From 6acc6add8412c6d3841a49684610fc5a6526312e Mon Sep 17 00:00:00 2001 From: Isabella Gottardi Date: Fri, 2 Feb 2018 17:19:18 +0000 Subject: COMPMID-846: Create a ConvolutionLayer for NEON Change-Id: I98bbef40bfac5b05134be4ef9fb54d14c0c9e8e8 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118806 Tested-by: Jenkins Reviewed-by: Anthony Barbier --- tests/benchmark/NEON/ConvolutionLayer.cpp | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) (limited to 'tests/benchmark') diff --git a/tests/benchmark/NEON/ConvolutionLayer.cpp b/tests/benchmark/NEON/ConvolutionLayer.cpp index d871a6958c..1be95a50c1 100644 --- a/tests/benchmark/NEON/ConvolutionLayer.cpp +++ b/tests/benchmark/NEON/ConvolutionLayer.cpp @@ -54,7 +54,7 @@ const auto data_types = framework::dataset::make("DataType", { DataType::F32, Da #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ } // namespace -using NEConvolutionLayerFixture = ConvolutionLayerFixture; +using NEGEMMConvolutionLayerFixture = ConvolutionLayerFixture; TEST_SUITE(NEON) #if defined(__aarch64__) @@ -77,53 +77,53 @@ REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetWinogradLayer, NEWinogradLayerFixture, framework::dataset::make("Batches", 1))); #endif /* __aarch64__ */ -REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL, +REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL, +REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL, +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL, +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), data_types), framework::dataset::make("Batches", 1))); -REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::ALL, +REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL, framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), data_types), framework::dataset::make("Batches", 1))); TEST_SUITE(NIGHTLY) -REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, +REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, framework::dataset::combine(framework::dataset::combine(datasets::AlexNetConvolutionLayerDataset(), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, +REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, +REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(), data_types), framework::dataset::make("Batches", { 4, 8 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, +REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), 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, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, +REGISTER_FIXTURE_DATA_TEST_CASE(VGG16ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), data_types), framework::dataset::make("Batches", { 1, 2 }))); -REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2ConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, +REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2ConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::NIGHTLY, framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), data_types), framework::dataset::make("Batches", { 1, 4, 8 }))); 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