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Gian Marco58c57942017-11-28 09:10:03 +00001/*
Pablo Tello54e98d92019-02-05 16:16:19 +00002 * Copyright (c) 2017-2019 ARM Limited.
Gian Marco58c57942017-11-28 09:10:03 +00003 *
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_NEASYMM_H__
25#define __ARM_COMPUTE_NEASYMM_H__
26
Manuel Bottini7bb56c62019-06-26 15:17:09 +010027#include "arm_compute/core/NEON/NEMath.h"
Gian Marco58c57942017-11-28 09:10:03 +000028#include <arm_neon.h>
29
30namespace arm_compute
31{
Michel Iwaniec5dfeae62017-11-29 10:48:23 +000032using qasymm8x8_t = uint8x8_t; /**< 8 bit quantized asymmetric vector with 8 elements */
33using qasymm8x8x2_t = uint8x8x2_t; /**< 8 bit quantized asymmetric vector with 16 elements */
34using qasymm8x8x3_t = uint8x8x3_t; /**< 8 bit quantized asymmetric vector with 24 elements */
35using qasymm8x8x4_t = uint8x8x4_t; /**< 8 bit quantized asymmetric vector with 32 elements */
36using qasymm8x16_t = uint8x16_t; /**< 8 bit quantized asymmetric vector with 16 elements */
37
Michel Iwaniec5dfeae62017-11-29 10:48:23 +000038/** Perform a multiply-accumulate on all 16 components of a QASYMM8 vector
39 *
40 * vd*vs + vo
41 *
42 * @param[in] vd Input vector value in QASYMM8 format
43 * @param[in] vs Vector multiplier in F32 format. The multiplier value must be duplicated across all four lanes.
44 * @param[in] vo Vector addend in F32 format. The addend value must be duplicated across all four lanes.
45 *
46 * @return A 16-component vector in QASYMM8 format, saturated to fit
47 */
48uint8x16_t vmlaq_qasymm8(qasymm8x16_t vd, float32x4_t vs, float32x4_t vo);
Georgios Pinitasf72f9362018-01-12 16:29:45 +000049
50/** Performs final quantization step on 16 elements
51 *
52 * @tparam is_bounded_relu Specified if a fused bounded relu should be applied
53 *
54 * @param in_s32 Input to be quantized.
55 * @param result_fixedpoint_multiplier Result multiplier parameter
56 * @param result_shift Result shift parameter
57 * @param result_offset_after_shift_s32 Result offset parameter
58 * @param min_u8 Relu lower bound
59 * @param max_u8 Relu upper bound
60 *
61 * @return Quantized values
62 */
63template <bool is_bounded_relu>
64uint8x16_t finalize_quantization(int32x4x4_t &in_s32,
65 int result_fixedpoint_multiplier,
66 int32_t result_shift,
67 int32x4_t result_offset_after_shift_s32,
68 uint8x16_t min_u8,
69 uint8x16_t max_u8)
70{
71 const static int32x4_t zero_s32 = vdupq_n_s32(0);
72
73 // Fixed point multiplication with vector saturating rounding doubling multiply high with scalar
74 in_s32.val[0] = vqrdmulhq_n_s32(in_s32.val[0], result_fixedpoint_multiplier);
75 in_s32.val[1] = vqrdmulhq_n_s32(in_s32.val[1], result_fixedpoint_multiplier);
76 in_s32.val[2] = vqrdmulhq_n_s32(in_s32.val[2], result_fixedpoint_multiplier);
77 in_s32.val[3] = vqrdmulhq_n_s32(in_s32.val[3], result_fixedpoint_multiplier);
78
79 // Round to the nearest division by a power-of-two using result_shift_s32
80 in_s32.val[0] = rounding_divide_by_pow2(in_s32.val[0], result_shift);
81 in_s32.val[1] = rounding_divide_by_pow2(in_s32.val[1], result_shift);
82 in_s32.val[2] = rounding_divide_by_pow2(in_s32.val[2], result_shift);
83 in_s32.val[3] = rounding_divide_by_pow2(in_s32.val[3], result_shift);
84
85 // Add the offset terms
86 in_s32.val[0] = vaddq_s32(in_s32.val[0], result_offset_after_shift_s32);
87 in_s32.val[1] = vaddq_s32(in_s32.val[1], result_offset_after_shift_s32);
88 in_s32.val[2] = vaddq_s32(in_s32.val[2], result_offset_after_shift_s32);
89 in_s32.val[3] = vaddq_s32(in_s32.val[3], result_offset_after_shift_s32);
90
91 // Saturate negative values
92 in_s32.val[0] = vmaxq_s32(in_s32.val[0], zero_s32);
93 in_s32.val[1] = vmaxq_s32(in_s32.val[1], zero_s32);
94 in_s32.val[2] = vmaxq_s32(in_s32.val[2], zero_s32);
95 in_s32.val[3] = vmaxq_s32(in_s32.val[3], zero_s32);
96
97 // Convert S32 to S16
98 const int16x8x2_t in_s16 =
99 {
100 {
101 vcombine_s16(vqmovn_s32(in_s32.val[0]), vqmovn_s32(in_s32.val[1])),
102 vcombine_s16(vqmovn_s32(in_s32.val[2]), vqmovn_s32(in_s32.val[3]))
103 }
104 };
105
106 // Convert S16 to U8
107 uint8x16_t out_u8 = vcombine_u8(vqmovun_s16(in_s16.val[0]), vqmovun_s16(in_s16.val[1]));
108
109 if(is_bounded_relu)
110 {
111 out_u8 = vmaxq_u8(out_u8, min_u8);
112 out_u8 = vminq_u8(out_u8, max_u8);
113 }
114
115 return out_u8;
116}
Pablo Tello54e98d92019-02-05 16:16:19 +0000117
Georgios Pinitasdbdea0d2019-10-16 19:21:40 +0100118/** Performs final quantization step on 16 elements for symmetric quantization
119 *
120 * @tparam is_bounded_relu Specified if a fused bounded relu should be applied
121 *
122 * @param in_s32 Input to be quantized.
123 * @param result_fixedpoint_multiplier Result multiplier parameter
124 * @param result_shift Result shift parameter
125 * @param result_offset_after_shift_s32 Result offset parameter
126 * @param min_s8 Relu lower bound
127 * @param max_s8 Relu upper bound
128 *
129 * @return Quantized values
130 */
131template <bool is_bounded_relu>
132inline int8x16_t finalize_quantization_symm(int32x4x4_t &in_s32,
133 const int32x4x4_t &result_fixedpoint_multiplier,
134 const int32x4x4_t &result_shift,
135 const int32x4_t &result_offset_after_shift_s32,
136 const int8x16_t &min_s8,
137 const int8x16_t &max_s8)
138{
139 // Fixed point multiplication with vector saturating rounding doubling multiply high with scalar
140 in_s32.val[0] = vqrdmulhq_s32(in_s32.val[0], result_fixedpoint_multiplier.val[0]);
141 in_s32.val[1] = vqrdmulhq_s32(in_s32.val[1], result_fixedpoint_multiplier.val[1]);
142 in_s32.val[2] = vqrdmulhq_s32(in_s32.val[2], result_fixedpoint_multiplier.val[2]);
143 in_s32.val[3] = vqrdmulhq_s32(in_s32.val[3], result_fixedpoint_multiplier.val[3]);
144
145 // Round to the nearest division by a power-of-two using result_shift_s32
146 in_s32.val[0] = rounding_divide_by_pow2(in_s32.val[0], result_shift.val[0]);
147 in_s32.val[1] = rounding_divide_by_pow2(in_s32.val[1], result_shift.val[1]);
148 in_s32.val[2] = rounding_divide_by_pow2(in_s32.val[2], result_shift.val[2]);
149 in_s32.val[3] = rounding_divide_by_pow2(in_s32.val[3], result_shift.val[3]);
150
151 // Add the offset terms
152 in_s32.val[0] = vaddq_s32(in_s32.val[0], result_offset_after_shift_s32);
153 in_s32.val[1] = vaddq_s32(in_s32.val[1], result_offset_after_shift_s32);
154 in_s32.val[2] = vaddq_s32(in_s32.val[2], result_offset_after_shift_s32);
155 in_s32.val[3] = vaddq_s32(in_s32.val[3], result_offset_after_shift_s32);
156
157 // Convert S32 to S16
158 const int16x8x2_t in_s16 =
159 {
160 {
161 vcombine_s16(vqmovn_s32(in_s32.val[0]), vqmovn_s32(in_s32.val[1])),
162 vcombine_s16(vqmovn_s32(in_s32.val[2]), vqmovn_s32(in_s32.val[3]))
163 }
164 };
165
166 // Convert S16 to S8
167 int8x16_t out_s8 = vcombine_s8(vqmovn_s16(in_s16.val[0]), vqmovn_s16(in_s16.val[1]));
168
169 if(is_bounded_relu)
170 {
171 out_s8 = vmaxq_s8(out_s8, min_s8);
172 out_s8 = vminq_s8(out_s8, max_s8);
173 }
174
175 return out_s8;
176}
177
George Wort2d7e6832019-02-22 16:37:41 +0000178/** Performs final quantization step on single element
179 *
180 * @tparam is_bounded_relu Specified if a fused bounded relu should be applied
181 *
182 * @param[in] in_value Input to be quantized.
183 * @param[in] result_fixedpoint_multiplier Result multiplier parameter
184 * @param[in] result_shift Result shift parameter
185 * @param[in] result_offset_after_shift_s32 Result offset parameter
186 * @param[in] min_u8 Relu lower bound
187 * @param[in] max_u8 Relu upper bound
188 *
189 * @return Quantized value
190 */
191template <bool is_bounded_relu>
192inline uint8_t finalize_quantization(int32_t in_value, int result_fixedpoint_multiplier,
193 int32_t result_shift, int32_t result_offset_after_shift_s32,
194 uint8_t min_u8, uint8_t max_u8)
195{
196 int32x4_t in_s32 = vdupq_n_s32(in_value);
197
198 // Fixed point multiplication with vector saturating rounding doubling multiply high with scalar
199 in_value = vgetq_lane_s32(vqrdmulhq_n_s32(in_s32, result_fixedpoint_multiplier), 0);
200
201 // Shift value by result_shift_s32
202 in_value = rounding_divide_by_pow2(in_value, result_shift);
203
204 // Add the offset term
205 in_value += result_offset_after_shift_s32;
206
207 // Bound the result
Georgios Pinitas6fa26382019-03-18 10:05:34 +0000208 uint8_t out_u8 = static_cast<uint8_t>(std::max<int32_t>(0, std::min<int32_t>(255, in_value)));
George Wort2d7e6832019-02-22 16:37:41 +0000209 if(is_bounded_relu)
210 {
211 out_u8 = static_cast<uint8_t>(std::max(min_u8, std::min(max_u8, out_u8)));
212 }
213
214 return out_u8;
215}
216
Georgios Pinitasdbdea0d2019-10-16 19:21:40 +0100217/** Performs final quantization step on single element
218 *
219 * @tparam is_bounded_relu Specified if a fused bounded relu should be applied
220 *
221 * @param[in] in_value Input to be quantized.
222 * @param[in] result_fixedpoint_multiplier Result multiplier parameter
223 * @param[in] result_shift Result shift parameter
224 * @param[in] result_offset_after_shift_s32 Result offset parameter
225 * @param[in] min_s8 Relu lower bound
226 * @param[in] max_s8 Relu upper bound
227 *
228 * @return Quantized value
229 */
230template <bool is_bounded_relu>
231inline int8_t finalize_quantization(int32_t in_value, int result_fixedpoint_multiplier,
232 int32_t result_shift, int32_t result_offset_after_shift_s32,
233 int8_t min_s8, int8_t max_s8)
234{
235 int32x4_t in_s32 = vdupq_n_s32(in_value);
236
237 // Fixed point multiplication with vector saturating rounding doubling multiply high with scalar
238 in_value = vgetq_lane_s32(vqrdmulhq_n_s32(in_s32, result_fixedpoint_multiplier), 0);
239
240 // Shift value by result_shift_s32
241 in_value = rounding_divide_by_pow2(in_value, result_shift);
242
243 // Add the offset term
244 in_value += result_offset_after_shift_s32;
245
246 // Bound the result
247 int8_t out_s8 = static_cast<int8_t>(std::max<int32_t>(-128, std::min<int32_t>(127, in_value)));
248 if(is_bounded_relu)
249 {
250 out_s8 = static_cast<int8_t>(std::max(min_s8, std::min(max_s8, out_s8)));
251 }
252
253 return out_s8;
254}
255
Georgios Pinitasd66094e2019-04-15 15:44:17 +0100256/** Dequantize a neon vector holding 8 quantized values.
257 *
258 * @param[in] qv Input values to be dequantized.
259 * @param[in] qi Quantization information to be used in the computation.
260 *
261 * @return Dequantized values in a neon vector
262 */
Georgios Pinitas4c5469b2019-05-21 13:32:43 +0100263inline float32x4x2_t vdequantize(const uint8x8_t &qv, const UniformQuantizationInfo &qi)
Georgios Pinitasd66094e2019-04-15 15:44:17 +0100264{
265 const float scale = qi.scale;
266 const int offset = qi.offset;
267 const int32x4_t voffset = vdupq_n_s32(offset);
268 const float32x4_t vscale = vdupq_n_f32(scale);
269 const float32x4x2_t vdequantized_input =
270 {
271 {
272 vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(qv)))), voffset)), vscale),
273 vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(qv)))), voffset)), vscale),
274 }
275 };
276 return vdequantized_input;
277}
278
Pablo Tello54e98d92019-02-05 16:16:19 +0000279/** Dequantize a neon vector holding 16 quantized values.
280 *
Georgios Pinitasd66094e2019-04-15 15:44:17 +0100281 * @param[in] qv Input values to be dequantized.
282 * @param[in] qi Quantization information to be used in the computation.
Pablo Tello54e98d92019-02-05 16:16:19 +0000283 *
284 * @return Dequantized values in a neon vector
285 */
Georgios Pinitas4c5469b2019-05-21 13:32:43 +0100286inline float32x4x4_t vdequantize(const uint8x16_t &qv, const UniformQuantizationInfo &qi)
Pablo Tello54e98d92019-02-05 16:16:19 +0000287{
288 const float scale = qi.scale;
289 const int offset = qi.offset;
290 const int32x4_t voffset = vdupq_n_s32(offset);
291 const float32x4_t vscale = vdupq_n_f32(scale);
292 const float32x4x4_t vdequantized_input =
293 {
294 {
295 vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(qv))))), voffset)), vscale),
296 vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(qv))))), voffset)), vscale),
297 vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(qv))))), voffset)), vscale),
298 vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(qv))))), voffset)), vscale),
299 }
300 };
301 return vdequantized_input;
302}
303
Georgios Pinitas3d13af82019-06-04 13:04:16 +0100304/** Dequantize following an asymmetric quantization scheme a neon vector holding 16 quantized values.
305 *
306 * @param[in] qv Input values to be dequantized.
307 * @param[in] scale Quantization scaling factor.
308 * @param[in] offset Zero quantization offset.
309 *
310 * @return Dequantized values in a neon vector
311 */
312inline float32x4x4_t vdequantize(const uint8x16_t &qv, float scale, int32_t offset)
313{
314 const int32x4_t voffset = vdupq_n_s32(offset);
315 const float32x4_t vscale = vdupq_n_f32(scale);
316 const float32x4x4_t vdequantized_input =
317 {
318 {
319 vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(qv))))), voffset)), vscale),
320 vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(qv))))), voffset)), vscale),
321 vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(qv))))), voffset)), vscale),
322 vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(qv))))), voffset)), vscale),
323 }
324 };
325 return vdequantized_input;
326}
327
Georgios Pinitas8217c8e2019-11-11 18:24:22 +0000328/** Dequantize following symmetric quantization scheme a neon vector holding 16 quantized values.
Michalis Spyrou3f632f32019-08-22 16:52:00 +0100329 *
Georgios Pinitas8217c8e2019-11-11 18:24:22 +0000330 * @param[in] qv Input values to be dequantized.
331 * @param[in] vscale Vector containing quantization scaling factors.
Michalis Spyrou3f632f32019-08-22 16:52:00 +0100332 *
333 * @return Dequantized values in a neon vector
334 */
Georgios Pinitas8217c8e2019-11-11 18:24:22 +0000335inline float32x4x4_t vdequantize(const int8x16_t &qv, const float32x4x4_t vscale)
Michalis Spyrou3f632f32019-08-22 16:52:00 +0100336{
337 const float32x4x4_t vdequantized_input =
338 {
339 {
Georgios Pinitas8217c8e2019-11-11 18:24:22 +0000340 vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_low_s8(qv))))), vscale.val[0]),
341 vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_low_s8(qv))))), vscale.val[1]),
342 vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_high_s8(qv))))), vscale.val[2]),
343 vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_high_s8(qv))))), vscale.val[3]),
Michalis Spyrou3f632f32019-08-22 16:52:00 +0100344 }
345 };
346 return vdequantized_input;
347}
348
Georgios Pinitas3d13af82019-06-04 13:04:16 +0100349/** Dequantize following a symmetric quantization scheme a neon vector holding 16 quantized values.
350 *
351 * @param[in] qv Input values to be dequantized.
352 * @param[in] scale Quantization scaling factor.
353 *
354 * @return Dequantized values in a neon vector
355 */
356inline float32x4x4_t vdequantize(const int8x16_t &qv, float scale)
357{
358 const float32x4_t vscale = vdupq_n_f32(scale);
359 const float32x4x4_t vdequantized_input =
360 {
361 {
362 vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_low_s8(qv))))), vscale),
363 vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_low_s8(qv))))), vscale),
364 vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_high_s8(qv))))), vscale),
365 vmulq_f32(vcvtq_f32_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_high_s8(qv))))), vscale),
366 }
367 };
368 return vdequantized_input;
369}
370
Georgios Pinitasd66094e2019-04-15 15:44:17 +0100371/** Quantize a neon vector holding 8 floating point values.
372 *
373 * @param[in] qv Input values to be quantized.
374 * @param[in] qi Quantization information to be used in the computation.
375 *
376 * @return A neon vector holding the quantized values
377 */
Georgios Pinitas4c5469b2019-05-21 13:32:43 +0100378inline uint8x8_t vquantize(const float32x4x2_t &qv, const UniformQuantizationInfo &qi)
Georgios Pinitasd66094e2019-04-15 15:44:17 +0100379{
380 const float scale = qi.scale;
381 const int offset = qi.offset;
382 const float32x4_t voffset = vdupq_n_f32(offset);
383 const float32x4_t vinvscale = vdupq_n_f32(1.f / scale);
384 const int32x4x4_t rf =
385 {
386 {
387#ifdef __aarch64__
388 vcvtnq_s32_f32(vmlaq_f32(voffset, qv.val[0], vinvscale)),
389 vcvtnq_s32_f32(vmlaq_f32(voffset, qv.val[1], vinvscale)),
390#else //__aarch64__
391 vcvtq_s32_f32(vmlaq_f32(voffset, qv.val[0], vinvscale)),
392 vcvtq_s32_f32(vmlaq_f32(voffset, qv.val[1], vinvscale)),
393#endif //__aarch64__
394 }
395 };
396 return vqmovun_s16(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
397}
398
Pablo Tello54e98d92019-02-05 16:16:19 +0000399/** Quantize a neon vector holding 16 floating point values.
400 *
Georgios Pinitasd66094e2019-04-15 15:44:17 +0100401 * @param[in] qv Input values to be quantized.
402 * @param[in] qi Quantization information to be used in the computation.
Pablo Tello54e98d92019-02-05 16:16:19 +0000403 *
404 * @return A neon vector holding the quantized values
405 */
Georgios Pinitas4c5469b2019-05-21 13:32:43 +0100406inline uint8x16_t vquantize(const float32x4x4_t &qv, const UniformQuantizationInfo &qi)
Pablo Tello54e98d92019-02-05 16:16:19 +0000407{
408 const float scale = qi.scale;
409 const int offset = qi.offset;
410 const float32x4_t voffset = vdupq_n_f32(offset);
411 const float32x4_t vinvscale = vdupq_n_f32(1.f / scale);
412 const int32x4x4_t rf =
413 {
414 {
415#ifdef __aarch64__
416 vcvtnq_s32_f32(vmlaq_f32(voffset, qv.val[0], vinvscale)),
417 vcvtnq_s32_f32(vmlaq_f32(voffset, qv.val[1], vinvscale)),
418 vcvtnq_s32_f32(vmlaq_f32(voffset, qv.val[2], vinvscale)),
419 vcvtnq_s32_f32(vmlaq_f32(voffset, qv.val[3], vinvscale)),
420#else //__aarch64__
421 vcvtq_s32_f32(vmlaq_f32(voffset, qv.val[0], vinvscale)),
422 vcvtq_s32_f32(vmlaq_f32(voffset, qv.val[1], vinvscale)),
423 vcvtq_s32_f32(vmlaq_f32(voffset, qv.val[2], vinvscale)),
424 vcvtq_s32_f32(vmlaq_f32(voffset, qv.val[3], vinvscale)),
425#endif //__aarch64__
426 }
427 };
428 const uint8x8_t pa = vqmovun_s16(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1])));
429 const uint8x8_t pb = vqmovun_s16(vcombine_s16(vqmovn_s32(rf.val[2]), vqmovn_s32(rf.val[3])));
430 return vcombine_u8(pa, pb);
431}
Michele Di Giorgiod64a46c2019-10-01 12:25:49 +0100432
433/** Quantize to QASYMM16 a neon vector holding 16 floating point values.
434 *
435 * @param[in] qv Input values to be quantized.
436 * @param[in] qi Quantization information to be used in the computation.
437 *
438 * @return A neon vector holding the quantized values
439 */
440inline uint16x8x2_t vquantize_qasymm16(const float32x4x4_t &qv, const UniformQuantizationInfo &qi)
441{
442 const float scale = qi.scale;
443 const int offset = qi.offset;
444 const float32x4_t voffset = vdupq_n_f32(offset);
445 const float32x4_t vinvscale = vdupq_n_f32(1.f / scale);
446 const int32x4x4_t rf =
447 {
448 {
449#ifdef __aarch64__
450 vcvtnq_s32_f32(vmlaq_f32(voffset, qv.val[0], vinvscale)),
451 vcvtnq_s32_f32(vmlaq_f32(voffset, qv.val[1], vinvscale)),
452 vcvtnq_s32_f32(vmlaq_f32(voffset, qv.val[2], vinvscale)),
453 vcvtnq_s32_f32(vmlaq_f32(voffset, qv.val[3], vinvscale)),
454#else //__aarch64__
455 vcvtq_s32_f32(vmlaq_f32(voffset, qv.val[0], vinvscale)),
456 vcvtq_s32_f32(vmlaq_f32(voffset, qv.val[1], vinvscale)),
457 vcvtq_s32_f32(vmlaq_f32(voffset, qv.val[2], vinvscale)),
458 vcvtq_s32_f32(vmlaq_f32(voffset, qv.val[3], vinvscale)),
459#endif //__aarch64__
460 }
461 };
462 const uint16x8_t pa = vcombine_u16(vqmovun_s32(rf.val[0]), vqmovun_s32(rf.val[1]));
463 const uint16x8_t pb = vcombine_u16(vqmovun_s32(rf.val[2]), vqmovun_s32(rf.val[3]));
464 return { pa, pb };
465}
Gian Marco58c57942017-11-28 09:10:03 +0000466} // namespace arm_compute
467#include "arm_compute/core/NEON/NEAsymm.inl"
Michel Iwaniec5dfeae62017-11-29 10:48:23 +0000468#endif // __ARM_COMPUTE_NEASYMM_H__