* 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

* add multi-scale test

This reverts commit 36a2e65bb74fc8ec9d1720b3db798757b5c0d044.

This reverts commit b591cc133ca04dc1ed50631c8d24031bb97db18b.

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

* unify reader to dataloader

* add check_version

* Add backbone and architecture for FaceBoxes and Blazeface.
* Add dataloader for WIDERFace dataset.

* Place mixed precision inside PaddleDetection

roll back to the monkey patch version as a temporary measure, before it is
merged into paddle

* Add command flag for `loss_scale`

* Fix a stupid indentation error

optimizer should be in the mixed precision context

* Initial FP16 training

* Add mixed precision training to rest of the detection models

* Revert "Add support for mixed precision training (#3406)"

This reverts commit 3a2c106271885071db7c0d85587540a8f83c24db.

* Bug fixes and some tweaks