code: def get_dataset_itr(
      self, disable_iterator_cache: bool = False
  ) -> None:
      return self.task.get_batch_iterator(
          dataset=self.task.dataset(self.cfg.dataset.gen_subset),
          max_tokens=self.cfg.dataset.max_tokens,
          max_sentences=self.cfg.dataset.batch_size,
          max_positions=(sys.maxsize, sys.maxsize),
          ignore_invalid_inputs=self.cfg.dataset.skip_invalid_size_inputs_valid_test,
          required_batch_size_multiple=self.cfg.dataset.required_batch_size_multiple,
          seed=self.cfg.common.seed,
          num_shards=self.data_parallel_world_size,
          shard_id=self.data_parallel_rank,
          num_workers=self.cfg.dataset.num_workers,
          data_buffer_size=self.cfg.dataset.data_buffer_size,
          disable_iterator_cache=disable_iterator_cache,
      ).next_epoch_itr(shuffle=False)
  
imports: import ast
  import hashlib
  import logging
  import os
  import shutil
  import sys
  import re
  from dataclasses import dataclass, field, is_dataclass
  from pathlib import Path
  from typing import Any, Dict, List, Optional, Tuple, Union
  import editdistance
  import torch
  import torch.distributed
  from examples.speech_recognition.new.decoders.decoder_config import DecoderConfig, FlashlightDecoderConfig
  from examples.speech_recognition.new.decoders.decoder import Decoder
  from fairseq import checkpoint_utils, distributed_utils, progress_bar, tasks, utils
  from fairseq.data.data_utils import post_process
  from fairseq.dataclass.configs import CheckpointConfig, CommonConfig, CommonEvalConfig, DatasetConfig, DistributedTrainingConfig, FairseqDataclass
  from fairseq.logging.meters import StopwatchMeter, TimeMeter
  from fairseq.logging.progress_bar import BaseProgressBar
  from fairseq.models.fairseq_model import FairseqModel
  from omegaconf import OmegaConf
  import hydra
  from hydra.core.config_store import ConfigStore
label_desc: Use image node_id 11 for calling the InferenceProcessor obj's underlying member method code with example usage: obj.get_dataset_itr(disable_iterator_cache) and returns: self