code: def test_dilated_conv(backend_default, fargs_tests):
      fsz = fargs_tests[0]
      dil = fargs_tests[1]
      stride = fargs_tests[2]
      be = backend_default
  
      o1, w1 = run(be, False, fsz, stride, 1, dil)
      o2, w2 = run(be, True, fsz, stride, 1, dil)
      # Verify that the results of faked dilation match those of actual dilation.
      assert allclose_with_out(o1, o2, atol=1e-1, rtol=4e-3)
      try:
          assert allclose_with_out(w1, w2, atol=0, rtol=1e-3)
      except Exception:
          if not isinstance(NervanaObject.be, NervanaGPU):
              assert allclose_with_out(w1, w2, atol=1e-1, rtol=1e-3)
          else:
              assert allclose_with_out(w1, w2, atol=0, rtol=1e-3)
  
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 10 for calling a global function with example usage: test_dilated_conv(backend_default, fargs_tests) without return types