Add MobileNetV2 pretrained model

fluid/PaddleCV/image_classification/README.md

@@ -209,6 +209,7 @@ Models are trained by starting with learning rate ```0.1``` and decaying it by `
 |[VGG16](https://paddle-imagenet-models-name.bj.bcebos.com/VGG16_pretrained.zip) | 72.08%/90.63% | 71.65%/90.57% |
 |[VGG19](https://paddle-imagenet-models-name.bj.bcebos.com/VGG19_pretrained.zip) | 72.56%/90.83% | 72.32%/90.98% |
 |[MobileNetV1](http://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV1_pretrained.zip) | 70.91%/89.54% | 70.51%/89.35% |
+|[MobileNetV2](https://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV2_pretrained.zip) | 71.90%/90.55% | 71.53%/90.41% |
 |[ResNet50](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_pretrained.zip) | 76.35%/92.80% | 76.22%/92.92% |
 |[ResNet101](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_pretrained.zip) | 77.49%/93.57% | 77.56%/93.64% |
 |[ResNet152](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet152_pretrained.zip) | 78.12%/93.93% | 77.92%/93.87% |

fluid/PaddleCV/image_classification/README_cn.md

@@ -204,6 +204,7 @@ Models包括两种模型：带有参数名字的模型，和不带有参数名
 |[VGG16](https://paddle-imagenet-models-name.bj.bcebos.com/VGG16_pretrained.zip) | 72.08%/90.63% | 71.65%/90.57% |
 |[VGG19](https://paddle-imagenet-models-name.bj.bcebos.com/VGG19_pretrained.zip) | 72.56%/90.83% | 72.32%/90.98% |
 |[MobileNetV1](http://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV1_pretrained.zip) | 70.91%/89.54% | 70.51%/89.35% |
+|[MobileNetV2](https://paddle-imagenet-models-name.bj.bcebos.com/MobileNetV2_pretrained.zip) | 71.90%/90.55% | 71.53%/90.41% |
 |[ResNet50](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_pretrained.zip) | 76.35%/92.80% | 76.22%/92.92% |
 |[ResNet101](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_pretrained.zip) | 77.49%/93.57% | 77.56%/93.64% |
 |[ResNet152](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet152_pretrained.zip) | 78.12%/93.93% | 77.92%/93.87% |

fluid/PaddleCV/image_classification/run.sh

@@ -6,7 +6,7 @@ python train.py \
        --class_dim=1000 \
        --image_shape=3,224,224 \
        --model_save_dir=output/ \
-       --with_mem_opt=False \
+       --with_mem_opt=True \
        --lr_strategy=piecewise_decay \
        --lr=0.1
 #      >log_SE_ResNeXt50_32x4d.txt 2>&1 &
@@ -19,7 +19,7 @@ python train.py \
 #       --class_dim=1000 \
 #       --image_shape=3,224,224 \
 #       --model_save_dir=output/ \
-#       --with_mem_opt=False \
+#       --with_mem_opt=True \
 #       --lr_strategy=piecewise_decay \
 #	--num_epochs=120 \
 #       --lr=0.01
@@ -32,7 +32,7 @@ python train.py \
 #       --class_dim=1000 \
 #       --image_shape=3,224,224 \
 #       --model_save_dir=output/ \
-#       --with_mem_opt=False \
+#       --with_mem_opt=True \
 #       --lr_strategy=piecewise_decay \
 #       --num_epochs=120 \
 #       --lr=0.1
@@ -46,12 +46,22 @@ python train.py \
 #       --class_dim=1000 \
 #       --image_shape=3,224,224 \
 #       --model_save_dir=output/ \
-#       --with_mem_opt=False \
+#       --with_mem_opt=True \
 #       --lr_strategy=piecewise_decay \
 #	--num_epochs=120 \
 #       --lr=0.1
 
-
+#python train.py \
+#	--model=MobileNetV2 \
+#	--batch_size=500 \
+#	--total_images=1281167 \
+#	--class_dim=1000 \
+#	--image_shape=3,224,224 \
+#	--model_save_dir=output/ \
+#	--with_mem_opt=True \
+#	--lr_strategy=cosine_decay \
+#	--num_epochs=200 \
+#	--lr=0.1
 #ResNet50:
 #python train.py \
 #       --model=ResNet50 \
@@ -60,7 +70,7 @@ python train.py \
 #       --class_dim=1000 \
 #       --image_shape=3,224,224 \
 #       --model_save_dir=output/ \
-#       --with_mem_opt=False \
+#       --with_mem_opt=True \
 #       --lr_strategy=piecewise_decay \
 #	--num_epochs=120 \
 #       --lr=0.1