code: def forward(self, x):
      identity = x
  
      out = self.conv1(x)
      out = self.bn1(out)
      out = self.relu(out)
  
      out = self.conv2(out)
      out = self.bn2(out)
      out = self.relu(out)
  
      out = self.conv3(out)
      out = self.bn3(out)
  
      if self.downsample is not None:
          identity = self.downsample(x)
  
      out += identity
      out = self.relu(out)
  
      return out
  
imports: import os
  from typing import Union
  import numpy
  import paddle
  import paddle.nn
  import paddlehub.vision.transforms
  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(x) and returns: out