* add amp for ResNet200_vd

* change use_fp16 to use_amp

* fix script format

* change batch_size

* add amp support for model SE_ResNet50_vd

* optimize code, add model ResNet50 and SE_ResNet50_vd to list

* merge develop

* add pure fp16 training.

* update the usage of cast_parameters_to_fp16.

* use fp32 to initilize parameter values and then cast to fp16.

* enable multi_precision when training with fp16.

* add static loss scaling.

* add the rescale_grad function in the pure fp16 training.

* use cast to complete the pure fp16 training.

* use sum loss for fp16 trainging and mean loss for fp32 training.

* refine codes according reviewers' suggestions

* Create inception_v3.py

* Update __init__.py

* Create InceptionV3.sh

* add fuse_bn_add_act_ops args

* add the fp16 support for ResNet50

* add docs for AMP.

* Add hrnet,res2net and some resnext pretrained models

refine code

* add_multiprocess_train_to_image_classification

Add EfficientNet

refine image classification and add 19 pre-trained models.

* Refine Image classification