diff --git a/tutorials/source_zh_cn/advanced_use/distributed_training.md b/tutorials/source_zh_cn/advanced_use/distributed_training.md
index 1582d6ea252d73d8919ae3676e00e09f584fc295..45fd0488d9cdc763e4d8217a6d295f9cfe9ac3a0 100644
--- a/tutorials/source_zh_cn/advanced_use/distributed_training.md
+++ b/tutorials/source_zh_cn/advanced_use/distributed_training.md
@@ -249,7 +249,7 @@ from resnet import resnet50
 
 device_id = int(os.getenv('DEVICE_ID'))
 context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
-context.set_context(enable_task_sink=True, device_id=device_id) # set task_sink and device_id
+context.set_context(device_id=device_id) # set device_id
 context.set_context(enable_loop_sink=True)
 
 def test_train_cifar(num_classes=10, epoch_size=10):
@@ -263,7 +263,7 @@ def test_train_cifar(num_classes=10, epoch_size=10):
     model.train(epoch_size, dataset, callbacks=[loss_cb], dataset_sink_mode=True)
 ```
 其中，  
-- `dataset_sink_mode=True`，`enable_task_sink=True`,`enable_loop_sink=True`：表示采用数据集和任务的下沉模式，即训练的计算下沉到硬件平台中执行。
+- `dataset_sink_mode=True`，`enable_loop_sink=True`：表示采用数据集的下沉模式，即训练的计算下沉到硬件平台中执行。
 - `LossMonitor`：能够通过回调函数返回Loss值，用于监控损失函数。
 
 ## 运行脚本
diff --git a/tutorials/tutorial_code/distributed_training/resnet50_distributed_training.py b/tutorials/tutorial_code/distributed_training/resnet50_distributed_training.py
index 5d84a7afbb5f64941460b538080bfd5b8bc42da3..6937cb1e9b72271ec18de159d22a3130b124be29 100644
--- a/tutorials/tutorial_code/distributed_training/resnet50_distributed_training.py
+++ b/tutorials/tutorial_code/distributed_training/resnet50_distributed_training.py
@@ -35,7 +35,7 @@ from resnet import resnet50
 
 device_id = int(os.getenv('DEVICE_ID'))
 context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
-context.set_context(enable_task_sink=True, device_id=device_id) # set task_sink and device_id
+context.set_context(device_id=device_id) # set device_id
 context.set_context(enable_loop_sink=True)
 context.set_context(enable_mem_reuse=False)
 init()
diff --git a/tutorials/tutorial_code/resnet/cifar_resnet50.py b/tutorials/tutorial_code/resnet/cifar_resnet50.py
index df890186b2f843e27e54609bb67d850192953cd3..40e66165ce640239113f2285fdaa49a08855de50 100644
--- a/tutorials/tutorial_code/resnet/cifar_resnet50.py
+++ b/tutorials/tutorial_code/resnet/cifar_resnet50.py
@@ -54,7 +54,7 @@ device_id = int(os.getenv('DEVICE_ID'))
 data_home = args_opt.dataset_path
 
 context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
-context.set_context(enable_task_sink=True, device_id=device_id)
+context.set_context(device_id=device_id)
 context.set_context(enable_loop_sink=False)
 context.set_context(enable_mem_reuse=False)
 
diff --git a/tutorials/tutorial_code/sample_for_cloud/resnet50_train.py b/tutorials/tutorial_code/sample_for_cloud/resnet50_train.py
index 0b422a250b4b33588ec396b048e445e838d7e90c..af5ee4fa09eae8255b319936e181f9d9d875436d 100644
--- a/tutorials/tutorial_code/sample_for_cloud/resnet50_train.py
+++ b/tutorials/tutorial_code/sample_for_cloud/resnet50_train.py
@@ -116,7 +116,7 @@ def resnet50_train(args_opt):
 
     # set graph mode and parallel mode
     context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", save_graphs=False)
-    context.set_context(enable_task_sink=True, device_id=device_id)
+    context.set_context(device_id=device_id)
     context.set_context(enable_loop_sink=True)
     context.set_context(enable_mem_reuse=True)
     if device_num > 1: