class_docstr: Takes a list of inputs, each with a shape CHWN, and transposes
  to HWCN, then concatenates along the HWC axis.
class_docstr_tok: ["Takes","a","list","of","inputs",",","each","with","a","shape","CHWN",",","and","transposes","to","HWCN",",","then","concatenates","along","the","HWC","axis","."]
code: def bprop(self, error):
      # error is in (HWC, N)
      # need to transpose to (CHW, N) and unstack
      start = 0
      for delta, num_channels in zip(self.deltas, self.channels):
          # reshape (C, HW, N)
          rdelta = delta.reshape((num_channels, -1, self.be.bsz))
  
          C, HW, N = rdelta.shape
          end = start + C * HW
  
          error_view = error[start:end, :].reshape((HW, C, N))
  
          self.be.copy_transpose(error_view, rdelta, axes=(1, 0, 2))
          start = end
  
      return self.deltas
  
imports: from neon.layers.layer import Layer, ParameterLayer
  import numpy
  from neon.transforms import Softmax
  from neon.initializers.initializer import Constant
  import math
  from collections import OrderedDict
label_desc: Use image node_id 5 for calling the ConcatTranspose obj's underlying member method code with example usage: obj.bprop(error) and returns: self