* rename multi_tensor_adam to fused_adam

* fix some bugs

* fix CI coverage

* rename test_fused_adam.py

* fix some bug

* add test_fused_adam_op.py

* fix some bugs

* fix fused_adam_op.cc

* fix CI bugs

* fix CI bug

* fix CI bug

[XPU] add multi_encoder_xpu_slice_fuse_pass, generate_sequence_xpu_fuse_pass, generate_sequence_xpu kernel (#50570)

* add logspace yaml

* update by comments

* resolve test framework conflicct

* add multi_tenosr_adam

* update multi_tensor_base.py, test_multi_tensor_adam.py, adamw.py

* fix adam.py optimizer.py

* fix adamw.py

* fix test_multi_tensor_adam.py

* fix CI bug

* fix CI coverage

* fix ci bug

* fix betapow

* fix some bugs

* fix test_adamw_op.py

* fix CI coverage

* fix multi_tensor_adam_kernel.cc

* fix CI bug

* fix multi_tensor_adam_op.cc and test_multi_tensor_adam.py

* fix code style

* update C++ parts

* remove python parts modification temporarily

* add C++ ut

* update betapow copy code logic

* fix ci ut

* fix windows ci

* fix coverage ci

* improve coverage rate

---------
Co-authored-by: Nsneaxiy <sneaxiy@126.com>

* add check for input of slice

* add unittest

* fix 0-d tensor for arg_min_max op.

* fix xpu.

* fix zero dims

* fix

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* Update test_zero_dim_tensor.py

* Update test_zero_dim_tensor_xpu.py

* Update test_zero_dim_tensor.py

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* add axis check for unbind

* add axis range check for unbind

* update unittest and axis validation for unbind

* add unittest invalid axis for unbind

* restore axis extract for unbind

* fix incorrect output shape of broadcast

* add unittest

* support 0d tensor for interpolate

* support 0d tensor for interpolate

* add xpu unittest for interp

* update unittest for interpolate

* fix coverage

* fix code style

* fix for coverage

* fix coverage

* add axis check in UniqueRawInferMeta

* add unittest for negative axis

* simplify check for unique

* add elements count check in atan2

* add unittest and pre-check in inferMeta

* add dimension check

* add zero size check in matrix_power_kernel_impl.h

* add zero size check in matrix_power_kernel_impl.h

* add zero size check in unittest

* bug_fix

* bug_fix

* bug_fix

* bug_fix

* bug_fix

* bug fix

* bug_fix

* bug_fix

* add static check

* delete the dy codes

* support negative index in repeat_interleave

* add unittest

* Add the cumsum 0d tensor

* xpu and cpu judge the 0d  tensor

* change to 2022 to 2023 in new commit

* fix the reverse logic

* add zero dims test

* update code

* fix zero dims

* update code

* lerp support 0 Tensor

* fix lerp grad

* fix lerp zero test

* fix 0D + ND/ND + 0D

* fix check

* update code

* fix lerp infer shape

* static backward test

* updata static graph test

* [Zero-Dim] support input 0D Tensor for maximum,minimum,allclose,sigmoid_focal_loss

* [Zero-Dim] add backward test for sigmoid_focal_loss with 0-D input Tensor

* support the drop_empty_grad in backward

* change code according to yunfei's review suggestion

* add 0-d support for paddle.kthvalue

* add 0-d support for paddle.mode

* fix coverage test for device

* fix check-bug in windows

* change axis check from LT to LE

* add shape & value check for grad when input is 0d tensor

* zero-tensor

* remove unused

* zero_dim_xpu

* relocate

* add value test

* fix syntax

* flatten op support 0D-tensor

* add test in zero dim py

* fix shape should be list

* short code for ci-coverage

* add backward test

* simple code for ci coverage

* add axis check

* add 0D-tensor test in test_flatten_contiguous_range_op.py

* add axis error test for Coverage CI

* add more test for CI-Coverage

* add more test for CI-Coverage

* support 0D for paddle.sort/argsort

* support 0D tensor for paddle.sort/argsort in xpu

* fix bug

* fix grad and add value assertion

* Use BroadcastKernel and ReduceKernel to optimize expand and expand_grad.

* Correct the axis when there is only 1 input in BroadcastKernel.

* Add the calculate of output's shape.