Correct the comments for `RandomChoiceWithMask` op.

mindspore/ops/operations/random_ops.py

@@ -25,20 +25,23 @@ class RandomChoiceWithMask(PrimitiveWithInfer):
     """
     Generates a random samply as index tensor with a mask tensor from a given tensor.
 
-    The input must be a tensor of rank >= 2, the first dimension specify the number of sample.
-    The index tensor and the mask tensor have the same and fixed shape. The index tensor denotes the index
-    of the nonzero sample, while the mask tensor denotes which element in the index tensor are valid.
+    The input must be a tensor of rank >= 1. If its rank >= 2, the first dimension specify the number of sample.
+    The index tensor and the mask tensor have the fixed shapes. The index tensor denotes the index of the nonzero
+    sample, while the mask tensor denotes which elements in the index tensor are valid.
 
     Args:
-        count (int): Number of items expected to get. Default: 256.
-        seed (int): Random seed.
-        seed2 (int): Random seed2.
+        count (int): Number of items expected to get and the number should be greater than 0. Default: 256.
+        seed (int): Random seed. Default: 0.
+        seed2 (int): Random seed2. Default: 0.
 
     Inputs:
-        - **input_x** (Tensor) - The input tensor.
+        - **input_x** (Tensor[bool]) - The input tensor.
 
     Outputs:
-        Tuple, two tensors, the first one is the index tensor and the other one is the mask tensor.
+        Two tensors, the first one is the index tensor and the other one is the mask tensor.
+
+        - **index** (Tensor) - The output has shape between 2-D and 5-D.
+        - **mask** (Tensor) - The output has shape 1-D.
 
     Examples:
         >>> rnd_choice_mask = RandomChoiceWithMask()