code: def __init__(
      self,
      dictionary,
      sup_speech_encoder,
      sup_s2s_speech_encoder,
      unsup_speech_encoder,
      text_encoder,
  ):
      super().__init__(dictionary)
      self.sup_speech_encoder = sup_speech_encoder
      self.sup_s2s_speech_encoder = sup_s2s_speech_encoder
      self.unsup_speech_encoder = unsup_speech_encoder
      self.text_encoder = text_encoder
  
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 1 to create a new SpeechTextPreTrainEncoder object from inherited base classes: MultiModalityEncoder with example: obj = SpeechTextPreTrainEncoder(dictionary, sup_speech_encoder, sup_s2s_speech_encoder, unsup_speech_encoder, text_encoder)