diff --git a/mindspore/ops/composite/math_ops.py b/mindspore/ops/composite/math_ops.py
index d6f197b3a2..c9f1406880 100644
--- a/mindspore/ops/composite/math_ops.py
+++ b/mindspore/ops/composite/math_ops.py
@@ -372,6 +372,8 @@ def _check_axes_for_batch_dot(x1_shape, x2_shape, axes):
             axes[0] += len(x1_shape)
         if axes[1] < 0:
             axes[1] += len(x2_shape)
+        validator.check_non_negative_int(axes[0], 'reversed axes[0]', 'batch_dot')
+        validator.check_non_negative_int(axes[1], 'reversed axes[1]', 'batch_dot')
         if axes[0] > len(x1_shape) or axes[1] > len(x2_shape):
             raise ValueError(
                 "Axes value too high for given input arrays dimensions.")
@@ -380,6 +382,7 @@ def _check_axes_for_batch_dot(x1_shape, x2_shape, axes):
             raise ValueError("Batch dim cannot be used as in axes.")
         if axes < 0:
             axes = [axes + len(x1_shape), axes + len(x2_shape)]
+            validator.check_non_negative_int(axes[0], 'reversed axes', 'batch_dot')
         elif axes > len(x1_shape) or axes > len(x2_shape):
             raise ValueError(
                 "Axes value too high for given input arrays dimensions.")
@@ -448,11 +451,12 @@ def batch_dot(x1, x2, axes=None):
 
     Raises:
         TypeError: If type of x1 and x2 are not the same.
+        TpyeError: If dtype of x1 or x2 is not float32.
         ValueError: If rank of x1 or x2 less than 2.
         ValueError: If batch dim used in axes.
-        ValueError: If dtype of x1 or x2 is not float32.
         ValueError: If len(axes) less than 2.
         ValueError: If axes is not one of those: None, int, (int, int).
+        ValueError: If axes reversed from negative int is too low for dimensions of input arrays.
         ValueError: If axes value is too high for dimensions of input arrays.
         ValueError: If batch size of x1 and x2 are not the same.