code: def test_slice_multi(self) -> None:
      from sklearn.datasets import make_classification
  
      num_classes = 3
      X, y = make_classification(
          n_samples=1000, n_informative=5, n_classes=num_classes
      )
      Xy = xgb.DMatrix(data=X, label=y)
      num_parallel_tree = 4
      num_boost_round = 16
  
      booster = xgb.train(
          {
              "num_parallel_tree": num_parallel_tree,
              "num_class": num_classes,
              "booster": "gbtree",
              "objective": "multi:softprob",
              "multi_strategy": "multi_output_tree",
              "tree_method": "hist",
              "base_score": 0,
          },
          num_boost_round=num_boost_round,
          dtrain=Xy,
          callbacks=[ResetStrategy()],
      )
      sliced = [t for t in booster]
      assert len(sliced) == 16
  
      predt0 = booster.predict(Xy, output_margin=True)
      predt1 = np.zeros(predt0.shape)
      for t in booster:
          predt1 += t.predict(Xy, output_margin=True)
  
      np.testing.assert_allclose(predt0, predt1, atol=1e-5)
  
imports: import json
  import os
  import tempfile
  import numpy
  import pytest
  import xgboost
  from xgboost import testing
  from xgboost.testing.updater import ResetStrategy
label_desc: Use image node_id 16 for calling the TestModels obj's underlying member method code with example usage: obj.test_slice_multi() without return types