class_docstr: ## Zero3 Layer
  
  Each layer of the model (or a combination of a few consecutive layers) should be wrapped in
  this module.
class_docstr_tok: ["#","#","Zero3","Layer","Each","layer","of","the","model","(","or","a","combination","of","a","few","consecutive","layers",")","should","be","wrapped","in","this","module","."]
docstr: #### Create an empty tensor of the given shape.
docstr_tok: ["#","#","#","#","Create","an","empty","tensor","of","the","given","shape","."]
code: def _empty(self, shape: Tuple[int, ...]) -> torch.Tensor:
      """
      #### Create an empty tensor of the given shape.
      """
      return torch.empty(shape, device=self.device, dtype=self.dtype)
  
imports: import functools
  from typing import List, Optional, Tuple
  import torch
  import torch.distributed
  from torch import nn
label_desc: Use image node_id 4 for calling the Zero3Layer obj's underlying member method code with example usage: obj._empty(shape) and returns: torch