code: def training_loop(self) -> None:
      pgf = train.get_context().get_trial_resources()
      assert pgf.strategy == "SPREAD"
      return super().training_loop()
  
imports: import json
  import pandas
  import pytest
  import xgboost
  from sklearn.datasets import load_breast_cancer
  from sklearn.model_selection import train_test_split
  import ray
  from ray import train, tune
  from ray.train import ScalingConfig
  from ray.train.constants import TRAIN_DATASET_KEY
  from ray.train.xgboost import XGBoostTrainer
label_desc: Use image node_id 1 for calling the ScalingConfigAssertingXGBoostTrainer obj's underlying member method code with example usage: obj.training_loop() and returns: super