* move_merge_selected_rows

* update code

* add amp yaml

* fix ci bugs

* move sum

* fix ci bugs

* fix ci bugs

* fix set_lod bugs

* fix infershape bugs

* fix ci bugs

* fix ci unittest bug

* fix ci bugs

* perfect code

* update code according comment

* add unittest

* fix ci bugs

* fix linspace error in amp

* fix log

* fix amp error

* normalize yaml op label

* revert op_compat yaml change

* fix prelu and rnn compat problem

* replace api by op

Adapt tensor output_size for conv2d_transpose and depthwise_conv2d_transpose

* add tensor array

* fix ci bugs

* fix ci bugs

* fix ci bugs

* fix ci bugs

* update by comment

* update code

* [Eager] fix pool2d interface under eager mode

* add use_gpudnn for pool2d

* fix pool2d yaml conflicts

* fix pool2d yaml

* [Eager, Performance optimization] fix pool3d under eager mode

* polish code

* [OpAttr]ksize of pool2d support Tensor type

* fix unittest

* add unittest

* [Eager] fix spectral_norm interface under eager mode

* fix spectral_norm yaml config

* [OpAttr]output_size of unpool support Tensor type

* fix coverage

* fix contain_var

* fix coverage

* fix split bug

* solve function redefine

* fix fluid.layers.split and add unit test

* delete splitInferMeta register in unary.cc

* modify test_split_op GPU unit test

* modify test_split_op GPU unit test place param

* refactor split op and fix infershape bugs

* add () in && and ||

* fix split C++ unit test

* fix split infershape

* add coalesce_tensor kernel

* polist coalesce_tensor kernel

* add sig and InferMeta

* add testcase

* add legacy_api.yaml

* fix infermeta

* fix yaml

* fix kernel implementation

* add compile dependency of phi/kernels

* fix MetaConfig

* add python api

* add and fix testcase

* rnn.py add import

* change _C_ops.coalesce_tensor

* remove useless comments

* add SetBackend

* restore XPU kernel temporarily

* fix code according to PR comments

* Adapt tensor axis for argmin/max

* Add UT

* Polish UT

* [OpAttr]Adapt tensor axis for reduce_min/max/mean/sum/prod

* [OpAttr]padding_value of Pad support Tensor type

* fix unittest

* fix unittest

* fix coverage

* [OpAttr]num_rows/num_colums of eye support Tensor type

* fix attr cast with long type

* add legacy_api.yaml

* set merged_momentum inplace only

* support inplace optional<vector<tensor>>

* add dygraph_mode api

* add merged_adam yaml

* add merged_adam python api

* change testcase of merged_adam and adam

* fix import of test_merged_adam_op

* [OpAttr]axis of Reverse Support Tensor type

* fix coverage

* fix unittest

* [OpAttr]min/max of Uniform_rand support Tensor type

* fix typo

* add python final state

* fix bug

* fix bugs

* fix bug

* fix bug

* revert impl, final state mul not support selected rows

* fix softmax use cudnn error

* add softlable false unitest

* revert loss.py

* add legacy_api.yaml

* set merged_momentum inplace only

* support inplace optional<vector<tensor>>

* add dygraph_mode api

* optimize TensorToConstDenseTensorPtr

* move distribute_fpn_proposals

* fix some code

* fix yaml bugs

* add set dtype

* move proposal_impl to funcs

* fix compile bugs

some python c api use final state

* 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

* 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

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

* reserve linear_interp param

* fix cross device import

* 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

* [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