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.
  //*****************************************************************************
  
  // clang-format off
  #ifdef ${BACKEND_NAME}_FLOAT_TOLERANCE_BITS
  #define DEFAULT_FLOAT_TOLERANCE_BITS ${BACKEND_NAME}_FLOAT_TOLERANCE_BITS
  #endif
  
  #ifdef ${BACKEND_NAME}_DOUBLE_TOLERANCE_BITS
  #define DEFAULT_DOUBLE_TOLERANCE_BITS ${BACKEND_NAME}_DOUBLE_TOLERANCE_BITS
  #endif
  // clang-format on
  
  #include "gtest/gtest.h"
  #include "runtime/backend.hpp"
  #include "ngraph/runtime/tensor.hpp"
  #include "ngraph/ngraph.hpp"
  #include "util/all_close.hpp"
  #include "util/all_close_f.hpp"
  #include "util/known_element_types.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}, sigmoid_n1c1h2w2)
  {
      auto input = make_shared<op::Parameter>(element::Type_t::f32, Shape{1, 1, 2, 2});
      auto sigmoid_node = make_shared<op::Sigmoid>(input);
      auto func = make_shared<Function>(sigmoid_node, ParameterVector{input});
  
      auto backend = runtime::Backend::create("${BACKEND_NAME}");
  
      shared_ptr<runtime::Tensor> a =
          backend->create_tensor(element::Type_t::f32, input->get_shape());
      shared_ptr<runtime::Tensor> result =
          backend->create_tensor(element::Type_t::f32, input->get_shape());
  
      float x1 = 1.0f;
      float x2 = 4.0f;
      float sigma1 = 1.0f / (1.0f + std::exp(-x1));
      float sigma2 = 1.0f / (1.0f + std::exp(-x2));
  
      vector<float> dataA{x1, x2, x1, x2};
      copy_data(a, dataA);
  
      auto handle = backend->compile(func);
      handle->call_with_validate({result}, {a});
      vector<float> expected{sigma1, sigma2, sigma1, sigma2};
      EXPECT_TRUE(test::all_close_f(read_vector<float>(result), expected));
  }
  
  NGRAPH_TEST(${BACKEND_NAME}, sigmoid_n1c1h4)
  {
      auto input = make_shared<op::Parameter>(element::Type_t::f32, Shape{1, 1, 4});
      auto sigmoid_node = make_shared<op::Sigmoid>(input);
      auto func = make_shared<Function>(sigmoid_node, ParameterVector{input});
  
      auto backend = runtime::Backend::create("${BACKEND_NAME}");
  
      shared_ptr<runtime::Tensor> a =
          backend->create_tensor(element::Type_t::f32, input->get_shape());
      shared_ptr<runtime::Tensor> result =
          backend->create_tensor(element::Type_t::f32, input->get_shape());
  
      float x1 = 1.0f;
      float x2 = 4.0f;
      float sigma1 = 1.0f / (1.0f + std::exp(-x1));
      float sigma2 = 1.0f / (1.0f + std::exp(-x2));
  
      vector<float> dataA{x1, x2, x1, x2};
      copy_data(a, dataA);
  
      auto handle = backend->compile(func);
      handle->call_with_validate({result}, {a});
      vector<float> expected{sigma1, sigma2, sigma1, sigma2};
      EXPECT_TRUE(test::all_close_f(read_vector<float>(result), expected));
  }
  