* auto parallel support pipeline scheduler with standalone executor

* rm check_fetch

* update cmakelist and flags env

* rm set micro batch id

* rm import

* update utils func

* raise error when merge tensor for return_numpy is False

* fix _pipeline_opt

* fix unittest

* [Auto Parallel] Reorganize the fold structure

* [Auto Parallel] Fix some import errors

* [CustomDevice] fix auto_paralell

* update

* update

* update

* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* fixed cyclic reference that caused patial import

* fixed bad change

* fix bad import

* fix bad import

* fix bad import

* fix ut failed caused by change in_dynamic_mode

* fix ut failed caused by change in_dynamic_mode

* fixed usage of in_dynamic_mode() or in_dygraph_mode()

* revert python3 to python in .pre-commit-config.yaml

* fix merge conflicts

* suport device_guard for npu

* fix comment

* fix typo

* remove _in_eager_mode_

* remove _in_eager_mode_

* Fix some problems in Paddle english instruction doc files.

* fix some new questions

* fix cn doc problems, test=document_fix

* rename monkey_patch_varbase as monkey_patch_tensor & monkey_patch_math_varbase as monkey_patch_math_tensor

* rename monkey_patch_varbase as monkey_patch_tensor & monkey_patch_math_varbase as monkey_patch_math_tensor

* rename monkey_patch_varbase as monkey_patch_tensor & monkey_patch_math_varbase as monkey_patch_math_tensor v2

* rename monkey_patch_varbase as monkey_patch_tensor & monkey_patch_math_varbase as monkey_patch_math_tensor fixed bug

* fix

* fix

* fix

* fix

* fix

* fix fuse group order

* rename _varbase_creator as create_tensor

* rename _varbase_creator as create_tensor

1. modify set_value op, use Scalars to represent attr `values`, instead of a bunch of attributs of various types; (#52408)

2. add program converter and set_value op as an example, which provides the functionality to convert `paddle::framework::ProgramDesc` between old and new formats(the differences are mainly some operators with incompatible updates in the definition);
3. program version and operator version map now are always saved when serializing `paddle::framework::ProgramDesc` to identify the version;
3. provide an option `legacy_format=false` in  serialization of `paddle::framework::ProgramDesc`, it decided whether to convert ProgramDesc back to a legacy format, which is compatible for paddle 2.4.2 or earlier versions to load and execute;
4. deserialization of `paddle::framework::ProgramDesc` is now automatically detecting whether the bytes it receives is in legacy format(contains any of the operators that has been incompatibly updated and have any attribute of type `Scalar`) and convert it to new format. But if you want a faithful deserialization without the automatic conversion, you can use protobuf's deserialization instead. Though it is not recommended, it can be used for the purpose of testing.

* remove c_comm_init_hccl_op.cc and c_gen_hccl_id_op.cc

* remove gen_hccl_id_op.cc

* add strategy force_sequential_run

* remove flag

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* remove run_program

* remove FLAGS_USE_STANDALONE_EXECUTOR

* rem is_compiled_with_npu

* rem nup related code

* make lint happy

* rem test

* remove some tests

* Update grad_scaler.py

* fix an error

Co-authored-by: Nxiongkun <xiongkun03@baidu.com>

* rem is_compiled_with_mlu

* fix some mlu_place and mlu_device_coount

* make lint happy

* delete old dygraph op test

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.

* remove fluid.data

* fix typro

* fix somme unitest error

* fix conflicts

* fix sample code error

* fxi sample coder error

* fxi sample code error

* fxi sample code error

* fix xpu test error

* fix xpu test error

* Delete ps_pb2.py

* fix test error

* fix typro

* fix sample code error

* fix comments

* fix test norm op data

* fix sample code error

* fix conflicts

* remove no used fluid beam_search_decoder

* move Layer and related helper to paddle.nn.common

* modify Layer references from dygraph.layers.Layer to paddle.nn.common.layers

* stash changge

* remove fluid layer_object_helper, layers.py

* remove fluid layers init

* add setip

* fix unitest

* delete layers in fluid.dygraph

* merge paddle.tensor.stat,py

* fix circle import

* fix curcle import

* remove redundant in_dygraph_mode import

* revoce paddle.nn.common.* in fluid.__init__

* recovery nn.rnn

* paddle.frame use lazy import import paddle.jit to avoid circle import

* remove left dygraph.layers ref

* merge develop

* fix import error

* fix test error

* fxi merge error

* fix test fluid.Layer

* fix test error

* fix test error

* fix import error

* fix import error

* fix comments

* fix circle import

* fix rnn import error

* fix circle import

* [CINN]Enhance CacheKey hash logic by considering input dtypes (#50557)

---------
Co-authored-by: Njiangcheng <thisjiang@qq.com>

* [prim] enable dygraph_to_static to support custom_vjp

* Pr 50885 (#7)

* [CINN]Enhance CacheKey hash logic by considering input dtypes (#50557)

* [CINN]Enhance CacheKey hash logic by considering input dtypes

---------
Co-authored-by: Njiangcheng <thisjiang@qq.com>

* [prim] enable dygraph_to_static to support custom_vjp

* fix code in a dy2static-friendly way.

* [dystatic] add hooker for prim

---------
Co-authored-by: NAurelius84 <zhangliujie@baidu.com>
Co-authored-by: Njiangcheng <thisjiang@qq.com>
Co-authored-by: Ncxxly <chenxx_id@163.com>

* [prim] enable dygraph_to_static to support custom_vjp

* fix cast prim and vjp dtype mapping error bug

* [dy2static-ci] fix dy2static ci errors.

---------
Co-authored-by: NAurelius84 <zhangliujie@baidu.com>
Co-authored-by: Njiangcheng <thisjiang@qq.com>
Co-authored-by: Ncxxly <chenxx_id@163.com>

* [framework]support pass stop_gradient in static mode

* fix control_flow op stop_gradient

* support warnings for extra attrs and axis in non default value

* support extra_attr warnings and add test case

* fix dict name

* polish

* polish

* polish