code: def load(weights, model, K, fsz, dil):
      index = 0
      layers = model.layers
      for layer in layers._layers:
          if hasattr(layer, "W"):
              if layer.W.shape == weights[index].shape:
                  layer.W[:] = weights[index]
              else:
                  layer.W[:] = dilate(weights[index], K, fsz, dil)
              index += 1
  
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 7 for calling a global function with example usage: load(weights, model, K, fsz, dil) without return types