code: def normalize_clusters(a0, b0, n_clusters):
      a = to_nparray(a0)
      b = to_nparray(b0)
  
      c = deepcopy(b)
  
      for i in range(n_clusters):
          (idx,) = np.where(a == i)
          a_to_b = c[idx[0]]
          b[c == a_to_b] = i
  
      return a, b
  
imports: import pytest
  from cuml.internals.mem_type import MemoryType
  from cuml.internals.input_utils import input_to_cuml_array, is_array_like
  from cuml.internals.base import Base
  import cuml
  from sklearn.model_selection import train_test_split
  from sklearn.metrics import mean_squared_error, brier_score_loss
  from sklearn.datasets import make_classification, make_regression
  from sklearn import datasets
  from pylibraft.common.cuda import Stream
  from sklearn.datasets import make_regression
  from numba.cuda.cudadrv.devicearray import DeviceNDArray
  from numbers import Number
  from cuml.internals.safe_imports import gpu_only_import_from
  from itertools import dropwhile
  from copy import deepcopy
  from cuml.internals.safe_imports import cpu_only_import
  import inspect
  from textwrap import dedent, indent
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 4 for calling a global function with example usage: normalize_clusters(a0, b0, n_clusters) and returns: a,  b