diff --git a/paddle/operators/edit_distance_op.cu b/paddle/operators/edit_distance_op.cu
index c165bbae7fcf9cc5b79f3eb5a4d5b346adbd8274..338fd79bcc125b86c7764645c2fd8953d4477d2a 100644
--- a/paddle/operators/edit_distance_op.cu
+++ b/paddle/operators/edit_distance_op.cu
@@ -39,8 +39,8 @@ __global__ void FillFirstColumn(T* dist, const int M, const int N) {
 }
 
 template <typename T>
-__global__ void Levenshtein(T* dist, const int* x1, const int* x2, const int M,
-                            const int N, const int start) {
+__global__ void Levenshtein(T* dist, const int64_t* x1, const int64_t* x2,
+                            const int M, const int N, const int start) {
   int idx = blockDim.x * blockIdx.x + threadIdx.x;
   int offset = N;
   int index = start + idx * offset;
diff --git a/python/paddle/v2/fluid/tests/test_edit_distance_op.py b/python/paddle/v2/fluid/tests/test_edit_distance_op.py
index cf118df634bb8288456009ebd4954f08d5eb4323..5f5634e2979431fccc390d9c1bbf201c4f2d93c9 100644
--- a/python/paddle/v2/fluid/tests/test_edit_distance_op.py
+++ b/python/paddle/v2/fluid/tests/test_edit_distance_op.py
@@ -51,8 +51,8 @@ class TestEditDistanceOp(OpTest):
     def setUp(self):
         self.op_type = "edit_distance"
         normalized = False
-        x1 = np.array([[0, 12, 3, 5, 8, 2]]).astype("int32")
-        x2 = np.array([[0, 12, 4, 7, 8]]).astype("int32")
+        x1 = np.array([[0, 12, 3, 5, 8, 2]]).astype("int64")
+        x2 = np.array([[0, 12, 4, 7, 8]]).astype("int64")
         x1 = np.transpose(x1)
         x2 = np.transpose(x2)
         x1_lod = [0, 1, 5]
@@ -79,8 +79,8 @@ class TestEditDistanceOpNormalized(OpTest):
     def setUp(self):
         self.op_type = "edit_distance"
         normalized = True
-        x1 = np.array([[0, 10, 3, 6, 5, 8, 2]]).astype("int32")
-        x2 = np.array([[0, 10, 4, 6, 7, 8]]).astype("int32")
+        x1 = np.array([[0, 10, 3, 6, 5, 8, 2]]).astype("int64")
+        x2 = np.array([[0, 10, 4, 6, 7, 8]]).astype("int64")
         x1 = np.transpose(x1)
         x2 = np.transpose(x2)
         x1_lod = [0, 1, 3, 6]