class_docstr: Hugging Face Transformers Decoder.
  
  Args:
      encoder_output_size: dimension of encoder attention
      model_name_or_path: Hugging Face Transformers model name
class_docstr_tok: ["Hugging","Face","Transformers","Decoder",".","Args",":","encoder_output_size",":","dimension","of","encoder","attention","model_name_or_path",":","Hugging","Face","Transformers","model","name"]
code: def reload_pretrained_parameters(self):
      self.decoder.load_state_dict(self.decoder_pretrained_params)
  
      if self.lm_head_pretrained_params is not None:
          self.lm_head.load_state_dict(self.lm_head_pretrained_params)
  
      logging.info("Pretrained Transformers model parameters reloaded!")
  
file_path: espnet/espnet2/asr/decoder/hugging_face_transformers_decoder.py
imports: import copy
  import logging
  from typing import Any, List, Tuple
  import torch
  import torch.nn.functional
  from typeguard import check_argument_types
  from espnet2.asr.decoder.abs_decoder import AbsDecoder
  from espnet.nets.pytorch_backend.nets_utils import make_pad_mask
  from espnet.nets.scorer_interface import BatchScorerInterface
label_desc: Use image node_id 3 for calling the HuggingFaceTransformersDecoder obj's underlying member method code with example usage: obj.reload_pretrained_parameters() without return types