* support user-defined quant and preprocess

* Implement the function of OueScaleForTraining/OutScaleForInference in dygraph

test=develop

* 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.

* Move hapi form paddle/incubate to paddle

* Remove vision/datasets/utils.py and clean code

* Add sample code for conll05

* Print pull path when saving model

* Fix sample code after paramter_list of SGD is changed to parameters

* Fix bug in wmt16 datase

* add InputSpec

* add unittest for tensorSpec and SimpleNet

* remove ProgramTranslator.save_inference_model

* adapt save_quantized_model

* revert buffer check implemention

* remove useless import function

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