code: def test_make_blobs(
      nrows, ncols, centers, cluster_std, dtype, nparts, order, client
  ):
      c = client
  
      nrows = int(nrows)
      X, y = make_blobs(
          nrows,
          ncols,
          centers=centers,
          cluster_std=cluster_std,
          dtype=dtype,
          n_parts=nparts,
          order=order,
          client=client,
      )
  
      assert len(X.chunks[0]) == nparts
      assert len(y.chunks[0]) == nparts
  
      assert X.shape == (nrows, ncols)
      assert y.shape == (nrows,)
  
      y_local = y.compute()
      assert len(cp.unique(y_local)) == centers
  
      X_ddh = DistributedDataHandler.create(data=X, client=c)
      X_first = X_ddh.gpu_futures[0][1].result()
  
      if order == "F":
          assert X_first.flags["F_CONTIGUOUS"]
      elif order == "C":
          assert X_first.flags["C_CONTIGUOUS"]
  
file_path: cuml/python/cuml/tests/dask/test_dask_datasets.py
imports: from cuml.dask.common.part_utils import _extract_partitions
  from cuml.testing.utils import unit_param, quality_param, stress_param
  from cuml.dask.common.input_utils import DistributedDataHandler
  from cuml.dask.datasets.blobs import make_blobs
  from cuml.internals.safe_imports import gpu_only_import
  import pytest
  import dask.array
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 1 for calling a global function with example usage: test_make_blobs(nrows, ncols, centers, cluster_std, dtype, nparts, order, client) without return types