code: def create_cp_sparse_dask_array(np_ar, n_parts):
      """
      Creates a sparse gpu dask array from the given numpy array
      """
      ar = generate_dask_array(np_ar, n_parts)
      meta = dask.array.from_array(
          cp_csr_matrix(cp.zeros(1, dtype=cp.float32))
      )
      ar = ar.map_blocks(
          create_cp_sparse_ar_from_dense_np_ar, meta=meta
      )
      return ar
  
file_path: cuml/python/cuml/tests/dask/test_dask_tfidf.py
imports: from sklearn.feature_extraction.text import TfidfTransformer
  from cuml.dask.feature_extraction.text import TfidfTransformer
  import dask
  import dask.array
  from cuml.internals.safe_imports import gpu_only_import_from
  from cuml.internals.safe_imports import cpu_only_import_from
  from cuml.internals.safe_imports import gpu_only_import
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 3 for calling a global function with example usage: create_cp_sparse_dask_array(np_ar, n_parts) and returns: ar