* Support double grad check of op in Eager mode

* fix bugs of backward yaml

* adjust code format

* Hackathon 23

* fix bug

* fix pylint error

* try

* fix CI-Coverage

* update and add more unittest

* update

* support int16 argmax kernel

* add fp16 test

* add _grad_name and _grad_value for eager tensor

* fix paddle_enforce

* fix paddle_enforce 2

* fix grad_name

* _grad_value return lodtensor rather than tensor

* fix

* 增加logspace的算子描述

* 增加logspace的形状推断

* 增加logspace核函数实现

* 在python中增加logspace接口

* 增加logspace单测

* 增加logspace

* Update logspace_kernel.cu

* Update logspace_op.cc

* 调整代码格式

* Update doc of logspace

* Update tensor.py

* Update logspace_op.cc

* Update logspace_kernel.cc

* Update logspace_kernel.cu

* Update test_logspace.py

* 调整 logspace 的位置

* 调整代码格式

* double accessor and show_scale

* double accessor and show_scale

* rename

* fix bug in pslib config

* add unittest

* reduce performance influence

* add unit test

* fix

* changes for md in tensor

* ci fix

* Temporarily limited dims for test

* ci fix

* removed unnecessary includes

* added reviewers suggestions

* checkouted two files to avoid changing more than 19 in single PR

* minor fix

* reverted one file to reduce files changed to 19

* fix according to suggestion

* add kernel summary

* improve coverage

* [Eager]Fix full_like/clip with np.generic type as attribute

* support numpy genertic

* remove usless code

* fix pad3d infer shape

* add dist reshape impl_idx=2

* fix cmakelist

* [Phi]Fix expand_sig infershape BUG under static graph mode

* [Phi]Fix expand_sig infershape BUG under static graph mode

* [Phi]Fix unittest

* [Phi]Fix unittest

* fix utest

* fix time

* [Eager] paddle.sort interface use final_state

* Add eager test case for paddle.sort()

* [Eager]Fix NeedTransformPlace behavior if set skip_transform in yaml

* add unittest for full_like

* fix unittest

* add dist_pnorm op

* update cmakelist

* fix cmakelist

* fix cmakelist

* [Eager] Fix numpy interface for constructing empty tensor

* Fix CI, construct empty tensor

* Modify empty tensor's shape from [] to [0]

* Add more test for constructing empty tensor

* add dist slice

* fix debug

* fix cmakelist

* add eids result for graph_sample_neighbors

* fix bug

* move fisher_yates sample to warp

* add cpu eid output

* delete comment

* delete comment

* change nullptr placeholder

* optimize sample kernel

* fix mutable_data

* [MLU]add op: reduce_sum, elementwise_sub

* [MLU]del unrelated code

* native commit for triple grad of sigmod

* Updated unittests files

* init functional jacobian api

* Updated trible_test func

* Updated gradient_checker & test_script

* finish test with dtype float32

* add float64 test case

* polish code

* use atol=1e-5 with dtype float64

* fix for ci

* set timeout for test_jacobian

* fix dygraph grad to support high differential

* polish API docstring

* Updated gradient checker and some related files

* fix double grad strip error for high differential

* fix double grad strip error for high differential

* Add Sigmoid triple grad tests

* fix dygraph double grad dtype error when calling for high differential senario

* Updated triple grad teses func

* Use np.random to initialize ddx

* Updated triple_grad_check func

* add todo for gradient checker and refine some comments

* remove additional code

* add test for warnging in backward.py

* format python code

* support multi input in triple gradient checker

* Add matmul triple grad kernel

* Updated comments of TODO

* Supported some special tests

* Change code-format to follow CI std

* Updated gradient_checker.py

* Fix conflicts

* Removed unnecessary printing log

* Change code style to follow CI std

* merge upstream

* add priops.py

* add_p

* rm useless files

* add sub_p mul_p div_p

* add sqrt_p and tanh_p

* add reshape_p

* add broadcast_p

* Add python primitive wrappers.

* Jvp rules updated.

* JVP rules done for all the 17 primops.

* quick check and fixes.

* add jvp(op, *args)

* add broadcast_p fill_constant_p matmul_p reduce_p reshape_p transpose_p

* add split_p and concat_p

* add gather_p and scatter_add_p

* add slice_select_p and slice_assign_p

* Add transpose rules.

* add multi input check for add_p, sub_p, mul_p, div_p

* update concat_p

* Linearize and transpose in progress..

* refine gather_p and scatter_add_p

* updated.

* update transpose.

* refine slice_assign_p and slice_select_p

* init commit for lower

* Merged with primitive ops.

* small update

* add rules for orig2prim and prim2orig

* add 9 test for prim ops

* add more test and fix some bug

* add more test

* register proto

* Adding primops test.

* add shape valid check for broadcast_p op, and add keepdim attr into reduce_p op proto

* support multi input and multi output for split_p and concat_p

* Test updated.

* update

* fix slice bug for slice_select_p and slice_assign_p

* updated.

* Ops updated.

* Refactor and bug fixes.

* updated.

* finish orig2prim and prim2orig rules

* dtype for axis attr should be long int

* update dtype for axis attr int64_t

* update for iscan CI

* Update primx.

* Refactor vars in primx.

* update for lower transform

* update primx.py

* update

* Fix linearize and transpose.

* Update is_dot

* Update is_dot

* Update is_dot

* add gradient aggregation, fix add_transpose.

* pass first linearize+transpose test.

* update test

* add_prim_op_pywrapper

* Add primops UT

* Fix set_value and update

* Fix code format and PR-CI-Coverage
Co-authored-by: Nveyron95 <veyron_wu@163.com>
Co-authored-by: NJiabin Yang <360788950@qq.com>
Co-authored-by: NTongxin Bai <waffle.bai@gmail.com>
Co-authored-by: N0x45f <wangzhen45@baidu.com>

* add adamw yaml

* fix test case error

* make the name of weight and bias in linear1 and linear2 to be constant

* [DoubleGrad] Enabled double grad test cases in eager_mode for test_imperative_double_grad

* Fixed elementwise issue

* Addressed CI failures

* [DoubleGrad] Enabled test_imperative_triple_grad test cases under eager_mode

* [DoubleGrad] Enabled test_autograd_functional_dynamic.py under eager mode

* Enabled more test cases

* [DoubleGrad] Enabled test_imperative_star_gan_with_gradient_penalty.py under eager mode

* Adjusted test_imperative_star_gan_with_gradient_penalty.py

* refactor mp in eager mode

* update

* update

* add uts