* [OpAttr]Add SupportTensor for OpMaker

* fix typo

* fix code style

* add SupportTensor for concat op

* add unittest for register Tensor

* add shape checker and split attribute

* [Auto Parallel] Move the distributed info from python to c++

* [Auto Parallel] Add dist_attrs for VarDesc and OpDesc

* [Auto Parallel] Add the lost file

* [Auto Parallel] Make the dist attr be unique_ptr

* [Auto Parallel] Add the proto conversion

* [Auto Parallel] Improve the proto support

* [Auto Parallel] Fix the bugs for adding a device or a link

* [Auto Parallel] Add the C++ ProcessMesh and DistributedMapper

* [Auto Parallel] Improve the impl of these dist attrs

* [Auto Parallel] Pybind11 ProcessMesh and DeviceMesh

* [Auto Parallel] Fix the unittest problem

* [Auto Parallel] Explicitly add the src file for auto_parallel target

* [Auto Parallel] Add the proto depedency explicitly

* [Auto Parallel] Fix the cmake bug on windows and mac

* [Auto Parallel] Remove the pybind11 header file in process_mesh.h

* [Auto Parallel] Remove unused codes

* [Auto Parallel] Check whether the dist attr is null

* [Auto Parallel] Implement the assign operator for OpDesc explicitly

* [OpAttr]Support VarDesc* and vector<VarDesc*> in Attribute

* add unittest for inference predictor

* add string tensor and case convert kernels

* Add strings empty kernel; Reorganize the structure of case convert kernel

* Add string infermeta

* Update mutable_data of string tensor

* rename kernel name

* add string copy tmp

* Fix strings copy device bug

* add utf8 gpu converter

* add string tensor c++ api

* Remove mutable_data of string tensor

* update string tensor interface

* remove charcases_flag.h

* remove some fluid headers

* Add make_ddim

* __HIPCC__ -> PADDLE_WITH_HIP

* remove fluid headers

* fix cpu compile

* remove std::hash

* Fix cudaMalloc

* Remove strings/impl directory

* Fix infrt/get_phi_kernel_info.py;Add custom_kernels deps

* Add empty kernel test

* Remove some comments

* Modify lower/upper api encoding type: string->bool

* STRING->PSTRING; Add CreateInferLikeMeta

* Add code gen for C++ String API

* remove strings_api_utils.h

* Add ignore file (strings_api.h, strings_api.cc)

* update strings gen script

* change args order of case convert kernels

* Add comments for pstring, StringTensor

* cpstring_internal.h -> cpstring_impl.h

* Update accordding to comments:

1. Remove fluid headers
2. paddle::platform::errors -> phi::errors
3. Use 'place.GetType() == phi::AllocationType::GPU' instead of 'paddle::platform::is_cpu_space()'
4. Use camel code style

* Remove all singletons in strings kernels

* fix rocm compile

* Fix py3 compile

* Fix c++ coverage

* 1. Add pstring proto type
2. Add StringTensor debug info
3. Rename case_convert_kernel to strings_lower_upper
4. Remove serialize derialize strings kernel

* DataLayout::PSTRING -> DataLayout::PSTRING_UNION

* Register pstring data type

* Fix strings api gen

* Fix dense tensor register pstring dtype

* Fix error messages

* remove line

* add pstring unittest

* remove test string api unitest

* remove empty line

* Remove some headers to decrease the size of executable file

Add Tokenizer related functionalities for Transformer model in order that the process of training and predicting is consistent.

* support the text string as an input Tensor
* support the "VOCAB"unordered_map<wstring, int> as an input Tensor to lookup tokens
* Tokenizer used for BERT. This tokenizer applies an end-to-end, text string to wordpiece tokenization.
* It first applies basic tokenization, followed by wordpiece tokenization.

* add auto_parallel apis

This PR added optional boolean is_parameter and stop_gradient in the VarDesc proto, and remove them during save_inference_model

Support vector<double> as type of op attribute and op set_value suppport vector<double> as value (#30126)

* add complex64 and complex128 type; add +-*/@ and slice opreator for complex types

* add test cases for complex elementwise, matmul and getitem unittest

* add test cases for complex types

* add test cases for complex matmul unittest

* Update Paddle-Lite commit hash.

* Add BF16 data type to VarTyp protobuf message.

* remove optimize_for in framework.proto
* test=develop

* update operator compatible info, test=develop

* revert cmake/version.cmake, test=develop

* add unit_tests and fix bugs, test=develop

* update ../paddle/fluid/framework/framework.proto, test=develop

* fix bug of paddle/fluid/inference/api/analysis_predictor.cc, test=develop

* update paddle/fluid/framework/version_test.cc, test=develop

* add comments and rename interfaces, test=develop

The new "fluid.data" changes old "fluid.layers.data":

1. Add shape and dtype check.
2. Remove "append_batch_size" parameter. We won't offer this in the new data layer because other deep learning platforms don't have this kind of data layer pre-processing. It may confuse users.
3. Remove "stop gradient" parameter because the data layer doesn't do back-propagation

TODO：
Now data layer feeded by executor is checked, will we want to check the feed data of readers in the future?

test=develop

test=develop

test=develop

test=develop

test=develop

* Support int8 type.

* "add inplace attribute"

* "register inplace attribute"

* "change se-next model for memory-reuse"

* "fix typo"

* repick

* fix merge conflict

* "fix stupid error"

* add the type of tuple

* add lod_tensor to tuple

* Add block.fwd_block_id

* fix bug in memory optimization transpiler

* Change DFS to BFS

* Add comments

Add Channel as a VarType