vjp.h

// 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

#ifndef _USE_MATH_DEFINES
#define _USE_MATH_DEFINES
#endif

#include <math.h>
#include <vector>

#include "paddle/fluid/primitive/primitive/primitive.h"
#include "paddle/ir/core/value.h"
#include "paddle/phi/api/include/tensor.h"

namespace paddle {
namespace primitive {
namespace experimental {
// TODO(wanghao107):
//  op's vjp will be auto generated.
std::vector<std::vector<paddle::Tensor>> tanh_vjp(
    const Tensor& out,
    const Tensor& grad_out,
    const std::vector<std::vector<int>>& stop_gradients);

std::vector<std::vector<paddle::Tensor>> mean_vjp(
    const Tensor& x,
    const Tensor& out_grad,
    std::vector<int64_t> axis,
    bool keepdim,
    bool reduce_all,
    const std::vector<std::vector<int>>& stop_gradients);

namespace details {
// NOTE: this namespace will store
// primitive ops grad composite rules.

}  // namespace details
}  // namespace experimental
}  // namespace primitive
}  // namespace paddle