code: def test_broadcast_arrays_executions(setup):
      x_data = [[1, 2, 3]]
      x = tensor(x_data, chunk_size=1)
      y_data = [[1], [2], [3]]
      y = tensor(y_data, chunk_size=2)
  
      a = broadcast_arrays(x, y)
  
      res = [arr.execute().fetch() for arr in a]
      expected = np.broadcast_arrays(x_data, y_data)
  
      for r, e in zip(res, expected):
          np.testing.assert_equal(r, e)
  
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 8 for calling a global function with example usage: test_broadcast_arrays_executions(setup) without return types