class_docstr: Token-based (input/output is tokens) retrieval encoder-decoder model
class_docstr_tok: ["Token-based","(","input\/output","is","tokens",")","retrieval","encoder-decoder","model"]
docstr: Customized load.
docstr_tok: ["Customized","load","."]
code: def load_state_dict(self, state_dict, strict=True):
      """Customized load."""
  
      self.encoder_embedding.encoder_embeddingload_state_dict(
          state_dict[self._encoder_embedding_key], strict=strict
      )
      self.encoder.load_state_dict(
          state_dict[self._encoder_key], strict=strict
      )
      self.pre_decoder.load_state_dict(
          state_dict[self._pre_decoder_key], strict=strict
      )
      self.post_decoder.load_state_dict(
          state_dict[self._post_decoder_key], strict=strict
      )
      self.tokens_head.load_state_dict(
          state_dict[self._tokens_head_key], strict=strict
      )
  
file_path: NeMo/nemo/collections/nlp/modules/common/megatron/retrieval_token_level_encoder_decoder.py
imports: import torch
  from nemo.collections.nlp.modules.common.megatron.language_model import Embedding
  from nemo.collections.nlp.modules.common.megatron.layer_type import LayerType
  from nemo.collections.nlp.modules.common.megatron.megatron_decoders import get_decoder_model
  from nemo.collections.nlp.modules.common.megatron.megatron_encoders import get_encoder_model
  from nemo.collections.nlp.modules.common.megatron.module import MegatronModule
  from nemo.collections.nlp.modules.common.megatron.mup.layer import MuReadout
  from nemo.collections.nlp.modules.common.megatron.utils import ApexGuardDefaults, init_method_normal, scaled_init_method_normal
label_desc: Use image node_id 5 for calling the MegatronRetrievalTokenLevelEncoderDecoderModule obj's underlying member method code with example usage: obj.load_state_dict(state_dict, strict) without return types