code: def test_predict(self):
      iterations = 10
      np.random.seed(1)
      test_num_rows = [10, 1000, 5000]
      test_num_cols = [10, 50, 500]
      for num_rows in test_num_rows:
          for num_cols in test_num_cols:
              dtrain = xgb.DMatrix(
                  np.random.randn(num_rows, num_cols),
                  label=[0, 1] * int(num_rows / 2),
              )
              dval = xgb.DMatrix(
                  np.random.randn(num_rows, num_cols),
                  label=[0, 1] * int(num_rows / 2),
              )
              dtest = xgb.DMatrix(
                  np.random.randn(num_rows, num_cols),
                  label=[0, 1] * int(num_rows / 2),
              )
              watchlist = [(dtrain, "train"), (dval, "validation")]
              res = {}
              param = {
                  "objective": "binary:logistic",
                  "eval_metric": "logloss",
                  "tree_method": "hist",
                  "device": "cpu",
                  "max_depth": 1,
                  "verbosity": 0,
              }
              bst = xgb.train(
                  param,
                  dtrain,
                  iterations,
                  evals=watchlist,
                  evals_result=res,
              )
              assert tm.non_increasing(res["train"]["logloss"])
              cpu_pred_train = bst.predict(dtrain, output_margin=True)
              cpu_pred_test = bst.predict(dtest, output_margin=True)
              cpu_pred_val = bst.predict(dval, output_margin=True)
  
              bst.set_param({"device": "sycl"})
              sycl_pred_train = bst.predict(dtrain, output_margin=True)
              sycl_pred_test = bst.predict(dtest, output_margin=True)
              sycl_pred_val = bst.predict(dval, output_margin=True)
  
              np.testing.assert_allclose(
                  cpu_pred_train, sycl_pred_train, rtol=1e-6
              )
              np.testing.assert_allclose(
                  cpu_pred_val, sycl_pred_val, rtol=1e-6
              )
              np.testing.assert_allclose(
                  cpu_pred_test, sycl_pred_test, rtol=1e-6
              )
  
file_path: xgboost/tests/python-sycl/test_sycl_prediction.py
imports: import sys
  import unittest
  import pytest
  import numpy
  import xgboost
  from hypothesis import given, strategies, assume, settings, note
  from xgboost import testing
label_desc: Use image node_id 1 for calling the TestSYCLPredict obj's underlying member method code with example usage: obj.test_predict() without return types