/* 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. */ #pragma once #include "paddle/phi/common/scalar.h" #include "paddle/phi/core/dense_tensor.h" #include "paddle/phi/infermeta/unary.h" namespace phi { #define DECLARE_ACTIVATION_KERNEL(name) \ template \ void name##Kernel( \ const Context& dev_ctx, const DenseTensor& x, DenseTensor* out); #define DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(name, attr) \ template \ void name##Kernel(const Context& dev_ctx, \ const DenseTensor& x, \ float attr, \ DenseTensor* out); #define DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS(name, attr1, attr2) \ template \ void name##Kernel(const Context& dev_ctx, \ const DenseTensor& x, \ float attr1, \ float attr2, \ DenseTensor* out); DECLARE_ACTIVATION_KERNEL(Cos) DECLARE_ACTIVATION_KERNEL(Tan) DECLARE_ACTIVATION_KERNEL(Acos) DECLARE_ACTIVATION_KERNEL(Sin) DECLARE_ACTIVATION_KERNEL(Asin) DECLARE_ACTIVATION_KERNEL(Atan) DECLARE_ACTIVATION_KERNEL(Sinh) DECLARE_ACTIVATION_KERNEL(Cosh) DECLARE_ACTIVATION_KERNEL(Asinh) DECLARE_ACTIVATION_KERNEL(Acosh) DECLARE_ACTIVATION_KERNEL(Atanh) DECLARE_ACTIVATION_KERNEL(Relu) DECLARE_ACTIVATION_KERNEL(Tanh) DECLARE_ACTIVATION_KERNEL(Exp) DECLARE_ACTIVATION_KERNEL(Expm1) DECLARE_ACTIVATION_KERNEL(Reciprocal) DECLARE_ACTIVATION_KERNEL(Square) DECLARE_ACTIVATION_KERNEL(Sqrt) DECLARE_ACTIVATION_KERNEL(Rsqrt) DECLARE_ACTIVATION_KERNEL(TanhShrink) DECLARE_ACTIVATION_KERNEL(Silu) DECLARE_ACTIVATION_KERNEL(Sigmoid) DECLARE_ACTIVATION_KERNEL(LogSigmoid) DECLARE_ACTIVATION_KERNEL(Log) DECLARE_ACTIVATION_KERNEL(Log2) DECLARE_ACTIVATION_KERNEL(Log10) DECLARE_ACTIVATION_KERNEL(Log1p) DECLARE_ACTIVATION_KERNEL(Round) DECLARE_ACTIVATION_KERNEL(Floor) DECLARE_ACTIVATION_KERNEL(Ceil) DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(LeakyRelu, alpha) DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(ThresholdedRelu, threshold) DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(SoftShrink, lambda) DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(HardShrink, threshold) DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(Elu, alpha) DECLARE_ACTIVATION_KERNEL_WITH_ONE_ATTRS(Swish, beta) DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS(BRelu, t_min, t_max) DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS(STanh, scale_a, scale_b) DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS(HardSigmoid, slope, offset) DECLARE_ACTIVATION_KERNEL_WITH_TWO_ATTRS(Softplus, beta, threshold) template void LogitKernel(const Context& dev_ctx, const DenseTensor& x, float eps, DenseTensor* out); template void MishKernel(const Context& dev_ctx, const DenseTensor& x, float threshold, DenseTensor* out); template void HardSwishKernel(const Context& dev_ctx, const DenseTensor& x, float threshold, float scale, float offset, DenseTensor* out); template void PowKernel(const Context& dev_ctx, const DenseTensor& x, const Scalar& factor, DenseTensor* out); } // namespace phi