code: def test_broadcast_to_execution(setup):
      raw = np.random.random((10, 5, 1))
      arr = tensor(raw, chunk_size=2)
      arr2 = broadcast_to(arr, (5, 10, 5, 6))
  
      res = arr2.execute().fetch()
      np.testing.assert_array_equal(
          res, np.broadcast_to(raw, (5, 10, 5, 6))
      )
  
      # test chunk with unknown shape
      arr1 = mt.random.rand(3, 4, chunk_size=2)
      arr2 = mt.random.permutation(arr1)
      arr3 = broadcast_to(arr2, (2, 3, 4))
  
      res = arr3.execute().fetch()
      assert res.shape == (2, 3, 4)
  
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 7 for calling a global function with example usage: test_broadcast_to_execution(setup) without return types