code: def test_repeat_execution(setup):
      a = repeat(3, 4)
  
      res = a.execute().fetch()
      expected = np.repeat(3, 4)
      np.testing.assert_equal(res, expected)
  
      x_data = np.random.randn(20, 30)
      x = tensor(x_data, chunk_size=(12, 16))
  
      t = repeat(x, 2)
  
      res = t.execute().fetch()
      expected = np.repeat(x_data, 2)
      np.testing.assert_equal(res, expected)
  
      t = repeat(x, 3, axis=1)
  
      res = t.execute().fetch()
      expected = np.repeat(x_data, 3, axis=1)
      np.testing.assert_equal(res, expected)
  
      t = repeat(x, np.arange(20), axis=0)
  
      res = t.execute().fetch()
      expected = np.repeat(x_data, np.arange(20), axis=0)
      np.testing.assert_equal(res, expected)
  
      t = repeat(x, arange(20, chunk_size=10), axis=0)
  
      res = t.execute().fetch()
      expected = np.repeat(x_data, np.arange(20), axis=0)
      np.testing.assert_equal(res, expected)
  
      x_data = sps.random(20, 30, density=0.1)
      x = tensor(x_data, chunk_size=(12, 16))
  
      t = repeat(x, 2, axis=1)
  
      res = t.execute().fetch()
      expected = np.repeat(x_data.toarray(), 2, axis=1)
      np.testing.assert_equal(res.toarray(), expected)
  
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 24 for calling a global function with example usage: test_repeat_execution(setup) without return types