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-rw-r--r--tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp131
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diff --git a/tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp b/tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp
deleted file mode 100644
index c79e0156cf..0000000000
--- a/tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp
+++ /dev/null
@@ -1,131 +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/GLES_COMPUTE/GCTensor.h"
-#include "arm_compute/runtime/GLES_COMPUTE/GCTensorAllocator.h"
-#include "arm_compute/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.h"
-#include "tests/GLES_COMPUTE/GCAccessor.h"
-#include "tests/benchmark/fixtures/ConvolutionLayerFixture.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/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
-{
-const auto data_types = framework::dataset::make("DataType", { DataType::F16 });
-} // namespace
-
-using GCConvolutionLayerFixture = ConvolutionLayerFixture<GCTensor, GCConvolutionLayer, GCAccessor>;
-
-TEST_SUITE(GC)
-
-REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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(AlexNetConvolutionLayer, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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 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(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(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