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

Get grads types from cpp for adam to speed up

* Get params and grads in cpp to avoid gpu idel time

* Using python param instead of cpp return param to fix test_asp_optimize_dynamic.py

* Get grads from cpp and construct params_grads on python

* Check meta and remove comments

* Get three grad lists in CPP to avoid gpu idle time

* Support legacy mode

* remove needless using tensor

* remove needless using tensor

* resolve conflict

* replace tensor using

* fix format error

* revert needless changing

* fix rocm and npu compile error

* fix cinn compile error

* fix format error

* fix mkldnn format error

* fix mkldnn format error

* fix cinn compile error

* fix cinn compile error

* fix cinn compile error

* resolve conflict

* refine gil use

* saved_tensors_hooks

* Pybind Fucniton and hide ExecutorEngine and PEEngine

* Remove FunctionNames in compilation_unit

* Polish function code

* Rename funciton to engine

* Fix Log msg and doc

* Rename Function to Engine and using new Function class to warp Engine

* Rename EngineInfo

* Adjust member variable order

* [Eager] fix to_uva_tensor without specific gpu number

* Update test_tensor_uva.py

update test case

* init

* move CUDAStream to phi

* fix compilation

* merge develop

* add stream_owned_ member

* split cuda_stream.h

* fix cpu compile

* fix constructor

* fix bug

* fix windows compile

* fix inference test_levit

* fix windows tests

* release gil when run backward

* [JIT]Layer support eager dygraph mode and polish Function interface

* remove usless code

* fix #define

* fix custom op error

* fix code error

* remove storage

* add glog include

* add glog include

* add glog include

* fix pylayer_memleak

* inc ref before return Py_None

* refine

* refine

* refine

* refine

* [Eager] support tensor uva, test=windows_ci

* Add headers to fix CI, test=windows_ci

* Expose _uva python interface, Fix windows ci issue

* Update ResNet test cases

* [Eager] Support uva, adamax, fill_diagonal_, to_list and so on.

* Fix CI

* Updated CUDA defined statement

* Fix CI

* Update headers, Fix CI

* Remove useless setting

* Updated func name to Fix windows-CI

* Remove tensor uva related codes

* Remove uva related code

* recover original test

* support pinned, test=develop

* support async_write, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine,test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refactor eager flags

* fix flags error when we switch from eager to dygraph

* fix ci problem

* fix ci

* fix ci

* merge develop and fix code style

* merge develop and fix code style

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* merge develop

* replace Backend by Place in C++ API

* fix left code

* fix test_to_api bug

* Supported Complex2Real Conversion for Eager Dygraph

* Supported Complex2Real Conversion for Eager Dygraph

* Enabled complex type promotion test for matmul_v2

* Fix CI issues

* Merged adj_edges_ with GradSlotMeta

* Fixed monir issue

* Adjusted num runs

* Recovered Eager performance tests configurations

* Recovered Eager performance tests configurations

* Adjusted performance tests configurations

* Fixed Minor Issues with performance tests

* Moved out Edge from GradSlotMeta

* Fixed issues from merge

* Fixed typo

* Addressed review comments

* Fixed minor issues

* [Eager] Support eager grad interface, draft version

* Support eager grad interface with allow_unused and multi startup_op

* Fix code format

* Fix allow_unused case, return PyNone if tensor not initialize

* Support output's stop_gradient related to create_graph

* Support grad exception case in eager mode, fix coverage CI

* Update ToPyObject, return PyNone if not initialize

* AccumulationNode add FLAGS_retain_grad_for_all_tensor

* Fix ci issue

* Fix CI issue

* fix, use core.eager.Tensor

* Add func SetBufferSlotRankZeros for GradTensorHolder

* Support retain_graph by using ClearTensorWrappers

* Support retain_graph by using ClearTensorWrappers

* Update retain_graph and no_grad_vars related test case

* Update code gen logic for ClearTensorWrappers

* Fix by override statement

* fix override func args

* Support retain_graph, update unit tests

* Updated ClearTensorWrappers logic

* fix grad python interface

* Use deep copy and update unit tests

* Polish code

* Polish code

* Fix CI issue, Deep copy only use when user set grad_tensors

* Fix CI, use Backward instead RunBackward

* Fix CI, Declare kernel explicitly in test file

* Polish, remove vector of TensorWrapper

* Refactor the logic of grad/backward, polish codes

* Update code after merge upstream develop

* Polish after merge upstream develop

* Update to adapt new GradNodeBase superclass

* Fix error introduced during conflict resolution

* Update purify potential_startup_nodes logic

* Fix errors

* Polish code

* Remove useless args for ToPyObject

* Remove useless TensorWrappersSet

* Fix code-format, re-install pre-commit

* Fix pre-process logic for potential_startup_ops

* Update unit tests, use eager mode

* eager, test=develop

* fix bug, test=develop

* eager, test=develop

* merge legacy to fluid

* eager, test=develop

* eager, test=develop

* Refactor TensorAdd func by template and remove gradient_accumulation in eager

* Remove needless target name

* eager, test=develop

* eager, test=develop

* Use overload instead of template

* Remove legacy code

* Remove legacy code

* selectedrows, test=develop

* Remove DataType test

* eager, test=develop

* eager, test=develop

* support gan, test=develop

* Using Tensor directly instead of using EagerTensor

* support gradient_accumulation

* make test_imperative_lod_tensor_to_selected_rows longer

* make test_imperative_lod_tensor_to_selected_rows longer

* refine code

* ptb, test=develop

* Rename all EagerTensor to Tensor

* Rename some EagerTensor to Tensor

* rename EagerTensor to EagerVariable

* eager, test=develop

* eager, test=develop

* eager, test=develop

* eager, test=develop

* add more test

* eager, test=develop

* Support copiable selected rows and merge develop

* save load, eager, test=develop

* save load, eager, test=develop

* refine, test=develop

* remove useless _set_value method

* refine, test=develop

* refine, test=develop

* revert static_runner, test=develop

* EagerTensor to Tensor, test=develop

* refine, test=develop

* refine, test=develop

* clear grad, test=develop

* merge, develop

* merge, develop

* merge, test=develop

* merge, test=develop

* Support quant and part of slice

* support legacy static save

* extend slim tests time

* remove imperative on inference

* remove imperative on inference

* merge develop

* fix typo

* fix typo

* split slice related code into 2 part for imperative and eager

* split slice from inference

* split slice from inference

* fix test_tensor_register_hook

* support custom op in eager mode

* fix inference deps error

* split eager utils from custom operator

* fix type match

* fix typo
Co-authored-by: NWang Huan <wanghuan29@baidu.com>
Co-authored-by: NWeilong Wu <veyron_wu@163.com>
Co-authored-by: Nwanghuancoder <wanghuancoder@163.com>

* rename pten_utils to phi_utils

* rename pten_utils target

* rename Pten to Phi

* replace pten with phi

* resolve conflict

* rename pten dir to phi

* rename namespace to phi

* rename infrt pten dir to phi

* resolve conflict

* rename pten to phi in cmake

* revert all infrt change

* change needed files

* fix infrt failed

* fix inference failed

* merge legacy to fluid

* Remove legacy code

* Remove legacy code

* Remove DataType test

* Using Tensor directly instead of using EagerTensor

* support gradient_accumulation

* make test_imperative_lod_tensor_to_selected_rows longer

* make test_imperative_lod_tensor_to_selected_rows longer

* refine code

* Rename all EagerTensor to Tensor

* Rename some EagerTensor to Tensor

* rename EagerTensor to EagerVariable

* add more test

* merge develop and refine code

* #1 migrate dist-related type()-> dtype()

* move datatype function from pten -> fluid/framework

* change type() in imperative into convert(dtype())

* modify xx_tensor->type into xx_tensor->dtype

* change the set_type interface and the caller

* modify xx_tensor.type into xx_tensor.dtype

* fix mutable_data(place, dtype())

* change caller of mutable_data in pten and distributed

* change the caller of mutable_data in fluid/framework

* change the caller of mutable_data in imperative directory

* mutable_data: inference

* update the call of mutable_data

* transfer MakePenScalarArray MakePtenScalar ResetHolderWithType

* pass the compile. the next step is remove VarType in Pten

* fix all and remove VarType from pten. success in linux. Next task is other platform

* fix conflict with develop

* fix compiled error

* Fix reset conversion

* fix conflict

* fix compiled problem

* fix typo

* Fix << in tensor_utils.cc

* fix type->dtype

* fix unittest

* fix tensor init constructor

* fix DataTypeSize for BFloat16

* fix code style

* fix npu compiled error

* fix npu

* compile npu sucessfully

* fix conflict

* fix conflict
Co-authored-by: Nxiongkun <xiongkun03@baidu.com>

* merge legacy to fluid

* Remove legacy code

* Remove legacy code

* Remove DataType test

* Using Tensor directly instead of using EagerTensor

* support gradient_accumulation

* make test_imperative_lod_tensor_to_selected_rows longer

* make test_imperative_lod_tensor_to_selected_rows longer