diff --git a/paddle/fluid/operators/hash_op.cc b/paddle/fluid/operators/hash_op.cc
index 6679c109b15a7db7ba9c54e3af21875dd06fc68b..5ef91dcb66638d5786e9769802bfc3790ffc6079 100644
--- a/paddle/fluid/operators/hash_op.cc
+++ b/paddle/fluid/operators/hash_op.cc
@@ -52,7 +52,7 @@ class HashOpMaker : public framework::OpProtoAndCheckerMaker {
         Execute `num_hash` times xxHash algorithm on all elements on second dimension of input. 
 )DOC");
     AddAttr<int>("num_hash", "").SetDefault(1);
-    AddAttr<int>("mod_by", "").SetDefault(100000);
+    AddAttr<int64_t>("mod_by", "").SetDefault(100000);
     AddAttr<bool>(framework::kAllKernelsMustComputeRuntimeShape,
                   "Skip calling InferShape() function in the runtime.")
         .SetDefault(true);
diff --git a/paddle/fluid/operators/hash_op.h b/paddle/fluid/operators/hash_op.h
index 14a4660aac738563232d8bdede4007f8825c5b9a..c2d530004912287b0720ab5d00da90c4e1b5cbc7 100644
--- a/paddle/fluid/operators/hash_op.h
+++ b/paddle/fluid/operators/hash_op.h
@@ -43,7 +43,7 @@ class HashKernel : public framework::OpKernel<T> {
   virtual void Compute(const framework::ExecutionContext& context) const {
     auto* out_t = context.Output<framework::LoDTensor>("Out");
     auto* in_t = context.Input<framework::LoDTensor>("X");
-    int mod_by = context.Attr<int>("mod_by");
+    int64_t mod_by = context.Attr<int64_t>("mod_by");
     int num_hash = context.Attr<int>("num_hash");
 
     auto in_dims = in_t->dims();
@@ -59,7 +59,7 @@ class HashKernel : public framework::OpKernel<T> {
     for (int idx = 0; idx < seq_length; ++idx) {
       for (int ihash = 0; ihash != num_hash; ++ihash) {
         output[idx * num_hash + ihash] =
-            XXH64(input, sizeof(int) * last_dim, ihash) % mod_by;
+            XXH64(input, sizeof(T) * last_dim, ihash) % mod_by;
       }
       input += last_dim;
     }
diff --git a/python/paddle/fluid/tests/unittests/test_hash_op.py b/python/paddle/fluid/tests/unittests/test_hash_op.py
index 7b4e9bf738b212059faf2e3046510497f820a723..75af02bd5f46ea61f0bf4bc2494cb941fb1f64b4 100644
--- a/python/paddle/fluid/tests/unittests/test_hash_op.py
+++ b/python/paddle/fluid/tests/unittests/test_hash_op.py
@@ -58,5 +58,49 @@ class TestHashNotLoDOp(TestHashOp):
         self.check_output()
 
 
+class TestHashOp2(TestHashOp):
+    """
+    Case:
+    int64 type input
+    """
+
+    def setUp(self):
+        self.op_type = "hash"
+        self.init_test_case()
+        self.inputs = {'X': self.in_seq}
+        self.attrs = {'num_hash': 2, 'mod_by': 10000}
+        self.outputs = {'Out': self.out_seq}
+
+    def init_test_case(self):
+        self.in_seq = np.array([1, 2**32 + 1]).reshape((2, 1)).astype("int64")
+        self.out_seq = np.array([1269, 9609, 3868, 7268]).reshape((2, 2, 1))
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestHashOp3(TestHashOp):
+    """
+    Case:
+    int64 type input
+    int64 type mod_by attr
+    """
+
+    def setUp(self):
+        self.op_type = "hash"
+        self.init_test_case()
+        self.inputs = {'X': self.in_seq}
+        self.attrs = {'num_hash': 2, 'mod_by': 2**32}
+        self.outputs = {'Out': self.out_seq}
+
+    def init_test_case(self):
+        self.in_seq = np.array([10, 5]).reshape((2, 1)).astype("int64")
+        self.out_seq = np.array(
+            [1204014882, 393011615, 3586283837, 2814821595]).reshape((2, 2, 1))
+
+    def test_check_output(self):
+        self.check_output()
+
+
 if __name__ == "__main__":
     unittest.main()