class_docstr: Base class for bottlenecks that implements `forward()` method.
class_docstr_tok: ["Base","class","for","bottlenecks","that","implements","`","forward","(",")","`","method","."]
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 = self.se_module(out) + residual
      out = self.relu(out)
  
      return out
  
imports: from __future__ import print_function, division, absolute_import
  from collections import OrderedDict
  import math
  import torch.nn
  from torch.utils import model_zoo
label_desc: Use image node_id 1 for calling the Bottleneck obj's underlying member method code with example usage: obj.forward(x) and returns: out