code: def fprop(model, inputs):
      layers = model.layers
      for l in layers._layers:
          l.be.convert_data(inputs, l.get_is_mklop())
          inputs = l.fprop(inputs)
      # Return outputs from the last layer.
      return layers._layers[-1].outputs
  
imports: from __future__ import print_function
  import itertools
  import numpy
  from neon.backends import gen_backend
  from neon.layers import Conv, Affine, GeneralizedCost
  from neon.models import Model
  from neon.initializers.initializer import Gaussian
  from neon.transforms import CrossEntropyBinary
  from neon.optimizers import GradientDescentMomentum
  from utils import allclose_with_out
  from neon import NervanaObject
label_desc: Use image node_id 2 for calling a global function with example usage: fprop(model, inputs) and returns: layers