diff --git a/mindspore/communication/management.py b/mindspore/communication/management.py
index 3fb4e7b9477..be07b538610 100755
--- a/mindspore/communication/management.py
+++ b/mindspore/communication/management.py
@@ -14,6 +14,7 @@
 # ============================================================================
 """Communication management API"""
 import os
+from mindspore import context
 from mindspore.parallel._auto_parallel_context import auto_parallel_context
 from ._comm_helper import Backend, _get_rank_helper, _get_size_helper, \
     _get_world_rank_from_group_rank_helper, _get_group_rank_from_world_rank_helper, \
@@ -45,7 +46,7 @@ class GlobalComm:
     WORLD_COMM_GROUP = DEFAULT_WORLD_COMM_GROUP
 
 
-def init(backend_name="hccl"):
+def init(backend_name=None):
     """
     Init distributed backend, e.g., hccl/nccl, it is required before communication service can be used.
 
@@ -57,11 +58,20 @@ def init(backend_name="hccl"):
         backend_name (str): Backend.
 
     Raises:
-        TypeError: If backend name is not a string.
+        TypeError: If backen_name is not a string.
+        RuntimeError: If device target is invalid.
         RuntimeError: If backend is invalid or distributed init fails.
     """
     if MS_ROLE in ("MS_PSERVER", "MS_SCHED"):
         return
+    if backend_name is None:
+        device_target = context.get_context("device_target")
+        if device_target == "Ascend":
+            backend_name = "hccl"
+        elif device_target == "GPU":
+            backend_name = "nccl"
+        else:
+            raise RuntimeError("Device target {} is not supported.".format(device_target))
     if not isinstance(backend_name, str):
         raise TypeError("Backend name must be a string, but got {}".format(type(backend_name)))
 
diff --git a/mindspore/ops/operations/comm_ops.py b/mindspore/ops/operations/comm_ops.py
index 2b84741fea6..6aff5037796 100644
--- a/mindspore/ops/operations/comm_ops.py
+++ b/mindspore/ops/operations/comm_ops.py
@@ -73,7 +73,7 @@ class AllReduce(PrimitiveWithInfer):
         >>> import mindspore.nn as nn
         >>> import mindspore.ops.operations as P
         >>>
-        >>> init('nccl')
+        >>> init()
         >>> class Net(nn.Cell):
         >>>     def __init__(self):
         >>>         super(Net, self).__init__()
@@ -136,7 +136,7 @@ class AllGather(PrimitiveWithInfer):
         >>> from mindspore.communication import init
         >>> from mindspore import Tensor
         >>>
-        >>> init('nccl')
+        >>> init()
         >>> class Net(nn.Cell):
         >>>     def __init__(self):
         >>>         super(Net, self).__init__()
@@ -246,7 +246,7 @@ class ReduceScatter(PrimitiveWithInfer):
         >>> import mindspore.nn as nn
         >>> import mindspore.ops.operations as P
         >>>
-        >>> init('nccl')
+        >>> init()
         >>> class Net(nn.Cell):
         >>>     def __init__(self):
         >>>         super(Net, self).__init__()
@@ -360,7 +360,7 @@ class Broadcast(PrimitiveWithInfer):
         >>> import mindspore.nn as nn
         >>> import mindspore.ops.operations as P
         >>>
-        >>> init('nccl')
+        >>> init()
         >>> class Net(nn.Cell):
         >>>     def __init__(self):
         >>>         super(Net, self).__init__()
diff --git a/model_zoo/official/cv/googlenet/train.py b/model_zoo/official/cv/googlenet/train.py
index 5181f9c484a..65300a673d2 100644
--- a/model_zoo/official/cv/googlenet/train.py
+++ b/model_zoo/official/cv/googlenet/train.py
@@ -81,7 +81,7 @@ if __name__ == '__main__':
                                               mirror_mean=True)
             init()
     elif device_target == "GPU":
-        init("nccl")
+        init()
 
         if device_num > 1:
             context.reset_auto_parallel_context()
diff --git a/model_zoo/official/cv/inceptionv3/train.py b/model_zoo/official/cv/inceptionv3/train.py
index f2d2256eef5..d07d3855fb3 100644
--- a/model_zoo/official/cv/inceptionv3/train.py
+++ b/model_zoo/official/cv/inceptionv3/train.py
@@ -57,10 +57,7 @@ if __name__ == '__main__':
     cfg = config_ascend if args_opt.platform == 'Ascend' else config_gpu
     # init distributed
     if args_opt.is_distributed:
-        if args_opt.platform == "Ascend":
-            init()
-        else:
-            init("nccl")
+        init()
         cfg.rank = get_rank()
         cfg.group_size = get_group_size()
         parallel_mode = ParallelMode.DATA_PARALLEL
diff --git a/model_zoo/official/cv/mobilenetv2/train.py b/model_zoo/official/cv/mobilenetv2/train.py
index 4fb800d6ddd..a282742381a 100644
--- a/model_zoo/official/cv/mobilenetv2/train.py
+++ b/model_zoo/official/cv/mobilenetv2/train.py
@@ -64,7 +64,7 @@ elif args_opt.device_target == "GPU":
     context.set_context(mode=context.GRAPH_MODE,
                         device_target="GPU",
                         save_graphs=False)
-    init("nccl")
+    init()
     context.set_auto_parallel_context(device_num=get_group_size(),
                                       parallel_mode=ParallelMode.DATA_PARALLEL,
                                       mirror_mean=True)
diff --git a/model_zoo/official/cv/mobilenetv2_quant/train.py b/model_zoo/official/cv/mobilenetv2_quant/train.py
index ebe60996cf9..eb59d37c367 100644
--- a/model_zoo/official/cv/mobilenetv2_quant/train.py
+++ b/model_zoo/official/cv/mobilenetv2_quant/train.py
@@ -57,7 +57,7 @@ if args_opt.device_target == "Ascend":
                         device_target="Ascend",
                         device_id=device_id, save_graphs=False)
 elif args_opt.device_target == "GPU":
-    init("nccl")
+    init()
     context.set_auto_parallel_context(device_num=get_group_size(),
                                       parallel_mode=ParallelMode.DATA_PARALLEL,
                                       mirror_mean=True)
diff --git a/model_zoo/official/cv/mobilenetv3/train.py b/model_zoo/official/cv/mobilenetv3/train.py
index 60f3723244e..ea1f9ec27ec 100644
--- a/model_zoo/official/cv/mobilenetv3/train.py
+++ b/model_zoo/official/cv/mobilenetv3/train.py
@@ -54,7 +54,7 @@ if args_opt.device_target == "GPU":
     context.set_context(mode=context.GRAPH_MODE,
                         device_target="GPU",
                         save_graphs=False)
-    init("nccl")
+    init()
     context.set_auto_parallel_context(device_num=get_group_size(),
                                       parallel_mode=ParallelMode.DATA_PARALLEL,
                                       mirror_mean=True)
diff --git a/model_zoo/official/cv/resnet/src/dataset.py b/model_zoo/official/cv/resnet/src/dataset.py
index 9d39b5ab77d..86ffecb1ec1 100755
--- a/model_zoo/official/cv/resnet/src/dataset.py
+++ b/model_zoo/official/cv/resnet/src/dataset.py
@@ -38,7 +38,7 @@ def create_dataset1(dataset_path, do_train, repeat_num=1, batch_size=32, target=
     if target == "Ascend":
         device_num, rank_id = _get_rank_info()
     else:
-        init("nccl")
+        init()
         rank_id = get_rank()
         device_num = get_group_size()
 
@@ -93,7 +93,7 @@ def create_dataset2(dataset_path, do_train, repeat_num=1, batch_size=32, target=
     if target == "Ascend":
         device_num, rank_id = _get_rank_info()
     else:
-        init("nccl")
+        init()
         rank_id = get_rank()
         device_num = get_group_size()
 
diff --git a/model_zoo/official/cv/resnet/train.py b/model_zoo/official/cv/resnet/train.py
index 81c7c08a625..8426c6b6458 100755
--- a/model_zoo/official/cv/resnet/train.py
+++ b/model_zoo/official/cv/resnet/train.py
@@ -85,7 +85,7 @@ if __name__ == '__main__':
             init()
         # GPU target
         else:
-            init("nccl")
+            init()
             context.set_auto_parallel_context(device_num=get_group_size(), parallel_mode=ParallelMode.DATA_PARALLEL,
                                               mirror_mean=True)
             if args_opt.net == "resnet50":
diff --git a/model_zoo/official/cv/resnet50_quant/src/dataset.py b/model_zoo/official/cv/resnet50_quant/src/dataset.py
index 3c35adeaaa0..7841bc403b7 100755
--- a/model_zoo/official/cv/resnet50_quant/src/dataset.py
+++ b/model_zoo/official/cv/resnet50_quant/src/dataset.py
@@ -46,7 +46,7 @@ def create_dataset(dataset_path, do_train, repeat_num=1, batch_size=32, target="
         device_num = int(os.getenv("RANK_SIZE"))
         rank_id = int(os.getenv("RANK_ID"))
     else:
-        init("nccl")
+        init()
         rank_id = get_rank()
         device_num = get_group_size()
 
@@ -114,7 +114,7 @@ def create_dataset_py(dataset_path, do_train, repeat_num=1, batch_size=32, targe
         device_num = int(os.getenv("RANK_SIZE"))
         rank_id = int(os.getenv("RANK_ID"))
     else:
-        init("nccl")
+        init()
         rank_id = get_rank()
         device_num = get_group_size()
 
diff --git a/model_zoo/official/cv/resnet_thor/src/dataset.py b/model_zoo/official/cv/resnet_thor/src/dataset.py
index fc6dc1bac98..3f3b006fb5c 100644
--- a/model_zoo/official/cv/resnet_thor/src/dataset.py
+++ b/model_zoo/official/cv/resnet_thor/src/dataset.py
@@ -40,7 +40,7 @@ def create_dataset(dataset_path, do_train, repeat_num=1, batch_size=32, target="
     if target == "Ascend":
         device_num, rank_id = _get_rank_info()
     else:
-        init("nccl")
+        init()
         rank_id = get_rank()
         device_num = get_group_size()
 
diff --git a/model_zoo/official/cv/resnet_thor/train.py b/model_zoo/official/cv/resnet_thor/train.py
index d7c667dffae..cef6ac0a3c4 100644
--- a/model_zoo/official/cv/resnet_thor/train.py
+++ b/model_zoo/official/cv/resnet_thor/train.py
@@ -106,7 +106,7 @@ if __name__ == '__main__':
             init()
         # GPU target
         else:
-            init("nccl")
+            init()
             context.set_auto_parallel_context(device_num=get_group_size(), parallel_mode=ParallelMode.DATA_PARALLEL,
                                               mirror_mean=True)
             ckpt_save_dir = config.save_checkpoint_path + "ckpt_" + str(get_rank()) + "/"
diff --git a/model_zoo/official/cv/resnext50/eval.py b/model_zoo/official/cv/resnext50/eval.py
index 4dc2aa485ab..06b4acfe05a 100644
--- a/model_zoo/official/cv/resnext50/eval.py
+++ b/model_zoo/official/cv/resnext50/eval.py
@@ -112,10 +112,7 @@ def test(cloud_args=None):
 
     # init distributed
     if args.is_distributed:
-        if args.platform == "Ascend":
-            init()
-        elif args.platform == "GPU":
-            init("nccl")
+        init()
         args.rank = get_rank()
         args.group_size = get_group_size()
         parallel_mode = ParallelMode.DATA_PARALLEL
diff --git a/model_zoo/official/cv/resnext50/train.py b/model_zoo/official/cv/resnext50/train.py
index d2cb72d5d21..6b31cbd8f1c 100644
--- a/model_zoo/official/cv/resnext50/train.py
+++ b/model_zoo/official/cv/resnext50/train.py
@@ -172,10 +172,7 @@ def train(cloud_args=None):
 
     # init distributed
     if args.is_distributed:
-        if args.platform == "Ascend":
-            init()
-        else:
-            init("nccl")
+        init()
         args.rank = get_rank()
         args.group_size = get_group_size()
         parallel_mode = ParallelMode.DATA_PARALLEL
diff --git a/model_zoo/official/cv/vgg16/train.py b/model_zoo/official/cv/vgg16/train.py
index ae2f934e1e7..d0f04271b10 100644
--- a/model_zoo/official/cv/vgg16/train.py
+++ b/model_zoo/official/cv/vgg16/train.py
@@ -135,7 +135,7 @@ if __name__ == '__main__':
             init()
             context.set_context(device_id=args.device_id)
         elif args.device_target == "GPU":
-            init("nccl")
+            init()
 
         args.rank = get_rank()
         args.group_size = get_group_size()
diff --git a/model_zoo/official/cv/warpctc/train.py b/model_zoo/official/cv/warpctc/train.py
index 380308653fd..2746b83fe7f 100755
--- a/model_zoo/official/cv/warpctc/train.py
+++ b/model_zoo/official/cv/warpctc/train.py
@@ -60,7 +60,7 @@ if __name__ == '__main__':
             device_num = int(os.environ.get("RANK_SIZE"))
             rank = int(os.environ.get("RANK_ID"))
         else:
-            init('nccl')
+            init()
             lr_scale = 0.5
             device_num = get_group_size()
             rank = get_rank()
diff --git a/model_zoo/official/nlp/bert/run_pretrain.py b/model_zoo/official/nlp/bert/run_pretrain.py
index 73b1021003e..2a12b7913da 100644
--- a/model_zoo/official/nlp/bert/run_pretrain.py
+++ b/model_zoo/official/nlp/bert/run_pretrain.py
@@ -70,11 +70,11 @@ def run_pretrain():
     ckpt_save_dir = args_opt.save_checkpoint_path
     if args_opt.distribute == "true":
         if args_opt.device_target == 'Ascend':
-            D.init('hccl')
+            D.init()
             device_num = args_opt.device_num
             rank = args_opt.device_id % device_num
         else:
-            D.init('nccl')
+            D.init()
             device_num = D.get_group_size()
             rank = D.get_rank()
             ckpt_save_dir = args_opt.save_checkpoint_path + 'ckpt_' + str(rank) + '/'
diff --git a/model_zoo/official/nlp/bert_thor/run_pretrain.py b/model_zoo/official/nlp/bert_thor/run_pretrain.py
index 5c5e1c282f7..0d9e4a4a204 100644
--- a/model_zoo/official/nlp/bert_thor/run_pretrain.py
+++ b/model_zoo/official/nlp/bert_thor/run_pretrain.py
@@ -73,11 +73,11 @@ def run_pretrain():
     ckpt_save_dir = args_opt.save_checkpoint_path
     if args_opt.distribute == "true":
         if args_opt.device_target == 'Ascend':
-            D.init('hccl')
+            D.init()
             device_num = args_opt.device_num
             rank = args_opt.device_id % device_num
         else:
-            D.init('nccl')
+            D.init()
             device_num = D.get_group_size()
             rank = D.get_rank()
             ckpt_save_dir = args_opt.save_checkpoint_path + 'ckpt_' + str(rank) + '/'
diff --git a/model_zoo/official/nlp/mass/train.py b/model_zoo/official/nlp/mass/train.py
index 81854bcb8c2..97a87b0ff35 100644
--- a/model_zoo/official/nlp/mass/train.py
+++ b/model_zoo/official/nlp/mass/train.py
@@ -227,10 +227,7 @@ def _build_training_pipeline(config: TransformerConfig,
 
 def _setup_parallel_env(platform):
     context.reset_auto_parallel_context()
-    if platform == "GPU":
-        MultiAscend.init("nccl")
-    else:
-        MultiAscend.init()
+    MultiAscend.init()
     context.set_auto_parallel_context(
         parallel_mode=ParallelMode.DATA_PARALLEL,
         device_num=MultiAscend.get_group_size(),
diff --git a/model_zoo/official/nlp/tinybert/run_general_distill.py b/model_zoo/official/nlp/tinybert/run_general_distill.py
index 8fdc86b8bcd..f1d7620ae0c 100644
--- a/model_zoo/official/nlp/tinybert/run_general_distill.py
+++ b/model_zoo/official/nlp/tinybert/run_general_distill.py
@@ -67,11 +67,11 @@ def run_general_distill():
 
     if args_opt.distribute == "true":
         if args_opt.device_target == 'Ascend':
-            D.init('hccl')
+            D.init()
             device_num = args_opt.device_num
             rank = args_opt.device_id % device_num
         else:
-            D.init('nccl')
+            D.init()
             device_num = D.get_group_size()
             rank = D.get_rank()
             save_ckpt_dir = save_ckpt_dir + '_ckpt_' + str(rank)
diff --git a/model_zoo/official/recommend/deepfm/train.py b/model_zoo/official/recommend/deepfm/train.py
index 95810c3a7e0..3dd8373c835 100644
--- a/model_zoo/official/recommend/deepfm/train.py
+++ b/model_zoo/official/recommend/deepfm/train.py
@@ -59,7 +59,7 @@ if __name__ == '__main__':
             init()
             rank_id = int(os.environ.get('RANK_ID'))
         elif args_opt.device_target == "GPU":
-            init("nccl")
+            init()
             context.set_context(mode=context.GRAPH_MODE, device_target=args_opt.device_target)
             context.reset_auto_parallel_context()
             context.set_auto_parallel_context(device_num=get_group_size(),
diff --git a/model_zoo/official/recommend/wide_and_deep/train_and_eval_auto_parallel.py b/model_zoo/official/recommend/wide_and_deep/train_and_eval_auto_parallel.py
index 4af6366e42d..38904a52c99 100644
--- a/model_zoo/official/recommend/wide_and_deep/train_and_eval_auto_parallel.py
+++ b/model_zoo/official/recommend/wide_and_deep/train_and_eval_auto_parallel.py
@@ -128,10 +128,7 @@ if __name__ == "__main__":
     context.set_context(variable_memory_max_size="24GB")
     context.set_context(enable_sparse=True)
     set_multi_subgraphs()
-    if wide_deep_config.device_target == "Ascend":
-        init("hccl")
-    elif wide_deep_config.device_target == "GPU":
-        init("nccl")
+    init()
     if wide_deep_config.host_device_mix == 1:
         context.set_auto_parallel_context(parallel_mode=ParallelMode.SEMI_AUTO_PARALLEL, mirror_mean=True)
     else:
diff --git a/model_zoo/official/recommend/wide_and_deep/train_and_eval_distribute.py b/model_zoo/official/recommend/wide_and_deep/train_and_eval_distribute.py
index 9e70cd1d681..96616171c99 100644
--- a/model_zoo/official/recommend/wide_and_deep/train_and_eval_distribute.py
+++ b/model_zoo/official/recommend/wide_and_deep/train_and_eval_distribute.py
@@ -122,10 +122,7 @@ if __name__ == "__main__":
     wide_deep_config.argparse_init()
 
     context.set_context(mode=context.GRAPH_MODE, device_target=wide_deep_config.device_target, save_graphs=True)
-    if wide_deep_config.device_target == "Ascend":
-        init("hccl")
-    elif wide_deep_config.device_target == "GPU":
-        init("nccl")
+    init()
     context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL, mirror_mean=True,
                                       device_num=get_group_size())
 
diff --git a/model_zoo/official/recommend/wide_and_deep/train_and_eval_parameter_server.py b/model_zoo/official/recommend/wide_and_deep/train_and_eval_parameter_server.py
index bab19acdc46..2ddce02725f 100644
--- a/model_zoo/official/recommend/wide_and_deep/train_and_eval_parameter_server.py
+++ b/model_zoo/official/recommend/wide_and_deep/train_and_eval_parameter_server.py
@@ -119,10 +119,7 @@ if __name__ == "__main__":
     wide_deep_config.argparse_init()
 
     context.set_context(mode=context.GRAPH_MODE, device_target=wide_deep_config.device_target)
-    if wide_deep_config.device_target == "Ascend":
-        init("hccl")
-    elif wide_deep_config.device_target == "GPU":
-        init("nccl")
+    init()
     context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL, mirror_mean=True,
                                       device_num=get_group_size())
 
diff --git a/tests/st/nccl/test_nccl_all_gather_op.py b/tests/st/nccl/test_nccl_all_gather_op.py
index 9d7ad205c9e..afaf6167215 100644
--- a/tests/st/nccl/test_nccl_all_gather_op.py
+++ b/tests/st/nccl/test_nccl_all_gather_op.py
@@ -24,7 +24,7 @@ from mindspore.ops import operations as P
 
 context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
 
-init('nccl')
+init()
 rank = get_rank()
 size = get_group_size()
 x = np.ones([1, 1, 3, 3]).astype(np.float32) * 0.01 * (rank + 1)
diff --git a/tests/st/nccl/test_nccl_all_reduce_op.py b/tests/st/nccl/test_nccl_all_reduce_op.py
index 0f00c6aef7e..c40bc48b9fa 100644
--- a/tests/st/nccl/test_nccl_all_reduce_op.py
+++ b/tests/st/nccl/test_nccl_all_reduce_op.py
@@ -24,7 +24,7 @@ from mindspore.ops import operations as P
 
 context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
 
-init('nccl')
+init()
 rank = get_rank()
 size = get_group_size()
 x = np.ones([3, 1, 3, 3]).astype(np.float32) * 0.01 * (rank + 1)
diff --git a/tests/st/nccl/test_nccl_broadcast_op.py b/tests/st/nccl/test_nccl_broadcast_op.py
index 4541bf6e6b7..fe3955dc396 100644
--- a/tests/st/nccl/test_nccl_broadcast_op.py
+++ b/tests/st/nccl/test_nccl_broadcast_op.py
@@ -24,7 +24,7 @@ from mindspore.ops import operations as P
 
 context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
 
-init('nccl')
+init()
 rank = get_rank()
 size = get_group_size()
 x = np.ones([3, 1, 3, 3]).astype(np.float32) * 0.01 * (rank + 1)
diff --git a/tests/st/nccl/test_nccl_lenet.py b/tests/st/nccl/test_nccl_lenet.py
index 37fd6363c06..632e8ec575b 100644
--- a/tests/st/nccl/test_nccl_lenet.py
+++ b/tests/st/nccl/test_nccl_lenet.py
@@ -25,7 +25,7 @@ from mindspore.nn.optim import Momentum
 from mindspore.ops import operations as P
 
 context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
-init('nccl')
+init()
 
 epoch = 5
 total = 5000
diff --git a/tests/st/nccl/test_nccl_reduce_scatter_op.py b/tests/st/nccl/test_nccl_reduce_scatter_op.py
index 59ede9cd76e..14b4c574b5e 100644
--- a/tests/st/nccl/test_nccl_reduce_scatter_op.py
+++ b/tests/st/nccl/test_nccl_reduce_scatter_op.py
@@ -24,7 +24,7 @@ from mindspore.ops import operations as P
 
 context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
 
-init('nccl')
+init()
 rank = get_rank()
 size = get_group_size()
 x = np.ones([size, 1, 3, 3]).astype(np.float32) * 0.01 * (rank + 1)
diff --git a/tests/st/ps/multi_full_ps/test_multi_full_ps.py b/tests/st/ps/multi_full_ps/test_multi_full_ps.py
index 30bf6176923..181d2512626 100644
--- a/tests/st/ps/multi_full_ps/test_multi_full_ps.py
+++ b/tests/st/ps/multi_full_ps/test_multi_full_ps.py
@@ -30,7 +30,7 @@ args, _ = parser.parse_known_args()
 device_target = args.device_target
 context.set_context(mode=context.GRAPH_MODE, device_target=device_target)
 if device_target == "GPU":
-    init('nccl')
+    init()
 
 
 def conv(in_channels, out_channels, kernel_size, stride=1, padding=0):
diff --git a/tests/ut/python/train/test_dataset_helper.py b/tests/ut/python/train/test_dataset_helper.py
index 6540adfe12f..916d87caad8 100644
--- a/tests/ut/python/train/test_dataset_helper.py
+++ b/tests/ut/python/train/test_dataset_helper.py
@@ -75,7 +75,7 @@ def test_dataset_iter_normal():
 
 @pytest.mark.skipif('not context.get_context("enable_ge")')
 def test_dataset_iter_ge():
-    init()
+    init("hccl")
     dataset = get_dataset(32)
     dataset_helper = DatasetHelper(dataset, dataset_sink_mode=True, sink_size=10)
     count = 0
@@ -87,7 +87,7 @@ def test_dataset_iter_ge():
 
 @pytest.mark.skipif('context.get_context("enable_ge")')
 def test_dataset_iter_ms_loop_sink():
-    init()
+    init("hccl")
     context.set_context(enable_loop_sink=True)
     dataset = get_dataset(32)
     dataset_helper = DatasetHelper(dataset, dataset_sink_mode=True, sink_size=10)
@@ -101,7 +101,7 @@ def test_dataset_iter_ms_loop_sink():
 
 @pytest.mark.skipif('context.get_context("enable_ge")')
 def test_dataset_iter_ms():
-    init()
+    init("hccl")
     context.set_context(enable_loop_sink=False)
     dataset = get_dataset(32)
     DatasetHelper(dataset, dataset_sink_mode=True, sink_size=10)