, init=init, batch_norm=True, activation=Rectlin()),
          Affine(nout=2, init=init, activation=Softmax()),
      ]
  
      return Model(layers=layers), GeneralizedCost(
          costfunc=CrossEntropyBinary()
      )
  
imports: from neon.initializers import GlorotUniform
  from neon.layers import Conv, Pooling, GeneralizedCost, Affine, DeepBiRNN, RecurrentLast
  from neon.models import Model
  from neon.transforms import CrossEntropyBinary, Rectlin, Softmax
label_desc: Use image node_id 1 for calling a global function with example usage: create_network() and returns: Model,  GeneralizedCost