docstr: Upgrade old state dicts to work with newer code.
docstr_tok: ["Upgrade","old","state","dicts","to","work","with","newer","code","."]
code: def upgrade_state_dict(self, state_dict):
      """Upgrade old state dicts to work with newer code."""
      if (
          "decoder.speech_decoder.output_projection.weight"
          in state_dict
      ):
          del state_dict[
              "decoder.speech_decoder.output_projection.weight"
          ]
      self.upgrade_state_dict_named(state_dict, "")
  
imports: import logging
  from collections import OrderedDict, namedtuple
  from typing import Dict, Optional
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from fairseq import checkpoint_utils, utils
  from fairseq.file_io import PathManager
  from fairseq.models import FairseqDecoder, FairseqEncoderDecoderModel, register_model, register_model_architecture
  from fairseq.models.speech_to_text import MultiInputDecoder, MultiModalityEncoder, SpeechWavTransformerEncoder, StackedSpeechWavTransformerEncoder
  from fairseq.models.transformer import TransformerDecoder, TransformerEncoder, TransformerModel
label_desc: Use image node_id 8 for calling the SpeechTextPreTrainModel obj's underlying member method code with example usage: obj.upgrade_state_dict(state_dict) without return types