/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #pragma once #include "paddle/fluid/operators/amp/fp16_type_traits.h" #include "paddle/fluid/operators/math.h" namespace pten { namespace funcs { // // MulFunctor // // NOTE(chenfeiyu): IT IS NOLONGER USED, use pten::funcs::MultiplyFunctor // instead // template // struct MulFunctor { // // out = x * y; // inline HOSTDEVICE T operator()(T x, T y) { return x * y; } // }; template struct MulGradFunctor { inline HOSTDEVICE T Dx(T x, T y) { return y; } inline HOSTDEVICE T Dy(T x, T y) { return x; } }; // // AddFunctor // // NOTE(chenfeiyu): IT IS NOLONGER USED, use pten::funcs::AddFunctor instead // template // struct AddFunctor { // // out = x + y; // inline HOSTDEVICE T operator()(T x, T y) { return x + y; } // }; template struct MaxFunctor { inline HOSTDEVICE T operator()(T a, T b) const { return a < b ? b : a; } }; template struct AddGradFunctor { inline HOSTDEVICE T Dx(T x, T y) { return static_cast(1.); } inline HOSTDEVICE T Dy(T x, T y) { return static_cast(1.); } }; template struct ScaleFunctor { explicit ScaleFunctor(const T coeff) : coeff_(coeff) {} inline HOSTDEVICE T operator()(T ele) { return ele * coeff_; } private: T coeff_; }; template struct ScaleGradFunctor { explicit ScaleGradFunctor(T coeff) : coeff_(coeff) {} inline HOSTDEVICE T UseX(T x) { return coeff_; } inline HOSTDEVICE T UseOut(T out) { return coeff_; } inline HOSTDEVICE T UseXAndOut(T x, T out) { return coeff_; } private: T coeff_; }; template struct ReluFunctor { inline HOSTDEVICE T operator()(T x) { return x * (x > static_cast(0) ? static_cast(1) : static_cast(0)); } }; template struct ReluGradFunctor { inline HOSTDEVICE T UseX(T x) { return x > static_cast(0) ? static_cast(1) : static_cast(0); } inline HOSTDEVICE T UseOut(T out) { return out > static_cast(0) ? static_cast(1) : static_cast(0); } inline HOSTDEVICE T UseXAndOut(T x, T out) { return out > static_cast(0) ? static_cast(1) : static_cast(0); } }; template struct TanhFunctor { const T kMin = static_cast(-40); const T kMax = static_cast(13); inline HOSTDEVICE T operator()(T x) { // y = 2 / (1 + e^-2x) - 1 T t0 = static_cast(2) * x; T t1 = (t0 < kMin) ? kMin : ((t0 > kMax) ? kMax : t0); return static_cast(2) / (static_cast(1) + paddle::operators::real_exp(-t1)) - static_cast(1); } }; template struct TanhGradFunctor { inline HOSTDEVICE T UseX(T x) { return static_cast(1) - x * x; } inline HOSTDEVICE T UseOut(T out) { return static_cast(1) - out * out; } inline HOSTDEVICE T UseXAndOut(T x, T out) { return static_cast(1) - out * out; } }; template struct SigmoidFunctor { const T kMin = static_cast(-40); const T kMax = static_cast(13); inline HOSTDEVICE T operator()(T x) { // y = 1 / (1 + e^-x) T tmp = (x < kMin) ? kMin : ((x > kMax) ? kMax : x); return static_cast(1) / (static_cast(1) + paddle::operators::real_exp(-tmp)); } }; template struct SigmoidGradFunctor { inline HOSTDEVICE T UseX(T x) { return x * (static_cast(1) - x); } inline HOSTDEVICE T UseOut(T out) { return out * (static_cast(1) - out); } inline HOSTDEVICE T UseXAndOut(T x, T out) { return out * (static_cast(1) - out); } }; template struct GeluFunctor { using MT = typename paddle::operators::details::MPTypeTrait::Type; inline HOSTDEVICE T operator()(T x) { // this function is tanh approximation of gelu // actual gelu is: // x * 0.5 * (1.0 + torch.erf(x * 0.70710678)) MT mx = static_cast(x); MT out = mx * static_cast(0.5) * (static_cast(1.0) + tanh(static_cast(0.79788456) * mx * (static_cast(1) + static_cast(0.044715) * mx * mx))); return static_cast(out); } }; template struct GeluGradFunctor { using MT = typename paddle::operators::details::MPTypeTrait::Type; inline HOSTDEVICE T UseX(T x) { MT mx = static_cast(x); MT tanh_out = tanh(static_cast(0.79788456) * mx * (static_cast(1) + static_cast(0.044715) * mx * mx)); MT ans = static_cast(0.5) * mx * ((static_cast(1) - tanh_out * tanh_out) * (static_cast(0.79788456) + static_cast(0.1070322243) * mx * mx)) + static_cast(0.5) * (static_cast(1) + tanh_out); return static_cast(ans); } inline HOSTDEVICE T UseOut(T x) { MT mx = static_cast(x); MT tanh_out = tanh(static_cast(0.79788456) * mx * (static_cast(1) + static_cast(0.044715) * mx * mx)); MT ans = static_cast(0.5) * mx * ((static_cast(1) - tanh_out * tanh_out) * (static_cast(0.79788456) + static_cast(0.1070322243) * mx * mx)) + static_cast(0.5) * (static_cast(1) + tanh_out); return static_cast(ans); } inline HOSTDEVICE T UseXAndOut(T x, T out) { MT mx = static_cast(x); MT tanh_out = tanh(static_cast(0.79788456) * mx * (static_cast(1) + static_cast(0.044715) * mx * mx)); MT ans = static_cast(0.5) * mx * ((static_cast(1) - tanh_out * tanh_out) * (static_cast(0.79788456) + static_cast(0.1070322243) * mx * mx)) + static_cast(0.5) * (static_cast(1) + tanh_out); return static_cast(ans); } }; } // namespace funcs } // namespace pten