diff --git a/tensorflow/python/data/experimental/kernel_tests/BUILD b/tensorflow/python/data/experimental/kernel_tests/BUILD
index dfdcc54411c..1733b9817b3 100644
--- a/tensorflow/python/data/experimental/kernel_tests/BUILD
+++ b/tensorflow/python/data/experimental/kernel_tests/BUILD
@@ -322,6 +322,8 @@ py_test(
         "//tensorflow/python:functional_ops",
         "//tensorflow/python:math_ops",
         "//tensorflow/python:session",
+        "//tensorflow/python:sparse_ops",
+        "//tensorflow/python:sparse_tensor",
         "//tensorflow/python/data/experimental/ops:map_defun",
         "//tensorflow/python/data/kernel_tests:test_base",
     ],
diff --git a/tensorflow/python/data/experimental/kernel_tests/map_defun_op_test.py b/tensorflow/python/data/experimental/kernel_tests/map_defun_op_test.py
index a48f0808a6a..4e99189279c 100644
--- a/tensorflow/python/data/experimental/kernel_tests/map_defun_op_test.py
+++ b/tensorflow/python/data/experimental/kernel_tests/map_defun_op_test.py
@@ -27,12 +27,14 @@ from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import errors
 from tensorflow.python.framework import ops
+from tensorflow.python.framework import sparse_tensor
 from tensorflow.python.framework import tensor_spec
 from tensorflow.python.framework import test_util
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import check_ops
 from tensorflow.python.ops import data_flow_ops
 from tensorflow.python.ops import math_ops
+from tensorflow.python.ops import sparse_ops
 from tensorflow.python.platform import test
 
 
@@ -254,6 +256,70 @@ class MapDefunTest(test_base.DatasetTestBase):
     expected = x + c
     self.assertAllEqual(self.evaluate(expected), self.evaluate(map_defun_op))
 
+  def testMapDefunWithVariantTensor(self):
+
+    @function.defun(
+        input_signature=[tensor_spec.TensorSpec([], dtypes.variant)])
+    def fn(x):
+      return x
+
+    st = sparse_tensor.SparseTensor(
+        indices=[[0, 0], [1, 2]], values=[1, 2], dense_shape=[3, 4])
+
+    serialized = sparse_ops.serialize_sparse_v2(st, out_type=dtypes.variant)
+    serialized = array_ops.stack([serialized, serialized])
+    map_defun_op = map_defun.map_defun(fn, [serialized], [dtypes.variant],
+                                       [None])[0]
+    deserialized = sparse_ops.deserialize_sparse(map_defun_op, dtypes.int32)
+    expected = sparse_tensor.SparseTensorValue(
+        indices=[[0, 0, 0], [0, 1, 2], [1, 0, 0], [1, 1, 2]],
+        values=[1, 2, 1, 2],
+        dense_shape=[2, 3, 4])
+    actual = self.evaluate(deserialized)
+    self.assertSparseValuesEqual(expected, actual)
+
+  def testMapDefunWithVariantTensorAsCaptured(self):
+
+    st = sparse_tensor.SparseTensor(
+        indices=[[0, 0], [1, 2]], values=[1, 2], dense_shape=[3, 4])
+    serialized = sparse_ops.serialize_sparse_v2(st, out_type=dtypes.variant)
+
+    @function.defun(input_signature=[tensor_spec.TensorSpec([], dtypes.int32)])
+    def fn(x):
+      del x
+      return serialized
+
+    x = constant_op.constant([0, 0])
+    map_defun_op = map_defun.map_defun(fn, [x], [dtypes.variant], [None])[0]
+    deserialized = sparse_ops.deserialize_sparse(map_defun_op, dtypes.int32)
+    expected = sparse_tensor.SparseTensorValue(
+        indices=[[0, 0, 0], [0, 1, 2], [1, 0, 0], [1, 1, 2]],
+        values=[1, 2, 1, 2],
+        dense_shape=[2, 3, 4])
+    actual = self.evaluate(deserialized)
+    self.assertSparseValuesEqual(expected, actual)
+
+  def testMapDefunWithStrTensor(self):
+
+    @function.defun(input_signature=[tensor_spec.TensorSpec([], dtypes.string)])
+    def fn(x):
+      return x
+
+    st = sparse_tensor.SparseTensor(
+        indices=[[0, 0], [1, 2]], values=[1, 2], dense_shape=[3, 4])
+
+    serialized = sparse_ops.serialize_sparse_v2(st, out_type=dtypes.string)
+    serialized = array_ops.stack([serialized, serialized])
+    map_defun_op = map_defun.map_defun(fn, [serialized], [dtypes.string],
+                                       [None])[0]
+    deserialized = sparse_ops.deserialize_sparse(map_defun_op, dtypes.int32)
+    expected = sparse_tensor.SparseTensorValue(
+        indices=[[0, 0, 0], [0, 1, 2], [1, 0, 0], [1, 1, 2]],
+        values=[1, 2, 1, 2],
+        dense_shape=[2, 3, 4])
+    actual = self.evaluate(deserialized)
+    self.assertSparseValuesEqual(expected, actual)
+
 
 if __name__ == "__main__":
   test.main()