code: def test_shap_categorical(self):
      X, y = tm.make_categorical(100, 20, 7, False)
      Xy = xgb.DMatrix(X, y, enable_categorical=True)
      booster = xgb.train(
          {"tree_method": "hist", "device": "gpu:0"},
          Xy,
          num_boost_round=10,
      )
  
      booster.set_param({"device": "cuda:0"})
      shap = booster.predict(Xy, pred_contribs=True)
      margin = booster.predict(Xy, output_margin=True)
      np.testing.assert_allclose(
          np.sum(shap, axis=len(shap.shape) - 1), margin, rtol=1e-3
      )
  
      booster.set_param({"device": "cpu"})
      shap = booster.predict(Xy, pred_contribs=True)
      margin = booster.predict(Xy, output_margin=True)
      np.testing.assert_allclose(
          np.sum(shap, axis=len(shap.shape) - 1), margin, rtol=1e-3
      )
  
imports: import sys
  from copy import copy
  import numpy
  import pytest
  from hypothesis import assume, given, settings, strategies
  import xgboost
  from xgboost import testing
  from xgboost.compat import PANDAS_INSTALLED
  from test_predict import run_predict_leaf
  from test_predict import run_threaded_predict
label_desc: Use image node_id 12 for calling the TestGPUPredict obj's underlying member method code with example usage: obj.test_shap_categorical() without return types