class_docstr: Base class for encoder decoder RNNT-based models.
docstr: Sets up the validation data loader via a Dict-like object.
  
  Args:
      val_data_config: A config that contains the information regarding construction
          of an ASR Training dataset.
  
  Supported Datasets:
      -   :class:`~nemo.collections.multimodal.speech_cv.data.video_to_text.VideoToCharDataset`
      -   :class:`~nemo.collections.asr.data.video_to_text.VideoToBPEDataset`
      -   :class:`~nemo.collections.asr.data.video_to_text.TarredVideoToBPEDataset`
docstr_tok: ["Sets","up","the","validation","data","loader","via","a","Dict-like","object",".","Args",":","val_data_config",":","A","config","that","contains","the","information","regarding","construction","of","an","ASR","Training","dataset",".","Supported","Datasets",":","-",":","class",":","`","~nemo.collections.multimodal.speech_cv.data.video_to_text.VideoToCharDataset","`","-",":","class",":","`","~nemo.collections.asr.data.video_to_text.VideoToBPEDataset","`","-",":","class",":","`","~nemo.collections.asr.data.video_to_text.TarredVideoToBPEDataset","`"]
code: def setup_validation_data(
      self, val_data_config: Optional[Union[DictConfig, Dict]]
  ):
      """
      Sets up the validation data loader via a Dict-like object.
  
      Args:
          val_data_config: A config that contains the information regarding construction
              of an ASR Training dataset.
  
      Supported Datasets:
          -   :class:`~nemo.collections.multimodal.speech_cv.data.video_to_text.VideoToCharDataset`
          -   :class:`~nemo.collections.asr.data.video_to_text.VideoToBPEDataset`
          -   :class:`~nemo.collections.asr.data.video_to_text.TarredVideoToBPEDataset`
      """
      if "shuffle" not in val_data_config:
          val_data_config["shuffle"] = False
  
      # preserve config
      self._update_dataset_config(
          dataset_name="validation", config=val_data_config
      )
  
      self._validation_dl = self._setup_dataloader_from_config(
          config=val_data_config
      )
  
imports: import copy
  import json
  import os
  import tempfile
  from math import ceil
  from typing import Dict, List, Optional, Tuple, Union
  import torch
  from omegaconf import DictConfig, OmegaConf, open_dict
  from pytorch_lightning import Trainer
  from tqdm.auto import tqdm
  from nemo.collections.asr.data import audio_to_text_dataset
  from nemo.collections.asr.losses.rnnt import RNNTLoss, resolve_rnnt_default_loss_name
  from nemo.collections.asr.metrics.wer import WER
  from nemo.collections.asr.models.asr_model import ASRModel
  from nemo.collections.asr.modules.rnnt import RNNTDecoderJoint
  from nemo.collections.asr.parts.mixins import ASRModuleMixin
  from nemo.collections.asr.parts.submodules.rnnt_decoding import RNNTDecoding, RNNTDecodingConfig
  from nemo.collections.asr.parts.utils.audio_utils import ChannelSelectorType
  from nemo.collections.multimodal.speech_cv.data import video_to_text_dataset
  from nemo.core.classes import Exportable
  from nemo.core.classes.common import PretrainedModelInfo, typecheck
  from nemo.core.classes.mixins import AccessMixin
  from nemo.core.neural_types import AcousticEncodedRepresentation, LengthsType, NeuralType, VideoSignal
  from nemo.utils import logging
label_desc: Use image node_id 9 for calling the VisualEncDecRNNTModel obj's underlying member method code with example usage: obj.setup_validation_data(val_data_config) without return types