* update doc on develop, test=document_fix

* update dependency of ppdet and paddle, test=document_fix

* update docs, test=document_fix

* Add S2ANet model for Oriented Object Detection.

* fix warning

* add Distill model
* add distill+prune

* unity weights

* add VisualDL and save best_model

* add VisualDLWriter callback

* add prune dygraph, test=dygraph

* fix slim readme and prune

* ppdet installable

Merge dygraph branch into master branch.
Co-authored-by: NFDInSky <48318485+FDInSky@users.noreply.github.com>
Co-authored-by: Nsunxl1988 <47514455+sunxl1988@users.noreply.github.com>
Co-authored-by: Nwangguanzhong <jerrywgz@126.com>
Co-authored-by: Nwangxinxin08 <69842442+wangxinxin08@users.noreply.github.com>
Co-authored-by: Nwanghuancoder <wanghuancoder@163.com>
Co-authored-by: Ncnn <liuhui29@baidu.com>
Co-authored-by: NGuanghua Yu <742925032@qq.com>
Co-authored-by: NKaipeng Deng <dengkaipeng@baidu.com>
Co-authored-by: Nroot <root@bjyz-sys-gpu-kongming0.bjyz.baidu.com>

* update solov2 some detail

* fix check paddle version

* add enable_static()

* follow comments

* remove blank line

* support infer for SOLOv2

* share train_batch_size from reader to model

* update floor_divide

* add makedirs for dumping config

Add image for visualdl board.

* Update docs
* Update README.md

* optimize python path

* update check config

* fix slim/xx

* add devices_num on reader

* refine capacity value

* refine bufsize

* Polish Reader to simplify preprocessing logic.
#  sample_transforms-> make batch -> batch_transforms in Reader.
* Clean some code
* Imporve yolov3_r50vd_dcn_obj365_pretrained_coco 41.4 to 41.8.
* Update all configs.

* Add cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms model on oidv5 and obj365.
* Add obj365 config annotation
* Update docs.

* update code & doc

* add export_model doc

This reverts commit b591cc133ca04dc1ed50631c8d24031bb97db18b.

* Add face detection configs and main code.
* Integration multi-scale evaluation.

* unify reader to dataloader

* add check_version

* Support finetune by custom dataset

* add finetune args

* add load finetune

* reconstruct load

* add transfer learning doc

* add fruit demo

* add quick start

* add data preprocessing FAQ