diff --git a/docs/lite/docs/source_en/use/runtime_train_cpp.md b/docs/lite/docs/source_en/use/runtime_train_cpp.md
index 4e5af9d4d63e1c86e4db8d7bb41b4f4e245dce48..5019b1d80a5fe795ed11feb17cf7e328d03cfb96 100644
--- a/docs/lite/docs/source_en/use/runtime_train_cpp.md
+++ b/docs/lite/docs/source_en/use/runtime_train_cpp.md
@@ -454,7 +454,7 @@ MindSpore Lite framework allows the user to set two callback functions that will
 - Name and type of the running node
 
 While the node name and type will be the same before and after running the node, the output tensors will differ between the two callbacks invocations.
-For some operators, also the input tesnors will vary.
+For some operators, also the input tensors will vary.
 
 ```cpp
 /// \brief  CallBackParam defines input arguments for callback function.
diff --git a/docs/mindspore/source_en/faq/data_processing.md b/docs/mindspore/source_en/faq/data_processing.md
index 23d1245ff53492a00e3c41dfb1a8117f0a219133..f4899f424aa1ab1359a6333cba1b935ee3d31ecc 100644
--- a/docs/mindspore/source_en/faq/data_processing.md
+++ b/docs/mindspore/source_en/faq/data_processing.md
@@ -371,7 +371,7 @@ A: The main reason is that the parameter `num_parallel_workers` is configured to
 
 A: When the `GeneratorDataset` is used to load Numpy array returned by Pyfunc, MindSpore performs conversion from the Numpy array to the MindSpore Tensor. If the memory pointed to by the Numpy array has been freed, a memory copy error may occur. An example is as shown below:
 
-- Perform an in place conversion among Numpy array, MindSpore Tensor and Numpy array in `__getitem__` function. Tensor `tensor` and Numpy array `ndarray_1` share the same memory and Tensor `tesnor` will go out of scope when the function exits, and the memory which is pointed to by Numpy array will be freed.
+- Perform an in place conversion among Numpy array, MindSpore Tensor and Numpy array in `__getitem__` function. Tensor `tensor` and Numpy array `ndarray_1` share the same memory and Tensor `tensor` will go out of scope when the function exits, and the memory which is pointed to by Numpy array will be freed.
 
     ```python