code: def test_layer_container_unsupported_layer(
      backend_default, test_args, deltas_buffer
  ):
      (
          indim,
          nifm,
          fshape,
          nofm,
          batch_size,
          stride,
          pad,
          init_unif,
      ) = test_args
      in_shape = indim
  
      def fail_on_accumulate_updates(f):
          def wrapper(*args, **kwargs):
              if "accumulate_updates" in kwargs:
                  raise AttributeError(
                      "Should not have gotten accumulate updates"
                  )
              out = f(*args, **kwargs)
              return out
  
          return wrapper
  
      unsupportedLayer = Linear(nout=indim, init=init_unif)
      unsupportedLayer.allocate = fail_on_accumulate_updates(
          unsupportedLayer.allocate
      )
      containerTest = LayerTest(
          Sequential(
              [
                  Linear(nout=indim, init=init_unif),
                  unsupportedLayer,
                  Linear(nout=indim, init=init_unif),
              ]
          ),
          in_shape,
          batch_size,
          deltas_buffer,
      )
      containerTest.test(["dW"])
  
imports: from utils import tensors_allclose, allclose_with_out
  import numpy
  import pytest
  from neon import NervanaObject
  from neon.initializers.initializer import Uniform
  from neon.layers.layer import Convolution, Deconvolution, Layer, Linear, Bias, BatchNorm
  from neon.layers.container import Sequential
label_desc: Use image node_id 16 for calling a global function with example usage: test_layer_container_unsupported_layer(backend_default, test_args, deltas_buffer) and returns: wrapper, out