code: def get_num_trees(booster: xgb.Booster) -> int:
      data = [
          json.loads(d) for d in booster.get_dump(dump_format="json")
      ]
      return len(data)
  
file_path: ray/python/ray/train/tests/test_xgboost_predictor.py
imports: import json
  import numpy
  import pandas
  import pytest
  import xgboost
  from ray.air.util.data_batch_conversion import _convert_pandas_to_batch_type
  from ray.train.predictor import TYPE_TO_ENUM
  from ray.train.tests.dummy_preprocessor import DummyPreprocessor
  from ray.train.xgboost import XGBoostCheckpoint, XGBoostPredictor
label_desc: Use image node_id 1 for calling a global function with example usage: get_num_trees(booster) and returns: len