* remove dumplicate element_size

* remove tensor_methon_* method

* add new tensor

* fix windows compile bugs

* fix ci bugs

* fix ci bugs

* fix ci bugs

* perfect according comment

* fix ci compile bugs

* add raw tensor

* fix ci bugs

* modify code by comment

* delete String

* [Eager] fix set_value logic when input's dtype is different

* value_tensor

* fix set_value logic when input's dtype is different

* [NPU] apply npu_identity to conv bn and copy2cpu, test=develop

* update npu identity to share data with x, test=develop

* address review comments, test=develop

* rm dependence to "convert_utils.h" in some files

* fix bugs

* replace DataType2String with DataTypeToString

* replace framework::DataTypeSize with phi::SizeOf

* mv convert_function from fluid to phi and rm old map

* recommit with pre-commit

* repalce ProtoVarType with ProtoDataType and update comment.

* fix error about include "dnnl.hpp"

* revert add dep mkldnn to convert_utils in phi

* add mkldnn deps in convert_utils.h in phi

* move deps to convert_utils.h in phi

* support default use_gpudnn=True

* fully support cudnn in phi

* add header file

* add white_list, verify accuracy

* phi support all cudnn

* opt affine_grad

* try different arches of pretrained_model

* try different arches of pretrained_model

* add debug string

* debug eager_method

* add debug string, pass all local ctest

* polish all debug code

* delete use_cudnn relevant code autogen

* fix depthwise_conv2d

* Share all other members of Tensor except use_cudnn

* polish codes according to review opinion

* polish codes according to review opinion, fix bug

* polish codes according to review opinion, opt performance

* polish codes according to review opinion, fix pooling.py

* do not calc reduce_all in eager mode

* refine python c cast list

* refine

* refine

* refine

* refine

* refine

* refine

* refine

* refine

* refine

* dense tensor in eager mode support data_ptr

* remove using lodtensor part1

* polish history code format

* add fp16 data type for set_value

* cancel flip modification

* add fp16 dtype support for set_value

* 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

* enable eager mode on xpu, test=kunlun

* add numpy support to xpu

* fix tensor using error

* fix  error, test=kunlun

* fix failed tests, test=kunlun

* [Eager] polish clone interface

* rm clone in python, add clone in eager_method.cc

* fix linspace error in amp

* fix log

* fix amp error

* fix ocr error which caused by amp

* add more check

* rename dtype ns

* make eager log readable

* fix compile error

* recover test

* invoke ci again

* add paddle.incubate.sparse.is_same_shape

* add paddle.incubate.sparse.is_same_shape

* add paddle.incubate.sparse.is_same_shape

* add paddle.incubate.sparse.is_same_shape

* fix doc

* Enhance slice to support 0 dims Tensor

* Add UT

* [Eager] add get_tensor_from_selected_rows

* add PADDLE_ENFORCE to check SelectedRows

* use _ prefix in temp

* [Eager] call final_state_slice under eager mode

* rm useless comments

* use eager final state instead intermidiate state

* update fill_constant yaml

* update fill_constant yaml

* modify wrapped_infermeta_gen logic to fix special case

* fix slice in manipulation

* use fill_constant_

* modify slice infermeta

* rm final_state_conv2d

* use final_state_slice

* use final_state_slice only

* polish slice, use final state

* add paddle_throw for SplitInferMeta

* rm fill_constant_ temply

* recover array_equal, not allclose

* recover original code

* fix bugs

* update

* update

* update

* code style

* code style check

* support set_grad_ivar for eager

* support set_grad_ivar for eager

* support set_grad_ivar for eager

* clear_gradient use set_constant but not zeros_like

* support is empty

* fix error

* fix code error

* change to fake empty

* using fake empty first

* using fake empty first

* adapt faster tokenizer op

* add eager test

* add unittest

* fix pylayer_memleak

* inc ref before return Py_None

* refine

* refine

* refine

* refine