// 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/core/dense_tensor.h" #include "paddle/phi/infermeta/binary.h" namespace phi { template void FMaxRawKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, int axis, DenseTensor* out); template void FMaxKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out); template void FMinKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out); template void MaximumRawKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, int axis, DenseTensor* out); template void MaximumKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out); template void MinimumRawKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, int axis, DenseTensor* out); template void MinimumKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out); template void RemainderRawKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, int axis, DenseTensor* out); template void RemainderKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out); template void FloorDivideRawKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, int axis, DenseTensor* out); template void FloorDivideKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out); template void ElementwisePowRawKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, int axis, DenseTensor* out); template void ElementwisePowKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out); template void HeavisideKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, DenseTensor* out); template DenseTensor Maximum(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y) { DenseTensor dense_out; MetaTensor meta_out(&dense_out); ElementwiseInferMeta(x, y, &meta_out); MaximumKernel(dev_ctx, x, y, &dense_out); return dense_out; } template DenseTensor Minimum(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y) { DenseTensor dense_out; MetaTensor meta_out(&dense_out); ElementwiseInferMeta(x, y, &meta_out); MinimumKernel(dev_ctx, x, y, &dense_out); return dense_out; } template DenseTensor Remainder(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y) { DenseTensor dense_out; MetaTensor meta_out(&dense_out); ElementwiseInferMeta(x, y, &meta_out); RemainderKernel(dev_ctx, x, y, &dense_out); return dense_out; } template DenseTensor FloorDivide(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y) { DenseTensor dense_out; MetaTensor meta_out(&dense_out); ElementwiseInferMeta(x, y, &meta_out); FloorDivideKernel(dev_ctx, x, y, &dense_out); return dense_out; } template DenseTensor Heaviside(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y) { DenseTensor dense_out; MetaTensor meta_out(&dense_out); ElementwiseInferMeta(x, y, &meta_out); HeavisideKernel(dev_ctx, x, y, &dense_out); return dense_out; } template DenseTensor ElementwisePow(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y) { DenseTensor dense_out; MetaTensor meta_out(&dense_out); ElementwiseInferMeta(x, y, &meta_out); ElementwisePowKernel(dev_ctx, x, y, &dense_out); return dense_out; } } // namespace phi