code: def _f_order_standard_normal(client, rs, chunksizes, ncols, dtype):
      workers = list(client.has_what().keys())
  
      n_chunks = len(chunksizes)
      chunks_workers = (workers * n_chunks)[:n_chunks]
  
      chunk_seeds = rs.permutation(len(chunksizes))
      chunks = [
          client.submit(
              _dask_f_order_standard_normal,
              chunksize,
              ncols,
              dtype,
              chunk_seeds[idx],
              workers=[chunks_workers[idx]],
              pure=False,
          )
          for idx, chunksize in enumerate(chunksizes)
      ]
  
      chunks_dela = _create_delayed(chunks, dtype, chunksizes, ncols)
  
      return da.concatenate(chunks_dela, axis=0)
  
imports: from cuml.dask.common.utils import get_client
  from cuml.dask.common.input_utils import DistributedDataHandler
  from cuml.common import with_cupy_rmm
  from cuml.dask.datasets.utils import _create_delayed
  from cuml.dask.datasets.utils import _get_labels
  from cuml.dask.datasets.utils import _get_X
  from cuml.internals.safe_imports import gpu_only_import
  import dask.array
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 3 for calling a global function with example usage: _f_order_standard_normal(client, rs, chunksizes, ncols, dtype) and returns: da