code: def build_model(cls, args, task):
      encoder = SpeechTextPreTrainEncoder.build_encoder(
          args, task.src_dict
      )
      decoder = SpeechTextPreTrainDecoder.build_decoder(
          args,
          task.tgt_dict,
          task.src_dict,
          encoder.text_encoder.embed_tokens,
      )
      model = SpeechTextPreTrainModel(encoder, decoder)
      return model
  
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 7 for calling the SpeechTextPreTrainModel obj's underlying member method code with example usage: obj.build_model(cls, args, task) and returns: model