* add outputs for code examples, test=document_fix

* missing code example update, test=document_fix

* missing returns, test=document_fix

* fix the case of proper nouns, test=document_fix

* fix SqueezeNet code example (add a blank line), test=document_fix

* fix ShuffleNetV2 args style, test=document_fix

* missing paper links, test=document_fix

* missing `optional`, test=document_fix

* refine parameter `pretrained`, test=document_fix

* add parameter `kwargs`, test=document_fix

* refine parameter `num_classes`, test=document_fix

* capitalize the first letter, test=document_fix

* missing output of code example, test=document_fix

* fix wrong api label, test=document_fix

* refine returns, test=document_fix

* add missing `.` after paper link, test=document_fix

* remove extra `:`, test=document_fix

* :math:\`0.0\`, test=document_fix

* 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

* update 2.0 public api in vision

* fix some flake8 errors

* rename manual_seed to seed

* rename xxx1d-->xxx1D, xxx2d-->xxx2D, xxx3d-->xxx3D

* rename manual_seed --> seed

* do not rename .cc, .cu and .h file

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* disable_static on doc example code

* donot change manual_seed on generator

* add enable_static on sample code

* convert python/paddle/fluid/layers/nn.py to bak

* fix typo

* fix code style

* fix seed to manual_seed when call functions of Generator()

* fix bug

* refine vision models

* 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

* 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

* 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.