diff --git a/tutorials/source_en/advanced_use/network_migration.md b/tutorials/source_en/advanced_use/network_migration.md
index 131e852ce8525bba2c209deb2e042a5431a29b19..d5c91ee3040bcbae535cd818831dc7c4d1312578 100644
--- a/tutorials/source_en/advanced_use/network_migration.md
+++ b/tutorials/source_en/advanced_use/network_migration.md
@@ -57,6 +57,8 @@ Prepare the hardware environment, find a platform corresponding to your environm
 
 MindSpore differs from TensorFlow and PyTorch in the network structure. Before migration, you need to clearly understand the original script and information of each layer, such as shape.
 
+> You can also use [MindConverter Tool](https://gitee.com/mindspore/mindinsight/tree/master/mindinsight/mindconverter) to automatically convert the PyTorch network definition script to MindSpore network definition script.
+
 The ResNet-50 network migration and training on the Ascend 910 is used as an example.
 
 1. Import MindSpore modules.
diff --git a/tutorials/source_zh_cn/advanced_use/network_migration.md b/tutorials/source_zh_cn/advanced_use/network_migration.md
index f1d8aa4feb3ad8fa1d308cbc98f9d83292f75375..b427c91d45c24eb8048dce50db6c03c0705138a0 100644
--- a/tutorials/source_zh_cn/advanced_use/network_migration.md
+++ b/tutorials/source_zh_cn/advanced_use/network_migration.md
@@ -55,6 +55,8 @@
 
 MindSpore与TensorFlow、PyTorch在网络结构组织方式上，存在一定差别，迁移前需要对原脚本有较为清晰的了解，明确地知道每一层的shape等信息。
 
+> 你也可以使用[MindConverter工具](https://gitee.com/mindspore/mindinsight/tree/master/mindinsight/mindconverter)实现PyTorch网络定义脚本到MindSpore网络定义脚本的自动转换。
+
 下面，我们以ResNet-50的迁移，并在Ascend 910上训练为例：
 
 1. 导入MindSpore模块。