code: def load_dataset(
      self, split: str, task_cfg: FairseqDataclass = None, **kwargs
  ):
      data_path = self.cfg.data
      cfg = task_cfg or self.cfg
  
      self.datasets[split] = MaeFinetuningImageDataset(
          root=data_path,
          split=split,
          is_train=split == "train",
          input_size=cfg.input_size,
          local_cache_path=cfg.local_cache_path,
          shuffle=split == "train",
      )
  
file_path: fairseq/examples/data2vec/tasks/mae_image_classification.py
imports: import logging
  import sys
  import torch
  from typing import Optional
  from dataclasses import dataclass, field
  from omegaconf import MISSING
  from fairseq.dataclass import FairseqDataclass
  from fairseq.tasks import FairseqTask, register_task
  from fairseq.logging import metrics
label_desc: Use image node_id 2 for calling the MaeImageClassificationTask obj's underlying member method code with example usage: obj.load_dataset(split, task_cfg) without return types