add image cls scripts

examples/image_classification/scripts/mobilenet_v1_x1.0.sh

+export CUDA_VISIBLE_DEVICES=0,1,2,3 
+
+# 默认imagenet数据存储在data/ILSVRC2012/下，去除-d便使用静态图模式运行
+python -m paddle.distributed.launch main.py \
+        --arch mobilenet_v1 \
+        --epoch 120 \
+        --batch-size 64 \
+        --learning-rate 0.1 \
+        --lr-scheduler piecewise \
+        --milestones 30 60 90 \
+        --weight-decay 3e-5 \
+        -d \
+        data/ILSVRC2012/
\ No newline at end of file

examples/image_classification/scripts/mobilenet_v2_x1.0.sh

+export CUDA_VISIBLE_DEVICES=0,1,2,3 
+
+# 默认imagenet数据存储在data/ILSVRC2012/下，去除-d便使用静态图模式运行
+python -m paddle.distributed.launch main.py \
+        --arch mobilenet_v2 \
+        --epoch 240 \
+        --batch-size 64 \
+        --learning-rate 0.1 \
+        --lr-scheduler cosine \
+        --weight-decay 4e-5 \
+        -d \
+        data/ILSVRC2012/
\ No newline at end of file

examples/image_classification/scripts/resnet101.sh

+export CUDA_VISIBLE_DEVICES=0,1,2,3 
+
+# 默认imagenet数据存储在data/ILSVRC2012/下，去除-d便使用静态图模式运行
+python -m paddle.distributed.launch main.py \
+        --arch resnet101 \
+        --epoch 90 \
+        --batch-size 64 \
+        --learning-rate 0.1 \
+        -d \
+        data/ILSVRC2012/
\ No newline at end of file

examples/image_classification/scripts/resnet152.sh

+export CUDA_VISIBLE_DEVICES=0,1,2,3 
+
+# 默认imagenet数据存储在data/ILSVRC2012/下，去除-d便使用静态图模式运行
+python -m paddle.distributed.launch main.py \
+        --arch resnet152 \
+        --epoch 90 \
+        --batch-size 64 \
+        --learning-rate 0.1 \
+        -d \
+        data/ILSVRC2012/
\ No newline at end of file

examples/image_classification/scripts/resnet18.sh

+export CUDA_VISIBLE_DEVICES=0,1,2,3 
+
+# 默认imagenet数据存储在data/ILSVRC2012/下，去除-d便使用静态图模式运行
+python -m paddle.distributed.launch main.py \
+        --arch resnet18 \
+        --epoch 120 \
+        --batch-size 64 \
+        --learning-rate 0.1 \
+        --lr-scheduler cosine \
+        -d \
+        data/ILSVRC2012/
\ No newline at end of file

examples/image_classification/scripts/resnet34.sh

+export CUDA_VISIBLE_DEVICES=0,1,2,3 
+
+# 默认imagenet数据存储在data/ILSVRC2012/下，去除-d便使用静态图模式运行
+python -m paddle.distributed.launch main.py \
+        --arch resnet34 \
+        --epoch 120 \
+        --batch-size 64 \
+        --learning-rate 0.1 \
+        --lr-scheduler cosine \
+        -d \
+        data/ILSVRC2012/
\ No newline at end of file

examples/image_classification/scripts/resnet50.sh

+export CUDA_VISIBLE_DEVICES=0,1,2,3 
+
+# 默认imagenet数据存储在data/ILSVRC2012/下，去除-d便使用静态图模式运行
+python -m paddle.distributed.launch main.py \
+        --arch resnet50 \
+        --epoch 90 \
+        --batch-size 64 \
+        --learning-rate 0.1 \
+        -d \
+        data/ILSVRC2012/
\ No newline at end of file

examples/image_classification/scripts/vgg16.sh

+export CUDA_VISIBLE_DEVICES=0,1,2,3 
+
+# 默认imagenet数据存储在data/ILSVRC2012/下，去除-d便使用静态图模式运行
+python -m paddle.distributed.launch main.py \
+        --arch vgg16 \
+        --epoch 90 \
+        --batch-size 64 \
+        --learning-rate 0.01 \
+        --lr-scheduler cosine \
+        -d \
+        data/ILSVRC2012/
\ No newline at end of file