!48366 Fix SearchSorted ERROR

Merge pull request !48366 from huangxinjing/code_docs_fix_search_sorted

docs/api/api_python/mindspore.ops.rst

@@ -344,9 +344,10 @@ Reduction函数
     mindspore.ops.lt
     mindspore.ops.maximum
     mindspore.ops.minimum
+    mindspore.ops.msort
     mindspore.ops.ne
     mindspore.ops.not_equal
-    mindspore.ops.msort
+    mindspore.ops.searchsorted
     mindspore.ops.topk
 
 线性代数函数

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

@@ -0,0 +1,21 @@
+mindspore.ops.searchsorted
+==========================
+
+.. py:function:: mindspore.ops.searchsorted(sorted_sequence, values, *, out_int32=False, right=False)
+
+    返回位置索引，根据这个索引将`values` 插入 `sorted_sequence`后，`sorted_sequence` 的最内维度的顺序保持不变。
+
+    参数：
+        - **sorted_sequence** (Tensor) - Tensor的形状为：math:`(x_1，x_2，…，x_R-1，x_R)` 或 `x_1`。在最里面的维度上必须包含单调递增的序列。
+        - **values** (Tensor) - 要插入元素的值。Tensor的形状为：math:`(x_1，x_2，…，x_R-1，x_S)`。
+
+    关键字参数：
+        - **out_int32** (bool, 可选) - 输出数据类型。如果为True，则输出数据类型将为int32；如果为False，则输出数据类型将为int64。默认值：False。
+        - **right** (bool, 可选) - 搜索策略。如果为True，则返回找到的最后一个合适的索引；如果为False，则返回第一个合适的索引。默认值：False。
+
+    返回：
+        表示`sorted_sequence`最内维度的索引的Tensor，如果插入`values` tensor中相应的值，则`sorted_sequence` tensor的顺序将被保留，如果out_int32为True，
+        则返回的数据类型为int32，否则为int64，并且形状与values的形状相同。
+
+    异常：
+        - **ValueError** - 如果 `sorted_sequence` 的维度不是1，并且除 `sorted_sequence` 和 `values` 的最后一个维度之外的维度不同。

docs/api/api_python_en/mindspore.ops.rst

@@ -344,9 +344,10 @@ Comparison Functions
     mindspore.ops.lt
     mindspore.ops.maximum
     mindspore.ops.minimum
+    mindspore.ops.msort
     mindspore.ops.ne
     mindspore.ops.not_equal
-    mindspore.ops.msort
+    mindspore.ops.searchsorted
     mindspore.ops.topk
 
 Linear Algebraic Functions

mindspore/python/mindspore/ops/function/__init__.py

@@ -150,7 +150,8 @@ from .array_func import (
     column_stack,
     hstack,
     movedim,
-    moveaxis
+    moveaxis,
+    searchsorted
 )
 from .parameter_func import (
     assign,

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

@@ -1219,23 +1219,25 @@ def unique_consecutive(x, return_idx=False, return_counts=False, axis=None):
 
 def searchsorted(sorted_sequence, values, *, out_int32=False, right=False):
     """
-    Find the indices from the innermost dimension of `sorted_sequence` such that the order of the innermost dimension
-    within `sorted_sequence` would be preserved when the corresponding values in `values` were inserted before the
-    indices.
+    Return the position indices such that after inserting the values into the `sorted_sequence`, the order of innermost
+    dimension of the `sorted_sequence` remains unchanged.
 
     Args:
         sorted_sequence (Tensor): The shape of tensor is :math:`(x_1, x_2, ..., x_R-1, x_R)` or `(x_1)`.
             It must contain a monotonically increasing sequence on the innermost dimension.
-        values (Tensor): The shape of tensor is :math:`(x_1, x_2, ..., x_R-1, x_S)`.
+        values (Tensor): The value that should be inserted.
+            The shape of tensor is :math:`(x_1, x_2, ..., x_R-1, x_S)`.
+
+    Keyword Args:
         out_int32 (bool, optional): Output datatype. If True, the output datatype will be int32;
             if False, the output datatype will be int64. Default: False.
         right (bool, optional): Search Strategy. If True, return the last suitable index found;
             if False, return the first such index. Default: False.
 
     Returns:
-        Tensor containing the indices from the innermost dimension of the input sequence such that,
-        if insert the corresponding value in the values tensor, the order of the tensor sequence would be preserved,
-        whose datatype is int32 if out_int32 is True, otherwise int64, and shape is the same as the shape of values.
+        Tensor containing the indices from the innermost dimension of `sorted_sequence` such that,
+        if insert the corresponding value in the `values` tensor, the order of `sorted_sequence` would be preserved,
+        whose datatype is int32 if out_int32 is True, otherwise int64, and shape is the same as the shape of `values`.
 
     Raises:
         ValueError: If the dimension of `sorted_sequence` isn't 1 and all dimensions except the last dimension of
@@ -1247,7 +1249,7 @@ def searchsorted(sorted_sequence, values, *, out_int32=False, right=False):
     Examples:
         >>> sorted_sequence = Tensor(np.array([[0, 1, 3, 5, 7], [2, 4, 6, 8, 10]]), mindspore.float32)
         >>> values = Tensor(np.array([[3, 6, 9], [3, 6, 9]]), mindspore.float32)
-        >>> output = ops.SearchSorted()(sorted_sequence, values)
+        >>> output = ops.searchsorted(sorted_sequence, values)
         >>> print(output)
         [[2 4 5]
          [1 2 4]]
@@ -6715,6 +6717,7 @@ __all__ = [
     'mvlgamma',
     'swapaxes',
     'swapdims',
+    'searchsorted',
     'argsort',
     'sequence_mask',
     'repeat_elements',