code: def forward(self, x, arg_route=(True, False), **kwargs):
      reverse = x.shape[1] > self.reverse_thres
      blocks = self.blocks if reverse else self.irrev_blocks
  
      if self.training and self.layer_dropout > 0:
          to_drop = (
              torch.empty(len(self.blocks)).uniform_(0, 1)
              < self.layer_dropout
          )
          blocks = [
              block
              for block, drop in zip(self.blocks, to_drop)
              if not drop
          ]
          blocks = self.blocks[:1] if len(blocks) == 0 else blocks
  
      f_args, g_args = map(
          lambda route: kwargs if route else {}, arg_route
      )
      block_kwargs = {"f_args": f_args, "g_args": g_args}
  
      if not reverse:
          for block in blocks:
              x = block(x, **block_kwargs)
          return x
  
      return _ReversibleFunction.apply(x, blocks, block_kwargs)
  
imports: import torch
  import torch.nn
  from torch.autograd.function import Function
  from torch.utils.checkpoint import get_device_states, set_device_states
label_desc: Use image node_id 2 for calling the ReversibleSequence obj's underlying member method code with example usage: obj.forward(x, arg_route) and returns: _ReversibleFunction, x