docstr: :param n_output_chns: int, number of output channels
  :param count: int, number of BottleneckBlocks to generate
  :param stride: int, stride for convolutional layer
  :param Conv: Layer, convolutional layer
  :param name: layer name
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code: def __init__(
      self, n_output_chns, count, stride, Conv, name="downres"
  ):
      """
  
      :param n_output_chns: int, number of output channels
      :param count: int, number of BottleneckBlocks to generate
      :param stride: int, stride for convolutional layer
      :param Conv: Layer, convolutional layer
      :param name: layer name
      """
      self.count = count
      self.stride = stride
      self.n_output_chns = n_output_chns
      self.Conv = Conv
      super(DownResBlock, self).__init__(name=name)
  
imports: from __future__ import absolute_import, print_function
  import functools
  from collections import namedtuple
  import tensorflow
  from niftynet.layer import layer_util
  from niftynet.layer.base_layer import TrainableLayer
  from niftynet.layer.bn import BNLayer
  from niftynet.layer.convolution import ConvolutionalLayer
  from niftynet.layer.fully_connected import FCLayer
  from niftynet.network.base_net import BaseNet
label_desc: Use image node_id 1 to create a new DownResBlock object from inherited base classes: TrainableLayer with example: obj = DownResBlock(n_output_chns, count, stride, Conv, name)