diff --git a/mindspore/ops/composite/math_ops.py b/mindspore/ops/composite/math_ops.py
index c9f1406880..774f86d6cc 100644
--- a/mindspore/ops/composite/math_ops.py
+++ b/mindspore/ops/composite/math_ops.py
@@ -279,6 +279,17 @@ def _check_invalid_input(x1_shape, x2_shape):
                          + f'while x1 is ({len(x1_shape)}) and x2 is ({len(x2_shape)}).')
 
 
+@constexpr
+def _typecheck_input_dot(x1_type, x2_type):
+    """
+    Check input tensor types to be valid and confirm they are the same type for dot and batch dot ops.
+    """
+    const_utils.check_type_valid(x1_type, [mstype.float16, mstype.float32], 'x1')
+    const_utils.check_type_valid(x2_type, [mstype.float16, mstype.float32], 'x2')
+    if x1_type != x2_type:
+        raise TypeError(f'Both Inputs must be the same Type. x1 is \'{x1_type}\' and x2 is \'{x2_type}\' ')
+
+
 @constexpr
 def _get_transpose_shape(x2_shape):
     x2_shape_range = tuple(range(len(x2_shape)))
@@ -297,6 +308,11 @@ def dot(x1, x2):
     Outputs:
         Tensor, dot product of x1 and x2.
 
+    Raises:
+        TypeError: If type of x1 and x2 are not the same.
+        TpyeError: If dtype of x1 or x2 is not float16 or float32.
+        ValueError: If rank of x1 or x2 less than 2.
+
     Supported Platforms:
         ``Ascend`` ``GPU`` ``CPU``
 
@@ -314,6 +330,9 @@ def dot(x1, x2):
     matmul_op = P.MatMul(False, False)
     x1_shape = shape_op(x1)
     x2_shape = shape_op(x2)
+    x1_type = F.dtype(x1)
+    x2_type = F.dtype(x2)
+    _typecheck_input_dot(x1_type, x2_type)
     _check_invalid_input(x1_shape, x2_shape)
 
     if len(x1_shape) > 2 or len(x2_shape) > 2: