* review

* modify opcompat bug

* modify pybind

* Fused elementwises kernels and ops

* change fuse pass name

* adjust .pbtxt files

* adjust quantization attributes

* add missing arguments and fix others, review fixed

* simplify fused kernel registration

* fix elementwise unit tests

* reuse one fused elementwise op

* adjust proto

* Add supported datatypes

* Change 'Scale' to 'scale' in tests, change some tests to onednn

* Revert breaking changes

* Fix unit tests

* Delete obsolete test cases

* Delete commented out code

* Fix codestyle

* delete temporary condition

* fix conflicts and delete duplicate fusing

* Fix code after merge

* Move tests to new directory

* fix tests volatility

* Rename test_elementwise_add_onednn_op.py to test_elementwise_add_mkldnn_op.py

* Update CMakeLists.txt add mkldnn op test

---------
Co-authored-by: NSilv3S <slawomir.siwek@intel.com>

* simplify layer_norm_op.cc

* support auto generate for op layer_norm

* update unittest for composite_layer_norm

* remove layer_norm_op.cc from scripts

* replace layer_norm_op with generated_op

* add get_expected_kernel for layer_norm

* update cmake kernel register function for layer_norm_mkldnn_op

* Add i1 and i1e op

* resolve merge conflicts

* static graph autogen code support for softmax op

* bug fixed

* fix PR-CI-Windows error

* fix CI error

* bug fixed

* fix conflicts

* mv InstanceNorm

* modify op_version.yaml

* modify add Operator:: in get_expected_kernel_func.cc

* rm gradexpectedkernel

* add extra

* add float epsilon=1e-5

* add rules

* modify no kernel yaml parse

* success op generate

* success test_silu_double

* modify bug

* modify static error

* modify silu_grad input

* modify kernel signature

* modify kernel signature

* code style

* code style

* review

* delete opinfo modify

* update

* Update backward.h

* Update composite_backward_api.h

* Update tensor_utils.cc

* Update backward.cc

* update

* stype

* update

* add ctest

* code stype

* modify concat_grad add sum comp rule

* delete default mul_double_grad

* delete high grad test

* recover yaml

* modify yaml

* recover add_double_grad prim

* added base code for i0 and i0e

* added grad base code for i0 and i0e

* added i0 and i0e python code

* added ops and backward yaml config

* added i0 and i0e cpu kernel, but not test.

* added i0 and i0e code and unitest files

* added test files

* added i0/i0e gpu implementation code

* updated code style

* updated code style

* fixed unitests code

* updated i0 with eigen3

* fixed bug and added more test cases

* refactor: fixed static graph bug

* refactor: removed i0 and i0e from op_compat

* refactor: updated code style

* refactor: updated op_compat.yaml

* refactor: updated op_compat.yaml

* refactor: fixed op name mapping and optimize unittest case

* refactor: manually implement i0 / i0e

* refactor: added grad kernel for i0 / i0e,didn't finish

* Update math.py

* refactor: added equation to doc in English and added comments for computing i0 / i0e gradient

* refactor: removed eigen implementation

* refactor: finished i0 / i0e cpu and gpu op

* refactor: updated code style

* fix: find  a bug but not fix

* fix: incorrect unittest cases

* update: updated code style and remove my file

* update: updated unittest case

* fix: fixed sign error

* fix: fixed mistakes when merging

* refactor: updated code style

* refactor: remove unused code

* refactor: updated code style

* add rules

* modify silu_grad input

* modify kernel signature

* modify kernel signature

* code style

* review

* modify concat_grad add sum comp rule

* delete default mul_double_grad

* delete high grad test

* recover yaml

* modify yaml

* add index_put api

* fix value broadcast in backward and add test case in static

* add timeout=120s for index_put

* add op_compat for index_put

* add inplace index_put test

* add test case when index tensor in indices is int32 when indices.size less than x.dims

* add index_put api backward in cpu place

* add backward test case

* refactor code to delete some duplicated code

* replace reshape with resize for decrease extra memcpy

* add datatype flag in backward yaml

* fix bug in documentation

* Update python/paddle/tensor/manipulation.py

---------
Co-authored-by: NLigoml <39876205+Ligoml@users.noreply.github.com>

* [phi][api] add autogen code coalesce_tensor

* [phi][api]fix args

* [phi][api] supplement attrs

* update

* fix bug

* support parsing fixed kernel data_type

* update op_compat

* update

* add mul doubel grad

* add sub_double_grad

* add add sub high test

* add mutiply test

* modify other unsqueeze

* delete api.yaml

* only for make ci run

* midify unsqueeze

* modify unsqueeze

* tmp

* modify operants gen

* [static op generation] triangular_solve

* [phi] mv triangular_solve_grad to static_backward

* [phi] fix import

* [phi] mv to ops.yaml、 backward.yaml

* fix forward attr

* [phi] fix triangular_solve_grad args

* modify concat_grad add sum comp rule

* modify opcompat

* add pad op

* add_some_code

* modify some code

* add some code

* add some code

* modify some code

* add some code

* modify some code

* Update composite_backward_api.h

* modify some code

* add some code

* add some code

* add some code

* add scatter_nd_add comp

* add scatter_nd_add prim

* fix

* fix

* add public_python_api in TestScatterNdAddSimpleOp setup function

* fix composite_backward_api.h

* fix composite_backward

* add test cases

* fix composite_backward_api.h, unittest

* support register single .cu file

* add register GPU kernel function

Add paddle.geometric.weighted_sample_neighbors API

* support the 'generate_proposals' for generating static graph ops

* fix bug

* fix bug

* Update ops.yaml

fix bug

* remove the generate_proposals_v2_op.cc from CMakeLists.txt

* fix bug

* fix bug

* delete overwrite from gather_grad

* fix

* Update gather_grad_kernel.cc

* remove axis from elementwise_grad

* Update elementwise_sig.cc

* add tile_grad composite rule

* support auto generate for op adam optimizer

* remove unnecessary files

* support auto generate for op adamw optimizer

* support auto generate for op merged_adam optimizer

* use manual_signature in adam_