* [Eager] Support test_dist_hapi_model under eager mode

* [Eager] Polish code

* Fix code-format issue, coverage-ci issue

* make hapi support amp, and add unittest

* make unittest only support GPU

* update parameters for amp in hapi.Model

* update hapi.Model.prepare interface, and update unittest

* fix test_model.py unittest bug

* add grad clear in dygraph

* use_fp16_guard defaults to True, which could avoid nan

* add input check, and add internal doc link to low level api

* update doc, and decrease the sample num of dataset to avoid timeout

* make hapi amp param  support str 'O1' or 'O2'

* resume calling , modify the code of the check part

* upgrade the usage of Fleet API, and disable 'pure_fp16' param

* fix ports conflict when launching multi-nodes in paddlecloud;test=develop

* add DISTRIBUTED_TRAINER_ENDPOINTS env for cloud;test=develop

* 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

* 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.