code: def val_data_loader(config, batch_size):
      val_dataset = LinearDataset(size=config.get("val_size", 400))
      validation_loader = torch.utils.data.DataLoader(
          val_dataset, batch_size=batch_size
      )
      return validation_loader
  
imports: import os
  from unittest import TestCase
  import numpy
  import pytest
  import torch
  import torch.nn
  from pyspark.sql import SparkSession
  from pyspark.sql.types import FloatType, ArrayType, StructType, StructField
  from bigdl.orca import OrcaContext
  from bigdl.orca.data.pandas import read_csv
  from bigdl.orca.learn.metrics import Accuracy
  from bigdl.dllib.nncontext import init_nncontext
  from bigdl.orca.learn.pytorch import Estimator
  from bigdl.orca.learn.pytorch.callbacks.base import Callback
  import tempfile
  import shutil
  import logging
label_desc: Use image node_id 2 for calling a global function with example usage: val_data_loader(config, batch_size) and returns: validation_loader