code: def _get_state_tensors(self, parameter):
      if not parameter in self.optimizer.state:
          return []
  
      tensor_list = []
      for value in self.optimizer.state[parameter].values():
          if torch.is_tensor(value):
              tensor_list.append(value)
  
      return tensor_list
  
imports: import os
  import torch
  from deepspeed import comm
  from deepspeed.utils.logging import logger
  from deepspeed.runtime.swap_tensor.constants import *
  from deepspeed.runtime.swap_tensor.utils import swap_in_tensors, swap_out_tensors, MIN_AIO_BYTES, AIO_ALIGNED_BYTES, get_sized_buffers
  from deepspeed.runtime.swap_tensor.utils import SwapBufferManager, SwapBufferPool
label_desc: Use image node_id 17 for calling the OptimizerSwapper obj's underlying member method code with example usage: obj._get_state_tensors(parameter) and returns: tensor_list, list