* feat(): dynamic_to_static support for ipu.

* fix(): format fix.

* fix format

* fix cpplint error

* use phi::errors

* fix format

* fix format

* fix(): add api to restore patched function.

* fix(): identity_loss uses cpu place as expected kernel type.

* doc(): add IPU dy2static related docs.

* fix(): combine test cases.

* fix format

* fix comment

* fix format

* apply comment

* fix compiling

* fix(): align docs.

* fix(): fix identity_loss function docs.

* fix(): adjust mean and sum in identity_loss.

* fix(): minor docs.

* move API to paddle.incubate.identity_loss

* fix UT
Co-authored-by: Nzhaorui chen <zhaoruic@graphcore.ai>

* make device_id=current_id when not given

* use tracer to get current device id

* [CustomKernel] add custom kernel c api

* update

* update

* fix unable to export capi
Co-authored-by: Nronny1996 <524019753@qq.com>

* refine enforce code

* refine enforce code

* fix compile failed

* fix infrt failed

* unify utils naming style

* polish details

* optimiaze performance of PreparePhiData

* dygraph performance optimization

* split phi and fluid infermeta context

* resolve conflict

* fix type error

* optimize scheduling perf

* spec small vector size

* replace all grad var name

* fix test failed

* move init defalut signature

* polish details

* polish details

* fix no init bug

* init sig for tests

* add init sig for infer

* fix infrt error

* fix infrt failed

* fix kunlun error

* fix infrt failed

* [Eager] support tensor uva, test=windows_ci

* Add headers to fix CI, test=windows_ci

* Expose _uva python interface, Fix windows ci issue

* move rnn kernel to phi

* move infershape of rnn to phi

* fix HIP bug

* rename function

* fix HIP bug

* fix hip bug

* refactor eager flags

* fix flags error when we switch from eager to dygraph

* fix ci problem

* fix ci

* fix ci

* merge develop and fix code style

* merge develop and fix code style

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* merge develop

* move deformable_conv_grad to phi

* move infershape of deformable_conv to phi

* adjust some code format

* move deformable_conv_v1 to phi

* fix some slice bug, test=develop

* eager slice, test=develop

* eager slice, test=develop

* refine, test=develop

* refine, test=develop

* fix bug, test=develop

* refine, test=develop

* rename function name, test=develop

* run python api in eager model and filter the out in argument list

* fix code

* add python api test in TestOp

* test_python_api if self.python_api is set

* fix code by CR

* eager, test=develop

* fix bug, test=develop

* eager, test=develop

* merge legacy to fluid

* eager, test=develop

* eager, test=develop

* Refactor TensorAdd func by template and remove gradient_accumulation in eager

* Remove needless target name

* eager, test=develop

* eager, test=develop

* Use overload instead of template

* Remove legacy code

* Remove legacy code

* selectedrows, test=develop

* Remove DataType test

* eager, test=develop

* eager, test=develop

* support gan, test=develop

* Using Tensor directly instead of using EagerTensor

* support gradient_accumulation

* make test_imperative_lod_tensor_to_selected_rows longer

* make test_imperative_lod_tensor_to_selected_rows longer

* refine code

* ptb, test=develop

* Rename all EagerTensor to Tensor

* Rename some EagerTensor to Tensor

* rename EagerTensor to EagerVariable

* eager, test=develop

* eager, test=develop

* eager, test=develop

* eager, test=develop

* add more test

* eager, test=develop

* Support copiable selected rows and merge develop

* save load, eager, test=develop

* save load, eager, test=develop

* refine, test=develop

* remove useless _set_value method

* refine, test=develop

* refine, test=develop

* revert static_runner, test=develop

* EagerTensor to Tensor, test=develop

* refine, test=develop

* refine, test=develop

* clear grad, test=develop

* merge, develop

* merge, develop

* merge, test=develop

* merge, test=develop

* Support quant and part of slice

* support legacy static save

* extend slim tests time

* remove imperative on inference

* remove imperative on inference

* merge develop

* fix typo

* fix typo

* split slice related code into 2 part for imperative and eager

* split slice from inference

* split slice from inference

* fix test_tensor_register_hook
Co-authored-by: NWang Huan <wanghuan29@baidu.com>
Co-authored-by: NWeilong Wu <veyron_wu@163.com>
Co-authored-by: Nwanghuancoder <wanghuancoder@163.com>

* [MLU] add cncl parallel context and mlu resource pool

* [MLU] fix the cncl_context_test

* rename pten dir to phi

* rename namespace to phi

* rename infrt pten dir to phi

* resolve conflict

* rename pten to phi in cmake

* revert all infrt change

* change needed files

* fix infrt failed

* fix inference failed

* Unify paddle/pten::framework::ddim into pten::ddim

* fix paddle namespace

* compile sucessfully

* fix npu src file

* fix conflict

* fix conflict

* fix tensorrt compiler error

* fix conflict

* fix conflict

* fix tesst file conflict

* fix conflict

* fix mlu file conflict

* fix mlu file conflict

* fix cinn header file conflict

* fix conflict

* fix conflict

* fix conflict

* fix conflict

* support dtype param for auto_cast

* add amp_dtype for tracer

* add unsupported bf16 list

* support bf16 amp for O2

* refine python interface for bfloat16

* refine code

* refine code

* refine unittest

* refine code

* refine code

* add bf16 o1

* refine code by comment

* add gradient accumulator

* add recompute

* [CustomRuntime] Add DeviceManager

* [CustomRuntime] Add DeviceInterface

* [CustomRuntime] Add Stream, Event, DeviceGuard, CallbackManager

* [CustomRuntime] Add plug-in device

* [CustomRuntime] Memory module support PluggableDevice

* [CustomRuntime] Add WITH_PLUGGABLE_DEVICE cmake option

* update

* [API] update API doc based on comments, test=develop
Co-authored-by: Nqili93 <qili93@qq.com>

* #1 migrate dist-related type()-> dtype()

* move datatype function from pten -> fluid/framework

* change type() in imperative into convert(dtype())

* modify xx_tensor->type into xx_tensor->dtype

* change the set_type interface and the caller

* modify xx_tensor.type into xx_tensor.dtype

* fix mutable_data(place, dtype())

* change caller of mutable_data in pten and distributed

* change the caller of mutable_data in fluid/framework

* change the caller of mutable_data in imperative directory

* mutable_data: inference

* update the call of mutable_data

* transfer MakePenScalarArray MakePtenScalar ResetHolderWithType

* pass the compile. the next step is remove VarType in Pten

* fix all and remove VarType from pten. success in linux. Next task is other platform

* fix conflict with develop

* fix compiled error

* Fix reset conversion

* fix conflict

* fix compiled problem

* fix typo

* Fix << in tensor_utils.cc

* fix type->dtype

* fix unittest

* fix tensor init constructor

* fix DataTypeSize for BFloat16

* fix code style

* fix npu compiled error

* fix npu

* compile npu sucessfully

* fix conflict

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

* add the test case for the UVA

* add the context load for the uva

* Add graph_sample kernel

* Add graph_sample commit

* add new commit for graph_sample

* add unsigned long long int

* delete some remarks

* add cpu version

* add cuda eids

* add cpu eids

* delete _uva

* optimize speed: emplace_back, last_layer

* add to_uva_tensor

* add cpu return_eids choice

* add gpu return_eids choice

* add cpu reindex_nodes

* add gpu reindex_nodes

* rename op and add OMP for cpu

* add incubate api

* fix the compile problem for the PADDLE_ENFORE and different device

* fix the rcom and windows compile problem

* add unittest for graph_sample_neighbors

* fix cpu unittest and unique problem

* fix uva unittest, fix cuda unique problem

* fix the windows compile problem

* fix the windows rand_r compile problem

* add correct unittest, add src_eids dispensable

* delete black

* combine uva unittest

* mv Sample_index to Sample_Index; check input shape; fix random sample func

* delete memset & cudaMemset

* fix according to PR comments

* fix rocm ci

* modify function names according to the specification

* fix windows_openblas ci

* refine annotations, fix windows unittest, add default value for uva device_id, fix bug for input nodes with empty neighbors

* fix rocm ci

* rename graph_sample_neighbors as graph_khop_sampler, add incubate api doc

* add data type

* fix conflict
Co-authored-by: Nwawltor <fangzeyang0904@hotmail.com>

* Added selected_rows and rw_lock to pten

* Renamed the unit test target to fix CI

* Removed Class SelectedRows in Fluid, changed include/cmake relationship, use pten::SelectedRows in Fluid

* Remove rw_lock.h,rw_lock_test.cc in fluid

* Use pten::RWLock and pten::AutoRDLock, fix CI

* Use pten::SelectedRows

* Use pten::SelectedRows

* Fix to pass NPU CI

* Use pten::SelectedRows, to pass NPU CI

* To fix NPU CI

* To fix NPU CI again

* 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

* eager test case

* support inference test

* refine test and fix initializer failed

* modify eagertensor patch method

* add eagertensor.clear_grandint, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* support create varbase and fix retain grad error

* call monkey_patch_varbase in _test_eager_guard, test=develop

* fix windows error

* split clear_gradient to clear_gradient and zero_grads, test=develop

* refine, test=develop

* refine, test=develop

* support test_imperative_basic test in eager mode

* remove additional log in variable.h

* remove additional log in variable.h

* remove additional code create in merge

* eager

* fix some eager logic, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* patch_tensor_method_func, test=develop

* refine, test=develop

* eager test case, test=develop

* refine, test=develop

* eager, test=develop

* eager, test=develop

* eager optimizer, test=develop

* eager optimizer, test=develop

* eager test_imperative_optimizer_v2, test=develop

* eager, test=develop

* refine, test=develop

* refine, test=develop

* eager, test=develop

* add resize in share buffer to, test=develop

* eager, test=develop

* fix _share_buffer_to, test=develop

* refine, test=develop

* refine, test=develop

* support eager for dataloader,test=develop
Co-authored-by: Njim19930609 <jim19930609@gmail.com>
Co-authored-by: NJiabinYang <360788950@qq.com>

* Merged LoDTensor with Tensor,test=allcases

* Patched python level LoDTensor

* Patched python level LoDTensor

* Merge Tensor into DenseTensor

* Fixed namespace issues,test=allcases

* Fixed merge issues

* Fixed inference issues

* Fixed NPU test issues

* Fixed merge issues

* add the uva api for the tensor

* fix the compiler problem for the uva

* fix the example for the _uva

* fix the compile problem in the pten library

* update the enviroment support for the uva

* use the make_shared replace the shared_ptr

* add pten::Place data structure.

* update ci problem

* fix ci problem

* update

* using platform::Place=pten::Place

* remove BOOST_GET_CONST for CPUPlace and GPUPlace

* compile pass 25%.

* compile pass 45%

* compile pass 60%

* remove boost_get for xpu npu mlu and ipu

* compile pass on cpu and gpu.

* fix compile problem

* fix compile error.

* update

* fix ci problem

* update

* ci approve

* fix ci problem

* fix ci eager test problem

* remove BOOST_GET_CONST

* fix npu compile

* Added shared_ptr<Allocation> member & corresponding interfaces to Storage

* Removed original pten::Allocation from Storage and adjusted the interfaces accordingly

* Fixed issues with storage offset

* Used place to malloc allocation for TensorStorage

* [Unify Tensors PR #3]Ported framework::Tensor interfaces to pten::DenseTensor

* Fixed issues with place

* Added comments

* Moved mutable_data with stream argument to DenseTensor

* Added set_offset interface

* Fixed CI issues,test=allcases

* [Unify Tensors PR #4] Port LoDTensor interfaces to DenseTensor

* Removed friend class EigenTensor/EigenMatrix/EigenVector from Tensor

* Modified framework::Tensor to inherit from DenseTensor

* Reverted changes too pten_layout() interface

* Removed friend classes

* Rearranged cfunction calls from tensor.data<void>() to tensor.data()

* Fixed CI issues

* Fixed lite issues

* Fixed data() interface issues,test=allcases

* Resolved IsInitialized() issues

* Fixed ResetHolder() issues

* Fixed MKLDNN & Storage issues

* Resolved ShareBufferWith() issues

* Fixed LoD issues

* 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>

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

* add new API: paddle.clone;Tensor.element_size;nn.utils.parameters_to_vector

* fix comment

* add inplace_map for trace_op in pybind

* fix inplace problem of setitem

* refactor the param format  of trace_op
Co-authored-by: Npangyoki <pangyoki@126.com>