modify format

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

@@ -20,7 +20,6 @@
 
     异常：
         - **TypeError** - `op` 或 `group` 不是str，或者输入的数据类型是bool。
-        - **ValueError** - `op` 为"prod"。
 
     样例：
 

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

@@ -28,13 +28,10 @@ mindspore.ops.norm
         - **ord** (Union[int, float, inf, -inf, 'fro', 'nuc'], 可选) - norm的模式。行为参考上表。默认值：None。
         - **dim** (Union[int, Tuple(int)], 可选) - 计算向量范数或矩阵范数的维度。默认值：None。
 
-            - 当 `dim` 为int时，会按向量范数计算。
-
-            - 当 `dim` 为一个二元组时，会按矩阵范数计算。
-
-            - 当 `dim` 为None且 `ord` 为None，`A` 将会被展平为1D并计算向量的2-范数。
-
-            - 当 `dim` 为None且 `ord` 不为None，`A` 必须为1D或者2D。
+          - 当 `dim` 为int时，会按向量范数计算。
+          - 当 `dim` 为一个二元组时，会按矩阵范数计算。
+          - 当 `dim` 为None且 `ord` 为None，`A` 将会被展平为1D并计算向量的2-范数。
+          - 当 `dim` 为None且 `ord` 不为None，`A` 必须为1D或者2D。
 
         - **keepdim** (bool) - 输出Tensor是否保留原有的维度。默认值：False。
 

mindspore/python/mindspore/ops/function/array_func.py

@@ -5640,7 +5640,7 @@ def topk(input_x, k, dim=None, largest=True, sorted=True):
         k (int): The number of top or bottom elements to be computed along the last dimension, constant input is needed.
         dim (int, optional): The dimension to sort along. Default: None.
         largest (bool, optional): If largest is False then the k smallest elements are returned. Default: True.
-        sorted (bool): If True, the obtained elements will be sorted by the values in descending order.
+        sorted (bool, optional): If True, the obtained elements will be sorted by the values in descending order.
             If False, the obtained elements will be sorted by the values in ascending order. Default: True.
 
     Returns:

mindspore/python/mindspore/ops/function/linalg_func.py

@@ -101,7 +101,7 @@ def pinv(x, *, atol=None, rtol=None, hermitian=False):
     atol or rtol is float.
     If atol or rtol is a Tensor, its shape must be broadcast to the singular value returned by
     `x.svd <https://www.mindspore.cn/docs/en/master/api_python/ops/mindspore.ops.svd.html>`_ .
-    If x.shape is :math:`(B, M, N)`, and the shape of atol or rtol is :math: `(K, B)`, the output
+    If x.shape is :math:`(B, M, N)`, and the shape of atol or rtol is :math:`(K, B)`, the output
     shape is :math:`(K, B, N, M)`.
     When the Hermitian is True, temporary support only real domain, x is treated as a real symmetric, so x is
     not checked internally, and only use the lower triangular part in the computations.

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

@@ -7214,21 +7214,21 @@ def norm(A, ord=None, dim=None, keepdim=False, *, dtype=None):
 
     `ord` is the calculation mode of norm. The following norm modes are supported.
 
-    ======================     =========================        ========================================================
-    `ord`                      norm for matrices                norm for vectors
-    ======================     =========================        ========================================================
-    `None` (default)           Frobenius norm                   `2`-norm (see below)
-    `'fro'`                    Frobenius norm                   -- not supported --
-    `'nuc'`                    nuclear norm                     -- not supported --
-    `inf`                      :math:`max(sum(abs(x), dim=1))`  :math:`max(abs(x))`
-    `-inf`                     :math:`min(sum(abs(x), dim=1))`  :math:`min(abs(x))`
-    `0`                        -- not supported --              :math:`sum(x != 0)`
-    `1`                        :math:`max(sum(abs(x), dim=0))`  as below
-    `-1`                       :math:`min(sum(abs(x), dim=0))`  as below
-    `2`                         largest singular value          as below
-    `-2`                       smallest singular value          as below
-    other `int` or `float`     -- not supported --              :math:`sum(abs(x)^{ord})^{(1 / ord)}`
-    ======================     =========================        ========================================================
+    ====================== ================================ ==========================================
+    `ord`                   norm for matrices               norm for vectors
+    ====================== ================================ ==========================================
+    `None` (default)        Frobenius norm                   `2`-norm (see below)
+    `'fro'`                 Frobenius norm                   -- not supported --
+    `'nuc'`                 nuclear norm                     -- not supported --
+    `inf`                   :math:`max(sum(abs(x), dim=1))`  :math:`max(abs(x))`
+    `-inf`                  :math:`min(sum(abs(x), dim=1))`  :math:`min(abs(x))`
+    `0`                     -- not supported --              :math:`sum(x != 0)`
+    `1`                     :math:`max(sum(abs(x), dim=0))`  as below
+    `-1`                    :math:`min(sum(abs(x), dim=0))`  as below
+    `2`                     largest singular value           as below
+    `-2`                    smallest singular value          as below
+    other `int` or `float`  -- not supported --              :math:`sum(abs(x)^{ord})^{(1 / ord)}`
+    ====================== ================================ ==========================================
 
     Args:
         A (Tensor): Tensor of shape :math:`(*, n)` or :math:`(*, m, n)` where * is zero or more batch dimensions.

mindspore/python/mindspore/ops/operations/array_ops.py

@@ -7822,7 +7822,7 @@ class TopK(Primitive):
     If the two compared elements are the same, the one with the smaller index value is returned first.
 
     Args:
-        sorted (bool): If True, the obtained elements will be sorted by the values in descending order.
+        sorted (bool, optional): If True, the obtained elements will be sorted by the values in descending order.
             If False, the obtained elements will be sorted by the values in ascending order. Default: True.
 
     Inputs: