* support infer for SOLOv2

* add ppyolo mobilenetv3

* unify log_smooth_windows and log_iter

test=develop

* remove duplicate log_iter

* remain mobile yml, since they are soft-link

test=develop

* share train_batch_size from reader to model

* update floor_divide

* add makedirs for dumping config

test=develop

* add solov2 model

* fix train batch size

* add solov2_r101_vd_fpn_3x

* fix batch size and update modelzoo

* refactor code of solov2

* fix deploy/python

* clean useless log in DataLoader

* fix infer set_sample_list_generator

* check md5 after weights download

* move train_batch_size sync from load_config to merge_config

test=develop

* warning when YOLOv3Loss.batch_size setting

* expand ratio=2.0 & add ppyolo_2x_bs12.yml

* add batch_size in YOLOv3Loss for backward compatable.

* sync TrainReader.batch to global train_batch_size

* fix voc mAP %.

* add tools/anchor_cluster.py

* add PrepareDataSet.md, test=document_fix

* update PrepareDataSet, test=document_fix

* update PrepareDataSet, test=document_fix

* Update CN README
* Change demo and update doc

Repalce fruit dataset with roadsign dataset, and update QUICK_STARTED, use PP-YOLO as demo, test=document_fix. (#1407)

* add roadsign_voc dataset and update FAQ

* Add roadsign_voc dataset, updatea FAQ.md, and add yolov3_voc and yolov3_coco config template files.

* remove configs/templates

* convert config template file to md file, update comment

* mv config annotation file to config_annotation.

* move to docs/advanced_tutorials/config_doc

* rename

* update style

* update 2019-->2020

* update yolov3_mobilenet_v1_roadsign.md

* addd preprocess as yolov3_reader

* remove yolov3_mobilenet_v1_roadsign.md and add yolov3_mobilenet_v1.md

* fix typo

* update INSTALL

* fix typo

* add demo image

* add use_gpu annotation

* fix link

* update style

* update style

* add install paddle

* use python3

* update INSTALL_cn.md

* update INSTALL_cn.md

* update INSTALL_cn.md

* fix typo

fix compile error in code
modify code for inference

reuse RetinaNet pipeline for now