code: def test_vdot_execution(setup):
      a_data = np.array([1 + 2j, 3 + 4j])
      b_data = np.array([5 + 6j, 7 + 8j])
      a = tensor(a_data, chunk_size=1)
      b = tensor(b_data, chunk_size=1)
  
      t = vdot(a, b)
  
      res = t.execute().fetch()
      expected = np.vdot(a_data, b_data)
      np.testing.assert_equal(res, expected)
  
      a_data = np.array([[1, 4], [5, 6]])
      b_data = np.array([[4, 1], [2, 2]])
      a = tensor(a_data, chunk_size=1)
      b = tensor(b_data, chunk_size=1)
  
      t = vdot(a, b)
  
      res = t.execute().fetch()
      expected = np.vdot(a_data, b_data)
      np.testing.assert_equal(res, expected)
  
imports: import numpy
  import scipy.sparse
  from ....learn.datasets.samples_generator import make_low_rank_matrix
  from ....lib.sparse import issparse, SparseNDArray
  from ....utils import ignore_warning
  from ...datasource import tensor, diag, ones, arange
  from ...random import uniform
  from ..None import qr, svd, cholesky, norm, lu, solve_triangular, solve, inv, tensordot, dot, inner, vdot, matmul, randomized_svd
label_desc: Use image node_id 13 for calling a global function with example usage: test_vdot_execution(setup) without return types