* [MLU]support calling mlu op from python interface

* [MLU]fix

* fix

* [mlu]fix mlu_places

* [mlu]fix required mlu

* fix

* [MLU]fix tensor copy

* [mlu] fix MLUPlace call path

* Rearranged Eager AutoCodeGen directory structure

* Removed USE_OP in Eager AutoCodeGen

* Enabled generation for Operators without Grad/Inputs/Outputs

* Resolved operators without input

* Fixed merge conflicts

* Enabled Eager AutoCodeGen for 10+ more operators

* Refactored Eager AutoCodeGen with more organized helper objects

* Enabled Eager AutoCodeGen for operators with multiple OpBases

* Adjusted Eager AutoCodeGen to Enable Passing Output Tensor as Input Argument

* Handled Dispensable Inputs/Outputs in Eager AutoCodeGen

* Adjusted function generation/call between Python-C API & Dygraph API

* Synchronized auto-generated Python-C API with Dygraph Forward Functions

* support more eager tensor api

* fix merge compile error

* fix compile error and fit develop code

* support pure CPU

* fix some logic error in eager_mode

* support _varbase_creator in eager mode

* Added safe_initialized interface to EagerTensor for use in processing dispensable inputs

* for eager mode

* refine

* support multiple constructor for eager tensor

* add place related code

* polish code

* specific randint with dtype of int64

* Support pure cpu test

* eager logic

* refine test in pure cpu

* eager logic

* eager logic

* eager logic, test=develop

* skip core.eager when in inference, test=develop

* refine, test=develop

* refine, test=develop

* call RetainGrad after run forward kernel, test=develop

* refine, test=develop

* support dygraph util, meta, guard test

* support inference test

* refine test and fix initializer failed

* support create varbase and fix retain grad error

* fix windows error

* support test code coverage

* support test code coverage

* support test code coverage
Co-authored-by: Njim19930609 <jim19930609@gmail.com>
Co-authored-by: NWang Huan <wanghuan29@baidu.com>

* add multi_tensor for momentum and clear_grads for optimizer

* fix bug for dygraph

* add unittest

* refine comment

* add param_group

* refine regularizaiton logic

* del clear_grads

* add clear_grads

* add dispensable check of None

* refine clear_grad

* fix build bug

* refine code by comment

* refine code

* add multi tensor check

* refine param_group update

* add multi tensor for static mode

* refine comments

* delete useless comma for momentum

* refine comment for momentum

* refine code by commment

* fix single card 8 unittests in new executor

* fix

* fix

* refine a test case, test=develop

* publish python c api for eager, test=develop

* revert modify about test_allclose_layer.py, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* delete numpy includes, use pybind11 numpy.h, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* suport eager error msg, and add grad test case, test=develop

* refine, test=develop

* refine, test=develop

* generate eager core ops, only 4 ops, test=develop

* Rearranged Eager AutoCodeGen directory structure

* Removed USE_OP in Eager AutoCodeGen

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* open 500 list

* refine, test=develop

* refine, test=develop

* refine, test=develop

* fix auto code gen, test=develop

* Enabled generation for Operators without Grad/Inputs/Outputs

* refine, test=develop

* refine, test=develop

* refine, test=develop

* add to pyobject, test=develop

* Resolved operators without input

* merge pr 37837

* refine

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine,test=develop
Co-authored-by: Njim19930609 <jim19930609@gmail.com>

Paddle don't have to set runtime_include_dir during run CINN.

* refine structure for cuda and rocm

* update

* update

* update

* update

* refine a test case, test=develop

* publish python c api for eager, test=develop

* revert modify about test_allclose_layer.py, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* delete numpy includes, use pybind11 numpy.h, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* suport eager error msg, and add grad test case, test=develop

* refine, test=develop

* refine, test=develop

* [NPU] reorganization for device API abstraction

* [NPU] delete old files

* [NPU] fix npu_collective_helper

* [NPU] fix collective_helper

* [NPU] fix ut

* [NPU] mod memory allocation and hccl_helper

* [NPU] fix place_type

* [NPU] split enfoce.h

* move acl* call into npu_info

* merge conflict

* fix merge

* merge conflict

* merge conflict

* [XPU] Reorganize xpu device codes in platform, test=develop

* fix xpu_header.h, test=develop

* Added HCCL backend support in dynamic graph mode

* fix segmentation fault

* add ut

* GeneratePass support attr condition and mapping, test=develop

* fix coverage, test=develop

* Add fuse_resnet_unit pass, test=develop

* fix CI errors, test=develop

* fix CI errors, test=develop

* fix unittest error when compiling without CUDA, test=develop

* fix static ci error, test=develop

* limit kernel size must equal 1, test=develop

* init

* add feed ops in python side

* import LRScheduler

* update_feed

* refine code format

* change username

* fix

* fix

* fix

* fix

* fix

* update

* update

* update unittests

* fix

* update

* fix

* update

* fix

* fix

* fix

* update

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update send_and_recv op. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* update. test=develop

* fix. test=develop

* fix. test=develop

* fix. test=develop

* fix. test=develop

* fix ut. test=develop

* fix unit. notest,test=coverage

* fix ut. notest, test=coverage

* update. notest,test=coverage

* fix ut. notest, test=coverage

* fix ut. notest, test=coverage

* fix. notest, test=coverage

* fix. notest, test=coverage

* fix ut. notest, test=coverage

* fix ut. notest, test=coverage

* fix ut. notest, test=coverage

* fix ut. notest, test=coverage

* add func. notest, test=coverage

* fix ut. notest, test=coverage

* fix. test=develop

* fix. test=develop

* Simplify constructor of InterpreterCore

* fix bool

* clean code

* refine layer to

* delete comment

* refine logic

* refine code

* refine pure_fp16_init

* refine comment

* try to fix CUDA Graph H2D copy bug

* remove useless code

* fix ci

* fix ROCM CI

* fix CUDA_VERSION

* improve CI coverage

* Refactor conv2d int8 unit test

* Correct according to review and add int8 check

* fix some bug in new executor, test=develop

* fix error message, test=develop

* [hapi] support dygrapg amp O2

* fix problem of static pure fp16 in hapi

* fix bug

* fix format

* fix ut

* follow comments

* update ut

* update amp save/load

* fix ut

* refine code format

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.

Remove RunFromCinn method in PE because We Will Call CinnRunner in Compute method of SubgraphOp

Add use_cinn flag and use it to control whether we run PaddlePaddle using CINN.

Also add:

Replace PaddlePaddle graph with a CINN graph in a pass
PE Method to feed data and run the graph by CINN

* support CUDA Graph on PE

* add ut, fix CI compile

* reduce memory consumption

* fix CUDA 10 CI

* improve coverage

* improve python coverage

* add basic support for CUDA Graph

* fix ci compile error

* fix LOG print, fix windows CI

* follow comments and update

* small fix for default ctor

* fix rocm compile error

* fix CPU compile error

* Initial Commit

* add unittest and add error information

* modify doc

* fix some error

* fix some word

* fix bug cudaDeviceProp* and modify error explanation

* fix cudaDeviceProp* error and unnitest samples

* fix hip error and PADDLE_WITH_HIP

* update style

* fix error is_compiled_with_cuda

* fix paddle.device.cuda.get_device_properties

* fix error for multi thread safe

* update style

* merge conflict

* modify after mentor review

* update style

* delete word

* fix unittest error for windows

* support string input and modify some code

* modify doc to support string input

* fix error for express information

* fix error for express information

* fix unnitest for windows

* fix device.startswith('gpu:')

* format error and doc

* fix after review

* format code

* fix error for doc compile

* fix error for doc compile

* fix error for doc compile

* fix error for doc compile

* fix error for doc compile

* fix py2 error

* fix wrong words and doc

* fix _gpuDeviceProperties

Add basic Cost Model, it uses executor to run program and profile it to get op time.

This is an early basic version, we will add more functions in the future.

* Clean ParaseMemInfo and fix unittest with multi-thread

* fix declare

#### 背景

#35602 提供Python侧开发子图替换类Pass的方式：

- 利用Paddle Python API或者辅助类型定义子图program用来匹配/替换图；
- Python侧注册Pass时，将注册函数最终转换为protobuf定义的PassDesc数据形式，供C++侧进行解析完成Pass实例注册。

本PR即为根据PassDesc规则描述解析生成Pass实例。

#### 方案设计

##### Pass规则验证

在以往的Pass开发中，会存在随着算子迭代引发的匹配失效或者错误匹配的问题，该问题可以通过扫描算子支持的参数设置及参数类型等来判断是否应该使用该Pass或者给出提示需要修改Pass代码。

当前Pass开发中提供了算子兼容性OpCompatSensiblePass用于解决上述问题。但同时还存在不足：由于以往Pass开发在运行时才能获取到pattern信息，所以需要在执行Pass时才可以判断。

使用PassDesc表示的Pass可以在执行Pass前验证上述问题，这个过程在VerifyDesc中完成。

##### 根据匹配子图构造pattern

GeneratePass对于图匹配和替换使用GraphPatternDecetor完成，构造匹配pattern实际上就是将对应对象成员PDPattern中添加PDNode和边关系。该过程在函数`InitGeneratePattern`中完成，该函数没有作为GeneratePass的成员方法，主要出于后续可能开发新的Decetor考虑，GeneratePass与Decetor的操作是没有关联的。

初始化pattern主要通过遍历匹配子图program的全部算子实现：

1. 添加当前算子对应PDNode及限制条件（算子类型、属性限制等）；
2. 遍历当前算子对应输入并从pattern中尝试获取PDNode：
   - 在pattern中获取到PDNode且为输出节点：表示属于匹配子图的中间节点，将该PDNode设置为中间节点；
   - 在pattern中没有获取到PDNode：添加该输入PDNode并设置作为输入节点；
   - 设置输入到算子的边关系；
3. 遍历当前算子对应输出：
   - 在pattern中获取到PDNode且为输入节点：表示属于匹配子图的中间节点，将该PDNode设置为中间节点；
   - 在pattern中没有获取到PDNode：添加该输入PDNode并设置作为输出节点；
   - 设置算子到输出的边关系；

##### 根据替换子图操作graph

替换子图操作的过程在`GetGenerateRewrite`函数中完成，与`InitGeneratePattern`类似没有作为GeneratePass的成员方法。

生成替换子图操作过程如下：

1. 判断冗余替换子图；
2. 遍历替换子图program的全部算子添加替换子图Node：
   1. 添加当前算子的Node及属性设置；
   2. 遍历当前算子对应输入，添加中间variable节点；
   3. 遍历当前算子对应输出，添加中间variable节点；
   4. 添加输入/输出节点与算子节点的边关系；
3. 删除匹配图中属于中间节点的Node；

##### 优化子图验证

对于替换子图或者替换后的计算图是否可以正确运行等，可以在执行Pass时验证，从而防止在后续执行计算图时出现异常。

当前Pass执行直接修改计算图，验证失败时无法很好的完成还原操作，目前子图验证暂时默认成功，留到后续改进。

* fix no_grad context error in dy2stat

* remove useless comments

* fix error by drop_kids in python

* add test and fix review

* Add empty_cache api to release idle gpu memory hold by allocator,test=develop

* Add empty_cache api to release idle gpu memory hold by allocator,test=develop

* Add empty_cache api to release idle gpu memory hold by allocator,test=develop

* Fix test coverage problem for empty_cache

* delete redundant check for empty_cache

* fix the problem of empty_cache's doc

* delete the nvidia-smi comment in doc of empty_cache, test=document_fix

* release gil before op run

* support npu grad test

* fix op_test

* polish code

* fix unittest on windows

* refine pybind interface

* support statistic MemSize of AllocatorPool

* Replace mutex into atomic