forked from PaddlePaddle/Paddle
-
Notifications
You must be signed in to change notification settings - Fork 0
/
elementwise_functor.h
588 lines (524 loc) · 16.8 KB
/
elementwise_functor.h
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
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
376
377
378
379
380
381
382
383
384
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
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
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
499
500
501
502
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
583
584
585
586
587
588
/* Copyright (c) 2021 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. */
#pragma once
#include "paddle/phi/common/complex.h"
#include "paddle/phi/common/float16.h"
#include "paddle/phi/core/enforce.h"
#include "paddle/phi/core/hostdevice.h"
namespace phi {
namespace funcs {
// Define the binary functors used in elementwise ops.
// Note: InverseXxxFunctor is needed when calling ElementwiseComputeEx on CPU.
// Add
template <typename T>
struct AddFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const { return a + b; }
};
template <typename T>
struct InverseAddFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const { return b + a; }
};
// Subtract
template <typename T>
struct SubtractFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const { return a - b; }
};
template <typename T>
struct InverseSubtractFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const { return b - a; }
};
// Multiply
template <typename T>
struct MultiplyFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const { return a * b; }
};
template <>
struct MultiplyFunctor<bool> {
inline HOSTDEVICE bool operator()(const bool a, const bool b) const {
return a && b;
}
};
template <typename T>
struct InverseMultiplyFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const { return b * a; }
};
template <>
struct InverseMultiplyFunctor<bool> {
inline HOSTDEVICE bool operator()(const bool a, const bool b) const {
return b && a;
}
};
template <typename T>
struct IsZeroFunctor {
HOSTDEVICE bool operator()(T x) const { return x == static_cast<T>(0); }
};
// Divide
#define DIV_ERROR_INFO \
"InvalidArgumentError: Integer division by zero encountered in " \
"(floor) divide. Please check the input value."
template <typename T, typename Enable = void>
struct DivideFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const { return a / b; }
};
template <typename T>
struct DivideFunctor<
T,
typename std::enable_if<std::is_integral<T>::value>::type> {
inline HOSTDEVICE T operator()(const T a, const T b) const {
// For int32/int64, need to check whether the divison is zero.
PADDLE_ENFORCE(b != 0, DIV_ERROR_INFO);
return a / b;
}
};
template <typename T, typename Enable = void>
struct InverseDivideFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const { return b / a; }
};
template <typename T>
using ComplexType = phi::dtype::complex<T>;
template <typename InT, typename OutT>
struct DivGradXYFunctor {
inline HOSTDEVICE phi::Array<OutT, 2> operator()(const InT a,
const InT b,
const InT c) {
// dx = dout / y
// dy = - dout * out / y
phi::Array<OutT, 2> outs;
outs[0] = a / c;
outs[1] = -a * b / c;
return outs;
}
};
template <typename InT, typename OutT>
struct DivGradXYFunctor<ComplexType<InT>, ComplexType<OutT>> {
inline HOSTDEVICE phi::Array<ComplexType<OutT>, 2> operator()(
const ComplexType<InT> a,
const ComplexType<InT> b,
const ComplexType<InT> c) {
phi::Array<ComplexType<OutT>, 2> outs;
ComplexType<InT> c_conj(c.real, -c.imag);
ComplexType<InT> out_div_c_conj((b / c).real, -(b / c).imag);
outs[0] = a / c_conj;
outs[1] = -a * out_div_c_conj;
return outs;
}
};
// Float div grad
template <typename T>
struct DivGradXFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const { return a / b; }
};
// ComplexType div grad
template <typename T>
struct DivGradXFunctor<ComplexType<T>> {
inline HOSTDEVICE ComplexType<T> operator()(const ComplexType<T> a,
const ComplexType<T> b) const {
ComplexType<T> b_conj(b.real, -b.imag);
return a / b_conj;
}
};
// Float mul and div
template <typename T>
struct DivGradYFunctor {
inline HOSTDEVICE T operator()(const T a, const T b, const T c) const {
return -a * b / c;
}
};
// ComplexType mul and div
template <typename T>
struct DivGradYFunctor<ComplexType<T>> {
inline HOSTDEVICE ComplexType<T> operator()(const ComplexType<T> a,
const ComplexType<T> b,
const ComplexType<T> c) const {
ComplexType<T> out_div_c_conj((b / c).real, -(b / c).imag);
return -a * out_div_c_conj;
}
};
// Fmin
template <typename T>
struct FMinFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const {
return std::fmin(a, b);
}
};
template <>
struct FMinFunctor<dtype::float16> {
inline HOSTDEVICE dtype::float16 operator()(const dtype::float16 a,
const dtype::float16 b) const {
float float_a = static_cast<float>(a);
float float_b = static_cast<float>(b);
auto result = std::fmin(float_a, float_b);
return static_cast<dtype::float16>(result);
}
};
template <>
struct FMinFunctor<int> {
inline HOSTDEVICE int operator()(const int a, const int b) const {
float float_a = static_cast<float>(a);
float float_b = static_cast<float>(b);
auto result = std::fmin(float_a, float_b);
return std::lrint(result);
}
};
template <>
struct FMinFunctor<int64_t> {
inline HOSTDEVICE int64_t operator()(const int64_t a, const int64_t b) const {
double double_a = static_cast<double>(a);
double double_b = static_cast<double>(b);
auto result = std::fmin(double_a, double_b);
return std::llrint(result);
}
};
// Fmax
template <typename T>
struct FMaxFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const {
return std::fmax(a, b);
}
};
template <>
struct FMaxFunctor<dtype::float16> {
inline HOSTDEVICE dtype::float16 operator()(const dtype::float16 a,
const dtype::float16 b) const {
float float_a = static_cast<float>(a);
float float_b = static_cast<float>(b);
auto result = std::fmax(float_a, float_b);
return static_cast<dtype::float16>(result);
}
};
template <>
struct FMaxFunctor<int> {
inline HOSTDEVICE int operator()(const int a, const int b) const {
float float_a = static_cast<float>(a);
float float_b = static_cast<float>(b);
auto result = std::fmax(float_a, float_b);
return std::lrint(result);
}
};
template <>
struct FMaxFunctor<int64_t> {
inline HOSTDEVICE int64_t operator()(const int64_t a, const int64_t b) const {
double double_a = static_cast<double>(a);
double double_b = static_cast<double>(b);
auto result = std::fmax(double_a, double_b);
return std::llrint(result);
}
};
template <typename T>
struct FMaxGradDx {
HOSTDEVICE T operator()(T x, T y, T out, T dout) const {
return dout * static_cast<T>((x >= y) || isnan(y));
}
};
template <>
struct FMaxGradDx<dtype::float16> {
HOSTDEVICE dtype::float16 operator()(dtype::float16 x,
dtype::float16 y,
dtype::float16 out,
dtype::float16 dout) const {
return dout * static_cast<dtype::float16>((x >= y) || dtype::isnan(y));
}
};
template <>
struct FMaxGradDx<int> {
HOSTDEVICE int operator()(int x, int y, int out, int dout) const {
return dout * static_cast<int>((x >= y));
}
};
template <>
struct FMaxGradDx<int64_t> {
HOSTDEVICE int64_t operator()(int64_t x,
int64_t y,
int64_t out,
int64_t dout) const {
return dout * static_cast<int64_t>((x >= y));
}
};
template <typename T>
struct FMaxGradDy {
HOSTDEVICE T operator()(T x, T y, T out, T dout) const {
return dout * static_cast<T>(!((x >= y) || isnan(y)));
}
};
template <>
struct FMaxGradDy<dtype::float16> {
HOSTDEVICE dtype::float16 operator()(dtype::float16 x,
dtype::float16 y,
dtype::float16 out,
dtype::float16 dout) const {
return dout * static_cast<dtype::float16>(!((x >= y) || dtype::isnan(y)));
}
};
template <>
struct FMaxGradDy<int64_t> {
HOSTDEVICE int64_t operator()(int64_t x,
int64_t y,
int64_t out,
int64_t dout) const {
return dout * static_cast<int64_t>(!((x >= y)));
}
};
template <>
struct FMaxGradDy<int> {
HOSTDEVICE int operator()(int x, int y, int out, int dout) const {
return dout * static_cast<int>(!((x >= y)));
}
};
template <typename T>
struct FMinGradDx {
HOSTDEVICE T operator()(T x, T y, T out, T dout) const {
return dout * static_cast<T>((x <= y) || isnan(y));
}
};
template <>
struct FMinGradDx<dtype::float16> {
HOSTDEVICE dtype::float16 operator()(dtype::float16 x,
dtype::float16 y,
dtype::float16 out,
dtype::float16 dout) const {
return dout * static_cast<dtype::float16>((x <= y) || dtype::isnan(y));
}
};
template <>
struct FMinGradDx<int> {
HOSTDEVICE int operator()(int x, int y, int out, int dout) const {
return dout * static_cast<int>((x <= y));
}
};
template <>
struct FMinGradDx<int64_t> {
HOSTDEVICE int64_t operator()(int64_t x,
int64_t y,
int64_t out,
int64_t dout) const {
return dout * static_cast<int64_t>((x <= y));
}
};
template <typename T>
struct FMinGradDy {
HOSTDEVICE T operator()(T x, T y, T out, T dout) const {
return dout * static_cast<T>(!((x <= y) || isnan(y)));
}
};
template <>
struct FMinGradDy<dtype::float16> {
HOSTDEVICE dtype::float16 operator()(dtype::float16 x,
dtype::float16 y,
dtype::float16 out,
dtype::float16 dout) const {
return dout * static_cast<dtype::float16>(!((x <= y) || dtype::isnan(y)));
}
};
template <>
struct FMinGradDy<int> {
HOSTDEVICE int operator()(int x, int y, int out, int dout) const {
return dout * static_cast<int>(!((x <= y)));
}
};
template <>
struct FMinGradDy<int64_t> {
HOSTDEVICE int64_t operator()(int64_t x,
int64_t y,
int64_t out,
int64_t dout) const {
return dout * static_cast<int64_t>(!((x <= y)));
}
};
template <typename T>
struct MultiplyGradFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const { return a * b; }
};
template <typename T>
struct MultiplyGradFunctor<ComplexType<T>> {
inline HOSTDEVICE ComplexType<T> operator()(const ComplexType<T> a,
const ComplexType<T> b) const {
ComplexType<T> b_conj(b.real, -b.imag);
return a * b_conj;
}
};
template <typename InT, typename OutT>
struct MultiplyGradXYFunctor {
inline HOSTDEVICE phi::Array<OutT, 2> operator()(const InT a,
const InT b,
const InT c) {
phi::Array<OutT, 2> outs;
// dx = dout * y
outs[0] = a * b;
// dy = dout * x
outs[1] = a * c;
return outs;
}
};
template <typename InT, typename OutT>
struct MultiplyGradXYFunctor<ComplexType<InT>, ComplexType<OutT>> {
inline HOSTDEVICE phi::Array<ComplexType<OutT>, 2> operator()(
const ComplexType<InT> a,
const ComplexType<InT> b,
const ComplexType<InT> c) {
phi::Array<ComplexType<OutT>, 2> outs;
// dx = dout * y
ComplexType<InT> b_conj(b.real, -b.imag);
outs[0] = a * b_conj;
// dy = dout * x
ComplexType<InT> c_conj(c.real, -c.imag);
outs[1] = a * c_conj;
return outs;
}
};
// Maximum
template <typename T>
struct MaximumFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const {
return a > b ? a : b;
}
};
template <typename T>
struct MaxGradXFunctor {
inline HOSTDEVICE T operator()(const T x, const T y, const T dout) const {
return dout * static_cast<T>(x > y);
}
};
template <typename T>
struct MaxGradYFunctor {
inline HOSTDEVICE T operator()(const T x, const T y, const T dout) const {
return dout * static_cast<T>(x <= y);
}
};
template <typename InT, typename OutT>
struct MaxGradXYFunctor {
inline HOSTDEVICE phi::Array<OutT, 2> operator()(const InT x,
const InT y,
const InT dout) {
phi::Array<OutT, 2> outs;
// dx = dout * (x > y)
outs[0] = static_cast<OutT>(dout * static_cast<InT>(x > y));
// dy = dout * (x <= y)
outs[1] = static_cast<OutT>(dout * static_cast<InT>(x <= y));
return outs;
}
};
// Minimum
template <typename T>
struct MinimumFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const {
return a < b ? a : b;
}
};
template <typename T>
struct MinGradXFunctor {
inline HOSTDEVICE T operator()(const T x, const T y, const T dout) const {
return dout * static_cast<T>(x < y);
}
};
template <typename T>
struct MinGradYFunctor {
inline HOSTDEVICE T operator()(const T x, const T y, const T dout) const {
return dout * static_cast<T>(x >= y);
}
};
template <typename InT, typename OutT>
struct MinGradXYFunctor {
inline HOSTDEVICE phi::Array<OutT, 2> operator()(const InT x,
const InT y,
const InT dout) {
phi::Array<OutT, 2> outs;
// dx = dout * (x < y)
outs[0] = static_cast<OutT>(dout * static_cast<InT>(x < y));
// dy = dout * (x >= y)
outs[1] = static_cast<OutT>(dout * static_cast<InT>(x >= y));
return outs;
}
};
// Modulo
template <typename T, typename Enable = void>
struct ModuloFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const {
T res = a % b;
// Accoding to #PR26732: in dividen % divsor
// remainder shall have the same sign as divsor.
if ((res != 0) && ((b ^ res) < 0)) res += b;
return res;
}
};
template <typename T>
struct ModuloFunctor<
T,
typename std::enable_if_t<std::is_floating_point<T>::value>> {
inline HOSTDEVICE T operator()(const T a, const T b) const {
T res = fmod(a, b);
// Accoding to #PR26732: in dividen % divsor
// remainder shall have the same sign as divsor.
if ((res != 0) && ((res < 0) != (b < 0))) res += b;
return res;
}
};
template <typename T, typename Enable = void>
struct InverseModuloFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const {
T res = b % a;
if ((res != 0) && ((res < 0) != (a < 0))) res += a;
return res;
}
};
template <typename T>
struct InverseModuloFunctor<
T,
typename std::enable_if_t<std::is_floating_point<T>::value>> {
inline HOSTDEVICE T operator()(const T a, const T b) const {
T res = fmod(b, a);
if ((res != 0) && ((a < 0) != (res < 0))) res += a;
return res;
}
};
template <typename T>
struct ElementwiseHeavisideFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const {
return a == static_cast<T>(0) ? b : static_cast<T>(a > 0);
}
};
template <typename T>
struct FloorDivideFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const {
#ifndef PADDLE_WITH_XPU_KP
PADDLE_ENFORCE(b != 0, DIV_ERROR_INFO);
#endif
return static_cast<T>(std::trunc(a / b));
}
};
template <typename T>
struct InverseFloorDivideFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const {
#ifndef PADDLE_WITH_XPU_KP
PADDLE_ENFORCE(a != 0, DIV_ERROR_INFO);
#endif
return static_cast<T>(std::trunc(b / a));
}
};
template <typename T>
struct ElementwisePowFunctor {
inline HOSTDEVICE T operator()(const T a, const T b) const {
// TODO(wujionghao): A potential speed improvement is supporting different
// types in C++.
#if defined(__CUDA_ARCH__) || defined(__HIPCC__)
// On CUDAPlace, std::pow(3, 1) calls pow(float, float), and
// it will return a float number like 2.99... , which floor to 2
// when cast to int by default and it is wrong.
// Use llrint to cast it to the nearest integer, which is 3.
if (std::is_integral<T>::value) {
return std::llrint(
std::pow(static_cast<double>(a), static_cast<double>(b)));
}
#endif
return std::pow(a, b);
}
};
} // namespace funcs
} // namespace phi