* [AutoParallel] selective recompute

* add cmakelist

* correct sync behavior for XPU distributed training

XPU support event mechanism similar to cuda event, so it is advisable to
use an event to sync compute/comm streams for performance. However this
mechanism is never fully tested, and inconsistent loss/ending_epochs are
reported. Therefore, this PR replaces event sync with stream waiting as
a temporary solution.

* remove compile warning

* 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

* Fix hAPI bug of not compatible with LayerHook

https://github.com/PaddlePaddle/Paddle/issues/47000

* Fix hAPI bug of not compatible with LayerHook

* Allow to specify train_bs and eval_bs separately in hapi.fit()

* Update model.py

* Update Model.py

* Update test_model.py

* update model.py

* clip extra and intermediate output of op

* fix bug

* fix bug

* polich code

* polich log

* remove unstack in nn.py under fluid

* remove unstack under fluid

* clean fluid elementwise_pow, remove API

* clean elem_pow doc

* clean elementwise_mod

* clean elementwise min, floordiv, mod

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

* fix doc

* address comments

* remove swish in nn.py under fluid

* fix tswish test case

* 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