/* 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 #include "paddle/phi/core/meta_tensor.h" #include "paddle/phi/infermeta/binary.h" #include "paddle/phi/infermeta/multiary.h" #include "paddle/phi/infermeta/ternary.h" #include "paddle/phi/infermeta/unary.h" namespace phi { // Common InferMeta Functions for backward operators. // // NOTE: The InferMeta Functions in this file are arranged in alphabetic order. void BilinearTensorProductGradInferMeta(const MetaTensor& x, const MetaTensor& y, const MetaTensor& weight, const MetaTensor& dout, MetaTensor* dx, MetaTensor* dy, MetaTensor* dweight, MetaTensor* dbias); void GatherNdGradInferMeta(const MetaTensor& x, const MetaTensor& index, const MetaTensor& out_grad, MetaTensor* x_grad); void GeneralBinaryGradInferMeta(const MetaTensor& x, const MetaTensor& y, MetaTensor* dx, MetaTensor* dy); void GeneralTernaryGradInferMeta(const MetaTensor& x, const MetaTensor& y, const MetaTensor& z, MetaTensor* dx, MetaTensor* dy, MetaTensor* dz); void GeneralUnaryGradInferMeta(const MetaTensor& x, MetaTensor* dx); void GumbelSoftmaxGradInferMeta(const MetaTensor& out, const MetaTensor& dout, int axis, MetaTensor* dx); void MaxPoolWithIndexGradInferMeta(const MetaTensor& x, const MetaTensor& mask, const MetaTensor& dout, const std::vector& kernel_size, const std::vector& strides, const std::vector& paddings, bool global_pooling, bool adaptive, MetaTensor* dx); void PsroiPoolGradInferMeta(const MetaTensor& x, const MetaTensor& rois, paddle::optional rois_num, const MetaTensor& dout, int pooled_height, int pooled_width, int output_channels, float spatial_scale, MetaTensor* dx); void PoolGradInferMeta(const MetaTensor& x, const MetaTensor& out, const MetaTensor& dout, const std::vector& kernel_size, const std::vector& strides, const std::vector& paddings, bool ceil_mode, bool exclusive, const std::string& data_format, const std::string& pooling_type, bool global_pooling, bool adaptive, const std::string& padding_algorithm, MetaTensor* dx); void ScatterGradInferMeta(const MetaTensor& index, const MetaTensor& updates, const MetaTensor& out_grad, bool overwrite, MetaTensor* x_grad, MetaTensor* updates_grad); void ScatterNdAddGradInferMeta(const MetaTensor& index, const MetaTensor& updates, const MetaTensor& out_grad, MetaTensor* x_grad, MetaTensor* updates_grad); } // namespace phi