!36006 update documents for InplaceAdd and InplaceSub

Merge pull request !36006 from zhujingxuan/code_docs_inplace_op

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

@@ -21,4 +21,5 @@ mindspore.ops.inplace_add
     **异常：**
 
     - **TypeError** - `indices` 不是int或tuple。
-    - **TypeError** - `indices` 是元组，但是其中的元素不是int。
+    - **TypeError** - `indices` 是元组，但是其中的元素不是int。
+    - **ValueError** - `x` 的维度与 `v` 的维度不相等。

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

@@ -3,7 +3,7 @@ mindspore.ops.inplace_sub
 
 .. py:function:: mindspore.ops.inplace_sub(x, v, indices)
 
-    根据 `indices`，将 `v` 从 `x` 中减掉。
+    根据 `indices`，将 `v` 从 `x` 中减去。
 
     .. note::
         `indices` 只能沿着最高轴进行索引。
@@ -21,4 +21,5 @@ mindspore.ops.inplace_sub
     **异常：**
 
     - **TypeError** - `indices` 不是int或tuple。
-    - **TypeError** - `indices` 是元组，但是其中的元素不是int。
+    - **TypeError** - `indices` 是元组，但是其中的元素不是int。
+    - **ValueError** - `x` 的维度与 `v` 的维度不相等。

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

@@ -824,17 +824,19 @@ def inplace_add(x, v, indices):
     Raises:
         TypeError: If `indices` is neither int nor tuple.
         TypeError: If `indices` is a tuple whose elements are not all int.
-        ValueError: If length of shape of `x` is not equal to length of shape of `input_v`.
+        ValueError: If the rank of `x` is not equal to the rank of `v`.
 
     Supported Platforms:
         ``Ascend`` ``CPU``
 
     Examples:
+        >>> import numpy as np
+        >>> import mindspore
+        >>> from mindspore import Tensor, ops
         >>> indices = (0, 1)
         >>> x = Tensor(np.array([[1, 2], [3, 4], [5, 6]]), mindspore.float32)
         >>> input_v = Tensor(np.array([[0.5, 1.0], [1.0, 1.5]]), mindspore.float32)
-        >>> inplaceAdd = ops.InplaceAdd(indices)
+        >>> output = ops.inplace_add(x, input_v, indices)
-        >>> output = inplaceAdd(x, input_v)
         >>> print(output)
         [[1.5 3. ]
          [4.  5.5]
@@ -862,17 +864,19 @@ def inplace_sub(x, v, indices):
     Raises:
         TypeError: If `indices` is neither int nor tuple.
         TypeError: If `indices` is a tuple whose elements are not all int.
-        ValueError: If length of shape of `x` is not equal to length of shape of `input_v`.
+        ValueError: If the rank of `x` is not equal to the rank of `v`.
 
     Supported Platforms:
         ``Ascend`` ``CPU``
 
     Examples:
+        >>> import numpy as np
+        >>> import mindspore
+        >>> from mindspore import Tensor, ops
         >>> indices = (0, 1)
         >>> x = Tensor(np.array([[1, 2], [3, 4], [5, 6]]), mindspore.float32)
         >>> input_v = Tensor(np.array([[0.5, 1.0], [1.0, 1.5]]), mindspore.float32)
-        >>> inplaceSub = ops.InplaceSub(indices)
+        >>> output = ops.inplace_sub(x, input_v, indices)
-        >>> output = inplaceSub(x, input_v)
         >>> print(output)
         [[0.5 1. ]
          [2.  2.5]
@@ -3251,6 +3255,7 @@ def rad2deg(x):
         out = x * 180.0 / math.pi
     return out
 
+
 #####################################
 # Reduction Operation Functions.
 #####################################

mindspore/python/mindspore/ops/operations/math_ops.py

@@ -1773,28 +1773,12 @@ class InplaceAdd(PrimitiveWithInfer):
     """
     Adds `v` into specified rows of `x`. Computes `y` = `x`; y[i,] += `v`.
 
-    Args:
+    Refer to :func:`mindspore.ops.inplace_add` for more detail.
-        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`).
-
-    Inputs:
-        - **x** (Tensor) - The first input is a tensor whose data type is float16, float32 or int32.
-          :math:`(N,*)` where :math:`*` means, any number of additional dimensions, its rank should be less than 8.
-        - **input_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`.
-
-    Outputs:
-        Tensor, has the same shape and dtype as `x`.
-
-    Raises:
-        TypeError: If `indices` is neither int nor tuple.
-        TypeError: If `indices` is a tuple whose elements are not all int.
-        ValueError: If length of shape of `x` is not equal to length of shape of `input_v`.
-
-    Supported Platforms:
-        ``Ascend`` ``CPU``
 
     Examples:
+        >>> import numpy as np
+        >>> import mindspore
+        >>> from mindspore import Tensor, ops
         >>> indices = (0, 1)
         >>> x = Tensor(np.array([[1, 2], [3, 4], [5, 6]]), mindspore.float32)
         >>> input_v = Tensor(np.array([[0.5, 1.0], [1.0, 1.5]]), mindspore.float32)
@@ -1842,28 +1826,12 @@ class InplaceSub(PrimitiveWithInfer):
     """
     Subtracts `v` into specified rows of `x`. Computes `y` = `x`; y[i,] -= `v`.
 
-    Args:
+    Refer to :func:`mindspore.ops.inplace_sub` for more detail.
-        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`).
-
-    Inputs:
-        - **x** (Tensor) - The first input is a tensor whose data type is float16, float32 or int32.
-          :math:`(N,*)` where :math:`*` means, any number of additional dimensions, its rank should be less than 8.
-        - **input_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`.
-
-    Outputs:
-        Tensor, has the same shape and dtype as `x`.
-
-    Raises:
-        TypeError: If `indices` is neither int nor tuple.
-        TypeError: If `indices` is a tuple whose elements are not all int.
-        ValueError: If length of shape of `x` is not equal to length of shape of `input_v`.
-
-    Supported Platforms:
-        ``Ascend`` ``CPU``
 
     Examples:
+        >>> import numpy as np
+        >>> import mindspore
+        >>> from mindspore import Tensor, ops
         >>> indices = (0, 1)
         >>> x = Tensor(np.array([[1, 2], [3, 4], [5, 6]]), mindspore.float32)
         >>> input_v = Tensor(np.array([[0.5, 1.0], [1.0, 1.5]]), mindspore.float32)