code: def test_init_score_for_multiclass_classification(init_score_type):
      init_score = [[i * 10 + j for j in range(3)] for i in range(10)]
      if init_score_type == "array":
          init_score = np.array(init_score)
      elif init_score_type == "dataframe":
          if not PANDAS_INSTALLED:
              pytest.skip("Pandas is not installed.")
          init_score = pd_DataFrame(init_score)
      data = np.random.rand(10, 2)
      ds = lgb.Dataset(data, init_score=init_score).construct()
      np.testing.assert_equal(ds.get_field("init_score"), init_score)
      np.testing.assert_equal(ds.init_score, init_score)
  
imports: import filecmp
  import numbers
  import re
  from copy import deepcopy
  from os import getenv
  from pathlib import Path
  import numpy
  import pytest
  from scipy import sparse
  from sklearn.datasets import dump_svmlight_file, load_svmlight_file
  from sklearn.model_selection import train_test_split
  import lightgbm
  from lightgbm.compat import PANDAS_INSTALLED, pd_DataFrame, pd_Series
  from .utils import dummy_obj, load_breast_cancer, mse_obj, np_assert_array_equal
label_desc: Use image node_id 23 for calling a global function with example usage: test_init_score_for_multiclass_classification(init_score_type) without return types