[Windows CI test] Enable unittest test_optimizer_in_control_flow and remove unnecessay code (#29851)

* fix conv_transpose bug when padding=same

* update, test=develop

* try to add fwd op input dtypes

* refactor base impl

* return tmp_ins after dygraph prepare data

* fix typo found in debug

* polish comment & add complex net test

* revert detail change

* fix unittest failed

* add complex kernel condition control

* fix xpu test failed & polish comment

* polish details by review comments

* add support for complex grad accumulated

* add unittest for coverage

* update test dtype

* remove useless blank line

* Fix Windows unittest of test_fetch_lod_tensor_array

* feat: support check_nan_inf for kunlun device

* support kunlun stack

* minor

* reopen python coverage --include for test, test=develop

* if no .py file modified, not use coverage run, test=develop

* remove test code, test=develop

* add WITH_INCREMENTAL_COVERAGE, test=develop

* refine if else, test=develop

This reverts commit 067d7f1d.

* oneps (3/4)
Co-authored-by: NMrChengmo <cmchengmo@163.com>
Co-authored-by: Nmalin10 <malin10@baidu.com>
Co-authored-by: Nchengmo <chengmo@baidu.com>

1. Type of index: int, slice(step must be 1).

2. Type of value: 
 (1) int32, int64, float32, bool; 
 (2) numpy.array(int32, int64, float32, bool);<Note: float64 is not supported>
 (3) paddle.Tensor(int32, int64, float32, float64, bool);

* remove duplicate ut reload

* remove duplicate ut define in cmakelist

* add conj op for complex types

* add conj for complex types

* add more test case

* add conj_op test

* modify conj api and impl

* add complex type for fill_constant_op xpu

* add setConstant for complex type

* remove complex conj test file

* user define grad for test_conj_op

* add test case for static mode of conj api

* modify conj doc

* change input args name to x

* remove useless codes

* conj support real types

* add conj test case for real number

* delete no need to calculate inputs in dygraph op_test

* delete no need to calculate inputs in dygraph op_test

* modify grad of mul for complex types

* fix the grads of inputs args order not match bug

* change the grad of div when complex types

* fix the grads of inputs args order not match bug

test=develop

* add nearest_interp_v2 on kunlun

* add nearest_interp_v2 on kunlun

4 APIs: array_length, array_read, array_write, create_array

[Dy2Stat] Fix bug for loop: a variable is used and created in loop, but used before created (#29769)

* add double grad for conv_transpose

* upgrade oneDNN with GRU INT8 optimizations

* fix test

Enable jit.save to Save Without Running.

Support to transformfor ele in var stms in which var is a slice of Tensor.

* delete no need to calculate inputs in dygraph op_test

* delete no need to calculate inputs in dygraph op_test

Before this commit, test_slice use old api `dygraph_to_static_func` to use Dynamic-t-Static and use Executor explicitly，which is not recommended to users.
After fixed, use recommended API `paddle.jit.to_static` to replace `dygraph_to_static_func`, which won't trigger the random exception on coverage CI.

Unit test reported memory not enough on CPU machines. Reduce batch size again.

* add conj op for complex types

* add conj for complex types

* add more test case

* add conj_op test

* modify conj api and impl

* add complex type for fill_constant_op xpu

* add setConstant for complex type

* remove complex conj test file

* user define grad for test_conj_op

* add test case for static mode of conj api

* modify conj doc

* change input args name to x

* remove useless codes

* conj support real types

* add conj test case for real number

* add complex real op & api & unittest

* add imag op & api & unittest

* refactor op impl

* revert simplify writing due to complile failed

* polish details

* polish grad op code

* fix expand && concat/transpose to new api

* update xpu_header

* update activation op on kunlun

* update activation op on kunlun

* update activation op on kunlun

* update activation op on kunlun

* update activation op on kunlun

* add nearest_interp on kunlun

* update error message