!37522 align docs for inplace_add and inplace_sub

Merge pull request !37522 from zhujingxuan/code_docs

docs/api/api_python/ops/mindspore.ops.func_inplace_add.rst

@@ -10,9 +10,9 @@ mindspore.ops.inplace_add
 
     **参数：**
 
-    - **x** (Tensor) - 待更新的Tensor。
-    - **v** (Tensor) - 待加上的值。
-    - **indices** (Union[int, tuple]) - 待更新值在原Tensor中的索引。
+    - **x** (Tensor) - 待更新的Tensor，支持的数据类型包括 float16，float32，float64，int32。
+    - **v** (Tensor) - 待加上的值，除第0维外每一维度需与 `x` 相同。数据类型应与 `x` 相同。
+    - **indices** (Union[int, tuple]) - 待更新值在原Tensor中的索引。取值范围[0, len(x))。若为tuple，则大小与 `v` 的第一维度大小相同。
 
     **返回：**
 

docs/api/api_python/ops/mindspore.ops.func_inplace_sub.rst

@@ -10,8 +10,8 @@ mindspore.ops.inplace_sub
 
     **参数：**
 
-    - **x** (Tensor) - 待更新的Tensor，其秩应小于8。
-    - **v** (Tensor) - 待减去的值。
+    - **x** (Tensor) - 待更新的Tensor，支持的数据类型包括 float16，float32，float64，int32。
+    - **v** (Tensor) - 待减去的值，除第0维外每一维度需与 `x` 相同。数据类型应与 `x` 相同。
     - **indices** (Union[int, tuple]) - 待更新值在原Tensor中的索引。取值范围[0, len(x))。若为tuple，则大小与 `v` 的第一维度大小相同。
 
     **返回：**

mindspore/python/mindspore/ops/function/math_func.py

@@ -876,7 +876,7 @@ def inplace_add(x, v, indices):
     Args:
         indices (Union[int, tuple]): Indices into the left-most dimension of `x`, and determines which rows of `x`
             to add with `v`. It is an integer or a tuple, whose value is in [0, the first dimension size of `x`).
-        x (Tensor) - The first input is a tensor whose data type is float16, float32 or int32.
+        x (Tensor) - The first input is a tensor whose data type is float16, float32, float64 or int32.
             :math:`(N,*)` where :math:`*` means, any number of additional dimensions, its rank should be less than 8.
         v (Tensor) - The second input is a tensor that has the same dimension sizes as `x` except
             the first dimension, which must be the same as indices' size. It has the same data type with `x`.
@@ -918,7 +918,7 @@ def inplace_sub(x, v, indices):
     Args:
         indices (Union[int, tuple]): Indices into the left-most dimension of `x`, and determines which rows of `x`
             to subtract with `v`. It is an int or tuple, whose value is in [0, the first dimension size of `x`).
-        x (Tensor) - The first input is a tensor whose data type is float16, float32 or int32.
+        x (Tensor) - The first input is a tensor whose data type is float16, float32, float64 or int32.
             :math:`(N,*)` where :math:`*` means, any number of additional dimensions, its rank should be less than 8.
         v (Tensor) - The second input is a tensor who has the same dimension sizes as `x` except
             the first dimension, which must be the same as indices' size. It has the same data type with `x`.