code: def test_sparse_cumlarray_serialization():
      X = cupyx.scipy.sparse.random(10, 5, format="csr", density=0.9)
  
      X_m = SparseCumlArray(X)
  
      stype, sbytes = serialize(X_m, serializers=["cuda"])
  
      assert stype["serializer"] == "cuda"
  
      stype, sbytes = serialize(X_m, serializers=["dask"])
  
      assert stype["serializer"] == "dask"
  
file_path: cuml/python/cuml/tests/dask/test_dask_serialization.py
imports: from distributed.protocol.serialize import serialize
  from cuml.naive_bayes.naive_bayes import MultinomialNB
  from cuml.internals.array_sparse import SparseCumlArray
  from cuml.dask.linear_model import LinearRegression
  from cuml.internals.safe_imports import gpu_only_import
  from dask import array
  from sklearn.datasets import make_regression
  import numpy
  import pickle
label_desc: Use image node_id 2 for calling a global function with example usage: test_sparse_cumlarray_serialization() without return types