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114 lines
4.4 KiB
114 lines
4.4 KiB
/*
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* Copyright (c) 2022 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#include "arm_compute/runtime/RuntimeContext.h"
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#include "tests/CL/CLAccessor.h"
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#include "tests/framework/Macros.h"
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#include "tests/framework/ParametersLibrary.h"
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#include "tests/validation/Validation.h"
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#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
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#include "arm_compute/runtime/CL/functions/CLPixelWiseMultiplication.h"
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#include "tests/validation/reference/ActivationLayer.h"
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#include "tests/validation/reference/PixelWiseMultiplication.h"
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#include <thread>
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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TEST_SUITE(CL)
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TEST_SUITE(UNIT)
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TEST_SUITE(RuntimeContext)
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// This test tries scheduling work concurrently from two independent threads
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TEST_CASE(MultipleThreadedScheduller, framework::DatasetMode::ALL)
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{
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constexpr auto num_threads(16u);
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std::array<CLActivationLayer, num_threads> func{};
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std::array<CLPixelWiseMultiplication, num_threads> pmul{};
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std::array<CLTensor, num_threads> s0{};
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std::array<CLTensor, num_threads> s1{};
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std::array<CLTensor, num_threads> st{};
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std::array<CLTensor, num_threads> dt{};
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const TensorShape tensor_shape(128u, 4u, 5u);
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const ActivationLayerInfo ainfo(ActivationLayerInfo::ActivationFunction::LOGISTIC, 0.5f, 1.f);
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std::array<std::thread, num_threads> threads;
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auto ctx = parameters->get_ctx<CLTensor>();
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for(auto i = 0u; i < num_threads; ++i)
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{
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s0[i] = create_tensor<CLTensor>(tensor_shape, DataType::F32, 1);
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s1[i] = create_tensor<CLTensor>(tensor_shape, DataType::F32, 1);
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st[i] = create_tensor<CLTensor>(tensor_shape, DataType::F32, 1);
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dt[i] = create_tensor<CLTensor>(tensor_shape, DataType::F32, 1);
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func[i] = CLActivationLayer(ctx);
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pmul[i] = CLPixelWiseMultiplication();
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threads[i] =
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std::thread([&,i]
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{
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auto &s = st[i];
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auto &t = dt[i];
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auto &p0 = s0[i];
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auto &p1 = s1[i];
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pmul[i].configure(&p0, &p1, &s, 1.f, ConvertPolicy::WRAP, RoundingPolicy::TO_NEAREST_UP);
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func[i].configure(&s, &t, ainfo);
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s.allocator()->allocate();
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t.allocator()->allocate();
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p0.allocator()->allocate();
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p1.allocator()->allocate();
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library->fill_tensor_uniform(CLAccessor(p0), 0, -1.f, 1.f);
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library->fill_tensor_uniform(CLAccessor(p1), 0, -1.f, 1.f);
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pmul[i].run();
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func[i].run();
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});
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}
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for(auto &t : threads)
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{
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t.join();
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}
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SimpleTensor<float> rs{ tensor_shape, DataType::F32, 1 };
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SimpleTensor<float> ra{ tensor_shape, DataType::F32, 1 };
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SimpleTensor<float> rb{ tensor_shape, DataType::F32, 1 };
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library->fill_tensor_uniform(ra, 0, -1.f, 1.f);
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library->fill_tensor_uniform(rb, 0, -1.f, 1.f);
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const auto mul = reference::pixel_wise_multiplication<float, float, float>(ra, rb, 1.f, ConvertPolicy::WRAP, RoundingPolicy::TO_NEAREST_UP, DataType::F32);
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const auto golden = reference::activation_layer<float>(mul, ainfo);
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for(auto &d : dt)
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{
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validate(CLAccessor(d), golden);
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}
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}
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TEST_SUITE_END() // MultipleThreadedScheduller
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TEST_SUITE_END() // UNIT
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TEST_SUITE_END() // CL
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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