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| author | Vidhya Sudhan Loganathan <vidhyasudhan.loganathan@arm.com> | 2018-04-19 14:22:16 +0100 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:49:37 +0000 |
| commit | b34690b71a0125c37d087b00becf2e60d66b46d1 (patch) | |
| tree | c3324e750ed7ee5a58f12afe4f7ff4c620a3ddaf /tests/benchmark | |
| parent | d727e85363aa7666e3fceb6967b668a3ac8d146e (diff) | |
| download | ComputeLibrary-b34690b71a0125c37d087b00becf2e60d66b46d1.tar.gz | |
COMPMID-1012 : Add OpenCL benchmarks for Winograd
Change-Id: I1cc64535fcd87d500d3ee1ec9e9ff0caef5bcf9f
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/128282
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Diffstat (limited to 'tests/benchmark')
| -rw-r--r-- | tests/benchmark/CL/ConvolutionLayer.cpp | 52 |
1 files changed, 52 insertions, 0 deletions
diff --git a/tests/benchmark/CL/ConvolutionLayer.cpp b/tests/benchmark/CL/ConvolutionLayer.cpp index ee25e12a0e..3cf04295e4 100644 --- a/tests/benchmark/CL/ConvolutionLayer.cpp +++ b/tests/benchmark/CL/ConvolutionLayer.cpp @@ -26,8 +26,10 @@ #include "arm_compute/runtime/CL/CLTensor.h" #include "arm_compute/runtime/CL/CLTensorAllocator.h" #include "arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h" +#include "arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h" #include "tests/CL/CLAccessor.h" #include "tests/benchmark/fixtures/ConvolutionLayerFixture.h" +#include "tests/benchmark/fixtures/WinogradLayerFixture.h" #include "tests/datasets/system_tests/alexnet/AlexNetConvolutionLayerDataset.h" #include "tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ConvolutionLayerDataset.h" #include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ConvolutionLayerDataset.h" @@ -55,6 +57,32 @@ using CLGEMMConvolutionLayerFixture = ConvolutionLayerFixture<CLTensor, CLGEMMCo TEST_SUITE(CL) +using CLWinogradLayerFixture = WinogradLayerFixture<CLTensor, CLWinogradConvolutionLayer, CLAccessor>; + +REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetWinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetWinogradLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("Batches", 1))); + +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1WinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1WinogradLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("Batches", 1))); + +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4WinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4WinogradLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo())), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("Batches", 1))); + +REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetWinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetWinogradLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo())), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("Batches", 1))); + REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), @@ -131,6 +159,30 @@ REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2ConvolutionLayer, CLGEMMConvolutionLayerFi framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo())), data_types), framework::dataset::make("Batches", { 1, 4, 8 }))); + +REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetWinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetWinogradLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("Batches", { 4, 8 }))); + +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1WinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1WinogradLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("Batches", { 4, 8 }))); + +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4WinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4WinogradLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo())), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("Batches", { 4, 8 }))); + +REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetWinogradLayer, CLWinogradLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetWinogradLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("Batches", { 4, 8 }))); TEST_SUITE_END() TEST_SUITE_END() } // namespace benchmark |