code: def test_sparkxgb_regressor_with_gpu(spark_diabetes_dataset):
      from pyspark.ml.evaluation import RegressionEvaluator
  
      regressor = SparkXGBRegressor(
          device="cuda", num_workers=num_workers
      )
      train_df, test_df = spark_diabetes_dataset
      model = regressor.fit(train_df)
      pred_result_df = model.transform(test_df)
      evaluator = RegressionEvaluator(metricName="rmse")
      rmse = evaluator.evaluate(pred_result_df)
      assert rmse <= 65.0
  
imports: import json
  import logging
  import subprocess
  import numpy
  import pytest
  import sklearn
  from xgboost import testing
  from pyspark.ml.linalg import Vectors
  from pyspark.ml.tuning import CrossValidator, ParamGridBuilder
  from pyspark.sql import SparkSession
  from xgboost.spark import SparkXGBClassifier, SparkXGBRegressor, SparkXGBRegressorModel
label_desc: Use image node_id 10 for calling a global function with example usage: test_sparkxgb_regressor_with_gpu(spark_diabetes_dataset) without return types