Add input check for axes which is float type or out of bound

mindspore/ops/composite/math_ops.py

@@ -365,14 +365,16 @@ def _check_axes_for_batch_dot(x1_shape, x2_shape, axes):
             raise ValueError("Require two axes inputs, given less")
         if isinstance(axes, tuple):
             axes = list(axes)
-        for sub_axes in axes:
-            if isinstance(sub_axes, (list, tuple)):
-                raise ValueError("Require dimension to be in any of those: None, int, (int, int).")
+        validator.check_value_type('axes[0]', axes[0], [int], 'batch_dot')
+        validator.check_value_type('axes[1]', axes[1], [int], 'batch_dot')
         # Reverse if axis < 0
         if axes[0] < 0:
             axes[0] += len(x1_shape)
         if axes[1] < 0:
             axes[1] += len(x2_shape)
+        if axes[0] > len(x1_shape) or axes[1] > len(x2_shape):
+            raise ValueError(
+                "Axes value too high for given input arrays dimensions.")
     elif isinstance(axes, int):
         if axes == 0:
             raise ValueError("Batch dim cannot be used as in axes.")
@@ -429,6 +431,9 @@ def batch_dot(x1, x2, axes=None):
     """
     Computation of batch dot product between samples in two tensors containing batch dims.
 
+    .. math::
+        output = x1[batch, :] * x2[batch, :]
+
     Inputs:
         - **x1** (Tensor) - First tensor in Batch Dot op with datatype float32
         - **x2** (Tensor) - Second tensor in Batch Dot op with datatype float32. x2's datatype should
@@ -439,13 +444,10 @@ def batch_dot(x1, x2, axes=None):
 
     Outputs:
         Tensor, batch dot product of x1 and x2. The Shape of output for input shapes (batch, d1, axes, d2) and
-          (batch, d3, axes, d4) is (batch, d1, d2, d3, d4)
-
-    .. math::
-        output = x1[batch, :] * x2[batch, :]
+        (batch, d3, axes, d4) is (batch, d1, d2, d3, d4)
 
     Raises:
-        TypeError: If shapes of x1 and x2 are not the same.
+        TypeError: If type of x1 and x2 are not the same.
         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.