* make fast through to linear

* make fast through to linear

* add to do for later upgrades

* support build once for now

* fix bug for MultiplicativeDecay

* remove changes to test_lr_scheduler.py

* [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

* update

* add conv yaml

* add backward

* remove useless code

* fix bug

* fix bug

* revert fluid dygraph conv2d

* remove useless infermeta function

* fix meta fn deluplicat error

* conv using custom impl

* remove amp include

* fix bug

* use final op in maskrcnn and hrnet

* refine
Co-authored-by: Nphlrain <phliuhongyu@126.com>

* create tensor by empty in custom op

* fix some bug

* add dist slice

* fix debug

* fix cmakelist

* [Auto Parallel] Add links for the reference codes.

* Update recorder.py

* Update trial.py

* Update test=document_fix

* Update test=document_fix

* adapot dist op

* [Auto Parallel] Support the auto completion of while_op

* add dist_fill_constant_batch_size_like

* align infer  accuracy

* [Eager] add _fallback_legacy_dygraph for npu/xpu/rocm

* fix import

* 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

* split phi and fluid infermeta context

* resolve conflict

* fix type error

* optimize scheduling perf

* spec small vector size

* replace all grad var name

* fix test failed

* move init defalut signature

* polish details

* polish details

* fix no init bug

* init sig for tests

* add init sig for infer

* fix infrt error

* fix infrt failed

* fix kunlun error

* fix infrt failed

* fix place type related compat error

* fix test failed

* remove dll decl

* revert place type change

* add dll decl

* moe ref

* ref commit; test=document_fix

* update; test=document_fix

* update test=document_fix

* update; test=document_fix

* 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>

* moe ref

* ref commit; test=document_fix

* update; test=document_fix

* update test=document_fix

* 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

* add gpupsutil and afsclient; test=develop