code: def make_train_loader(
      manifest_file,
      manifest_root,
      backend_obj,
      subset_pct=100,
      random_seed=0,
  ):
      aeon_config = common_config(
          manifest_file, manifest_root, backend_obj.bsz, subset_pct
      )
  
      aeon_config["iteration_mode"] = "ONCE"
      aeon_config["shuffle_manifest"] = True
      aeon_config["shuffle_enable"] = True
      aeon_config["random_seed"] = random_seed
      aeon_config["augmentation"][0]["center"] = False
      aeon_config["augmentation"][0]["flip_enable"] = True
  
      return wrap_dataloader(AeonDataLoader(aeon_config))
  
file_path: neon/examples/cifar10_msra/data.py
imports: import numpy
  import os
  from tqdm import tqdm
  from neon.data import CIFAR10
  from neon.data.aeon_shim import AeonDataLoader
  from neon.data.dataloader_transformers import OneHot, TypeCast, BGRMeanSubtract
  from neon.util.persist import get_data_cache_or_nothing
  from PIL import Image
label_desc: Use image node_id 4 for calling a global function with example usage: make_train_loader(manifest_file, manifest_root, backend_obj, subset_pct, random_seed) and returns: wrap_dataloader