* Supported Complex2Real Conversion for Eager Dygraph

* Supported Complex2Real Conversion for Eager Dygraph

* Enabled complex type promotion test for matmul_v2

* pylayer, test=develop

* Fix CI issues

* Support initializing specific grad tensors to zero for selected operators

* finish forward, test=develop

* create grad node finish, test=develop

* Merged adj_edges_ with GradSlotMeta

* Fixed monir issue

* backward finish, start dbg, test=develop

* Adjusted num runs

* Recovered Eager performance tests configurations

* Recovered Eager performance tests configurations

* finish, test=develop

* polish, test=develop

* polish, test=develop

* refine, test=develop

* eager, test=develop

* Adjusted performance tests configurations

* Fixed Minor Issues with performance tests

* [Phi] Fix macro name typo

* support set_materialize_grads, test=develop

* suppotr mark_non_differentiable, test=develop

* support once_differentiable, test=develop

* refine, test=develop

* refine, test=develop

* Moved out Edge from GradSlotMeta

* Fixed issues from merge

* Fixed typo

* Addressed review comments

* Fixed merge issues

* Fixed minor issues

* Fixed minor issue

* refine, test=develop

* refine, test=develop

* refine, test=develop

* Fixed major issues and enabled auto_prune test cases

* Fixed issues from merge

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop
Co-authored-by: Njim19930609 <jim19930609@gmail.com>
Co-authored-by: NAurelius84 <zhangliujie@baidu.com>

* Use _C_ops.yolov3_loss in eager mode for test_yolov3.py

* fix code for test_yolov3_loss_op

* remove useless import

* Fix dygraph_mode flag

* So Parser

* add macro

* add macro

* slotrecord

* add macro

* code format

* [Eager] Support SelectedRows in eager mode

* Remove unnecessary codes

* Adapt new dygraph flag

* Refine test_lac.py for eager mode

* refine code

* Fix test_program_translator for eager

* update

* remove useless code

* remove label smooth test

* polish code

* polish code

* polish code

* remove _in_eager_mode error;

* 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

* approve amp for intermediate_dygraph

* add amp_utils for intermediate_dygraph

* add amp needcast check for mlu & npu

* test unittest

* add SetGradNode for set_stop_gradient && add checktensor for GradientHooks

* refine code

* refien unittest of imperative_amp for new dygraph

* inplace api skip amp

* add test_imperative_qat_amp for intermediate amp

* refine code

* refine test_amp ci strategy

* refine unittest code

* refine amp_utils code

* refine amp getpromotetype for some special op

* refine unittest code

* Refine eager run_program OP for dy2st UT

* append run_program error string and refine run_program_grad

* remove some comments

* refine ConstructXGradTensors

* fix benchmark and communicator config

* fix bugs of the_one_ps

* multi program and fix bug in optimizer

* multi program in the_one_ps

* public commcontext

* ps optimizer multi programs

* cvm & datanorm backend

* fix dim

* fix unittest

* fix

* the one ps merge

* remove comm

* add DownpourLiteWorker

* all

* fix

* fix

* device worker downpour lite

* fix

* fix bug in global shuffle

* save inference model

* fix & add log

* fix

* remove log

* fix

* fix save summary

* fix

* fix pscore

* fix

* fix

* fix

* fix

* fix

* remove logs

* fix

* fix

* fix

* fix

* fix

* add some comments

* fix
Co-authored-by: Nesythan <esythan@126.com>

* disable scatter case in test_inplace_eager_fluid

* Update register_hook logic

* Add register_hook test cases
Co-authored-by: Npangyoki <pangyoki@126.com>

* suppor sharding api

* support multi api for sharding in eager

* support multi api for sharding in eager

* fix test

* fix test coverage

* move deformable_conv_grad to phi

* move infershape of deformable_conv to phi

* adjust some code format

* move deformable_conv_v1 to phi

* fix error; test=develop

* update

* close some yaml

* fix backward attrite error; test=develop

* add div test

* polish code; test=develop

* remove none gbk charactor;

* remove some yaml;

* fix optional bug

* recover yaml config

* resolve confilct; test=develop

* close div; test=develop

* 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

* add event record for model profiling

* fix format

* fix format

* fix code example bug

* no

* add profiler statistic

* add profiler feature

* fix bug

* fix bug

* fix bug

* fix bug

* required: gpu

* required: gpu

* fix bug

* required: gpu

* fix ci bug

* fix ci error

* fix ci error

* upgrade document

* fix doc

* fix ci bug

* add doc and fix bug

* nothing

* fix bug

* fix format bug

* modify format

* add deprecated description for old profiler

* fix bug

* fix bug

* fix

* add load_profiler_reuslt doc

* add load_profiler_reuslt doc

* add load_profiler_reuslt doc

* help fix old profiler sample code

* add api doc

* fix format

* fix api doc

* fix api doc format

* fix api doc format

* fix api doc c format

* fix api doc format

* async prepare deps

* fix bug that std::future is not set

* add ut

* refine code

* fix standalone ut

* disable prof

* replace Backend by Place in C++ API

* fix left code

* fix test_to_api bug

* Refine to_tensor for eager mode

* support gpu_pinned

* refine code

* support gpu_pinned copy_to

* fix layer.__setattr__

* support to_tensor for gpu_pinned

* fix unit test

* refine gpu_pinned

* restore the original code

* add is_gup_pinned() and refine eager.Tensor._copy_to()

* remove duplicate code;

* add some line; test=document_fix

* switch eager mode and change it

* set default is eager

* set default is eager

* fix error; test=develop

* fix some error; test=develop

* update

* upd

* update code; test=develop

* update

* fix some bug; test=develop

* fix bug; test=develop

* fix bug; test=develop

* fix bug; test=develop

* fix error; test=develop

* format; test=develop
Co-authored-by: NJiabinYang <360788950@qq.com>

* sync changes

* copy sOpNamescope

* fix UTs

* add authors
Co-authored-by: NXiaobing Wang <xiaobingw@graphcore.ai>
Co-authored-by: NAllen Guo <alleng@graphcore.ai>
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>
Co-authored-by: NZhaorui Chen <zhaoruic@graphcore.ai>
Co-authored-by: NHan Zhao <hanzhao@graphcore.ai>

* fix code-format

* fix compile error

* add comments for feed_op
Co-authored-by: NXiaobing Wang <xiaobingw@graphcore.ai>
Co-authored-by: NZhixin Yao <zhixiny@graphcore.ai>
Co-authored-by: NZhaorui Chen <zhaoruic@graphcore.ai>
Co-authored-by: NHan Zhao <hanzhao@graphcore.ai>

* add add yaml

* add elementwise add yaml; test=develop

* add norm

* update

* add some yaml config; test=develop

* fix bug; test=develop

* fix compare error; test=develop

* revert erger_gen.py

* update; test=deveop

* remove usless code; test=deveop

* fix bug; test=develop

* fix test error; test=develop

* remove int_type; test=develop

* fix type error; test=develop

* format; test=develop

* remove type register; test=develop

* polish code; test=develop

* fix ci error; test=develop

* call sparse api from python

* [Eager] Support eager grad interface, draft version

* Support eager grad interface with allow_unused and multi startup_op

* Fix code format

* Fix allow_unused case, return PyNone if tensor not initialize

* Support output's stop_gradient related to create_graph

* Support grad exception case in eager mode, fix coverage CI

* Update ToPyObject, return PyNone if not initialize

* AccumulationNode add FLAGS_retain_grad_for_all_tensor

* Fix ci issue

* Fix CI issue

* fix, use core.eager.Tensor

* Add func SetBufferSlotRankZeros for GradTensorHolder

* Support retain_graph by using ClearTensorWrappers

* Support retain_graph by using ClearTensorWrappers

* Update retain_graph and no_grad_vars related test case

* Update code gen logic for ClearTensorWrappers

* Fix by override statement

* fix override func args

* Support retain_graph, update unit tests

* Updated ClearTensorWrappers logic

* fix grad python interface

* Use deep copy and update unit tests

* Polish code

* Polish code

* Fix CI issue, Deep copy only use when user set grad_tensors

* Fix CI, use Backward instead RunBackward

* Fix CI, Declare kernel explicitly in test file

* Polish, remove vector of TensorWrapper

* Refactor the logic of grad/backward, polish codes

* Update code after merge upstream develop

* Polish after merge upstream develop

* Update to adapt new GradNodeBase superclass

* Fix error introduced during conflict resolution

* support inplace strategy in eager_fluid state

* solve conflict

* nothing

* Update purify potential_startup_nodes logic

* Fix errors

* Polish code

* Remove useless args for ToPyObject

* Remove useless TensorWrappersSet

* fix record conflict

* Fix code-format, re-install pre-commit

* fix tensor_wrapper bug

* Fix pre-process logic for potential_startup_ops

* Update unit tests, use eager mode

* Fix conflicts

* fix unittest timeout

* little change
Co-authored-by: NWeilong Wu <veyron_wu@163.com>

* Supported Complex2Real Conversion for Eager Dygraph

* Supported Complex2Real Conversion for Eager Dygraph

* Enabled complex type promotion test for matmul_v2

* Fix CI issues

* Merged adj_edges_ with GradSlotMeta

* Fixed monir issue

* Adjusted num runs

* Recovered Eager performance tests configurations

* Recovered Eager performance tests configurations

* Adjusted performance tests configurations

* Fixed Minor Issues with performance tests

* Moved out Edge from GradSlotMeta

* Fixed issues from merge

* Fixed typo

* Addressed review comments

* Fixed minor issues

* fix bug

* fix bug

* [infrt] rename pd dialect from mlir to infrt. test=develop

* [infrt] fix the kernel signature generator bug.

* extract sub-graph

* graph-engine merging

* fix

* fix

* fix heter-ps config

* [Eager] Support eager grad interface, draft version

* Support eager grad interface with allow_unused and multi startup_op

* Fix code format

* Fix allow_unused case, return PyNone if tensor not initialize

* Support output's stop_gradient related to create_graph

* Support grad exception case in eager mode, fix coverage CI

* Update ToPyObject, return PyNone if not initialize

* AccumulationNode add FLAGS_retain_grad_for_all_tensor

* Fix ci issue

* Fix CI issue

* fix, use core.eager.Tensor

* Add func SetBufferSlotRankZeros for GradTensorHolder

* Support retain_graph by using ClearTensorWrappers

* Support retain_graph by using ClearTensorWrappers

* Update retain_graph and no_grad_vars related test case

* Update code gen logic for ClearTensorWrappers

* Fix by override statement

* fix override func args

* Support retain_graph, update unit tests

* Updated ClearTensorWrappers logic

* fix grad python interface

* Use deep copy and update unit tests

* Polish code

* Polish code

* Fix CI issue, Deep copy only use when user set grad_tensors

* Fix CI, use Backward instead RunBackward

* Fix CI, Declare kernel explicitly in test file

* Polish, remove vector of TensorWrapper

* Refactor the logic of grad/backward, polish codes

* Update code after merge upstream develop

* Polish after merge upstream develop

* Update to adapt new GradNodeBase superclass

* Fix error introduced during conflict resolution

* Update purify potential_startup_nodes logic

* Fix errors

* Polish code

* Remove useless args for ToPyObject

* Remove useless TensorWrappersSet

* Fix code-format, re-install pre-commit

* Fix pre-process logic for potential_startup_ops

* Update unit tests, use eager mode

* fix copy_ problem by doing it with phi copy

* improve test coverage

* refactor copy with sr kernel

* [Auto Parallel] Support the auto completion of while_op

* [Auto Parallel] Improve the completion algorithms

* [Auto Parallel] Fix bugs for ernie inference

* [Auto Parallel] Remove attrs which cannot be pickled

* [Auto Parallel] make the dims_mappings of LodTensorArray vars empty

* [Auto Parallel] Fix bugs for the ernie inference in the pipeline parallel

* [Auto Parallel] Remove unncessary comments

* [Auto Parallel] Fix a bug of the CMakeLists

* [Auto Parallel] Use the newest APIs to write the unit test

* [Auto Parallel] Remove unnecessary statements

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

* fix code

* [NPU] add AMP O1 support

* [NPU] fix NOTE and warnings