* update Conv2d Conv3d conv2d conv3d api

* Refine Model

1. Take the network (instance of Layer) as the input of Model.
2. Refine set_dict/load_dict of Layer.
3. Refine Input interface, so update code sample about Input

* add relu for lenet, test=develop

* fix test model, 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

* 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.