code: def call_checkpoint_bottleneck(self, input):
      # type: (List[Tensor]) -> Tensor
      def closure(*inputs):
          return self.bn_function(*inputs)
  
      return cp.checkpoint(closure, input)
  
imports: import re
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from collections import OrderedDict
  from torch.hub import load_state_dict_from_url
  from torch import Tensor
  from torch.jit.annotations import List
  from ..tools.custom_modules import FakeReLU
label_desc: Use image node_id 4 for calling the _DenseLayer obj's underlying member method code with example usage: obj.call_checkpoint_bottleneck(input) and returns: cp, self