* add forward inplace final state api

* fix bug

* fix reshape

* fix coverage

* add inplace info for erfinv, lerp, put_along_axis

* fix put_along_axis infer_meta

* fix format

* update yaml

* fix

* add group_norm dyanmic plugin

* transfer trilinear op to phi, change name from trilinear_interp_v2 to trilinear_interp

* reserve linear_interp param

* change testcase scale if-branch

* testcase test_imperative_case

* fix trilinear testcase

* import paddle in test_trilinear_interp_v2

* [OpAttr]Squeeze axes support Tensor

* add support_tensor

* fix unittest

* fix coverage

* change to async mode for xpu multi-card training in static graph mode

* minor bugfix

* irrelevant. move to another pr

* move change to other pr

* fix stream issue

* fix 'stream not meet with current context' error

* fix branch diverge, test=kunlun

* transfer bilinear op to phi, change bname from bilinear_interp_v2 to bilinear_interp

* reserve linear_interp param

* fix cross device import

* use addKernel

* fix compile

* remove elementwiseAddto

* add return

* fix custom place

* xpu unittest grad compute supports more types, *test=kunlun

* add instance norm xpu, *test=kunlun

* transfer bicubic_interp op to phi, change name from bicubic_interp_v2 to bicubic_interp

* test final_state_bicubic_interp api

* testcase match imperative case

* fix squared_l2_norm bug

* update buffer.h

* move check finite and unscale kernel into phi

* move infershape into phi

* move update_loss_scaling kernel into phi

* remove original kernels

* move update loss scaling infershape into phi

* add header for xpu and npu

* solve coverage failed

* fix npu test failed

* remove mutable data in cu file

* fix new executor failed

* add valid check for meta tensor output

* initial commit

* fix op maker bug

* fix mul grad bug

* add unittest

* fix add grad bug, add cpu kernel

* add paddle.geometric.message_passing

* add paddle.geometric.send_uv api, add unittest

* add fp16 judgement

* fix file typo, move compute_type to message_op

* add impl file

* fix unittest timeout time

* add review revise

* [Eager draft] forward_only interface migrate to autograd_api

* strings api add dygraph forward function

* rm useless comments

* draft version for check CI

* fix ci

* forward-only no need compute_require_grad and pass stop_gradient, rm useless comments

* polish yaml and using CPUPlace = phi::CPUPlace

* rm useless comments

* polish yaml and update some test case

* rm useless funcs

* polish eager_gen code

* polish code

* change name linear_interp_v2 to linear_interp

* fix deprecated_op_names

* deprecated_op_names add linear_interp_grad

* fix sync batch norm to inplace

* fix compile error

* remove v2_transpose_reshape

* matmul_transpose_reshape

* reshape_transpose_matmul

* Add int8 support for matmulV2

* restore ut

* adjust old ut

* restore parallel UT ruels

* remove mkldnn code from base ops

* move enforces to pass

* remove duplicated functions

* delete duplicated enforces

* feedback from review

* add comments to variables

* enable eltwise support

* dynamic attribute

* remove fusepass tests from op test

* remove fuse pass cases from op test

* revert introduction of dynamic attributes

* style
Co-authored-by: Nwozna <joanna.wozna@intel.com>

* support optional<vector<Tensor>> in yaml and eager

* delete useless comments in eager_gen.py

* fix api_base.py support optional<vector<TTensor>>

* python_c_gen.py support optional<vector<tensor>>

* transfer linear_interp_v2 yaml from fluid to phi

* fix op_test typo error

* change linear_interp_v2 testcase

* fix args in final_state_linear_interp_v2

* fix zeropad2d typo. test=document_fix

* transfer memcpy_h2d from fluid to phi

* use UnchangedInferMeta instead

* restore test_standalone_executor

* add newline to fix codestyle check

* rename pt -> phi

* simplify logic and add check

* make the comment more clear

* remove useless comment

* refine code

* remove some custom_impl api and make them generated by yaml completely

* delete useless code

* fix adamw bug

* fix infermeta

* revert adamw

* polish code

* fix bug

* enhance grid_sampler to support 3d input

* add init file

* add op definition and infermeta

* add kernel definition funcs

* add broadcast infer shape

* add gpu forward kernel

* delete SUB and DIV

* add x_grad

* add template

* add e_grad for min and max

* fix small bug

* temp commit

* temp commit

* add e_grad for sum and mean

* fix some compile bug

* fix compile bugs

* fix compile problem

* add sum forward unittest

* fix broadcast error, add kernel sig, register e_grad, change unit test

* fix grad

* add temp grad fix

* temp commit

* add min max unittest

* add max, min unittest, fix mul bug

* add cpu forward sum and mean

* add forward min max, fix mean unittest

* add cpu backward min max

* fix code-style

* add backward sum mean

* fix rocm ci

* set uniitest timeout

* fix bug of x broadcast to e, gpu grad

* fix bug of x broadcast to e, cpu grad

* rename BOOST_GET_CONST macro

* fix rocm ci

* mv graph_send_e_recv to graph_send_ue_recv

* move out_size to IntArray

* add eager op test

* fix max pool type bug, add unittest for api

* revise api doc

* add fp16 for atomic min and max, add unittest

* add unittest

* add fp16 support for graph_send_recv

* fix unittest fp16 bug

* change OutSizeTensor to Out_size

* move E to Y

* add copyright, fix comment

* review code

* fix thread block size

* fix thread block size

* change api attribute name: pool_type to reduce_op, compute_type to message_op

* change api attribute name, move pool_type to reduce_op, move compute_type to message_op

* make affine_grid_op support 5d_input on cpu and gpu

* fix

* add control flag and input shapes for new dygraph

* fix file mode

* improve code coverage

* fix a bug in statstic

* fix according to review

* optimize performance

* fix

* fix submanifold conv

1. change the codegen code to avoid conversion from heterogeneous 'initializer list' to tuple, which fails on gcc 5.4; (#45036)

2. add a template CheckTensorHasNanOrInf to handle arbitary tuple of supported types.