code: def check_broadcast(ms_layer):
      for branch in ms_layer.layers:
          assert type(branch) is Sequential
          # first layer in each branch should share
          # the container deltas
          assert branch.layers[0].deltas.ptr == ms_layer.deltas.ptr
          ptr = None
          for layer in branch.layers[1:]:
              if ptr is None:
                  assert layer.deltas is not None
                  ptr = layer.deltas.ptr
              else:
                  assert layer.deltas.ptr != ptr
                  ptr = layer.deltas.ptr
  
imports: import numpy
  import pytest
  from builtins import zip
  from neon import NervanaObject
  from neon.initializers import Gaussian, Constant, Kaiming
  from neon.layers import GeneralizedCost, Affine, Activation, Dropout
  from neon.layers import Conv, Pooling, Sequential, MergeMultistream
  from neon.layers import MergeSum, SkipNode, BatchNorm, MergeBroadcast, GeneralizedCostMask
  from neon.layers import BranchNode, Multicost, SingleOutputTree, LSTM
  from neon.layers.container import Broadcast
  from neon.models import Model
  from neon.transforms import Rectlin, CrossEntropyBinary, Softmax, Tanh
  from neon.transforms import Logistic, CrossEntropyMulti
label_desc: Use image node_id 1 for calling a global function with example usage: check_broadcast(ms_layer) without return types