docstr: #### Creates and caches a layer
  
  Copying cached layers is faster than initializing new layers because it takes time to
  initialize parameters.
  
  :param name: is the name of the layer
  :param creator: is the function to create the layer
  :return: the created layer or a copy of the cached layer
code: def _create_and_cache_layer(
      self, name: str, creator: Callable[[], NeoXModule]
  ):
      """
      #### Creates and caches a layer
  
      Copying cached layers is faster than initializing new layers because it takes time to
      initialize parameters.
  
      :param name: is the name of the layer
      :param creator: is the function to create the layer
      :return: the created layer or a copy of the cached layer
      """
  
      if not self.is_clone_layers:
          return self._prepare_layer(creator())
  
      if self.pre_created_layers[name] is None:
          self.pre_created_layers[name] = self._prepare_layer(creator())
  
      layer = copy.deepcopy(self.pre_created_layers[name])
      return layer
  
imports: import copy
  import math
  from typing import Dict, Optional, Set, Callable, Any, Generator, Tuple
  import torch
  from torch import nn
  from torch.cuda.amp import autocast
  from labml import monit, logger
  from labml.logger import Text
  from labml_nn.neox import checkpoint
  from labml_nn.neox.utils.cache import get_cache
label_desc: Use image node_id 4 for calling the LayerGenerator obj's underlying member method code with example usage: obj._create_and_cache_layer(name, creator) and returns: layer, self