diff --git a/tensorflow/core/grappler/optimizers/function_api_info.cc b/tensorflow/core/grappler/optimizers/function_api_info.cc
index 201df2dc8ce..9f6352f1f2e 100644
--- a/tensorflow/core/grappler/optimizers/function_api_info.cc
+++ b/tensorflow/core/grappler/optimizers/function_api_info.cc
@@ -59,13 +59,6 @@ Status FunctionApiInfo::Init(const FunctionDef& function_def) {
         "Function '", function_def.signature().name(),
         "' has a preferred device, but does not implement an interface");
   }
-  // Handles the case that api_implements exists but prefered_device does not
-  // exist. Currently this is for tf lite/mlir, which depends on api_implements.
-  if (!interface_name_.empty() && preferred_device_.empty()) {
-    VLOG(1) << "A function has api_implements: " << interface_name_ << ", but "
-            << "api_preferred_device";
-    interface_name_.clear();
-  }
   return Status::OK();
 }
 
diff --git a/tensorflow/core/grappler/optimizers/function_api_info_test.cc b/tensorflow/core/grappler/optimizers/function_api_info_test.cc
index 8f1412f46b6..9bb517faa31 100644
--- a/tensorflow/core/grappler/optimizers/function_api_info_test.cc
+++ b/tensorflow/core/grappler/optimizers/function_api_info_test.cc
@@ -138,9 +138,11 @@ TEST(FunctionApiInfoTest, ParseTags) {
 
   EXPECT_EQ("DoStuff", GetInterfaceName(lib_api_info, "DoStuffCpu"));
   EXPECT_EQ("DoStuff", GetInterfaceName(lib_api_info, "DoStuffGpu"));
+  EXPECT_EQ("DoThings", GetInterfaceName(lib_api_info, "DoThings"));
 
   EXPECT_EQ("CPU", GetPreferredDevice(lib_api_info, "DoStuffCpu"));
   EXPECT_EQ("GPU", GetPreferredDevice(lib_api_info, "DoStuffGpu"));
+  EXPECT_EQ("", GetPreferredDevice(lib_api_info, "DoThings"));
 
   EXPECT_TRUE(CheckEquivImpl(lib_api_info, "DoStuffCpu", {"DoStuffGpu"}));
   EXPECT_TRUE(CheckEquivImpl(lib_api_info, "DoStuffGpu", {"DoStuffCpu"}));
@@ -183,19 +185,6 @@ TEST(FunctionApiInfoTest, MismatchedArguments) {
   EXPECT_FALSE(ret.ok());
 }
 
-TEST(FunctionApiInfoTest, ImplementsWithoutDevice) {
-  FunctionDefLibrary func_lib;
-  const std::vector<ArgSpec> func_args{{"in1", "float32"}, {"in2", "int32"}};
-  const std::vector<ArgSpec> output_args{{"out", "float32"}};
-  PopulateFunction("DoThings", "DoThings", "", func_args, output_args, "", "",
-                   func_lib.add_function());
-  FunctionLibraryApiInfo lib_api_info;
-  const Status ret = lib_api_info.Init(func_lib);
-  EXPECT_TRUE(ret.ok());
-  EXPECT_TRUE(lib_api_info.empty());
-  EXPECT_TRUE(CheckEquivImpl(lib_api_info, "DoThings", {}));
-}
-
 }  // namespace
 }  // namespace grappler
 }  // namespace tensorflow
diff --git a/tensorflow/core/grappler/optimizers/implementation_selector_test.cc b/tensorflow/core/grappler/optimizers/implementation_selector_test.cc
index 13a6e60b0ae..2ef8bb878cc 100644
--- a/tensorflow/core/grappler/optimizers/implementation_selector_test.cc
+++ b/tensorflow/core/grappler/optimizers/implementation_selector_test.cc
@@ -220,62 +220,6 @@ TEST_F(ImplementationSelectorTest, TwoTypesOfSwapImplementation) {
   }
 }
 
-TEST_F(ImplementationSelectorTest, NoSwapWithImplementsOnly) {
-  using test::function::NDef;
-  ImplementationSelector optimizer;
-  GraphDef output;
-  GrapplerItem item;
-  // DeviceIndex op based implementation selector.
-  AttrValue device_names;
-  device_names.mutable_list()->add_s("CPU");
-  device_names.mutable_list()->add_s("TPU_REPLICATED_CORE");
-  device_names.mutable_list()->add_s("GPU");
-
-  // Api_implements exists, api_preferred_device does not, no swap.
-  auto cpu_def = test::function::XTimesTwo();
-  auto* func_attr = cpu_def.mutable_attr();
-  (*func_attr)["api_implements"].set_s("times_two");
-
-  auto gpu_def = test::function::XAddX();
-  auto* func2_attr = gpu_def.mutable_attr();
-  (*func2_attr)["api_implements"].set_s("times_two");
-
-  item.graph = test::function::GDef(
-      {NDef("x", "DeviceIndex", {}, {{"device_names", device_names}},
-            CpuDevice),
-       NDef("case", "Case", {"x"}, {{"T", DT_FLOAT}}, GpuDevice),
-       NDef("y", "DeviceIndex", {}, {{"device_names", device_names}},
-            GpuDevice),
-       NDef("case_y", "Case", {"y"}, {{"T", DT_FLOAT}}, TpuDevice),
-       NDef("y1", "XTimesTwo", {"x"}, {{"T", DT_FLOAT}}, GpuDevice),
-       NDef("z1", "Identity", {"y1"}, {{"T", DT_FLOAT}}, GpuDevice),
-       NDef("y2", "XTimesTwo", {"x"}, {{"T", DT_FLOAT}}, CpuDevice),
-       NDef("z2", "Identity", {"y2"}, {{"T", DT_FLOAT}}, CpuDevice)},
-      // FunctionLib
-      {cpu_def, gpu_def});
-
-  TF_EXPECT_OK(optimizer.Optimize(nullptr, item, &output));
-  for (const NodeDef& node : output.node()) {
-    if (node.name() == "x") {
-      // Rewrite DeviceIndex op to a Const op with value of GPU index 1.
-      EXPECT_EQ("Const", node.op());
-      EXPECT_EQ(2, node.attr().at("value").tensor().int_val(0));
-    }
-    if (node.name() == "y") {
-      // Rewrite DeviceIndex op to a Const op with value of CPU index 0.
-      EXPECT_EQ("Const", node.op());
-      EXPECT_EQ(1, node.attr().at("value").tensor().int_val(0));
-    }
-    if (node.name() == "y1") {
-      // api_implements only, no preferred device, no swap.
-      EXPECT_EQ("XTimesTwo", node.op());
-    } else if (node.name() == "y2") {
-      // Make sure the implementation is not changed.
-      EXPECT_EQ("XTimesTwo", node.op());
-    }
-  }
-}
-
 TEST_F(ImplementationSelectorTest, SwapImplementation) {
   using test::function::NDef;
   auto cpu_def = test::function::XTimesTwo();