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Diffstat (limited to 'tests/benchmark/NEON/DirectConvolutionLayer.cpp')
| -rw-r--r-- | tests/benchmark/NEON/DirectConvolutionLayer.cpp | 127 |
1 files changed, 0 insertions, 127 deletions
diff --git a/tests/benchmark/NEON/DirectConvolutionLayer.cpp b/tests/benchmark/NEON/DirectConvolutionLayer.cpp deleted file mode 100644 index f94ef6be19..0000000000 --- a/tests/benchmark/NEON/DirectConvolutionLayer.cpp +++ /dev/null @@ -1,127 +0,0 @@ -/* - * Copyright (c) 2017-2018 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/NEDirectConvolutionLayer.h" -#include "arm_compute/runtime/Tensor.h" -#include "arm_compute/runtime/TensorAllocator.h" -#include "tests/NEON/Accessor.h" -#include "tests/benchmark/fixtures/DirectConvolutionLayerFixture.h" -#include "tests/datasets/DirectConvolutionLayerDataset.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/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 -{ -// Special data types for networks that need 5x5 direct convolution -#ifdef ARM_COMPUTE_ENABLE_F16 -const auto data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32 }); -#else /* ARM_COMPUTE_ENABLE_F16 */ -const auto data_types = framework::dataset::make("DataType", { DataType::F32 }); -#endif /* ARM_COMPUTE_ENABLE_F16 */ -} // namespace - -using NEDirectConvolutionLayerFixture = DirectConvolutionLayerFixture<Tensor, NEDirectConvolutionLayer, Accessor>; - -TEST_SUITE(NEON) - -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, 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, 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, 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, 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, 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, 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, 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, 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, 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() -TEST_SUITE_END() -} // namespace benchmark -} // namespace test -} // namespace arm_compute |