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

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

* Impelement 2.0 API version Conv2d and Linear layer quantization in imperative mode.

* use cudnn softmax in static Lenet

* Modified ChannelwiseQAT Unittest for 2.0 API.

* For CI python coverage.

* replace config by kwargs

* change save path form dir to prefix

* fix failed unittests

* revert unittest name change

* polish en docs

* add more tests for coverage

* default open dygraph mode

* fix CI-Mac

* fix Mac-CI other unittest file

* fix CI-Py3

* fix test_communicator_geo and test_buffer_shared_memory_reuse_pass

* add enable_static to fix CI-Py3

* add enable_static to fix CI-coverage

* delete try except

* Finished ChannelWiseQuantDequantAbsMaxOp and Passed unittests.

* Finished channel-wise quantize strategy in imperative quantization.

* Added Cuda code of ChannelWiseQuantDequantMaxAbsOP
Add Cuda code of ChannelWiseQuantDequantMaxAbsOp

* Add quant_axis for channel_wise quant.

* fixed a bug in unnitests, which will not trigger axis = 1 case and cannot meet the coverage rate requirement.

* Added some assert infomation and fixed some coding style mistakes.

* Add the imperative quantization aware training.
*  This is the python part of Imperative QAT. test=develop