code: def create_network():
      layers = [
          DataTransform(transform=Normalizer(divisor=128.0)),
          Conv(
              (11, 11, 96),
              init=Kaiming(),
              activation=Rectlin(),
              strides=4,
              padding=1,
          ),
          Conv(
              (1, 1, 96),
              init=Kaiming(),
              activation=Rectlin(),
              strides=1,
          ),
          Conv(
              (3, 3, 96),
              init=Kaiming(),
              activation=Rectlin(),
              strides=2,
              padding=1,
          ),  # 54->2,
          Conv(
              (5, 5, 256),
              init=Kaiming(),
              activation=Rectlin(),
              strides=1,
          ),  # 27->2,
          Conv(
              (1, 1, 256),
              init=Kaiming(),
              activation=Rectlin(),
              strides=1,
          ),
          Conv(
              (3, 3, 256),
              init=Kaiming(),
              activation=Rectlin(),
              strides=2,
              padding=1,
          ),  # 23->1,
          Conv(
              (3, 3, 384),
              init=Kaiming(),
              activation=Rectlin(),
              strides=1,
              padding=1,
          ),
          Conv(
              (1, 1, 384),
              init=Kaiming(),
              activation=Rectlin(),
              strides=1,
          ),
          Conv(
              (3, 3, 384),
              init=Kaiming(),
              activation=Rectlin(),
              strides=2,
              padding=1,
          ),  # 12->,
          Dropout(keep=0.5),
          Conv(
              (3, 3, 1024),
              init=Kaiming(),
              activation=Rectlin(),
              strides=1,
              padding=1,
          ),
          Conv(
              (1, 1, 1024),
              init=Kaiming(),
              activation=Rectlin(),
              strides=1,
          ),
          Conv(
              (1, 1, 1000),
              init=Kaiming(),
              activation=Rectlin(),
              strides=1,
          ),
          Pooling(6, op="avg"),
          Activation(Softmax()),
      ]
  
      return Model(layers=layers), GeneralizedCost(
          costfunc=CrossEntropyMulti()
      )
  
imports: from neon.initializers import Kaiming
  from neon.layers import Conv, Pooling, GeneralizedCost, Dropout, DataTransform, Activation
  from neon.transforms import Rectlin, Softmax, CrossEntropyMulti, Normalizer
  from neon.models import Model
label_desc: Use image node_id 1 for calling a global function with example usage: create_network() and returns: Model,  GeneralizedCost