The requirements.txt used for COCO specifies python version >= 3.4.

* fix resnet for resnet34

* fix ResNet18 and ResNet34

* update modelzoo and fix configs

* fix configs

* fix resnet bn

* update readme

* rm useless png

* fix bn warning

* Clean up a bit

* Add `__shared__` annotation for shared variables between modules

* Dedup `num_classes` configurations

* Document `__shared__` usage

* Remove some unused variable

* Improve docstring and add comments for `__shared__`

* add cn doc for INSTALL/GETTING_START

* cn for GETTING_STARTED

* fix doc

add run shell and infer shell for cgan and dcgan
update infer.py for gan and dcgan

* add instance norm

* Add a model for WebVision 2018.

* baiduzhixing score tools

* update name and add baseline model

some of the global config values are reference type, e.g., objects, lists or
dicts, if the created module instances modify those values (see FPN and
spatial_scale), global config will reflect these changes, and instances of the
same class created later will inherit the changed values

* refine bbox_normalize in infer.py

* add is_bbox_normalize

* rename _forward to build

* check callable

* fix_bn=1

* Support to set multiprocess in SSD model
* clean code

* fix_nan

* add check gpu for deeplabe3+, icnet, rcnn

* modify based on review

* modify based on review

* check gpu for ppdet/yolov3

* add random shape descp in MODEL_ZOO

* refine doc

* not use core

* add cuda check to show errors when run on paddle compiled with cpu only

* change use_cuda to use_gpu in the error infomation to be consistent with code

* update checkgpu

* Add faster_rcnn_x101_vd_64x4d_fpn_1x.yml
* Release faster_rcnn_r101_vd_fpn_1x.tar, faster_rcnn_x101_vd_64x4d_fpn_1x.tar, mask_rcnn_r50_2x.tar

* add save_inference_model in infer.py

* format code

* add comment

* add save_inference_model doc

* refine doc