code: def test_copyto_execution(setup):
      a = ones((2, 3), chunk_size=1)
      b = tensor([3, -1, 3], chunk_size=2)
  
      copyto(a, b, where=b > 1)
  
      res = a.execute().fetch()
      expected = np.array([[3, 1, 3], [3, 1, 3]])
  
      np.testing.assert_equal(res, expected)
  
      a = ones((2, 3), chunk_size=1)
      b = tensor(np.asfortranarray(np.random.rand(2, 3)), chunk_size=2)
  
      copyto(b, a)
  
      res = b.execute().fetch()
      expected = np.asfortranarray(np.ones((2, 3)))
  
      np.testing.assert_array_equal(res, expected)
      assert res.flags["F_CONTIGUOUS"] is True
      assert res.flags["C_CONTIGUOUS"] is False
  
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 2 for calling a global function with example usage: test_copyto_execution(setup) without return types