code: def forward(self, x):
      residual = 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:
          residual = self.downsample(x)
  
      out += residual
      out = self.relu(out)
  
      return out
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  import math
  from functools import partial
label_desc: Use image node_id 2 for calling the Bottleneck obj's underlying member method code with example usage: obj.forward(x) and returns: out