code: def test_tensordot_execution(setup):
      rs = np.random.RandomState(0)
      # size_executor = ExecutorForTest(sync_provider_type=ExecutorForTest.SyncProviderType.MOCK)
      #
      # a_data = np.arange(60).reshape(3, 4, 5)
      # a = tensor(a_data, chunk_size=2)
      # b_data = np.arange(24).reshape(4, 3, 2)
      # b = tensor(b_data, chunk_size=2)
      #
      # axes = ([1, 0], [0, 1])
      # c = tensordot(a, b, axes=axes)
      # size_res = size_executor.execute_tensor(c, mock=True)
      # assert sum(s[0] for s in size_res) == c.nbytes
      # assert sum(s[1] for s in size_res) == c.nbytes
  
      a = ones((100, 200), chunk_size=50)
      b = ones((200, 10), chunk_size=50)
      c = dot(a, b)
      res = c.execute().fetch()
      expected = np.dot(np.ones((100, 200)), np.ones((200, 10)))
      np.testing.assert_array_equal(res, expected)
  
      a = ones((10, 8), chunk_size=4)
      b = ones((8, 10), chunk_size=4)
      c = a.dot(b)
      res = c.execute().fetch()
      np.testing.assert_array_equal(res, np.tile([8], [10, 10]))
  
      a = ones((500, 500), chunk_size=500)
      b = ones((500, 100), chunk_size=500)
      c = a.dot(b)
      res = c.execute().fetch()
      np.testing.assert_array_equal(res, np.tile([500], [500, 100]))
  
      raw_a = rs.random((100, 200, 50))
      raw_b = rs.random((200, 10, 100))
      a = tensor(raw_a, chunk_size=50)
      b = tensor(raw_b, chunk_size=33)
      c = tensordot(a, b, axes=((0, 1), (2, 0)))
      res = c.execute().fetch()
      expected = np.tensordot(
          raw_a, raw_b, axes=(c.op.a_axes, c.op.b_axes)
      )
      np.testing.assert_array_almost_equal(res, expected)
  
      a = ones((100, 200), chunk_size=50)
      b = ones((10, 200), chunk_size=50)
      c = inner(a, b)
      res = c.execute().fetch()
      expected = np.inner(np.ones((100, 200)), np.ones((10, 200)))
      np.testing.assert_array_equal(res, expected)
  
      a = ones((100, 100), chunk_size=30)
      b = ones((100, 100), chunk_size=30)
      c = a.dot(b)
      res = c.execute().fetch()
      np.testing.assert_array_equal(res, np.ones((100, 100)) * 100)
  
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 11 for calling a global function with example usage: test_tensordot_execution(setup) without return types