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diff --git a/tensorflow/contrib/lite/delegates/eager/buffer_map_test.cc b/tensorflow/contrib/lite/delegates/eager/buffer_map_test.cc
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+++ b/tensorflow/contrib/lite/delegates/eager/buffer_map_test.cc
@@ -0,0 +1,174 @@
+/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+#include "tensorflow/contrib/lite/delegates/eager/buffer_map.h"
+
+#include <gmock/gmock.h>
+#include <gtest/gtest.h>
+#include "tensorflow/contrib/lite/interpreter.h"
+#include "tensorflow/contrib/lite/testing/util.h"
+#include "tensorflow/contrib/lite/util.h"
+
+namespace tflite {
+namespace eager {
+namespace {
+
+using ::testing::ElementsAre;
+
+// A bit of RAII to simplify handling of TfLiteTensors in the tests.
+using UniqueTfLiteTensor =
+    std::unique_ptr<TfLiteTensor, std::function<void(TfLiteTensor*)>>;
+
+template <typename T>
+UniqueTfLiteTensor MakeLiteTensor(const std::vector<int>& shape,
+                                  const std::vector<T>& data) {
+  auto tensor = UniqueTfLiteTensor(new TfLiteTensor, [](TfLiteTensor* t) {
+    TfLiteTensorDataFree(t);
+    TfLiteIntArrayFree(t->dims);
+    delete t;
+  });
+  tensor->allocation_type = kTfLiteDynamic;
+  tensor->type = typeToTfLiteType<T>();
+  tensor->dims = ConvertVectorToTfLiteIntArray(shape);
+  tensor->data.raw = nullptr;
+  TfLiteTensorRealloc(data.size() * sizeof(T), tensor.get());
+  memcpy(tensor->data.raw, data.data(), data.size() * sizeof(T));
+  return tensor;
+}
+
+template <typename T>
+tensorflow::Tensor MakeTensor(const std::vector<int>& shape,
+                              const std::vector<T>& data) {
+  BufferMap buffer_map;  // BufferMap is the easiest way to build the tensor.
+  UniqueTfLiteTensor t1 = MakeLiteTensor<T>(shape, data);
+  buffer_map.SetFromTfLite(0, t1.get());
+  return buffer_map.GetTensor(0);
+}
+
+std::vector<int64> GetTensorShape(const tensorflow::Tensor& t) {
+  std::vector<int64> shape(t.dims());
+  for (int i = 0; i < t.dims(); ++i) {
+    shape[i] = t.dim_size(i);
+  }
+  return shape;
+}
+
+template <typename T>
+std::vector<T> GetTensorData(const tensorflow::Tensor& t) {
+  const T* data = t.flat<T>().data();
+  return std::vector<T>(data, data + t.NumElements());
+}
+
+TEST(BufferMapTest, EmptyBuffer) {
+  BufferMap buffer_map;
+  EXPECT_FALSE(buffer_map.HasTensor(0));
+}
+
+TEST(BufferMapTest, SetFromTfLite) {
+  BufferMap buffer_map;
+
+  UniqueTfLiteTensor t =
+      MakeLiteTensor<float>({1, 2, 1, 3}, {0, 0, 0, 0.123f, 0, 0});
+  buffer_map.SetFromTfLite(0, t.get());
+  ASSERT_TRUE(buffer_map.HasTensor(0));
+
+  EXPECT_THAT(GetTensorData<float>(buffer_map.GetTensor(0)),
+              ElementsAre(0, 0, 0, 0.123f, 0, 0));
+
+  // Also check details of the tensor.
+  tensorflow::Tensor out_tensor = buffer_map.GetTensor(0);
+  ASSERT_EQ(out_tensor.dtype(), tensorflow::DT_FLOAT);
+  ASSERT_EQ(out_tensor.NumElements(), 6);
+  ASSERT_THAT(GetTensorShape(out_tensor), ElementsAre(1, 2, 1, 3));
+}
+
+TEST(BufferMapTest, SetFromTfLiteTwice) {
+  UniqueTfLiteTensor t1 =
+      MakeLiteTensor<float>({1, 2, 1, 3}, {0, 0, 0, 0.123f, 0, 0});
+  UniqueTfLiteTensor t2 =
+      MakeLiteTensor<int>({1, 2, 4}, {0, 0, 0, 3, 0, 0, 1, 2});
+
+  BufferMap buffer_map;
+  buffer_map.SetFromTfLite(0, t1.get());
+  buffer_map.SetFromTfLite(0, t2.get());
+
+  EXPECT_THAT(GetTensorData<int>(buffer_map.GetTensor(0)),
+              ElementsAre(0, 0, 0, 3, 0, 0, 1, 2));
+}
+
+TEST(BufferMapTest, SetFromTensorFlow) {
+  tensorflow::Tensor t1 =
+      MakeTensor<float>({1, 2, 1, 3}, {0, 0, 0, 0.123f, 0, 0});
+
+  BufferMap buffer_map;
+  buffer_map.SetFromTensorFlow(0, t1);
+
+  EXPECT_THAT(GetTensorData<float>(buffer_map.GetTensor(0)),
+              ElementsAre(0, 0, 0, 0.123f, 0, 0));
+
+  // Also check details of the tensor.
+  tensorflow::Tensor out_tensor = buffer_map.GetTensor(0);
+  ASSERT_EQ(out_tensor.dtype(), tensorflow::DT_FLOAT);
+  ASSERT_EQ(out_tensor.NumElements(), 6);
+  ASSERT_THAT(GetTensorShape(out_tensor), ElementsAre(1, 2, 1, 3));
+}
+
+TEST(BufferMapTest, SetFromTensorFlowTwice) {
+  tensorflow::Tensor t1 =
+      MakeTensor<float>({1, 2, 1, 3}, {0, 0, 0, 0.123f, 0, 0});
+  tensorflow::Tensor t2 = MakeTensor<int>({1, 2, 4}, {0, 0, 0, 3, 0, 0, 1, 2});
+  BufferMap buffer_map;
+  buffer_map.SetFromTensorFlow(0, t1);
+  buffer_map.SetFromTensorFlow(0, t2);
+
+  EXPECT_THAT(GetTensorData<int>(buffer_map.GetTensor(0)),
+              ElementsAre(0, 0, 0, 3, 0, 0, 1, 2));
+}
+
+TEST(BufferMapTest, TfLiteOverwritesTensorFlow) {
+  tensorflow::Tensor t1 =
+      MakeTensor<float>({1, 2, 1, 3}, {0, 0, 0, 0.123f, 0, 0});
+  UniqueTfLiteTensor t2 =
+      MakeLiteTensor<int>({1, 2, 4}, {0, 0, 0, 3, 0, 0, 1, 2});
+
+  BufferMap buffer_map;
+  buffer_map.SetFromTensorFlow(0, t1);
+  buffer_map.SetFromTfLite(0, t2.get());
+
+  EXPECT_THAT(GetTensorData<int>(buffer_map.GetTensor(0)),
+              ElementsAre(0, 0, 0, 3, 0, 0, 1, 2));
+}
+
+TEST(BufferMapTest, TensorFlowOverwritesTfLite) {
+  tensorflow::Tensor t1 =
+      MakeTensor<float>({1, 2, 1, 3}, {0, 0, 0, 0.123f, 0, 0});
+  UniqueTfLiteTensor t2 =
+      MakeLiteTensor<int>({1, 2, 4}, {0, 0, 0, 3, 0, 0, 1, 2});
+  BufferMap buffer_map;
+  buffer_map.SetFromTfLite(0, t2.get());
+  buffer_map.SetFromTensorFlow(0, t1);
+
+  EXPECT_THAT(GetTensorData<float>(buffer_map.GetTensor(0)),
+              ElementsAre(0, 0, 0, 0.123f, 0, 0));
+}
+
+}  // namespace
+}  // namespace eager
+}  // namespace tflite
+
+int main(int argc, char** argv) {
+  ::tflite::LogToStderr();
+  ::testing::InitGoogleTest(&argc, argv);
+  return RUN_ALL_TESTS();
+}