* [CodeStyle][py2][U004] unecessary explicit `object` inheritance in class definition

* fix an increment

* [CodeStyle][py2][U008] remove unnecessary args in `super()`

* remove remained args

* revert changes in test_pylayer_op

* Revert "revert changes in test_pylayer_op"

This reverts commit ff185a9ae738afac3b0264f61bde6c6b7f72e7c4.

* revert some changes in example code

* [CodeStyle][py2] remove `six` package (part2)

* six.ensure_str

* remove unused `import six`

* remove six from BUILTIN_LIKELY_MODULES

* remove six in example code

* remove some decode

* try to fix example code

* fix MockEtcdClient get/get_prefix returns data type

* fix MockEtcdClient get_prefix returns data

* fix MockEtcdClient get returns data

* remove `six` in pypi and conda requirements

* fix MockEtcdClient add_watch_callback/add_watch_prefix_callback returns data type

* refine MockEtcdClient

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

* [CodeStyle] remove all future import

* revert test_error.py

* restore future import in example code

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

* add quant pass

* use yapf to format all python file

* yapf exclude two unittests file for they rely on writing and reading file, and format will break them

* disable diff_py_file because too many diff files cause command following failed

* clip op extra information when export model,test=ocr

* rename clip_extra parameter to kwargs in save_inference_model, test=ocr

* PTQ save quantized model

* Wrap simulated layer

* post process the inference model

* refine ptq according comments
* reuse the module to calculate kl threshold

* Save all scales to target ops
* Move quant layers to paddle.nn.quant

* dygraph post training quantization

* refine the ptq config

* refine ptq quantizer

* Add wrap for functional api
* Refine the wraped api
* Add unit test for quant functional layers
* Update all unit tests for dygraph qat

* Use layer to calculate output scale
* add backward for moving_average_abs_max_scale and save output scales to op's attr

* Refine saving output scale to infer program

* Fix skip_quant in QAT

* Refine calculating output scale of dygraph qat, test=develop