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/*
* Copyright (c) 2022 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/runtime/RuntimeContext.h"
#include "tests/CL/CLAccessor.h"
#include "tests/framework/Macros.h"
#include "tests/framework/ParametersLibrary.h"
#include "tests/validation/Validation.h"
#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
#include "arm_compute/runtime/CL/functions/CLPixelWiseMultiplication.h"
#include "tests/validation/reference/ActivationLayer.h"
#include "tests/validation/reference/PixelWiseMultiplication.h"
#include <thread>
namespace arm_compute
{
namespace test
{
namespace validation
{
TEST_SUITE(CL)
TEST_SUITE(UNIT)
TEST_SUITE(RuntimeContext)
// This test tries scheduling work concurrently from two independent threads
TEST_CASE(MultipleThreadedScheduller, framework::DatasetMode::ALL)
{
constexpr auto num_threads(16u);
std::array<CLActivationLayer, num_threads> func{};
std::array<CLPixelWiseMultiplication, num_threads> pmul{};
std::array<CLTensor, num_threads> s0{};
std::array<CLTensor, num_threads> s1{};
std::array<CLTensor, num_threads> st{};
std::array<CLTensor, num_threads> dt{};
const TensorShape tensor_shape(128u, 4u, 5u);
const ActivationLayerInfo ainfo(ActivationLayerInfo::ActivationFunction::LOGISTIC, 0.5f, 1.f);
std::array<std::thread, num_threads> threads;
auto ctx = parameters->get_ctx<CLTensor>();
for(auto i = 0u; i < num_threads; ++i)
{
s0[i] = create_tensor<CLTensor>(tensor_shape, DataType::F32, 1);
s1[i] = create_tensor<CLTensor>(tensor_shape, DataType::F32, 1);
st[i] = create_tensor<CLTensor>(tensor_shape, DataType::F32, 1);
dt[i] = create_tensor<CLTensor>(tensor_shape, DataType::F32, 1);
func[i] = CLActivationLayer(ctx);
pmul[i] = CLPixelWiseMultiplication();
threads[i] =
std::thread([&,i]
{
auto &s = st[i];
auto &t = dt[i];
auto &p0 = s0[i];
auto &p1 = s1[i];
pmul[i].configure(&p0, &p1, &s, 1.f, ConvertPolicy::WRAP, RoundingPolicy::TO_NEAREST_UP);
func[i].configure(&s, &t, ainfo);
s.allocator()->allocate();
t.allocator()->allocate();
p0.allocator()->allocate();
p1.allocator()->allocate();
library->fill_tensor_uniform(CLAccessor(p0), 0, -1.f, 1.f);
library->fill_tensor_uniform(CLAccessor(p1), 0, -1.f, 1.f);
pmul[i].run();
func[i].run();
});
}
for(auto &t : threads)
{
t.join();
}
SimpleTensor<float> rs{ tensor_shape, DataType::F32, 1 };
SimpleTensor<float> ra{ tensor_shape, DataType::F32, 1 };
SimpleTensor<float> rb{ tensor_shape, DataType::F32, 1 };
library->fill_tensor_uniform(ra, 0, -1.f, 1.f);
library->fill_tensor_uniform(rb, 0, -1.f, 1.f);
const auto mul = reference::pixel_wise_multiplication<float, float, float>(ra, rb, 1.f, ConvertPolicy::WRAP, RoundingPolicy::TO_NEAREST_UP, DataType::F32);
const auto golden = reference::activation_layer<float>(mul, ainfo);
for(auto &d : dt)
{
validate(CLAccessor(d), golden);
}
}
TEST_SUITE_END() // MultipleThreadedScheduller
TEST_SUITE_END() // UNIT
TEST_SUITE_END() // CL
} // namespace validation
} // namespace test
} // namespace arm_compute
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