code: def test_extract_partitions_worker_list(
      nrows, ncols, n_parts, input_type, colocated, client
  ):
      adj_input_type = (
          "dataframe" if input_type == "series" else input_type
      )
  
      X_arr, y_arr = make_blobs(
          n_samples=int(nrows), n_features=ncols, n_parts=n_parts
      )
  
      if adj_input_type == "dataframe" or input_type == "dataframe":
          X = to_dask_cudf(X_arr)
          y = to_dask_cudf(y_arr)
      elif input_type == "array":
          X, y = X_arr, y_arr
  
      if input_type == "series":
          X = X[X.columns[0]]
  
      if colocated:
          ddh = DistributedDataHandler.create((X, y), client)
      else:
          ddh = DistributedDataHandler.create(X, client)
  
      parts = list(map(lambda x: x[1], ddh.gpu_futures))
      assert len(parts) == n_parts
  
file_path: cuml/python/cuml/tests/dask/test_dask_input_utils.py
imports: from cuml.dask.common.dask_arr_utils import to_dask_cudf
  import pytest
  from cuml.dask.datasets.blobs import make_blobs
  from cuml.dask.common.input_utils import DistributedDataHandler
  import dask.array
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 1 for calling a global function with example usage: test_extract_partitions_worker_list(nrows, ncols, n_parts, input_type, colocated, client) without return types