!2829 googlenet support multy node training

Merge pull request !2829 from caojian05/ms_master_dev

model_zoo/googlenet/scripts/run_train.sh

@@ -33,10 +33,12 @@ MINDSPORE_HCCL_CONFIG_PATH=$(realpath $1)
 export MINDSPORE_HCCL_CONFIG_PATH
 echo "MINDSPORE_HCCL_CONFIG_PATH=${MINDSPORE_HCCL_CONFIG_PATH}"
 
+export SERVER_ID=0
+rank_start=$((DEVICE_NUM * SERVER_ID))
 for((i=0; i<${DEVICE_NUM}; i++))
 do
     export DEVICE_ID=$i
-    export RANK_ID=$i
+    export RANK_ID=$((rank_start + i))
     rm -rf ./train_parallel$i
     mkdir ./train_parallel$i
     cp -r ./src ./train_parallel$i

model_zoo/googlenet/src/dataset.py

@@ -31,8 +31,7 @@ def create_dataset(data_home, repeat_num=1, training=True):
     if not training:
         data_dir = os.path.join(data_home, "cifar-10-verify-bin")
 
-    rank_size = int(os.environ.get("RANK_SIZE")) if os.environ.get("RANK_SIZE") else None
-    rank_id = int(os.environ.get("RANK_ID")) if os.environ.get("RANK_ID") else None
+    rank_size, rank_id = _get_rank_info()
     data_set = ds.Cifar10Dataset(data_dir, num_shards=rank_size, shard_id=rank_id)
 
     resize_height = cfg.image_height
@@ -65,3 +64,19 @@ def create_dataset(data_home, repeat_num=1, training=True):
     data_set = data_set.batch(batch_size=cfg.batch_size, drop_remainder=True)
 
     return data_set
+
+
+def _get_rank_info():
+    """
+    get rank size and rank id
+    """
+    rank_size = int(os.environ.get("RANK_SIZE", 1))
+
+    if rank_size > 1:
+        from mindspore.communication.management import get_rank, get_group_size
+        rank_size = get_group_size()
+        rank_id = get_rank()
+    else:
+        rank_size = rank_id = None
+
+    return rank_size, rank_id