vgg16 support imagenet dataset on Ascend

model_zoo/official/cv/vgg16/scripts/run_distribute_train.sh

@@ -14,9 +14,9 @@
 # limitations under the License.
 # ============================================================================
 
-if [ $# != 2 ]
+if [ $# != 2 ] && [ $# != 3 ]
 then
-    echo "Usage: sh run_distribute_train.sh [RANK_TABLE_FILE] [DATA_PATH]"
+    echo "Usage: sh run_distribute_train.sh [RANK_TABLE_FILE] [DATA_PATH] [cifar10|imagenet2012]"
 exit 1
 fi
 
@@ -32,6 +32,19 @@ then
 exit 1
 fi
 
+
+dataset_type='cifar10'
+if [ $# == 3 ]
+then
+    if [ $3 != "cifar10" ] && [ $3 != "imagenet2012" ]
+    then
+        echo "error: the selected dataset is neither cifar10 nor imagenet2012"
+    exit 1
+    fi
+    dataset_type=$3
+fi
+
+
 export DEVICE_NUM=8
 export RANK_SIZE=8
 export RANK_TABLE_FILE=$1
@@ -45,8 +58,8 @@ do
     cp *.py ./train_parallel$i
     cp -r src ./train_parallel$i
     cd ./train_parallel$i || exit
-    echo "start training for rank $RANK_ID, device $DEVICE_ID"
+    echo "start training for rank $RANK_ID, device $DEVICE_ID, $dataset_type"
     env > env.log
-    python train.py --data_path=$2 --device_target="Ascend" --device_id=$i --is_distributed=1 &> log &
+    python train.py --data_path=$2 --device_target="Ascend" --device_id=$i --is_distributed=1 --dataset=$dataset_type &> log &
     cd ..
 done

model_zoo/official/cv/vgg16/src/vgg.py

@@ -139,5 +139,8 @@ def vgg16(num_classes=1000, args=None, phase="train"):
         >>> vgg16(num_classes=1000, args=args)
     """
 
+    if args is None:
+        from .config import cifar_cfg
+        args = cifar_cfg
     net = Vgg(cfg['16'], num_classes=num_classes, args=args, batch_norm=args.batch_norm, phase=phase)
     return net