class_docstr: PyTorch Lightning data module version of ``Vimeo90kSeptuplet``.
  
  Args:
      data_dir: root directory of Vimeo dataset.
      train_batch_size: the batch size to use during training.
      val_batch_size: the batch size to use during validation.
      patch_size: the size of the crop to take from the original images.
      num_workers: the number of parallel workers to create to load data
          items (see PyTorch's Dataloader documentation for more details).
      pin_memory: whether prepared items should be loaded into pinned memory
          or not. This improves performance on GPUs.
class_docstr_tok: ["PyTorch","Lightning","data","module","version","of","``","Vimeo90kSeptuplet","``",".","Args",":","data_dir",":","root","directory","of","Vimeo","dataset",".","train_batch_size",":","the","batch","size","to","use","during","training",".","val_batch_size",":","the","batch","size","to","use","during","validation",".","patch_size",":","the","size","of","the","crop","to","take","from","the","original","images",".","num_workers",":","the","number","of","parallel","workers","to","create","to","load","data","items","(","see","PyTorch","'s","Dataloader","documentation","for","more","details",")",".","pin_memory",":","whether","prepared","items","should","be","loaded","into","pinned","memory","or","not",".","This","improves","performance","on","GPUs","."]
code: def val_dataloader(self) -> Union[DataLoader, List[DataLoader]]:
      return DataLoader(
          self.val_dataset,
          batch_size=self.val_batch_size,
          num_workers=self.num_workers,
          shuffle=False,
          pin_memory=self.pin_memory,
          collate_fn=self._custom_collate,
      )
  
file_path: NeuralCompression/projects/torch_vct/datamodules/vimeo.py
imports: from typing import List, Optional, Sequence, Union
  import torchvision
  from datamodules.video_data_api import VimeoDataset
  from pytorch_lightning import LightningDataModule
  from torch.utils.data import DataLoader, default_collate
  from torchvision.transforms import CenterCrop, Compose, RandomChoice, RandomCrop, RandomHorizontalFlip, RandomResizedCrop
  from neuralcompression.data import Vimeo90kSeptuplet
label_desc: Use image node_id 6 for calling the VimeoDataModule obj's underlying member method code with example usage: obj.val_dataloader() and returns: DataLoader