quantize_kernel.cpp 31.0 KB
Newer Older
T
Tian 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

15
#ifdef QUANT_OP
16

17
#include "operators/kernel/quantize_kernel.h"
18
#include <cmath>
T
Tian 已提交
19

20 21
#if defined(__ARM_NEON__) || defined(__ARM_NEON)
#include <arm_neon.h>
H
Refine  
hjchen2 已提交
22

23
#ifndef __aarch64__
H
hjchen2 已提交
24
inline float32_t vmaxvq_f32(float32x4_t r) {
25 26 27 28 29
  float32x2_t v = vmax_f32(vget_high_f32(r), vget_low_f32(r));
  return vget_lane_f32(vpmax_f32(v, v), 0);
}
#endif

H
hjchen2 已提交
30
inline int32x4_t vrnd_towards_zero(float32x4_t r) { return vcvtq_s32_f32(r); }
31

H
hjchen2 已提交
32
inline int32x4_t vrnd_away_zero(float32x4_t r) {
33
  float32x4_t plus = vdupq_n_f32(0.5);
34
  float32x4_t minus = vdupq_n_f32(-0.5);
35
  float32x4_t zero = vdupq_n_f32(0);
H
Refine  
hjchen2 已提交
36
  uint32x4_t more_than_zero = vcgtq_f32(r, zero);
37
  float32x4_t temp = vbslq_f32(more_than_zero, plus, minus);
H
Refine  
hjchen2 已提交
38
  temp = vaddq_f32(r, temp);
39 40 41 42
  int32x4_t ret = vcvtq_s32_f32(temp);
  return ret;
}

H
hjchen2 已提交
43
inline int32x4_t vrnd_to_even(float32x4_t r) {
H
Refine  
hjchen2 已提交
44
#if 0
45
  int32x4_t ret;
H
Refine  
hjchen2 已提交
46 47
  float value[4];
  vst1q_f32(value, r);
48
  for (int i = 0; i < 4; ++i) {
H
Refine  
hjchen2 已提交
49
    float v = round(value[i]);
50
    int32_t q = (int32_t)v;
H
Refine  
hjchen2 已提交
51
    if (abs(abs(v - value[i]) - 0.5) > 0) {
52 53 54 55 56
      ret[i] = q;
    } else {
      if (abs(q) % 2 == 0) {
        ret[i] = q;
      } else {
H
hjchen2 已提交
57
        ret[i] = q + ((q > 0) ? -1 : 1);
58 59 60 61
      }
    }
  }
  return ret;
62
#else
H
Refine  
hjchen2 已提交
63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82
  float32x4_t point5 = vdupq_n_f32(0.5);
  int32x4_t one = vdupq_n_s32(1);
  int32x4_t zero = vdupq_n_s32(0);

  int32x4_t rnd = vrnd_away_zero(r);
  float32x4_t frnd = vcvtq_f32_s32(rnd);
  frnd = vsubq_f32(frnd, r);
  frnd = vabsq_f32(frnd);
  uint32x4_t equal_point5 = vceqq_f32(frnd, point5);
  int32x4_t abs_rnd = vabsq_s32(rnd);
  abs_rnd = vandq_s32(abs_rnd, one);
  uint32x4_t not_mod2 = vreinterpretq_u32_s32(abs_rnd);
  uint32x4_t mask = vandq_u32(equal_point5, not_mod2);
  uint32x4_t more_than_zero = vcgtq_s32(rnd, zero);
  more_than_zero = vandq_u32(more_than_zero, vreinterpretq_u32_s32(one));
  mask = veorq_u32(more_than_zero, mask);
  more_than_zero = veorq_u32(more_than_zero, vreinterpretq_u32_s32(one));
  mask = vaddq_u32(more_than_zero, mask);
  int32x4_t smask = vreinterpretq_s32_u32(mask);
  smask = vsubq_s32(smask, one);
83
  rnd = vaddq_s32(rnd, smask);
H
Refine  
hjchen2 已提交
84
  return rnd;
85
#endif
86 87
}

88 89 90
namespace paddle_mobile {
namespace operators {

91
static float find_abs_max(const Tensor *input) {
92
  float max_abs = 0.f;
93
  const float *x = input->data<const float>();
94 95 96 97 98 99
  size_t size = input->numel();
#if defined(__ARM_NEON__) || defined(__ARM_NEON)
  size_t loop = size >> 4;
  size_t remain = size & 0xF;
  for (size_t i = 0; i < loop; ++i) {
    float32x4_t max;
H
Refine  
hjchen2 已提交
100 101 102 103 104
    float32x4_t r0 = vld1q_f32(x);
    float32x4_t r1 = vld1q_f32(x + 4);
    float32x4_t r2 = vld1q_f32(x + 8);
    float32x4_t r3 = vld1q_f32(x + 12);
    r0 = vabsq_f32(r0);
105 106 107
    r1 = vabsq_f32(r1);
    r2 = vabsq_f32(r2);
    r3 = vabsq_f32(r3);
H
Refine  
hjchen2 已提交
108 109 110 111
    max[0] = vmaxvq_f32(r0);
    max[1] = vmaxvq_f32(r1);
    max[2] = vmaxvq_f32(r2);
    max[3] = vmaxvq_f32(r3);
112 113 114 115 116 117 118 119 120
    max[0] = vmaxvq_f32(max);
    if (max[0] > max_abs) {
      max_abs = max[0];
    }
    x += 16;
  }
  size = remain;
#endif
  for (size_t i = 0; i < size; ++i) {
121 122 123 124 125 126 127 128
    float value = std::abs(x[i]);
    if (value > max_abs) {
      max_abs = value;
    }
  }
  return max_abs;
}

H
hjchen2 已提交
129
#ifdef __aarch64__
130
static void quantize_round_to_even(const Tensor *input, const float scale,
131
                                   Tensor *output) {
132
  const float *x = input->data<const float>();
H
hjchen2 已提交
133
  int8_t *y = output->mutable_data<int8_t>();
134 135 136 137
  size_t size = input->numel();
#if defined(__ARM_NEON__) || defined(__ARM_NEON)
  size_t loop = size >> 4;
  size_t remain = size & 0xF;
H
hjchen2 已提交
138 139

  #pragma omp parallel for
140
  for (size_t i = 0; i < loop; ++i) {
H
hjchen2 已提交
141 142 143 144 145 146
    const float *local_x = x + (i << 4);
    int8_t *local_y = y + (i << 4);
    float32x4_t r0 = vld1q_f32(local_x);
    float32x4_t r1 = vld1q_f32(local_x + 4);
    float32x4_t r2 = vld1q_f32(local_x + 8);
    float32x4_t r3 = vld1q_f32(local_x + 12);
147 148 149 150 151 152 153 154 155 156 157 158
    r0 = vmulq_n_f32(r0, scale);
    r1 = vmulq_n_f32(r1, scale);
    r2 = vmulq_n_f32(r2, scale);
    r3 = vmulq_n_f32(r3, scale);
    int32x4_t q0 = vrnd_to_even(r0);
    int32x4_t q1 = vrnd_to_even(r1);
    int32x4_t q2 = vrnd_to_even(r2);
    int32x4_t q3 = vrnd_to_even(r3);
    int16x4_t d0 = vmovn_s32(q0);
    int16x4_t d1 = vmovn_s32(q1);
    int16x4_t d2 = vmovn_s32(q2);
    int16x4_t d3 = vmovn_s32(q3);
H
hjchen2 已提交
159 160
    int16x8_t q5 = vcombine_s16(d0, d1);
    int16x8_t q6 = vcombine_s16(d2, d3);
H
Refine  
hjchen2 已提交
161 162
    int8x8_t d5 = vmovn_s16(q5);
    int8x8_t d6 = vmovn_s16(q6);
H
hjchen2 已提交
163 164
    vst1_s8(local_y, d5);
    vst1_s8(local_y + 8, d6);
165 166
  }
  size = remain;
H
hjchen2 已提交
167 168
  x += (loop << 4);
  y += (loop << 4);
169 170
#endif
  for (size_t i = 0; i < size; ++i) {
171
    float value = x[i] * scale;
H
Refine  
hjchen2 已提交
172 173 174 175
    float v = round(value);
    int32_t q = (int32_t)v;
    if (abs(abs(q - value) - 0.5) > 0) {
      y[i] = q;
176
    } else {
H
Refine  
hjchen2 已提交
177 178
      if (abs(q) % 2 == 0) {
        y[i] = q;
179
      } else {
H
hjchen2 已提交
180
        y[i] = q + ((q > 0) ? -1 : 1);
181 182 183 184 185
      }
    }
  }
}

186 187
static void quantize_round_to_zero(const Tensor *input, const float scale,
                                   Tensor *output) {
188
  const float *x = input->data<const float>();
H
hjchen2 已提交
189
  int8_t *y = output->mutable_data<int8_t>();
190
  size_t size = input->numel();
H
hjchen2 已提交
191
#if defined(__ARM_NEON__) || defined(__ARM_NEON)
192 193
  size_t loop = size >> 4;
  size_t remain = size & 0xF;
H
hjchen2 已提交
194 195

  #pragma omp parallel for
196
  for (size_t i = 0; i < loop; ++i) {
H
hjchen2 已提交
197 198 199 200 201 202
    const float *local_x = x + (i << 4);
    int8_t *local_y = y + (i << 4);
    float32x4_t r0 = vld1q_f32(local_x);
    float32x4_t r1 = vld1q_f32(local_x + 4);
    float32x4_t r2 = vld1q_f32(local_x + 8);
    float32x4_t r3 = vld1q_f32(local_x + 12);
203 204 205 206 207 208 209 210 211 212 213 214
    r0 = vmulq_n_f32(r0, scale);
    r1 = vmulq_n_f32(r1, scale);
    r2 = vmulq_n_f32(r2, scale);
    r3 = vmulq_n_f32(r3, scale);
    int32x4_t q0 = vrnd_towards_zero(r0);
    int32x4_t q1 = vrnd_towards_zero(r1);
    int32x4_t q2 = vrnd_towards_zero(r2);
    int32x4_t q3 = vrnd_towards_zero(r3);
    int16x4_t d0 = vmovn_s32(q0);
    int16x4_t d1 = vmovn_s32(q1);
    int16x4_t d2 = vmovn_s32(q2);
    int16x4_t d3 = vmovn_s32(q3);
H
hjchen2 已提交
215 216
    int16x8_t q5 = vcombine_s16(d0, d1);
    int16x8_t q6 = vcombine_s16(d2, d3);
H
Refine  
hjchen2 已提交
217 218
    int8x8_t d5 = vmovn_s16(q5);
    int8x8_t d6 = vmovn_s16(q6);
H
hjchen2 已提交
219 220
    vst1_s8(local_y, d5);
    vst1_s8(local_y + 8, d6);
221 222
  }
  size = remain;
H
hjchen2 已提交
223 224
  x += (loop << 4);
  y += (loop << 4);
225 226
#endif
  for (size_t i = 0; i < size; ++i) {
H
hjchen2 已提交
227
    y[i] = static_cast<int8_t>(x[i] * scale);
228 229 230
  }
}

231 232
static void quantize_round_to_nearest(const Tensor *input, const float scale,
                                      Tensor *output) {
233
  const float *x = input->data<const float>();
H
hjchen2 已提交
234
  int8_t *y = output->mutable_data<int8_t>();
235
  size_t size = input->numel();
236
#if defined(__ARM_NEON__) || defined(__ARM_NEON)
237 238
  size_t loop = size >> 4;
  size_t remain = size & 0xF;
H
hjchen2 已提交
239 240

  #pragma omp parallel for
241
  for (size_t i = 0; i < loop; ++i) {
H
hjchen2 已提交
242 243 244 245 246 247
    const float *local_x = x + (i << 4);
    int8_t *local_y = y + (i << 4);
    float32x4_t r0 = vld1q_f32(local_x);
    float32x4_t r1 = vld1q_f32(local_x + 4);
    float32x4_t r2 = vld1q_f32(local_x + 8);
    float32x4_t r3 = vld1q_f32(local_x + 12);
248 249 250 251 252 253 254 255 256 257 258 259
    r0 = vmulq_n_f32(r0, scale);
    r1 = vmulq_n_f32(r1, scale);
    r2 = vmulq_n_f32(r2, scale);
    r3 = vmulq_n_f32(r3, scale);
    int32x4_t q0 = vrnd_away_zero(r0);
    int32x4_t q1 = vrnd_away_zero(r1);
    int32x4_t q2 = vrnd_away_zero(r2);
    int32x4_t q3 = vrnd_away_zero(r3);
    int16x4_t d0 = vmovn_s32(q0);
    int16x4_t d1 = vmovn_s32(q1);
    int16x4_t d2 = vmovn_s32(q2);
    int16x4_t d3 = vmovn_s32(q3);
H
hjchen2 已提交
260 261
    int16x8_t q5 = vcombine_s16(d0, d1);
    int16x8_t q6 = vcombine_s16(d2, d3);
H
Refine  
hjchen2 已提交
262 263
    int8x8_t d5 = vmovn_s16(q5);
    int8x8_t d6 = vmovn_s16(q6);
H
hjchen2 已提交
264 265
    vst1_s8(local_y, d5);
    vst1_s8(local_y + 8, d6);
266 267
  }
  size = remain;
H
hjchen2 已提交
268 269
  x += (loop << 4);
  y += (loop << 4);
270 271
#endif
  for (size_t i = 0; i < size; ++i) {
H
hjchen2 已提交
272
    y[i] = round(x[i] * scale);
273 274
  }
}
275
#else   // __aarch64__
H
hjchen2 已提交
276 277 278 279 280 281 282 283 284

static void quantize_round_to_even(const Tensor *input, const float scale,
                                   const std::vector<int> &paddings,
                                   const int8_t padding_val, Tensor *output) {}

static void quantize_round_to_nearest(const Tensor *input, const float scale,
                                      const std::vector<int> &paddings,
                                      const int8_t padding_val,
                                      Tensor *output) {}
285

H
hjchen2 已提交
286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301
static void quantize_round_to_zero(const Tensor *input, const float scale,
                                   const std::vector<int> &paddings,
                                   const int8_t padding_val, Tensor *output) {
  int channels = input->dims()[1];
  int input_h = input->dims()[2];
  int input_w = input->dims()[3];
  int output_h = output->dims()[2];
  int output_w = output->dims()[3];
  int input_spatial_size = input_h * input_w;
  int output_spatial_size = output_h * output_w;
  const float *x = input->data<float>();
  int8_t *y = output->mutable_data<int8_t>();
  // valid area start
  int start = paddings[0] * output_w + paddings[1];

  for (int batch = 0; batch < input->dims()[0]; ++batch) {
302
    #pragma omp parallel for
H
hjchen2 已提交
303
    for (int c = 0; c < channels - 3; c += 4) {
H
hjchen2 已提交
304 305 306 307 308
      const float *input0 = x + (batch * channels + c) * input_spatial_size;
      const float *input1 = input0 + input_spatial_size;
      const float *input2 = input1 + input_spatial_size;
      const float *input3 = input2 + input_spatial_size;
      size_t offset = (batch * channels + c) * output_spatial_size;
H
hjchen2 已提交
309 310 311 312 313 314 315
      for (int h = 0; h < 2; ++h) {
        int8_t *y0 =
            y + offset + h * ((input_h + paddings[0]) * output_w - paddings[1]);
        int8_t *y1 = y0 + output_spatial_size;
        int8_t *y2 = y1 + output_spatial_size;
        int8_t *y3 = y2 + output_spatial_size;
        int loop = start >> 4;
H
hjchen2 已提交
316
        int remain = start & 0xF;
H
hjchen2 已提交
317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375
        asm volatile(
            "vdup.s8    q0,     %[val]      \n"
            "cmp        %[loop], #0         \n"
            "ble        start_remain_%=     \n"

            "store_16w_%=:                  \n"
            "vst1.32    {q0}, [%[y0]]!      \n"
            "vst1.32    {q0}, [%[y1]]!      \n"
            "vst1.32    {q0}, [%[y2]]!      \n"
            "vst1.32    {q0}, [%[y3]]!      \n"
            "subs       %[loop], #1         \n"
            "bne        store_16w_%=        \n"

            "start_remain_%=:               \n"
            "cmp        %[remain], #8       \n"
            "blt        store_4w_%=         \n"
            "vst1.32    {d0}, [%[y0]]!      \n"
            "vst1.32    {d0}, [%[y1]]!      \n"
            "vst1.32    {d0}, [%[y2]]!      \n"
            "vst1.32    {d0}, [%[y3]]!      \n"
            "sub        %[remain], #8       \n"

            "store_4w_%=:                   \n"
            "cmp        %[remain], #4       \n"
            "blt        store_2w_%=         \n"
            "vst1.32    {d0[0]}, [%[y0]]!   \n"
            "vst1.32    {d0[0]}, [%[y1]]!   \n"
            "vst1.32    {d0[0]}, [%[y2]]!   \n"
            "vst1.32    {d0[0]}, [%[y3]]!   \n"
            "sub        %[remain], #4       \n"

            "store_2w_%=:                   \n"
            "cmp        %[remain], #4       \n"
            "blt        store_1w_%=         \n"
            "vst1.16    {d0[0]}, [%[y0]]!   \n"
            "vst1.16    {d0[0]}, [%[y1]]!   \n"
            "vst1.16    {d0[0]}, [%[y2]]!   \n"
            "vst1.16    {d0[0]}, [%[y3]]!   \n"
            "sub        %[remain], #2       \n"

            "store_1w_%=:                   \n"
            "cmp        %[remain], #1       \n"
            "blt        end_%=              \n"
            "vst1.8     {d0[0]}, [%[y0]]!   \n"
            "vst1.8     {d0[0]}, [%[y1]]!   \n"
            "vst1.8     {d0[0]}, [%[y2]]!   \n"
            "vst1.8     {d0[0]}, [%[y3]]!   \n"
            "end_%=:                        \n"
            : [y0] "+r"(y0), [y1] "+r"(y1), [y2] "+r"(y2), [y3] "+r"(y3),
              [loop] "+r"(loop), [remain] "+r"(remain)
            : [val] "r"(padding_val)
            : "cc", "memory", "q0");
      }
      // quantize valid area
      int8_t *y0 = y + offset + start;
      int8_t *y1 = y0 + output_spatial_size;
      int8_t *y2 = y1 + output_spatial_size;
      int8_t *y3 = y2 + output_spatial_size;
      for (int h = 0; h < input_h; ++h) {
H
hjchen2 已提交
376 377 378 379
        const float *x0 = input0 + h * input_w;
        const float *x1 = input1 + h * input_w;
        const float *x2 = input2 + h * input_w;
        const float *x3 = input3 + h * input_w;
H
hjchen2 已提交
380
        int loop = input_w >> 4;
H
hjchen2 已提交
381
        int remain = input_w & 0xF;
H
hjchen2 已提交
382
        int pad_loop = paddings[1] >> 1;
H
hjchen2 已提交
383 384
        int pad_remain = paddings[1] & 0x1;
        int remain_steps = remain;
H
hjchen2 已提交
385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454
        asm volatile(
            "vdup.f32   q0, %[scale]        \n"
            "cmp        %[loop], #0         \n"
            "ble        quantize_remain_%=  \n"

            "loop_quantize_%=:              \n"
            "vld1.32    {q1, q2}, [%[x0]]!  \n"
            "vld1.32    {q3, q4}, [%[x1]]!  \n"
            "vld1.32    {q5, q6}, [%[x2]]!  \n"
            "vld1.32    {q7, q8}, [%[x3]]!  \n"
            "vmul.f32  q1, q1, q0           \n"
            "vmul.f32  q2, q2, q0           \n"
            "vmul.f32  q3, q3, q0           \n"
            "vmul.f32  q4, q4, q0           \n"
            "vmul.f32  q5, q5, q0           \n"
            "vmul.f32  q6, q6, q0           \n"
            "vmul.f32  q7, q7, q0           \n"
            "vmul.f32  q8, q8, q0           \n"
            "vcvt.s32.f32  q1, q1           \n"
            "vcvt.s32.f32  q2, q2           \n"
            "vcvt.s32.f32  q3, q3           \n"
            "vcvt.s32.f32  q4, q4           \n"
            "vcvt.s32.f32  q5, q5           \n"
            "vcvt.s32.f32  q6, q6           \n"
            "vcvt.s32.f32  q7, q7           \n"
            "vcvt.s32.f32  q8, q8           \n"
            "vmovn.s32  d2, q1              \n"
            "vmovn.s32  d3, q2              \n"
            "vmovn.s32  d4, q3              \n"
            "vmovn.s32  d5, q4              \n"
            "vmovn.s32  d6, q5              \n"
            "vmovn.s32  d7, q6              \n"
            "vmovn.s32  d8, q7              \n"
            "vmovn.s32  d9, q8              \n"
            "vmovn.s16  d18, q1             \n"
            "vmovn.s16  d20, q2             \n"
            "vmovn.s16  d22, q3             \n"
            "vmovn.s16  d24, q4             \n"
            "vld1.32    {q1, q2}, [%[x0]]!  \n"
            "vld1.32    {q3, q4}, [%[x1]]!  \n"
            "vld1.32    {q5, q6}, [%[x2]]!  \n"
            "vld1.32    {q7, q8}, [%[x3]]!  \n"
            "vmul.f32  q1, q1, q0           \n"
            "vmul.f32  q2, q2, q0           \n"
            "vmul.f32  q3, q3, q0           \n"
            "vmul.f32  q4, q4, q0           \n"
            "vmul.f32  q5, q5, q0           \n"
            "vmul.f32  q6, q6, q0           \n"
            "vmul.f32  q7, q7, q0           \n"
            "vmul.f32  q8, q8, q0           \n"
            "vcvt.s32.f32  q1, q1           \n"
            "vcvt.s32.f32  q2, q2           \n"
            "vcvt.s32.f32  q3, q3           \n"
            "vcvt.s32.f32  q4, q4           \n"
            "vcvt.s32.f32  q5, q5           \n"
            "vcvt.s32.f32  q6, q6           \n"
            "vcvt.s32.f32  q7, q7           \n"
            "vcvt.s32.f32  q8, q8           \n"
            "vmovn.s32  d2, q1              \n"
            "vmovn.s32  d3, q2              \n"
            "vmovn.s32  d4, q3              \n"
            "vmovn.s32  d5, q4              \n"
            "vmovn.s32  d6, q5              \n"
            "vmovn.s32  d7, q6              \n"
            "vmovn.s32  d8, q7              \n"
            "vmovn.s32  d9, q8              \n"
            "vmovn.s16  d19, q1             \n"
            "vmovn.s16  d21, q2             \n"
            "vmovn.s16  d23, q3             \n"
            "vmovn.s16  d25, q4             \n"
H
hjchen2 已提交
455 456 457 458
            "vst1.32    {q9}, [%[y0]]!      \n"
            "vst1.32    {q10}, [%[y1]]!     \n"
            "vst1.32    {q11}, [%[y2]]!     \n"
            "vst1.32    {q12}, [%[y3]]!     \n"
H
hjchen2 已提交
459 460 461 462 463 464 465 466

            "subs       %[loop], #1         \n"
            "bne        loop_quantize_%=    \n"

            "quantize_remain_%=:            \n"
            "cmp        %[remain], #0       \n"
            "ble        end_%=              \n"

H
hjchen2 已提交
467 468 469 470
            "vld1.32    {q1, q2}, [%[x0]]!  \n"
            "vld1.32    {q3, q4}, [%[x1]]!  \n"
            "vld1.32    {q5, q6}, [%[x2]]!  \n"
            "vld1.32    {q7, q8}, [%[x3]]!  \n"
H
hjchen2 已提交
471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498
            "vmul.f32  q1, q1, q0           \n"
            "vmul.f32  q2, q2, q0           \n"
            "vmul.f32  q3, q3, q0           \n"
            "vmul.f32  q4, q4, q0           \n"
            "vmul.f32  q5, q5, q0           \n"
            "vmul.f32  q6, q6, q0           \n"
            "vmul.f32  q7, q7, q0           \n"
            "vmul.f32  q8, q8, q0           \n"
            "vcvt.s32.f32  q1, q1           \n"
            "vcvt.s32.f32  q2, q2           \n"
            "vcvt.s32.f32  q3, q3           \n"
            "vcvt.s32.f32  q4, q4           \n"
            "vcvt.s32.f32  q5, q5           \n"
            "vcvt.s32.f32  q6, q6           \n"
            "vcvt.s32.f32  q7, q7           \n"
            "vcvt.s32.f32  q8, q8           \n"
            "vmovn.s32  d2, q1              \n"
            "vmovn.s32  d3, q2              \n"
            "vmovn.s32  d4, q3              \n"
            "vmovn.s32  d5, q4              \n"
            "vmovn.s32  d6, q5              \n"
            "vmovn.s32  d7, q6              \n"
            "vmovn.s32  d8, q7              \n"
            "vmovn.s32  d9, q8              \n"
            "vmovn.s16  d18, q1             \n"
            "vmovn.s16  d20, q2             \n"
            "vmovn.s16  d22, q3             \n"
            "vmovn.s16  d24, q4             \n"
H
hjchen2 已提交
499 500 501 502
            "vld1.32    {q1, q2}, [%[x0]]   \n"
            "vld1.32    {q3, q4}, [%[x1]]   \n"
            "vld1.32    {q5, q6}, [%[x2]]   \n"
            "vld1.32    {q7, q8}, [%[x3]]   \n"
H
hjchen2 已提交
503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582
            "vmul.f32  q1, q1, q0           \n"
            "vmul.f32  q2, q2, q0           \n"
            "vmul.f32  q3, q3, q0           \n"
            "vmul.f32  q4, q4, q0           \n"
            "vmul.f32  q5, q5, q0           \n"
            "vmul.f32  q6, q6, q0           \n"
            "vmul.f32  q7, q7, q0           \n"
            "vmul.f32  q8, q8, q0           \n"
            "vcvt.s32.f32  q1, q1           \n"
            "vcvt.s32.f32  q2, q2           \n"
            "vcvt.s32.f32  q3, q3           \n"
            "vcvt.s32.f32  q4, q4           \n"
            "vcvt.s32.f32  q5, q5           \n"
            "vcvt.s32.f32  q6, q6           \n"
            "vcvt.s32.f32  q7, q7           \n"
            "vcvt.s32.f32  q8, q8           \n"
            "vmovn.s32  d2, q1              \n"
            "vmovn.s32  d3, q2              \n"
            "vmovn.s32  d4, q3              \n"
            "vmovn.s32  d5, q4              \n"
            "vmovn.s32  d6, q5              \n"
            "vmovn.s32  d7, q6              \n"
            "vmovn.s32  d8, q7              \n"
            "vmovn.s32  d9, q8              \n"
            "vmovn.s16  d19, q1             \n"
            "vmovn.s16  d21, q2             \n"
            "vmovn.s16  d23, q3             \n"
            "vmovn.s16  d25, q4             \n"

            "cmp        %[remain], #8       \n"
            "blt        store_4w_%=         \n"
            "vst1.32    {d18}, [%[y0]]!     \n"
            "vst1.32    {d20}, [%[y1]]!     \n"
            "vst1.32    {d22}, [%[y2]]!     \n"
            "vst1.32    {d24}, [%[y3]]!     \n"
            "vmov.32    d18, d19            \n"
            "vmov.32    d20, d21            \n"
            "vmov.32    d22, d23            \n"
            "vmov.32    d24, d25            \n"
            "sub        %[remain], #8       \n"

            "store_4w_%=:                   \n"
            "cmp        %[remain], #4       \n"
            "blt        store_2w_%=         \n"
            "vst1.32    {d18[0]}, [%[y0]]!  \n"
            "vst1.32    {d20[0]}, [%[y1]]!  \n"
            "vst1.32    {d22[0]}, [%[y2]]!  \n"
            "vst1.32    {d24[0]}, [%[y3]]!  \n"
            "vext.32    d18, d18, d18, #1   \n"
            "vext.32    d20, d20, d20, #1   \n"
            "vext.32    d22, d22, d22, #1   \n"
            "vext.32    d24, d24, d24, #1   \n"
            "sub        %[remain], #4       \n"

            "store_2w_%=:                   \n"
            "cmp        %[remain], #2       \n"
            "blt        store_1w_%=         \n"
            "vst1.16    {d18[0]}, [%[y0]]!  \n"
            "vst1.16    {d20[0]}, [%[y1]]!  \n"
            "vst1.16    {d22[0]}, [%[y2]]!  \n"
            "vst1.16    {d24[0]}, [%[y3]]!  \n"
            "vext.16    d18, d18, d18, #1   \n"
            "vext.16    d20, d20, d20, #1   \n"
            "vext.16    d22, d22, d22, #1   \n"
            "vext.16    d24, d24, d24, #1   \n"
            "sub        %[remain], #2       \n"

            "store_1w_%=:"
            "cmp        %[remain], #1       \n"
            "blt        end_%=              \n"
            "vst1.8     {d18[0]}, [%[y0]]!  \n"
            "vst1.8     {d20[0]}, [%[y1]]!  \n"
            "vst1.8     {d22[0]}, [%[y2]]!  \n"
            "vst1.8     {d24[0]}, [%[y3]]!  \n"

            "end_%=:                        \n"
            : [x0] "+r"(x0), [x1] "+r"(x1), [x2] "+r"(x2), [x3] "+r"(x3),
              [y0] "+r"(y0), [y1] "+r"(y1), [y2] "+r"(y2), [y3] "+r"(y3),
              [loop] "+r"(loop), [remain] "+r"(remain)
            : [scale] "r"(scale)
H
hjchen2 已提交
583 584
            : "cc", "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7",
              "q8", "q9", "q10", "q11", "q12");
H
hjchen2 已提交
585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616
        asm volatile(
            "vdup.s8    d0, %[val]          \n"
            "cmp        %[pad_loop], #0     \n"
            "ble        store_pad_2w_%=     \n"
            "loop_pad_4w_%=:                \n"
            "vst1.32    {d0[0]}, [%[y0]]!   \n"
            "vst1.32    {d0[0]}, [%[y1]]!   \n"
            "vst1.32    {d0[0]}, [%[y2]]!   \n"
            "vst1.32    {d0[0]}, [%[y3]]!   \n"
            "subs       %[pad_loop], #1     \n"
            "bne        loop_pad_4w_%=      \n"

            "store_pad_2w_%=:               \n"
            "cmp        %[pad_remain], #2   \n"
            "ble        store_pad_1w_%=     \n"
            "vst1.16    {d0[0]}, [%[y0]]!   \n"
            "vst1.16    {d0[0]}, [%[y1]]!   \n"
            "vst1.16    {d0[0]}, [%[y2]]!   \n"
            "vst1.16    {d0[0]}, [%[y3]]!   \n"
            "sub        %[pad_remain], #2   \n"

            "store_pad_1w_%=:               \n"
            "cmp        %[pad_remain], #1   \n"
            "ble        end_%=              \n"
            "vst1.8    {d0[0]}, [%[y0]]!    \n"
            "vst1.8    {d0[0]}, [%[y1]]!    \n"
            "vst1.8    {d0[0]}, [%[y2]]!    \n"
            "vst1.8    {d0[0]}, [%[y3]]!    \n"
            "end_%=:                        \n"
            : [y0] "+r"(y0), [y1] "+r"(y1), [y2] "+r"(y2), [y3] "+r"(y3),
              [pad_loop] "+r"(pad_loop), [pad_remain] "+r"(pad_remain)
            : [val] "r"(padding_val)
H
hjchen2 已提交
617 618
            : "cc", "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7",
              "q8", "q9", "q10", "q11", "q12");
H
hjchen2 已提交
619 620 621
      }
    }
    for (int c = (channels & 0xFFFC); c < channels; ++c) {
H
hjchen2 已提交
622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669
      const float *input0 = x + (batch * channels + c) * input_spatial_size;
      size_t offset = (batch * channels + c) * output_spatial_size;
      for (int h = 0; h < 2; ++h) {
        int8_t *y0 =
            y + offset + h * ((input_h + paddings[0]) * output_w - paddings[1]);
        int loop = start >> 4;
        int remain = start & 0xF;
        asm volatile(
            "vdup.s8    q0,     %[val]      \n"
            "cmp        %[loop], #0         \n"
            "ble        start_remain_%=     \n"

            "store_16w_%=:                  \n"
            "vst1.32    {q0}, [%[y0]]!      \n"
            "subs       %[loop], #1         \n"
            "bne        store_16w_%=        \n"

            "start_remain_%=:               \n"
            "cmp        %[remain], #8       \n"
            "blt        store_4w_%=         \n"
            "vst1.32    {d0}, [%[y0]]!      \n"
            "sub        %[remain], #8       \n"

            "store_4w_%=:                   \n"
            "cmp        %[remain], #4       \n"
            "blt        store_2w_%=         \n"
            "vst1.32    {d0[0]}, [%[y0]]!   \n"
            "sub        %[remain], #4       \n"

            "store_2w_%=:                   \n"
            "cmp        %[remain], #4       \n"
            "blt        store_1w_%=         \n"
            "vst1.16    {d0[0]}, [%[y0]]!   \n"
            "sub        %[remain], #2       \n"

            "store_1w_%=:                   \n"
            "cmp        %[remain], #1       \n"
            "blt        end_%=              \n"
            "vst1.8     {d0[0]}, [%[y0]]!   \n"
            "end_%=:                        \n"
            : [y0] "+r"(y0), [loop] "+r"(loop), [remain] "+r"(remain)
            : [val] "r"(padding_val)
            : "cc", "memory", "q0");
      }
      // quantize valid area
      int8_t *y0 = y + offset + start;
      for (int h = 0; h < input_h; ++h) {
        const float *x0 = input0 + h * input_w;
H
hjchen2 已提交
670
        int loop = input_w >> 4;
H
hjchen2 已提交
671
        int remain = input_w & 0xF;
H
hjchen2 已提交
672
        int pad_loop = paddings[1] >> 1;
H
hjchen2 已提交
673
        int pad_remain = paddings[1] & 0x1;
H
hjchen2 已提交
674 675 676 677 678 679 680
        asm volatile(
            "vdup.f32   q0, %[scale]        \n"
            "cmp        %[loop], #0         \n"
            "ble        quantize_remain_%=  \n"

            "loop_quantize_%=:              \n"
            "vld1.32    {q1, q2}, [%[x0]]!  \n"
H
hjchen2 已提交
681 682
            "vmul.f32   q1, q1, q0          \n"
            "vmul.f32   q2, q2, q0          \n"
H
hjchen2 已提交
683 684 685 686 687 688
            "vcvt.s32.f32  q1, q1           \n"
            "vcvt.s32.f32  q2, q2           \n"
            "vmovn.s32  d2, q1              \n"
            "vmovn.s32  d3, q2              \n"
            "vmovn.s16  d18, q1             \n"
            "vld1.32    {q1, q2}, [%[x0]]!  \n"
H
hjchen2 已提交
689 690
            "vmul.f32   q1, q1, q0          \n"
            "vmul.f32   q2, q2, q0          \n"
H
hjchen2 已提交
691 692 693 694 695
            "vcvt.s32.f32  q1, q1           \n"
            "vcvt.s32.f32  q2, q2           \n"
            "vmovn.s32  d2, q1              \n"
            "vmovn.s32  d3, q2              \n"
            "vmovn.s16  d19, q1             \n"
H
hjchen2 已提交
696
            "vst1.32    {q9}, [%[y0]]!      \n"
H
hjchen2 已提交
697 698 699 700 701 702 703 704

            "subs       %[loop], #1         \n"
            "bne        loop_quantize_%=    \n"

            "quantize_remain_%=:            \n"
            "cmp        %[remain], #0       \n"
            "ble        start_pad_%=        \n"

H
hjchen2 已提交
705 706 707
            "vldm       %[x0], {d2-d9}      \n"
            "vmul.f32   q1, q1, q0          \n"
            "vmul.f32   q2, q2, q0          \n"
H
hjchen2 已提交
708 709 710 711 712
            "vcvt.s32.f32  q1, q1           \n"
            "vcvt.s32.f32  q2, q2           \n"
            "vmovn.s32  d2, q1              \n"
            "vmovn.s32  d3, q2              \n"
            "vmovn.s16  d18, q1             \n"
H
hjchen2 已提交
713 714 715 716
            "vmul.f32   q3, q3, q0          \n"
            "vmul.f32   q4, q4, q0          \n"
            "vcvt.s32.f32  q1, q3           \n"
            "vcvt.s32.f32  q2, q4           \n"
H
hjchen2 已提交
717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769
            "vmovn.s32  d2, q1              \n"
            "vmovn.s32  d3, q2              \n"
            "vmovn.s16  d19, q1             \n"

            "cmp        %[remain], #8       \n"
            "blt        store_4w_%=         \n"
            "vst1.32    {d18}, [%[y0]]!     \n"
            "vmov.32    d18, d19            \n"
            "sub        %[remain], #8       \n"

            "store_4w_%=:                   \n"
            "cmp        %[remain], #4       \n"
            "blt        store_2w_%=         \n"
            "vst1.32    {d18[0]}, [%[y0]]!  \n"
            "vext.32    d18, d18, d18, #1   \n"
            "sub        %[remain], #4       \n"

            "store_2w_%=:                   \n"
            "cmp        %[remain], #2       \n"
            "blt        store_1w_%=         \n"
            "vst1.16    {d18[0]}, [%[y0]]!  \n"
            "vext.16    d18, d18, d18, #1   \n"
            "sub        %[remain], #2       \n"

            "store_1w_%=:"
            "cmp        %[remain], #1       \n"
            "blt        start_pad_%=        \n"
            "vst1.8     {d18[0]}, [%[y0]]!  \n"

            "start_pad_%=:                  \n"
            "vdup.s8    d0, %[val]          \n"
            "cmp        %[pad_loop], #0     \n"
            "ble        pad_remain_%=       \n"
            "loop_pad_4w_%=:                \n"
            "vst1.32    {d0[0]}, [%[y0]]!   \n"
            "subs       %[pad_loop], #1     \n"
            "bne        loop_pad_4w_%=      \n"

            "pad_remain_%=:                 \n"
            "cmp        %[pad_remain], #2   \n"
            "ble        store_pad_1w_%=     \n"
            "vst1.16    {d0[0]}, [%[y0]]!   \n"
            "sub        %[pad_remain], #2   \n"

            "store_pad_1w_%=:               \n"
            "cmp        %[pad_remain], #1   \n"
            "ble        end_%=              \n"
            "vst1.8    {d0[0]}, [%[y0]]!    \n"
            "end_%=:                        \n"
            : [x0] "+r"(x0), [y0] "+r"(y0), [loop] "+r"(loop),
              [remain] "+r"(remain), [pad_loop] "+r"(pad_loop),
              [pad_remain] "+r"(pad_remain)
            : [scale] "r"(scale), [val] "r"(padding_val)
H
hjchen2 已提交
770
            : "cc", "memory", "q0", "q1", "q2", "q3", "q4", "q9");
H
hjchen2 已提交
771 772 773 774 775 776
      }
    }
  }
}
#endif  // __aarch64__
#endif  // ARM_NEON
777

778
template <>
779 780 781 782
bool QuantizeKernel<CPU, float>::Init(QuantizeParam<CPU> *param) {
  return true;
}

783
template <>
L
liuruilong 已提交
784
void QuantizeKernel<CPU, float>::Compute(const QuantizeParam<CPU> &param) {
785
  const Tensor *input = param.input_;
H
hjchen2 已提交
786
  Tensor *output = param.output_;
787
  Tensor *output_scale = param.online_scale_;
H
hjchen2 已提交
788
  float max_abs = 0.f;
789 790 791 792 793
  if (param.is_static_) {
    max_abs = param.static_scale_;
  } else {
    max_abs = find_abs_max(input);
  }
H
hjchen2 已提交
794
  max_abs = std::max(max_abs, 1e-6f);
795
  // only support int8 currently
796 797
  float scale = 127 / max_abs;
  param.online_scale_->mutable_data<float>()[0] = max_abs;
H
hjchen2 已提交
798 799 800 801
  //  const auto &paddings = param.paddings_;
  std::vector<int> paddings = {0, 0};
  //  const auto padding_val = param.padding_val_;
  int8_t padding_val = 127;
802 803
  switch (param.round_type_) {
    case ROUND_NEAREST_TO_EVEN:
H
hjchen2 已提交
804
      quantize_round_to_even(input, scale, paddings, padding_val, output);
805 806
      break;
    case ROUND_NEAREST_TOWARDS_ZERO:
H
hjchen2 已提交
807
      quantize_round_to_zero(input, scale, paddings, padding_val, output);
808 809
      break;
    case ROUND_NEAREST_AWAY_ZERO:
H
hjchen2 已提交
810
      quantize_round_to_nearest(input, scale, paddings, padding_val, output);
811
      break;
812 813 814 815
    default:
      LOG(kLOG_ERROR) << "round type is not supported.";
      break;
  }
816 817 818
}

}  // namespace operators
819
}  // namespace paddle_mobile
820 821

#endif