* 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 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 resnet for resnet34

* fix ResNet18 and ResNet34

* update modelzoo and fix configs

* fix configs

* fix resnet bn

* check gpu for ppdet/yolov3

* add random shape descp in MODEL_ZOO

* refine doc

* not use core

* Rename object_detection to PaddleDetection
* Small fix for doc

* Add GC in train.py by defalut and change data co dataset in configs
* Update docs/INSTALL.md
* Enable build_strategy.enable_inplace = True

* Fix missing `absolute_import`

* Fix cycle import

* Fix missing export

* Remove some extra blank line and whitespaces

* Rename `create_feeds` -> `create_feed`

* Fix minor issues in tool scripts

* Add ipython notebook demo

* Tweak visualization bbox label style

* Tweak command line scripts

enable fine grained control of command flags parsing
switch to attribute style of accessing config options

* Break down visualization function

decouple it from IO operations

* Move flag parsing out of `main()`

* Fix a bug where `None` is returned instead of `{}`

* Rename `save_xxx` to `output_xxx` in command line flags

could be confusing since checkpoint is stored in `save_dir`

* Support image file extensions in upper case

* Fix type for faster_rcnn_50_2x.
* Make sure that type of cpu_num is int.

* Fix dtype for Yolov3.
* Clean unit testing.
* Add eval() for COCO-based algo.

* Unified object detection framework based on PaddlePaddle.
* Include algo: Faster, Mask, FPN, Cascade, RetinaNet, Yolo v3, SSD.