Compute Library
 21.02
cl_sgemm.cpp
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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
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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,
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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"
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:
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 
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  }
172  void do_run() override
173  {
174  // Execute the function
175  sgemm.run();
176 
177  // Make sure all the OpenCL jobs are done executing:
179  }
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  */
205 int main(int argc, char **argv)
206 {
207  return utils::run_example<CLSGEMMExample>(argc, argv);
208 }
Basic implementation of the OpenCL tuner interface.
Definition: CLTuner.h:40
unsigned int M
Shape of a tensor.
Definition: TensorShape.h:39
bool is_fortran()
Return true if a NPY file is in fortran order.
Definition: Utils.h:366
static CLScheduler & get()
Access the scheduler singleton.
void init_tensor(T &tensor, arm_compute::DataType dt)
Initialise the tensor&#39;s metadata with the dimensions of the NPY file currently open.
Definition: Utils.h:377
void fill_tensor(T &tensor)
Fill a tensor with the content of the currently open NPY file.
Definition: Utils.h:406
1 channel, 1 F32 per channel
unsigned int N
Copyright (c) 2017-2021 Arm Limited.
void fill_random_tensor(TensorType &tensor, std::random_device::result_type seed, T lower_bound=std::numeric_limits< T >::lowest(), T upper_bound=std::numeric_limits< T >::max())
Definition: Utils.h:774
Interface to enqueue OpenCL kernels and get/set the OpenCL CommandQueue and ICLTuner.
void save_to_npy(T &tensor, const std::string &npy_filename, bool fortran_order)
Template helper function to save a tensor image to a NPY file.
Definition: Utils.h:627
int main(int argc, char **argv)
Main program for sgemm test.
Definition: cl_sgemm.cpp:205
Numpy data loader.
Definition: Utils.h:328
Basic function to execute GEMM on OpenCL.
Definition: CLGEMM.h:108
Abstract Example class.
Definition: Utils.h:78
bool is_open()
Return true if a NPY file is currently open.
Definition: Utils.h:360
void sync()
Blocks until all commands in the associated command queue have finished.
Definition: CLScheduler.cpp:72
void open(const std::string &npy_filename, DataLayout file_layout=DataLayout::NCHW)
Open a NPY file and reads its metadata.
Definition: Utils.h:342
Store the tensor&#39;s metadata.
Definition: TensorInfo.h:45
unsigned int K
void default_init(ICLTuner *cl_tuner=nullptr, CLGEMMHeuristicsHandle *gemm_h=nullptr)
Initialises the context and command queue used by the scheduler to default values and sets a default ...
void init_sgemm_output(T &dst, T &src0, T &src1, arm_compute::DataType dt)
Definition: Utils.h:808
Basic implementation of the OpenCL tensor interface.
Definition: CLTensor.h:41