class_docstr: Encoder decoder CTC-based models with Byte Pair Encoding.
class_docstr_tok: ["Encoder","decoder","CTC-based","models","with","Byte","Pair","Encoding","."]
code: def _setup_dataloader_from_config(self, config: Optional[Dict]):
      dataset = video_to_text_dataset.get_video_to_text_bpe_dataset_from_config(
          config=config,
          local_rank=self.local_rank,
          global_rank=self.global_rank,
          world_size=self.world_size,
          tokenizer=self.tokenizer,
          preprocessor_cfg=self.cfg.get("preprocessor", None),
      )
  
      if dataset is None:
          return None
  
      shuffle = config["shuffle"]
      if config.get("is_tarred", False):
          shuffle = False
  
      if hasattr(dataset, "collate_fn"):
          collate_fn = dataset.collate_fn
      else:
          collate_fn = dataset.datasets[0].collate_fn
  
      return torch.utils.data.DataLoader(
          dataset=dataset,
          batch_size=config["batch_size"],
          collate_fn=collate_fn,
          drop_last=config.get("drop_last", False),
          shuffle=shuffle,
          num_workers=config.get("num_workers", 0),
          pin_memory=config.get("pin_memory", False),
          prefetch_factor=config.get("prefetch_factor", 2),
      )
  
imports: import copy
  import os
  from typing import Dict, List, Optional, Union
  import torch
  from omegaconf import DictConfig, ListConfig, OmegaConf, open_dict
  from nemo.collections.asr.losses.ctc import CTCLoss
  from nemo.collections.asr.metrics.wer import WER
  from nemo.collections.asr.parts.mixins import ASRBPEMixin
  from nemo.collections.asr.parts.submodules.ctc_decoding import CTCBPEDecoding, CTCBPEDecodingConfig
  from nemo.collections.multimodal.speech_cv.data import video_to_text_dataset
  from nemo.collections.multimodal.speech_cv.models.visual_ctc_models import VisualEncDecCTCModel
  from nemo.core.classes.common import PretrainedModelInfo
  from nemo.utils import logging, model_utils
label_desc: Use image node_id 2 for calling the VisualEncDecCTCModelBPE obj's underlying member method code with example usage: obj._setup_dataloader_from_config(config) and returns: torch, None