docstr: ### Generator to get layers
code: def get_layers(
      self,
  ) -> Generator[Tuple[NeoXModule, Tuple[str, str]], None, None]:
      """
      ### Generator to get layers
      """
      # Embedding layer
      if 0 in self.filter_layers:
          with monit.section("Embedding layer"):
              layer = self._prepare_layer(
                  self._create_embedding_layer()
              )
          yield layer, (
              "layer_00-model_00-model_states.pt",
              "layer_00-model_01-model_states.pt",
          )
  
      # Transformer layers
      for i in range(self.n_layers):
          # Transformer layer
          if i + 1 in self.filter_layers:
              with monit.section(f"Transformer Layer {i}"):
                  yield self._create_transformer_layer(), (
                      f"layer_{i + 2 :02d}-model_00-model_states.pt",
                      f"layer_{i + 2 :02d}-model_01-model_states.pt",
                  )
  
      # Final normalization layer
      if self.n_layers + 1 in self.filter_layers:
          with monit.section("Final norm layer"):
              layer = self._prepare_layer(
                  self._create_final_norm_layer()
              )
          yield layer, (
              "layer_47-model_00-model_states.pt",
              "layer_47-model_01-model_states.pt",
          )
  
      # Readout layer
      if self.n_layers + 2 in self.filter_layers:
          with monit.section("Readout layer"):
              layer = self._prepare_layer(self._create_readout_layer())
          yield layer, (
              "layer_48-model_00-model_states.pt",
              "layer_48-model_01-model_states.pt",
          )
  
      for k in self.pre_created_layers.keys():
          self.pre_created_layers[k] = None
  
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 9 for calling the LayerGenerator obj's underlying member method code with example usage: obj.get_layers() without return types