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/common/scalar.h"
#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.
//
// The InferMeta Functions in this file are arranged in alphabetic order.

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

void EmbeddingInferMeta(const MetaTensor& input,
                        const MetaTensor& weight,
                        int64_t padding_idx,
                        MetaTensor* out);

void KLDivInferMeta(const MetaTensor& x,
                    const MetaTensor& label,
                    const std::string& reduction,
                    MetaTensor* out,
                    MetaConfig config = MetaConfig());

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

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

void BincountInferMeta(const MetaTensor& x,
                       const MetaTensor& weights,
                       int minlength,
                       MetaTensor* out);

void CholeskySolveInferMeta(const MetaTensor& x,
                            const MetaTensor& y,
                            bool upper,
                            MetaTensor* out);

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

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

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

void ConvInferMeta(const MetaTensor& input,
                   const MetaTensor& filter,
                   const std::vector<int>& strides,
                   const std::vector<int>& paddings,
                   const std::string& paddding_algorithm,
                   int groups,
                   const std::vector<int>& dilations,
                   const std::string& data_format,
                   bool use_addto,
                   int workspace_size_MB,
                   bool exhaustive_search,
                   MetaTensor* out,
                   MetaConfig config = MetaConfig());

void ConvInferInferMeta(const MetaTensor& input,
                        const MetaTensor& filter,
                        const std::vector<int>& strides,
                        const std::vector<int>& paddings,
                        const std::string& paddding_algorithm,
                        int groups,
                        const std::vector<int>& dilations,
                        const std::string& data_format,
                        MetaTensor* out,
                        MetaConfig config = MetaConfig());

void ConvTransposeInferMeta(const MetaTensor& x,
                            const MetaTensor& filter,
                            const std::vector<int>& strides,
                            const std::vector<int>& paddings,
                            const std::vector<int>& output_padding,
                            const std::vector<int>& output_size,
                            const std::string& padding_algorithm,
                            int groups,
                            const std::vector<int>& dilations,
                            const std::string& data_format,
                            MetaTensor* out,
                            MetaConfig config = MetaConfig());

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

void CrossEntropyWithSoftmaxInferMeta(const MetaTensor& logits,
                                      const MetaTensor& label,
                                      bool soft_label,
                                      bool use_softmax,
                                      bool numeric_stable_mode,
                                      int ignore_index,
                                      int axis,
                                      MetaTensor* softmax,
                                      MetaTensor* loss,
                                      MetaConfig config = MetaConfig());

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

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

void DropoutInferMeta(const MetaTensor& x,
                      const MetaTensor& seed_tensor,
                      float p,
                      bool is_test,
                      const std::string& mode,
                      int seed,
                      bool fix_seed,
                      MetaTensor* out,
                      MetaTensor* mask);

void DropoutNdInferMeta(const MetaTensor& x,
                        const MetaTensor& seed_tensor,
                        float p,
                        bool is_test,
                        const std::string& mode,
                        int seed,
                        bool fix_seed,
                        const std::vector<int>& axis,
                        MetaTensor* out,
                        MetaTensor* mask);

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 EmbeddingInferMeta(const MetaTensor& x,
                        const MetaTensor& weight,
                        int64_t padding_idx,
                        bool sparse,
                        MetaTensor* out);

void ExpandAsInferMeta(const MetaTensor& x,
                       const MetaTensor& y,
                       const std::vector<int>& target_shape,
                       MetaTensor* out);

void GatherInferMeta(const MetaTensor& x,
                     const MetaTensor& index,
                     const Scalar& axis,
                     MetaTensor* out);

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

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

void GridSampleBaseInferMeta(const MetaTensor& x,
                             const MetaTensor& grid,
                             MetaTensor* out,
                             MetaConfig config = MetaConfig());

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

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

void IndexSelectInferMeta(const MetaTensor& x,
                          const MetaTensor& index,
                          int dim,
                          MetaTensor* output);

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

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

void MaskedSelectInferMeta(const MetaTensor& x,
                           const MetaTensor& mask,
                           MetaTensor* out);

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

void MatmulWithFlattenInferMeta(const MetaTensor& x,
                                const MetaTensor& y,
                                int x_num_col_dims,
                                int y_num_col_dims,
                                MetaTensor* out);

void MatrixRankTolInferMeta(const MetaTensor& x,
                            const MetaTensor& atol_tensor,
                            bool use_default_tol,
                            bool hermitian,
                            MetaTensor* out);

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

void PReluInferMeta(const MetaTensor& x,
                    const MetaTensor& alpha,
                    const std::string& data_format,
                    const std::string& mode,
                    MetaTensor* out,
                    MetaConfig config = MetaConfig());

void SearchsortedInferMeta(const MetaTensor& sorted_sequence,
                           const MetaTensor& value,
                           bool out_int32,
                           bool right,
                           MetaTensor* out);

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

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

void TakeAlongAxisInferMeta(const MetaTensor& x,
                            const MetaTensor& index,
                            int axis,
                            MetaTensor* out);

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

void YoloBoxInferMeta(const MetaTensor& x,
                      const MetaTensor& img_size,
                      const std::vector<int>& anchors,
                      int class_num,
                      float conf_thresh,
                      int downsample_ratio,
                      bool clip_bbox,
                      float scale_x_y,
                      bool iou_aware,
                      float iou_aware_factor,
                      MetaTensor* boxes,
                      MetaTensor* scores,
                      MetaConfig config = MetaConfig());

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

}  // namespace phi