class_docstr: Residual linear bottleneck block: x + F(x), F = bottleneck transform.
class_docstr_tok: ["Residual","linear","bottleneck","block",":","x","+","F","(","x",")",",","F","=","bottleneck","transform","."]
code: def forward(self, x):
      return x + self.f(x) if self.has_skip else self.f(x)
  
imports: import math
  from collections import OrderedDict
  from enum import auto, Enum
  from typing import Any, Dict, Optional, Sequence
  import torch.nn
  from classy_vision.generic.util import get_torch_version
  from classy_vision.models import ClassyModel, register_model
  from classy_vision.models.squeeze_and_excitation_layer import SqueezeAndExcitationLayer
label_desc: Use image node_id 2 for calling the ResBottleneckLinearBlock obj's underlying member method code with example usage: obj.forward(x) and returns: unknown