code: def test_meta_schedule_xgb_model_reupdate():
      extractor = RandomFeatureExtractor()
      model = XGBModel(extractor=extractor, num_warmup_samples=2)
      update_sample_count = 60
      predict_sample_count = 100
      model.update(
          TuneContext(),
          [_dummy_candidate() for i in range(update_sample_count)],
          [_dummy_result() for i in range(update_sample_count)],
      )
      model.update(
          TuneContext(),
          [_dummy_candidate() for i in range(update_sample_count)],
          [_dummy_result() for i in range(update_sample_count)],
      )
      model.update(
          TuneContext(),
          [_dummy_candidate() for i in range(update_sample_count)],
          [_dummy_result() for i in range(update_sample_count)],
      )
      model.predict(
          TuneContext(),
          [_dummy_candidate() for i in range(predict_sample_count)],
      )
  
imports: import os
  import re
  import shutil
  import tempfile
  import unittest
  from functools import partial
  from typing import List
  import numpy
  import tvm
  import tvm.testing
  from tvm.meta_schedule.cost_model import PyCostModel, RandomModel, XGBModel
  from tvm.meta_schedule.cost_model.xgb_model import PackSum, _get_custom_call_back
  from tvm.meta_schedule.feature_extractor import RandomFeatureExtractor
  from tvm.meta_schedule.runner import RunnerResult
  from tvm.meta_schedule.search_strategy import MeasureCandidate
  from tvm.meta_schedule.tune_context import TuneContext
  from tvm.meta_schedule.utils import derived_object
  from tvm.script import tir
  from tvm.tir.schedule.schedule import Schedule
label_desc: Use image node_id 11 for calling a global function with example usage: test_meta_schedule_xgb_model_reupdate() without return types