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authorStephen Li <stephen.li@arm.com>2018-01-04 14:13:22 +0800
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:43:42 +0000
commite855c237a5b61c4ed5a5ab79dd4af27385cf72f5 (patch)
treeeb81a77c6c588c8d25937c27249552524791b4d0 /tests/benchmark/GLES_COMPUTE
parent81ce008ebbc6dc19b22034794d12124b58ee334b (diff)
downloadComputeLibrary-e855c237a5b61c4ed5a5ab79dd4af27385cf72f5.tar.gz
APPBROWSER-377: GCConvoutionLayer support for FP16
Change-Id: I801b5e393a16a9f92c062826e6fcfd5982ca7bb3 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/116584 Tested-by: Jenkins <bsgcomp@arm.com> Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'tests/benchmark/GLES_COMPUTE')
-rw-r--r--tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp119
1 files changed, 119 insertions, 0 deletions
diff --git a/tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp b/tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp
new file mode 100644
index 0000000000..0d8edb757d
--- /dev/null
+++ b/tests/benchmark/GLES_COMPUTE/ConvolutionLayer.cpp
@@ -0,0 +1,119 @@
+/*
+ * 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
+{
+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(datasets::AlexNetConvolutionLayerDataset(),
+ data_types),
+ framework::dataset::make("Batches", 1)));
+
+REGISTER_FIXTURE_DATA_TEST_CASE(LeNet5ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL,
+ framework::dataset::combine(framework::dataset::combine(datasets::LeNet5ConvolutionLayerDataset(),
+ data_types),
+ framework::dataset::make("Batches", 1)));
+
+REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV1ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL,
+ framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV1ConvolutionLayerDataset(),
+ data_types),
+ framework::dataset::make("Batches", 1)));
+
+REGISTER_FIXTURE_DATA_TEST_CASE(GoogLeNetInceptionV4ConvolutionLayer, GCConvolutionLayerFixture, framework::DatasetMode::ALL,
+ framework::dataset::combine(framework::dataset::combine(datasets::GoogLeNetInceptionV4ConvolutionLayerDataset(),
+ data_types),
+ framework::dataset::make("Batches", 1)));
+
+REGISTER_FIXTURE_DATA_TEST_CASE(SqueezeNetConvolutionLayer, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, 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, GCConvolutionLayerFixture, framework::DatasetMode::NIGHTLY,
+ framework::dataset::combine(framework::dataset::combine(datasets::SqueezeNetConvolutionLayerDataset(),
+ 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(datasets::VGG16ConvolutionLayerDataset(),
+ data_types),
+ framework::dataset::make("Batches", { 1, 4 })));
+
+REGISTER_FIXTURE_DATA_TEST_CASE(YOLOV2ConvolutionLayer, GCConvolutionLayerFixture, 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