aboutsummaryrefslogtreecommitdiff
path: root/tests/benchmark/NEON/ConvolutionLayer.cpp
diff options
context:
space:
mode:
Diffstat (limited to 'tests/benchmark/NEON/ConvolutionLayer.cpp')
-rw-r--r--tests/benchmark/NEON/ConvolutionLayer.cpp213
1 files changed, 0 insertions, 213 deletions
diff --git a/tests/benchmark/NEON/ConvolutionLayer.cpp b/tests/benchmark/NEON/ConvolutionLayer.cpp
deleted file mode 100644
index 2ae893bdec..0000000000
--- a/tests/benchmark/NEON/ConvolutionLayer.cpp
+++ /dev/null
@@ -1,213 +0,0 @@
-/*
- * Copyright (c) 2017-2019 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#include "arm_compute/core/TensorShape.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h"
-#include "arm_compute/runtime/NEON/functions/NEFFTConvolutionLayer.h"
-#include "arm_compute/runtime/NEON/functions/NEWinogradConvolutionLayer.h"
-#include "arm_compute/runtime/Tensor.h"
-#include "arm_compute/runtime/TensorAllocator.h"
-#include "tests/NEON/Accessor.h"
-#include "tests/benchmark/fixtures/ConvolutionLayerFixture.h"
-#include "tests/benchmark/fixtures/FFTConvolutionLayerFixture.h"
-#include "tests/benchmark/fixtures/WinogradConvolutionLayerFixture.h"
-#include "tests/datasets/SmallConvolutionLayerDataset.h"
-#include "tests/datasets/system_tests/alexnet/AlexNetConvolutionLayerDataset.h"
-#include "tests/datasets/system_tests/googlenet/inceptionv1/GoogLeNetInceptionV1ConvolutionLayerDataset.h"
-#include "tests/datasets/system_tests/googlenet/inceptionv4/GoogLeNetInceptionV4ConvolutionLayerDataset.h"
-#include "tests/datasets/system_tests/lenet5/LeNet5ConvolutionLayerDataset.h"
-#include "tests/datasets/system_tests/mobilenet/MobileNetConvolutionLayerDataset.h"
-#include "tests/datasets/system_tests/resnet12/ResNet12ConvolutionLayerDataset.h"
-#include "tests/datasets/system_tests/squeezenet/SqueezeNetConvolutionLayerDataset.h"
-#include "tests/datasets/system_tests/vgg/vgg16/VGG16ConvolutionLayerDataset.h"
-#include "tests/datasets/system_tests/yolo/v2/YOLOV2ConvolutionLayerDataset.h"
-#include "tests/framework/Macros.h"
-#include "tests/framework/datasets/Datasets.h"
-#include "utils/TypePrinter.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-namespace
-{
-#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-const auto data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32, DataType::QASYMM8 });
-#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
-const auto data_types = framework::dataset::make("DataType", { DataType::F32, DataType::QASYMM8 });
-
-#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
-} // namespace
-
-using NEGEMMConvolutionLayerFixture = ConvolutionLayerFixture<Tensor, NEGEMMConvolutionLayer, Accessor>;
-using NEFFTConvolutionLayerFixture = FFTConvolutionLayerFixture<Tensor, NEFFTConvolutionLayer, Accessor>;
-
-TEST_SUITE(NEON)
-#if defined(__aarch64__)
-using NEWinogradConvolutionLayerFixture = WinogradConvolutionLayerFixture<Tensor, NEWinogradConvolutionLayer, Accessor>;
-
-REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetWinogradLayer, NEWinogradConvolutionLayerFixture, framework::DatasetMode::ALL,
- framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetWinogradLayerDataset(),
- framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
- framework::dataset::make("DataType", DataType::F32)),
- framework::dataset::make("Batches", 1)));
-
-REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1WinogradLayer, NEWinogradConvolutionLayerFixture, framework::DatasetMode::ALL,
- framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1WinogradLayerDataset(),
- framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
- framework::dataset::make("DataType", DataType::F32)),
- framework::dataset::make("Batches", 1)));
-
-REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4WinogradLayer, NEWinogradConvolutionLayerFixture, framework::DatasetMode::ALL,
- framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4WinogradLayerDataset(),
- framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
- framework::dataset::make("DataType", DataType::F32)),
- framework::dataset::make("Batches", 1)));
-
-REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetWinogradLayer, NEWinogradConvolutionLayerFixture, framework::DatasetMode::ALL,
- framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetWinogradLayerDataset(),
- framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
- framework::dataset::make("DataType", DataType::F32)),
- framework::dataset::make("Batches", 1)));
-#endif /* __aarch64__ */
-
-REGISTER_FIXTURE_DATA_TEST_CASE(ResNet12FFTLayer, NEFFTConvolutionLayerFixture, framework::DatasetMode::ALL,
- framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::ResNet12FFTConvolutionLayerDataset(),
- framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
- framework::dataset::make("DataType", { DataType::F32 })),
- framework::dataset::make("Batches", 1)));
-
-REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, NEGEMMConvolutionLayerFixture, framework::DatasetMode::ALL,
- 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(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(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(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(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(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(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(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(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(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(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(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(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, NEWinogradConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
- framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::AlexNetWinogradLayerDataset(),
- framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
- framework::dataset::make("DataType", DataType::F32)),
- framework::dataset::make("Batches", { 4, 8 })));
-
-REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1WinogradLayer, NEWinogradConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
- framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1WinogradLayerDataset(),
- framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
- framework::dataset::make("DataType", DataType::F32)),
- framework::dataset::make("Batches", { 4, 8 })));
-
-REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4WinogradLayer, NEWinogradConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
- framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4WinogradLayerDataset(),
- framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
- framework::dataset::make("DataType", DataType::F32)),
- framework::dataset::make("Batches", { 4, 8 })));
-
-REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetWinogradLayer, NEWinogradConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
- framework::dataset::combine(framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetWinogradLayerDataset(),
- framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))),
- framework::dataset::make("DataType", DataType::F32)),
- framework::dataset::make("Batches", { 4, 8 })));
-#endif /* __aarch64__ */
-
-TEST_SUITE_END()
-TEST_SUITE_END()
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-30 04:51:10 +0000