* 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>

* Refactor partial_grad/backward logic

* Add DuplicateCheck and polish code

* Refactor partial_grad/backward more clearly

* Refactor GeneralGrad by SingleInstance

* 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

* add infer meta; test=develop

* add histogram infer meta; test=develop

* fix unitest bug; test=develop

* format; test=develop

* format; test=develop

* bn not use new infer meta; test=develop

* add infer meta; test=develop

* fixbug; test=develop

* fix bug;

* recover unitest; test=develop

* [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>

[NPU] fix fp16 (PART I)

* support assign x.shape to dict['key'] in dy2st

* remove replace_dot

* refine unit test

* 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

[NPU] fix fp16 (PART II)

* update

* fix bugs; test=develop

* update; test=develop

* fix test compile error; test=develop

* fix cpu compile error; test=develop

* fix test error; test=develo

* fix layer_norm_op plugin error; test=develop

* fix error; test=develop

* fix test bug; test=develop

* update; test=develop

* polish code; test=develop

* fix bugs; test=develop

* remove unused depency; test=develop

* polish code; test=develop

* [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

* for test_mnist.py

* remove comments

* using type() replace isinstance()

* valid vars for run program OP in io.py

* open test_mnist in eager_gurad for coverage

* Optimize performance

* optimiaze c++ api performance

* remove unsed code

* fix paddle throw

* updata format

* segment pool support for int int64 kernel.

* add support in python api

* init commit

* correct namespace

* Add yaml config for pool2d

* Fix CI error

* Fix code format error

* Refactor elementwise op grad classes

* Add more refactor changes

* Revert set layout and format deletion

* Fix failing elementwise test

* Modify save_quant_model.py to support differnet input and output filenames

* Correct wrong order of arguments

* align to cn docs

* add parameter `weight_decay`

* [PHI] Migrate index_select op

* [PHI] Fix bug in test_variable

* [PHI] migrate index_select op

* [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

* add some op for full_quantization

* add expert count op

add ut for expert_count

* update UT only for cuda

* fix for rocm

* update ut

* add moe module

* add expert count op

add ut for expert_count

* update UT only for cuda

* update ut

* add moe module

* make expert count private

* rename expert count op
Co-authored-by: Nhlygit66666 <2570058140@qq.com>

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

* fix code

* formatted.

* Remove dead code.

* Fix error message in the unit test.

* polish formats.

* [Einsum] fix bugs.

* [NPU] add AMP O1 support

* [NPU] fix NOTE and warnings