text: # ******************************************************************************
  # Copyright 2017-2020 Intel Corporation
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  # ******************************************************************************
  import numpy as np
  import pytest
  
  import ngraph as ng
  from tests.test_ngraph.util import run_op_node
  from tests import xfail_issue_34323
  
  
  @xfail_issue_34323
  @pytest.mark.parametrize(
      "shape_a, shape_b, transpose_a, transpose_b",
      [
          # matrix, vector
          ([2, 4], [4], False, False),
          ([4], [4, 2], False, False),
          # matrix, matrix
          ([2, 4], [4, 2], False, False),
          # tensor, vector
          ([2, 4, 5], [5], False, False),
          # # tensor, matrix
          ([2, 4, 5], [5, 4], False, False),
          # # tensor, tensor
          ([2, 2, 4], [2, 4, 2], False, False),
      ],
  )
  def test_matmul(shape_a, shape_b, transpose_a, transpose_b):
      np.random.seed(133391)
      left_input = -100.0 + np.random.rand(*shape_a).astype(np.float32) * 200.0
      right_input = -100.0 + np.random.rand(*shape_b).astype(np.float32) * 200.0
  
      result = run_op_node([left_input, right_input], ng.matmul, transpose_a, transpose_b)
  
      if transpose_a:
          left_input = np.transpose(left_input)
      if transpose_b:
          right_input = np.transpose(right_input)
  
      expected = np.matmul(left_input, right_input)
      assert np.allclose(result, expected)
  