* 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

* Disable optimizer fusion for RCNN models

waiting for upstream fix

* Disable completely

* Add support for mixed precision training

* Disable `fuse_all_reduce_ops` when training in mixed precision

waiting for upstream fix

* Initial support for distributed training

* Housekeep on rank 0 only

* Conform to models convention

In PaddleDetection,  making use of tb-paddle to record data, so as to display in TensorBoard.  (#3295)

* use tb_paddle to log data
including:

* loss
* mAP
* image

* modified:   requirements.txt
* modify the missing argument --use_tb
* modify GETTING_STARTED.md and docs/GETTING_STARTED_cn.md

add the argument of tb-paddle in docs.
* optimize the display name of image displaying.

* Add benchmark (fps) in MODEL_ZOO doc

* fix add map_type

# Add VGG-SSD on VOC and COCO dataset.
# Add config and model zoo. 
# Refine bbox2out and draw_bbox:
    - Add bbox de-normalize in bbox2out function.
    - Remove bbox de-normalize in draw_bbox.

* add save best model & fix dcn configs

* fix yolov3 voc eval in train

* fix comment

* fix easy problem

* add voc_eval and yolo_darknet_voc

* add yolov3_darknet_voc in MODEL_ZOO

* fix default im_size

* fix MODEL_ZOO note

* fix is_bbox_normalized

* extract map to map_utils.py

* update yolov3_dorknet_voc mixup

* add yolov3_r34_voc

* add yolov3_mobilenet_v1_voc

* fix drop empty in VAL mode

* use cfg.num_classes

* assert metric valid

* enable difficulty can be None

* add comment for bbox_eval

* num_classes in retinanet

* add log iter argument

* ppdet log time smooth

* ppdet log eta

* fix save_inference_model cannot find feed vars

* remove comment

* fix format

* add comment for pruned var

* add log for prune

* fix resnet for resnet34

* fix ResNet18 and ResNet34

* update modelzoo and fix configs

* fix configs

* fix resnet bn

* refine bbox_normalize in infer.py

* add is_bbox_normalize

* rename _forward to build

* check callable

* check gpu for ppdet/yolov3

* add random shape descp in MODEL_ZOO

* refine doc

* not use core

* add save_inference_model in infer.py

* format code

* add comment

* add save_inference_model doc

* refine doc

* improve quality of images

* update url for install doc

* refine README & use a better visualization for doc

* fix typo in GETTING STARTED