class_docstr: Residual bottleneck block: x + f(x), f = bottleneck transform.
class_docstr_tok: ["Residual","bottleneck","block",":","x","+","f","(","x",")",",","f","=","bottleneck","transform","."]
code: def forward(self, x):
      x_p = self.bn(self.proj(x)) if self.proj else x
      return self.af(x_p + self.f(x))
  
imports: import numpy
  from torch import nn
  from detectron2.layers import CNNBlockBase, ShapeSpec, get_norm
  from .backbone import Backbone
label_desc: Use image node_id 2 for calling the ResBottleneckBlock obj's underlying member method code with example usage: obj.forward(x) and returns: self