code: def get_state_buffer(self, p, dtype=torch.float32):
      if not self.is_paged or p.numel() < 1e5:
          return torch.zeros_like(p, dtype=dtype, device=p.device)
      else:
          # > 1 MB
          buff = F.get_paged(*p.shape, dtype=dtype, device=p.device)
          F.fill(buff, 0)
          self.page_mng.paged_tensors.append(buff)
          return buff
  
imports: from collections import abc
  from collections import defaultdict
  from copy import deepcopy
  from itertools import chain
  import torch
  import bitsandbytes.functional
label_desc: Use image node_id 11 for calling the Optimizer8bit obj's underlying member method code with example usage: obj.get_state_buffer(p, dtype) and returns: torch, buff