!13202 Update documentation for TensorScatterUpdate

From: @peilin-wang
Reviewed-by: @liangchenghui,@wuxuejian
Signed-off-by: @liangchenghui

mindspore/ops/operations/array_ops.py

@@ -3372,11 +3372,25 @@ class GatherNd(PrimitiveWithInfer):
 
 class TensorScatterUpdate(PrimitiveWithInfer):
     """
-    Updates tensor values using given values, along with the input indices.
+    Creates a new tensor by updating the positions in `input_x` indicicated by
+    `indices`, with values from `update`. This operation is almost equivalent to using
+    ScatterNd, except that the updates are applied on `input_x` instead of a zero tensor.
+
+    `indices` must have rank atleast 2, the last axis is the depth of each index
+    vectors. For each index vector, there must be a corresponding value in `update`. If
+    the depth of each index tensor matches the rank of `input_x`, then each index
+    vector corresponds to a scalar in `input_x` and each update updates a scalar. If
+    the depth of each index tensor is less than the rnak of `input_x`, then each index
+    vector corresponds to a slice in `input_x`, and each update updates a slice.
+    
+    The order in which updates are applied is nondeterministic, meaning that if there
+    are multiple index vectors in `indices` that correspond to the same position, the
+    value of that position in the output will be nondeterministic.
 
     Inputs:
         - **input_x** (Tensor) - The target tensor. The dimension of input_x must be no less than indices.shape[-1].
         - **indices** (Tensor) - The index of input tensor whose data type is int32 or int64.
+          The rank must be atleast 2.
         - **update** (Tensor) - The tensor to update the input tensor, has the same type as input,
           and update.shape = indices.shape[:-1] + input_x.shape[indices.shape[-1]:].
 
@@ -3388,7 +3402,7 @@ class TensorScatterUpdate(PrimitiveWithInfer):
         ValueError: If length of shape of `input_x` is less than the last dimension of shape of `indices`.
 
     Supported Platforms:
-        ``Ascend``
+        ``Ascend`` ``GPU``
 
     Examples:
         >>> input_x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]), mindspore.float32)