class_docstr: Bottleneck Block for ResNet152_vd.
class_docstr_tok: ["Bottleneck","Block","for","ResNet152_vd","."]
code: def forward(self, inputs: paddle.Tensor):
      y = self.conv0(inputs)
      conv1 = self.conv1(y)
      conv2 = self.conv2(conv1)
  
      if self.shortcut:
          short = inputs
      else:
          short = self.short(inputs)
      y = paddle.elementwise_add(x=short, y=conv2, act="relu")
      return y
  
imports: import os
  import math
  import numpy
  import paddle
  from paddle import ParamAttr
  import paddle.nn
  from paddle.nn import Conv2d, BatchNorm, Linear, Dropout
  from paddle.nn import AdaptiveAvgPool2d, MaxPool2d, AvgPool2d
  from paddle.nn.initializer import Uniform
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.cv_module import ImageClassifierModule
label_desc: Use image node_id 2 for calling the BottleneckBlock obj's underlying member method code with example usage: obj.forward(inputs) and returns: y