docstr: :param input_chns: int, number of input channel
  :return: tuple, with series of convolutional layers
docstr_tok: [":","param","input_chns",":","int",",","number","of","input","channel",":","return",":","tuple",",","with","series","of","convolutional","layers"]
code: def create(self, input_chns):
      """
  
      :param input_chns: int, number of input channel
      :return: tuple, with series of convolutional layers
      """
      if self.n_output_chns == input_chns:
          b1 = self.Conv(
              self.bottle_neck_chns, kernel_size=1, stride=self.stride
          )
          b2 = self.Conv(self.bottle_neck_chns, kernel_size=3)
          b3 = self.Conv(self.n_output_chns, 1)
          return BottleneckBlockDesc1(conv=[b1, b2, b3])
      else:
          b1 = BNLayer()
          b2 = self.Conv(
              self.bottle_neck_chns,
              kernel_size=1,
              stride=self.stride,
              acti_func=None,
              feature_normalization=None,
          )
          b3 = self.Conv(self.bottle_neck_chns, kernel_size=3)
          b4 = self.Conv(self.n_output_chns, kernel_size=1)
          b5 = self.Conv(
              self.n_output_chns,
              kernel_size=1,
              stride=self.stride,
              acti_func=None,
              feature_normalization=None,
          )
          return BottleneckBlockDesc2(
              common_bn=b1, conv=[b2, b3, b4], conv_shortcut=b5
          )
  
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 2 for calling the BottleneckBlock obj's underlying member method code with example usage: obj.create(input_chns) and returns: BottleneckBlockDesc1, BottleneckBlockDesc2