From 639a085d93fa2b9849476bf6b548cdcc6b4c3c1f Mon Sep 17 00:00:00 2001
From: lihongkang <[lihongkang1@huawei.com]>
Date: Wed, 21 Oct 2020 17:19:15 +0800
Subject: [PATCH] fix bugs

---
 mindspore/ops/operations/array_ops.py | 2 ++
 mindspore/ops/operations/math_ops.py  | 1 +
 mindspore/ops/operations/nn_ops.py    | 1 +
 3 files changed, 4 insertions(+)

diff --git a/mindspore/ops/operations/array_ops.py b/mindspore/ops/operations/array_ops.py
index 24c3784afa..51cd96c1b8 100644
--- a/mindspore/ops/operations/array_ops.py
+++ b/mindspore/ops/operations/array_ops.py
@@ -826,6 +826,7 @@ class Rank(PrimitiveWithInfer):
         >>> input_tensor = Tensor(np.array([[2, 2], [2, 2]]), mindspore.float32)
         >>> rank = P.Rank()
         >>> rank(input_tensor)
+        2
     """
 
     @prim_attr_register
@@ -896,6 +897,7 @@ class Size(PrimitiveWithInfer):
         >>> input_tensor = Tensor(np.array([[2, 2], [2, 2]]), mindspore.float32)
         >>> size = P.Size()
         >>> output = size(input_tensor)
+        4
     """
 
     @prim_attr_register
diff --git a/mindspore/ops/operations/math_ops.py b/mindspore/ops/operations/math_ops.py
index e294bb92e4..3e123c6a7d 100644
--- a/mindspore/ops/operations/math_ops.py
+++ b/mindspore/ops/operations/math_ops.py
@@ -2938,6 +2938,7 @@ class Sin(PrimitiveWithInfer):
         >>> sin = P.Sin()
         >>> input_x = Tensor(np.array([0.62, 0.28, 0.43, 0.62]), mindspore.float32)
         >>> output = sin(input_x)
+        [0.5810352 0.27635565 0.41687083 0.5810352]
     """
 
     @prim_attr_register
diff --git a/mindspore/ops/operations/nn_ops.py b/mindspore/ops/operations/nn_ops.py
index 5bd8e0edca..cdcf3da1f2 100644
--- a/mindspore/ops/operations/nn_ops.py
+++ b/mindspore/ops/operations/nn_ops.py
@@ -1761,6 +1761,7 @@ class SparseSoftmaxCrossEntropyWithLogits(PrimitiveWithInfer):
 
     @prim_attr_register
     def __init__(self, is_grad=False):
+        validator.check_value_type('is_grad', is_grad, [bool], self.name)
         self.init_prim_io_names(inputs=['features', 'labels'], outputs=['output'])
         self.is_grad = is_grad
         self.add_prim_attr('sens', 1.0)