code: def get_holdout(train_dataset, target_column):
      return train_test_split(
          train_dataset,
          test_size=0.33,
          random_state=1,
          stratify=train_dataset.loc[:, target_column],
      )
  
imports: from hyperparameter_hunter import Environment, CVExperiment
  from hyperparameter_hunter.callbacks.bases import BaseCallback
  from hyperparameter_hunter.settings import G
  from hyperparameter_hunter.utils.learning_utils import get_breast_cancer_data
  from copy import deepcopy
  import pandas
  import pytest
  from sklearn.datasets import load_iris
  from sklearn.metrics import f1_score
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import LabelEncoder
  from xgboost import XGBClassifier
label_desc: Use image node_id 2 for calling a global function with example usage: get_holdout(train_dataset, target_column) and returns: train_test_split