* add build

* add build

* refine code

* refine code

* refine code

* refine code

* refine interface

* fix bug

* fix bug

* fix bug

* refine yaml

* static graph autogen code for check_finite_and_unscale_ op

* bug fixed

* update

* update cmake

* update

* update

* update

* update

* Revert "update cmake"

This reverts commit 1e1dc1b2bc9967b725201272607f939260070fd4.

* update

* update

* update

* update

* support auto generate for static op reduce_amax

* set reduce_amax attr 'axis' type as IntArray

* refine auto gen

* refine code

* refine code

* fix bug

* fix bug

* fix bug

* fix bug

* fix bug

* fix bug

* update

* update

* update

* update

* update

* update

* update

* update

* support auto generate for activation_op relu6

* add generated_static_op for activation_op in CMakeLists.txt

Fixed the bug in the api.cc file where there was an inconsistency between the specified type (std::vector<DenseTensor*>&) in the function pointer kernel_signature and the type of the phi kernel parameter (std::vector<DenseTensor*>) when the phi kernel is set to output as std::vector<DenseTensor*>. test=kunlun (#54053)

* [phi] autogen code tril_triu

* [phi][api]fix tril_triu_grad args

* [fluid] clean cmake; [phi] fix infer_meta

* static graph autogen code support for pad3d op

* bug fixed

* add ut for pad3d mkldnn op

* fix coverage

* fix bug

* fix bug

* Delete test_pad3d_mkldnn_op.py

* fix the static op generation for group_norm

* fix bug of mismatch

* fix bug of AssertionError

* fix setting of composite

* add minimum grad composite rules

* add public python api

* fix format

* fix format

* update testcase

* fix testcase

* fix format

* fix cmakelist.txt

* fix format

* fix param problem

* fix op and composite rule

* fix bf16 cpu support problem

* fix bf16 cpu issue

* fix axis error log

* add axis for maximum

* revert commit

* remove .orig

* fix generic problem

* revert max op

* fix axis error

* fix maximum axis

* fix test_check_output

* fix cinn

* fix minimum maximum axis check

* 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