binary.h

/* Copyright (c) 2021 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/meta_tensor.h"

namespace phi {

// Common InferMeta Functions for binary operators, The format like:
//
//   1. void [FunctionDesc|OpName]InferMeta(const MetaTensor& x,
//                                          const MetaTensor& y,
//                                          ...,
//                                          MetaTensor* out) {}
//
// NOTE: The name "InferShape" may be not appropriate. "InferMeta" may be good.
//   Because functions in this file not only can infer shape, but also need
//   infer lod or other useful data.

void CompareInferMeta(const MetaTensor& x,
                      const MetaTensor& y,
                      int axis,
                      MetaTensor* out);

void CompareAllInferMeta(const MetaTensor& x,
                         const MetaTensor& y,
                         MetaTensor* out);

void DotInferMeta(const MetaTensor& x, const MetaTensor& y, MetaTensor* out);

void MatmulInferMeta(const MetaTensor& x,
                     const MetaTensor& y,
                     bool trans_x,
                     bool trans_y,
                     MetaTensor* out);

void ElementwiseInferMeta(const MetaTensor& x,
                          const MetaTensor& y,
                          MetaTensor* out);

void ElementwiseRawInferMeta(const MetaTensor& x_meta,
                             const MetaTensor& y_meta,
                             int axis,
                             MetaTensor* out);

void HuberLossInferMeta(const MetaTensor& input_meta,
                        const MetaTensor& label_meta,
                        float delta,
                        MetaTensor* out,
                        MetaTensor* residual,
                        MetaConfig config = MetaConfig());

void TriangularSolveInferMeta(const MetaTensor& x,
                              const MetaTensor& y,
                              bool upper,
                              bool transpose,
                              bool unitriangular,
                              MetaTensor* out);

void IndexSampleInferMeta(const MetaTensor& x,
                          const MetaTensor& y,
                          MetaTensor* out,
                          MetaConfig config = MetaConfig());

void CrossInferMeta(const MetaTensor& x,
                    const MetaTensor& y,
                    int axis,
                    MetaTensor* out);

void Atan2InferMeta(const MetaTensor& x, const MetaTensor& y, MetaTensor* out);

void SegmentPoolInferMeta(const MetaTensor& x,
                          const MetaTensor& segment_ids,
                          const std::string& pooltype,
                          MetaTensor* out,
                          MetaTensor* summed_ids,
                          MetaConfig config = MetaConfig());

void BCELossInferMeta(const MetaTensor& input,
                      const MetaTensor& label,
                      MetaTensor* out,
                      MetaConfig config = MetaConfig());

void BincountInferMeta(const MetaTensor& x,
                       const paddle::optional<const MetaTensor&> weights,
                       int minlength,
                       MetaTensor* out);

void DistInferMeta(const MetaTensor& x,
                   const MetaTensor& y,
                   float p,
                   MetaTensor* out);

void GatherNdInferMeta(const MetaTensor& x,
                       const MetaTensor& index,
                       MetaTensor* out);

void GatherTreeMeta(const MetaTensor& ids,
                    const MetaTensor& parents,
                    MetaTensor* out);

void LogLossInferMeta(const MetaTensor& input,
                      const MetaTensor& label,
                      float epsilon,
                      MetaTensor* out,
                      MetaConfig config = MetaConfig());

void MvInferMeta(const MetaTensor& x, const MetaTensor& vec, MetaTensor* out);

void SigmoidCrossEntropyWithLogitsInferMeta(const MetaTensor& x,
                                            const MetaTensor& label,
                                            bool normalize,
                                            int ignore_index,
                                            MetaTensor* out,
                                            MetaConfig config = MetaConfig());

}  // namespace phi