diff --git a/tensorflow/compiler/tf2xla/BUILD b/tensorflow/compiler/tf2xla/BUILD
index 92ba474fbcd..14bd9d4b138 100644
--- a/tensorflow/compiler/tf2xla/BUILD
+++ b/tensorflow/compiler/tf2xla/BUILD
@@ -317,11 +317,13 @@ tf_cc_test(
         ":tf2xla_util",
         "//tensorflow/cc:cc_ops",
         "//tensorflow/cc:function_ops",
+        "//tensorflow/cc:functional_ops",
         "//tensorflow/cc:ops",
         "//tensorflow/core:core_cpu_internal",
         "//tensorflow/core:framework",
         "//tensorflow/core:lib",
         "//tensorflow/core:math_ops_op_lib",
+        "//tensorflow/core:ops",
         "//tensorflow/core:protos_all_cc",
         "//tensorflow/core:test",
         "//tensorflow/core:test_main",
diff --git a/tensorflow/compiler/tf2xla/tf2xla_util.cc b/tensorflow/compiler/tf2xla/tf2xla_util.cc
index 18d87727c50..c64f78e1a1b 100644
--- a/tensorflow/compiler/tf2xla/tf2xla_util.cc
+++ b/tensorflow/compiler/tf2xla/tf2xla_util.cc
@@ -265,6 +265,13 @@ Status PropagateConstIntoWhileNode(Graph* g, Node* while_node,
     }
 
     // Check if i-th retval's input comes from i-th arg directly.
+    // For resource variable input of While nodes, TF2XLA convention is to place
+    // them at the end of all inputs (after all data inputs), and *not* return
+    // them. So number of While node inputs might be larger than number of its
+    // outputs.
+    if (i >= body_func->signature().output_arg_size()) {
+      continue;
+    }
     const OpDef_ArgDef& output_arg = body_func->signature().output_arg(i);
     auto output_arg_input = body_func->ret().find(output_arg.name());
     if (output_arg_input == body_func->ret().end()) {
diff --git a/tensorflow/compiler/tf2xla/tf2xla_util_test.cc b/tensorflow/compiler/tf2xla/tf2xla_util_test.cc
index 202e929315c..9e9c3cecee6 100644
--- a/tensorflow/compiler/tf2xla/tf2xla_util_test.cc
+++ b/tensorflow/compiler/tf2xla/tf2xla_util_test.cc
@@ -21,11 +21,13 @@ limitations under the License.
 #include "tensorflow/cc/framework/ops.h"
 #include "tensorflow/cc/ops/data_flow_ops.h"
 #include "tensorflow/cc/ops/function_ops.h"
+#include "tensorflow/cc/ops/functional_ops.h"
 #include "tensorflow/cc/ops/standard_ops.h"
 #include "tensorflow/compiler/tf2xla/sharding_util.h"
 #include "tensorflow/core/common_runtime/graph_optimizer.h"
 #include "tensorflow/core/common_runtime/process_function_library_runtime.h"
 #include "tensorflow/core/framework/function.h"
+#include "tensorflow/core/framework/graph_to_functiondef.h"
 #include "tensorflow/core/framework/node_def.pb.h"
 #include "tensorflow/core/graph/graph.h"
 #include "tensorflow/core/lib/core/status.h"
@@ -329,5 +331,37 @@ TEST(CachedFunctionHandles, Basic) {
   TF_EXPECT_OK(cached_function_handles.ReleaseAllHandles());
 }
 
+TEST(PropagateConstIntoFunctionalNodes, WhileLoopWithResourceInput) {
+  FunctionLibraryDefinition fld(OpRegistry::Global(), {});
+  {
+    // Cond graph & body graph.
+    Scope scope = Scope::NewRootScope().ExitOnError();
+    auto pred = ops::_Arg(scope.WithOpName("pred"), DT_BOOL, 0);
+    auto input = ops::_Arg(scope.WithOpName("input"), DT_RESOURCE, 1);
+    auto ret = ops::_Retval(scope.WithOpName("ret"), pred, 0);
+    Graph graph(OpRegistry::Global());
+    TF_ASSERT_OK(scope.ToGraph(&graph));
+    FunctionDef cond_fdef;
+    TF_ASSERT_OK(GraphToFunctionDef(graph, "cond", &cond_fdef));
+    TF_ASSERT_OK(fld.AddFunctionDef(cond_fdef));
+    FunctionDef body_fdef;
+    TF_ASSERT_OK(GraphToFunctionDef(graph, "body", &body_fdef));
+    TF_ASSERT_OK(fld.AddFunctionDef(body_fdef));
+  }
+  Scope scope = Scope::NewRootScope().ExitOnError();
+  auto pred = ops::Const(scope.WithOpName("pred"), false, TensorShape({}));
+  auto input = ops::Const(scope.WithOpName("input"), 0, TensorShape({}));
+  NameAttrList cond_fn, body_fn;
+  cond_fn.set_name("cond");
+  body_fn.set_name("body");
+  auto while_op =
+      ops::While(scope.WithOpName("while"),
+                 std::initializer_list<Input>{pred, input}, cond_fn, body_fn);
+  Graph graph(OpRegistry::Global());
+  TF_ASSERT_OK(scope.ToGraph(&graph));
+
+  TF_EXPECT_OK(PropagateConstIntoFunctionalNodes(&graph, &fld, &fld));
+}
+
 }  // namespace
 }  // namespace tensorflow