1 /*
2 * Copyright (c) 2016-2020 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 #include "src/core/NEON/kernels/NEGEMMMatrixAdditionKernel.h"
25
26 #include "arm_compute/core/Error.h"
27 #include "arm_compute/core/Helpers.h"
28 #include "arm_compute/core/Types.h"
29 #include "arm_compute/core/Validate.h"
30 #include "src/core/CPP/Validate.h"
31 #include "src/core/NEON/NEFixedPoint.h"
32 #include "src/core/helpers/AutoConfiguration.h"
33 #include "src/core/helpers/WindowHelpers.h"
34
35 #include <arm_neon.h>
36
37 namespace arm_compute
38 {
39 namespace
40 {
41 constexpr unsigned int num_elems_processed_per_iteration = 16;
42
validate_arguments(const ITensorInfo * input,const ITensorInfo * output,float beta)43 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, float beta)
44 {
45 ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
46 ARM_COMPUTE_UNUSED(beta);
47
48 ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input);
49 ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
50
51 if(output->total_size() > 0)
52 {
53 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
54 ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
55 }
56
57 return Status{};
58 }
59
matrix_addition_f32(const ITensor * input,ITensor * output,const Window & window,float beta)60 void matrix_addition_f32(const ITensor *input, ITensor *output, const Window &window, float beta)
61 {
62 const float32x4_t beta_f32 = vdupq_n_f32(beta);
63
64 Iterator in(input, window);
65 Iterator out(output, window);
66
67 execute_window_loop(window, [&](const Coordinates &)
68 {
69 const auto in_ptr = reinterpret_cast<const float *>(in.ptr());
70 const auto out_ptr = reinterpret_cast<float *>(out.ptr());
71
72 float32x4x4_t alpha_ab = vld4q_f32(out_ptr);
73 const float32x4x4_t c = vld4q_f32(in_ptr);
74
75 // Multiply matrix C by its weight and accumulate
76 alpha_ab.val[0] = vmlaq_f32(alpha_ab.val[0], c.val[0], beta_f32);
77 alpha_ab.val[1] = vmlaq_f32(alpha_ab.val[1], c.val[1], beta_f32);
78 alpha_ab.val[2] = vmlaq_f32(alpha_ab.val[2], c.val[2], beta_f32);
79 alpha_ab.val[3] = vmlaq_f32(alpha_ab.val[3], c.val[3], beta_f32);
80
81 vst4q_f32(out_ptr, alpha_ab);
82 },
83 in, out);
84 }
85
86 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
matrix_addition_f16(const ITensor * input,ITensor * output,const Window & window,float beta)87 void matrix_addition_f16(const ITensor *input, ITensor *output, const Window &window, float beta)
88 {
89 const float16x8_t beta_f16 = vdupq_n_f16(beta);
90
91 Iterator in(input, window);
92 Iterator out(output, window);
93
94 execute_window_loop(window, [&](const Coordinates &)
95 {
96 const auto in_ptr = reinterpret_cast<const float16_t *>(in.ptr());
97 const auto out_ptr = reinterpret_cast<float16_t *>(out.ptr());
98
99 float16x8x2_t alpha_ab = vld2q_f16(out_ptr);
100 const float16x8x2_t c = vld2q_f16(in_ptr);
101 // Multiply matrix C by its weight and accumulate
102 alpha_ab.val[0] = vaddq_f16(alpha_ab.val[0], vmulq_f16(c.val[0], beta_f16));
103 alpha_ab.val[1] = vaddq_f16(alpha_ab.val[1], vmulq_f16(c.val[1], beta_f16));
104
105 vst2q_f16(out_ptr + 0, alpha_ab);
106 },
107 in, out);
108 }
109 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
110
111 } // namespace
112
NEGEMMMatrixAdditionKernel()113 NEGEMMMatrixAdditionKernel::NEGEMMMatrixAdditionKernel()
114 : INESimpleKernel(), _func(nullptr), _beta(0.0f)
115 {
116 }
117
configure(const ITensor * input,ITensor * output,float beta)118 void NEGEMMMatrixAdditionKernel::configure(const ITensor *input, ITensor *output, float beta)
119 {
120 ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
121
122 // Perform validation step
123 ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), beta));
124
125 switch(input->info()->data_type())
126 {
127 case DataType::F32:
128 _func = &matrix_addition_f32;
129 break;
130 case DataType::F16:
131 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
132 _func = &matrix_addition_f16;
133 break;
134 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
135 default:
136 ARM_COMPUTE_ERROR("Data type not supported");
137 break;
138 }
139
140 // Configure kernel window
141 INESimpleKernel::configure(input, output, num_elems_processed_per_iteration);
142
143 _beta = beta;
144 }
145
validate(const ITensorInfo * input,const ITensorInfo * output,float beta)146 Status NEGEMMMatrixAdditionKernel::validate(const ITensorInfo *input, const ITensorInfo *output, float beta)
147 {
148 ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, beta));
149 ARM_COMPUTE_RETURN_ON_ERROR(INESimpleKernel::validate(input->clone().get(), output->clone().get(), num_elems_processed_per_iteration));
150 return Status{};
151 }
152
run(const Window & window,const ThreadInfo & info)153 void NEGEMMMatrixAdditionKernel::run(const Window &window, const ThreadInfo &info)
154 {
155 ARM_COMPUTE_UNUSED(info);
156 ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
157 ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INESimpleKernel::window(), window);
158
159 if(_beta != 0.0f)
160 {
161 (*_func)(_input, _output, window, _beta);
162 }
163 }
164 } // namespace arm_compute
165