xref: /aosp_15_r20/external/ComputeLibrary/examples/cl_sgemm.cpp (revision c217d954acce2dbc11938adb493fc0abd69584f3)
1 /*
2  * Copyright (c) 2017-2020 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
5  *
6  * Permission is hereby granted, free of charge, to any person obtaining a copy
7  * of this software and associated documentation files (the "Software"), to
8  * deal in the Software without restriction, including without limitation the
9  * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10  * sell copies of the Software, and to permit persons to whom the Software is
11  * furnished to do so, subject to the following conditions:
12  *
13  * The above copyright notice and this permission notice shall be included in all
14  * copies or substantial portions of the Software.
15  *
16  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22  * SOFTWARE.
23  */
24 #ifndef ARM_COMPUTE_CL /* Needed by Utils.cpp to handle OpenCL exceptions properly */
25 #error "This example needs to be built with -DARM_COMPUTE_CL"
26 #endif /* ARM_COMPUTE_CL */
27 
28 #include "arm_compute/core/Types.h"
29 #include "arm_compute/runtime/CL/CLScheduler.h"
30 #include "arm_compute/runtime/CL/CLTuner.h"
31 #include "arm_compute/runtime/CL/functions/CLGEMM.h"
32 #include "utils/Utils.h"
33 
34 #include <cstdlib>
35 
36 using namespace arm_compute;
37 using namespace utils;
38 
39 class CLSGEMMExample : public Example
40 {
41 public:
do_setup(int argc,char ** argv)42     bool do_setup(int argc, char **argv) override
43     {
44         NPYLoader npy0;
45         NPYLoader npy1;
46         NPYLoader npy2;
47         alpha = 1.0f;
48         beta  = 0.0f;
49 
50         CLScheduler::get().default_init(&tuner);
51 
52         std::ifstream stream;
53         if(argc > 1)
54         {
55             stream.open(argv[1], std::fstream::in);
56         }
57 
58         if(argc < 3 || (argc < 4 && stream.bad()))
59         {
60             // Print help
61             std::cout << "Usage: 1) ./build/cl_sgemm input_matrix_1.npy input_matrix_2.npy [input_matrix_3.npy] [alpha = 1] [beta = 0]\n";
62             std::cout << "       2) ./build/cl_sgemm M N K [alpha = 1.0f] [beta = 0.0f]\n\n";
63             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";
64 
65             src0.allocator()->init(TensorInfo(TensorShape(5U, 7U), 1, DataType::F32));
66             src1.allocator()->init(TensorInfo(TensorShape(3U, 5U), 1, DataType::F32));
67             src2.allocator()->init(TensorInfo(TensorShape(3U, 7U), 1, DataType::F32));
68         }
69         else
70         {
71             if(stream.good()) /* case file1.npy file2.npy [file3.npy] [alpha = 1.0f] [beta = 0.0f] */
72             {
73                 npy0.open(argv[1]);
74                 npy0.init_tensor(src0, DataType::F32);
75                 npy1.open(argv[2]);
76                 npy1.init_tensor(src1, DataType::F32);
77 
78                 if(argc > 3)
79                 {
80                     stream.close();
81                     stream.clear();
82                     stream.open(argv[3], std::fstream::in);
83                     if(stream.good()) /* case with third file */
84                     {
85                         npy2.open(argv[3]);
86                         npy2.init_tensor(src2, DataType::F32);
87 
88                         if(argc > 4)
89                         {
90                             // Convert string to float
91                             alpha = strtof(argv[4], nullptr);
92 
93                             if(argc > 5)
94                             {
95                                 // Convert string to float
96                                 beta = strtof(argv[5], nullptr);
97                             }
98                         }
99                     }
100                     else /* case without third file */
101                     {
102                         alpha = strtof(argv[3], nullptr);
103 
104                         if(argc > 4)
105                         {
106                             beta = strtof(argv[4], nullptr);
107                         }
108                     }
109                 }
110             }
111             else /* case M N K [alpha = 1.0f] [beta = 0.0f] */
112             {
113                 size_t M = strtol(argv[1], nullptr, 10);
114                 size_t N = strtol(argv[2], nullptr, 10);
115                 size_t K = strtol(argv[3], nullptr, 10);
116 
117                 src0.allocator()->init(TensorInfo(TensorShape(K, M), 1, DataType::F32));
118                 src1.allocator()->init(TensorInfo(TensorShape(N, K), 1, DataType::F32));
119                 src2.allocator()->init(TensorInfo(TensorShape(N, M), 1, DataType::F32));
120 
121                 if(argc > 4)
122                 {
123                     alpha = strtof(argv[4], nullptr);
124 
125                     if(argc > 5)
126                     {
127                         beta = strtof(argv[5], nullptr);
128                     }
129                 }
130             }
131         }
132 
133         init_sgemm_output(dst, src0, src1, DataType::F32);
134 
135         // Configure function
136         sgemm.configure(&src0, &src1, (src2.info()->total_size() > 0) ? &src2 : nullptr, &dst, alpha, beta);
137 
138         // Allocate all the images
139         src0.allocator()->allocate();
140         src1.allocator()->allocate();
141         dst.allocator()->allocate();
142 
143         // Fill the input images with either the data provided or random data
144         if(npy0.is_open())
145         {
146             npy0.fill_tensor(src0);
147             npy1.fill_tensor(src1);
148 
149             output_filename = "sgemm_out.npy";
150             is_fortran      = npy0.is_fortran();
151 
152             if(npy2.is_open())
153             {
154                 src2.allocator()->allocate();
155                 npy2.fill_tensor(src2);
156             }
157         }
158         else
159         {
160             src2.allocator()->allocate();
161 
162             fill_random_tensor(src0, -1.f, 1.f);
163             fill_random_tensor(src1, -1.f, 1.f);
164             fill_random_tensor(src2, -1.f, 1.f);
165         }
166 
167         // Dummy run for CLTuner
168         sgemm.run();
169 
170         return true;
171     }
do_run()172     void do_run() override
173     {
174         // Execute the function
175         sgemm.run();
176 
177         // Make sure all the OpenCL jobs are done executing:
178         CLScheduler::get().sync();
179     }
do_teardown()180     void do_teardown() override
181     {
182         if(!output_filename.empty()) /* Save to .npy file */
183         {
184             save_to_npy(dst, output_filename, is_fortran);
185         }
186     }
187 
188 private:
189     CLTensor    src0{};
190     CLTensor    src1{};
191     CLTensor    src2{};
192     CLTensor    dst{};
193     CLGEMM      sgemm{};
194     CLTuner     tuner{};
195     float       alpha{}, beta{};
196     bool        is_fortran{};
197     std::string output_filename{};
198 };
199 
200 /** Main program for sgemm test
201  *
202  * @param[in] argc Number of arguments
203  * @param[in] argv Arguments ( [optional] Matrix A, [optional] Matrix B, [optional] Matrix C, [optional] alpha, [optional] beta )
204  */
main(int argc,char ** argv)205 int main(int argc, char **argv)
206 {
207     return utils::run_example<CLSGEMMExample>(argc, argv);
208 }
209