refine code

* Use iterable dataloader for image classification

* Support imagenet dataset with plain folder structure

* Add dali section to README.md

* Improve docs

* Remove some flags from docs

* Add dali reader for image classification

* Fix elapsed time calculation

* add profiler and max_iter for yolov3 model

* modify image_classification train

* update train.py

* modify args position

* move release 1.6 code to dev for tagging

* syn merged pr

* fix_infer_bug_release_some_model

* add_multiprocess_train_to_image_classification

test=develop

Add EfficientNet

* fix mobilenet bug

* fix inplce warning

refine image classification and add 19 pre-trained models.

* remove use_inplace=True and add save_step params

* remove useless params when using global pooling

* Refine Image classification

* 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

* Refine SE-ResNeXt model and use ParallelExecutor.

* Fix code style.

* Follow comments.

2. Add inference script
3. Add load model script
4. Add some functions into ctc_reader

1. Move all network defining to 'crnn_ctc_model.py'
2. Add initilizer for some layers
3. Rename 'fluid/ocr' to 'fluid/ocr_recognition'
4. Remove copyright
5. Rename some functions

1. Remove 'ocr_ctc' directory to 'ocr'.
2. Init README.md
3. Fix learning rate and l2
4. Refine training log format
5. Reduce arguments of train function
6. Set filter_size of im2sequence dynamicly
7. Add fc op before GRU op