code: def xgb_train_test_data():
      dataset = loadtxt(
          os.path.join(
              XGB_RESOURCE_DIR, "classification_training_data.data.csv"
          ),
          delimiter=",",
      )
  
      X = dataset[:, 0:8]
      Y = dataset[:, 8]
  
      # split data into train and test sets
      seed = 7
      test_size = 0.33
  
      x_train, x_test, y_train, y_test = train_test_split(
          X, Y, test_size=test_size, random_state=seed
      )
  
      return XgbTrainTestSplit(x_train, y_train, x_test, y_test)
  
imports: from __future__ import absolute_import
  import os
  import shutil
  import pytest
  import pathlib
  import collections
  import platform
  from numpy import loadtxt
  from xgboost import XGBClassifier
  from sklearn.model_selection import train_test_split
  from sagemaker import serve, image_uris
  from tests.integ import DATA_DIR
  from tests.integ.timeout import timeout
label_desc: Use image node_id 3 for calling a global function with example usage: xgb_train_test_data() and returns: XgbTrainTestSplit