text: //*****************************************************************************
  // Copyright 2017-2019 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.
  //*****************************************************************************
  
  #include "gtest/gtest.h"
  #include "ngraph/ngraph.hpp"
  #include "util/all_close.hpp"
  #include "util/all_close_f.hpp"
  #include "util/ndarray.hpp"
  #include "util/test_control.hpp"
  #include "util/test_tools.hpp"
  
  using namespace std;
  using namespace ngraph;
  
  static string s_manifest = "${MANIFEST}";
  
  NGRAPH_TEST(${BACKEND_NAME}, convert_int32_float32)
  {
      Shape shape{2, 2};
      auto A = make_shared<op::Parameter>(element::i32, shape);
      auto f = make_shared<Function>(make_shared<op::Convert>(A, element::f32), ParameterVector{A});
  
      auto backend = runtime::Backend::create("${BACKEND_NAME}");
  
      // Create some tensors for input/output
      auto a = backend->create_tensor(element::i32, shape);
      copy_data(a, vector<int32_t>{281, 2, 3, 4});
      auto result = backend->create_tensor(element::f32, shape);
  
      auto handle = backend->compile(f);
      handle->call_with_validate({result}, {a});
      EXPECT_TRUE(test::all_close_f((vector<float>{281, 2, 3, 4}), read_vector<float>(result)));
  }
  
  NGRAPH_TEST(${BACKEND_NAME}, convert_uint16_float32)
  {
      Shape shape{2, 2};
      auto A = make_shared<op::Parameter>(element::u16, shape);
      auto f = make_shared<Function>(make_shared<op::Convert>(A, element::f32), ParameterVector{A});
  
      auto backend = runtime::Backend::create("${BACKEND_NAME}");
  
      // Create some tensors for input/output
      auto a = backend->create_tensor(element::u16, shape);
      copy_data(a, vector<uint16_t>{1, 2, 3, 4});
      auto result = backend->create_tensor(element::f32, shape);
  
      auto handle = backend->compile(f);
      handle->call_with_validate({result}, {a});
      EXPECT_TRUE(test::all_close_f(
          (vector<float>{1, 2, 3, 4}), read_vector<float>(result), MIN_FLOAT_TOLERANCE_BITS));
  }
  
  NGRAPH_TEST(${BACKEND_NAME}, convert_int32_bool)
  {
      Shape shape{2, 3};
      auto A = make_shared<op::Parameter>(element::i32, shape);
      auto f =
          make_shared<Function>(make_shared<op::Convert>(A, element::boolean), ParameterVector{A});
  
      auto backend = runtime::Backend::create("${BACKEND_NAME}");
  
      int32_t lowest = std::numeric_limits<int32_t>::lowest();
      int32_t max = std::numeric_limits<int32_t>::max();
  
      // Create some tensors for input/output
      auto a = backend->create_tensor(element::i32, shape);
      copy_data(a, vector<int32_t>{0, 12, 23, 0, lowest, max});
      auto result = backend->create_tensor(element::boolean, shape);
  
      auto handle = backend->compile(f);
      handle->call_with_validate({result}, {a});
      EXPECT_EQ((vector<char>{0, 1, 1, 0, 1, 1}), read_vector<char>(result));
  }
  
  NGRAPH_TEST(${BACKEND_NAME}, convert_float32_bool)
  {
      Shape shape{3, 3};
      auto A = make_shared<op::Parameter>(element::f32, shape);
      auto f =
          make_shared<Function>(make_shared<op::Convert>(A, element::boolean), ParameterVector{A});
  
      auto backend = runtime::Backend::create("${BACKEND_NAME}");
  
      float lowest = std::numeric_limits<float>::lowest();
      float max = std::numeric_limits<float>::max();
      float min = std::numeric_limits<float>::min();
      float pos_inf = std::numeric_limits<float>::infinity();
      float neg_inf = -std::numeric_limits<float>::infinity();
  
      // Create some tensors for input/output
      auto a = backend->create_tensor(element::f32, shape);
      copy_data(a, vector<float>{0.f, 1.5745f, 0.12352f, 0.f, lowest, max, min, pos_inf, neg_inf});
      auto result = backend->create_tensor(element::boolean, shape);
  
      auto handle = backend->compile(f);
      handle->call_with_validate({result}, {a});
      EXPECT_EQ((vector<char>{0, 1, 1, 0, 1, 1, 1, 1, 1}), read_vector<char>(result));
  }
  
  NGRAPH_TEST(${BACKEND_NAME}, convert_float32_bf16)
  {
      Shape shape_a{1, 1, 3, 5};
  
      // input data
      vector<float> a_data = {
          0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f};
  
      auto A = make_shared<op::Parameter>(element::f32, shape_a);
      auto convert = make_shared<op::Convert>(A, element::bf16);
      auto f = make_shared<Function>(NodeVector{convert}, ParameterVector{A});
      auto backend = runtime::Backend::create("${BACKEND_NAME}");
      // Create some tensors for input/output
      auto a = backend->create_tensor(element::f32, shape_a);
      copy_data(a, a_data);
      auto result = backend->create_tensor(element::bf16, shape_a);
      auto handle = backend->compile(f);
      handle->call_with_validate({result}, {a});
      EXPECT_EQ((vector<bfloat16>{
                    0.5, 1.5, 0.5, 2.5, 1.5, 0.5, 3.5, 2.5, 0.5, 0.5, 2.5, 0.5, 0.5, 0.5, 1.5}),
                read_vector<bfloat16>(result));
  }
  
  NGRAPH_TEST(${BACKEND_NAME}, convert_bf16_float32)
  {
      Shape shape_a{1, 1, 3, 5};
  
      // input data
      vector<bfloat16> a_data = {
          0.5, 1.5, 0.5, 2.5, 1.5, 0.5, 3.5, 2.5, 0.5, 0.5, 2.5, 0.5, 0.5, 0.5, 1.5};
  
      auto A = make_shared<op::Parameter>(element::bf16, shape_a);
      auto convert = make_shared<op::Convert>(A, element::f32);
      auto f = make_shared<Function>(NodeVector{convert}, ParameterVector{A});
      auto backend = runtime::Backend::create("${BACKEND_NAME}");
      // Create some tensors for input/output
      auto a = backend->create_tensor(element::bf16, shape_a);
      copy_data(a, a_data);
      auto result = backend->create_tensor(element::f32, shape_a);
      auto handle = backend->compile(f);
      handle->call_with_validate({result}, {a});
      EXPECT_EQ((vector<float>{0.5f,
                               1.5f,
                               0.5f,
                               2.5f,
                               1.5f,
                               0.5f,
                               3.5f,
                               2.5f,
                               0.5f,
                               0.5f,
                               2.5f,
                               0.5f,
                               0.5f,
                               0.5f,
                               1.5f}),
                read_vector<float>(result));
  }
  