class_docstr: Transformer encoder model.
      
docstr: For easy load.
docstr_tok: ["For","easy","load","."]
code: def state_dict_for_save_checkpoint(
      self, destination=None, prefix="", keep_vars=False
  ):
      """For easy load."""
  
      state_dict_ = {}
  
      state_dict_[
          self._model_key
      ] = self.model.state_dict_for_save_checkpoint(
          destination, prefix, keep_vars
      )
  
      return state_dict_
  
imports: import torch
  import torch.nn.functional
  from einops import rearrange, repeat
  from nemo.collections.nlp.modules.common.megatron.module import MegatronModule
  from nemo.collections.nlp.modules.common.megatron.position_embedding import RotaryEmbedding
  from nemo.collections.nlp.modules.common.megatron.transformer import ParallelTransformer
  from nemo.collections.nlp.modules.common.megatron.utils import ApexGuardDefaults, build_attention_mask_3d
label_desc: Use image node_id 5 for calling the MegatronRetrievalTransformerEncoderModule obj's underlying member method code with example usage: obj.state_dict_for_save_checkpoint(destination, prefix, keep_vars) and returns: state_dict_