fixed MatrixSetDiag

mindspore/ops/operations/_inner_ops.py

@@ -616,7 +616,7 @@ class MatrixDiagPart(PrimitiveWithInfer):
         Tensor, data type same as input `x`. The shape should be x.shape[:-2] + [min(x.shape[-2:])].
 
     Examples:
-        >>> x = Tensor([[[-1, 0], [0, 1]], [-1, 0], [0, 1]], [[-1, 0], [0, 1]]], mindspore.float32)
+        >>> x = Tensor([[[-1, 0], [0, 1]], [[-1, 0], [0, 1]], [[-1, 0], [0, 1]]], mindspore.float32)
         >>> assist = Tensor(np.arange(-12, 0).reshape(3, 2, 2), mindspore.float32)
         >>> matrix_diag_part = P.MatrixDiagPart()
         >>> result = matrix_diag_part(x, assist)
@@ -658,11 +658,11 @@ class MatrixSetDiag(PrimitiveWithInfer):
         Tensor, data type same as input `x`. The shape same as `x`.
 
     Examples:
-        >>> x = Tensor([[[-1, 0], [0, 1]], [-1, 0], [0, 1]], [[-1, 0], [0, 1]]], mindspore.float32)
+        >>> x = Tensor([[[-1, 0], [0, 1]], [[-1, 0], [0, 1]], [[-1, 0], [0, 1]]], mindspore.float32)
         >>> diagonal = Tensor([[-1., 2.], [-1., 1.], [-1., 1.]], mindspore.float32)
         >>> matrix_set_diag = P.MatrixSetDiag()
         >>> result = matrix_set_diag(x, diagonal)
-        [[[-1, 0], [0, 2]], [-1, 0], [0, 1]], [[-1, 0], [0, 1]]]
+        [[[-1, 0], [0, 2]], [[-1, 0], [0, 1]], [[-1, 0], [0, 1]]]
 
     """
 
@@ -681,10 +681,10 @@ class MatrixSetDiag(PrimitiveWithInfer):
         validator.check("x shape", x_shape, "assist shape", assist_shape, Rel.EQ, self.name)
 
         if x_shape[-2] < x_shape[-1]:
-            validator.check("x shape excluding the last dimension", x_shape[:-1], "diagnoal shape",
-                            diagonal_shape, Rel.EQ, self.name)
+            validator.check("diagnoal shape", diagonal_shape, "x shape excluding the last dimension",
+                            x_shape[:-1], Rel.EQ, self.name)
         else:
-            validator.check("x shape excluding the second to last dimension", x_shape[:-2]+x_shape[-1:],
-                            "diagonal shape", diagonal_shape, Rel.EQ, self.name)
+            validator.check("diagonal shape", diagonal_shape, "x shape excluding the second last dimension",
+                            x_shape[:-2] + x_shape[-1:], Rel.EQ, self.name)
 
         return assist_shape

mindspore/ops/operations/nn_ops.py

@@ -1851,7 +1851,7 @@ class ApplyRMSProp(PrimitiveWithInfer):
         >>> decay = 0.0
         >>> momentum = 1e-10
         >>> epsilon = 0.001
-        >>> result = apply_rms(input_x, mean_square, moment, grad, learning_rate, decay, momentum, epsilon)
+        >>> result = apply_rms(input_x, mean_square, moment, learning_rate, grad, decay, momentum, epsilon)
         (-2.9977674, 0.80999994, 1.9987665)
     """