code: def __init__(self, cfg: MultimodalPretrainingConfig):
      super().__init__(cfg)
      self.audio_task = (
          AudioPretrainingTask(cfg.audio)
          if cfg.audio is not None
          else None
      )
      self.image_task = (
          MaeImagePretrainingTask(cfg.image)
          if cfg.image is not None
          else None
      )
      self.text_task = (
          MaskedLMTask(cfg.text) if cfg.text is not None else None
      )
  
      self.mult_ratios = []
  
imports: import sys
  from dataclasses import dataclass
  from typing import Optional, List
  from omegaconf import II
  from fairseq.data.iterators import GroupedEpochBatchIterator
  from fairseq.dataclass import FairseqDataclass
  from fairseq.tasks import FairseqTask, register_task
  from fairseq.tasks.audio_pretraining import AudioPretrainingConfig, AudioPretrainingTask
  from fairseq.tasks.masked_lm import MaskedLMConfig, MaskedLMTask
  from .mae_image_pretraining import MaeImagePretrainingConfig, MaeImagePretrainingTask
  from examples.data2vec.data.modality import Modality
  from fairseq.data.audio.multi_modality_dataset import MultiModalityDataset, ModalityDatasetItem
label_desc: Use image node_id 1 to create a new MultimodalPretrainingTask object from inherited base classes: FairseqTask with example: obj = MultimodalPretrainingTask(cfg)