inference-engine/tests/unit/engines/mkldnn/test_layers.cpp

   1 // Copyright (C) 2018-2019 Intel Corporation
   2 // SPDX-License-Identifier: Apache-2.0
   3 //
   4
   5 //#include <gtest/gtest.h>
   6 //#include "mkldnn_plugin/mkldnn_layers.h"
   7 //
   8 //using namespace std;
   9 //
  10 //class MKLDNNLayersTests : public ::testing::Test {
  11 //protected:
  12 //    virtual void TearDown() override{
  13 //    }
  14 //
  15 //    virtual void SetUp() override{
  16 //    }
  17 //
  18 //};
  19 //
  20 //TEST_F(MKLDNNLayersTests, canCreateContext) {
  21 //    std::vector<float> sd;
  22 //    std::vector<float> dd;
  23 //    std::vector<size_t> ds;
  24 //    unique_ptr<MKLDNNPlugin::Context> dl ( new MKLDNNPlugin::Context({}, mkldnn::engine(mkldnn::engine::cpu, 0), &sd, &dd, &ds));
  25 //
  26 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::Context*>(dl.get()));
  27 //}
  28 //
  29 //TEST_F(MKLDNNLayersTests, canCreateConvLayer) {
  30 //    std::vector<float> sd;
  31 //    std::vector<float> dd;
  32 //    std::vector<size_t> ds;
  33 //    InferenceEngine::TBlob<float>::Ptr blobPtr(new InferenceEngine::TBlob<float>());
  34 //    unique_ptr<MKLDNNPlugin::Context> ctx ( new MKLDNNPlugin::Context(blobPtr, mkldnn::engine(mkldnn::engine::cpu, 0), &sd, &dd, &ds));
  35 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get()));
  36 //
  37 //    InferenceEngine::ConvolutionLayer convLayer({});
  38 //    InferenceEngine::DataPtr dPtr(new InferenceEngine::Data("testData"));
  39 //    dPtr->dims = {0, 0, 0, 0};
  40 //
  41 //    convLayer.insData.push_back(dPtr);
  42 //    convLayer.outData.push_back(dPtr);
  43 //    unique_ptr<MKLDNNPlugin::Layer> dl ( MKLDNNPlugin::LayerRegistry::CreateLayer(&convLayer, nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get())));
  44 //
  45 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::ConvLayer*>(dl.get()));
  46 //}
  47 //
  48 //TEST_F(MKLDNNLayersTests, canCreateLRNLayer) {
  49 //    std::vector<float> sd;
  50 //    std::vector<float> dd;
  51 //    std::vector<size_t> ds;
  52 //    unique_ptr<MKLDNNPlugin::Context> ctx ( new MKLDNNPlugin::Context({}, mkldnn::engine(mkldnn::engine::cpu, 0), &sd, &dd, &ds));
  53 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get()));
  54 //
  55 //    InferenceEngine::NormLayer normLayer({});
  56 //    InferenceEngine::DataPtr dPtr(new InferenceEngine::Data("testData"));
  57 //    dPtr->dims = {1, 1, 27, 27};
  58 //
  59 //    normLayer.insData.push_back(dPtr);
  60 //    normLayer.outData.push_back(dPtr);
  61 //    unique_ptr<MKLDNNPlugin::Layer> dl ( MKLDNNPlugin::LayerRegistry::CreateLayer(&normLayer, nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get())));
  62 //
  63 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::LRNLayer*>(dl.get()));
  64 //}
  65 //
  66 //TEST_F(MKLDNNLayersTests, canCreatePoolingLayer) {
  67 //    std::vector<float> sd;
  68 //    std::vector<float> dd;
  69 //    std::vector<size_t> ds;
  70 //    unique_ptr<MKLDNNPlugin::Context> ctx ( new MKLDNNPlugin::Context({}, mkldnn::engine(mkldnn::engine::cpu, 0), &sd, &dd, &ds));
  71 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get()));
  72 //
  73 //    InferenceEngine::PoolingLayer poolingLayer({});
  74 //    InferenceEngine::DataPtr dPtr(new InferenceEngine::Data("testData"));
  75 //    dPtr->dims = {1, 1, 27, 27};
  76 //
  77 //    poolingLayer.insData.push_back(dPtr);
  78 //    poolingLayer.outData.push_back(dPtr);
  79 //    unique_ptr<MKLDNNPlugin::Layer> dl ( MKLDNNPlugin::LayerRegistry::CreateLayer(&poolingLayer, nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get())));
  80 //
  81 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::PoolingLayer*>(dl.get()));
  82 //}
  83 //
  84 //TEST_F(MKLDNNLayersTests, canCreateSplitLayer) {
  85 //    std::vector<float> sd;
  86 //    std::vector<float> dd;
  87 //    std::vector<size_t> ds;
  88 //    unique_ptr<MKLDNNPlugin::Context> ctx ( new MKLDNNPlugin::Context({}, mkldnn::engine(mkldnn::engine::cpu, 0), &sd, &dd, &ds));
  89 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get()));
  90 //
  91 //    InferenceEngine::SplitLayer splitLayer({});
  92 //    unique_ptr<MKLDNNPlugin::Layer> dl ( MKLDNNPlugin::LayerRegistry::CreateLayer(&splitLayer, nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get())));
  93 //
  94 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::SplitLayer*>(dl.get()));
  95 //}
  96 //
  97 //TEST_F(MKLDNNLayersTests, canCreateConcatLayer) {
  98 //    std::vector<float> sd;
  99 //    std::vector<float> dd;
 100 //    std::vector<size_t> ds;
 101 //    unique_ptr<MKLDNNPlugin::Context> ctx ( new MKLDNNPlugin::Context({}, mkldnn::engine(mkldnn::engine::cpu, 0), &sd, &dd, &ds));
 102 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get()));
 103 //
 104 //    InferenceEngine::ConcatLayer concatLayer({});
 105 //    unique_ptr<MKLDNNPlugin::Layer> dl ( MKLDNNPlugin::LayerRegistry::CreateLayer(&concatLayer, nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get())));
 106 //
 107 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::ConcatLayer*>(dl.get()));
 108 //}
 109 //
 110 //TEST_F(MKLDNNLayersTests, canCreateFullyConnectedLayer) {
 111 //    std::vector<float> sd;
 112 //    std::vector<float> dd;
 113 //    std::vector<size_t> ds;
 114 //    InferenceEngine::TBlob<float>::Ptr blobPtr(new InferenceEngine::TBlob<float>());
 115 //    unique_ptr<MKLDNNPlugin::Context> ctx ( new MKLDNNPlugin::Context(blobPtr, mkldnn::engine(mkldnn::engine::cpu, 0), &sd, &dd, &ds));
 116 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get()));
 117 //
 118 //    InferenceEngine::FullyConnectedLayer fcLayer({});
 119 //    InferenceEngine::DataPtr dPtr(new InferenceEngine::Data("testData"));
 120 //    dPtr->dims = {0, 0, 0, 0};
 121 //    InferenceEngine::DataPtr dPtr2(new InferenceEngine::Data("testData2"));
 122 //    dPtr2->dims = {0, 0};
 123 //
 124 //    fcLayer.insData.push_back(dPtr);
 125 //    fcLayer.outData.push_back(dPtr2);
 126 //    unique_ptr<MKLDNNPlugin::Layer> dl ( MKLDNNPlugin::LayerRegistry::CreateLayer(&fcLayer, nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get())));
 127 //
 128 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::FullyConnectedLayer*>(dl.get()));
 129 //}
 130 //
 131 //TEST_F(MKLDNNLayersTests, canCreateSoftMaxLayer) {
 132 //    std::vector<float> sd;
 133 //    std::vector<float> dd;
 134 //    std::vector<size_t> ds;
 135 //    unique_ptr<MKLDNNPlugin::Context> ctx ( new MKLDNNPlugin::Context({}, mkldnn::engine(mkldnn::engine::cpu, 0), &sd, &dd, &ds));
 136 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get()));
 137 //
 138 //    InferenceEngine::SoftMaxLayer softmaxLayer({});
 139 //    InferenceEngine::DataPtr dPtr(new InferenceEngine::Data("testData"));
 140 //    dPtr->dims = {0, 0, 0, 0};
 141 //    InferenceEngine::DataPtr dPtr2(new InferenceEngine::Data("testData2"));
 142 //    dPtr2->dims = {0, 0};
 143 //
 144 //    softmaxLayer.insData.push_back(dPtr);
 145 //    softmaxLayer.outData.push_back(dPtr2);
 146 //    unique_ptr<MKLDNNPlugin::Layer> dl ( MKLDNNPlugin::LayerRegistry::CreateLayer(&softmaxLayer, nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get())));
 147 //
 148 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::SoftMaxLayer*>(dl.get()));
 149 //}
 150 //
 151 //TEST_F(MKLDNNLayersTests, canCreateReLULayer) {
 152 //    std::vector<float> sd;
 153 //    std::vector<float> dd;
 154 //    std::vector<size_t> ds;
 155 //    unique_ptr<MKLDNNPlugin::Context> ctx ( new MKLDNNPlugin::Context({}, mkldnn::engine(mkldnn::engine::cpu, 0), &sd, &dd, &ds));
 156 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get()));
 157 //
 158 //    InferenceEngine::ReLULayer reLULayer({});
 159 //    InferenceEngine::DataPtr dPtr(new InferenceEngine::Data("testData"));
 160 //    dPtr->dims = {1, 1, 27, 27};
 161 //
 162 //    reLULayer.insData.push_back(dPtr);
 163 //    reLULayer.outData.push_back(dPtr);
 164 //    unique_ptr<MKLDNNPlugin::Layer> dl ( MKLDNNPlugin::LayerRegistry::CreateLayer(&reLULayer, nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get())));
 165 //
 166 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::ReLULayer*>(dl.get()));
 167 //}
 168 //
 169 //TEST_F(MKLDNNLayersTests, canNotCreateCNNLayer) {
 170 //    std::vector<float> sd;
 171 //    std::vector<float> dd;
 172 //    std::vector<size_t> ds;
 173 //    unique_ptr<MKLDNNPlugin::Context> ctx ( new MKLDNNPlugin::Context({}, mkldnn::engine(mkldnn::engine::cpu, 0), &sd, &dd, &ds));
 174 //    ASSERT_NE(nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get()));
 175 //
 176 //    InferenceEngine::CNNLayer cnnLayer({});
 177 //    EXPECT_THROW(MKLDNNPlugin::LayerRegistry::CreateLayer(&cnnLayer, nullptr, dynamic_cast<MKLDNNPlugin::Context*>(ctx.get())) , InferenceEngine::details::InferenceEngineException);
 178 //}
 179 //
 180 //TEST_F(MKLDNNLayersTests, canNotCreateLayerWithoutContext) {
 181 //    InferenceEngine::ConvolutionLayer convLayer({});
 182 //    EXPECT_THROW(MKLDNNPlugin::LayerRegistry::CreateLayer(&convLayer, nullptr, nullptr), InferenceEngine::details::InferenceEngineException);
 183 //}