code: def build_dataloader(
      batch_size: int,
      coordinator: DistCoordinator,
      plugin: DPPluginBase,
  ):
      # transform
      transform_train = transforms.Compose(
          [
              transforms.RandomCrop(32, padding=4),
              transforms.RandomHorizontalFlip(),
              transforms.ToTensor(),
              transforms.Normalize(
                  (0.49139968, 0.48215827, 0.44653124),
                  (0.24703233, 0.24348505, 0.26158768),
              ),
          ]
      )
      transform_test = transforms.Compose(
          [
              transforms.Resize(32),
              transforms.ToTensor(),
              transforms.Normalize(
                  (0.49139968, 0.48215827, 0.44653124),
                  (0.24703233, 0.24348505, 0.26158768),
              ),
          ]
      )
  
      # CIFAR-10 dataset
      data_path = os.environ.get("DATA", "./data")
      with coordinator.priority_execution():
          train_dataset = torchvision.datasets.CIFAR10(
              root=data_path,
              train=True,
              transform=transform_train,
              download=True,
          )
          test_dataset = torchvision.datasets.CIFAR10(
              root=data_path,
              train=False,
              transform=transform_test,
              download=True,
          )
  
      # Data loader
      train_dataloader = plugin.prepare_dataloader(
          train_dataset,
          batch_size=batch_size,
          shuffle=True,
          drop_last=True,
      )
      test_dataloader = plugin.prepare_dataloader(
          test_dataset,
          batch_size=batch_size,
          shuffle=False,
          drop_last=False,
      )
      return train_dataloader, test_dataloader
  
imports: import argparse
  import os
  from pathlib import Path
  import torch
  import torch.distributed
  import torch.nn
  import torchvision
  import torchvision.transforms
  from timm.models.vision_transformer import _cfg, _create_vision_transformer
  from torch.optim import Optimizer
  from torch.utils.data import DataLoader
  from tqdm import tqdm
  import colossalai
  from colossalai.booster import Booster
  from colossalai.booster.plugin import GeminiPlugin, LowLevelZeroPlugin, TorchDDPPlugin
  from colossalai.booster.plugin.dp_plugin_base import DPPluginBase
  from colossalai.cluster import DistCoordinator
  from colossalai.nn.lr_scheduler import LinearWarmupLR
  from colossalai.nn.optimizer import HybridAdam
  from colossalai.utils import get_current_device
label_desc: Use image node_id 2 for calling a global function with example usage: build_dataloader(batch_size, coordinator, plugin) and returns: train_dataloader,  test_dataloader