activation_op.kps 61.4 KB
Newer Older
1
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
L
Luo Tao 已提交
2 3 4 5 6 7 8 9 10
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. */
L
liaogang 已提交
11

Y
Yi Wang 已提交
12
#include "paddle/fluid/operators/activation_op.h"
13 14
#include "paddle/fluid/operators/amp/fp16_type_traits.h"
#include "paddle/fluid/operators/elementwise/elementwise_op_impl.cu.h"
15
#include "paddle/fluid/platform/bfloat16.h"
16
#include "paddle/fluid/platform/device/gpu/gpu_device_function.h"
17

18 19 20
namespace paddle {
namespace operators {

21 22 23 24 25 26 27 28 29 30
template <typename T>
struct CudaLeakyReluFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  float alpha;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"alpha", &alpha}};
  }

  // leakyrelu(x) = x > 0 ? x : alpha * x
31
  __device__ __forceinline__ T operator()(const T x) const {
32
    return x > zero ? x : static_cast<T>(alpha) * x;
33
  }
34 35
};

36 37 38 39 40 41 42 43 44 45
template <typename T>
struct CudaLeakyReluGradFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  float alpha;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"alpha", &alpha}};
  }

  // dx = dout * (x > 0 ? 1 : alpha)
46
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
47
    return x > zero ? dout : static_cast<T>(alpha) * dout;
48 49
  }

50
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
51 52 53
};

template <typename T>
54 55 56 57 58
struct CudaSigmoidFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);

  // sigmoid(x) = 1 / (1 + exp(-x))
59
  __device__ __forceinline__ T operator()(const T arg_x) const {
60
    MPType x = static_cast<MPType>(arg_x);
61 62 63
    return static_cast<T>(one / (one + exp(-x)));
  }
};
64

65 66 67 68 69
template <typename T>
struct CudaSigmoidGradFunctor : public BaseActivationFunctor<T> {
  T one = static_cast<T>(1.0f);

  // dx = dout * out * (1 - out)
70
  __device__ __forceinline__ T operator()(const T dout, const T out) const {
71
    return dout * out * (one - out);
72
  }
73

74 75 76
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kDepOut;
  }
77 78
};

79 80 81 82 83 84
template <typename T>
struct CudaSiluFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);

  // silu(x) = x / (1 + exp(-x))
85
  __device__ __forceinline__ T operator()(const T arg_x) const {
86
    MPType x = static_cast<MPType>(arg_x);
87 88 89
    return static_cast<T>(x / (one + exp(-x)));
  }
};
90 91

template <typename T>
92 93 94 95 96
struct CudaSiluGradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);

  // dx = dout * (1 + exp(-x) + x * exp(-x) / (1 + exp(-x))^2)
97 98
  __device__ __forceinline__ T operator()(const T arg_dout,
                                          const T arg_x) const {
99 100
    MPType dout = static_cast<MPType>(arg_dout);
    MPType x = static_cast<MPType>(arg_x);
101 102 103
    MPType temp = one / (one + exp(-x));
    return static_cast<T>(dout * (temp * (one + x * (one - temp))));
  }
104

105
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
106
};
107

108 109 110 111 112 113 114 115 116
template <typename T>
struct CudaLogSigmoidFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType zero = static_cast<MPType>(0.0f);

  // logsigmoid(x) = log(1 / (1 + exp(-x)))
  // For numerical stability,
  // logsigmoid(x) =
  //          - (max(-x, 0) + log(exp(-max(-x, 0)) + exp(-x - max(-x, 0))))
117
  __device__ __forceinline__ T operator()(const T arg_x) const {
118
    MPType x = static_cast<MPType>(arg_x);
119 120 121 122
    MPType temp = x > zero ? zero : -x;
    return static_cast<T>(-temp - log(exp(-temp) + exp(-x - temp)));
  }
};
123 124

template <typename T>
125 126 127 128 129 130 131 132
struct CudaLogSigmoidGradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType zero = static_cast<MPType>(0.0f);

  // dx = dout * exp(-x) / (1 + exp(-x))
  // For numerical stability:
  // dx = dout * exp(-x - max(-x, 0)) / (exp(-max(-x, 0)) + exp(-x - max(-x,
  // 0)))
133 134
  __device__ __forceinline__ T operator()(const T arg_dout,
                                          const T arg_x) const {
135 136
    MPType dout = static_cast<MPType>(arg_dout);
    MPType x = static_cast<MPType>(arg_x);
137 138 139 140
    MPType temp1 = x > zero ? zero : -x;
    MPType temp2 = exp(-x - temp1);
    return static_cast<T>(dout * (temp2 / (exp(-temp1) + temp2)));
  }
141

142
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
143 144 145 146 147 148 149 150 151 152 153 154 155
};

template <typename T>
struct CudaSoftShrinkFunctor : public BaseActivationFunctor<T> {
  float lambda;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"lambda", &lambda}};
  }

  // softshrink(x) = x - lambda, if x > lambda;
  //                 x + lambda, if x < -lambda;
  //                 0, otherwise.
156
  __device__ __forceinline__ T operator()(const T x) const {
157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173
    T l = static_cast<T>(lambda);
    T temp1 = static_cast<T>(x > l);
    T temp2 = static_cast<T>(x < -l);
    return temp1 * (x - l) + temp2 * (x + l);
  }
};

template <typename T>
struct CudaSoftShrinkGradFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  float lambda;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"lambda", &lambda}};
  }

  // dx = dout, if x > lambda or x < -lambda else 0
174
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
175
    T l = static_cast<T>(lambda);
176
    return (x >= -l && x <= l) ? zero : dout;
177 178
  }

179
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
180 181 182 183 184 185 186
};

template <typename T>
struct CudaCeilFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // ceil(x) = ceil(x)
187
  __device__ __forceinline__ T operator()(const T arg_x) const {
188
    MPType x = static_cast<MPType>(arg_x);
189 190 191 192 193 194 195 196 197
    return static_cast<T>(ceil(x));
  }
};

template <typename T>
struct CudaFloorFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // floor(x) = floor(x)
198
  __device__ __forceinline__ T operator()(const T arg_x) const {
199
    MPType x = static_cast<MPType>(arg_x);
200 201 202 203 204 205 206 207 208
    return static_cast<T>(floor(x));
  }
};

template <typename T>
struct CudaRoundFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // round(x) = round(x)
209
  __device__ __forceinline__ T operator()(const T arg_x) const {
210
    MPType x = static_cast<MPType>(arg_x);
211 212 213 214
    return static_cast<T>(round(x));
  }
};

215
// GradFunctor for ceil, floor and round
216 217
template <typename T>
struct CudaZeroGradFunctor : public BaseActivationFunctor<T> {
218
  __device__ __forceinline__ T operator()(const T x) const {
219 220 221
    return static_cast<T>(0.0f);
  }

222 223
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kNoDeps;
224 225 226 227 228 229 230 231
  }
};

template <typename T>
struct CudaTanhFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // tanh(x) = tanh(x)
232
  __device__ __forceinline__ T operator()(const T arg_x) const {
233
    MPType x = static_cast<MPType>(arg_x);
234
    return static_cast<T>(tanh(x));
235
  }
236
};
237

238 239 240 241 242
template <typename T>
struct CudaTanhGradFunctor : public BaseActivationFunctor<T> {
  T one = static_cast<T>(1.0f);

  // dx = dout * (1 - out^2)
243
  __device__ __forceinline__ T operator()(const T dout, const T out) const {
244
    return dout * (one - out * out);
245 246
  }

247 248
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kDepOut;
X
xiaoting 已提交
249 250 251
  }
};

252 253 254 255 256
template <typename T>
struct CudaReciprocalFunctor : public BaseActivationFunctor<T> {
  T one = static_cast<T>(1.0f);

  // reciprocal(x) = 1 / x
257
  __device__ __forceinline__ T operator()(const T x) const { return one / x; }
258
};
259

260
template <typename T>
261 262
struct CudaReciprocalGradFunctor : public BaseActivationFunctor<T> {
  // dx = -dout * out^2
263
  __device__ __forceinline__ T operator()(const T dout, const T out) const {
264
    return -dout * out * out;
265
  }
266

267 268 269
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kDepOut;
  }
270
};
271

272 273 274 275 276
template <typename T>
struct CudaExpFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // exp(x) = exp(x)
277
  __device__ __forceinline__ T operator()(const T arg_x) const {
278
    MPType x = static_cast<MPType>(arg_x);
279 280 281
    return static_cast<T>(exp(x));
  }
};
282 283

template <typename T>
284 285
struct CudaExpGradFunctor : public BaseActivationFunctor<T> {
  // dx = dout * out
286
  __device__ __forceinline__ T operator()(const T dout, const T out) const {
287
    return dout * out;
288
  }
289

290 291 292
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kDepOut;
  }
293
};
294

R
ronnywang 已提交
295 296 297 298 299
template <typename T>
struct CudaExpm1Functor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // expm1(x) = expm1(x)
300
  __device__ __forceinline__ T operator()(const T arg_x) const {
301
    MPType x = static_cast<MPType>(arg_x);
R
ronnywang 已提交
302 303 304 305 306 307 308
    return static_cast<T>(expm1(x));
  }
};

template <typename T>
struct CudaExpm1GradFunctor : public BaseActivationFunctor<T> {
  // dx = dout * out
309
  __device__ __forceinline__ T operator()(const T dout, const T out) const {
310
    return dout * out + dout;
R
ronnywang 已提交
311 312
  }

313 314 315
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kDepOut;
  }
R
ronnywang 已提交
316 317
};

318 319 320 321 322
template <typename T>
struct CudaLogFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // log(x) = log(x)
323
  __device__ __forceinline__ T operator()(const T arg_x) const {
324
    MPType x = static_cast<MPType>(arg_x);
325 326 327 328 329 330 331
    return static_cast<T>(log(x));
  }
};

template <typename T>
struct CudaLogGradFunctor : public BaseActivationFunctor<T> {
  // dx = dout / x
332
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
333
    return dout / x;
334 335
  }

336
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
337 338 339 340 341
};

template <typename T>
struct CudaSquareFunctor : public BaseActivationFunctor<T> {
  // square(x) = x * x
342
  __device__ __forceinline__ T operator()(const T x) const { return x * x; }
343
};
344

345 346 347 348 349
template <typename T>
struct CudaSquareGradFunctor : public BaseActivationFunctor<T> {
  T two = static_cast<T>(2.0f);

  // dx = dout * 2 * x
350
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
351
    return dout * two * x;
352 353
  }

354
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
355 356
};

357 358 359 360 361
template <typename T>
struct CudaSqrtFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // sqrt(x) = sqrt(x)
362
  __device__ __forceinline__ T operator()(const T arg_x) const {
363
    MPType x = static_cast<MPType>(arg_x);
364 365 366
    return static_cast<T>(sqrt(x));
  }
};
367

368 369 370 371 372
template <typename T>
struct CudaSqrtGradFunctor : public BaseActivationFunctor<T> {
  T one_half = static_cast<T>(0.5f);

  // dx = dout * 0.5 / out
373
  __device__ __forceinline__ T operator()(const T dout, const T out) const {
374
    return one_half * dout / out;
375 376
  }

377 378 379
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kDepOut;
  }
380
};
381

382 383 384 385 386
template <typename T>
struct CudaRsqrtFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // rsqrt(x) = rsqrt(x)
387
  __device__ __forceinline__ T operator()(const T arg_x) const {
388
    MPType x = static_cast<MPType>(arg_x);
389 390 391 392 393 394 395 396
    return static_cast<T>(rsqrt(x));
  }
};

template <typename T>
struct CudaRsqrtGradFunctor : public BaseActivationFunctor<T> {
  T minus_one_half = static_cast<T>(-0.5f);

397
  // dx = -0.5 * dout * out^3
398
  __device__ __forceinline__ T operator()(const T dout, const T out) const {
399
    return minus_one_half * dout * out * out * out;
400 401
  }

402 403 404
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kDepOut;
  }
405
};
406

407 408 409 410 411 412
template <typename T>
struct CudaLog1pFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);

  // log1p(x) = log(1 + x)
413
  __device__ __forceinline__ T operator()(const T arg_x) const {
414
    MPType x = static_cast<MPType>(arg_x);
415 416 417 418 419 420 421 422 423
    return static_cast<T>(log(one + x));
  }
};

template <typename T>
struct CudaLog1pGradFunctor : public BaseActivationFunctor<T> {
  T one = static_cast<T>(1.0f);

  // dx = dout / (1 + x)
424
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
425
    return dout / (one + x);
426 427
  }

428
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
429 430 431 432 433 434 435
};

template <typename T>
struct CudaLog2Functor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // log2(x) = log2(x)
436
  __device__ __forceinline__ T operator()(const T arg_x) const {
437
    MPType x = static_cast<MPType>(arg_x);
438 439 440 441 442 443 444 445 446 447
    return static_cast<T>(log2(x));
  }
};

template <typename T>
struct CudaLog2GradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  T log_two = static_cast<T>(log(static_cast<MPType>(2.0f)));

  // dx = dout / (x * log(2))
448
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
449
    return dout / (x * log_two);
450 451
  }

452
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
453 454 455 456 457 458 459
};

template <typename T>
struct CudaLog10Functor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // log10(x) = log10(x)
460
  __device__ __forceinline__ T operator()(const T arg_x) const {
461
    MPType x = static_cast<MPType>(arg_x);
462 463 464 465 466 467 468 469 470 471
    return static_cast<T>(log10(x));
  }
};

template <typename T>
struct CudaLog10GradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  T log_ten = static_cast<T>(log(static_cast<MPType>(10.0f)));

  // dx = dout / (x * log(10))
472
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
473
    return dout / (x * log_ten);
474 475
  }

476
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
477 478 479 480 481 482 483 484 485 486 487 488
};

template <typename T>
struct CudaBReluFunctor : public BaseActivationFunctor<T> {
  float t_min;
  float t_max;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"t_min", &t_min}, {"t_max", &t_max}};
  }

  // brelu(x) = min(max(x, t_min), t_max)
489
  __device__ __forceinline__ T operator()(const T x) const {
490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508
    T t_min_cast = static_cast<T>(t_min);
    T t_max_cast = static_cast<T>(t_max);
    T temp_max = x > t_min_cast ? x : t_min_cast;
    T temp_min = temp_max < t_max_cast ? temp_max : t_max_cast;
    return temp_min;
  }
};

template <typename T>
struct CudaBReluGradFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  float t_min;
  float t_max;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"t_min", &t_min}, {"t_max", &t_max}};
  }

  // dx = (x > t_min && x < t_max) ? dout : 0
509
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
510 511 512 513 514
    T t_min_cast = static_cast<T>(t_min);
    T t_max_cast = static_cast<T>(t_max);
    return (x > t_min_cast && x < t_max_cast) ? dout : zero;
  }

515
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
516 517 518 519 520 521 522 523 524 525 526 527 528 529
};

template <typename T>
struct CudaSoftReluFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}};
  }

  // soft_relu(x) = log(1 + exp(max(min(x, threshold), -threshold)))
  // threshold should not be negative
530
  __device__ __forceinline__ T operator()(const T arg_x) const {
531
    MPType x = static_cast<MPType>(arg_x);
532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550
    MPType t = static_cast<MPType>(threshold);
    MPType temp_min = x < t ? x : t;
    MPType temp_max = temp_min > -t ? temp_min : -t;
    return static_cast<T>(log(one + exp(temp_max)));
  }
};

template <typename T>
struct CudaSoftReluGradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}};
  }

  // dx = (out > -threshold && out < threshold) ? dout * (1 - exp(-out)) : 0
  // threshold should not be negative
551 552
  __device__ __forceinline__ T operator()(const T arg_dout,
                                          const T arg_out) const {
553 554
    MPType dout = static_cast<MPType>(arg_dout);
    MPType out = static_cast<MPType>(arg_out);
555 556 557 558 559
    MPType t = static_cast<MPType>(threshold);
    return (out > -t && out < t) ? static_cast<T>(dout * (one - exp(-out)))
                                 : static_cast<T>(0.0f);
  }

560 561 562
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kDepOut;
  }
563 564 565 566 567 568 569 570 571 572 573 574 575
};

template <typename T>
struct CudaSTanhFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  float scale_a;
  float scale_b;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"scale_a", &scale_a}, {"scale_b", &scale_b}};
  }

  // stanh(x) = b * tanh(a * x)
576
  __device__ __forceinline__ T operator()(const T arg_x) const {
577
    MPType x = static_cast<MPType>(arg_x);
578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595
    MPType a = static_cast<MPType>(scale_a);
    MPType b = static_cast<MPType>(scale_b);
    return static_cast<T>(b * tanh(a * x));
  }
};

template <typename T>
struct CudaSTanhGradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);
  float scale_a;
  float scale_b;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"scale_a", &scale_a}, {"scale_b", &scale_b}};
  }

  // dx = dout * a * b * (1 - tanh(a * x) * tanh(a * x))
596 597
  __device__ __forceinline__ T operator()(const T arg_dout,
                                          const T arg_x) const {
598 599
    MPType dout = static_cast<MPType>(arg_dout);
    MPType x = static_cast<MPType>(arg_x);
600 601 602 603 604 605
    MPType a = static_cast<MPType>(scale_a);
    MPType b = static_cast<MPType>(scale_b);
    MPType temp = tanh(a * x);
    return static_cast<T>(dout * a * b * (one - temp * temp));
  }

606
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
607 608 609 610 611 612 613 614 615 616 617 618 619 620
};

template <typename T>
struct CudaSoftplusFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);
  float beta;
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"beta", &beta}, {"threshold", &threshold}};
  }

  // softplus(x) = beta * x > threshold ? x : log(1 + exp(beta * x)) / beta
621
  __device__ __forceinline__ T operator()(const T arg_x) const {
622
    MPType x = static_cast<MPType>(arg_x);
623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641
    MPType b = static_cast<MPType>(beta);
    MPType t = static_cast<MPType>(threshold);
    MPType x_beta = x * beta;
    return static_cast<T>(x_beta > t ? x : log(one + exp(x_beta)) / b);
  }
};

template <typename T>
struct CudaSoftplusGradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);
  float beta;
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"beta", &beta}, {"threshold", &threshold}};
  }

  // dx = x * beta > threshold ? dout : dout / (1 + exp(-beta * x))
642 643
  __device__ __forceinline__ T operator()(const T arg_dout,
                                          const T arg_x) const {
644 645
    MPType dout = static_cast<MPType>(arg_dout);
    MPType x = static_cast<MPType>(arg_x);
646 647 648
    MPType b = static_cast<MPType>(beta);
    MPType t = static_cast<MPType>(threshold);
    MPType x_beta = x * beta;
649
    return x_beta > t ? arg_dout : static_cast<T>(dout / (one + exp(-x_beta)));
650 651
  }

652
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
653 654 655 656 657 658 659
};

template <typename T>
struct CudaSoftsignFunctor : public BaseActivationFunctor<T> {
  T one = static_cast<T>(1.0f);

  // softsign(x) = x / (1 + abs(x))
660
  __device__ __forceinline__ T operator()(const T x) const {
661
    return x / (one + abs(x));
662 663 664 665 666 667 668 669
  }
};

template <typename T>
struct CudaSoftsignGradFunctor : public BaseActivationFunctor<T> {
  T one = static_cast<T>(1.0f);

  // dx = dout / (1 + abs(x))^2
670
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
671 672
    T temp = one + abs(x);
    return dout / (temp * temp);
673 674
  }

675
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
676 677 678 679 680 681 682 683 684 685 686 687
};

template <typename T>
struct CudaRelu6Functor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}};
  }

  // relu6(x) = min(max(0, x), 6)
688
  __device__ __forceinline__ T operator()(const T x) const {
689
    T t = static_cast<T>(threshold);
690
    return x <= zero ? zero : (x < t ? x : t);
691 692 693 694 695 696 697 698 699 700 701 702 703
  }
};

template <typename T>
struct CudaRelu6GradFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}};
  }

  // dx = (out > 0 && out < t) ? dout : 0
704
  __device__ __forceinline__ T operator()(const T dout, const T out) const {
705
    T t = static_cast<T>(threshold);
706
    return (out > zero && out < t) ? dout : zero;
707 708
  }

709 710 711
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kDepOut;
  }
712 713 714 715 716 717 718
};

template <typename T>
struct CudaTanhShrinkFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // tanhshrink(x) = x - tanh(x)
719
  __device__ __forceinline__ T operator()(const T arg_x) const {
720
    MPType x = static_cast<MPType>(arg_x);
721 722 723 724 725 726 727 728 729
    return static_cast<T>(x - tanh(x));
  }
};

template <typename T>
struct CudaTanhShrinkGradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;

  // dx = dout * tanh(x)^2
730 731
  __device__ __forceinline__ T operator()(const T arg_dout,
                                          const T arg_x) const {
732 733
    MPType dout = static_cast<MPType>(arg_dout);
    MPType x = static_cast<MPType>(arg_x);
734 735 736
    return static_cast<T>(dout * tanh(x) * tanh(x));
  }

737
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
738 739 740 741 742 743 744 745 746 747 748 749
};

template <typename T>
struct CudaHardShrinkFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}};
  }

  // hadrshrink(x) = (x > -threshold && x < threshold) ? 0 : x
750
  __device__ __forceinline__ T operator()(const T x) const {
751 752 753 754 755 756 757 758 759 760 761 762 763 764 765
    T t = static_cast<T>(threshold);
    return (x > -t && x < t) ? zero : x;
  }
};

template <typename T>
struct CudaHardShrinkGradFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}};
  }

  // dx = (x > -threshold && x < threshold) ? 0 : dout
766
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
767
    T t = static_cast<T>(threshold);
768
    return (x > -t && x < t) ? zero : dout;
769 770
  }

771
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787
};

template <typename T>
struct CudaHardSigmoidFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  T one = static_cast<T>(1.0f);
  float slope;
  float offset;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"slope", &slope}, {"offset", &offset}};
  }

  // hard_sigmoid(x) = 0, when x <= -3
  //                   1, when x >= 3
  //                   x * slope + offset, otherwise
788
  __device__ __forceinline__ T operator()(const T x) const {
789
    T temp = x * static_cast<T>(slope) + static_cast<T>(offset);
790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807
    T temp_max = temp > zero ? temp : zero;
    T temp_min = temp_max < one ? temp_max : one;
    return temp_min;
  }
};

template <typename T>
struct CudaHardSigmoidGradFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  T one = static_cast<T>(1.0f);
  float slope;
  float offset;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"slope", &slope}, {"offset", &offset}};
  }

  // dx = (out > 0 && out < 1) ? dout * slope : 0
808
  __device__ __forceinline__ T operator()(const T dout, const T out) const {
809
    return (out > zero && out < one) ? dout * static_cast<T>(slope) : zero;
810 811
  }

812 813 814
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kDepOut;
  }
815 816 817 818 819 820 821 822 823 824 825 826 827
};

template <typename T>
struct CudaSwishFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);
  float beta;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"beta", &beta}};
  }

  // swish(x) = x / (1 + exp(-beta * x))
828
  __device__ __forceinline__ T operator()(const T arg_x) const {
829
    MPType x = static_cast<MPType>(arg_x);
830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845
    MPType b = static_cast<MPType>(beta);
    return static_cast<T>(x / (one + exp(-b * x)));
  }
};

template <typename T>
struct CudaSwishGradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);
  float beta;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"beta", &beta}};
  }

  // dx = dout * (1 + exp(-b * x) + b * x * exp(-b * x) / (1 + exp(-b * x))^2)
846 847
  __device__ __forceinline__ T operator()(const T arg_dout,
                                          const T arg_x) const {
848 849
    MPType dout = static_cast<MPType>(arg_dout);
    MPType x = static_cast<MPType>(arg_x);
850 851 852 853 854 855 856 857
    MPType b = static_cast<MPType>(beta);
    MPType temp1 = one / (one + exp(-b * x));
    MPType out = x * temp1;
    MPType temp2 = b * out;
    MPType temp3 = temp1 * (one - temp2);
    return static_cast<T>(dout * (temp2 + temp3));
  }

858
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
859 860
};

861 862 863 864 865 866 867 868 869 870 871 872 873 874
template <typename T>
struct CudaMishFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}};
  }

  // mish(x) = x * tanh(softplus(x))
  // softplus(x) = x, if x > threshold
  //             = ln(1 + exp(x)), otherwise
  // Inputs: args[0], the input x
875
  __device__ __forceinline__ T operator()(const T arg_x) const {
876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895
    MPType x = static_cast<MPType>(arg_x);
    MPType sp = (x > static_cast<MPType>(threshold)) ? x : log(one + exp(x));
    return static_cast<T>(x * tanh(sp));
  }
};

template <typename T>
struct CudaMishGradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType one = static_cast<MPType>(1.0f);
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}};
  }

  // dx = dout * (tanh(sp) + x * (1 - tanh(sp) ** 2) * (1 - exp(-sp)))
  // sp = softplus(x)
  // Inputs: args[0], the input dout
  //         args[1], the input x
896 897
  __device__ __forceinline__ T operator()(const T arg_dout,
                                          const T arg_x) const {
898 899 900 901 902 903 904 905 906
    MPType dout = static_cast<MPType>(arg_dout);
    MPType x = static_cast<MPType>(arg_x);
    MPType sp = (x > static_cast<MPType>(threshold)) ? x : log(one + exp(x));
    MPType gsp =
        (x > static_cast<MPType>(threshold)) ? one : one / (one + exp(-x));
    MPType tsp = tanh(sp);
    return static_cast<T>(dout * (tsp + x * (one - tsp * tsp) * gsp));
  }

907
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
908 909
};

910 911 912 913 914 915 916 917 918 919
template <typename T>
struct CudaThresholdedReluFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}};
  }

  // thresholded_relu(x) = x > threshold ? x : 0
920
  __device__ __forceinline__ T operator()(const T x) const {
921
    return x > static_cast<T>(threshold) ? x : zero;
922 923 924 925 926 927 928 929 930 931 932 933 934
  }
};

template <typename T>
struct CudaThresholdedReluGradFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  float threshold;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}};
  }

  // dx = x > threshold ? dout : 0
935
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
936
    return x > static_cast<T>(threshold) ? dout : zero;
937 938
  }

939
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956
};

template <typename T>
struct CudaHardSwishFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  float threshold;
  float scale;
  float offset;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}, {"scale", &scale}, {"offset", &offset}};
  }

  // hard_swish(x) = 0, when x <= -offset
  //                 x , when x >= threshold - offset
  //                 x * (x + offset) / scale, otherwise
  // threshold = scale = 6, offset = 3 by default
957
  __device__ __forceinline__ T operator()(const T x) const {
958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982
    T t = static_cast<T>(threshold);
    T temp = x + static_cast<T>(offset);
    T temp_max = temp > zero ? temp : zero;
    T temp_min = temp_max < t ? temp_max : t;
    return temp_min * x / static_cast<T>(scale);
  }
};

template <typename T>
struct CudaHardSwishGradFunctor : public BaseActivationFunctor<T> {
  T zero = static_cast<T>(0.0f);
  T one = static_cast<T>(1.0f);
  T two = static_cast<T>(2.0f);
  float threshold;
  float scale;
  float offset;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"threshold", &threshold}, {"scale", &scale}, {"offset", &offset}};
  }

  // dx = 0, when x <= -offset
  //      dout , when x >= threshold - offset
  //      dout * (2 * x / scale + offset / scale), otherwise
  // threshold = scale = 6, offset = 3 by default
983
  __device__ __forceinline__ T operator()(const T dout, const T x) const {
984 985 986 987
    T o = static_cast<T>(offset);
    T s = static_cast<T>(scale);
    T temp1 = static_cast<T>(x + o > zero);
    T temp2 = static_cast<T>(x + o < static_cast<T>(threshold));
988
    return dout * (temp1 * temp2 * (two * x + o) / s + one - temp2);
989 990
  }

991
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004
};

template <typename T>
struct CudaELUFunctor : public BaseActivationFunctor<T> {
  using CT = typename details::MPTypeTrait<T>::Type;
  CT zero = static_cast<CT>(0.0f);
  CT one = static_cast<CT>(1.0f);
  float alpha;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"alpha", &alpha}};
  }

Z
zhupengyang 已提交
1005 1006
  // elu(x) = x, if x > 0
  // elu(x) = alpha * (e^x - 1), if x <= 0
1007
  __device__ __forceinline__ T operator()(const T arg_x) const {
1008
    CT x = static_cast<CT>(arg_x);
1009
    CT temp = static_cast<CT>(alpha) * (exp(x) - one);
Z
zhupengyang 已提交
1010
    CT res = x > zero ? x : temp;
1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024
    return static_cast<T>(res);
  }
};

template <typename T>
struct CudaELUGradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType zero = static_cast<MPType>(0.0f);
  float alpha;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"alpha", &alpha}};
  }

Z
zhupengyang 已提交
1025 1026 1027
  // case 1: alpha >= 0
  // dx = dout, if out > 0
  // dx = dout * (out + alpha), if out <= 0
1028
  __device__ __forceinline__ T operator()(T arg_dout, T arg_out) const {
Z
zhupengyang 已提交
1029 1030 1031 1032 1033 1034 1035 1036
    MPType dout = static_cast<MPType>(arg_dout);
    MPType out = static_cast<MPType>(arg_out);
    MPType a = static_cast<MPType>(alpha);
    MPType out_pos = static_cast<MPType>(out > zero);
    MPType out_neg = static_cast<MPType>(out <= zero);
    return static_cast<T>(dout * (out_pos + out_neg * (out + a)));
  }

1037 1038 1039
  static constexpr ActBwdOpFwdDeps FwdDeps() {
    return ActBwdOpFwdDeps::kDepOut;
  }
Z
zhupengyang 已提交
1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054
};

template <typename T>
struct CudaELUGradNegativeAlphaFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType zero = static_cast<MPType>(0.0f);
  float alpha;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"alpha", &alpha}};
  }

  // case 2: alpha < 0
  // dx = dout, if x > 0
  // dx = dout * (out + alpha), if x <=0
1055 1056
  __device__ __forceinline__ T operator()(const T arg_dout, const T arg_out,
                                          const T arg_x) const {
1057
    MPType dout = static_cast<MPType>(arg_dout);
Z
zhupengyang 已提交
1058
    MPType out = static_cast<MPType>(arg_out);
1059
    MPType x = static_cast<MPType>(arg_x);
1060
    MPType a = static_cast<MPType>(alpha);
Z
zhupengyang 已提交
1061 1062 1063
    MPType x_pos = static_cast<MPType>(x > zero);
    MPType x_neg = static_cast<MPType>(x <= zero);
    return static_cast<T>(dout * (x_pos + x_neg * (out + a)));
1064 1065
  }

1066
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
1067 1068
};

Z
zhupengyang 已提交
1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085
template <typename DeviceContext, typename T>
class ELUGradCudaKernel : public framework::OpKernel<T> {
 public:
  void Compute(const framework::ExecutionContext& ctx) const {
    auto* d_out = ctx.Input<framework::Tensor>(framework::GradVarName("Out"));
    auto* out = ctx.Input<framework::Tensor>("Out");
    auto* x = ctx.Input<framework::Tensor>("X");
    auto* d_x = ctx.Output<framework::Tensor>(framework::GradVarName("X"));
    d_x->mutable_data<T>(ctx.GetPlace());
    const float alpha = ctx.Attr<float>("alpha");

    auto& dev_ctx = ctx.device_context<DeviceContext>();
    std::vector<const framework::Tensor*> ins = {d_out, out};
    std::vector<framework::Tensor*> outs = {d_x};
    if (alpha > 0) {
      CudaELUGradFunctor<T> functor;
      functor.alpha = alpha;
1086 1087
      paddle::operators::LaunchSameDimsElementwiseCudaKernel<T>(dev_ctx, ins,
                                                                &outs, functor);
Z
zhupengyang 已提交
1088 1089 1090 1091
    } else {
      CudaELUGradNegativeAlphaFunctor<T> functor;
      functor.alpha = alpha;
      ins.push_back(x);
1092 1093
      paddle::operators::LaunchSameDimsElementwiseCudaKernel<T>(dev_ctx, ins,
                                                                &outs, functor);
Z
zhupengyang 已提交
1094 1095 1096 1097
    }
  }
};

1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109
template <typename T>
struct CudaCELUFunctor : public BaseActivationFunctor<T> {
  using CT = typename details::MPTypeTrait<T>::Type;
  CT zero = static_cast<CT>(0.0f);
  CT one = static_cast<CT>(1.0f);
  float alpha;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"alpha", &alpha}};
  }

  // celu(x) = max(0, x) + min(0, alpha * (exp(x/alpha) - 1))
1110
  __device__ __forceinline__ T operator()(const T arg_x) const {
1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132
    CT x = static_cast<CT>(arg_x);
    CT temp = static_cast<CT>(alpha) * (exp(x / static_cast<CT>(alpha)) - one);
    CT res = (x > zero ? x : zero) + (temp > zero ? zero : temp);
    return static_cast<T>(res);
  }
};

template <typename T>
struct CudaCELUGradFunctor : public BaseActivationFunctor<T> {
  using MPType = typename details::MPTypeTrait<T>::Type;
  MPType zero = static_cast<MPType>(0.0f);
  MPType one = static_cast<MPType>(1.0f);
  float alpha;

  typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
    return {{"alpha", &alpha}};
  }

  // dx = dout, if alpha > 0 and x > 0
  // dx = dout * (x/alpha).exp(), if alpha > 0 and x <= 0
  // dx = dout , if alpha < 0 and x > 0
  // dx = dout * (x/alpha).exp(), if alpha < 0 and x <=0
1133 1134
  __device__ __forceinline__ T operator()(const T arg_dout,
                                          const T arg_x) const {
1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147
    MPType dout = static_cast<MPType>(arg_dout);
    MPType x = static_cast<MPType>(arg_x);
    MPType a = static_cast<MPType>(alpha);
    MPType temp_a_pos = static_cast<MPType>(alpha > 0.0f);
    MPType temp_a_neg = static_cast<MPType>(alpha <= 0.0f);
    MPType temp_x_pos = static_cast<MPType>(x > zero);
    MPType temp_x_neg = static_cast<MPType>(x <= zero);
    return static_cast<T>(
        dout *
        (temp_a_pos * temp_x_pos + temp_a_pos * temp_x_neg * exp(x / a) +
         temp_a_neg * temp_x_pos + exp(x / a) * temp_a_neg * temp_x_neg));
  }

1148
  static constexpr ActBwdOpFwdDeps FwdDeps() { return ActBwdOpFwdDeps::kDepX; }
1149 1150
};

1151
template <typename DeviceContext, typename Functor>
1152
class ActivationCudaKernel
1153 1154 1155
    : public framework::OpKernel<typename Functor::ELEMENT_TYPE> {
 public:
  using T = typename Functor::ELEMENT_TYPE;
1156 1157
  void Compute(const framework::ExecutionContext& ctx) const override {
    const framework::Tensor* x = nullptr;
1158
    framework::Tensor* out = nullptr;
1159 1160 1161 1162 1163 1164
    ExtractActivationTensor(ctx, &x, &out);
    out->mutable_data<T>(ctx.GetPlace());
    auto& dev_ctx = ctx.template device_context<DeviceContext>();
    std::vector<const framework::Tensor*> ins = {x};
    std::vector<framework::Tensor*> outs = {out};
    auto functor = Functor();
1165 1166
    auto attrs = functor.GetAttrs();
    for (auto& attr : attrs) {
1167
      *attr.second = ctx.Attr<float>(attr.first);
1168
    }
1169 1170
    paddle::operators::LaunchSameDimsElementwiseCudaKernel<T>(dev_ctx, ins,
                                                              &outs, functor);
1171 1172 1173 1174
  }
};

template <typename DeviceContext, typename Functor>
1175
class ActivationGradCudaKernel
1176 1177 1178
    : public framework::OpKernel<typename Functor::ELEMENT_TYPE> {
 public:
  using T = typename Functor::ELEMENT_TYPE;
1179
  void Compute(const framework::ExecutionContext& ctx) const override {
1180 1181 1182
    const framework::Tensor *x, *out, *d_out;
    framework::Tensor* d_x = nullptr;
    x = out = d_out = nullptr;
1183
    ExtractActivationGradTensor<Functor::FwdDeps()>(ctx, &x, &out, &d_out,
1184
                                                    &d_x);
1185 1186 1187 1188 1189 1190 1191 1192 1193 1194
    d_x->mutable_data<T>(ctx.GetPlace());
    auto& dev_ctx = ctx.template device_context<DeviceContext>();
    auto functor = Functor();
    auto attrs = functor.GetAttrs();
    for (auto& attr : attrs) {
      *attr.second = ctx.Attr<float>(attr.first);
    }

    std::vector<const framework::Tensor*> ins = {d_out};
    std::vector<framework::Tensor*> outs = {d_x};
1195

1196 1197
    if (static_cast<int>(Functor::FwdDeps()) ==
        static_cast<int>(ActBwdOpFwdDeps::kDepOut)) {
1198
      // Only need forward output Out
1199
      ins.push_back(out);
1200 1201
      paddle::operators::LaunchSameDimsElementwiseCudaKernel<T>(dev_ctx, ins,
                                                                &outs, functor);
1202
    } else if (static_cast<int>(Functor::FwdDeps()) ==
1203
               static_cast<int>(ActBwdOpFwdDeps::kDepX)) {
1204
      // Only need forward input X
1205
      ins.push_back(x);
1206 1207
      paddle::operators::LaunchSameDimsElementwiseCudaKernel<T>(dev_ctx, ins,
                                                                &outs, functor);
1208
    } else {
1209 1210
      paddle::operators::LaunchSameDimsElementwiseCudaKernel<T>(dev_ctx, ins,
                                                                &outs, functor);
1211 1212 1213 1214 1215 1216 1217
    }
  }
};

}  // namespace operators
}  // namespace paddle

1218
namespace ops = paddle::operators;
1219 1220
namespace plat = paddle::platform;

1221 1222
#define REGISTER_ACTIVATION_CUDA_KERNEL(act_type, op_name, functor,            \
                                        grad_functor)                          \
1223
  REGISTER_OP_CUDA_KERNEL(                                                     \
1224 1225 1226 1227 1228
      act_type, ops::ActivationCudaKernel<paddle::platform::CUDADeviceContext, \
                                          ops::functor<float>>,                \
      ops::ActivationCudaKernel<paddle::platform::CUDADeviceContext,           \
                                ops::functor<double>>,                         \
      ops::ActivationCudaKernel<plat::CUDADeviceContext,                       \
1229 1230 1231
                                ops::functor<plat::float16>>,                  \
      ops::ActivationCudaKernel<plat::CUDADeviceContext,                       \
                                ops::functor<plat::bfloat16>>);                \
1232
  REGISTER_OP_CUDA_KERNEL(                                                     \
1233 1234 1235 1236 1237 1238
      act_type##_grad,                                                         \
      ops::ActivationGradCudaKernel<plat::CUDADeviceContext,                   \
                                    ops::grad_functor<float>>,                 \
      ops::ActivationGradCudaKernel<plat::CUDADeviceContext,                   \
                                    ops::grad_functor<double>>,                \
      ops::ActivationGradCudaKernel<plat::CUDADeviceContext,                   \
1239 1240 1241
                                    ops::grad_functor<plat::float16>>,         \
      ops::ActivationGradCudaKernel<plat::CUDADeviceContext,                   \
                                    ops::grad_functor<plat::bfloat16>>);
1242

1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254
#define REGISTER_ACTIVATION_CUDA_KERNEL_INT(act_type, op_name, functor,        \
                                            grad_functor)                      \
  REGISTER_OP_CUDA_KERNEL(                                                     \
      act_type, ops::ActivationCudaKernel<paddle::platform::CUDADeviceContext, \
                                          ops::functor<float>>,                \
      ops::ActivationCudaKernel<paddle::platform::CUDADeviceContext,           \
                                ops::functor<double>>,                         \
      ops::ActivationCudaKernel<paddle::platform::CUDADeviceContext,           \
                                ops::functor<int>>,                            \
      ops::ActivationCudaKernel<paddle::platform::CUDADeviceContext,           \
                                ops::functor<int64_t>>,                        \
      ops::ActivationCudaKernel<plat::CUDADeviceContext,                       \
1255 1256 1257
                                ops::functor<plat::float16>>,                  \
      ops::ActivationCudaKernel<plat::CUDADeviceContext,                       \
                                ops::functor<plat::bfloat16>>);                \
1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268
  REGISTER_OP_CUDA_KERNEL(                                                     \
      act_type##_grad,                                                         \
      ops::ActivationGradCudaKernel<plat::CUDADeviceContext,                   \
                                    ops::grad_functor<float>>,                 \
      ops::ActivationGradCudaKernel<plat::CUDADeviceContext,                   \
                                    ops::grad_functor<double>>,                \
      ops::ActivationGradCudaKernel<plat::CUDADeviceContext,                   \
                                    ops::grad_functor<int>>,                   \
      ops::ActivationGradCudaKernel<plat::CUDADeviceContext,                   \
                                    ops::grad_functor<int64_t>>,               \
      ops::ActivationGradCudaKernel<plat::CUDADeviceContext,                   \
1269 1270 1271
                                    ops::grad_functor<plat::float16>>,         \
      ops::ActivationGradCudaKernel<plat::CUDADeviceContext,                   \
                                    ops::grad_functor<plat::bfloat16>>);
1272

1273
/* ======================== leaky relu register  ============================ */
1274 1275
REGISTER_ACTIVATION_CUDA_KERNEL(leaky_relu, LeakyRelu, CudaLeakyReluFunctor,
                                CudaLeakyReluGradFunctor);
1276 1277 1278 1279 1280 1281 1282 1283 1284

REGISTER_OP_CUDA_KERNEL(
    leaky_relu_grad_grad,
    ops::ActivationDoubleGradKernel<plat::CUDADeviceContext,
                                    ops::LeakyReluGradGradFunctor<float>>,
    ops::ActivationDoubleGradKernel<plat::CUDADeviceContext,
                                    ops::LeakyReluGradGradFunctor<double>>,
    ops::ActivationDoubleGradKernel<
        plat::CUDADeviceContext, ops::LeakyReluGradGradFunctor<plat::float16>>);
1285
/* ========================================================================== */
1286

D
Double_V 已提交
1287
/* ======================== elu register  ============================ */
Z
zhupengyang 已提交
1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298
REGISTER_OP_CUDA_KERNEL(
    elu, ops::ActivationCudaKernel<paddle::platform::CUDADeviceContext,
                                   ops::CudaELUFunctor<float>>,
    ops::ActivationCudaKernel<paddle::platform::CUDADeviceContext,
                              ops::CudaELUFunctor<double>>,
    ops::ActivationCudaKernel<plat::CUDADeviceContext,
                              ops::CudaELUFunctor<plat::float16>>);
REGISTER_OP_CUDA_KERNEL(
    elu_grad, ops::ELUGradCudaKernel<plat::CUDADeviceContext, float>,
    ops::ELUGradCudaKernel<plat::CUDADeviceContext, double>,
    ops::ELUGradCudaKernel<plat::CUDADeviceContext, plat::float16>);
D
Double_V 已提交
1299 1300 1301 1302 1303 1304 1305 1306 1307 1308

REGISTER_OP_CUDA_KERNEL(
    elu_grad_grad, ops::ELUDoubleGradKernel<plat::CUDADeviceContext,
                                            ops::ELUGradGradFunctor<float>>,
    ops::ELUDoubleGradKernel<plat::CUDADeviceContext,
                             ops::ELUGradGradFunctor<double>>,
    ops::ELUDoubleGradKernel<plat::CUDADeviceContext,
                             ops::ELUGradGradFunctor<plat::float16>>);
/* ========================================================================== */

1309 1310 1311 1312 1313 1314 1315 1316 1317 1318 1319 1320 1321
/* ======================== celu register  ============================ */
REGISTER_ACTIVATION_CUDA_KERNEL(celu, CELU, CudaCELUFunctor,
                                CudaCELUGradFunctor);

REGISTER_OP_CUDA_KERNEL(
    celu_grad_grad, ops::CELUDoubleGradKernel<plat::CUDADeviceContext,
                                              ops::CELUGradGradFunctor<float>>,
    ops::CELUDoubleGradKernel<plat::CUDADeviceContext,
                              ops::CELUGradGradFunctor<double>>,
    ops::CELUDoubleGradKernel<plat::CUDADeviceContext,
                              ops::CELUGradGradFunctor<plat::float16>>);
/* ========================================================================== */

1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333
/* ===========================    sigmoid register  ============================
 */
REGISTER_ACTIVATION_CUDA_KERNEL(sigmoid, Sigmoid, CudaSigmoidFunctor,
                                CudaSigmoidGradFunctor);

REGISTER_OP_CUDA_KERNEL(
    sigmoid_grad_grad,
    ops::SigmoidDoubleGradKernel<paddle::platform::CUDADeviceContext,
                                 ops::SigmoidGradGradFunctor<float>>,
    ops::SigmoidDoubleGradKernel<paddle::platform::CUDADeviceContext,
                                 ops::SigmoidGradGradFunctor<double>>,
    ops::SigmoidDoubleGradKernel<plat::CUDADeviceContext,
1334 1335 1336
                                 ops::SigmoidGradGradFunctor<plat::float16>>,
    ops::SigmoidDoubleGradKernel<plat::CUDADeviceContext,
                                 ops::SigmoidGradGradFunctor<plat::bfloat16>>);
1337 1338 1339 1340 1341 1342 1343 1344

REGISTER_OP_CUDA_KERNEL(
    sigmoid_triple_grad,
    ops::SigmoidTripleGradKernel<paddle::platform::CUDADeviceContext,
                                 ops::SigmoidTripleGradFunctor<float>>,
    ops::SigmoidTripleGradKernel<paddle::platform::CUDADeviceContext,
                                 ops::SigmoidTripleGradFunctor<double>>,
    ops::SigmoidTripleGradKernel<plat::CUDADeviceContext,
1345 1346 1347 1348
                                 ops::SigmoidTripleGradFunctor<plat::float16>>,
    ops::SigmoidTripleGradKernel<
        plat::CUDADeviceContext,
        ops::SigmoidTripleGradFunctor<plat::bfloat16>>);
1349 1350
/* ========================================================================== */

1351
/* ===========================    tanh register  ============================ */
1352 1353
REGISTER_ACTIVATION_CUDA_KERNEL(tanh, Tanh, CudaTanhFunctor,
                                CudaTanhGradFunctor);
1354 1355 1356 1357 1358 1359 1360 1361 1362

REGISTER_OP_CUDA_KERNEL(
    tanh_grad_grad,
    ops::TanhDoubleGradKernel<paddle::platform::CUDADeviceContext,
                              ops::TanhGradGradFunctor<float>>,
    ops::TanhDoubleGradKernel<paddle::platform::CUDADeviceContext,
                              ops::TanhGradGradFunctor<double>>,
    ops::TanhDoubleGradKernel<plat::CUDADeviceContext,
                              ops::TanhGradGradFunctor<plat::float16>>);
1363 1364 1365 1366 1367 1368 1369 1370 1371

REGISTER_OP_CUDA_KERNEL(
    tanh_triple_grad,
    ops::TanhTripeGradKernel<paddle::platform::CUDADeviceContext,
                             ops::TanhTripleGradFunctor<float>>,
    ops::TanhTripeGradKernel<paddle::platform::CUDADeviceContext,
                             ops::TanhTripleGradFunctor<double>>,
    ops::TanhTripeGradKernel<plat::CUDADeviceContext,
                             ops::TanhTripleGradFunctor<plat::float16>>);
1372 1373
/* ========================================================================== */

L
lvmengsi 已提交
1374
/* ===========================   sqrt register  ============================= */
1375 1376
REGISTER_ACTIVATION_CUDA_KERNEL(sqrt, Sqrt, CudaSqrtFunctor,
                                CudaSqrtGradFunctor);
L
lvmengsi 已提交
1377 1378 1379 1380 1381 1382 1383 1384

REGISTER_OP_CUDA_KERNEL(
    sqrt_grad_grad,
    ops::SqrtDoubleGradKernel<paddle::platform::CUDADeviceContext,
                              ops::SqrtGradGradFunctor<float>>,
    ops::SqrtDoubleGradKernel<paddle::platform::CUDADeviceContext,
                              ops::SqrtGradGradFunctor<double>>,
    ops::SqrtDoubleGradKernel<paddle::platform::CUDADeviceContext,
1385 1386 1387
                              ops::SqrtGradGradFunctor<plat::float16>>,
    ops::SqrtDoubleGradKernel<paddle::platform::CUDADeviceContext,
                              ops::SqrtGradGradFunctor<plat::bfloat16>>);
L
lvmengsi 已提交
1388 1389
/* ========================================================================== */

W
whs 已提交
1390 1391
/* ===========================   rsqrt register  =============================
 */
1392 1393
REGISTER_ACTIVATION_CUDA_KERNEL(rsqrt, Rsqrt, CudaRsqrtFunctor,
                                CudaRsqrtGradFunctor);
W
whs 已提交
1394 1395 1396 1397 1398 1399 1400 1401 1402 1403 1404

REGISTER_OP_CUDA_KERNEL(
    rsqrt_grad_grad,
    ops::RsqrtDoubleGradKernel<paddle::platform::CUDADeviceContext,
                               ops::RsqrtGradGradFunctor<float>>,
    ops::RsqrtDoubleGradKernel<paddle::platform::CUDADeviceContext,
                               ops::RsqrtGradGradFunctor<double>>,
    ops::RsqrtDoubleGradKernel<paddle::platform::CUDADeviceContext,
                               ops::RsqrtGradGradFunctor<plat::float16>>);
/* ========================================================================== */

1405
/* ===========================  square register  ============================ */
1406 1407
REGISTER_ACTIVATION_CUDA_KERNEL_INT(square, Square, CudaSquareFunctor,
                                    CudaSquareGradFunctor);
1408 1409 1410 1411 1412 1413 1414 1415

REGISTER_OP_CUDA_KERNEL(
    square_grad_grad,
    ops::SquareDoubleGradKernel<paddle::platform::CUDADeviceContext,
                                ops::SquareGradGradFunctor<float>>,
    ops::SquareDoubleGradKernel<paddle::platform::CUDADeviceContext,
                                ops::SquareGradGradFunctor<double>>,
    ops::SquareDoubleGradKernel<plat::CUDADeviceContext,
1416
                                ops::SquareGradGradFunctor<plat::float16>>,
1417 1418
    ops::SquareDoubleGradKernel<plat::CUDADeviceContext,
                                ops::SquareGradGradFunctor<plat::bfloat16>>,
1419 1420 1421 1422
    ops::SquareDoubleGradKernel<paddle::platform::CUDADeviceContext,
                                ops::SquareGradGradFunctor<int>>,
    ops::SquareDoubleGradKernel<paddle::platform::CUDADeviceContext,
                                ops::SquareGradGradFunctor<int64_t>>);
1423
/* ========================================================================== */
1424 1425 1426 1427 1428

/* ==========================   pow register  ============================ */
REGISTER_OP_CUDA_KERNEL(
    pow, ops::PowKernel<plat::CUDADeviceContext, ops::PowFunctor<float>>,
    ops::PowKernel<plat::CUDADeviceContext, ops::PowFunctor<double>>,
1429 1430
    ops::PowKernel<plat::CUDADeviceContext, ops::PowFunctor<int>>,
    ops::PowKernel<plat::CUDADeviceContext, ops::PowFunctor<int64_t>>,
1431 1432 1433 1434 1435
    ops::PowKernel<plat::CUDADeviceContext, ops::PowFunctor<plat::float16>>);
REGISTER_OP_CUDA_KERNEL(
    pow_grad,
    ops::PowGradKernel<plat::CUDADeviceContext, ops::PowGradFunctor<float>>,
    ops::PowGradKernel<plat::CUDADeviceContext, ops::PowGradFunctor<double>>,
1436 1437
    ops::PowGradKernel<plat::CUDADeviceContext, ops::PowGradFunctor<int>>,
    ops::PowGradKernel<plat::CUDADeviceContext, ops::PowGradFunctor<int64_t>>,
1438 1439 1440
    ops::PowGradKernel<plat::CUDADeviceContext,
                       ops::PowGradFunctor<plat::float16>>);
/* ========================================================================== */
1441

W
wangzhen38 已提交
1442 1443 1444 1445 1446 1447 1448 1449 1450 1451 1452 1453 1454 1455 1456
/* ==========================   logit register  ============================ */
namespace ops = paddle::operators;
REGISTER_OP_CUDA_KERNEL(
    logit, ops::LogitKernel<paddle::platform::CUDADeviceContext, float>,
    ops::LogitKernel<paddle::platform::CUDADeviceContext, double>,
    ops::LogitKernel<paddle::platform::CUDADeviceContext,
                     paddle::platform::float16>);
REGISTER_OP_CUDA_KERNEL(
    logit_grad,
    ops::LogitGradKernel<paddle::platform::CUDADeviceContext, float>,
    ops::LogitGradKernel<paddle::platform::CUDADeviceContext, double>,
    ops::LogitGradKernel<paddle::platform::CUDADeviceContext,
                         paddle::platform::float16>);
/* ========================================================================== */

1457 1458
/* ==========================   exp register  ============================ */
REGISTER_OP_CUDA_KERNEL(
1459 1460 1461 1462
    exp, ops::ActivationCudaKernel<plat::CUDADeviceContext,
                                   ops::CudaExpFunctor<float>>,
    ops::ActivationCudaKernel<plat::CUDADeviceContext,
                              ops::CudaExpFunctor<double>>,
1463 1464
    ops::ActivationKernel<plat::CUDADeviceContext, ops::ExpFunctor<int>>,
    ops::ActivationKernel<plat::CUDADeviceContext, ops::ExpFunctor<int64_t>>,
1465 1466
    ops::ActivationCudaKernel<plat::CUDADeviceContext,
                              ops::CudaExpFunctor<plat::float16>>);
1467
REGISTER_OP_CUDA_KERNEL(
1468 1469 1470 1471 1472 1473 1474 1475 1476 1477
    exp_grad, ops::ActivationGradCudaKernel<plat::CUDADeviceContext,
                                            ops::CudaExpGradFunctor<float>>,
    ops::ActivationGradCudaKernel<plat::CUDADeviceContext,
                                  ops::CudaExpGradFunctor<double>>,
    ops::ActivationGradCudaKernel<plat::CUDADeviceContext,
                                  ops::CudaExpGradFunctor<int>>,
    ops::ActivationGradCudaKernel<plat::CUDADeviceContext,
                                  ops::CudaExpGradFunctor<int64_t>>,
    ops::ActivationGradCudaKernel<plat::CUDADeviceContext,
                                  ops::CudaExpGradFunctor<plat::float16>>);
1478 1479
/* ========================================================================== */

R
ronnywang 已提交
1480 1481 1482 1483 1484 1485 1486 1487 1488 1489 1490 1491 1492 1493 1494 1495 1496 1497
/* ==========================   expm1 register  ============================ */

REGISTER_OP_CUDA_KERNEL(
    expm1, ops::ActivationCudaKernel<plat::CUDADeviceContext,
                                     ops::CudaExpm1Functor<float>>,
    ops::ActivationCudaKernel<plat::CUDADeviceContext,
                              ops::CudaExpm1Functor<double>>,
    ops::ActivationCudaKernel<plat::CUDADeviceContext,
                              ops::CudaExpm1Functor<plat::float16>>);
REGISTER_OP_CUDA_KERNEL(
    expm1_grad, ops::ActivationGradCudaKernel<plat::CUDADeviceContext,
                                              ops::CudaExpm1GradFunctor<float>>,
    ops::ActivationGradCudaKernel<plat::CUDADeviceContext,
                                  ops::CudaExpm1GradFunctor<double>>,
    ops::ActivationGradCudaKernel<plat::CUDADeviceContext,
                                  ops::CudaExpm1GradFunctor<plat::float16>>);
/* ========================================================================== */

1498
/* ==========================  Log register ==================================*/
1499
REGISTER_ACTIVATION_CUDA_KERNEL(log, Log, CudaLogFunctor, CudaLogGradFunctor);
1500 1501 1502 1503 1504 1505 1506 1507 1508

REGISTER_OP_CUDA_KERNEL(
    log_grad_grad, ops::LogDoubleGradKernel<plat::CUDADeviceContext,
                                            ops::LogGradGradFunctor<float>>,
    ops::LogDoubleGradKernel<plat::CUDADeviceContext,
                             ops::LogGradGradFunctor<double>>,
    ops::LogDoubleGradKernel<plat::CUDADeviceContext,
                             ops::LogGradGradFunctor<plat::float16>>);
/* ========================================================================== */
1509

1510 1511 1512 1513 1514 1515 1516 1517 1518 1519 1520 1521 1522 1523 1524 1525 1526 1527 1528 1529 1530 1531 1532 1533 1534 1535 1536
#define FOR_EACH_ACTIVATION_CUDA_OP(__macro)                                  \
  __macro(silu, Silu, CudaSiluFunctor, CudaSiluGradFunctor);                  \
  __macro(logsigmoid, LogSigmoid, CudaLogSigmoidFunctor,                      \
          CudaLogSigmoidGradFunctor);                                         \
  __macro(softshrink, SoftShrink, CudaSoftShrinkFunctor,                      \
          CudaSoftShrinkGradFunctor);                                         \
  __macro(ceil, Ceil, CudaCeilFunctor, CudaZeroGradFunctor);                  \
  __macro(floor, Floor, CudaFloorFunctor, CudaZeroGradFunctor);               \
  __macro(round, Round, CudaRoundFunctor, CudaZeroGradFunctor);               \
  __macro(reciprocal, Reciprocal, CudaReciprocalFunctor,                      \
          CudaReciprocalGradFunctor);                                         \
  __macro(log1p, Log1p, CudaLog1pFunctor, CudaLog1pGradFunctor);              \
  __macro(log2, Log2, CudaLog2Functor, CudaLog2GradFunctor);                  \
  __macro(log10, Log10, CudaLog10Functor, CudaLog10GradFunctor);              \
  __macro(brelu, BRelu, CudaBReluFunctor, CudaBReluGradFunctor);              \
  __macro(soft_relu, SoftRelu, CudaSoftReluFunctor, CudaSoftReluGradFunctor); \
  __macro(stanh, STanh, CudaSTanhFunctor, CudaSTanhGradFunctor);              \
  __macro(softplus, Softplus, CudaSoftplusFunctor, CudaSoftplusGradFunctor);  \
  __macro(softsign, Softsign, CudaSoftsignFunctor, CudaSoftsignGradFunctor);  \
  __macro(relu6, Relu6, CudaRelu6Functor, CudaRelu6GradFunctor);              \
  __macro(tanh_shrink, TanhShrink, CudaTanhShrinkFunctor,                     \
          CudaTanhShrinkGradFunctor);                                         \
  __macro(hard_shrink, HardShrink, CudaHardShrinkFunctor,                     \
          CudaHardShrinkGradFunctor);                                         \
  __macro(hard_sigmoid, HardSigmoid, CudaHardSigmoidFunctor,                  \
          CudaHardSigmoidGradFunctor);                                        \
  __macro(swish, Swish, CudaSwishFunctor, CudaSwishGradFunctor);              \
1537
  __macro(mish, Mish, CudaMishFunctor, CudaMishGradFunctor);                  \
1538 1539 1540 1541 1542
  __macro(thresholded_relu, ThresholdedRelu, CudaThresholdedReluFunctor,      \
          CudaThresholdedReluGradFunctor);                                    \
  __macro(hard_swish, HardSwish, CudaHardSwishFunctor,                        \
          CudaHardSwishGradFunctor);
FOR_EACH_ACTIVATION_CUDA_OP(REGISTER_ACTIVATION_CUDA_KERNEL)
1543 1544 1545 1546 1547 1548 1549 1550 1551 1552 1553 1554 1555 1556 1557 1558 1559 1560 1561 1562 1563 1564 1565 1566 1567 1568 1569 1570 1571 1572 1573 1574 1575 1576 1577 1578 1579 1580 1581 1582 1583 1584 1585 1586 1587 1588 1589 1590 1591 1592 1593 1594 1595 1596 1597 1598 1599 1600 1601 1602 1603 1604

#ifdef PADDLE_WITH_XPU_KP
#define REGISTER_ACTIVATION_XPU_KERNEL(act_type, op_name, functor,             \
                                       grad_functor)                           \
  REGISTER_OP_KERNEL(                                                          \
      act_type, KP, plat::XPUPlace,                                            \
      ops::ActivationCudaKernel<plat::XPUDeviceContext, ops::functor<float>>); \
  REGISTER_OP_KERNEL(act_type##_grad, KP, plat::XPUPlace,                      \
                     ops::ActivationGradCudaKernel<plat::XPUDeviceContext,     \
                                                   ops::grad_functor<float>>);

REGISTER_ACTIVATION_XPU_KERNEL(leaky_relu, LeakyRelu, CudaLeakyReluFunctor,
                               CudaLeakyReluGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(sigmoid, Sigmoid, CudaSigmoidFunctor,
                               CudaSigmoidGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(exp, Exp, CudaExpFunctor, CudaExpGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(log, Log, CudaLogFunctor, CudaLogGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(reciprocal, Reciprocal, CudaReciprocalFunctor,
                               CudaReciprocalGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(softplus, Softplus, CudaSoftplusFunctor,
                               CudaSoftplusGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(hard_swish, HardSwish, CudaHardSwishFunctor,
                               CudaHardSwishGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(elu, Elu, CudaELUFunctor, CudaELUGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(celu, Celu, CudaCELUFunctor,
                               CudaCELUGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(sqrt, Sqrt, CudaSqrtFunctor,
                               CudaSqrtGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(square, Square, CudaSquareFunctor,
                               CudaSquareGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(silu, Silu, CudaSiluFunctor,
                               CudaSiluGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(logsigmoid, LogSigmoid, CudaLogSigmoidFunctor,
                               CudaLogSigmoidGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(softshrink, SoftShrink, CudaSoftShrinkFunctor,
                               CudaSoftShrinkGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(ceil, Ceil, CudaCeilFunctor,
                               CudaZeroGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(floor, Floor, CudaFloorFunctor,
                               CudaZeroGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(log1p, Log1p, CudaLog1pFunctor,
                               CudaLog1pGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(brelu, BRelu, CudaBReluFunctor,
                               CudaBReluGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(soft_relu, SoftRelu, CudaSoftReluFunctor,
                               CudaSoftReluGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(softsign, Softsign, CudaSoftsignFunctor,
                               CudaSoftsignGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(relu6, Relu6, CudaRelu6Functor,
                               CudaRelu6GradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(hard_shrink, HardShrink, CudaHardShrinkFunctor,
                               CudaHardShrinkGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(hard_sigmoid, HardSigmoid,
                               CudaHardSigmoidFunctor,
                               CudaHardSigmoidGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(swish, Swish, CudaSwishFunctor,
                               CudaSwishGradFunctor);
REGISTER_ACTIVATION_XPU_KERNEL(thresholded_relu, ThresholdedRelu,
                               CudaThresholdedReluFunctor,
                               CudaThresholdedReluGradFunctor);

#endif  // PADDLE_WITH_XPU_KP