refine code

* fix_infer_bug_release_some_model

* add_multiprocess_train_to_image_classification

Add EfficientNet

* Refine Image classification

* Transfer resnext50 multi-process multi-gpu changes from benchmark to models
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* refine code
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* Reduce buf size in image_classification/reader
* Fix format

* Shift up fluid models

* Update nlp submodules

* Add redirect guide in org readme

* Move HiNAS_models to AutoDL

* Move models to legacy, rename models_name to models, refine README
* Refine eval/infer/train code
* Release ResNet 18/34, GoogleNet and ShuffleNet v2.
* Add RMSProp optimizer.

* Delete file
* Rever the raw file

* Adjust the structure of whole repo

* Correct the readme for speec

* Update submodules LAC, Senta and SimNet

* Update Image Classification Models.

* Add more model configure, such as AlexNet, VGG, GoogleNet, DPN, ResNet etc.
* Add download_imagenet2012.sh
* Update doc.
* Add Chinese doc.

* revise se_resnext for imagenet classification

* Add the method to train a SE-ResNeXt model

The current code can successfully implement the result of SE-ResNeXt-50.

* Update ImageNet2012 URL

* update

* update readme

* Update readme with download URL

* add unzip

* update se_resnext.py with parallel_exe

* delete train function in se_resnext.py

* add eval.py and infer.py

* move cosine_decay from se_resnext.py to train.py