diff --git a/mindspore/nn/layer/math.py b/mindspore/nn/layer/math.py
index e5f942110d..723ec6b6ee 100644
--- a/mindspore/nn/layer/math.py
+++ b/mindspore/nn/layer/math.py
@@ -945,7 +945,7 @@ class Moments(Cell):
         self.squeeze = P.Squeeze(self.axis)
 
     def construct(self, x):
-        tensor_dtype = x.dtype
+        tensor_dtype = F.dtype(x)
         _check_input_dtype("input x", tensor_dtype, [mstype.float16, mstype.float32], self.cls_name)
         if tensor_dtype == mstype.float16:
             x = self.cast(x, mstype.float32)
diff --git a/mindspore/ops/composite/clip_ops.py b/mindspore/ops/composite/clip_ops.py
index 7836e23599..14fa798456 100644
--- a/mindspore/ops/composite/clip_ops.py
+++ b/mindspore/ops/composite/clip_ops.py
@@ -25,6 +25,12 @@ from mindspore._checkparam import Validator as validator
 from mindspore.ops.primitive import constexpr
 
 
+@constexpr
+def _check_shape(input_shape, out_shape):
+    if input_shape != out_shape:
+        raise ValueError("Cannot broadcast the shape of x to the shape of clip_value_min or clip_value_max.")
+
+
 def clip_by_value(x, clip_value_min, clip_value_max):
     """
     Clips tensor values to a specified min and max.
@@ -63,6 +69,7 @@ def clip_by_value(x, clip_value_min, clip_value_max):
     max_op = P.Maximum()
     x_min = min_op(x, clip_value_max)
     x_max = max_op(x_min, clip_value_min)
+    _check_shape(F.shape(x), F.shape(x_max))
     return x_max