diff --git a/mindspore/common/tensor.py b/mindspore/common/tensor.py
index 9f8de3f49d..5115ea1ff5 100644
--- a/mindspore/common/tensor.py
+++ b/mindspore/common/tensor.py
@@ -176,6 +176,8 @@ class Tensor(Tensor_):
         return out
 
     def __getitem__(self, index):
+        if isinstance(index, int) and index >= self.shape[0]:
+            raise IndexError("index {} is out of bounds for axis 0 with size {}".format(index, self.shape[0]))
         out = tensor_operator_registry.get('__getitem__')(self, index)
         return out
 
@@ -319,7 +321,7 @@ class Tensor(Tensor_):
 
         Args:
             shape (Tensor): The input tensor. The shape of input tensor must obey
-            the broadcasting rule.
+                the broadcasting rule.
 
         Returns:
             Tensor, has the same dimension as input tensor.
diff --git a/mindspore/nn/layer/basic.py b/mindspore/nn/layer/basic.py
index f660ce67ab..51b21fcc8f 100644
--- a/mindspore/nn/layer/basic.py
+++ b/mindspore/nn/layer/basic.py
@@ -725,7 +725,7 @@ class Tril(Cell):
 
     def construct(self, x, k=0):
         assist = tril(x.shape, self.dtype(x), k)
-        result = self.mul(self.cast(x, mstype.int32), self.cast(assist, mstype.int32))
+        result = self.mul(self.cast(x, mstype.float32), self.cast(assist, mstype.float32))
         return self.cast(result, self.dtype(x))
 
 
@@ -767,7 +767,7 @@ class Triu(Cell):
 
     def construct(self, x, k=0):
         assist = triu(x.shape, self.dtype(x), k)
-        result = self.mul(self.cast(x, mstype.int32), self.cast(assist, mstype.int32))
+        result = self.mul(self.cast(x, mstype.float32), self.cast(assist, mstype.float32))
         return self.cast(result, self.dtype(x))