* fcos initialization

* delete the codes not used

* pre-commit the committed code

* delete the unused function

* modify the capacity in loader from 64 to 16

* add devices_num on reader

* refine capacity value

* refine bufsize

* add yolov3_mobilenet_v3

* add server side rcnn model, 62 fps with coco mAP 41.6% and 20fps with coco mAP 47.8%

fix multi-scale def

* add multi-scale testing function in cascade rcnn clsaware architecture

* Replace `switch` ops with `cond`

* Use func instead of lambda

* exit1 in travis failed

add libra rcnn, including
  * libra loss
  * libra fpn(bfp)
  * libra sampling

* add iou loss to yolov3
* modify the comment and delete redundant yml file
* fix the low speed bug in dropblock module

* add slim quantization demo

* add quantization demo

* add skip quant

* fix details in doc

* fix details

* fix details

* fix details

* fix details

* fix details

* fix details

* add model zoo link in doc

* remove result in doc

* add dropblock module
* move dropblock module from yolo_head to ops
* fix obj365 num classes

* add gcnet model : https://arxiv.org/abs/1904.11492

* add diou nms.
* fix typo in diou nms and soft nms (lod_leval->lod_level).

* Add GIOU loss.
* Add DIOU/CIOU loss.
* Change loss box type in bbox_head.py.
* Remove fuse_elewise_add_act_ops flag in train.py (Error may happen for elem_divbased on the flag).

- 1.add cn docs
- 2.fix fddb evaluate
- 3.fix get_shrink
- 4.delete FLAGS.dataset_dir

* split yolov3 loss

* add step in prior_box

* refine README

* add res2net model

* modify yml files

* add res2net model zoo

* add hrnet model

* modify model zoo

* minor fix readme

* update readme in dirs

* minor fix softnms bug

* refine model zoo

* modify yml files

* modify pretrain names

* 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.

* change fluid.layers.data to fluid.data

* fix export_model doc

* Fix nolocal naming
* Fix `cb_resnet` as well

* add softnms, nonlocal, resnet200_vd_backbone
* add CBNet
* update model zoo

* update code & doc

* remove actual_shape

* add fpn fix