COMPMID-415: Rename and move tests

The boost validation is now "standalone" in validation_old and builds as
arm_compute_validation_old. The new validation builds now as
arm_compute_validation.

Change-Id: Ib93ba848a25680ac60afb92b461d574a0757150d
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/86187
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 111 insertions, 0 deletions

diff --git a/tests/benchmark/NEON/ConvolutionLayer.cpp b/tests/benchmark/NEON/ConvolutionLayer.cpp
new file mode 100644
index 0000000000..ba682825f1
--- /dev/null
+++ b/tests/benchmark/NEON/ConvolutionLayer.cpp
@@ -0,0 +1,111 @@
+/*
+ * Copyright (c) 2017 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/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+#include "tests/NEON/Accessor.h"
+#include "tests/TypePrinter.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"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace
+{
+#ifdef ARM_COMPUTE_ENABLE_FP16
+const auto data_types = framework::dataset::make("DataType", { DataType::F16, DataType::F32, DataType::QS8, DataType::QS16 });
+#else  /* ARM_COMPUTE_ENABLE_FP16 */
+const auto data_types = framework::dataset::make("DataType", { DataType::F32, DataType::QS8, DataType::QS16 });
+#endif /* ARM_COMPUTE_ENABLE_FP16 */
+} // namespace
+
+using NEConvolutionLayerFixture = ConvolutionLayerFixture<Tensor, NEConvolutionLayer, Accessor>;
+
+TEST_SUITE(NEON)
+
+REGISTER_FIXTURE_DATA_TEST_CASE(AlexNetConvolutionLayer, NEConvolutionLayerFixture, 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,
+                                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,
+                                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,
+                                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,
+                                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,
+                                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,
+                                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,
+                                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,
+                                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,
+                                framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(), data_types),
+                                                            framework::dataset::make("Batches", { 4, 8 })));
+
+REGISTER_FIXTURE_DATA_TEST_CASE(VGG16ConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
+                                framework::dataset::combine(framework::dataset::combine(datasets::VGG16ConvolutionLayerDataset(), data_types),
+                                                            framework::dataset::make("Batches", { 1, 4, 8 })));
+
+REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2ConvolutionLayer, NEConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
+                                framework::dataset::combine(framework::dataset::combine(datasets::YOLOV2ConvolutionLayerDataset(), data_types),
+                                                            framework::dataset::make("Batches", { 1, 4, 8 })));
+
+TEST_SUITE_END()
+TEST_SUITE_END()
+} // namespace test
+} // namespace arm_compute