code: def data_sample():
      root = get_dataset_path(dataset="bottle")
      datamodule = Folder(
          root=root,
          normal_dir="good",
          abnormal_dir="broken_large",
          mask_dir="ground_truth/broken_large",
          normal_split_ratio=0.2,
          image_size=(256, 256),
          train_batch_size=1,
          eval_batch_size=1,
          num_workers=0,
          task="classification",
          val_split_mode="from_test",
      )
      datamodule.setup()
      _, data = next(enumerate(datamodule.train_dataloader()))
      return data
  
imports: import os
  import numpy
  import pytest
  from anomalib.config import update_input_size_config
  from anomalib.data import Avenue, BTech, Folder, MVTec, ShanghaiTech, UCSDped, Visa, get_datamodule
  from anomalib.data.utils import DirType
  from anomalib.pre_processing.transforms import Denormalize, ToNumpy
  from tests.helpers.config import get_test_configurable_parameters
  from tests.helpers.dataset import TestDataset, get_dataset_path
label_desc: Use image node_id 9 for calling a global function with example usage: data_sample() and returns: data