Move BUILD file to OVIC folder and add model validation.

PiperOrigin-RevId: 196940252

5 files changed, 191 insertions, 57 deletions

diff --git a/tensorflow/contrib/lite/java/BUILD b/tensorflow/contrib/lite/java/BUILD
index 1e57922603..593af81a18 100644
--- a/tensorflow/contrib/lite/java/BUILD
+++ b/tensorflow/contrib/lite/java/BUILD
@@ -1,7 +1,9 @@
 # Description:
 # TensorFlow Lite Java API.
 
-package(default_visibility = ["//visibility:private"])
+package(default_visibility = [
+    "//tensorflow/contrib/lite/java/ovic:__pkg__",
+])
 
 licenses(["notice"])  # Apache 2.0
 
@@ -46,38 +48,6 @@ android_library(
     ],
 )
 
-android_library(
-    name = "ovicbenchmarkerlib",
-    srcs = [
-        "ovic/src/main/java/org/tensorflow/ovic/OvicClassifier.java",
-        "ovic/src/main/java/org/tensorflow/ovic/OvicSingleImageResult.java",
-    ],
-    manifest = "AndroidManifest.xml",
-    visibility = ["//visibility:public"],
-    deps = [
-        ":tensorflowlite",
-        "//tensorflow/contrib/lite/java/src/testhelper/java/org/tensorflow/lite:testhelper",
-        "@org_checkerframework_qual",
-    ],
-)
-
-java_library(
-    name = "ovicbenchmarkerlib_java",
-    srcs = [
-        "ovic/src/main/java/org/tensorflow/ovic/OvicClassifier.java",
-        "ovic/src/main/java/org/tensorflow/ovic/OvicSingleImageResult.java",
-    ],
-    javacopts = JAVACOPTS,
-    visibility = ["//visibility:public"],
-    deps = [
-        ":libtensorflowlite_jni.so",
-        ":tensorflowlite_java",
-        "//tensorflow/contrib/lite/java/src/main/native",
-        "//tensorflow/contrib/lite/java/src/testhelper/java/org/tensorflow/lite:testhelper",
-        "@org_checkerframework_qual",
-    ],
-)
-
 java_library(
     name = "tensorflowlitelib",
     srcs = glob(
@@ -180,24 +150,6 @@ java_test(
     ],
 )
 
-java_test(
-    name = "OvicClassifierTest",
-    size = "medium",
-    srcs = ["ovic/src/test/java/org/tensorflow/ovic/OvicClassifierTest.java"],
-    data = [
-        "//tensorflow/contrib/lite/java/ovic/src/testdata:labels.txt",
-        "//tensorflow/contrib/lite/java/ovic/src/testdata:ovic_testdata",
-    ],
-    javacopts = JAVACOPTS,
-    test_class = "org.tensorflow.ovic.OvicClassifierTest",
-    visibility = ["//visibility:public"],
-    deps = [
-        ":ovicbenchmarkerlib_java",
-        "@com_google_truth",
-        "@junit",
-    ],
-)
-
 filegroup(
     name = "libtensorflowlite_jni",
     srcs = select({
diff --git a/tensorflow/contrib/lite/java/ovic/BUILD b/tensorflow/contrib/lite/java/ovic/BUILD
new file mode 100644
index 0000000000..362d93636f
--- /dev/null
+++ b/tensorflow/contrib/lite/java/ovic/BUILD
@@ -0,0 +1,68 @@
+# Description:
+# OVIC Benchmarker Java API.
+
+package(default_visibility = ["//visibility:public"])
+
+licenses(["notice"])  # Apache 2.0
+
+load("//tensorflow/java:build_defs.bzl", "JAVACOPTS")
+
+java_test(
+    name = "OvicClassifierTest",
+    size = "medium",
+    srcs = ["src/test/java/org/tensorflow/ovic/OvicClassifierTest.java"],
+    data = [
+        "//tensorflow/contrib/lite/java/ovic/src/testdata:labels.txt",
+        "//tensorflow/contrib/lite/java/ovic/src/testdata:ovic_testdata",
+    ],
+    javacopts = JAVACOPTS,
+    test_class = "org.tensorflow.ovic.OvicClassifierTest",
+    visibility = ["//visibility:public"],
+    deps = [
+        "//tensorflow/contrib/lite/java/ovic:ovicbenchmarkerlib_java",
+        "@com_google_truth",
+        "@junit",
+    ],
+)
+
+java_binary(
+    name = "ovic_validator",
+    srcs = ["src/main/java/org/tensorflow/ovic/OvicValidator.java"],
+    data = [
+        "//tensorflow/contrib/lite/java/ovic/src/testdata:labels.txt",
+    ],
+    main_class = "org.tensorflow.ovic.OvicValidator",
+    deps = [
+        "//tensorflow/contrib/lite/java/ovic:ovicbenchmarkerlib_java",
+    ],
+)
+
+android_library(
+    name = "ovicbenchmarkerlib",
+    srcs = [
+        "src/main/java/org/tensorflow/ovic/OvicClassifier.java",
+        "src/main/java/org/tensorflow/ovic/OvicSingleImageResult.java",
+    ],
+    manifest = "//tensorflow/contrib/lite/java:AndroidManifest.xml",
+    deps = [
+        "//tensorflow/contrib/lite/java:tensorflowlite",
+        "//tensorflow/contrib/lite/java/src/testhelper/java/org/tensorflow/lite:testhelper",
+        "@org_checkerframework_qual",
+    ],
+)
+
+java_library(
+    name = "ovicbenchmarkerlib_java",
+    srcs = [
+        "src/main/java/org/tensorflow/ovic/OvicClassifier.java",
+        "src/main/java/org/tensorflow/ovic/OvicSingleImageResult.java",
+    ],
+    javacopts = JAVACOPTS,
+    deps = [
+        "//tensorflow/contrib/lite/java:libtensorflowlite_jni.so",
+        "//tensorflow/contrib/lite/java:tensorflowlite_java",
+        "//tensorflow/contrib/lite/java/src/main/native",
+        "//tensorflow/contrib/lite/java/src/testhelper/java/org/tensorflow/lite:testhelper",
+        "@org_checkerframework_qual",
+    ],
+)
diff --git a/tensorflow/contrib/lite/java/ovic/README.md b/tensorflow/contrib/lite/java/ovic/README.md
index 77799b3569..5efa70987e 100644
--- a/tensorflow/contrib/lite/java/ovic/README.md
+++ b/tensorflow/contrib/lite/java/ovic/README.md
@@ -37,19 +37,37 @@ unzip -j /tmp/ovic.zip -d tensorflow/contrib/lite/java/ovic/src/testdata/
 You can run test with Bazel as below. This helps to ensure that the installation is correct.
 
 ```sh
-bazel test --cxxopt=--std=c++11 //tensorflow/contrib/lite/java:OvicClassifierTest --cxxopt=-Wno-all --test_output=all
+bazel test --cxxopt=--std=c++11 //tensorflow/contrib/lite/java/ovic:OvicClassifierTest --cxxopt=-Wno-all --test_output=all
 ```
 
 ### Test your submissions
 
-Once you have a submission that follows the instructions from the [competition site](https://rebootingcomputing.ieee.org/home/sitemap/14-lpirc/80-low-power-image-recognition-challenge-lpirc-2018), you can verify it as below.
+Once you have a submission that follows the instructions from the [competition site](https://rebootingcomputing.ieee.org/home/sitemap/14-lpirc/80-low-power-image-recognition-challenge-lpirc-2018), you can verify it in two ways:
 
-* Move your submission to the testdata folder:
+#### Validate using randomly generated images
+
+You can call the validator binary below to verify that your model fits the format requirements. This often helps you to catch size mismatches (e.g. output should be [1, 1001] instead of [1,1,1,1001]). Let say the submission file is located at `/path/to/my_model.lite`, then call:
+
+```sh
+bazel build --cxxopt--std=c++11 //tensorflow/contrib/lite/java/ovic:ovic_validator --cxxopt=-Wno-all
+bazel-bin/tensorflow/contrib/lite/java/ovic/ovic_validator /path/to/my_model.lite
+```
+
+Successful validation should print the following message to terminal:
+
+```
+Successfully validated /path/to/my_model.lite.
+
+```
+
+#### Test that the model produces sensible outcomes
 
-Let say the submission file is located at `/tmp/my_model.lite`, then
+You can go a step further to verify that the model produces results as expected. This helps you catch bugs during TOCO conversion (e.g. using the wrong mean and std values).
+
+* Move your submission to the testdata folder:
 
 ```sh
-cp /tmp/my_model.lite tensorflow/contrib/lite/java/ovic/src/testdata/
+cp /path/to/my_model.lite tensorflow/contrib/lite/java/ovic/src/testdata/
 ```
 
 * Resize the test image to the resolutions that are expected by your submission:
@@ -136,3 +154,5 @@ Note: the benchmarking results can be quite different depending on the backgroun
 | quantized_model.lite | 85                    | 74                   |
 |  low_res_model.lite  | 4.2                   | 4.0                  |
 
+Since Pixel 2 has excellent support for 8-bit quantized models, we strongly recommend you to check out the [quantization training tutorial](https://www.tensorflow.org/performance/quantization).
+
diff --git a/tensorflow/contrib/lite/java/ovic/demo/app/BUILD b/tensorflow/contrib/lite/java/ovic/demo/app/BUILD
index 47101ff574..83974f4b33 100644
--- a/tensorflow/contrib/lite/java/ovic/demo/app/BUILD
+++ b/tensorflow/contrib/lite/java/ovic/demo/app/BUILD
@@ -21,8 +21,8 @@ android_binary(
     resource_files = glob(["res/**"]),
     tags = ["manual"],
     deps = [
-        "//tensorflow/contrib/lite/java:ovicbenchmarkerlib",
         "//tensorflow/contrib/lite/java:tensorflowlite",
+        "//tensorflow/contrib/lite/java/ovic:ovicbenchmarkerlib",
         "@androidsdk//com.android.support:support-v13-25.2.0",
         "@androidsdk//com.android.support:support-v4-25.2.0",
     ],
diff --git a/tensorflow/contrib/lite/java/ovic/src/main/java/org/tensorflow/ovic/OvicValidator.java b/tensorflow/contrib/lite/java/ovic/src/main/java/org/tensorflow/ovic/OvicValidator.java
new file mode 100644
index 0000000000..a504ec74a9
--- /dev/null
+++ b/tensorflow/contrib/lite/java/ovic/src/main/java/org/tensorflow/ovic/OvicValidator.java
@@ -0,0 +1,94 @@
+/*Copyright 2018 Google LLC
+
+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
+
+    https://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 org.tensorflow.ovic;
+
+import java.io.File;
+import java.io.FileInputStream;
+import java.io.IOException;
+import java.io.InputStream;
+import java.io.PrintStream;
+import java.nio.ByteBuffer;
+import java.nio.ByteOrder;
+import java.nio.MappedByteBuffer;
+import java.nio.channels.FileChannel;
+import java.util.Random;
+
+/** Validate a submission model. */
+public class OvicValidator {
+  private static void printUsage(PrintStream s) {
+    s.println("Java program that validates a submission model.");
+    s.println();
+    s.println("Usage: ovic_validator <submission file>");
+    s.println();
+    s.println("Where:");
+    s.println("<submission file> is the model in TfLite format;");
+  }
+
+  public static void main(String[] args) {
+    if (args.length != 1) {
+      printUsage(System.err);
+      System.exit(1);
+    }
+    final String labelPath =
+        "tensorflow/contrib/lite/java/ovic/src/testdata/labels.txt";
+
+    final String modelFile = args[0];
+    try {
+      File labelsfile = new File(labelPath);
+      InputStream labelsInputStream = new FileInputStream(labelsfile);
+      MappedByteBuffer model = loadModelFile(modelFile);
+      OvicClassifier classifier = new OvicClassifier(labelsInputStream, model);
+      ByteBuffer imgData = createByteBufferForClassifier(classifier);
+      OvicSingleImageResult testResult = classifier.classifyByteBuffer(imgData);
+      if (testResult.topKClasses.isEmpty()) {
+        throw new RuntimeException("Failed to return top K predictions.");
+      }
+      System.out.printf("Successfully validated %s.%n", modelFile);
+    } catch (Exception e) {
+      System.out.println(e.getMessage());
+      System.out.printf("Failed to validate %s.%n", modelFile);
+    }
+  }
+
+  private static ByteBuffer createByteBufferForClassifier(OvicClassifier classifier) {
+    if (classifier == null) {
+      throw new RuntimeException("Cannot create image buffer with the classifier.");
+    }
+    int[] inputDims = classifier.getInputDims();
+    int imgHeight = inputDims[1];
+    int imgWidth = inputDims[2];
+    ByteBuffer imgData = ByteBuffer.allocateDirect(imgHeight * imgWidth * 3);
+    imgData.order(ByteOrder.nativeOrder());
+    Random rand = new Random();
+    for (int y = 0; y < imgHeight; y++) {
+      for (int x = 0; x < imgWidth; x++) {
+        int val = rand.nextInt();
+        imgData.put((byte) ((val >> 16) & 0xFF));
+        imgData.put((byte) ((val >> 8) & 0xFF));
+        imgData.put((byte) (val & 0xFF));
+      }
+    }
+    return imgData;
+  }
+
+  private static MappedByteBuffer loadModelFile(String modelFilePath) throws IOException {
+    File modelfile = new File(modelFilePath);
+    FileInputStream inputStream = new FileInputStream(modelfile);
+    FileChannel fileChannel = inputStream.getChannel();
+    long startOffset = 0L;
+    long declaredLength = fileChannel.size();
+    return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
+  }
+}