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117 lines
3.6 KiB
C++
117 lines
3.6 KiB
C++
/*
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* Copyright (c) 2025 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/core/Types.h"
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#include "arm_compute/runtime/NEON/NEFunctions.h"
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#include "utils/Utils.h"
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using namespace arm_compute;
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using namespace utils;
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class NEMatMulExample : public Example
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{
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public:
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bool do_setup(int argc, char **argv) override
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{
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size_t m = 4096;
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size_t n = 4096;
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size_t k = 128;
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if (argc == 4)
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{
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try
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{
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m = std::stoul(argv[1]);
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n = std::stoul(argv[2]);
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k = std::stoul(argv[3]);
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}
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catch (const std::exception &e)
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{
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ARM_COMPUTE_ERROR(e.what());
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return false;
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}
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}
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else if (argc != 1)
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{
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ARM_COMPUTE_ERROR("Invalid number of arguments. Usage:\n"
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"<M> <N> <K>\n");
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return false;
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}
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const TensorInfo a_info{TensorShape{k, m}, 1, DataType::F32, DataLayout::NHWC};
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const TensorInfo b_info{TensorShape{n, k}, 1, DataType::F32, DataLayout::NHWC};
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const TensorInfo output_info{TensorShape{n, m}, 1, DataType::F32, DataLayout::NHWC};
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a.allocator()->init(a_info);
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b.allocator()->init(b_info);
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output.allocator()->init(output_info);
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a.info()->set_are_values_constant(false);
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b.info()->set_are_values_constant(false);
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output.info()->set_are_values_constant(false);
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const MatMulInfo info;
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const CpuMatMulSettings settings;
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auto status = NEMatMul::validate(a.info(), b.info(), output.info(), info, settings);
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if (status.error_code() != ErrorCode::OK)
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{
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ARM_COMPUTE_ERROR(status.error_description().c_str());
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return false;
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}
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matmul.configure(&a, &b, &output, info, settings);
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a.allocator()->allocate();
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b.allocator()->allocate();
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output.allocator()->allocate();
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// Fill with fixed values
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const std::vector<float> values_a(m * k, 2.2f);
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const std::vector<float> values_b(n * k, 3.5f);
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fill_tensor_vector(a, values_a);
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fill_tensor_vector(b, values_b);
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return true;
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}
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void do_run() override
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{
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matmul.run();
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}
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private:
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NEMatMul matmul{};
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Tensor a{}, b{}, output{};
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};
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/** Main program for MatMul test
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*
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* @param[in] argc Number of arguments
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* @param[in] argv Arguments (M, N, K)
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*/
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int main(int argc, char **argv)
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{
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return utils::run_example<NEMatMulExample>(argc, argv);
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}
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