This reverts commit ee813e34.

* add maxunpool3d op

* update doc for maxunpool3d op

* update doc for maxunpool3d op

* update doc for maxunpool3d op

* update sample code for maxunpool3d

* add maxunpool1d op

* update some code for maxunpool1d

* add mish operator and api

* remove redundant code and modify grad_atol of mish unittest

* modify mish code to be consistent with other activation implementation

* add multi tensor for adam

* add merged_adam op

* refine code

* refine adam compute logic

* delete the modification of dygraph

* CI

* check CI

* modify the retrun value of get_lr

* reuploaded files

* Changed year from 2021 to 2022

* minor change

* fixed requirements.txt file

* Handled special sum_grad_op code gen in Eager Dygraph

* Fixed merge issues

* added exp activation and use_dst_for_bwd kernels

* CI RERUN

* minor change

* Rearranged Eager AutoCodeGen directory structure

* Removed USE_OP in Eager AutoCodeGen

* Enabled generation for Operators without Grad/Inputs/Outputs

* Resolved operators without input

* Fixed merge conflicts

* Enabled Eager AutoCodeGen for 10+ more operators

* Refactored Eager AutoCodeGen with more organized helper objects

* Enabled Eager AutoCodeGen for operators with multiple OpBases

* Adjusted Eager AutoCodeGen to Enable Passing Output Tensor as Input Argument

* Handled Dispensable Inputs/Outputs in Eager AutoCodeGen

* Adjusted function generation/call between Python-C API & Dygraph API

* Synchronized auto-generated Python-C API with Dygraph Forward Functions

* support more eager tensor api

* fix merge compile error

* fix compile error and fit develop code

* support pure CPU

* fix some logic error in eager_mode

* support _varbase_creator in eager mode

* Added safe_initialized interface to EagerTensor for use in processing dispensable inputs

* for eager mode

* refine

* support multiple constructor for eager tensor

* add place related code

* polish code

* specific randint with dtype of int64

* Support pure cpu test

* eager logic

* refine test in pure cpu

* eager logic

* eager logic

* eager logic, test=develop

* skip core.eager when in inference, test=develop

* refine, test=develop

* refine, test=develop

* call RetainGrad after run forward kernel, test=develop

* refine, test=develop

* support dygraph util, meta, guard test

* eager test case

* support inference test

* refine test and fix initializer failed

* modify eagertensor patch method

* add eagertensor.clear_grandint, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* call monkey_patch_varbase in _test_eager_guard, test=develop

* split clear_gradient to clear_gradient and zero_grads, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop
Co-authored-by: Njim19930609 <jim19930609@gmail.com>
Co-authored-by: NJiabinYang <360788950@qq.com>

* fix for matmul_v2 broadcasting

* fix for output shape not broadcasted

* add huber_loss for kunlun

* update xpu.cmake

* update unitests

* update unitests

* update elementwise_add

* update elementwise_add

* update elementwise_add

* Support EagerTensor init with kwargs

* Updated comments

* Updated unit tests case

* Refactor InitTensor related code to reduce duplicate code

* Updated the error reporting msg

* Updated VLOG msg

* Merge develop and Update EagerTensor init func

* Polish switch case, reduce some code

* Add SyntaxError unit test case

* Refactor the related initialization func of EagerTensor

* Remove ParseStopGradient and ParseZeroCopy and ParsePersistable, construct ParseBooleanArgs instead.

* Updated error msg to pass CI

* Updated PADDLE_ENFORCE error type

[NPU] add pad and pad_grad

* fix error when set buffer in forward

* add unittest

* refine class name

* refine not framework.in_dygraph_mode() in if

* fix UT error

* add comment

* refine code

* remove useless import

* [XPU]add split op for kunlun2,*test=kunlun

* [XPU]add split op for kunlun2,*test=kunlun

* [XPU]add split op for kunlun,*test=kunlun
Co-authored-by: NQingshuChen <chenqingshu@baidu.com>

* add new api/op kthvalue

* kthvalue cuda kernel to cub sorting

* fix example code error

* throw errors instead of LOG in cuda sort

* throw errors by Paddle_ENFORCE

* add mul_gru_fuse_pass ut

* update ut

* update ut

* update ut timeout setting

* update ut

* add beta distribution
* add kl_divergence and register_kl api

* add new api paddle.quantile and paddle.Tensor.quantile

* add take_todo and fix UT

* [Auto Parallel] add gradient merge pass

* fix ci issue

* fix ci issue

* fix ci issue

* fix ci issue

* fix ci issue

* fix ci issue

* fix ci issue

* fix ci issue

* fix ci issue

* fix pr review

* fix pr review

* fix pr review

* fix pr review

* fix pr review

* fix pr review

* add fold opereators, test=develop

* add fold opereators, test=develop

* add fold opereators, test=develop

* update fold op error test, test=develop

* fix unitext, test=develop

* fix unitext, test=develop

Paddle new APIs: put_along_axis.

Xu Huang is on holiday so we created this PR to work on it. It is based on his PR: https://github.com/PaddlePaddle/Paddle/pull/37921

* unify data layout

* fix test_transfer_layout error

LGTM

* add sigmoid cross entropy with logits to kl1. test=kunlun

* add sigmoid cross entropy with logits to kl1. test=kunlun

Add exp, abs_grad, reciprocal, reciprocal_grad operator for XPU and update xpu2_op_list.h,test=kunlun (#38570)

* add new OP mode

* rename trans-variable name and fix UT

* add cpu kernel of lstsq

* update

* modify code style

* modify unittest

* remove support for complex

* Rearranged Eager AutoCodeGen directory structure

* Removed USE_OP in Eager AutoCodeGen

* Enabled generation for Operators without Grad/Inputs/Outputs

* Resolved operators without input

* Fixed merge conflicts

* Enabled Eager AutoCodeGen for 10+ more operators

* Refactored Eager AutoCodeGen with more organized helper objects

* Enabled Eager AutoCodeGen for operators with multiple OpBases

* Adjusted Eager AutoCodeGen to Enable Passing Output Tensor as Input Argument

* Handled Dispensable Inputs/Outputs in Eager AutoCodeGen

* Adjusted function generation/call between Python-C API & Dygraph API

* Synchronized auto-generated Python-C API with Dygraph Forward Functions

* support more eager tensor api

* fix merge compile error

* fix compile error and fit develop code

* support pure CPU

* fix some logic error in eager_mode

* support _varbase_creator in eager mode

* Added safe_initialized interface to EagerTensor for use in processing dispensable inputs

* for eager mode

* refine

* support multiple constructor for eager tensor

* add place related code

* polish code

* specific randint with dtype of int64

* Support pure cpu test

* eager logic

* refine test in pure cpu

* eager logic

* eager logic

* eager logic, test=develop

* skip core.eager when in inference, test=develop

* refine, test=develop

* refine, test=develop

* call RetainGrad after run forward kernel, test=develop

* refine, test=develop

* support dygraph util, meta, guard test

* support inference test

* refine test and fix initializer failed

* support create varbase and fix retain grad error

* fix windows error

* support test_imperative_basic test in eager mode

* remove additional log in variable.h

* remove additional log in variable.h

* remove additional code create in merge
Co-authored-by: Njim19930609 <jim19930609@gmail.com>
Co-authored-by: NWang Huan <wanghuan29@baidu.com>