code: def setup(self, stage: Optional[str] = None) -> None:
      self.train_dataset = pytorchvideo.data.Kinetics(
          data_path=os.path.join(self.data_dir, "train"),
          clip_sampler=pytorchvideo.data.make_clip_sampler(
              self.train_clip_sampler, self.clip_duration
          ),
          decode_audio=False,
          transform=self._video_transform(mode="train"),
      )
      self.val_dataset = pytorchvideo.data.Kinetics(
          data_path=os.path.join(self.data_dir, "val"),
          clip_sampler=pytorchvideo.data.make_clip_sampler(
              "uniform", self.clip_duration
          ),
          decode_audio=False,
          transform=self._video_transform(mode="val"),
      )
  
imports: import os
  from typing import List, Optional, Union
  import pytorchvideo.data
  import torch
  import torch.nn
  import torch.utils.data
  import torchvision
  from datamodules.video_data_api import KineticsDataset
  from pytorch_lightning import LightningDataModule
  from pytorchvideo.transforms import ApplyTransformToKey, Normalize, RemoveKey, UniformTemporalSubsample
  from torchvision.transforms import CenterCrop, Compose, Lambda, RandomChoice, RandomCrop, RandomHorizontalFlip, RandomResizedCrop
label_desc: Use image node_id 4 for calling the KineticsDataModule obj's underlying member method code with example usage: obj.setup(stage) without return types