code: def train_data_loader(config, batch_size):
      train_dataset = LinearDataset(size=config.get("data_size", 1000))
      train_loader = torch.utils.data.DataLoader(
          train_dataset, batch_size=batch_size
      )
      return train_loader
  
imports: import os
  from unittest import TestCase
  import numpy
  import pytest
  import torch
  import torch.nn
  from zoo.orca import OrcaContext
  from zoo.orca.data.pandas import read_csv
  from zoo.orca.learn.metrics import Accuracy
  from zoo import init_nncontext
  from zoo.orca.learn.pytorch import Estimator
  from zoo.orca.data import SparkXShards
  from zoo.orca.data.image.utils import chunks
label_desc: Use image node_id 1 for calling a global function with example usage: train_data_loader(config, batch_size) and returns: train_loader