code: def _topk_slow(a, k, axis, largest, order):
      if axis is None:
          a = a.flatten()
          axis = 0
      a = np.sort(a, axis=axis, order=order)
      if largest:
          a = a[(slice(None),) * axis + (slice(None, None, -1),)]
      return a[(slice(None),) * axis + (slice(k),)]
  
imports: import numpy
  import scipy.sparse
  import pandas
  import pytest
  from ....None import dataframe
  from ....None import tensor
  from ....None import execute, fetch
  from ....tests.core import require_cupy
  from ...datasource import tensor, ones, zeros, arange
  from ..None import copyto, transpose, moveaxis, broadcast_to, broadcast_arrays, where, expand_dims, rollaxis, atleast_1d, atleast_2d, atleast_3d, argwhere, array_split, split, hsplit, vsplit, dsplit, roll, squeeze, diff, ediff1d, flip, flipud, fliplr, repeat, tile, isin, searchsorted, unique, sort, argsort, partition, argpartition, topk, argtopk, trapz, shape, to_gpu, to_cpu, swapaxes
label_desc: Use image node_id 38 for calling a global function with example usage: _topk_slow(a, k, axis, largest, order) and returns: a