* Format error message for ops, test=develop

* Fix check in sequence_expand, test=develop

fix check info for flatten hash is_empty op; test=develop

* update err msg for dynamic_lstm and dynamic_lstmp, test=develop

test=develop

* fix error info for transpose sequence_conv_pool max_sequence_len sequence_erase, test=develop

* fix error info for transpose sequence_conv_pool max_sequence_len sequence_erase, test=develop

* update modify, test=develop

* update modify, test=develop

* fixed some modifications, test=develop

[Fix bug] Init scale node in OutScaleForTrainingPass and enable test_quantization_scale_pass UT (#24393)

* Init scale node in OutScaleForTrainingPass, test=develop
* Enable test_quantization_scale, test=develop

Fix the elementwise_ops axis bug, make elementwise_ops has the same the op function for override ops

* polish some sl api error message, test=develop

* polish python input check of stride slice, test=develop

* fix unittest bugs, test=develop

* fix bug with `if Tensor` in is_control_flow test=develop

* remove continue test=develop

* add vision

* fix predict, test=develop

* add unittest for vision apis, test=develop

* fix typos

* add hapi models api, test=develop

* fix code format, test=develop

* fix typos, test=develop

* fix sample code import, test=develop

* fix sample codes, test=develop

* add decompress, test=develop

* rm darknet, test=develop

* rm debug code, test=develop

* enhance rank_loss error message, test=develop

* enhance similarity_focus error message, test=develop

* enhance squeeze error message, test=develop

* add scale_x_y for yolo_box, test=develop

* refine eps in iou_similarity, test=develop

* fix error log: resahpe, range, reverse.

* test=develop add linear interpolate operator

* Remove the error in the elementwise op, use the backup mode to calculate

* fix bug of cross_entropy_loss,test=develop
* fix log_softmax and some comment,test=develop

* Merge hapi into Paddle

Hapi is a high level API for training and inference.
The main modules include Model, Loss, Metrics, Dataset.
Also includes common modules and models in NLP and computer vision, such as BERT, ResNet.

These modules are developed by:
0YuanZhang0, guoshengCS heavengate, LielinJiang, qingqing01, xyzhou-puck huangjun12, wangxiao1021, zhangyang.

* fix rnn check_type list error

* tigger ci, test=develop

* update modify, test=develop

* support save_inference_model in program_translator test=develop

* fix compatibility with OrderedDict.values() in python3 test=develop

* synchronized random_seed test=develop

* Polish Error Message test=develop

* copy dygraph api to paddle.imperative, test=develop

* polish the code, test=develop

* polish code, test=develop

* polish code, test=develop

* move paddle.imperative.Layer to paddle.nn.Layer, test=develop

* [Dy2Stat] Add test for bert pretraining. 

* Construct fake data. 

* Synchronous random seed of program. 

* fix numpy ndarray mul var base error; test=develop

* add comment for __array_ufunc__ ; test=develop

* move unitest from imperative math op path to test_math_op_patch_var_base;
test=develop

* raise index error when slice out of range; test=develop

* add uni test; test=develop

* fix format error; test=develop

* add comment for py::index_error; test=develop

* polish error message; test=develop

* polish error message; test=develop

* Enabled quantize all and skip missing in QAT

* add clean up; test=develop

* add import; test=develop

* support to train in static

* support to independent decorator

* remove in_dygraph_mode condition in ProgramTranslator

* fix import param_guard and add train/eval test=develop

* Modify into ShareVarsFromScope and rm __all__ in partial_program test=develop

1. To make ProgramTranslator to support `assert` grammar, this PR adds `assert` python API and C++ code. 

2. Fix a bug: graph_pattern_detector.h #include <gtest/gtest_prod.h> but didn't declared dependency at CMakeLists, which can cause single build failure.

3. Refactoring `Formatter` in print_op to make it reusable and reuse the formatter to print in assert op.

目前在while_loop的执行过程中，loop_vars中的变量在每次的循环中都会进行拷贝，但是LoDTensorArray类型的变量在while循环体中已经完成了读/写的操作，即完成了更新，此时在进行拷贝属于冗余的操作，故该PR跳过每次循环中loop_vars中LoDTensorArray类型的变量的复制过程。

在PaddleCV/ocr_recognition/atention模型的预测过程中进行性能测试：
|性能|with this PR|without this PR|提升|
|---|---|---|---|
|速度|4957.4ms|4978.47ms|0.4%|