code: def _create_covariance(dims, seed, dtype="float32"):
      local_rs = cp.random.RandomState(seed=seed)
      return 2 * local_rs.rand(*dims, dtype=dtype) - 1
  
file_path: cuml/python/cuml/dask/datasets/classification.py
imports: from cuml.internals.safe_imports import cpu_only_import
  from cuml.datasets.classification import _generate_hypercube
  from cuml.datasets.classification import make_classification
  from cuml.datasets.utils import _create_rs_generator
  from cuml.dask.datasets.utils import _get_X
  from cuml.dask.datasets.utils import _get_labels
  from cuml.dask.datasets.utils import _create_delayed
  from cuml.dask.common.utils import get_client
  from cuml.common import with_cupy_rmm
  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: _create_covariance(dims, seed, dtype) and returns: unknown