* apply gcc12 to gpups

* apply gcc12 to gpups

* apply gcc12 to gpups

* apply gcc12 to gpups

* apply gcc12 to gpups

* apply gcc12 to gpups

* apply gcc12 to gpips

* apply gcc12 to gpups

* apply gcc12 to gpups

* test

* test

* apply gcc12 to gpups

* apply_gcc12_to_gpups

* fix compiler bug

* fix compiler bug

* test

* fix dangling-pointer compiler

* fix dangling-pointer compiler

* fix dangling-pointer compiler

* apply_gcc12_to_gpups

* apply gcc12 to gpups

* Update cuda_streams_py.cc

* Delete temp param in eager_gen

* support 0-D output and 0-D as indice in __getitem__

* fix tests

* fix inference and UT

* add unittest for setitem

* fix xpu test

* fix xpu 0-d

* [CustomOP error] Add attrs type check

* fix global variable order bug

* include unordered_set

* fix ParseAttrStr compile error

* [CustomDevice] add recompute support

* update

* cherry-pick fleet executor from 2.4

* fix test case

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.

* support set master_grad

* move register_hook to auto_cast

* update unittest

* fix fp16 test

* update for review comments

* [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

* add strategy force_sequential_run

* remove flag

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix

* mv WITH_ASCEND_CL

* mv WITH_ASCEND

* rollback

* remove WITH_ASCEND

* remove WITH_ASCEND

* add strategy force_sequential_run

* fix

* fix

* fix

* fix

* fix

* mv WITH_ASCEND_CL

* mv WITH_ASCEND

* rollback

* rem is_compiled_with_npu

* rem nup related code

* make lint happy

* rem test

* remove some tests

* Update grad_scaler.py

* fix an error

* add gloo gather

* add gloo_tools

* fix CI bug

* use gloo gather

* remove redundant code

* fix process_group_gloo.py

* rename send_recv

* fix conflict

* fix conflict

* fix codestyle

* fix CI bug

* add PADDLE_ENFORCE_NE

* rem is_compiled_with_mlu

* fix some mlu_place and mlu_device_coount

* make lint happy

* Delete the /paddle/fluid/platform/device/npu directory

* clear Cmakelists

* Try removing npu in the header file

* gather with doc

* resolve comment

* polish

* polish

* code style

* polish doc

* add_test

* polish

* polish

* add test check

* add test check

* polish

* polish

* polish

* polish

* fix_time_out

* polish

* fix timeout

* fix_timeout

* polish

* polish

* polish

* polish

* polish

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

* delete custom_inplace_setup.py

* [CustomOP Optional Inplace] Custom operator supports inplace optional Tensor input

* fix bug for vector<Tensor> inplace test

1. add type caster for paddle's complex type, to allow pybind to automatically cast it with python's complex type;
2. add complex64 and complex128 data type for `libpaddle.Tensor`'s element get and set(which is required to perturb an element to get the numerical derivative)
3. add support for cuda pinned place in `libpaddle.Tensor` element get and set

---
4. fix a bug in op code generation.(Creation of output folder in concurrent with parsing op yamls.)

* [AMP] Add python API for collecting operator stats.

* Fix import and polish codes.

* Add more unittest.

* Add doc for the new APIs.