diff --git a/tensorflow/lite/models/BUILD b/tensorflow/lite/models/BUILD
deleted file mode 100644
index 6332636a0db..00000000000
--- a/tensorflow/lite/models/BUILD
+++ /dev/null
@@ -1,12 +0,0 @@
-# Model tests
-package(
-    default_visibility = ["//visibility:public"],
-)
-
-licenses(["notice"])  # Apache 2.0
-
-exports_files(["LICENSE"])
-
-exports_files(glob([
-    "testdata/*",
-]))
diff --git a/tensorflow/lite/models/smartreply/BUILD b/tensorflow/lite/models/smartreply/BUILD
deleted file mode 100644
index 9819c804cc2..00000000000
--- a/tensorflow/lite/models/smartreply/BUILD
+++ /dev/null
@@ -1,117 +0,0 @@
-load("//tensorflow:tensorflow.bzl", "tf_cc_test")
-load("//tensorflow/lite:build_def.bzl", "gen_selected_ops", "tflite_copts")
-
-package(
-    default_visibility = [
-        "//visibility:public",
-    ],
-    licenses = ["notice"],  # Apache 2.0
-)
-
-exports_files(["LICENSE"])
-
-gen_selected_ops(
-    name = "smartreply_ops",
-    model = ["@tflite_smartreply//:smartreply.tflite"],
-)
-
-cc_library(
-    name = "custom_ops",
-    srcs = [
-        "ops/extract_feature.cc",
-        "ops/normalize.cc",
-        "ops/predict.cc",
-        ":smartreply_ops",
-    ],
-    copts = tflite_copts(),
-    deps = [
-        "//tensorflow/lite:framework",
-        "//tensorflow/lite:string_util",
-        "//tensorflow/lite/kernels:builtin_ops",
-        "//tensorflow/lite/kernels:kernel_util",
-        "//tensorflow/lite/kernels/internal:tensor",
-        "@com_google_absl//absl/strings",
-        "@com_googlesource_code_re2//:re2",
-        "@farmhash_archive//:farmhash",
-    ],
-    alwayslink = 1,
-)
-
-cc_library(
-    name = "predictor_lib",
-    srcs = ["predictor.cc"],
-    hdrs = ["predictor.h"],
-    copts = tflite_copts(),
-    deps = [
-        ":custom_ops",
-        "//tensorflow/lite:framework",
-        "//tensorflow/lite:string_util",
-        "//tensorflow/lite/kernels:builtin_ops",
-        "@com_google_absl//absl/strings",
-        "@com_googlesource_code_re2//:re2",
-    ],
-)
-
-# TODO(b/118895218): Make this test compatible with oss.
-tf_cc_test(
-    name = "predictor_test",
-    srcs = ["predictor_test.cc"],
-    data = [
-        "//tensorflow/lite/models:testdata/smartreply_samples.tsv",
-        "@tflite_smartreply//:smartreply.tflite",
-    ],
-    tags = ["no_oss"],
-    deps = [
-        ":predictor_lib",
-        "//tensorflow/core:test",
-        "//tensorflow/lite:string_util",
-        "//tensorflow/lite/testing:util",
-        "@com_google_absl//absl/strings",
-        "@com_google_googletest//:gtest",
-    ],
-)
-
-cc_test(
-    name = "extract_feature_op_test",
-    size = "small",
-    srcs = ["ops/extract_feature_test.cc"],
-    tags = ["no_oss"],
-    deps = [
-        ":custom_ops",
-        "//tensorflow/lite:framework",
-        "//tensorflow/lite/kernels:builtin_ops",
-        "//tensorflow/lite/kernels:test_util",
-        "@com_google_googletest//:gtest",
-        "@farmhash_archive//:farmhash",
-    ],
-)
-
-cc_test(
-    name = "normalize_op_test",
-    size = "small",
-    srcs = ["ops/normalize_test.cc"],
-    tags = ["no_oss"],
-    deps = [
-        ":custom_ops",
-        "//tensorflow/lite:framework",
-        "//tensorflow/lite:string_util",
-        "//tensorflow/lite/kernels:builtin_ops",
-        "//tensorflow/lite/kernels:test_util",
-        "@com_google_googletest//:gtest",
-    ],
-)
-
-cc_test(
-    name = "predict_op_test",
-    size = "small",
-    srcs = ["ops/predict_test.cc"],
-    tags = ["no_oss"],
-    deps = [
-        ":custom_ops",
-        "//tensorflow/lite:framework",
-        "//tensorflow/lite:string_util",
-        "//tensorflow/lite/kernels:builtin_ops",
-        "//tensorflow/lite/kernels:test_util",
-        "@com_google_googletest//:gtest",
-    ],
-)
diff --git a/tensorflow/lite/models/smartreply/demo/app/src/main/AndroidManifest.xml b/tensorflow/lite/models/smartreply/demo/app/src/main/AndroidManifest.xml
deleted file mode 100644
index 75ed9432c8f..00000000000
--- a/tensorflow/lite/models/smartreply/demo/app/src/main/AndroidManifest.xml
+++ /dev/null
@@ -1,38 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<!--
- Copyright 2017 The Android Open Source Project
-
- 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.
--->
-<manifest xmlns:android="http://schemas.android.com/apk/res/android"
-  package="com.example.android.smartreply" >
-
-  <uses-sdk
-      android:minSdkVersion="15"
-      android:targetSdkVersion="24" />
-
-  <application android:label="TfLite SmartReply Demo">
-    <activity
-        android:name="com.example.android.smartreply.MainActivity"
-        android:configChanges="orientation|keyboardHidden|screenSize"
-        android:windowSoftInputMode="stateUnchanged|adjustPan"
-        android:label="TfLite SmartReply Demo"
-        android:screenOrientation="portrait" >
-      <intent-filter>
-        <action android:name="android.intent.action.MAIN" />
-        <category android:name="android.intent.category.LAUNCHER" />
-      </intent-filter>
-    </activity>
-  </application>
-
-</manifest>
diff --git a/tensorflow/lite/models/smartreply/demo/app/src/main/BUILD b/tensorflow/lite/models/smartreply/demo/app/src/main/BUILD
deleted file mode 100644
index 8c489cf729f..00000000000
--- a/tensorflow/lite/models/smartreply/demo/app/src/main/BUILD
+++ /dev/null
@@ -1,68 +0,0 @@
-load("@build_bazel_rules_android//android:rules.bzl", "android_binary")
-load(
-    "//tensorflow/lite:build_def.bzl",
-    "tflite_copts",
-    "tflite_jni_binary",
-)
-
-package(
-    default_visibility = ["//visibility:public"],
-    licenses = ["notice"],  # Apache 2.0
-)
-
-filegroup(
-    name = "assets",
-    srcs = [
-        "@tflite_smartreply//:model_files",
-    ],
-)
-
-android_binary(
-    name = "SmartReplyDemo",
-    srcs = glob(["java/**/*.java"]),
-    assets = [":assets"],
-    assets_dir = "",
-    custom_package = "com.example.android.smartreply",
-    manifest = "AndroidManifest.xml",
-    nocompress_extensions = [
-        ".tflite",
-    ],
-    resource_files = glob(["res/**"]),
-    tags = ["manual"],
-    deps = [
-        ":smartreply_runtime",
-        "@androidsdk//com.android.support:support-v13-25.2.0",
-        "@androidsdk//com.android.support:support-v4-25.2.0",
-    ],
-)
-
-cc_library(
-    name = "smartreply_runtime",
-    srcs = ["libsmartreply_jni.so"],
-    visibility = ["//visibility:public"],
-)
-
-tflite_jni_binary(
-    name = "libsmartreply_jni.so",
-    deps = [
-        ":smartreply_jni_lib",
-    ],
-)
-
-cc_library(
-    name = "smartreply_jni_lib",
-    srcs = [
-        "smartreply_jni.cc",
-    ],
-    copts = tflite_copts(),
-    linkopts = [
-        "-lm",
-        "-ldl",
-    ],
-    deps = [
-        "//tensorflow/lite:framework",
-        "//tensorflow/lite/java/jni",
-        "//tensorflow/lite/models/smartreply:predictor_lib",
-    ],
-    alwayslink = 1,
-)
diff --git a/tensorflow/lite/models/smartreply/demo/app/src/main/assets/BUILD b/tensorflow/lite/models/smartreply/demo/app/src/main/assets/BUILD
deleted file mode 100644
index 86023676484..00000000000
--- a/tensorflow/lite/models/smartreply/demo/app/src/main/assets/BUILD
+++ /dev/null
@@ -1,16 +0,0 @@
-package(
-    default_visibility = ["//visibility:public"],
-    licenses = ["notice"],  # Apache 2.0
-)
-
-exports_files(glob(["*"]))
-
-filegroup(
-    name = "assets_files",
-    srcs = glob(
-        ["**/*"],
-        exclude = [
-            "BUILD",
-        ],
-    ),
-)
diff --git a/tensorflow/lite/models/smartreply/demo/app/src/main/assets/backoff_response.txt b/tensorflow/lite/models/smartreply/demo/app/src/main/assets/backoff_response.txt
deleted file mode 100644
index a0a5b46b5f8..00000000000
--- a/tensorflow/lite/models/smartreply/demo/app/src/main/assets/backoff_response.txt
+++ /dev/null
@@ -1,16 +0,0 @@
-Ok
-Yes
-No
-👍
-☺
-😟
-❤️
-Lol
-Thanks
-Got it
-Done
-Nice
-I don't know
-What?
-Why?
-What's up?
diff --git a/tensorflow/lite/models/smartreply/demo/app/src/main/java/com/example/android/smartreply/MainActivity.java b/tensorflow/lite/models/smartreply/demo/app/src/main/java/com/example/android/smartreply/MainActivity.java
deleted file mode 100644
index 02fec9ae5e9..00000000000
--- a/tensorflow/lite/models/smartreply/demo/app/src/main/java/com/example/android/smartreply/MainActivity.java
+++ /dev/null
@@ -1,99 +0,0 @@
-/* Copyright 2017 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.
-==============================================================================*/
-
-package com.example.android.smartreply;
-
-import android.app.Activity;
-import android.os.Bundle;
-import android.os.Handler;
-import android.util.Log;
-import android.view.View;
-import android.widget.Button;
-import android.widget.EditText;
-import android.widget.TextView;
-
-/**
- * The main (and only) activity of this demo app. Displays a text box which updates as messages are
- * received.
- */
-public class MainActivity extends Activity {
-  private static final String TAG = "SmartReplyDemo";
-  private SmartReplyClient client;
-
-  private Button sendButton;
-  private TextView messageTextView;
-  private EditText messageInput;
-
-  private Handler handler;
-
-  @Override
-  protected void onCreate(Bundle savedInstanceState) {
-    super.onCreate(savedInstanceState);
-    Log.v(TAG, "onCreate");
-    setContentView(R.layout.main_activity);
-
-    client = new SmartReplyClient(getApplicationContext());
-    handler = new Handler();
-
-    sendButton = (Button) findViewById(R.id.send_button);
-    sendButton.setOnClickListener(
-        (View v) -> {
-          send(messageInput.getText().toString());
-        });
-
-    messageTextView = (TextView) findViewById(R.id.message_text);
-    messageInput = (EditText) findViewById(R.id.message_input);
-  }
-
-  @Override
-  protected void onStart() {
-    super.onStart();
-    Log.v(TAG, "onStart");
-    handler.post(
-        () -> {
-          client.loadModel();
-        });
-  }
-
-  @Override
-  protected void onStop() {
-    super.onStop();
-    Log.v(TAG, "onStop");
-    handler.post(
-        () -> {
-          client.unloadModel();
-        });
-  }
-
-  private void send(final String message) {
-    handler.post(
-        () -> {
-          messageTextView.append("Input: " + message + "\n");
-
-          SmartReply[] ans = client.predict(new String[] {message});
-          for (SmartReply reply : ans) {
-            appendMessage("Reply: " + reply.getText());
-          }
-          appendMessage("------");
-        });
-  }
-
-  private void appendMessage(final String message) {
-    handler.post(
-        () -> {
-          messageTextView.append(message + "\n");
-        });
-  }
-}
diff --git a/tensorflow/lite/models/smartreply/demo/app/src/main/java/com/example/android/smartreply/SmartReply.java b/tensorflow/lite/models/smartreply/demo/app/src/main/java/com/example/android/smartreply/SmartReply.java
deleted file mode 100644
index 3357fd17c11..00000000000
--- a/tensorflow/lite/models/smartreply/demo/app/src/main/java/com/example/android/smartreply/SmartReply.java
+++ /dev/null
@@ -1,44 +0,0 @@
-/* Copyright 2017 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.
-==============================================================================*/
-
-package com.example.android.smartreply;
-
-import android.support.annotation.Keep;
-
-/**
- * SmartReply contains predicted message, and confidence.
- *
- * <p>NOTE: this class used by JNI, class name and constructor should not be obfuscated.
- */
-@Keep
-public class SmartReply {
-
-  private final String text;
-  private final float score;
-
-  @Keep
-  public SmartReply(String text, float score) {
-    this.text = text;
-    this.score = score;
-  }
-
-  public String getText() {
-    return text;
-  }
-
-  public float getScore() {
-    return score;
-  }
-}
diff --git a/tensorflow/lite/models/smartreply/demo/app/src/main/java/com/example/android/smartreply/SmartReplyClient.java b/tensorflow/lite/models/smartreply/demo/app/src/main/java/com/example/android/smartreply/SmartReplyClient.java
deleted file mode 100644
index cbd155bb0cd..00000000000
--- a/tensorflow/lite/models/smartreply/demo/app/src/main/java/com/example/android/smartreply/SmartReplyClient.java
+++ /dev/null
@@ -1,131 +0,0 @@
-/* Copyright 2017 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.
-==============================================================================*/
-
-package com.example.android.smartreply;
-
-import android.content.Context;
-import android.content.res.AssetFileDescriptor;
-import android.support.annotation.Keep;
-import android.support.annotation.WorkerThread;
-import android.util.Log;
-import java.io.BufferedReader;
-import java.io.FileInputStream;
-import java.io.IOException;
-import java.io.InputStreamReader;
-import java.nio.MappedByteBuffer;
-import java.nio.channels.FileChannel;
-import java.util.ArrayList;
-import java.util.List;
-
-/** Interface to load TfLite model and provide predictions. */
-public class SmartReplyClient implements AutoCloseable {
-  private static final String TAG = "SmartReplyDemo";
-  private static final String MODEL_PATH = "smartreply.tflite";
-  private static final String BACKOFF_PATH = "backoff_response.txt";
-  private static final String JNI_LIB = "smartreply_jni";
-
-  private final Context context;
-  private long storage;
-  private MappedByteBuffer model;
-
-  private volatile boolean isLibraryLoaded;
-
-  public SmartReplyClient(Context context) {
-    this.context = context;
-  }
-
-  public boolean isLoaded() {
-    return storage != 0;
-  }
-
-  @WorkerThread
-  public synchronized void loadModel() {
-    if (!isLibraryLoaded) {
-      try {
-        System.loadLibrary(JNI_LIB);
-        isLibraryLoaded = true;
-      } catch (Exception e) {
-        Log.e(TAG, "Failed to load prebuilt smartreply_jni lib", e);
-        return;
-      }
-    }
-
-    try {
-      model = loadModelFile();
-      String[] backoff = loadBackoffList();
-      storage = loadJNI(model, backoff);
-    } catch (IOException e) {
-      Log.e(TAG, "Fail to load model", e);
-      return;
-    }
-  }
-
-  @WorkerThread
-  public synchronized SmartReply[] predict(String[] input) {
-    if (storage != 0) {
-      return predictJNI(storage, input);
-    } else {
-      return new SmartReply[] {};
-    }
-  }
-
-  @WorkerThread
-  public synchronized void unloadModel() {
-    close();
-  }
-
-  @Override
-  public synchronized void close() {
-    if (storage != 0) {
-      unloadJNI(storage);
-      storage = 0;
-    }
-  }
-
-  private MappedByteBuffer loadModelFile() throws IOException {
-    try (AssetFileDescriptor fileDescriptor = context.getAssets().openFd(MODEL_PATH);
-        FileInputStream inputStream = new FileInputStream(fileDescriptor.getFileDescriptor())) {
-      FileChannel fileChannel = inputStream.getChannel();
-      long startOffset = fileDescriptor.getStartOffset();
-      long declaredLength = fileDescriptor.getDeclaredLength();
-      return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
-    }
-  }
-
-  private String[] loadBackoffList() throws IOException {
-    List<String> labelList = new ArrayList<String>();
-    try (BufferedReader reader =
-        new BufferedReader(new InputStreamReader(context.getAssets().open(BACKOFF_PATH)))) {
-      String line;
-      while ((line = reader.readLine()) != null) {
-        if (!line.isEmpty()) {
-          labelList.add(line);
-        }
-      }
-    }
-    String[] ans = new String[labelList.size()];
-    labelList.toArray(ans);
-    return ans;
-  }
-
-  @Keep
-  private native long loadJNI(MappedByteBuffer buffer, String[] backoff);
-
-  @Keep
-  private native SmartReply[] predictJNI(long storage, String[] text);
-
-  @Keep
-  private native void unloadJNI(long storage);
-}
diff --git a/tensorflow/lite/models/smartreply/demo/app/src/main/res/layout/main_activity.xml b/tensorflow/lite/models/smartreply/demo/app/src/main/res/layout/main_activity.xml
deleted file mode 100644
index 23b4cadc007..00000000000
--- a/tensorflow/lite/models/smartreply/demo/app/src/main/res/layout/main_activity.xml
+++ /dev/null
@@ -1,44 +0,0 @@
-<LinearLayout xmlns:android="http://schemas.android.com/apk/res/android"
-    xmlns:tools="http://schemas.android.com/tools"
-    android:layout_width="match_parent"
-    android:layout_height="match_parent"
-    android:orientation="vertical">
-
-    <LinearLayout
-        android:layout_width="fill_parent"
-        android:layout_height="0dp"
-        android:padding="5dip"
-        android:layout_weight="3">
-
-        <TextView
-            android:id="@+id/message_text"
-            android:layout_width="fill_parent"
-            android:layout_height="fill_parent"
-            android:scrollbars="vertical"
-            android:gravity="bottom"/>
-    </LinearLayout>
-
-    <LinearLayout
-        android:layout_width="fill_parent"
-        android:layout_height="0dp"
-        android:padding="5dip"
-        android:layout_weight="1">
-
-        <EditText
-            android:id="@+id/message_input"
-            android:layout_width="0dp"
-            android:layout_height="fill_parent"
-            android:layout_weight="6"
-            android:scrollbars="vertical"
-            android:hint="Enter Text"
-            android:gravity="top"
-            android:inputType="text"/>
-        <Button
-            android:id="@+id/send_button"
-            android:layout_width="0dp"
-            android:layout_height="fill_parent"
-            android:layout_weight="2"
-            android:text="Send" />
-    </LinearLayout>
-
-</LinearLayout>
diff --git a/tensorflow/lite/models/smartreply/demo/app/src/main/smartreply_jni.cc b/tensorflow/lite/models/smartreply/demo/app/src/main/smartreply_jni.cc
deleted file mode 100644
index 9b5df36c37a..00000000000
--- a/tensorflow/lite/models/smartreply/demo/app/src/main/smartreply_jni.cc
+++ /dev/null
@@ -1,129 +0,0 @@
-/* Copyright 2017 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 <jni.h>
-#include <utility>
-#include <vector>
-
-#include "tensorflow/lite/model.h"
-#include "tensorflow/lite/models/smartreply/predictor.h"
-
-const char kIllegalStateException[] = "java/lang/IllegalStateException";
-
-using tflite::custom::smartreply::GetSegmentPredictions;
-using tflite::custom::smartreply::PredictorResponse;
-
-template <typename T>
-T CheckNotNull(JNIEnv* env, T&& t) {
-  if (t == nullptr) {
-    env->ThrowNew(env->FindClass(kIllegalStateException), "");
-    return nullptr;
-  }
-  return std::forward<T>(t);
-}
-
-std::vector<std::string> jniStringArrayToVector(JNIEnv* env,
-                                                jobjectArray string_array) {
-  int count = env->GetArrayLength(string_array);
-  std::vector<std::string> result;
-  for (int i = 0; i < count; i++) {
-    auto jstr =
-        reinterpret_cast<jstring>(env->GetObjectArrayElement(string_array, i));
-    const char* raw_str = env->GetStringUTFChars(jstr, JNI_FALSE);
-    result.emplace_back(std::string(raw_str));
-    env->ReleaseStringUTFChars(jstr, raw_str);
-  }
-  return result;
-}
-
-struct JNIStorage {
-  std::vector<std::string> backoff_list;
-  std::unique_ptr<::tflite::FlatBufferModel> model;
-};
-
-extern "C" JNIEXPORT jlong JNICALL
-Java_com_example_android_smartreply_SmartReplyClient_loadJNI(
-    JNIEnv* env, jobject thiz, jobject model_buffer,
-    jobjectArray backoff_list) {
-  const char* buf =
-      static_cast<char*>(env->GetDirectBufferAddress(model_buffer));
-  jlong capacity = env->GetDirectBufferCapacity(model_buffer);
-
-  JNIStorage* storage = new JNIStorage;
-  storage->model = tflite::FlatBufferModel::BuildFromBuffer(
-      buf, static_cast<size_t>(capacity));
-  storage->backoff_list = jniStringArrayToVector(env, backoff_list);
-
-  if (!storage->model) {
-    delete storage;
-    env->ThrowNew(env->FindClass(kIllegalStateException), "");
-    return 0;
-  }
-  return reinterpret_cast<jlong>(storage);
-}
-
-extern "C" JNIEXPORT jobjectArray JNICALL
-Java_com_example_android_smartreply_SmartReplyClient_predictJNI(
-    JNIEnv* env, jobject /*thiz*/, jlong storage_ptr, jobjectArray input_text) {
-  // Predict
-  if (storage_ptr == 0) {
-    return nullptr;
-  }
-  JNIStorage* storage = reinterpret_cast<JNIStorage*>(storage_ptr);
-  if (storage == nullptr) {
-    return nullptr;
-  }
-  std::vector<PredictorResponse> responses;
-  GetSegmentPredictions(jniStringArrayToVector(env, input_text),
-                        *storage->model, {storage->backoff_list}, &responses);
-
-  // Create a SmartReply[] to return back to Java
-  jclass smart_reply_class = CheckNotNull(
-      env, env->FindClass("com/example/android/smartreply/SmartReply"));
-  if (env->ExceptionCheck()) {
-    return nullptr;
-  }
-  jmethodID smart_reply_ctor = CheckNotNull(
-      env,
-      env->GetMethodID(smart_reply_class, "<init>", "(Ljava/lang/String;F)V"));
-  if (env->ExceptionCheck()) {
-    return nullptr;
-  }
-  jobjectArray array = CheckNotNull(
-      env, env->NewObjectArray(responses.size(), smart_reply_class, nullptr));
-  if (env->ExceptionCheck()) {
-    return nullptr;
-  }
-  for (int i = 0; i < responses.size(); i++) {
-    jstring text =
-        CheckNotNull(env, env->NewStringUTF(responses[i].GetText().data()));
-    if (env->ExceptionCheck()) {
-      return nullptr;
-    }
-    jobject reply = env->NewObject(smart_reply_class, smart_reply_ctor, text,
-                                   responses[i].GetScore());
-    env->SetObjectArrayElement(array, i, reply);
-  }
-  return array;
-}
-
-extern "C" JNIEXPORT void JNICALL
-Java_com_example_android_smartreply_SmartReplyClient_unloadJNI(
-    JNIEnv* env, jobject thiz, jlong storage_ptr) {
-  if (storage_ptr != 0) {
-    JNIStorage* storage = reinterpret_cast<JNIStorage*>(storage_ptr);
-    delete storage;
-  }
-}
diff --git a/tensorflow/lite/models/smartreply/g3doc/README.md b/tensorflow/lite/models/smartreply/g3doc/README.md
deleted file mode 100644
index 04439293337..00000000000
--- a/tensorflow/lite/models/smartreply/g3doc/README.md
+++ /dev/null
@@ -1,146 +0,0 @@
-# Smart Reply Model
-
-## What is On-Device Smart Reply Model?
-
-Smart Replies are contextually relevant, one-touch responses that help the user
-to reply to an incoming text message (or email) efficiently and effortlessly.
-Smart Replies have been highly successful across several Google products
-including
-[Gmail](https://www.blog.google/products/gmail/save-time-with-smart-reply-in-gmail/),
-[Inbox](https://www.blog.google/products/gmail/computer-respond-to-this-email/)
-and
-[Allo](https://blog.google/products/allo/google-allo-smarter-messaging-app/).
-
-The On-device Smart Reply model is targeted towards text chat use cases. It has
-a completely different architecture from its cloud-based counterparts, and is
-built specifically for memory constraints devices such as phones & watches. It
-has been successfully used to provide [Smart Replies on Android
-Wear](https://research.googleblog.com/2017/02/on-device-machine-intelligence.html)
-to all first- & third-party apps.
-
-The on-device model comes with several benefits. It is:
-
-*   **Faster**: The model resides on the device and does not require internet
-    connectivity. Thus, the inference is very fast and has an average latency of
-    only a few milliseconds.
-*   **Resource efficient**: The model has a small memory footprint on
-    the device.
-*   **Privacy-friendly**: The user data never leaves the device and this
-    eliminates any privacy restrictions.
-
-A caveat, though, is that the on-device model has lower triggering rate than its
-cloud counterparts (triggering rate is the percentage of times the model
-suggests a response for an incoming message).
-
-## When to use this Model?
-
-The On-Device Smart Reply model is aimed towards improving the messaging
-experience for day-to-day conversational chat messages. We recommend using this
-model for similar use cases. Some sample messages on which the model does well
-are provided in this [tsv
-file](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/models/testdata/smartreply_samples.tsv)
-for reference. The file format is:
-
-```
-   {incoming_message  smart_reply1   [smart_reply2]   [smart_reply3]}
-```
-
-For the current model, we see a triggering rate of about 30-40% for messages
-which are similar to those provided in the tsv file above.
-
-In case the model does not trigger any response, the system falls back to
-suggesting replies from a fixed back-off set that was compiled from popular
-response intents observed in chat conversations. Some of the fallback responses
-are `Ok, Yes, No, 👍, ☺`.
-
-The model can only be used for inference at this time (i.e. it cannot be custom
-trained). If you are interested to know how the model was trained, please refer
-to this [blog
-post](https://research.googleblog.com/2017/02/on-device-machine-intelligence.html)
-and [research paper](https://arxiv.org/pdf/1708.00630).
-
-## How to use this Model?
-
-We have provided a pre-built demo APK that you can download, install and test on
-your phone
-([demo APK here](https://storage.googleapis.com/download.tensorflow.org/deps/tflite/SmartReplyDemo.apk)).
-
-The On-Device Smart Reply demo App works in the following way:
-
-1.  Android app links to the JNI binary with a predictor library.
-
-2.  In the predictor library, `GetSegmentPredictions` is called with a list of input
-    strings.
-
-    2.1 The input string can be 1-3 most recent messages of the conversations in
-    form of string vector. The model will run on these input sentences and
-    provide Smart Replies corresponding to them.
-
-    2.2 The function performs some preprocessing on input data which includes:
-
-    *   Sentence splitting: The input message will be split into sentences if
-        message has more than one sentence. Eg: a message like “How are you?
-        Want to grab lunch?” will be broken down into 2 different sentences.
-    *   Normalization: The individual sentences will be normalized by converting
-        them into lower cases, removing unnecessary punctuations, etc. Eg: “how
-        are you????” will be converted to “how are you?” (refer for NORMALIZE op
-        for more details).
-
-        The input string content will be converted to tensors.
-
-    2.3 The function then runs the prediction model on the input tensors.
-
-    2.4 The function also performs some post-processing which includes
-    aggregating the model predictions for the input sentences from 2.2 and
-    returning the appropriate responses.
-
-3.  Finally, it gets response(s) from `std::vector<PredictorResponse>`, and
-    returns back to Android app. Responses are sorted in descending order of
-    confidence score.
-
-## Ops and Functionality Supported
-
-Following are the ops supported for using On-Device Smart Reply model:
-
-*   **NORMALIZE**
-
-    This is a custom op which normalizes the sentences by:
-
-    *   Converting all sentences into lower case.
-    *   Removing unnecessary punctuations (eg: “how are you????” → “how are
-        you?”).
-    *   Expanding sentences wherever necessary (eg: “ I’m home” → “I am home”).
-
-*   **SKIP_GRAM**
-
-    This is an op inside TensorFlow Lite that converts sentences into a list of
-    skip grams. The configurable parameters are `ngram_size` and
-    `max_skip_size`. For the model provided, the values for these parameters are
-    set to 3 & 2 respectively.
-
-*   **EXTRACT_FEATURES**
-
-    This is a custom op that hashes skip grams to features represented as
-    integers. Longer skip-grams are allocated higher weights.
-
-*   **LSH_PROJECTION**
-
-    This is an op inside TensorFlow Lite that projects input features to a
-    corresponding bit vector space using Locality Sensitive Hashing (LSH).
-
-*   **PREDICT**
-
-    This is a custom op that runs the input features through the projection
-    model (details [here](https://arxiv.org/pdf/1708.00630.pdf)), computes the
-    appropriate response labels along with weights for the projected features,
-    and aggregates the response labels and weights together.
-
-*   **HASHTABLE_LOOKUP**
-
-    This is an op inside TensorFlow Lite that uses label id from predict op and
-    looks up the response text from the given label id.
-
-## Further Information
-
-*   Open source code
-    [here](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/models/smartreply/).
diff --git a/tensorflow/lite/models/smartreply/ops/extract_feature.cc b/tensorflow/lite/models/smartreply/ops/extract_feature.cc
deleted file mode 100644
index ea5b185af60..00000000000
--- a/tensorflow/lite/models/smartreply/ops/extract_feature.cc
+++ /dev/null
@@ -1,121 +0,0 @@
-/* Copyright 2017 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.
-==============================================================================*/
-
-// Convert a list of strings to integers via hashing.
-// Input:
-//     Input[0]: A list of ngrams. string[num of input]
-//
-// Output:
-//     Output[0]: Hashed features. int32[num of input]
-//     Output[1]: Weights. float[num of input]
-
-#include <algorithm>
-#include <map>
-
-#include "tensorflow/lite/context.h"
-#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
-#include "tensorflow/lite/kernels/kernel_util.h"
-#include "tensorflow/lite/string_util.h"
-#include <farmhash.h>
-
-namespace tflite {
-namespace ops {
-namespace custom {
-
-namespace extract {
-
-static const int kMaxDimension = 1000000;
-static const std::vector<string> kBlacklistNgram = {"<S>", "<E>", "<S> <E>"};
-
-bool Equals(const string& x, const tflite::StringRef& strref) {
-  if (strref.len != x.length()) {
-    return false;
-  }
-  if (strref.len > 0) {
-    int r = memcmp(strref.str, x.data(), strref.len);
-    return r == 0;
-  }
-  return true;
-}
-
-bool IsValidNgram(const tflite::StringRef& strref) {
-  for (const auto& s : kBlacklistNgram) {
-    if (Equals(s, strref)) {
-      return false;
-    }
-  }
-  return true;
-}
-
-TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
-  const TfLiteTensor* input = GetInput(context, node, 0);
-  int dim = input->dims->data[0];
-  if (dim == 0) {
-    // TFLite non-string output should have size greater than 0.
-    dim = 1;
-  }
-  TF_LITE_ENSURE_EQ(context, input->type, kTfLiteString);
-  TfLiteIntArray* outputSize1 = TfLiteIntArrayCreate(1);
-  TfLiteIntArray* outputSize2 = TfLiteIntArrayCreate(1);
-  outputSize1->data[0] = dim;
-  outputSize2->data[0] = dim;
-  context->ResizeTensor(context, GetOutput(context, node, 0), outputSize1);
-  context->ResizeTensor(context, GetOutput(context, node, 1), outputSize2);
-  return kTfLiteOk;
-}
-
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
-  const TfLiteTensor* input = GetInput(context, node, 0);
-  int num_strings = tflite::GetStringCount(input);
-  TfLiteTensor* label = GetOutput(context, node, 0);
-  TfLiteTensor* weight = GetOutput(context, node, 1);
-
-  int32_t* label_data = GetTensorData<int32_t>(label);
-  float* weight_data = GetTensorData<float>(weight);
-
-  std::map<int64_t, int> feature_id_counts;
-  for (int i = 0; i < num_strings; i++) {
-    // Use fingerprint of feature name as id.
-    auto strref = tflite::GetString(input, i);
-    if (!IsValidNgram(strref)) {
-      label_data[i] = 0;
-      weight_data[i] = 0;
-      continue;
-    }
-
-    int64_t feature_id =
-        ::util::Fingerprint64(strref.str, strref.len) % kMaxDimension;
-    label_data[i] = static_cast<int32_t>(feature_id);
-    weight_data[i] = std::count(strref.str, strref.str + strref.len, ' ') + 1;
-  }
-  // Explicitly set an empty result to make preceding ops run.
-  if (num_strings == 0) {
-    label_data[0] = 0;
-    weight_data[0] = 0;
-  }
-  return kTfLiteOk;
-}
-
-}  // namespace extract
-
-TfLiteRegistration* Register_EXTRACT_FEATURES() {
-  static TfLiteRegistration r = {nullptr, nullptr, extract::Prepare,
-                                 extract::Eval};
-  return &r;
-}
-
-}  // namespace custom
-}  // namespace ops
-}  // namespace tflite
diff --git a/tensorflow/lite/models/smartreply/ops/extract_feature_test.cc b/tensorflow/lite/models/smartreply/ops/extract_feature_test.cc
deleted file mode 100644
index 914b47c1a9d..00000000000
--- a/tensorflow/lite/models/smartreply/ops/extract_feature_test.cc
+++ /dev/null
@@ -1,100 +0,0 @@
-/* Copyright 2017 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 <vector>
-
-#include <gtest/gtest.h>
-#include "tensorflow/lite/interpreter.h"
-#include "tensorflow/lite/kernels/register.h"
-#include "tensorflow/lite/kernels/test_util.h"
-#include "tensorflow/lite/model.h"
-#include <farmhash.h>
-
-namespace tflite {
-
-namespace ops {
-namespace custom {
-TfLiteRegistration* Register_EXTRACT_FEATURES();
-
-namespace {
-
-using ::testing::ElementsAre;
-
-class ExtractFeatureOpModel : public SingleOpModel {
- public:
-  explicit ExtractFeatureOpModel(const std::vector<string>& input) {
-    input_ = AddInput(TensorType_STRING);
-    signature_ = AddOutput(TensorType_INT32);
-    weight_ = AddOutput(TensorType_FLOAT32);
-
-    SetCustomOp("ExtractFeatures", {}, Register_EXTRACT_FEATURES);
-    BuildInterpreter({{static_cast<int>(input.size())}});
-    PopulateStringTensor(input_, input);
-  }
-
-  std::vector<int> GetSignature() { return ExtractVector<int>(signature_); }
-  std::vector<float> GetWeight() { return ExtractVector<float>(weight_); }
-
- private:
-  int input_;
-  int signature_;
-  int weight_;
-};
-
-int CalcFeature(const string& str) {
-  return ::util::Fingerprint64(str) % 1000000;
-}
-
-TEST(ExtractFeatureOpTest, RegularInput) {
-  ExtractFeatureOpModel m({"<S>", "<S> Hi", "Hi", "Hi !", "!", "! <E>", "<E>"});
-  m.Invoke();
-  EXPECT_THAT(m.GetSignature(),
-              ElementsAre(0, CalcFeature("<S> Hi"), CalcFeature("Hi"),
-                          CalcFeature("Hi !"), CalcFeature("!"),
-                          CalcFeature("! <E>"), 0));
-  EXPECT_THAT(m.GetWeight(), ElementsAre(0, 2, 1, 2, 1, 2, 0));
-}
-
-TEST(ExtractFeatureOpTest, OneInput) {
-  ExtractFeatureOpModel m({"Hi"});
-  m.Invoke();
-  EXPECT_THAT(m.GetSignature(), ElementsAre(CalcFeature("Hi")));
-  EXPECT_THAT(m.GetWeight(), ElementsAre(1));
-}
-
-TEST(ExtractFeatureOpTest, ZeroInput) {
-  ExtractFeatureOpModel m({});
-  m.Invoke();
-  EXPECT_THAT(m.GetSignature(), ElementsAre(0));
-  EXPECT_THAT(m.GetWeight(), ElementsAre(0));
-}
-
-TEST(ExtractFeatureOpTest, AllBlacklistInput) {
-  ExtractFeatureOpModel m({"<S>", "<E>"});
-  m.Invoke();
-  EXPECT_THAT(m.GetSignature(), ElementsAre(0, 0));
-  EXPECT_THAT(m.GetWeight(), ElementsAre(0, 0));
-}
-
-}  // namespace
-}  // namespace custom
-}  // namespace ops
-}  // namespace tflite
-
-int main(int argc, char** argv) {
-  ::tflite::LogToStderr();
-  ::testing::InitGoogleTest(&argc, argv);
-  return RUN_ALL_TESTS();
-}
diff --git a/tensorflow/lite/models/smartreply/ops/normalize.cc b/tensorflow/lite/models/smartreply/ops/normalize.cc
deleted file mode 100644
index 3cb11cc055b..00000000000
--- a/tensorflow/lite/models/smartreply/ops/normalize.cc
+++ /dev/null
@@ -1,108 +0,0 @@
-/* Copyright 2017 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.
-==============================================================================*/
-
-// Normalize the string input.
-//
-// Input:
-//     Input[0]: One sentence. string[1]
-//
-// Output:
-//     Output[0]: Normalized sentence. string[1]
-//
-
-#include <algorithm>
-#include <string>
-
-#include "absl/strings/str_cat.h"
-#include "absl/strings/strip.h"
-#include "re2/re2.h"
-#include "tensorflow/lite/context.h"
-#include "tensorflow/lite/kernels/kernel_util.h"
-#include "tensorflow/lite/string_util.h"
-
-namespace tflite {
-namespace ops {
-namespace custom {
-
-namespace normalize {
-
-// Predictor transforms.
-const char kPunctuationsRegex[] = "[.*()\"]";
-
-const std::map<string, string>* kRegexTransforms =
-    new std::map<string, string>({
-        {"([^\\s]+)n't", "\\1 not"},
-        {"([^\\s]+)'nt", "\\1 not"},
-        {"([^\\s]+)'ll", "\\1 will"},
-        {"([^\\s]+)'re", "\\1 are"},
-        {"([^\\s]+)'ve", "\\1 have"},
-        {"i'm", "i am"},
-    });
-
-static const char kStartToken[] = "<S>";
-static const char kEndToken[] = "<E>";
-static const int32_t kMaxInputChars = 300;
-
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
-  tflite::StringRef input = tflite::GetString(GetInput(context, node, 0), 0);
-
-  string result(absl::AsciiStrToLower(absl::string_view(input.str, input.len)));
-  absl::StripAsciiWhitespace(&result);
-  // Do not remove commas, semi-colons or colons from the sentences as they can
-  // indicate the beginning of a new clause.
-  RE2::GlobalReplace(&result, kPunctuationsRegex, "");
-  RE2::GlobalReplace(&result, "\\s('t|'nt|n't|'d|'ll|'s|'m|'ve|'re)([\\s,;:/])",
-                     "\\1\\2");
-  RE2::GlobalReplace(&result, "\\s('t|'nt|n't|'d|'ll|'s|'m|'ve|'re)$", "\\1");
-  for (auto iter = kRegexTransforms->begin(); iter != kRegexTransforms->end();
-       iter++) {
-    RE2::GlobalReplace(&result, iter->first, iter->second);
-  }
-
-  // Treat questions & interjections as special cases.
-  RE2::GlobalReplace(&result, "([?])+", "\\1");
-  RE2::GlobalReplace(&result, "([!])+", "\\1");
-  RE2::GlobalReplace(&result, "([^?!]+)([?!])", "\\1 \\2 ");
-  RE2::GlobalReplace(&result, "([?!])([?!])", "\\1 \\2");
-
-  RE2::GlobalReplace(&result, "[\\s,:;\\-&'\"]+$", "");
-  RE2::GlobalReplace(&result, "^[\\s,:;\\-&'\"]+", "");
-  absl::StripAsciiWhitespace(&result);
-
-  // Add start and end token.
-  // Truncate input to maximum allowed size.
-  if (result.length() <= kMaxInputChars) {
-    absl::StrAppend(&result, " ", kEndToken);
-  } else {
-    result = result.substr(0, kMaxInputChars);
-  }
-  result = absl::StrCat(kStartToken, " ", result);
-
-  tflite::DynamicBuffer buf;
-  buf.AddString(result.data(), result.length());
-  buf.WriteToTensorAsVector(GetOutput(context, node, 0));
-  return kTfLiteOk;
-}
-
-}  // namespace normalize
-
-TfLiteRegistration* Register_NORMALIZE() {
-  static TfLiteRegistration r = {nullptr, nullptr, nullptr, normalize::Eval};
-  return &r;
-}
-
-}  // namespace custom
-}  // namespace ops
-}  // namespace tflite
diff --git a/tensorflow/lite/models/smartreply/ops/normalize_test.cc b/tensorflow/lite/models/smartreply/ops/normalize_test.cc
deleted file mode 100644
index 46d2aebe756..00000000000
--- a/tensorflow/lite/models/smartreply/ops/normalize_test.cc
+++ /dev/null
@@ -1,90 +0,0 @@
-/* Copyright 2017 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 <vector>
-
-#include <gtest/gtest.h>
-#include "tensorflow/lite/interpreter.h"
-#include "tensorflow/lite/kernels/register.h"
-#include "tensorflow/lite/kernels/test_util.h"
-#include "tensorflow/lite/model.h"
-#include "tensorflow/lite/string_util.h"
-
-namespace tflite {
-
-namespace ops {
-namespace custom {
-TfLiteRegistration* Register_NORMALIZE();
-
-namespace {
-
-using ::testing::ElementsAreArray;
-
-class NormalizeOpModel : public SingleOpModel {
- public:
-  explicit NormalizeOpModel(const string& input) {
-    input_ = AddInput(TensorType_STRING);
-    output_ = AddOutput(TensorType_STRING);
-
-    SetCustomOp("Normalize", {}, Register_NORMALIZE);
-    BuildInterpreter({{static_cast<int>(input.size())}});
-    PopulateStringTensor(input_, {input});
-  }
-
-  std::vector<string> GetStringOutput() {
-    TfLiteTensor* output = interpreter_->tensor(output_);
-    int num = GetStringCount(output);
-    std::vector<string> result(num);
-    for (int i = 0; i < num; i++) {
-      auto ref = GetString(output, i);
-      result[i] = string(ref.str, ref.len);
-    }
-    return result;
-  }
-
- private:
-  int input_;
-  int output_;
-};
-
-TEST(NormalizeOpTest, RegularInput) {
-  NormalizeOpModel m("I'm good; you're welcome");
-  m.Invoke();
-  EXPECT_THAT(m.GetStringOutput(),
-              ElementsAreArray({"<S> i am good; you are welcome <E>"}));
-}
-
-TEST(NormalizeOpTest, OneInput) {
-  NormalizeOpModel m("Hi!!!!");
-  m.Invoke();
-  EXPECT_THAT(m.GetStringOutput(), ElementsAreArray({"<S> hi ! <E>"}));
-}
-
-TEST(NormalizeOpTest, EmptyInput) {
-  NormalizeOpModel m("");
-  m.Invoke();
-  EXPECT_THAT(m.GetStringOutput(), ElementsAreArray({"<S>  <E>"}));
-}
-
-}  // namespace
-}  // namespace custom
-}  // namespace ops
-}  // namespace tflite
-
-int main(int argc, char** argv) {
-  ::tflite::LogToStderr();
-  ::testing::InitGoogleTest(&argc, argv);
-  return RUN_ALL_TESTS();
-}
diff --git a/tensorflow/lite/models/smartreply/ops/predict.cc b/tensorflow/lite/models/smartreply/ops/predict.cc
deleted file mode 100644
index 38ebe8b9810..00000000000
--- a/tensorflow/lite/models/smartreply/ops/predict.cc
+++ /dev/null
@@ -1,176 +0,0 @@
-/* Copyright 2017 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.
-==============================================================================*/
-
-// Lookup projected hash signatures in Predictor model,
-// output predicted labels and weights in decreasing order.
-//
-// Input:
-//     Input[0]: A list of hash signatures. int32[num of input]
-//     Input[1]: Hash signature keys in the model. int32[keys of model]
-//     Input[2]: Labels in the model. int32[keys of model, item per entry]
-//     Input[3]: Weights in the model. float[keys of model, item per entry]
-//
-// Output:
-//     Output[0]: Predicted labels. int32[num of output]
-//     Output[1]: Predicted weights. float[num of output]
-//
-
-#include <algorithm>
-#include <cstdlib>
-#include <cstdio>
-#include <unordered_map>
-#include <vector>
-
-#include "tensorflow/lite/context.h"
-
-namespace tflite {
-namespace ops {
-namespace custom {
-
-namespace predict {
-
-struct PredictOption {
-  int32_t num_output;
-  float weight_threshold;
-
-  static PredictOption* Cast(void* ptr) {
-    return reinterpret_cast<PredictOption*>(ptr);
-  }
-};
-
-bool WeightGreater(const std::pair<int32_t, float>& a,
-                   const std::pair<int32_t, float>& b) {
-  return a.second > b.second;
-}
-
-void* Init(TfLiteContext* context, const char* custom_option, size_t length) {
-  if (custom_option == nullptr || length != sizeof(PredictOption)) {
-    fprintf(stderr, "No Custom option set\n");
-    exit(1);
-  }
-  PredictOption* option = new PredictOption;
-  int offset = 0;
-  option->num_output =
-      *reinterpret_cast<const int32_t*>(custom_option + offset);
-  offset += sizeof(int32_t);
-  option->weight_threshold =
-      *reinterpret_cast<const float*>(custom_option + offset);
-  return reinterpret_cast<void*>(option);
-}
-
-void Free(TfLiteContext* context, void* buffer) {
-  delete PredictOption::Cast(buffer);
-}
-
-TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
-  TF_LITE_ENSURE_EQ(context, node->inputs->size, 4);
-  TF_LITE_ENSURE_EQ(context, node->outputs->size, 2);
-
-  TfLiteTensor* lookup = &context->tensors[node->inputs->data[0]];
-  TfLiteTensor* model_key = &context->tensors[node->inputs->data[1]];
-  TfLiteTensor* model_label = &context->tensors[node->inputs->data[2]];
-  TfLiteTensor* model_weight = &context->tensors[node->inputs->data[3]];
-  TF_LITE_ENSURE_EQ(context, lookup->type, kTfLiteInt32);
-  TF_LITE_ENSURE_EQ(context, model_key->type, kTfLiteInt32);
-  TF_LITE_ENSURE_EQ(context, model_label->type, kTfLiteInt32);
-  TF_LITE_ENSURE_EQ(context, model_weight->type, kTfLiteFloat32);
-  TF_LITE_ENSURE_EQ(context, lookup->dims->size, 1);
-  TF_LITE_ENSURE_EQ(context, model_key->dims->size, 1);
-  TF_LITE_ENSURE_EQ(context, model_label->dims->size, 2);
-  TF_LITE_ENSURE_EQ(context, model_weight->dims->size, 2);
-  TF_LITE_ENSURE_EQ(context, model_key->dims->data[0],
-                    model_label->dims->data[0]);
-  TF_LITE_ENSURE_EQ(context, model_key->dims->data[0],
-                    model_weight->dims->data[0]);
-  TF_LITE_ENSURE_EQ(context, model_label->dims->data[1],
-                    model_weight->dims->data[1]);
-
-  PredictOption* option = PredictOption::Cast(node->user_data);
-  TfLiteTensor* output_label = &context->tensors[node->outputs->data[0]];
-  TfLiteTensor* output_weight = &context->tensors[node->outputs->data[1]];
-  TF_LITE_ENSURE_EQ(context, output_label->type, kTfLiteInt32);
-  TF_LITE_ENSURE_EQ(context, output_weight->type, kTfLiteFloat32);
-
-  TfLiteIntArray* label_size = TfLiteIntArrayCreate(1);
-  label_size->data[0] = option->num_output;
-  TfLiteIntArray* weight_size = TfLiteIntArrayCreate(1);
-  weight_size->data[0] = option->num_output;
-  TfLiteStatus status =
-      context->ResizeTensor(context, output_label, label_size);
-  if (status != kTfLiteOk) {
-    return status;
-  }
-  return context->ResizeTensor(context, output_weight, weight_size);
-}
-
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
-  TfLiteTensor* lookup = &context->tensors[node->inputs->data[0]];
-  TfLiteTensor* model_key = &context->tensors[node->inputs->data[1]];
-  TfLiteTensor* model_label = &context->tensors[node->inputs->data[2]];
-  TfLiteTensor* model_weight = &context->tensors[node->inputs->data[3]];
-
-  // Aggregate by key
-  std::unordered_map<int32_t, float> aggregation;
-  const int num_input = lookup->dims->data[0];
-  const int num_rows = model_key->dims->data[0];
-  const int items = model_label->dims->data[1];
-  int* model_key_end = model_key->data.i32 + num_rows;
-
-  for (int i = 0; i < num_input; i++) {
-    int* ptr = std::lower_bound(model_key->data.i32, model_key_end,
-                                lookup->data.i32[i]);
-    if (ptr != nullptr && ptr != model_key_end && *ptr == lookup->data.i32[i]) {
-      int idx = ptr - model_key->data.i32;
-      for (int j = 0; j < items; j++) {
-        aggregation[model_label->data.i32[idx * items + j]] +=
-            model_weight->data.f[idx * items + j] / num_input;
-      }
-    }
-  }
-
-  // Sort by value
-  std::vector<std::pair<int32_t, float>> sorted_labels(aggregation.begin(),
-                                                       aggregation.end());
-  std::sort(sorted_labels.begin(), sorted_labels.end(), WeightGreater);
-
-  PredictOption* option = PredictOption::Cast(node->user_data);
-  TfLiteTensor* output_label = &context->tensors[node->outputs->data[0]];
-  TfLiteTensor* output_weight = &context->tensors[node->outputs->data[1]];
-  for (int i = 0; i < output_label->dims->data[0]; i++) {
-    if (i >= sorted_labels.size() ||
-        sorted_labels[i].second < option->weight_threshold) {
-      // Set -1 to avoid lookup message with id 0, which is set for backoff.
-      output_label->data.i32[i] = -1;
-      output_weight->data.f[i] = 0.0f;
-    } else {
-      output_label->data.i32[i] = sorted_labels[i].first;
-      output_weight->data.f[i] = sorted_labels[i].second;
-    }
-  }
-
-  return kTfLiteOk;
-}
-
-}  // namespace predict
-
-TfLiteRegistration* Register_PREDICT() {
-  static TfLiteRegistration r = {predict::Init, predict::Free, predict::Prepare,
-                                 predict::Eval};
-  return &r;
-}
-
-}  // namespace custom
-}  // namespace ops
-}  // namespace tflite
diff --git a/tensorflow/lite/models/smartreply/ops/predict_test.cc b/tensorflow/lite/models/smartreply/ops/predict_test.cc
deleted file mode 100644
index 6896a342c79..00000000000
--- a/tensorflow/lite/models/smartreply/ops/predict_test.cc
+++ /dev/null
@@ -1,183 +0,0 @@
-/* Copyright 2017 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 <vector>
-
-#include <gtest/gtest.h>
-#include "tensorflow/lite/interpreter.h"
-#include "tensorflow/lite/kernels/register.h"
-#include "tensorflow/lite/kernels/test_util.h"
-#include "tensorflow/lite/model.h"
-#include "tensorflow/lite/string_util.h"
-
-namespace tflite {
-
-namespace ops {
-namespace custom {
-TfLiteRegistration* Register_PREDICT();
-
-namespace {
-
-using ::testing::ElementsAreArray;
-
-class PredictOpModel : public SingleOpModel {
- public:
-  PredictOpModel(std::initializer_list<int> input_signature_shape,
-                 std::initializer_list<int> key_shape,
-                 std::initializer_list<int> labelweight_shape, int num_output,
-                 float threshold) {
-    input_signature_ = AddInput(TensorType_INT32);
-    model_key_ = AddInput(TensorType_INT32);
-    model_label_ = AddInput(TensorType_INT32);
-    model_weight_ = AddInput(TensorType_FLOAT32);
-    output_label_ = AddOutput(TensorType_INT32);
-    output_weight_ = AddOutput(TensorType_FLOAT32);
-
-    std::vector<uint8_t> predict_option;
-    writeInt32(num_output, &predict_option);
-    writeFloat32(threshold, &predict_option);
-    SetCustomOp("Predict", predict_option, Register_PREDICT);
-    BuildInterpreter({{input_signature_shape, key_shape, labelweight_shape,
-                       labelweight_shape}});
-  }
-
-  void SetInputSignature(std::initializer_list<int> data) {
-    PopulateTensor<int>(input_signature_, data);
-  }
-
-  void SetModelKey(std::initializer_list<int> data) {
-    PopulateTensor<int>(model_key_, data);
-  }
-
-  void SetModelLabel(std::initializer_list<int> data) {
-    PopulateTensor<int>(model_label_, data);
-  }
-
-  void SetModelWeight(std::initializer_list<float> data) {
-    PopulateTensor<float>(model_weight_, data);
-  }
-
-  std::vector<int> GetLabel() { return ExtractVector<int>(output_label_); }
-  std::vector<float> GetWeight() {
-    return ExtractVector<float>(output_weight_);
-  }
-
-  void writeFloat32(float value, std::vector<uint8_t>* data) {
-    union {
-      float v;
-      uint8_t r[4];
-    } float_to_raw;
-    float_to_raw.v = value;
-    for (unsigned char i : float_to_raw.r) {
-      data->push_back(i);
-    }
-  }
-
-  void writeInt32(int32_t value, std::vector<uint8_t>* data) {
-    union {
-      int32_t v;
-      uint8_t r[4];
-    } int32_to_raw;
-    int32_to_raw.v = value;
-    for (unsigned char i : int32_to_raw.r) {
-      data->push_back(i);
-    }
-  }
-
- private:
-  int input_signature_;
-  int model_key_;
-  int model_label_;
-  int model_weight_;
-  int output_label_;
-  int output_weight_;
-};
-
-TEST(PredictOpTest, AllLabelsAreValid) {
-  PredictOpModel m({4}, {5}, {5, 2}, 2, 0.0001);
-  m.SetInputSignature({1, 3, 7, 9});
-  m.SetModelKey({1, 2, 4, 6, 7});
-  m.SetModelLabel({11, 12, 11, 12, 11, 12, 11, 12, 11, 12});
-  m.SetModelWeight({0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0.2});
-  m.Invoke();
-  EXPECT_THAT(m.GetLabel(), ElementsAreArray({12, 11}));
-  EXPECT_THAT(m.GetWeight(), ElementsAreArray(ArrayFloatNear({0.1, 0.05})));
-}
-
-TEST(PredictOpTest, MoreLabelsThanRequired) {
-  PredictOpModel m({4}, {5}, {5, 2}, 1, 0.0001);
-  m.SetInputSignature({1, 3, 7, 9});
-  m.SetModelKey({1, 2, 4, 6, 7});
-  m.SetModelLabel({11, 12, 11, 12, 11, 12, 11, 12, 11, 12});
-  m.SetModelWeight({0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0.2});
-  m.Invoke();
-  EXPECT_THAT(m.GetLabel(), ElementsAreArray({12}));
-  EXPECT_THAT(m.GetWeight(), ElementsAreArray(ArrayFloatNear({0.1})));
-}
-
-TEST(PredictOpTest, OneLabelDoesNotPassThreshold) {
-  PredictOpModel m({4}, {5}, {5, 2}, 2, 0.07);
-  m.SetInputSignature({1, 3, 7, 9});
-  m.SetModelKey({1, 2, 4, 6, 7});
-  m.SetModelLabel({11, 12, 11, 12, 11, 12, 11, 12, 11, 12});
-  m.SetModelWeight({0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0.2});
-  m.Invoke();
-  EXPECT_THAT(m.GetLabel(), ElementsAreArray({12, -1}));
-  EXPECT_THAT(m.GetWeight(), ElementsAreArray(ArrayFloatNear({0.1, 0})));
-}
-
-TEST(PredictOpTest, NoneLabelPassThreshold) {
-  PredictOpModel m({4}, {5}, {5, 2}, 2, 0.6);
-  m.SetInputSignature({1, 3, 7, 9});
-  m.SetModelKey({1, 2, 4, 6, 7});
-  m.SetModelLabel({11, 12, 11, 12, 11, 12, 11, 12, 11, 12});
-  m.SetModelWeight({0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0.2, 0.1, 0.2});
-  m.Invoke();
-  EXPECT_THAT(m.GetLabel(), ElementsAreArray({-1, -1}));
-  EXPECT_THAT(m.GetWeight(), ElementsAreArray(ArrayFloatNear({0, 0})));
-}
-
-TEST(PredictOpTest, OnlyOneLabelGenerated) {
-  PredictOpModel m({4}, {5}, {5, 2}, 2, 0.0001);
-  m.SetInputSignature({1, 3, 7, 9});
-  m.SetModelKey({1, 2, 4, 6, 7});
-  m.SetModelLabel({11, 0, 11, 0, 11, 0, 11, 0, 11, 0});
-  m.SetModelWeight({0.1, 0, 0.1, 0, 0.1, 0, 0.1, 0, 0.1, 0});
-  m.Invoke();
-  EXPECT_THAT(m.GetLabel(), ElementsAreArray({11, -1}));
-  EXPECT_THAT(m.GetWeight(), ElementsAreArray(ArrayFloatNear({0.05, 0})));
-}
-
-TEST(PredictOpTest, NoLabelGenerated) {
-  PredictOpModel m({4}, {5}, {5, 2}, 2, 0.0001);
-  m.SetInputSignature({5, 3, 7, 9});
-  m.SetModelKey({1, 2, 4, 6, 7});
-  m.SetModelLabel({11, 0, 11, 0, 11, 0, 11, 0, 0, 0});
-  m.SetModelWeight({0.1, 0, 0.1, 0, 0.1, 0, 0.1, 0, 0, 0});
-  m.Invoke();
-  EXPECT_THAT(m.GetLabel(), ElementsAreArray({-1, -1}));
-  EXPECT_THAT(m.GetWeight(), ElementsAreArray(ArrayFloatNear({0, 0})));
-}
-
-}  // namespace
-}  // namespace custom
-}  // namespace ops
-}  // namespace tflite
-
-int main(int argc, char** argv) {
-  ::tflite::LogToStderr();
-  ::testing::InitGoogleTest(&argc, argv);
-  return RUN_ALL_TESTS();
-}
diff --git a/tensorflow/lite/models/smartreply/predictor.cc b/tensorflow/lite/models/smartreply/predictor.cc
deleted file mode 100644
index 59bf4a3cf1e..00000000000
--- a/tensorflow/lite/models/smartreply/predictor.cc
+++ /dev/null
@@ -1,117 +0,0 @@
-/* Copyright 2017 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/lite/models/smartreply/predictor.h"
-
-#include "absl/strings/str_split.h"
-#include "re2/re2.h"
-#include "tensorflow/lite/interpreter.h"
-#include "tensorflow/lite/kernels/register.h"
-#include "tensorflow/lite/model.h"
-#include "tensorflow/lite/op_resolver.h"
-#include "tensorflow/lite/string_util.h"
-
-void RegisterSelectedOps(::tflite::MutableOpResolver* resolver);
-
-namespace tflite {
-namespace custom {
-namespace smartreply {
-
-// Split sentence into segments (using punctuation).
-std::vector<std::string> SplitSentence(const std::string& input) {
-  string result(input);
-
-  RE2::GlobalReplace(&result, "([?.!,])+", " \\1");
-  RE2::GlobalReplace(&result, "([?.!,])+\\s+", "\\1\t");
-  RE2::GlobalReplace(&result, "[ ]+", " ");
-  RE2::GlobalReplace(&result, "\t+$", "");
-
-  return absl::StrSplit(result, '\t');
-}
-
-// Predict with TfLite model.
-void ExecuteTfLite(const std::string& sentence,
-                   ::tflite::Interpreter* interpreter,
-                   std::map<std::string, float>* response_map) {
-  {
-    TfLiteTensor* input = interpreter->tensor(interpreter->inputs()[0]);
-    tflite::DynamicBuffer buf;
-    buf.AddString(sentence.data(), sentence.length());
-    buf.WriteToTensorAsVector(input);
-    interpreter->AllocateTensors();
-
-    interpreter->Invoke();
-
-    TfLiteTensor* messages = interpreter->tensor(interpreter->outputs()[0]);
-    TfLiteTensor* confidence = interpreter->tensor(interpreter->outputs()[1]);
-
-    for (int i = 0; i < confidence->dims->data[0]; i++) {
-      float weight = confidence->data.f[i];
-      auto response_text = tflite::GetString(messages, i);
-      if (response_text.len > 0) {
-        (*response_map)[string(response_text.str, response_text.len)] += weight;
-      }
-    }
-  }
-}
-
-void GetSegmentPredictions(
-    const std::vector<std::string>& input,
-    const ::tflite::FlatBufferModel& model, const SmartReplyConfig& config,
-    std::vector<PredictorResponse>* predictor_responses) {
-  // Initialize interpreter
-  std::unique_ptr<::tflite::Interpreter> interpreter;
-  ::tflite::MutableOpResolver resolver;
-  RegisterSelectedOps(&resolver);
-  ::tflite::InterpreterBuilder(model, resolver)(&interpreter);
-
-  if (!model.initialized()) {
-    fprintf(stderr, "Failed to mmap model \n");
-    return;
-  }
-
-  // Execute Tflite Model
-  std::map<std::string, float> response_map;
-  std::vector<std::string> sentences;
-  for (const std::string& str : input) {
-    std::vector<std::string> splitted_str = SplitSentence(str);
-    sentences.insert(sentences.end(), splitted_str.begin(), splitted_str.end());
-  }
-  for (const auto& sentence : sentences) {
-    ExecuteTfLite(sentence, interpreter.get(), &response_map);
-  }
-
-  // Generate the result.
-  for (const auto& iter : response_map) {
-    PredictorResponse prediction(iter.first, iter.second);
-    predictor_responses->emplace_back(prediction);
-  }
-  std::sort(predictor_responses->begin(), predictor_responses->end(),
-            [](const PredictorResponse& a, const PredictorResponse& b) {
-              return a.GetScore() > b.GetScore();
-            });
-
-  // Add backoff response.
-  for (const auto& backoff : config.backoff_responses) {
-    if (predictor_responses->size() >= config.num_response) {
-      break;
-    }
-    predictor_responses->emplace_back(backoff, config.backoff_confidence);
-  }
-}
-
-}  // namespace smartreply
-}  // namespace custom
-}  // namespace tflite
diff --git a/tensorflow/lite/models/smartreply/predictor.h b/tensorflow/lite/models/smartreply/predictor.h
deleted file mode 100644
index 6b8f9298a36..00000000000
--- a/tensorflow/lite/models/smartreply/predictor.h
+++ /dev/null
@@ -1,80 +0,0 @@
-/* Copyright 2017 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.
-==============================================================================*/
-
-#ifndef TENSORFLOW_LITE_MODELS_SMARTREPLY_PREDICTOR_H_
-#define TENSORFLOW_LITE_MODELS_SMARTREPLY_PREDICTOR_H_
-
-#include <string>
-#include <vector>
-
-#include "tensorflow/lite/model.h"
-
-namespace tflite {
-namespace custom {
-namespace smartreply {
-
-const int kDefaultNumResponse = 10;
-const float kDefaultBackoffConfidence = 1e-4;
-
-class PredictorResponse;
-struct SmartReplyConfig;
-
-// With a given string as input, predict the response with a Tflite model.
-// When config.backoff_response is not empty, predictor_responses will be filled
-// with messagees from backoff response.
-void GetSegmentPredictions(const std::vector<std::string>& input,
-                           const ::tflite::FlatBufferModel& model,
-                           const SmartReplyConfig& config,
-                           std::vector<PredictorResponse>* predictor_responses);
-
-// Data object used to hold a single predictor response.
-// It includes messages, and confidence.
-class PredictorResponse {
- public:
-  PredictorResponse(const std::string& response_text, float score) {
-    response_text_ = response_text;
-    prediction_score_ = score;
-  }
-
-  // Accessor methods.
-  const std::string& GetText() const { return response_text_; }
-  float GetScore() const { return prediction_score_; }
-
- private:
-  std::string response_text_ = "";
-  float prediction_score_ = 0.0;
-};
-
-// Configurations for SmartReply.
-struct SmartReplyConfig {
-  // Maximum responses to return.
-  int num_response;
-  // Default confidence for backoff responses.
-  float backoff_confidence;
-  // Backoff responses are used when predicted responses cannot fulfill the
-  // list.
-  std::vector<std::string> backoff_responses;
-
-  SmartReplyConfig(const std::vector<std::string>& backoff_responses)
-      : num_response(kDefaultNumResponse),
-        backoff_confidence(kDefaultBackoffConfidence),
-        backoff_responses(backoff_responses) {}
-};
-
-}  // namespace smartreply
-}  // namespace custom
-}  // namespace tflite
-
-#endif  // TENSORFLOW_LITE_MODELS_SMARTREPLY_PREDICTOR_H_
diff --git a/tensorflow/lite/models/smartreply/predictor_test.cc b/tensorflow/lite/models/smartreply/predictor_test.cc
deleted file mode 100644
index f4a9453b422..00000000000
--- a/tensorflow/lite/models/smartreply/predictor_test.cc
+++ /dev/null
@@ -1,163 +0,0 @@
-/* Copyright 2017 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/lite/models/smartreply/predictor.h"
-
-#include <fstream>
-#include <unordered_set>
-
-#include <gmock/gmock.h>
-#include <gtest/gtest.h>
-#include "absl/strings/str_cat.h"
-#include "absl/strings/str_split.h"
-#include "tensorflow/core/platform/test.h"
-#include "tensorflow/lite/string_util.h"
-#include "tensorflow/lite/testing/util.h"
-
-namespace tflite {
-namespace custom {
-namespace smartreply {
-namespace {
-
-const char kSamples[] = "smartreply_samples.tsv";
-
-string GetModelFilePath() {
-  return "external/tflite_smartreply/smartreply.tflite";  // NOLINT
-}
-
-string GetSamplesFilePath() {
-  return string(absl::StrCat(tensorflow::testing::TensorFlowSrcRoot(), "/",
-                             "lite/models/testdata/", kSamples));
-}
-
-MATCHER_P(IncludeAnyResponesIn, expected_response, "contains the response") {
-  bool has_expected_response = false;
-  for (const auto &item : *arg) {
-    const string &response = item.GetText();
-    if (expected_response.find(response) != expected_response.end()) {
-      has_expected_response = true;
-      break;
-    }
-  }
-  return has_expected_response;
-}
-
-class PredictorTest : public ::testing::Test {
- protected:
-  PredictorTest() {}
-  ~PredictorTest() override {}
-
-  void SetUp() override {
-    model_ = tflite::FlatBufferModel::BuildFromFile(GetModelFilePath().c_str());
-    ASSERT_NE(model_.get(), nullptr);
-  }
-
-  std::unique_ptr<::tflite::FlatBufferModel> model_;
-};
-
-TEST_F(PredictorTest, GetSegmentPredictions) {
-  std::vector<PredictorResponse> predictions;
-
-  GetSegmentPredictions({"Welcome"}, *model_, /*config=*/{{}}, &predictions);
-  EXPECT_GT(predictions.size(), 0);
-
-  float max = 0;
-  for (const auto &item : predictions) {
-    if (item.GetScore() > max) {
-      max = item.GetScore();
-    }
-  }
-
-  EXPECT_GT(max, 0.3);
-  EXPECT_THAT(
-      &predictions,
-      IncludeAnyResponesIn(std::unordered_set<string>({"Thanks very much"})));
-}
-
-TEST_F(PredictorTest, TestTwoSentences) {
-  std::vector<PredictorResponse> predictions;
-
-  GetSegmentPredictions({"Hello", "How are you?"}, *model_, /*config=*/{{}},
-                        &predictions);
-  EXPECT_GT(predictions.size(), 0);
-
-  float max = 0;
-  for (const auto &item : predictions) {
-    if (item.GetScore() > max) {
-      max = item.GetScore();
-    }
-  }
-
-  EXPECT_GT(max, 0.3);
-  EXPECT_THAT(&predictions, IncludeAnyResponesIn(std::unordered_set<string>(
-                                {"Hi, how are you doing?"})));
-}
-
-TEST_F(PredictorTest, TestBackoff) {
-  std::vector<PredictorResponse> predictions;
-
-  GetSegmentPredictions({"你好"}, *model_, /*config=*/{{}}, &predictions);
-  EXPECT_EQ(predictions.size(), 0);
-
-  // Backoff responses are returned in order.
-  GetSegmentPredictions({"你好"}, *model_, /*config=*/{{"Yes", "Ok"}},
-                        &predictions);
-  EXPECT_EQ(predictions.size(), 2);
-  EXPECT_EQ(predictions[0].GetText(), "Yes");
-  EXPECT_EQ(predictions[1].GetText(), "Ok");
-}
-
-TEST_F(PredictorTest, BatchTest) {
-  int total_items = 0;
-  int total_responses = 0;
-  int total_triggers = 0;
-
-  string line;
-  std::ifstream fin(GetSamplesFilePath());
-  while (std::getline(fin, line)) {
-    const std::vector<string> fields = absl::StrSplit(line, '\t');
-    if (fields.empty()) {
-      continue;
-    }
-
-    // Parse sample file and predict
-    const string &msg = fields[0];
-    std::vector<PredictorResponse> predictions;
-    GetSegmentPredictions({msg}, *model_, /*config=*/{{}}, &predictions);
-
-    // Validate response and generate stats.
-    total_items++;
-    total_responses += predictions.size();
-    if (!predictions.empty()) {
-      total_triggers++;
-    }
-    EXPECT_THAT(&predictions, IncludeAnyResponesIn(std::unordered_set<string>(
-                                  fields.begin() + 1, fields.end())));
-  }
-
-  EXPECT_EQ(total_triggers, total_items);
-  EXPECT_GE(total_responses, total_triggers);
-}
-
-}  // namespace
-}  // namespace smartreply
-}  // namespace custom
-}  // namespace tflite
-
-int main(int argc, char **argv) {
-  ::tflite::LogToStderr();
-  ::testing::InitGoogleTest(&argc, argv);
-  return RUN_ALL_TESTS();
-}
diff --git a/tensorflow/lite/models/testdata/smartreply_samples.tsv b/tensorflow/lite/models/testdata/smartreply_samples.tsv
deleted file mode 100644
index dfdc7831060..00000000000
--- a/tensorflow/lite/models/testdata/smartreply_samples.tsv
+++ /dev/null
@@ -1,50 +0,0 @@
-any chance ur free tonight	Maybe not
-any updates?	No update yet
-anything i can do to help?	No, but thanks	No, but thank you	No, but thanks for asking
-be safe.	I will be	Will do my best	Thanks, I will
-congratulations	Thanks thanks	Congratulations
-cool, let me know when you have time	Cool	Yes very cool	Yeah, cool
-drive safe	Thank you, I will	Home now	I will thanks
-hang in there, you'll be okay	Doing my best	Of course we will
-happy birthday!	Hey, thanks
-happy new year!	Wish you the same	Thanks and same to you
-have a safe flight	Thanks, love you too	Safe travels
-hey	What is up?	How it going?	Can I help you?
-hey, got a sec?	What is up?	How it going?	Can I help you?
-how are you doing?	Great and you?	I am doing great
-how are you feeling	Feeling okay	A little better	Much much better
-how was your weekend?	It was real good
-how you doing	Okay and you
-hugs.	So sweet	Thanks sweetie	Take care of yourself
-i'm bored	Sorry to hear that	Join the club	No you are not
-i'm planning on coming next week. let me know if that works.	Works	Perfect, thanks
-i'm sick	Sorry to hear that
-i'm so happy for you	Thanks me too
-i'm so hungry	Haha me too
-i'm sorry	No I am sorry	Why sorry?	No worries love
-i'm sorry, i'm going to have to cancel.	No I am sorry	Why sorry?	No worries love
-is there anything i can do to help?	No, but thanks	No, but thanks for asking
-lunch?	Yes coming
-okay. lemme know as soon as you find out.	Any more questions?	It is done
-omg amazing	So amazing
-on my way	Okay see you soon	Cool, see you soon	Oh wow, ok
-oops, mistexted.	Oops	Haha, oh well	That was funny
-safe travels.	Thanks, love you too	Safe travels
-so sorry	So sorry
-sorry, i can't.	No worries at all	Sorry what?
-sorry, i can't do saturday	No worries at all
-thank you so much.	You are so welcome	You are so very welcome	You are most welcome
-thanks for coming	It was my pleasure
-thanks, this has been great.	Glad to help	So happy for you
-tomorrow would be ideal.	Yes it would
-tried calling	Try again?
-ugh, my flight is delayed.	Ugh indeed
-what are you guys up to tonight?	Nothing planned
-what day works best for you	Any day
-what do you want for dinner	Your call	Whatever is fine
-what time will you be home?	Not sure why
-where are you?!?	At my house
-wish you were here.	I wish the same	Me too honey
-you're amazing	You are too	You are amazing	I am
-you're marvelous	You are too
-you're the best.	I do my best	You are the best	Well, I try
\ No newline at end of file
diff --git a/tensorflow/workspace.bzl b/tensorflow/workspace.bzl
index 30cdebd4ae9..61517d696cb 100755
--- a/tensorflow/workspace.bzl
+++ b/tensorflow/workspace.bzl
@@ -855,16 +855,6 @@ def tf_repositories(path_prefix = "", tf_repo_name = ""):
         ],
     )
 
-    tf_http_archive(
-        name = "tflite_smartreply",
-        build_file = clean_dep("//third_party:tflite_smartreply.BUILD"),
-        sha256 = "8980151b85a87a9c1a3bb1ed4748119e4a85abd3cb5744d83da4d4bd0fbeef7c",
-        urls = [
-            "https://storage.googleapis.com/mirror.tensorflow.org/storage.googleapis.com/download.tensorflow.org/models/tflite/smartreply_1.0_2017_11_01.zip",
-            "https://storage.googleapis.com/download.tensorflow.org/models/tflite/smartreply_1.0_2017_11_01.zip",
-        ],
-    )
-
     tf_http_archive(
         name = "tflite_ovic_testdata",
         build_file = clean_dep("//third_party:tflite_ovic_testdata.BUILD"),