1 /*
2 * Copyright (c) 2020-2021 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 "arm_compute/core/Helpers.h"
25 #include "arm_compute/core/ITensor.h"
26 #include "arm_compute/core/Types.h"
27 #include "arm_compute/core/utils/misc/Traits.h"
28 #include "src/core/NEON/wrapper/intrinsics/intrinsics.h"
29 #include "src/core/helpers/WindowHelpers.h"
30
31 namespace arm_compute
32 {
33 namespace cpu
34 {
add_qsymm16_neon(const ITensor * src0,const ITensor * src1,ITensor * dst,const ConvertPolicy & policy,const Window & window)35 void add_qsymm16_neon(const ITensor *src0, const ITensor *src1, ITensor *dst, const ConvertPolicy &policy, const Window &window)
36 {
37 ARM_COMPUTE_UNUSED(policy);
38
39 // Create input windows
40 Window input1_win = window.broadcast_if_dimension_le_one(src0->info()->tensor_shape());
41 Window input2_win = window.broadcast_if_dimension_le_one(src1->info()->tensor_shape());
42
43 // Clear X Dimension on execution window as we handle manually
44 Window win = window;
45 win.set(Window::DimX, Window::Dimension(0, 1, 1));
46
47 const int window_step_x = 8;
48 const auto window_start_x = static_cast<int>(window.x().start());
49 const auto window_end_x = static_cast<int>(window.x().end());
50 const bool is_broadcast_across_x = src0->info()->tensor_shape().x() != src1->info()->tensor_shape().x();
51
52 const UniformQuantizationInfo iq1_info = src0->info()->quantization_info().uniform();
53 const UniformQuantizationInfo iq2_info = src1->info()->quantization_info().uniform();
54 const UniformQuantizationInfo oq_info = dst->info()->quantization_info().uniform();
55
56 const float32x4_t vscale1 = vdupq_n_f32(iq1_info.scale);
57 const float32x4_t vscale2 = vdupq_n_f32(iq2_info.scale);
58 const float32x4_t invvscaleo = vdupq_n_f32(1.f / oq_info.scale);
59
60 if(is_broadcast_across_x)
61 {
62 const bool is_broadcast_input_2 = input2_win.x().step() == 0;
63 Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win;
64 Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win;
65 const ITensor *broadcast_tensor = is_broadcast_input_2 ? src1 : src0;
66 const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? src1 : src0;
67 const UniformQuantizationInfo broadcast_qinfo = broadcast_tensor->info()->quantization_info().uniform();
68 const UniformQuantizationInfo non_broadcast_qinfo = non_broadcast_tensor->info()->quantization_info().uniform();
69
70 // Clear X Dimension on execution window as we handle manually
71 non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1));
72
73 Iterator broadcast_input(broadcast_tensor, broadcast_win);
74 Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win);
75 Iterator output(dst, win);
76
77 execute_window_loop(win, [&](const Coordinates &)
78 {
79 const auto non_broadcast_input_ptr = reinterpret_cast<const int16_t *>(non_broadcast_input.ptr());
80 const auto output_ptr = reinterpret_cast<int16_t *>(output.ptr());
81
82 const int16_t broadcast_value = *reinterpret_cast<const int16_t *>(broadcast_input.ptr());
83 const int16x8_t broadcast_value_vec = vdupq_n_s16(broadcast_value);
84
85 const auto bf_0 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(broadcast_value_vec))), vscale2);
86 const auto bf_1 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(broadcast_value_vec))), vscale2);
87 const float bfs = static_cast<int32_t>(broadcast_value) * broadcast_qinfo.scale;
88
89 // Compute S elements per iteration
90 int x = window_start_x;
91 for(; x <= (window_end_x - window_step_x); x += window_step_x)
92 {
93 const int16x8_t a = vld1q_s16(non_broadcast_input_ptr + x);
94 const auto af_0 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1);
95 const auto af_1 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1);
96
97 int32x4_t rf_0{};
98 int32x4_t rf_1{};
99 #ifdef __aarch64__
100 rf_0 = vcvtnq_s32_f32(vmulq_f32(vaddq_f32(af_0, bf_0), invvscaleo));
101 rf_1 = vcvtnq_s32_f32(vmulq_f32(vaddq_f32(af_1, bf_1), invvscaleo));
102 #else //__aarch64__
103 rf_0 = vcvtq_s32_f32(vmulq_f32(vaddq_f32(af_0, bf_0), invvscaleo));
104 rf_1 = vcvtq_s32_f32(vmulq_f32(vaddq_f32(af_1, bf_1), invvscaleo));
105 #endif //__aarch64__
106
107 const int16x8_t pa = vcombine_s16(vqmovn_s32(rf_0), vqmovn_s32(rf_1));
108 vst1q_s16(output_ptr + x, pa);
109 }
110
111 // Compute left-over elements
112 for(; x < window_end_x; ++x)
113 {
114 const float afs = static_cast<int32_t>(*(non_broadcast_input_ptr + x)) * non_broadcast_qinfo.scale;
115 *(output_ptr + x) = quantize_qsymm16((afs + bfs), oq_info);
116 }
117 },
118 broadcast_input, non_broadcast_input, output);
119 }
120 else
121 {
122 // Clear X Dimension on execution window as we handle manually
123 input1_win.set(Window::DimX, Window::Dimension(0, 1, 1));
124 input2_win.set(Window::DimX, Window::Dimension(0, 1, 1));
125
126 Iterator input1(src0, input1_win);
127 Iterator input2(src1, input2_win);
128 Iterator output(dst, win);
129
130 execute_window_loop(win, [&](const Coordinates &)
131 {
132 const auto input1_ptr = reinterpret_cast<const int16_t *>(input1.ptr());
133 const auto input2_ptr = reinterpret_cast<const int16_t *>(input2.ptr());
134 const auto output_ptr = reinterpret_cast<int16_t *>(output.ptr());
135
136 // Compute S elements per iteration
137 int x = window_start_x;
138 for(; x <= (window_end_x - window_step_x); x += window_step_x)
139 {
140 const int16x8_t a = vld1q_s16(input1_ptr + x);
141 const int16x8_t b = vld1q_s16(input2_ptr + x);
142
143 const auto af_0 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(a))), vscale1);
144 const auto af_1 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(a))), vscale1);
145 const auto bf_0 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(b))), vscale2);
146 const auto bf_1 = vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(b))), vscale2);
147
148 int32x4_t rf_0{};
149 int32x4_t rf_1{};
150 #ifdef __aarch64__
151 rf_0 = vcvtnq_s32_f32(vmulq_f32(vaddq_f32(af_0, bf_0), invvscaleo));
152 rf_1 = vcvtnq_s32_f32(vmulq_f32(vaddq_f32(af_1, bf_1), invvscaleo));
153 #else //__aarch64__
154 rf_0 = vcvtq_s32_f32(vmulq_f32(vaddq_f32(af_0, bf_0), invvscaleo));
155 rf_1 = vcvtq_s32_f32(vmulq_f32(vaddq_f32(af_1, bf_1), invvscaleo));
156 #endif //__aarch64__
157
158 const int16x8_t pa = vcombine_s16(vqmovn_s32(rf_0), vqmovn_s32(rf_1));
159 vst1q_s16(output_ptr + x, pa);
160 }
161
162 // Compute left-over elements
163 for(; x < window_end_x; ++x)
164 {
165 const float afs = static_cast<int32_t>((*(input1_ptr + x))) * iq1_info.scale;
166 const float bfs = static_cast<int32_t>((*(input2_ptr + x))) * iq2_info.scale;
167 *(output_ptr + x) = quantize_qsymm16((afs + bfs), dst->info()->quantization_info());
168 }
169 },
170 input1, input2, output);
171 }
172 }
173 } // namespace cpu
174 } // namespace arm_compute