!13845 Update API documentation of MatrixDiag, ScatterND and NMSWithMask

From: @yuyiyang_3418
Reviewed-by: @liangchenghui,@wuxuejian
Signed-off-by: @liangchenghui

mindspore/nn/layer/basic.py

@@ -935,7 +935,7 @@ class MatrixDiag(Cell):
         ``Ascend``
 
     Examples:
-        >>> x = Tensor(np.array([1, -1]), mstype.float32)
+        >>> x = Tensor(np.array([1, -1]), mindspore.float32)
         >>> matrix_diag = nn.MatrixDiag()
         >>> output = matrix_diag(x)
         >>> print(output)

mindspore/ops/operations/array_ops.py

@@ -3558,15 +3558,25 @@ class ScatterNdUpdate(_ScatterNdOp):
         ``Ascend`` ``CPU``
 
     Examples:
-        >>> np_x = np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]])
-        >>> input_x = mindspore.Parameter(Tensor(np_x, mindspore.float32), name="x")
-        >>> indices = Tensor(np.array([[0, 0], [1, 1]]), mindspore.int32)
-        >>> updates = Tensor(np.array([1.0, 2.2]), mindspore.float32)
-        >>> op = ops.ScatterNdUpdate()
-        >>> output = op(input_x, indices, updates)
+        >>> # Example 1: Scatter [9, 0, 7, 3] by indices [3, 4, 1, 8] in a 1-D tensor
+        >>> op = ops.ScatterNd()
+        >>> indices = Tensor(np.array([3, 4, 1, 8]), mindspore.int32)
+        >>> updates = Tensor(np.array([8, 9, 7, 3]), mindspore.int32)
+        >>> shape = (10, )
+        >>> output = op(indices, updates, shape)
         >>> print(output)
-        [[ 1.   0.3  3.6]
-         [ 0.4  2.2 -3.2]]
+        [0 7 0 8 9 0 0 0 3 0]
+
+        >>> # Example 2: Scatter [3.2, 1.1] by indices [[0, 1], [1, 1]] in a 2-D tensor
+        >>> op = ops.ScatterNd()
+        >>> indices = Tensor(np.array([[0, 1], [1, 1]]), mindspore.int32)
+        >>> updates = Tensor(np.array([3.2, 1.1]), mindspore.float32)
+        >>> shape = (3, 3)
+        >>> output = op(indices, updates, shape)
+        >>> print(output)
+        [[0.  3.2 0. ]
+         [0.  1.1 0. ]
+         [0.  0.  0. ]]
     """
 
     @prim_attr_register

mindspore/ops/operations/math_ops.py

@@ -3791,15 +3791,16 @@ class NMSWithMask(PrimitiveWithInfer):
         ``Ascend`` ``GPU``
 
     Examples:
-        >>> bbox = np.array([[0.4, 0.2, 0.4, 0.3, 0.1], [0.4, 0.3, 0.6, 0.8, 0.7]])
+        >>> bbox = np.array([[100.0, 100.0, 50.0, 68.0, 0.63], [150.0, 75.0, 165.0, 115.0, 0.55],
+        [12.0, 190.0, 288.0, 200.0, 0.9], [28.0, 130.0, 106.0, 172.0, 0.3]])
         >>> bbox[:, 2] += bbox[:, 0]
         >>> bbox[:, 3] += bbox[:, 1]
         >>> inputs = Tensor(bbox, mindspore.float32)
-        >>> nms = ops.NMSWithMask(0.5)
+        >>> nms = ops.NMSWithMask(0.1)
         >>> output_boxes, indices, mask = nms(inputs)
         >>> indices_np = indices.asnumpy()
         >>> print(indices_np[mask.asnumpy()])
-        [0 1]
+        [0 1 2]
     """
 
     @prim_attr_register