diff options
Diffstat (limited to 'tests')
21 files changed, 598 insertions, 323 deletions
diff --git a/tests/benchmark/CL/ConvolutionLayer.cpp b/tests/benchmark/CL/ConvolutionLayer.cpp index bad644f8b8..ee25e12a0e 100644 --- a/tests/benchmark/CL/ConvolutionLayer.cpp +++ b/tests/benchmark/CL/ConvolutionLayer.cpp @@ -56,69 +56,79 @@ using CLGEMMConvolutionLayerFixture = ConvolutionLayerFixture<CLTensor, CLGEMMCo TEST_SUITE(CL) REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo())), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo())), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::MobileNetConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); TEST_SUITE(NIGHTLY) REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo())), data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo())), data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); // 8 batches use about 1.8GB of memory which is too much for most devices! REGISTER_FIXTURE_DATA_TEST_CASE(VGG16ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 1, 4 }))); REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2ConvolutionLayer, CLGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), + 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 }))); TEST_SUITE_END() diff --git a/tests/benchmark/CL/DirectConvolutionLayer.cpp b/tests/benchmark/CL/DirectConvolutionLayer.cpp index c7b07807e9..df63d3ac5d 100644 --- a/tests/benchmark/CL/DirectConvolutionLayer.cpp +++ b/tests/benchmark/CL/DirectConvolutionLayer.cpp @@ -49,58 +49,67 @@ namespace const auto data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32 }); } // namespace -using CLConvolutionLayerFixture = DirectConvolutionLayerFixture<CLTensor, CLDirectConvolutionLayer, CLAccessor>; +using CLDirectConvolutionLayerFixture = DirectConvolutionLayerFixture<CLTensor, CLDirectConvolutionLayer, CLAccessor>; TEST_SUITE(CL) -REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, CLConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, CLDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, CLConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, CLDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, CLConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, CLDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo())), data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, CLConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, CLDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); TEST_SUITE(NIGHTLY) -REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, CLConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, CLDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, CLConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, CLDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, CLConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, CLDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo())), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, CLConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, CLDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(VGG16DirectConvolutionLayer, CLConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(VGG16DirectConvolutionLayer, CLDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 1, 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2DirectConvolutionLayer, CLConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2DirectConvolutionLayer, CLDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + 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 }))); TEST_SUITE_END() diff --git a/tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp b/tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp index 4cb020caf4..c79e0156cf 100644 --- a/tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp +++ b/tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp @@ -55,64 +55,73 @@ using GCConvolutionLayerFixture = ConvolutionLayerFixture<GCTensor, GCConvolutio TEST_SUITE(GC) REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo())), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo())), data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); TEST_SUITE(NIGHTLY) REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", ActivationLayerInfo())), data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo())), data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); // 8 batches use about 1.8GB of memory which is too much for most devices! REGISTER_FIXTURE_DATA_TEST_CASE(VGG16ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 1, 4 }))); REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), + 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 }))); TEST_SUITE_END() diff --git a/tests/benchmark/GLES_COMPUTE/DirectConvolutionLayer.cpp b/tests/benchmark/GLES_COMPUTE/DirectConvolutionLayer.cpp index d319c41088..66fd8fc216 100644 --- a/tests/benchmark/GLES_COMPUTE/DirectConvolutionLayer.cpp +++ b/tests/benchmark/GLES_COMPUTE/DirectConvolutionLayer.cpp @@ -49,58 +49,68 @@ namespace const auto data_types = framework::dataset::make("DataType", { DataType::F32, DataType::F16 }); } // namespace -using GCConvolutionLayerFixture = DirectConvolutionLayerFixture<GCTensor, GCDirectConvolutionLayer, GCAccessor>; +using GCDirectConvolutionLayerFixture = DirectConvolutionLayerFixture<GCTensor, GCDirectConvolutionLayer, GCAccessor>; TEST_SUITE(GC) -REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, GCDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, GCDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, GCDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo())), data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, GCDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", 1))); TEST_SUITE(NIGHTLY) -REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, GCDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, GCDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, GCDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo())), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, GCDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(VGG16DirectConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(VGG16DirectConvolutionLayer, GCDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), framework::dataset::make("ActivationInfo", + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), data_types), framework::dataset::make("Batches", { 1, 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2DirectConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), +REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2DirectConvolutionLayer, GCDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + 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 }))); TEST_SUITE_END() diff --git a/tests/benchmark/NEON/ConvolutionLayer.cpp b/tests/benchmark/NEON/ConvolutionLayer.cpp index a425d95a6e..e7f2788020 100644 --- a/tests/benchmark/NEON/ConvolutionLayer.cpp +++ b/tests/benchmark/NEON/ConvolutionLayer.cpp @@ -65,91 +65,133 @@ TEST_SUITE(NEON) using NEWinogradLayerFixture = WinogradLayerFixture<Tensor, NEWinogradLayer, Accessor>; REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetWinogradLayer, NEWinogradLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetWinogradLayerDataset(), framework::dataset::make("DataType", DataType::F32)), + 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, NEWinogradLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1WinogradLayerDataset(), framework::dataset::make("DataType", DataType::F32)), + 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, NEWinogradLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4WinogradLayerDataset(), framework::dataset::make("DataType", DataType::F32)), + 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, NEWinogradLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetWinogradLayerDataset(), framework::dataset::make("DataType", DataType::F32)), + 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))); #endif /* __aarch64__ */ REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo())), + data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo())), + data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", 1))); REGISTER_FIXTURE_DATA_TEST_CASE(MobileNetConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::MobileNetConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::MobileNetConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", 1))); TEST_SUITE(NIGHTLY) REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo())), + data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo())), + data_types), framework::dataset::make("Batches", { 4, 8 }))); REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", { 4, 8 }))); // 8 batches use about 2GB of memory which is too much for most devices! REGISTER_FIXTURE_DATA_TEST_CASE(VGG16ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), data_types), + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", { 1, 2 }))); REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), data_types), + 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 }))); #if defined(__aarch64__) REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetWinogradLayer, NEWinogradLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetWinogradLayerDataset(), framework::dataset::make("DataType", DataType::F32)), + 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, NEWinogradLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1WinogradLayerDataset(), framework::dataset::make("DataType", DataType::F32)), + 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, NEWinogradLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4WinogradLayerDataset(), framework::dataset::make("DataType", DataType::F32)), + 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, NEWinogradLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetWinogradLayerDataset(), framework::dataset::make("DataType", DataType::F32)), + 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 }))); #endif /* __aarch64__ */ diff --git a/tests/benchmark/NEON/DirectConvolutionLayer.cpp b/tests/benchmark/NEON/DirectConvolutionLayer.cpp index 8a17f3c03c..22f1bd2942 100644 --- a/tests/benchmark/NEON/DirectConvolutionLayer.cpp +++ b/tests/benchmark/NEON/DirectConvolutionLayer.cpp @@ -55,49 +55,69 @@ const auto data_types = framework::dataset::make("DataType", { DataType::F32 }); #endif /* ARM_COMPUTE_ENABLE_F16 */ } // namespace -using NEConvolutionLayerFixture = DirectConvolutionLayerFixture<Tensor, NEDirectConvolutionLayer, Accessor>; +using NEDirectConvolutionLayerFixture = DirectConvolutionLayerFixture<Tensor, NEDirectConvolutionLayer, Accessor>; TEST_SUITE(NEON) -REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), data_types), +REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), data_types), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), data_types), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo())), + data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), data_types), +REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::ALL, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", 1))); TEST_SUITE(NIGHTLY) -REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), data_types), +REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetDirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetDirectConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), data_types), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1DirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1DirectConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), data_types), +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4DirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4DirectConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo())), + data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), data_types), +REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetDirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(VGG16DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), data_types), +REGISTER_FIXTURE_DATA_TEST_CASE(VGG16DirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + data_types), framework::dataset::make("Batches", { 1, 2 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2DirectConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, - framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), data_types), +REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2DirectConvolutionLayer, NEDirectConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, + 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 }))); TEST_SUITE_END() diff --git a/tests/benchmark/fixtures/ConvolutionLayerFixture.h b/tests/benchmark/fixtures/ConvolutionLayerFixture.h index 7558b4c9a8..511daf73b3 100644 --- a/tests/benchmark/fixtures/ConvolutionLayerFixture.h +++ b/tests/benchmark/fixtures/ConvolutionLayerFixture.h @@ -42,7 +42,8 @@ class ConvolutionLayerFixture : public framework::Fixture { public: template <typename...> - void setup(TensorShape src_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape dst_shape, PadStrideInfo info, Size2D dilation, DataType data_type, int batches) + void setup(TensorShape src_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape dst_shape, PadStrideInfo info, Size2D dilation, ActivationLayerInfo act_info, DataType data_type, + int batches) { // Set batched in source and destination shapes const unsigned int fixed_point_position = 4; @@ -57,7 +58,7 @@ public: dst = create_tensor<TensorType>(dst_shape, data_type, 1, fixed_point_position); // Create and configure function - conv_layer.configure(&src, &weights, &biases, &dst, info, WeightsInfo(), dilation); + conv_layer.configure(&src, &weights, &biases, &dst, info, WeightsInfo(), dilation, act_info); // Allocate tensors src.allocator()->allocate(); diff --git a/tests/benchmark/fixtures/DirectConvolutionLayerFixture.h b/tests/benchmark/fixtures/DirectConvolutionLayerFixture.h index e3289b7fbc..419f6dd822 100644 --- a/tests/benchmark/fixtures/DirectConvolutionLayerFixture.h +++ b/tests/benchmark/fixtures/DirectConvolutionLayerFixture.h @@ -43,7 +43,8 @@ class DirectConvolutionLayerFixture : public framework::Fixture { public: template <typename...> - void setup(TensorShape src_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape dst_shape, PadStrideInfo info, Size2D dilation, DataType data_type, int batches) + void setup(TensorShape src_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape dst_shape, PadStrideInfo info, Size2D dilation, ActivationLayerInfo act_info, DataType data_type, + int batches) { ARM_COMPUTE_UNUSED(dilation); @@ -60,7 +61,7 @@ public: dst = create_tensor<TensorType>(dst_shape, data_type, 1, fixed_point_position); // Create and configure function - conv_layer.configure(&src, &weights, &biases, &dst, info); + conv_layer.configure(&src, &weights, &biases, &dst, info, act_info); // Allocate tensors src.allocator()->allocate(); diff --git a/tests/benchmark/fixtures/WinogradLayerFixture.h b/tests/benchmark/fixtures/WinogradLayerFixture.h index 31a1eb8e1c..0be535f4cc 100644 --- a/tests/benchmark/fixtures/WinogradLayerFixture.h +++ b/tests/benchmark/fixtures/WinogradLayerFixture.h @@ -42,7 +42,8 @@ class WinogradLayerFixture : public framework::Fixture { public: template <typename...> - void setup(TensorShape src_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape dst_shape, PadStrideInfo info, Size2D dilation, DataType data_type, int batches) + void setup(TensorShape src_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape dst_shape, PadStrideInfo info, Size2D dilation, ActivationLayerInfo act_info, DataType data_type, + int batches) { ARM_COMPUTE_UNUSED(dilation); @@ -59,7 +60,7 @@ public: dst = create_tensor<TensorType>(dst_shape, data_type, 1, fixed_point_position); // Create and configure function - conv_layer.configure(&src, &weights, &biases, &dst, info); + conv_layer.configure(&src, &weights, &biases, &dst, info, act_info); // Allocate tensors src.allocator()->allocate(); diff --git a/tests/validation/CL/ConvolutionLayer.cpp b/tests/validation/CL/ConvolutionLayer.cpp index c50519b6ac..b50bb94bbb 100644 --- a/tests/validation/CL/ConvolutionLayer.cpp +++ b/tests/validation/CL/ConvolutionLayer.cpp @@ -60,6 +60,13 @@ const auto CNNDataTypes = framework::dataset::make("DataType", DataType::QS16, DataType::QASYMM8, }); +const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) +}); } // namespace TEST_SUITE(CL) @@ -109,18 +116,18 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z ConvolutionMethod is_valid = CLConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), - &output_info.clone()->set_is_resizable(false), conv_info, WeightsInfo(), gpu_target); + &output_info.clone()->set_is_resizable(false), conv_info, WeightsInfo(), ActivationLayerInfo(), gpu_target); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } TEST_SUITE_END() TEST_SUITE(GEMMConvolutionLayer) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()), CNNDataTypes), - input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()), + CNNDataTypes), + ActivationFunctionsDataset), + input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info) { - ARM_COMPUTE_UNUSED(dilation); - // Set fixed point position data type allowed int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0; @@ -142,7 +149,7 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::da // Create and configure function CLGEMMConvolutionLayer conv; - conv.configure(&src, &weights, &bias, &dst, info); + conv.configure(&src, &weights, &bias, &dst, info, WeightsInfo(), dilation, act_info); // Validate valid region const ValidRegion src_valid_region = shape_to_valid_region(input_shape); @@ -168,18 +175,22 @@ using CLGEMMConvolutionLayerFixture = ConvolutionValidationFixture<CLTensor, CLA TEST_SUITE(Float) TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallConvolutionLayerDataset(), + +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", - DataType::F16))) + DataType::F16)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeConvolutionLayerDataset(), + +FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F16))) + framework::dataset::make("DataType", + DataType::F16)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); @@ -187,18 +198,22 @@ FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerFixture<half>, framework: TEST_SUITE_END() TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallConvolutionLayerDataset(), + +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", - DataType::F32))) + DataType::F32)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeConvolutionLayerDataset(), + +FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F32))) + framework::dataset::make("DataType", + DataType::F32)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); @@ -212,20 +227,23 @@ using CLGEMMConvolutionLayerFixedPointFixture = ConvolutionValidationFixedPointF TEST_SUITE(FixedPoint) TEST_SUITE(QS8) // We test for fixed point precision [4,6] -FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::TinyConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::TinyConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QS8)), - framework::dataset::make("FractionalBits", 4, 7))) + framework::dataset::make("FractionalBits", 4, 7)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fixed); } -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallConvolutionLayerDataset(), + +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QS8)), - framework::dataset::make("FractionalBits", 4, 7))) + framework::dataset::make("FractionalBits", 4, 7)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fixed); @@ -234,20 +252,23 @@ TEST_SUITE_END() TEST_SUITE(QS16) // Testing for fixed point position [1,14) -FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::TinyConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::TinyConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QS16)), - framework::dataset::make("FractionalBits", 1, 14))) + framework::dataset::make("FractionalBits", 1, 14)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fixed); } -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallConvolutionLayerDataset(), + +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QS16)), - framework::dataset::make("FractionalBits", 1, 14))) + framework::dataset::make("FractionalBits", 1, 14)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fixed); @@ -258,20 +279,30 @@ TEST_SUITE_END() template <typename T> using CLGEMMConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>; +const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f) +}); + TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallConvolutionLayerDataset(), + +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) }))) + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + QuantizedActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 0) }))) + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 0) })), + QuantizedActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); diff --git a/tests/validation/CL/DilatedConvolutionLayer.cpp b/tests/validation/CL/DilatedConvolutionLayer.cpp index dadae2227b..532d04b431 100644 --- a/tests/validation/CL/DilatedConvolutionLayer.cpp +++ b/tests/validation/CL/DilatedConvolutionLayer.cpp @@ -113,7 +113,7 @@ DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(z ConvolutionMethod is_valid = CLConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), - &output_info.clone()->set_is_resizable(false), conv_info, WeightsInfo(), gpu_target, dilation); + &output_info.clone()->set_is_resizable(false), conv_info, WeightsInfo(), ActivationLayerInfo(), gpu_target, dilation); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } TEST_SUITE_END() @@ -171,18 +171,18 @@ using CLGEMMDilatedConvolutionLayerFixture = ConvolutionValidationFixture<CLTens TEST_SUITE(Float) TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F16))) + framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F16))) + framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num); @@ -190,18 +190,18 @@ FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerFixture<half>, fra TEST_SUITE_END() TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F32))) + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::F32))) + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); @@ -215,20 +215,24 @@ using CLGEMMDilatedConvolutionLayerFixedPointFixture = ConvolutionValidationFixe TEST_SUITE(FixedPoint) TEST_SUITE(QS8) // We test for fixed point precision [4,6] -FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMDilatedConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::TinyDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::QS8)), - framework::dataset::make("FractionalBits", 4, 7))) +FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMDilatedConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, + combine(combine(combine(combine(datasets::TinyDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", + DataType::QS8)), + framework::dataset::make("FractionalBits", 4, 7)), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fixed); } -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::QS8)), - framework::dataset::make("FractionalBits", 4, 7))) +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, + combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", + DataType::QS8)), + framework::dataset::make("FractionalBits", 4, 7)), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fixed); @@ -237,20 +241,24 @@ TEST_SUITE_END() TEST_SUITE(QS16) // Testing for fixed point position [1,14) -FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMDilatedConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::TinyDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::QS16)), - framework::dataset::make("FractionalBits", 1, 14))) +FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMDilatedConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, + combine(combine(combine(combine(datasets::TinyDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", + DataType::QS16)), + framework::dataset::make("FractionalBits", 1, 14)), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fixed); } -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", - DataType::QS16)), - framework::dataset::make("FractionalBits", 1, 14))) +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, + combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", + DataType::QS16)), + framework::dataset::make("FractionalBits", 1, 14)), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fixed); @@ -263,18 +271,22 @@ using CLGEMMDilatedConvolutionLayerQuantizedFixture = ConvolutionValidationQuant TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) -FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) }))) +FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, + combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 0) }))) +FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, + combine(combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 0) })), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); diff --git a/tests/validation/CL/DirectConvolutionLayer.cpp b/tests/validation/CL/DirectConvolutionLayer.cpp index bf8b4057ee..4564c647b3 100644 --- a/tests/validation/CL/DirectConvolutionLayer.cpp +++ b/tests/validation/CL/DirectConvolutionLayer.cpp @@ -73,6 +73,14 @@ const auto data_fixed_point = combine(datasets::TinyDirectConvolutionShapes(), combine(framework::dataset::make("PadY", 0, 2), framework::dataset::make("KernelSize", { 3 })))), framework::dataset::make("NumKernels", { 1, 4, 8, 16 }))))); +/** Activation function Dataset*/ +const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) +}); } // namespace TEST_SUITE(CL) @@ -82,7 +90,7 @@ TEST_SUITE(DirectConvolutionLayer) // *INDENT-OFF* // clang-format off -DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching data type input/weights TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching input feature maps TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Unsupported kernel width @@ -143,10 +151,14 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( PadStrideInfo(1, 1, 0, 0), PadStrideInfo(1, 1, 0, 0), })), + framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +})), framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, false, false, true })), - input_info, weights_info, biases_info, output_info, conv_info, expected) + input_info, weights_info, biases_info, output_info, conv_info, act_info, expected) { - bool is_valid = bool(CLDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info)); + bool is_valid = bool(CLDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, act_info)); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } // clang-format on @@ -159,7 +171,7 @@ using CLDirectConvolutionValidationWithTensorShapesFixture = DirectConvolutionVa TEST_SUITE(Float) TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(data, framework::dataset::make("DataType", DataType::F16))) +FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(data, framework::dataset::make("DataType", DataType::F16)), ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fp16, tolerance_num); @@ -167,7 +179,8 @@ FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixture<half>, framework::Da TEST_SUITE_END() TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(data, framework::dataset::make("DataType", DataType::F32))) +FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(data, framework::dataset::make("DataType", DataType::F32)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fp32); @@ -175,8 +188,9 @@ FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixture<float>, framework::D TEST_SUITE_END() TEST_SUITE(FP32_CustomDataset) -FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionValidationWithTensorShapesFixture<float>, framework::DatasetMode::ALL, combine(datasets::DirectConvolutionLayerDataset(), - framework::dataset::make("DataType", DataType::F32))) +FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionValidationWithTensorShapesFixture<float>, framework::DatasetMode::ALL, combine(combine(datasets::DirectConvolutionLayerDataset(), + framework::dataset::make("DataType", DataType::F32)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_fp32); @@ -189,8 +203,10 @@ using CLDirectConvolutionLayerFixedPointFixture = DirectConvolutionValidationFix TEST_SUITE(FixedPoint) TEST_SUITE(QS8) -FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(data_fixed_point, framework::dataset::make("DataType", DataType::QS8)), - framework::dataset::make("FractionalBits", 2, 7))) +FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(data_fixed_point, framework::dataset::make("DataType", + DataType::QS8)), + framework::dataset::make("FractionalBits", 2, 7)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qs8); @@ -198,8 +214,10 @@ FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixedPointFixture<int8_t>, f TEST_SUITE_END() TEST_SUITE(QS16) -FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::ALL, combine(combine(data_fixed_point, framework::dataset::make("DataType", DataType::QS16)), - framework::dataset::make("FractionalBits", 2, 15))) +FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::ALL, combine(combine(combine(data_fixed_point, framework::dataset::make("DataType", + DataType::QS16)), + framework::dataset::make("FractionalBits", 2, 15)), + ActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qs16); @@ -212,10 +230,17 @@ using CLDirectConvolutionLayerQuantizedFixture = DirectConvolutionValidationQuan template <typename T> using CLDirectConvolutionValidationWithTensorShapesQuantizedFixture = DirectConvolutionValidationWithTensorShapesQuantizedFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; +const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f) +}); TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) -FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(data, framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10) }))) +FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(data, framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 10) })), + QuantizedActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); @@ -223,9 +248,10 @@ FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerQuantizedFixture<uint8_t>, f TEST_SUITE_END() TEST_SUITE(QASYMM8_CustomDataset) -FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionValidationWithTensorShapesQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(datasets::DirectConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionValidationWithTensorShapesQuantizedFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(datasets::DirectConvolutionLayerDataset(), framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127) }))) + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255, 127) })), + QuantizedActivationFunctionsDataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); diff --git a/tests/validation/CL/Winograd.cpp b/tests/validation/CL/Winograd.cpp index 07a52f8ebc..9aba8f776c 100644 --- a/tests/validation/CL/Winograd.cpp +++ b/tests/validation/CL/Winograd.cpp @@ -373,14 +373,17 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( // *INDENT-ON* using CLWinogradConvolutionLayerFixture = WinogradConvolutionLayerValidationFixture<CLTensor, CLAccessor, CLWinogradConvolutionLayer, float>; -FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFixture, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallWinogradConvolutionLayer3x3Dataset(), - framework::dataset::make("DataType", { DataType::F32 }))) +FIXTURE_DATA_TEST_CASE(RunSmall, CLWinogradConvolutionLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallWinogradConvolutionLayer3x3Dataset(), + framework::dataset::make("DataType", { DataType::F32 })), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, combine(datasets::LargeWinogradConvolutionLayer3x3Dataset(), framework::dataset::make("DataType", { DataType::F32 }))) +FIXTURE_DATA_TEST_CASE(RunLarge, CLWinogradConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeWinogradConvolutionLayer3x3Dataset(), + framework::dataset::make("DataType", { DataType::F32 })), + framework::dataset::make("ActivationLayerInfo", { ActivationLayerInfo() }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); diff --git a/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp b/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp index aaa0d159be..8808d82d34 100644 --- a/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp +++ b/tests/validation/GLES_COMPUTE/ConvolutionLayer.cpp @@ -53,13 +53,21 @@ const auto CNNDataTypes = framework::dataset::make("DataType", DataType::F16, // DataType::F32, }); +const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f) +}); } // namespace TEST_SUITE(GC) TEST_SUITE(ConvolutionLayer) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()), CNNDataTypes), - input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()), + CNNDataTypes), + ActivationFunctionsDataset), + input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info) { // Set fixed point position data type allowed int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0; @@ -82,7 +90,7 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::da // Create and configure function GCConvolutionLayer conv; - conv.configure(&src, &weights, &bias, &dst, info, WeightsInfo(), dilation); + conv.configure(&src, &weights, &bias, &dst, info, WeightsInfo(), dilation, act_info); // Validate valid region const ValidRegion src_valid_region = shape_to_valid_region(input_shape); @@ -108,18 +116,20 @@ using GCConvolutionLayerFixture = ConvolutionValidationFixture<GCTensor, GCAcces TEST_SUITE(Float) TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(RunSmall, GCConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, GCConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", - DataType::F16))) + framework::dataset::make("DataType", + DataType::F16)), + ActivationFunctionsDataset)) { // Validate output validate(GCAccessor(_target), _reference, tolerance_f16, tolerance_num); } -FIXTURE_DATA_TEST_CASE(RunLarge, GCConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunLarge, GCConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", - DataType::F16))) + framework::dataset::make("DataType", + DataType::F16)), + ActivationFunctionsDataset)) { // Validate output validate(GCAccessor(_target), _reference, tolerance_f16, tolerance_num); diff --git a/tests/validation/GLES_COMPUTE/DirectConvolutionLayer.cpp b/tests/validation/GLES_COMPUTE/DirectConvolutionLayer.cpp index 153b060757..47c35f9c6f 100644 --- a/tests/validation/GLES_COMPUTE/DirectConvolutionLayer.cpp +++ b/tests/validation/GLES_COMPUTE/DirectConvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -68,6 +68,13 @@ const auto data = combine(datasets::SmallDirectConvolutionShapes(), combine(framework::dataset::make("PadY", 0, 2), framework::dataset::make("KernelSize", { 3, 5 })))), framework::dataset::make("NumKernels", { 1, 4, 8, 16 }))))); +/** Activation function Dataset*/ +const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LOGISTIC), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), +}); } // namespace TEST_SUITE(GC) @@ -80,7 +87,8 @@ using GCDirectConvolutionLayerFixture = DirectConvolutionValidationFixture<GCTen TEST_SUITE(Float) TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(Run, GCDirectConvolutionLayerFixture<half_float::half>, framework::DatasetMode::ALL, combine(data, framework::dataset::make("DataType", DataType::F16))) +FIXTURE_DATA_TEST_CASE(Run, GCDirectConvolutionLayerFixture<half_float::half>, framework::DatasetMode::ALL, combine(combine(data, framework::dataset::make("DataType", DataType::F16)), + ActivationFunctionsDataset)) { // Validate output validate(GCAccessor(_target), _reference, tolerance_fp16, tolerance_num); @@ -88,7 +96,8 @@ FIXTURE_DATA_TEST_CASE(Run, GCDirectConvolutionLayerFixture<half_float::half>, f TEST_SUITE_END() TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(Run, GCDirectConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(data, framework::dataset::make("DataType", DataType::F32))) +FIXTURE_DATA_TEST_CASE(Run, GCDirectConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(data, framework::dataset::make("DataType", DataType::F32)), + ActivationFunctionsDataset)) { // Validate output validate(GCAccessor(_target), _reference, tolerance_fp32); diff --git a/tests/validation/NEON/ConvolutionLayer.cpp b/tests/validation/NEON/ConvolutionLayer.cpp index 313e4bc4d6..27216af6d1 100644 --- a/tests/validation/NEON/ConvolutionLayer.cpp +++ b/tests/validation/NEON/ConvolutionLayer.cpp @@ -65,6 +65,12 @@ const auto CNNDataTypes = framework::dataset::make("DataType", DataType::QS16, DataType::QASYMM8, }); +const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f) +}); } // namespace TEST_SUITE(NEON) @@ -112,9 +118,11 @@ template <typename T> using NEWinogradConvolutionLayerFixture = WinogradConvolutionLayerValidationFixture<Tensor, Accessor, NEWinogradLayer, T>; TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSmall, NEWinogradConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(framework::dataset::concat(datasets::SmallWinogradConvolutionLayer3x3Dataset(), - datasets::SmallWinogradConvolutionLayer5x5Dataset()), - framework::dataset::make("DataType", { DataType::F32 }))) +FIXTURE_DATA_TEST_CASE(RunSmall, NEWinogradConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, + combine(combine(framework::dataset::concat(datasets::SmallWinogradConvolutionLayer3x3Dataset(), + datasets::SmallWinogradConvolutionLayer5x5Dataset()), + framework::dataset::make("DataType", { DataType::F32 })), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_f32); @@ -125,11 +133,12 @@ TEST_SUITE_END() TEST_SUITE(GEMMConvolutionLayer) -DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()), CNNDataTypes), - input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type) +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()), + CNNDataTypes), + framework::dataset::make("ActivationInfo", +{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) })), +input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, act_info) { - ARM_COMPUTE_UNUSED(dilation); - // Set fixed point position data type allowed int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0; @@ -151,7 +160,7 @@ DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::da // Create and configure function NEGEMMConvolutionLayer conv; - conv.configure(&src, &weights, &bias, &dst, info); + conv.configure(&src, &weights, &bias, &dst, info, WeightsInfo(), dilation, act_info); // Validate valid region const ValidRegion src_valid_region = shape_to_valid_region(input_shape); @@ -178,16 +187,18 @@ using NEGEMMConvolutionLayerFixture = ConvolutionValidationFixture<Tensor, Acces TEST_SUITE(Float) #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::F16))) + framework::dataset::make("DataType", DataType::F16)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_f16); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::F16))) + framework::dataset::make("DataType", DataType::F16)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_f16); @@ -196,16 +207,18 @@ TEST_SUITE_END() #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::F32))) + framework::dataset::make("DataType", DataType::F32)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::F32))) + framework::dataset::make("DataType", DataType::F32)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_f32); @@ -219,18 +232,20 @@ using NEGEMMConvolutionLayerFixedPointFixture = ConvolutionValidationFixedPointF TEST_SUITE(FixedPoint) TEST_SUITE(QS8) // We test for fixed point precision [4,6] -FIXTURE_DATA_TEST_CASE(RunTiny, NEGEMMConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::TinyConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunTiny, NEGEMMConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::TinyConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), framework::dataset::make("DataType", DataType::QS8)), - framework::dataset::make("FractionalBits", 4, 7))) + framework::dataset::make("FractionalBits", 4, 7)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_q); } -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), framework::dataset::make("DataType", DataType::QS8)), - framework::dataset::make("FractionalBits", 4, 7))) + framework::dataset::make("FractionalBits", 4, 7)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_q); @@ -239,18 +254,20 @@ TEST_SUITE_END() TEST_SUITE(QS16) // Testing for fixed point position [1,14) -FIXTURE_DATA_TEST_CASE(RunTiny, NEGEMMConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::TinyConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunTiny, NEGEMMConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::TinyConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), framework::dataset::make("DataType", DataType::QS16)), - framework::dataset::make("FractionalBits", 1, 14))) + framework::dataset::make("FractionalBits", 1, 14)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_q); } -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), framework::dataset::make("DataType", DataType::QS16)), - framework::dataset::make("FractionalBits", 1, 14))) + framework::dataset::make("FractionalBits", 1, 14)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_q); @@ -261,20 +278,28 @@ TEST_SUITE_END() template <typename T> using NEGEMMConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<Tensor, Accessor, NEGEMMConvolutionLayer, T>; +const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f) +}); TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) }))) + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + QuantizedActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true })), framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) }))) + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + QuantizedActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); diff --git a/tests/validation/NEON/DilatedConvolutionLayer.cpp b/tests/validation/NEON/DilatedConvolutionLayer.cpp index c0a72ec8cb..1e8c19fc5e 100644 --- a/tests/validation/NEON/DilatedConvolutionLayer.cpp +++ b/tests/validation/NEON/DilatedConvolutionLayer.cpp @@ -163,16 +163,18 @@ using NEGEMMDilatedConvolutionLayerFixture = ConvolutionValidationFixture<Tensor TEST_SUITE(Float) #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::F16))) + framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(Accessor(_target), _reference, tolerance_f16); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::F16))) + framework::dataset::make("DataType", DataType::F16)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(Accessor(_target), _reference, tolerance_f16); @@ -181,16 +183,18 @@ TEST_SUITE_END() #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::F32))) + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(Accessor(_target), _reference, tolerance_f32); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), +FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::F32))) + framework::dataset::make("DataType", DataType::F32)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(Accessor(_target), _reference, tolerance_f32); @@ -204,18 +208,22 @@ using NEGEMMDilatedConvolutionLayerFixedPointFixture = ConvolutionValidationFixe TEST_SUITE(FixedPoint) TEST_SUITE(QS8) // We test for fixed point precision [4,6] -FIXTURE_DATA_TEST_CASE(RunTiny, NEGEMMDilatedConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::TinyDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::QS8)), - framework::dataset::make("FractionalBits", 4, 7))) +FIXTURE_DATA_TEST_CASE(RunTiny, NEGEMMDilatedConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, + combine(combine(combine(combine(datasets::TinyDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true, false })), + framework::dataset::make("DataType", DataType::QS8)), + framework::dataset::make("FractionalBits", 4, 7)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(Accessor(_target), _reference, tolerance_q); } -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::QS8)), - framework::dataset::make("FractionalBits", 4, 7))) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, + combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true, false })), + framework::dataset::make("DataType", DataType::QS8)), + framework::dataset::make("FractionalBits", 4, 7)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(Accessor(_target), _reference, tolerance_q); @@ -224,18 +232,22 @@ TEST_SUITE_END() TEST_SUITE(QS16) // Testing for fixed point position [1,14) -FIXTURE_DATA_TEST_CASE(RunTiny, NEGEMMDilatedConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::TinyDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::QS16)), - framework::dataset::make("FractionalBits", 1, 14))) +FIXTURE_DATA_TEST_CASE(RunTiny, NEGEMMDilatedConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, + combine(combine(combine(combine(datasets::TinyDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true, false })), + framework::dataset::make("DataType", DataType::QS16)), + framework::dataset::make("FractionalBits", 1, 14)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(Accessor(_target), _reference, tolerance_q); } -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true, false })), - framework::dataset::make("DataType", DataType::QS16)), - framework::dataset::make("FractionalBits", 1, 14))) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, + combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true, false })), + framework::dataset::make("DataType", DataType::QS16)), + framework::dataset::make("FractionalBits", 1, 14)), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(Accessor(_target), _reference, tolerance_q); @@ -248,18 +260,22 @@ using NEGEMMDilatedConvolutionLayerQuantizedFixture = ConvolutionValidationQuant TEST_SUITE(Quantized) TEST_SUITE(QASYMM8) -FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) }))) +FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, + combine(combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); } -FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), - framework::dataset::make("ReshapeWeights", { true })), - framework::dataset::make("DataType", DataType::QASYMM8)), - framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) }))) +FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, + combine(combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(), + framework::dataset::make("ReshapeWeights", { true })), + framework::dataset::make("DataType", DataType::QASYMM8)), + framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })), + framework::dataset::make("ActivationLayerInfo", ActivationLayerInfo()))) { // Validate output validate(Accessor(_target), _reference, tolerance_qasymm8); diff --git a/tests/validation/NEON/DirectConvolutionLayer.cpp b/tests/validation/NEON/DirectConvolutionLayer.cpp index 57e030c349..b6f9f62ff0 100644 --- a/tests/validation/NEON/DirectConvolutionLayer.cpp +++ b/tests/validation/NEON/DirectConvolutionLayer.cpp @@ -86,6 +86,14 @@ const auto data_qs16 = combine(datasets::TinyDirectConvolutionShapes(), combine(framework::dataset::make("PadY", 0), combine(framework::dataset::make("KernelSize", 1), framework::dataset::make("NumKernels", { 1, 4, 8, 16 }))))))); +/** Activation function Dataset*/ +const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f) +}); } // namespace TEST_SUITE(NEON) @@ -93,7 +101,7 @@ TEST_SUITE(DirectConvolutionLayer) // *INDENT-OFF* // clang-format off -DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching data type input/weights TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Mismatching input feature maps TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32, 0), // Unsupported kernel width @@ -144,10 +152,15 @@ DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip( PadStrideInfo(1, 1, 0, 0), PadStrideInfo(1, 1, 0, 0), })), + framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +})), framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, false })), - input_info, weights_info, biases_info, output_info, conv_info, expected) + input_info, weights_info, biases_info, output_info, conv_info, act_info, expected) { - bool is_valid = bool(NEDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info)); + bool is_valid = bool(NEDirectConvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &biases_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), conv_info, act_info)); ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS); } // clang-format on @@ -161,7 +174,8 @@ using NEDirectConvolutionLayerFixture = DirectConvolutionValidationFixture<Tenso TEST_SUITE(Float) #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC TEST_SUITE(FP16) -FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(data_f32, framework::dataset::make("DataType", DataType::F16))) +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixture<half>, framework::DatasetMode::ALL, combine(combine(data_f32, framework::dataset::make("DataType", DataType::F16)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_fp16); @@ -170,7 +184,8 @@ TEST_SUITE_END() #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ TEST_SUITE(FP32) -FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(data_f32, framework::dataset::make("DataType", DataType::F32))) +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(combine(data_f32, framework::dataset::make("DataType", DataType::F32)), + ActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_fp32); @@ -181,11 +196,19 @@ TEST_SUITE_END() template <typename T> using NEDirectConvolutionLayerFixedPointFixture = DirectConvolutionValidationFixedPointFixture<Tensor, Accessor, NEDirectConvolutionLayer, T>; +const auto QuantizedActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f) +}); + TEST_SUITE(Quantized) TEST_SUITE(QS8) // We test for fixed point precision [4,6] -FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(data_qs8, framework::dataset::make("DataType", DataType::QS8)), - framework::dataset::make("FractionalBits", 4, 7))) +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(data_qs8, framework::dataset::make("DataType", DataType::QS8)), + framework::dataset::make("FractionalBits", 4, 7)), + QuantizedActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qs); @@ -194,8 +217,9 @@ TEST_SUITE_END() TEST_SUITE(QS16) // We test for fixed point precision [4,13] -FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::ALL, combine(combine(data_qs16, framework::dataset::make("DataType", DataType::QS16)), - framework::dataset::make("FractionalBits", 4, 14))) +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::ALL, combine(combine(combine(data_qs16, framework::dataset::make("DataType", DataType::QS16)), + framework::dataset::make("FractionalBits", 4, 14)), + QuantizedActivationFunctionsDataset)) { // Validate output validate(Accessor(_target), _reference, tolerance_qs); diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h index 3d073e3f79..1bcffed526 100644 --- a/tests/validation/fixtures/ConvolutionLayerFixture.h +++ b/tests/validation/fixtures/ConvolutionLayerFixture.h @@ -33,6 +33,7 @@ #include "tests/framework/Asserts.h" #include "tests/framework/Fixture.h" #include "tests/validation/Helpers.h" +#include "tests/validation/reference/ActivationLayer.h" #include "tests/validation/reference/ConvolutionLayer.h" #include "tests/validation/reference/Utils.h" @@ -55,7 +56,7 @@ public: public: template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, - DataType data_type, int fractional_bits, QuantizationInfo quantization_info) + DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info) { _data_type = data_type; _is_quantized = is_data_type_quantized_asymmetric(data_type); @@ -63,8 +64,8 @@ public: _fractional_bits = fractional_bits; _quantization_info = quantization_info; - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, reshape_weights, dilation); - _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, dilation); + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, reshape_weights, dilation, act_info); + _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, dilation, act_info); } protected: @@ -98,7 +99,7 @@ protected: } TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, - bool reshape_weights, const Size2D &dilation) + bool reshape_weights, const Size2D &dilation, const ActivationLayerInfo act_info) { const bool is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && _data_type == DataType::F32; @@ -140,7 +141,7 @@ protected: // Create and configure function FunctionType conv; - conv.configure(&src, &weights, &bias, &dst, info, weights_info, dilation); + conv.configure(&src, &weights, &bias, &dst, info, weights_info, dilation, act_info); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); @@ -210,7 +211,7 @@ protected: } SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, - const Size2D &dilation) + const Size2D &dilation, const ActivationLayerInfo act_info) { // Create reference SimpleTensor<T> src{ input_shape, _data_type, 1, _fractional_bits, _quantization_info }; @@ -222,7 +223,9 @@ protected: fill(weights, 1); fill(bias, 2); - return reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation); + return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation), + act_info) : + reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation); } TensorType _target{}; @@ -283,10 +286,12 @@ class ConvolutionValidationFixture : public ConvolutionValidationGenericFixture< { public: template <typename...> - void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type) + void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type, + ActivationLayerInfo act_info) { ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights, data_type, 0, - QuantizationInfo()); + QuantizationInfo(), + act_info); } }; @@ -296,10 +301,11 @@ class ConvolutionValidationFixedPointFixture : public ConvolutionValidationGener public: template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type, - int fractional_bits) + int fractional_bits, + ActivationLayerInfo act_info) { ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights, data_type, fractional_bits, - QuantizationInfo()); + QuantizationInfo(), act_info); } }; @@ -309,10 +315,10 @@ class ConvolutionValidationQuantizedFixture : public ConvolutionValidationGeneri public: template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type, - QuantizationInfo quantization_info) + QuantizationInfo quantization_info, ActivationLayerInfo act_info) { ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights, data_type, 0, - quantization_info); + quantization_info, act_info); } }; } // namespace validation diff --git a/tests/validation/fixtures/DirectConvolutionLayerFixture.h b/tests/validation/fixtures/DirectConvolutionLayerFixture.h index fef9d2dc6e..ef7721dd5e 100644 --- a/tests/validation/fixtures/DirectConvolutionLayerFixture.h +++ b/tests/validation/fixtures/DirectConvolutionLayerFixture.h @@ -49,7 +49,7 @@ public: public: template <typename...> void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, - DataType data_type, int fractional_bits, QuantizationInfo quantization_info) + DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info) { _fractional_bits = fractional_bits; _quantization_info = quantization_info; @@ -61,13 +61,13 @@ public: const TensorShape output_shape = get_output_shape(input_shape, weights_shape, info); const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info); - _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info); + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info); + _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info); } template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, - DataType data_type, int fractional_bits, QuantizationInfo quantization_info) + DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info) { ARM_COMPUTE_UNUSED(dilation); @@ -77,8 +77,8 @@ public: const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type; - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info); - _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info); + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info); + _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info); } protected: @@ -112,7 +112,7 @@ protected: } TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, - DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info) + DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info, ActivationLayerInfo act_info) { // Create tensors TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position, quantization_info); @@ -122,7 +122,7 @@ protected: // Create and configure function FunctionType conv; - conv.configure(&src, &weights, &bias, &dst, info); + conv.configure(&src, &weights, &bias, &dst, info, act_info); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); @@ -152,7 +152,7 @@ protected: } SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, - DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info) + DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info, ActivationLayerInfo act_info) { // Create reference SimpleTensor<T> src{ input_shape, data_type, 1, fixed_point_position, quantization_info }; @@ -164,7 +164,9 @@ protected: fill(weights, 1); fill(bias, 2); - return reference::convolution_layer<T>(src, weights, bias, output_shape, info); + return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info), + act_info) : + reference::convolution_layer<T>(src, weights, bias, output_shape, info); } TensorType _target{}; @@ -194,9 +196,10 @@ class DirectConvolutionValidationFixture : public DirectConvolutionValidationGen { public: template <typename...> - void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type) + void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, ActivationLayerInfo act_info) { - DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, QuantizationInfo()); + DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, QuantizationInfo(), + act_info); } }; @@ -205,10 +208,11 @@ class DirectConvolutionValidationFixedPointFixture : public DirectConvolutionVal { public: template <typename...> - void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, int fractional_bits) + void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, int fractional_bits, + ActivationLayerInfo act_info) { DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, fractional_bits, - QuantizationInfo()); + QuantizationInfo(), act_info); } }; @@ -217,9 +221,11 @@ class DirectConvolutionValidationQuantizedFixture : public DirectConvolutionVali { public: template <typename...> - void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, QuantizationInfo quantization_info) + void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, QuantizationInfo quantization_info, + ActivationLayerInfo act_info) { - DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, quantization_info); + DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, quantization_info, + act_info); } }; @@ -229,9 +235,10 @@ class DirectConvolutionValidationWithTensorShapesQuantizedFixture : public Direc public: template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, - DataType data_type, QuantizationInfo quantization_info) + DataType data_type, QuantizationInfo quantization_info, ActivationLayerInfo act_info) { - DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, quantization_info); + DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, quantization_info, + act_info); } }; @@ -241,9 +248,10 @@ class DirectConvolutionValidationWithTensorShapesFixture : public DirectConvolut public: template <typename...> void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, - DataType data_type) + DataType data_type, ActivationLayerInfo act_info) { - DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, QuantizationInfo()); + DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, QuantizationInfo(), + act_info); } }; diff --git a/tests/validation/fixtures/WinogradLayerFixture.h b/tests/validation/fixtures/WinogradLayerFixture.h index a86f24f35e..5210cbf720 100644 --- a/tests/validation/fixtures/WinogradLayerFixture.h +++ b/tests/validation/fixtures/WinogradLayerFixture.h @@ -33,6 +33,7 @@ #include "tests/framework/Asserts.h" #include "tests/framework/Fixture.h" #include "tests/validation/Helpers.h" +#include "tests/validation/reference/ActivationLayer.h" #include "tests/validation/reference/ConvolutionLayer.h" #include "tests/validation/reference/Utils.h" #include "tests/validation/reference/Winograd.h" @@ -52,12 +53,12 @@ class WinogradConvolutionLayerValidationFixture : public framework::Fixture { public: template <typename...> - void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, DataType data_type) + void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, DataType data_type, ActivationLayerInfo act_info) { ARM_COMPUTE_UNUSED(dilation); - _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type); - _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type); + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, act_info); + _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, act_info); } protected: @@ -82,7 +83,7 @@ protected: } TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, - DataType data_type) + DataType data_type, ActivationLayerInfo act_info) { // Create tensors TensorType src = create_tensor<TensorType>(input_shape, data_type, 1); @@ -92,7 +93,7 @@ protected: // Create and configure function FunctionType conv; - conv.configure(&src, &weights, &bias, &dst, info); + conv.configure(&src, &weights, &bias, &dst, info, act_info); ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS); @@ -122,7 +123,7 @@ protected: } SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, - DataType data_type) + DataType data_type, ActivationLayerInfo act_info) { // Create reference SimpleTensor<T> src{ input_shape, data_type, 1 }; @@ -134,7 +135,8 @@ protected: fill(weights, 1, -1.f, 1.f); fill(bias, 2, -1.f, 1.f); - return reference::convolution_layer<T>(src, weights, bias, output_shape, info); + return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info), act_info) : reference::convolution_layer<T>(src, weights, bias, + output_shape, info); } TensorType _target{}; |