diff --git a/tensorflow/python/saved_model/BUILD b/tensorflow/python/saved_model/BUILD
index 10cf520f4e5..9c1cc090d7d 100644
--- a/tensorflow/python/saved_model/BUILD
+++ b/tensorflow/python/saved_model/BUILD
@@ -442,6 +442,7 @@ py_strict_library(
         ":loader",
         ":signature_serialization",
         "//tensorflow/python:array_ops",
+        "//tensorflow/python:composite_tensor",
         "//tensorflow/python:constant_op",
         "//tensorflow/python:dtypes",
         "//tensorflow/python:framework_ops",
@@ -449,6 +450,7 @@ py_strict_library(
         "//tensorflow/python:platform",
         "//tensorflow/python:saver",
         "//tensorflow/python:sparse_tensor",
+        "//tensorflow/python:util",
         "//tensorflow/python/eager:context",
         "//tensorflow/python/eager:lift_to_graph",
         "//tensorflow/python/eager:wrap_function",
diff --git a/tensorflow/python/saved_model/load_v1_in_v2.py b/tensorflow/python/saved_model/load_v1_in_v2.py
index add3b4e6320..a8627701bb8 100644
--- a/tensorflow/python/saved_model/load_v1_in_v2.py
+++ b/tensorflow/python/saved_model/load_v1_in_v2.py
@@ -23,6 +23,7 @@ import functools
 from tensorflow.python.eager import context
 from tensorflow.python.eager import lift_to_graph
 from tensorflow.python.eager import wrap_function
+from tensorflow.python.framework import composite_tensor
 from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import func_graph
@@ -36,6 +37,7 @@ from tensorflow.python.saved_model import signature_serialization
 from tensorflow.python.training import monitored_session
 from tensorflow.python.training import saver as tf_saver
 from tensorflow.python.training.tracking import tracking
+from tensorflow.python.util import nest
 
 
 class _Initializer(tracking.CapturableResource):
@@ -154,6 +156,11 @@ class _EagerSavedModelLoader(loader_impl.SavedModelLoader):
           dense_shape_name = "%s_dense_shape" % original_input_name
           input_names.extend([indices_name, values_name, dense_shape_name])
           input_tensors.extend([feed.indices, feed.values, feed.dense_shape])
+        elif isinstance(feed, composite_tensor.CompositeTensor):
+          component_tensors = nest.flatten(feed, expand_composites=True)
+          input_names.extend("%s_component_%d" % (original_input_name, n)
+                             for n in range(len(component_tensors)))
+          input_tensors.extend(component_tensors)
         else:
           input_names.append(original_input_name)
           input_tensors.append(feed)
diff --git a/tensorflow/python/saved_model/load_v1_in_v2_test.py b/tensorflow/python/saved_model/load_v1_in_v2_test.py
index 806a4db6fba..cab2c8bedb0 100644
--- a/tensorflow/python/saved_model/load_v1_in_v2_test.py
+++ b/tensorflow/python/saved_model/load_v1_in_v2_test.py
@@ -45,6 +45,7 @@ from tensorflow.python.ops import random_ops
 from tensorflow.python.ops import resource_variable_ops
 from tensorflow.python.ops import variable_scope
 from tensorflow.python.ops import variables
+from tensorflow.python.ops.ragged import ragged_factory_ops
 from tensorflow.python.saved_model import builder_impl
 from tensorflow.python.saved_model import load
 from tensorflow.python.saved_model import save
@@ -566,6 +567,25 @@ class LoadTest(test.TestCase):
         start_dense_shape=dense_shape)
     self.assertAllEqual([84, 86, 88], result["output"].values.numpy())
 
+  def _model_with_ragged_input(self):
+    """Generate a graph with a RaggedTensor input and serialize in V1 format."""
+    export_graph = ops.Graph()
+    with export_graph.as_default():
+      x = ragged_factory_ops.placeholder(dtypes.float32, 1, [])
+      y = x * 2
+      with session_lib.Session() as sess:
+        path = os.path.join(self.get_temp_dir(), "saved_model", str(ops.uid()))
+        simple_save.simple_save(sess, path, inputs={"x": x}, outputs={"y": y})
+    return path
+
+  def test_load_ragged_inputs(self):
+    path = self._model_with_ragged_input()
+    imported = load.load(path)
+    imported_fn = imported.signatures["serving_default"]
+    x = ragged_factory_ops.constant([[10., 20.], [30.]])
+    result = imported_fn(x_component_0=x.values, x_component_1=x.row_splits)
+    self.assertAllEqual(result["y"], [[20., 40.], [60.]])
+
   def _model_with_defun(self):
     """Generate a graph with a Defun and serialize in V1 format."""
     export_graph = ops.Graph()