diff --git a/tensorflow/compiler/tf2xla/kernels/scan_ops.cc b/tensorflow/compiler/tf2xla/kernels/scan_ops.cc
index 8431724f438..beb8e7aa174 100644
--- a/tensorflow/compiler/tf2xla/kernels/scan_ops.cc
+++ b/tensorflow/compiler/tf2xla/kernels/scan_ops.cc
@@ -36,10 +36,8 @@ limitations under the License.
 namespace tensorflow {
 namespace {
 
-// TODO(phawkins): implement double-sized windowed reductions in XLA and remove
-// the type constraint.
-constexpr std::array<DataType, 4> kScanOpTypes = {
-    {DT_HALF, DT_BFLOAT16, DT_FLOAT, DT_INT32}};
+constexpr std::array<DataType, 5> kScanOpTypes = {
+    {DT_HALF, DT_BFLOAT16, DT_FLOAT, DT_DOUBLE, DT_INT32}};
 
 class ScanOp : public XlaOpKernel {
  public:
diff --git a/tensorflow/python/eager/def_function_xla_jit_test.py b/tensorflow/python/eager/def_function_xla_jit_test.py
index 0e89887647a..5fdf0487333 100644
--- a/tensorflow/python/eager/def_function_xla_jit_test.py
+++ b/tensorflow/python/eager/def_function_xla_jit_test.py
@@ -355,6 +355,15 @@ class DefFunctionTest(test.TestCase):
     self.assertAllClose([5.0, 5.0, 5.0], g())
     self.assertAllClose(compiled_g(), g())
 
+  def testCumsum(self):
+
+    @def_function.function(experimental_compile=True)
+    def f(x):
+      return math_ops.cumsum(x)
+
+    f64_input = constant_op.constant([1.1, 2.2, 3.3], dtype=dtypes.float64)
+    self.assertAllClose([1.1, 3.3, 6.6], f(f64_input))
+
 
 if __name__ == '__main__':
   ops.enable_eager_execution()