// Copyright (c) 2023 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/primitive/primitive/primitive.h" #include "paddle/ir/core/value.h" #include "paddle/phi/api/include/tensor.h" #include "paddle/phi/common/int_array.h" namespace paddle { namespace primitive { using IntArray = paddle::experimental::IntArray; // TODO(wanghao107): // op's vjp will be auto generated. std::vector> tanh_vjp( const Tensor& out, const Tensor& grad_out, const std::vector>& stop_gradients); std::vector> mean_vjp( const Tensor& x, const Tensor& out_grad, const IntArray& axis, bool keepdim, bool reduce_all, const std::vector>& stop_gradients); std::vector> add_vjp( const Tensor& x, const Tensor& y, const Tensor& out_grad, int axis, const std::vector>& stop_gradients); std::vector> divide_vjp( const Tensor& x, const Tensor& y, const Tensor& out, const Tensor& out_grad, int axis, const std::vector>& stop_gradients); std::vector> sum_vjp( const Tensor& x, const Tensor& out_grad, const IntArray& axis, bool keepdim, bool reduce_all, const std::vector>& stop_gradients); } // namespace primitive } // namespace paddle