code: def make_avenue_data_module(
      task="classification", batch_size=1, val_split_mode="from_test"
  ):
      root = get_dataset_path(dataset="avenue")
      data_module = Avenue(
          root=root,
          gt_dir=os.path.join(root, "ground_truth_demo"),
          image_size=(256, 256),
          train_batch_size=batch_size,
          eval_batch_size=batch_size,
          num_workers=0,
          task=task,
          val_split_mode=val_split_mode,
      )
      data_module.setup()
      return data_module
  
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 1 for calling a global function with example usage: make_avenue_data_module(task, batch_size, val_split_mode) and returns: data_module