text: // Copyright (C) 2020 Intel Corporation
  // SPDX-License-Identifier: Apache-2.0
  //
  
  #include "bfloat16_helpers.hpp"
  
  #include <memory>
  #include <tuple>
  #include <vector>
  #include <string>
  #include <functional>
  #include <map>
  #include <utility>
  
  #include <ie_core.hpp>
  
  #include "functional_test_utils/blob_utils.hpp"
  #include "common_test_utils/common_utils.hpp"
  
  #include "ngraph/opsets/opset1.hpp"
  
  using namespace std;
  using namespace ngraph;
  using namespace InferenceEngine;
  
  namespace LayerTestsDefinitions {
  
  class ScaleshiftConvEluConv : public BasicBF16Test {
  protected:
      std::shared_ptr<ngraph::Function> createGraph(InferenceEngine::Precision netPrecision) override {
          //              scaleshift (FP32)
          //                 |
          //                Conv (BF16)
          //                |
          //                Elu (FP32 for now, this must be fixed and it must be fused into Conv)
          //                 |
          //                Conv (BF16)
  
          ngraph::element::Type ntype = (netPrecision == Precision::FP32) ? ngraph::element::f32 : ngraph::element::bf16;
          auto channelsCount = inputShapes[1];
  
          // multiply
          auto input1 = std::make_shared<opset1::Parameter>(ntype, ngraph::Shape{inputShapes});
          input1->set_friendly_name("Input_1");
          std::shared_ptr<ngraph::opset1::Constant> const1 = nullptr;
          if (netPrecision == Precision::FP32) {
              const1 = opset1::Constant::create(ntype, Shape{1}, { 2.0f });
          } else {
              const1 = opset1::Constant::create(ntype, Shape{1}, { bfloat16::from_bits(FuncTestUtils::Bf16TestUtils::reducePrecisionBitwiseS(2.0f)) });
          }
          auto mulNode = std::make_shared<opset1::Multiply>(input1, const1);
  
          // add
          std::shared_ptr<ngraph::opset1::Constant> const2 = nullptr;
          if (netPrecision == Precision::FP32) {
              const2 = opset1::Constant::create(ntype, Shape{1}, { 1.0f });
          } else {
              const2 = opset1::Constant::create(ntype, Shape{1}, { bfloat16::from_bits(FuncTestUtils::Bf16TestUtils::reducePrecisionBitwiseS(1.0f)) });
          }
          auto addNode = std::make_shared<opset1::Add>(mulNode, const2);
          addNode->set_friendly_name("ADD_1");
  
          // convolution
          std::shared_ptr<ngraph::opset1::Constant> weightsNode = nullptr;
          ngraph::Shape convFilterShape = { channelsCount, channelsCount, 3, 3 };  // out channel, /input channels, kernel h, kernel w
          if (netPrecision == Precision::FP32) {
              std::vector<float> weightValuesFP32;
              weightValuesFP32.resize(channelsCount * channelsCount * 3 * 3);
              FuncTestUtils::fillInputsBySinValues(weightValuesFP32.data(), weightValuesFP32.size());
              weightsNode = std::make_shared<ngraph::opset1::Constant>(ntype, convFilterShape, weightValuesFP32);
          } else {
              std::vector<short> weightValuesBF16;
              weightValuesBF16.resize(channelsCount * channelsCount * 3 * 3);
              FuncTestUtils::fillInputsBySinValues(weightValuesBF16.data(), weightValuesBF16.size());
              weightsNode = std::make_shared<ngraph::opset1::Constant>(ntype, convFilterShape, weightValuesBF16.data());
          }
  
          std::shared_ptr<ngraph::Node> convNode1 = std::make_shared<ngraph::opset1::Convolution>(
              addNode, weightsNode,
              ngraph::Strides({ 1, 1 }),   // strides
              ngraph::CoordinateDiff({ 1, 1 }),  // pad begin
              ngraph::CoordinateDiff({ 1, 1 }),   // pad end
              ngraph::Strides({ 1, 1 }),        // dilation
              ngraph::op::PadType::EXPLICIT);   // pad type
          convNode1->set_friendly_name("CONV_1");
  
          // Elu
          auto eluNode =  std::make_shared<opset1::Elu>(convNode1, 2);
          eluNode->set_friendly_name("ELU_1");
  
          // Conv
          std::shared_ptr<ngraph::Node> convNode2 = std::make_shared<ngraph::opset1::Convolution>(
              eluNode, weightsNode,
              ngraph::Strides({ 1, 1 }),   // strides
              ngraph::CoordinateDiff({ 1, 1 }),  // pad begin
              ngraph::CoordinateDiff({ 1, 1 }),   // pad end
              ngraph::Strides({ 1, 1 }),        // dilation
              ngraph::op::PadType::EXPLICIT);   // pad type
          convNode2->set_friendly_name("CONV_2");
  
          return std::make_shared<ngraph::Function>(ngraph::NodeVector{convNode2}, ngraph::ParameterVector{input1});
      }
      void SetUp() override {
          std::tie(inputPrecision, netPrecision, inputShapes, newInputShapes, targetDevice) = this->GetParam();
          fnPtr = createGraph(netPrecision);
  
          // STAGE1:
          threshold = 1;
          // STAGE2:
          // filling of expected precision of layer execution defined by precisoin of input tensor to the primitive and reflected in
          // performance counters
          expectedPrecisions["ADD_1"] = "FP32";
          expectedPrecisions["CONV_1"] = "BF16";
          expectedPrecisions["CONV_2"] = "BF16";
      }
  };
  
  TEST_P(ScaleshiftConvEluConv, CompareWithRefImpl) {
      test();
  };
  
  INSTANTIATE_TEST_CASE_P(FP32_bfloat16_NoReshape, ScaleshiftConvEluConv,
                          ::testing::Combine(
                                  ::testing::Values(Precision::FP32),
                                  ::testing::Values(Precision::FP32),
                                  ::testing::Values(SizeVector({ 1, 3, 40, 40 })),
                                  ::testing::Values(SizeVector()),
                                  ::testing::Values(CommonTestUtils::DEVICE_CPU)),
                          ScaleshiftConvEluConv::getTestCaseName);
  
  INSTANTIATE_TEST_CASE_P(BF16_bfloat16_NoReshape, ScaleshiftConvEluConv,
                          ::testing::Combine(
                              ::testing::Values(Precision::FP32),
                              ::testing::Values(Precision::BF16),
                              ::testing::Values(SizeVector({ 1, 3, 40, 40 })),
                              ::testing::Values(SizeVector()),
                              ::testing::Values(CommonTestUtils::DEVICE_CPU)),
                          ScaleshiftConvEluConv::getTestCaseName);
  
  
  }  // namespace LayerTestsDefinitions
  