activation_kernel.cu 9.2 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
/* Copyright (c) 2022 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. */

#include "paddle/phi/kernels/activation_kernel.h"

#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/common/bfloat16.h"
#include "paddle/phi/common/float16.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/elementwise_base.h"
22
#include "paddle/phi/kernels/impl/activation_impl.h"
23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

#include "paddle/fluid/platform/device/gpu/gpu_device_function.h"

namespace phi {

template <typename T, typename Context, typename Functor>
void ActivationGPUImpl(const Context& dev_ctx,
                       const DenseTensor& x,
                       DenseTensor* out,
                       const Functor& functor) {
  PADDLE_ENFORCE_NOT_NULL(out,
                          errors::NotFound("Output Out should not be nullptr"));
  dev_ctx.template Alloc<T>(out);
  std::vector<const DenseTensor*> ins = {&x};
  std::vector<DenseTensor*> outs = {out};
  funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
}

Y
YuanRisheng 已提交
41 42 43 44 45 46 47
#define DEFINE_GPU_ACTIVATION_KERNEL(name, functor_class)               \
  template <typename T, typename Context>                               \
  void name##Kernel(                                                    \
      const Context& dev_ctx, const DenseTensor& x, DenseTensor* out) { \
    funcs::functor_class<T> functor;                                    \
    ActivationGPUImpl<T, Context, funcs::functor_class<T>>(             \
        dev_ctx, x, out, functor);                                      \
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
#define DEFINE_GPU_ACT_KERNEL_WITH_ONE_ATTRS(name, functor_class, attr) \
  template <typename T, typename Context>                               \
  void name##Kernel(const Context& dev_ctx,                             \
                    const DenseTensor& x,                               \
                    float attr,                                         \
                    DenseTensor* out) {                                 \
    funcs::functor_class<T> functor;                                    \
    auto attrs = functor.GetAttrs();                                    \
    *(attrs[0].second) = attr;                                          \
    ActivationGPUImpl<T, Context, funcs::functor_class<T>>(             \
        dev_ctx, x, out, functor);                                      \
  }

#define DEFINE_GPU_ACT_KERNEL_WITH_TWO_ATTRS(               \
    name, functor_class, attr1, attr2)                      \
  template <typename T, typename Context>                   \
  void name##Kernel(const Context& dev_ctx,                 \
                    const DenseTensor& x,                   \
                    float attr1,                            \
                    float attr2,                            \
                    DenseTensor* out) {                     \
    funcs::functor_class<T> functor;                        \
    auto attrs = functor.GetAttrs();                        \
    *(attrs[0].second) = attr1;                             \
    *(attrs[1].second) = attr2;                             \
    ActivationGPUImpl<T, Context, funcs::functor_class<T>>( \
        dev_ctx, x, out, functor);                          \
  }

Y
YuanRisheng 已提交
79 80 81 82 83 84 85 86 87 88 89 90 91 92 93
DEFINE_GPU_ACTIVATION_KERNEL(Cos, CudaCosFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Tan, CudaTanFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Acos, CudaAcosFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Sin, CudaSinFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Asin, CudaAsinFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Atan, CudaAtanFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Sinh, CudaSinhFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Cosh, CudaCoshFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Asinh, CudaAsinhFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Acosh, CudaAcoshFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Atanh, CudaAtanhFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Relu, CudaReluFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Tanh, CudaTanhFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(TanhShrink, CudaTanhShrinkFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Silu, CudaSiluFunctor)
Y
YuanRisheng 已提交
94 95
DEFINE_GPU_ACTIVATION_KERNEL(Sigmoid, CudaSigmoidFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(LogSigmoid, CudaLogSigmoidFunctor)
96 97 98 99
DEFINE_GPU_ACTIVATION_KERNEL(Log, CudaLogFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Log2, CudaLog2Functor)
DEFINE_GPU_ACTIVATION_KERNEL(Log10, CudaLog10Functor)
DEFINE_GPU_ACTIVATION_KERNEL(Log1p, CudaLog1pFunctor)
Y
YuanRisheng 已提交
100 101 102
DEFINE_GPU_ACTIVATION_KERNEL(Round, CudaRoundFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Floor, CudaFloorFunctor)
DEFINE_GPU_ACTIVATION_KERNEL(Ceil, CudaCeilFunctor)
103 104 105 106 107

DEFINE_GPU_ACT_KERNEL_WITH_ONE_ATTRS(LeakyRelu, CudaLeakyReluFunctor, alpha)
DEFINE_GPU_ACT_KERNEL_WITH_ONE_ATTRS(ThresholdedRelu,
                                     CudaThresholdedReluFunctor,
                                     threshold)
Y
YuanRisheng 已提交
108 109 110 111 112
DEFINE_GPU_ACT_KERNEL_WITH_ONE_ATTRS(HardShrink,
                                     CudaHardShrinkFunctor,
                                     threshold)
DEFINE_GPU_ACT_KERNEL_WITH_ONE_ATTRS(SoftShrink, CudaSoftShrinkFunctor, lambda)
DEFINE_GPU_ACT_KERNEL_WITH_ONE_ATTRS(Elu, CudaELUFunctor, alpha)
Y
YuanRisheng 已提交
113
DEFINE_GPU_ACT_KERNEL_WITH_ONE_ATTRS(Swish, CudaSwishFunctor, beta)
114 115

DEFINE_GPU_ACT_KERNEL_WITH_TWO_ATTRS(BRelu, CudaBReluFunctor, t_min, t_max)
Y
YuanRisheng 已提交
116 117 118 119
DEFINE_GPU_ACT_KERNEL_WITH_TWO_ATTRS(HardSigmoid,
                                     CudaHardSigmoidFunctor,
                                     slope,
                                     offset)
120

Y
YuanRisheng 已提交
121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136
template <typename T, typename Context>
void HardSwishKernel(const Context& dev_ctx,
                     const DenseTensor& x,
                     float threshold,
                     float scale,
                     float offset,
                     DenseTensor* out) {
  funcs::CudaHardSwishFunctor<T> functor;
  auto attrs = functor.GetAttrs();
  *(attrs[0].second) = threshold;
  *(attrs[1].second) = scale;
  *(attrs[2].second) = offset;
  ActivationGPUImpl<T, Context, funcs::CudaHardSwishFunctor<T>>(
      dev_ctx, x, out, functor);
}

137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156
}  // namespace phi

#ifdef PADDLE_WITH_HIP
PD_REGISTER_KERNEL(relu,
                   GPU,
                   ALL_LAYOUT,
                   phi::ReluKernel,
                   float,
                   double,
                   phi::dtype::float16) {}
#else
PD_REGISTER_KERNEL(relu,
                   GPU,
                   ALL_LAYOUT,
                   phi::ReluKernel,
                   float,
                   double,
                   phi::dtype::float16,
                   phi::dtype::bfloat16) {}
#endif
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

#define PD_REGISTER_ACTIVATION_KERNEL(name, func) \
  PD_REGISTER_KERNEL(name,                        \
                     GPU,                         \
                     ALL_LAYOUT,                  \
                     phi::func,                   \
                     float,                       \
                     double,                      \
                     phi::dtype::float16,         \
                     phi::dtype::bfloat16) {}

PD_REGISTER_ACTIVATION_KERNEL(sin, SinKernel)
PD_REGISTER_ACTIVATION_KERNEL(cos, CosKernel)
PD_REGISTER_ACTIVATION_KERNEL(tan, TanKernel)
PD_REGISTER_ACTIVATION_KERNEL(acos, AcosKernel)
PD_REGISTER_ACTIVATION_KERNEL(asin, AsinKernel)
PD_REGISTER_ACTIVATION_KERNEL(atan, AtanKernel)
PD_REGISTER_ACTIVATION_KERNEL(sinh, SinhKernel)
PD_REGISTER_ACTIVATION_KERNEL(cosh, CoshKernel)
PD_REGISTER_ACTIVATION_KERNEL(asinh, AsinhKernel)
PD_REGISTER_ACTIVATION_KERNEL(acosh, AcoshKernel)
PD_REGISTER_ACTIVATION_KERNEL(atanh, AtanhKernel)
PD_REGISTER_ACTIVATION_KERNEL(tanh, TanhKernel)
PD_REGISTER_ACTIVATION_KERNEL(brelu, BReluKernel)
PD_REGISTER_ACTIVATION_KERNEL(thresholded_relu, ThresholdedReluKernel)
PD_REGISTER_ACTIVATION_KERNEL(leaky_relu, LeakyReluKernel)
Y
YuanRisheng 已提交
183 184 185 186 187
PD_REGISTER_ACTIVATION_KERNEL(hard_shrink, HardShrinkKernel)
PD_REGISTER_ACTIVATION_KERNEL(soft_shrink, SoftShrinkKernel)
PD_REGISTER_ACTIVATION_KERNEL(tanh_shrink, TanhShrinkKernel)
PD_REGISTER_ACTIVATION_KERNEL(elu, EluKernel)
PD_REGISTER_ACTIVATION_KERNEL(silu, SiluKernel)
Y
YuanRisheng 已提交
188 189 190
PD_REGISTER_ACTIVATION_KERNEL(sigmoid, SigmoidKernel)
PD_REGISTER_ACTIVATION_KERNEL(logsigmoid, LogSigmoidKernel)
PD_REGISTER_ACTIVATION_KERNEL(hard_sigmoid, HardSigmoidKernel)
191 192 193 194
PD_REGISTER_ACTIVATION_KERNEL(log, LogKernel)
PD_REGISTER_ACTIVATION_KERNEL(log2, Log2Kernel)
PD_REGISTER_ACTIVATION_KERNEL(log10, Log10Kernel)
PD_REGISTER_ACTIVATION_KERNEL(log1p, Log1pKernel)
Y
YuanRisheng 已提交
195 196 197 198 199 200 201 202 203 204 205 206 207 208
PD_REGISTER_ACTIVATION_KERNEL(hard_swish, HardSwishKernel)
PD_REGISTER_ACTIVATION_KERNEL(swish, SwishKernel)
PD_REGISTER_ACTIVATION_KERNEL(round, RoundKernel)
PD_REGISTER_ACTIVATION_KERNEL(floor, FloorKernel)
PD_REGISTER_ACTIVATION_KERNEL(ceil, CeilKernel)
PD_REGISTER_KERNEL(pow,
                   GPU,
                   ALL_LAYOUT,
                   phi::PowKernel,
                   float,
                   double,
                   int,
                   int64_t,
                   phi::dtype::float16) {}