* fix device id issue for xpu eager

xpu device id is not correctly set in eager mode, thus vars are on dev0 unless
XPUDeviceGurad is called, leading to this error message for all node rank != 0:
"NotImplementedError: (Unimplemented) Place Place(xpu:0) is not supported."

* fix typo

* fix pybind error

* Refactor conv_kernel and conv_grad_kernel to provide interface for CUDNNv8 implementation

* Fix macro

* Add implementation for conv_kernel and conv_grad_kernel

* Modification after rebase onto latest develop

* Modify plan cache to comply with the API of phi::autotune

* Refactor to reduce duplicate code

* Review fix:
- move functions in  conv_kernel_impl_v8.h and conv_grad_kernel_impl_v8.h to conv_kernel.cu and conv_grad_kernelk.cu
- add const specifier for input tensor
- add logging when plans fail to execute
- move CudnnConvBwdFilterV8 and CudnnConvBwdDataV8 to conv_cudnn_frontend.h

* - move plan building outside of cache

* Fix ROCM build

* remove "gpu_primitives.h" in fluid namespace

* fix PR-CI-GpuPS fail

* fix PR-CI-GpuPS fail

* clip extra and intermediate output of op

* fix bug

* fix bug

* polich code

* polich log

* [NPU] add _npu_identity op and api, test=develop

* fix doc

* address comments

* int scale

* round

* revert commit

* standard api

* fix xpu bugs

* add_cast_bool

* cast

* Implement a common dims simplifier.

* Fix the include position error.

* Reduce the cpu overhead of broadcast computing.

* rm "paddle/fluid/operators/math.h" in phi

* rm "paddle/fluid/operators/math.h" in fluit

Support bfloat16 for adamw and adam optimizer. Fit the lr for pure bf16 training with tensor fusion. (#48041)

* add bfloat16 for adamw

* set lr not to bfloat16 for pure bf16 training

* update the logic

* update the adamw optimizer

* support bfloat for adam

* add vectorized bfloat16 atomicAdd

* fix compile error

* fix compile error again

* fix V100 compile error

* fix V100 compile again

* [NPU] update npu prop, test=develop

* remove ddim.h

* remove diff

* update storage prop, test=develop

* add_fill_any_like

* add_fill_any_like

* elementwise_op

* add teller

* modify ut

* comments

* modify ut

* return

* modify

* simplify depthwise_conv2d phi kernel selection

* fix depthwise_conv2d

* Enable bf16 in oneDNN bilinear_interp kernel

* Fix bilinear_interp_v2 not enabled in models

* Remove unnecessary checks

* add stat tool

* add roll and roll_grad kernels and strided_slice and strided_slice_grad kernels, test=kunlun

* embedding and embedding_grad add int32 input, test=kunlun

* remove avx check

* fix bug;

* refactor: update pg custom

* fix: use new api in ut

* fix: typo

* revert: recover legacy apis

* fix: add GetDeviceContext