* support prim test in OpTest

* fix cmake

* fix op test

* fix test_input_spec

* disable cinn in reduce_sum unit test

* add bfloat16 dtype for sum

* polish code

* add clear jit program function

* convert grad out from tensor to numpy

* remove unnecessary code

* add only_prim flag

* fix flag

* fix op test

* fix optest comp inplace error

* fix op test

* fix op test with guard

* add initialization of check_comp flag

* fix comp inplace error in op test

* rename check_comp with check_prim and add bfloat16 dtype convert

* rename comp_op_type to prim_op_type

* rename comp to prim

* remove useless code

* skip ci check for only prim

* add no_grad_vars and grad_outputs in prim test

* fix var_dict

* fix op test for only_prim

* fix dy2static bugs

* polish some code

* process unit test matched test_p*

* fix ci bug

* fix ci bugs

* fix codestyle

* remove all tests about pe and restore some irrelated tests

* delete test_parallel_executor_test_while_train.py

* assert len(self.places) == 1

* remove with_data_parallel in unittest

* remove multi-card related checks

* remove with_data_parallel in test_multiprocess_dataloader*

* fix error hint

* fix typo

* fix composite mean op map

* fix composite check output

* init layer_norm

* init layer_norm

* map output from composite rule to origin op

* add dropout op map

* add input map check

* polish log

* modify rules

* success test_forward

* modify test without cinn

* modify cinn test

* modify cinn test

* except fp64

* except fp64

* delete flatten

* delete unused change

* review

* pass cpu test

* code style

* delete flatten fp16 error

* modify flatten test

---------
Co-authored-by: Ncyber-pioneer <chenzhuo@tju.edu.cn>

* Check -1 shape for input_spec and program when prim or cinn enabled

* Polish neg shape check

* Polish code

* Fix UT

* Fix UT in static

* [RM FLUID] trainer_pass&heter_trainer_pass
* [RM FLUID] rm distributed_strategy

* [dy2static] support fallback for whole graph. (stage 1)

* bug fix

* bug fix and add a new unittest

* fix code by code review

* fix coverage

* [dy2static] ParameterRecorder Part 2

* Parameter Recorder - 2 bug fix

* bugfix: fix the dygraph go into _jst.ld() errors.

* fix ci error.

* fix ci error

* check win

* fix random error

* fix manage

* change error

* fix

* Add unittest for zero-dim kron.

* Fix zero dim kron.

* rename multi_tensor_adam to fused_adam

* fix some bugs

* fix CI coverage

* rename test_fused_adam.py

* fix some bug

* add test_fused_adam_op.py

* fix some bugs

* fix fused_adam_op.cc

* fix CI bugs

* fix CI bug

* fix CI bug

* change SHA

* update to oneDNN 2.7

* update to 2.7.1

* update to 2.7.2

* add supported hardsigmoid

* update to 2.7.3

* limit cpu threads for int8 test

* group activations

* [XPU] add fp16 support for cumsum and log.

* [XPU] add fp16 support for cumsum and log.

[XPU] add multi_encoder_xpu_slice_fuse_pass, generate_sequence_xpu_fuse_pass, generate_sequence_xpu kernel (#50570)

* [RM FLUID] rm fluid_pslib_init

* [RM FLUID] for ci

* [RM FLUID] for ci

* [dy2static-bugfix] fix backward gradient aggregation bugs
1. Yolov3 and Yolov5 all face the same problem.

* remove set_device

* code review fix

* New onednn test

* checkopoint

* added new test, fixed issue with onednn bias

* fix bias check

* remove prints, refactor code

* delete old test

* update python tests cmake

* Delete depracated conv bias

* Delete outdated bias from convolution test

* add logspace yaml

* update by comments

* resolve test framework conflicct

* support xpu multi-card infer

* add ut

* clean code

* clean code

* fix

* fix

* fix

* fix

* [XPU] add group_norm kernel

* update

* add xpu sin, cos, randint, linspace kernels

* update

* update

* disable unewanted dygraph tests

* mine_hard_exa

* beta

* small commit

* add batch_norm composite rule

move composite test case

remove unuseful var

add composite op blacklist

* small change v2

* finish the test_composite_mean and test_composite_mean_grad

* add ops assertion to the tests

* add cinn test

* fix the error and inappropriate usage in func: mean_composite

* remove the ref of outer lib in primtives.py

* modify sample code of reduce_sum

* fix composite mean op map

* modify testcases to test more float type

* remove cpu float16 test

* cinn test fix

* remove reduce_max

* change the name sum to sum_x

* change the use of reduce_sum to sum

---------
Co-authored-by: Ncyber-pioneer <chenzhuo@tju.edu.cn>

* Done

* Deleted old python test, fixed new python test, changed names in parallel_UT

* Revert parallel UT changes

* Revert parallel UT changes v2

* Review fixes and simplification of conv output shape calculation, disabled sqrt from conv_act_duse_pass

* delete sqrt from possible activations from conv_concat_relu test

* review refactor

* merge main

* delete sqrt from list of compatible activations

* Test with no outdated inputs

* auto parallel align tool

* modify function get_var's return

* add save and load in align_tool

* modify load function and save function

* add finding different ops in align tool

* full auto parallel align tool

add test file for auto parallel align tool

set timeout for test

modify get_backward_tmp_var function

add annotation for align tool

modify test file

modify code to restart CI

remove timeout

* set timeout

* map output from composite rule to origin op

add mean layer_norm dropout op map

add input map check

composite softmax support input shape []

* composite softmax support shape []

* polish log

* solve conflict

* polish code

* polish op map output

* add check dtype