* update readme test=document_fix

* update conll05 docs

* update conll05 docs test=document_fix

* add args check and comment for exp,polynomy decay

* modify according to zhouwei's comment

* update dist tensor

* add unitest

* update unitest

* refactor dist tensor

* update dist tensor and unitest

* check amp.decorate and DataParallel

* refine coverage

* fix layer dtype

* refine code

* Pre-save hooks of jit.save

1. Added pre_save_hooks features to jit.save.
2. Added related unittests

* Added jit pre_save_hooks functions's alias to paddle.jit and copyright.

* Make jit.save_pre_hook style be consisent with Paddle's rule.

* Fixed arguments passing bug in run_save_pre_hooks

* Added API Documents

* Move clear and run_pre_save_hooks as internal methonds only.

* Made register_save_pre_hook as an internal function.

* 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

* support create varbase and fix retain grad error

* call monkey_patch_varbase in _test_eager_guard, test=develop

* fix windows error

* split clear_gradient to clear_gradient and zero_grads, test=develop

* refine, test=develop

* refine, test=develop

* 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

* eager

* fix some eager logic, test=develop

* refine, test=develop

* refine, 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>

* add lstsq gpu kernel

* update

* add docs_en

* modify ut

* fix bugs

* modify example in docs_en

* remove lstsq_op.cu from ROCM cmake

* modify docs_en

* modify docs_en

* modify docs_en

* remove unneccessary TensorCopy

* Add the backward support for QR

* Remove unnecessary comments

This reverts commit ee813e34.

* unify infer_shape func calling

* support set grad infer shape fn for custom op

* unify infershape in new executor and eager

* remove todo comment

* revert infershape in operator

* 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