| /* |
| * Copyright (c) 2017-2020 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. |
| */ |
| #ifndef ARM_COMPUTE_CL /* Needed by Utils.cpp to handle OpenCL exceptions properly */ |
| #error "This example needs to be built with -DARM_COMPUTE_CL" |
| #endif /* ARM_COMPUTE_CL */ |
| |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/runtime/CL/CLScheduler.h" |
| #include "arm_compute/runtime/CL/CLTuner.h" |
| #include "arm_compute/runtime/CL/functions/CLGEMM.h" |
| #include "utils/Utils.h" |
| |
| #include <cstdlib> |
| |
| using namespace arm_compute; |
| using namespace utils; |
| |
| class CLSGEMMExample : public Example |
| { |
| public: |
| bool do_setup(int argc, char **argv) override |
| { |
| NPYLoader npy0; |
| NPYLoader npy1; |
| NPYLoader npy2; |
| alpha = 1.0f; |
| beta = 0.0f; |
| |
| CLScheduler::get().default_init(&tuner); |
| |
| std::ifstream stream; |
| if(argc > 1) |
| { |
| stream.open(argv[1], std::fstream::in); |
| } |
| |
| if(argc < 3 || (argc < 4 && stream.bad())) |
| { |
| // Print help |
| std::cout << "Usage: 1) ./build/cl_sgemm input_matrix_1.npy input_matrix_2.npy [input_matrix_3.npy] [alpha = 1] [beta = 0]\n"; |
| std::cout << " 2) ./build/cl_sgemm M N K [alpha = 1.0f] [beta = 0.0f]\n\n"; |
| std::cout << "Too few or no input_matrices provided. Using M=7, N=3, K=5, alpha=1.0f and beta=0.0f\n\n"; |
| |
| src0.allocator()->init(TensorInfo(TensorShape(5U, 7U), 1, DataType::F32)); |
| src1.allocator()->init(TensorInfo(TensorShape(3U, 5U), 1, DataType::F32)); |
| src2.allocator()->init(TensorInfo(TensorShape(3U, 7U), 1, DataType::F32)); |
| } |
| else |
| { |
| if(stream.good()) /* case file1.npy file2.npy [file3.npy] [alpha = 1.0f] [beta = 0.0f] */ |
| { |
| npy0.open(argv[1]); |
| npy0.init_tensor(src0, DataType::F32); |
| npy1.open(argv[2]); |
| npy1.init_tensor(src1, DataType::F32); |
| |
| if(argc > 3) |
| { |
| stream.close(); |
| stream.clear(); |
| stream.open(argv[3], std::fstream::in); |
| if(stream.good()) /* case with third file */ |
| { |
| npy2.open(argv[3]); |
| npy2.init_tensor(src2, DataType::F32); |
| |
| if(argc > 4) |
| { |
| // Convert string to float |
| alpha = strtof(argv[4], nullptr); |
| |
| if(argc > 5) |
| { |
| // Convert string to float |
| beta = strtof(argv[5], nullptr); |
| } |
| } |
| } |
| else /* case without third file */ |
| { |
| alpha = strtof(argv[3], nullptr); |
| |
| if(argc > 4) |
| { |
| beta = strtof(argv[4], nullptr); |
| } |
| } |
| } |
| } |
| else /* case M N K [alpha = 1.0f] [beta = 0.0f] */ |
| { |
| size_t M = strtol(argv[1], nullptr, 10); |
| size_t N = strtol(argv[2], nullptr, 10); |
| size_t K = strtol(argv[3], nullptr, 10); |
| |
| src0.allocator()->init(TensorInfo(TensorShape(K, M), 1, DataType::F32)); |
| src1.allocator()->init(TensorInfo(TensorShape(N, K), 1, DataType::F32)); |
| src2.allocator()->init(TensorInfo(TensorShape(N, M), 1, DataType::F32)); |
| |
| if(argc > 4) |
| { |
| alpha = strtof(argv[4], nullptr); |
| |
| if(argc > 5) |
| { |
| beta = strtof(argv[5], nullptr); |
| } |
| } |
| } |
| } |
| |
| init_sgemm_output(dst, src0, src1, DataType::F32); |
| |
| // Configure function |
| sgemm.configure(&src0, &src1, (src2.info()->total_size() > 0) ? &src2 : nullptr, &dst, alpha, beta); |
| |
| // Allocate all the images |
| src0.allocator()->allocate(); |
| src1.allocator()->allocate(); |
| dst.allocator()->allocate(); |
| |
| // Fill the input images with either the data provided or random data |
| if(npy0.is_open()) |
| { |
| npy0.fill_tensor(src0); |
| npy1.fill_tensor(src1); |
| |
| output_filename = "sgemm_out.npy"; |
| is_fortran = npy0.is_fortran(); |
| |
| if(npy2.is_open()) |
| { |
| src2.allocator()->allocate(); |
| npy2.fill_tensor(src2); |
| } |
| } |
| else |
| { |
| src2.allocator()->allocate(); |
| |
| fill_random_tensor(src0, -1.f, 1.f); |
| fill_random_tensor(src1, -1.f, 1.f); |
| fill_random_tensor(src2, -1.f, 1.f); |
| } |
| |
| // Dummy run for CLTuner |
| sgemm.run(); |
| |
| return true; |
| } |
| void do_run() override |
| { |
| // Execute the function |
| sgemm.run(); |
| |
| // Make sure all the OpenCL jobs are done executing: |
| CLScheduler::get().sync(); |
| } |
| void do_teardown() override |
| { |
| if(!output_filename.empty()) /* Save to .npy file */ |
| { |
| save_to_npy(dst, output_filename, is_fortran); |
| } |
| } |
| |
| private: |
| CLTensor src0{}; |
| CLTensor src1{}; |
| CLTensor src2{}; |
| CLTensor dst{}; |
| CLGEMM sgemm{}; |
| CLTuner tuner{}; |
| float alpha{}, beta{}; |
| bool is_fortran{}; |
| std::string output_filename{}; |
| }; |
| |
| /** Main program for sgemm test |
| * |
| * @param[in] argc Number of arguments |
| * @param[in] argv Arguments ( [optional] Matrix A, [optional] Matrix B, [optional] Matrix C, [optional] alpha, [optional] beta ) |
| */ |
| int main(int argc, char **argv) |
| { |
| return utils::run_example<CLSGEMMExample>(argc, argv); |
| } |