* reuse ConvNormActivation in some vision models (#40431)

* reuse ConvNormActivation in some vision models

* reimplement ResNeXt based on ResNet (#40588)

* refactor resnext

* update 2.0 public api in vision

* fix some flake8 errors

* rename manual_seed to seed

* rename xxx1d-->xxx1D, xxx2d-->xxx2D, xxx3d-->xxx3D

* rename manual_seed --> seed

* do not rename .cc, .cu and .h file

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* disable_static on doc example code

* donot change manual_seed on generator

* add enable_static on sample code

* convert python/paddle/fluid/layers/nn.py to bak

* fix typo

* fix code style

* fix seed to manual_seed when call functions of Generator()

* fix bug

* fix hapi load

* refine vision models

* Move hapi form paddle/incubate to paddle

* Remove vision/datasets/utils.py and clean code

* Add sample code for conll05

* Print pull path when saving model

* Fix sample code after paramter_list of SGD is changed to parameters

* Fix bug in wmt16 datase

* Refine Model

1. Take the network (instance of Layer) as the input of Model.
2. Refine set_dict/load_dict of Layer.
3. Refine Input interface, so update code sample about Input

* add vision

* fix predict, test=develop

* add unittest for vision apis, test=develop

* fix typos

* add hapi models api, test=develop

* fix code format, test=develop

* fix typos, test=develop

* fix sample code import, test=develop

* fix sample codes, test=develop

* add decompress, test=develop

* rm darknet, test=develop

* rm debug code, test=develop