COMPMID-415: Port benchmark tests and remove google benchmark

Change-Id: I2f17720a4e974b2cc4481f2884d9f351e8f78b5f
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/79776
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 0 insertions, 302 deletions

diff --git a/tests/benchmark/NEON/ConvolutionLayer.cpp b/tests/benchmark/NEON/ConvolutionLayer.cpp
deleted file mode 100644
index a0b1236177..0000000000
--- a/tests/benchmark/NEON/ConvolutionLayer.cpp
+++ /dev/null
@@ -1,302 +0,0 @@
-/*
- * 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 "Globals.h"
-#include "NEON/NEAccessor.h"
-#include "TensorLibrary.h"
-#include "benchmark/Datasets.h"
-#include "benchmark/Profiler.h"
-#include "benchmark/WallClockTimer.h"
-
-#include "arm_compute/core/Helpers.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 "benchmark/benchmark_api.h"
-
-using namespace arm_compute;
-using namespace arm_compute::test;
-using namespace arm_compute::test::benchmark;
-using namespace arm_compute::test::neon;
-
-#include "benchmark/common/ConvolutionLayer.h"
-
-namespace
-{
-using ConvolutionLayerAlexNetF32 = ConvolutionLayer<AlexNetConvolutionLayerDataset, Tensor, NEAccessor, NEConvolutionLayer>;
-using ConvolutionLayerAlexNetQS8 = ConvolutionLayer<AlexNetConvolutionLayerDataset, Tensor, NEAccessor, NEConvolutionLayer, DataType::QS8>;
-using ConvolutionLayerLeNet5     = ConvolutionLayer<LeNet5ConvolutionLayerDataset, Tensor, NEAccessor, NEConvolutionLayer>;
-using ConvolutionLayerGoogLeNet1 = ConvolutionLayer<GoogLeNetConvolutionLayerDataset1, Tensor, NEAccessor, NEConvolutionLayer>;
-using ConvolutionLayerGoogLeNet2 = ConvolutionLayer<GoogLeNetConvolutionLayerDataset2, Tensor, NEAccessor, NEConvolutionLayer>;
-} // namespace
-
-// F32
-BENCHMARK_DEFINE_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetF32, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 4, 1, 4, 8>);
-
-// QS8
-BENCHMARK_DEFINE_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerAlexNetQS8, neon_alexnet)
-->Threads(1)
-->Apply(DataSetArgBatched<AlexNetConvolutionLayerDataset, 4, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(ConvolutionLayerLeNet5, neon_lenet5)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ConvolutionLayerLeNet5, neon_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5ConvolutionLayerDataset, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerLeNet5, neon_lenet5)
-->Threads(1)
-->Apply(DataSetArgBatched<LeNet5ConvolutionLayerDataset, 1, 1, 4, 8>);
-
-BENCHMARK_DEFINE_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_DEFINE_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-(::benchmark::State &state)
-{
-    while(state.KeepRunning())
-    {
-        // Run function
-        profiler.start();
-        conv_layer->run();
-        profiler.stop();
-    }
-}
-
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 4, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 5, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 6, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 7, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 8, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 9, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 10, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 11, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 12, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 13, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 14, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 15, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 16, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 17, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 18, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 19, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 20, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 21, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 22, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 23, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 24, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 25, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 26, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 27, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 28, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 29, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 30, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet1, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset1, 31, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 0, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 1, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 2, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 3, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 4, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 5, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 6, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 7, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 8, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 9, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 10, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 11, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 12, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 13, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 14, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 15, 1, 4, 8>);
-BENCHMARK_REGISTER_F(ConvolutionLayerGoogLeNet2, neon_googlenet)
-->Threads(1)
-->Apply(DataSetArgBatched<GoogLeNetConvolutionLayerDataset2, 16, 1, 4, 8>);