* [Opt Performance] Optimize custom operator performance, reconstruct python API auto-gen, add cache and use const inference

* opt AutoGradMeta implementation

* remove profiler codes

* fix unit test

* change year, 2021->2023

* fix int64_t parse bug

* [CustomOP Inplace] Automap inplace dtype and shape, prepare for vector<Tensor> output

* delete dtype,shape func of multi_inplace op

* [CustomOP Inplace] Automap inplace dtype and shape, support vector<Tensor> output

* [CustomOP Inplace] Auto-generate python API for inplace vector<Tensor> output

Add basic functionalities to support Scalar & Scalars in operator attribute.

1. extend allowed types in operator's attribute type, add `paddle::experimental::Scalar`, add corresponding protobuf Message types;
2. Scalar enhancement, add formatting, equality;
3. add code to handle Scalar & Scalars in opmaker, conversion from  paddle operator to phi kernel, opdesc construction and manipulation,  tensorrt converter, tracer, operator construction, etc;
4. bind `paddle::experimental::Scalar` to python, as `libpaddle.Scalar`;
5. add functionality to canonicalize attribute map according to OpProto(if the op the attribute map used for has an OpProto);
6. add code to manipulate Scalar proto message via protobuffer python API;

Add unittests.

1. add test cases for formatting, equality for Scalars, and WrapAsScalars;
2. add test cases for 'casting' between different morphs of attributes;
3. add test cases for extracting scalar & scalars from attribute;
4. add test cases for CanonicalizeScalarAttrs(and fix a bug in type index offset);
5. fix gmock's library filename on windows platform.
6. clean code: use canonicalize_attrs instead of inlining the function;
7. add test cases for libpaddle.Scalar in python code.
8. add test cases for `make_scalar_proto`, which manipulate proto message `Scalar` via protobuffer python API.

* allow return none when stop_gradient=True

* remove useless code

* refine code

* refine code

* fix test cast

* change more test

* add more tests

* move DataType from paddle::experimental to phi

* convert namespace

* convert namespace

* convert namespace

* clarify namespace

* convert more datatype

* Revert "convert more datatype"

This reverts commit 083b462959e6a22d4d8767707b628b95b396642e.

* convert more in auto_code_generator

* fix conflicts for XPU

* fix namespace conflicts

* fix errors

* Revert "fix errors"

This reverts commit f9d9958b54ee32141112274c8a5c3c381ab0f876.

* fix errors

* fix formatting

* init unit test commit, contains register thinking

* support inplace

* get inplaced x.grad

* Try support inplace and hook at the same time

* Support inplace, need debug

* Support inplace successfully

* Inplace use Tensor&, consistent with Tensor*

* fix MapPlainOutputs bug

* fix double grad inplace error

* update include directory

* fully support C++ extension, pass unittest

* fix include directory

* support both extension and operator in one file

* polish testcase

* add jit unittest

* update third_party.cmake, pass CI test

* fix cmake

* fix setup

* fix inference, fix unittest precision

* fix unittest precision

* fix inference_lib cmake

* try fix setup, try fix inference_lib

* try fix inference_lib pybind

* fix mix_op_extension, fix inference_lib

* fix mix_op_extension, fix inference_lib

* change cmake

* change cmake

* add compile flags

* add Python.h headerfile

* add test_custom_plugin_creater cmake

* comment compile flag

* pass all CI

* pass all CI

* comment compile flag

* try solve test_custom_plugin_creater link error

* try solve test_custom_plugin_creater link error

* polish codes

* remove windows compile flag

* remove python_include_path

* update pybind11, 2.4.3->2.6.0

* update pybind11, 2.6.0->2.10.0

* update pybind11, 2.10.0->2.6.0b1

* update pybind11, 2.6.0b1->2.6.0, start fix unittest

* fix pybind11 2.6.0 VarBase print error

* fix pybind11 2.6.0 VarBase print error

* handle PADDLE_ON_INFERENCE

* modify according to reviewer

* fix cmake

* cmake decouple pybind_util when not ON_INFER

* cmake decouple pybind_util when not ON_INFER

* remove copy of inference_lib.cmake

* change pybind.cc headerfile fluid->phi

* fix copysign compile error on Windows

* fix more files' macro

* add FP16 dtype for CastNumpy2Scalar

* fix throw message

* add test

* fix SyntaxWarning

* test skip for float16

* fix dtype mistakes

* add new tensor

* fix windows compile bugs

* fix ci bugs

* fix ci bugs

* fix ci bugs

* perfect according comment

* fix ci compile bugs

* add raw tensor

* fix ci bugs

* modify code by comment

* delete String

* do not link python lib in tensor wrapper

* do not calc reduce_all in eager mode

* refine python c cast list

* refine

* refine

* refine

* refine

* refine

* refine

* refine

* refine

* refine

Get grads types from cpp for adam to speed up

* refine python call error report

* Get three grad lists in CPP to avoid gpu idle time

* Support legacy mode

* Add missing <cstddef>
  * Fix some iterator type
  * Currently use host protobuf to bypass build failure

* remove using lodtensor part1

* polish history code format

* remove needless using tensor

* remove needless using tensor

* resolve conflict

* replace tensor using

* fix format error

* revert needless changing

* fix rocm and npu compile error

* fix cinn compile error

* fix format error

* fix mkldnn format error

* fix mkldnn format error

* fix cinn compile error

* fix cinn compile error

* fix cinn compile error

* resolve conflict

* [Eager] math op sink to Cpp level

* fix ci errors

* draft version


* support + and - operator under cpp directly

* add static test

* polish code

* promote types or unify right type to left

* recover static test case

* polish code and fix some ci errors

* support complex and polish code

* fix conflicts

* fix windows ci errors

* fix windows-inference-ci errors

* polish and fix tests

* fix test case

* polish code

* [Eager, Performance optimization] support multiply( * operator) to sink to Cpp layer

* rm useless glog

* polish code

* polish code and fix code-format

* polish code

* fix CI

* polish code

* add tensor array

* fix ci bugs

* fix ci bugs

* fix ci bugs

* fix ci bugs

* update by comment

* update code

* make full_like support double_max in dygraph

* fix bug

* support optional<vector<Tensor>> in yaml and eager

* delete useless comments in eager_gen.py

* fix api_base.py support optional<vector<TTensor>>

* python_c_gen.py support optional<vector<tensor>>

* transfer linear_interp_v2 yaml from fluid to phi

* fix op_test typo error

* change linear_interp_v2 testcase

* fix args in final_state_linear_interp_v2

* fix zeropad2d typo. test=document_fix

* [Eager] use final_state_fill_constant_

* fill_constant use str_value

* add fill_constant_ to no_amp_list

* use float(value) as input

* support final state full_ same as fill_constant

* Pybind Fucniton and hide ExecutorEngine and PEEngine

* Remove FunctionNames in compilation_unit

* Polish function code

* Rename funciton to engine

* Fix Log msg and doc

* Rename Function to Engine and using new Function class to warp Engine

* Rename EngineInfo

* Adjust member variable order

* Move Function classes to a sub dir

* Format code

* [Phi] Add yaml for assign_value

* [Phi] Fix the bug of the assign api and modify the unittest

* [Phi] Fix the bug when the tensor does not have the backend info

* [Phi] Replace the functional-style cast init by the brace-init

* [Phi] Cast the data explicitly

* Support predictor function in JitLayer

* Pybind PEFunction

* Pybind PEFunction and call phi api in layer_test

* Call sqrt phi API

* Polish flags

* Fix comments

* [JIT]Layer support eager dygraph mode and polish Function interface

* remove usless code

* fix #define

* inplace op without backward supports input of multiple inplace vars

* support inplace without backward in eager mode and fix python_c in eager_fluid

* fix output in yaml

* fix map to const&

* solve conflict v2