Android: update TensorFlowInferenceInterface: replace error code returns with exceptions, use longs for dimensions, and simplify method signatures where possible.

Note this is a breaking change and will cause the TF demo in tensorflow/examples/android to not work with older jars/.so binaries built from tensorflow/contrib/android
Change: 151061702

5 files changed, 134 insertions, 197 deletions

diff --git a/tensorflow/contrib/android/java/org/tensorflow/contrib/android/TensorFlowInferenceInterface.java b/tensorflow/contrib/android/java/org/tensorflow/contrib/android/TensorFlowInferenceInterface.java
index 713f63b806..1f180429b2 100644
--- a/tensorflow/contrib/android/java/org/tensorflow/contrib/android/TensorFlowInferenceInterface.java
+++ b/tensorflow/contrib/android/java/org/tensorflow/contrib/android/TensorFlowInferenceInterface.java
@@ -30,6 +30,7 @@ import java.util.ArrayList;
 import java.util.List;
 import org.tensorflow.DataType;
 import org.tensorflow.Graph;
+import org.tensorflow.Operation;
 import org.tensorflow.Session;
 import org.tensorflow.Tensor;
 import org.tensorflow.TensorFlow;
@@ -45,7 +46,13 @@ public class TensorFlowInferenceInterface {
   private static final String TAG = "TensorFlowInferenceInterface";
   private static final String ASSET_FILE_PREFIX = "file:///android_asset/";
 
-  public TensorFlowInferenceInterface() {
+  /*
+   * Load a TensorFlow model from the AssetManager or from disk if it is not an asset file.
+   *
+   * @param assetManager The AssetManager to use to load the model file.
+   * @param model The filepath to the GraphDef proto representing the model.
+   */
+  public TensorFlowInferenceInterface(AssetManager assetManager, String model) {
     Log.i(TAG, "Checking to see if TensorFlow native methods are already loaded");
     try {
       // Hack to see if the native libraries have been loaded.
@@ -63,16 +70,12 @@ public class TensorFlowInferenceInterface {
                 + " libraries are present in the APK.");
       }
     }
-  }
 
-  /**
-   * Load a TensorFlow model from the AssetManager or from disk if it is not an asset file.
-   *
-   * @param assetManager The AssetManager to use to load the model file.
-   * @param model The filepath to the GraphDef proto representing the model.
-   * @return 0 on success.
-   */
-  public int initializeTensorFlow(AssetManager assetManager, String model) {
+    this.modelName = model;
+    this.g = new Graph();
+    this.sess = new Session(g);
+    this.runner = sess.runner();
+
     final boolean hasAssetPrefix = model.startsWith(ASSET_FILE_PREFIX);
     InputStream is = null;
     try {
@@ -80,37 +83,42 @@ public class TensorFlowInferenceInterface {
       is = assetManager.open(aname);
     } catch (IOException e) {
       if (hasAssetPrefix) {
-        Log.e(TAG, "Failed to load model from '" + model + "': " + e.toString());
-        return 1;
+        throw new RuntimeException("Failed to load model from '" + model + "'", e);
       }
       // Perhaps the model file is not an asset but is on disk.
       try {
         is = new FileInputStream(model);
       } catch (IOException e2) {
-        Log.e(TAG, "Failed to load model from '" + model + "': " + e2.toString());
-        return 1;
+        throw new RuntimeException("Failed to load model from '" + model + "'", e);
       }
     }
     try {
-      load(is);
+      loadGraph(is, g);
       is.close();
       Log.i(TAG, "Successfully loaded model from '" + model + "'");
-      return 0;
     } catch (IOException e) {
-      Log.e(TAG, "Failed to load model from '" + model + "': " + e.toString());
-      return 1;
+      throw new RuntimeException("Failed to load model from '" + model + "'", e);
     }
   }
 
   /**
-   * Runs inference between the previously registered input nodes (via fillNode*) and the requested
-   * output nodes. Output nodes can then be queried with the readNode* methods.
+   * Runs inference between the previously registered input nodes (via feed*) and the requested
+   * output nodes. Output nodes can then be queried with the fetch* methods.
    *
    * @param outputNames A list of output nodes which should be filled by the inference pass.
-   * @return 0 on success.
    */
-  public int runInference(String[] outputNames) {
-    // Release any Tensors from the previous runInference calls.
+  public void run(String[] outputNames) {
+    run(outputNames, false);
+  }
+
+  /**
+   * Runs inference between the previously registered input nodes (via feed*) and the requested
+   * output nodes. Output nodes can then be queried with the fetch* methods.
+   *
+   * @param outputNames A list of output nodes which should be filled by the inference pass.
+   */
+  public void run(String[] outputNames, boolean enableStats) {
+    // Release any Tensors from the previous run calls.
     closeFetches();
 
     // Add fetches.
@@ -125,6 +133,10 @@ public class TensorFlowInferenceInterface {
       if (enableStats) {
         Session.Run r = runner.setOptions(RunStats.runOptions()).runAndFetchMetadata();
         fetchTensors = r.outputs;
+
+        if (runStats == null) {
+          runStats = new RunStats();
+        }
         runStats.add(r.metadata);
       } else {
         fetchTensors = runner.run();
@@ -139,16 +151,13 @@ public class TensorFlowInferenceInterface {
               + "], outputs:["
               + TextUtils.join(", ", fetchNames)
               + "]");
-      Log.e(TAG, "Inference exception: " + e.toString());
-      return -1;
+      throw e;
     } finally {
-      // Always release the feeds (to save resources) and reset the runner, this runInference is
+      // Always release the feeds (to save resources) and reset the runner, this run is
       // over.
       closeFeeds();
       runner = sess.runner();
     }
-
-    return 0;
   }
 
   /** Returns a reference to the Graph describing the computation run during inference. */
@@ -156,15 +165,13 @@ public class TensorFlowInferenceInterface {
     return g;
   }
 
-  /**
-   * Whether to collect stats during inference. This should only be enabled when needed, as it will
-   * add overhead.
-   */
-  public void enableStatLogging(boolean enabled) {
-    enableStats = enabled;
-    if (enableStats && runStats == null) {
-      runStats = new RunStats();
+  public Operation graphOperation(String operationName) {
+    final Operation operation = g.operation(operationName);
+    if (operation == null) {
+      throw new RuntimeException(
+          "Node '" + operationName + "' does not exist in model '" + modelName + "'");
     }
+    return operation;
   }
 
   /** Returns the last stat summary string if logging is enabled. */
@@ -185,7 +192,15 @@ public class TensorFlowInferenceInterface {
       runStats.close();
     }
     runStats = null;
-    enableStats = false;
+  }
+
+  @Override
+  protected void finalize() throws Throwable {
+    try {
+      close();
+    } finally {
+      super.finalize();
+    }
   }
 
   // Methods for taking a native Tensor and filling it with values from Java arrays.
@@ -196,8 +211,8 @@ public class TensorFlowInferenceInterface {
    * as many elements as that of the destination Tensor. If {@link src} has more elements than the
    * destination has capacity, the copy is truncated.
    */
-  public void fillNodeFloat(String inputName, int[] dims, float[] src) {
-    addFeed(inputName, Tensor.create(mkDims(dims), FloatBuffer.wrap(src)));
+  public void feed(String inputName, float[] src, long... dims) {
+    addFeed(inputName, Tensor.create(dims, FloatBuffer.wrap(src)));
   }
 
   /**
@@ -206,8 +221,8 @@ public class TensorFlowInferenceInterface {
    * as many elements as that of the destination Tensor. If {@link src} has more elements than the
    * destination has capacity, the copy is truncated.
    */
-  public void fillNodeInt(String inputName, int[] dims, int[] src) {
-    addFeed(inputName, Tensor.create(mkDims(dims), IntBuffer.wrap(src)));
+  public void feed(String inputName, int[] src, long... dims) {
+    addFeed(inputName, Tensor.create(dims, IntBuffer.wrap(src)));
   }
 
   /**
@@ -216,8 +231,8 @@ public class TensorFlowInferenceInterface {
    * as many elements as that of the destination Tensor. If {@link src} has more elements than the
    * destination has capacity, the copy is truncated.
    */
-  public void fillNodeDouble(String inputName, int[] dims, double[] src) {
-    addFeed(inputName, Tensor.create(mkDims(dims), DoubleBuffer.wrap(src)));
+  public void feed(String inputName, double[] src, long... dims) {
+    addFeed(inputName, Tensor.create(dims, DoubleBuffer.wrap(src)));
   }
 
   /**
@@ -226,8 +241,8 @@ public class TensorFlowInferenceInterface {
    * as many elements as that of the destination Tensor. If {@link src} has more elements than the
    * destination has capacity, the copy is truncated.
    */
-  public void fillNodeByte(String inputName, int[] dims, byte[] src) {
-    addFeed(inputName, Tensor.create(DataType.UINT8, mkDims(dims), ByteBuffer.wrap(src)));
+  public void feed(String inputName, byte[] src, long... dims) {
+    addFeed(inputName, Tensor.create(DataType.UINT8, dims, ByteBuffer.wrap(src)));
   }
 
   // Methods for taking a native Tensor and filling it with src from Java native IO buffers.
@@ -239,8 +254,8 @@ public class TensorFlowInferenceInterface {
    * elements as that of the destination Tensor. If {@link src} has more elements than the
    * destination has capacity, the copy is truncated.
    */
-  public void fillNodeFromFloatBuffer(String inputName, IntBuffer dims, FloatBuffer src) {
-    addFeed(inputName, Tensor.create(mkDims(dims), src));
+  public void feed(String inputName, FloatBuffer src, long... dims) {
+    addFeed(inputName, Tensor.create(dims, src));
   }
 
   /**
@@ -250,8 +265,8 @@ public class TensorFlowInferenceInterface {
    * elements as that of the destination Tensor. If {@link src} has more elements than the
    * destination has capacity, the copy is truncated.
    */
-  public void fillNodeFromIntBuffer(String inputName, IntBuffer dims, IntBuffer src) {
-    addFeed(inputName, Tensor.create(mkDims(dims), src));
+  public void feed(String inputName, IntBuffer src, long... dims) {
+    addFeed(inputName, Tensor.create(dims, src));
   }
 
   /**
@@ -261,8 +276,8 @@ public class TensorFlowInferenceInterface {
    * elements as that of the destination Tensor. If {@link src} has more elements than the
    * destination has capacity, the copy is truncated.
    */
-  public void fillNodeFromDoubleBuffer(String inputName, IntBuffer dims, DoubleBuffer src) {
-    addFeed(inputName, Tensor.create(mkDims(dims), src));
+  public void feed(String inputName, DoubleBuffer src, long... dims) {
+    addFeed(inputName, Tensor.create(dims, src));
   }
 
   /**
@@ -272,52 +287,44 @@ public class TensorFlowInferenceInterface {
    * elements as that of the destination Tensor. If {@link src} has more elements than the
    * destination has capacity, the copy is truncated.
    */
-  public void fillNodeFromByteBuffer(String inputName, IntBuffer dims, ByteBuffer src) {
-    addFeed(inputName, Tensor.create(DataType.UINT8, mkDims(dims), src));
+  public void feed(String inputName, ByteBuffer src, long... dims) {
+    addFeed(inputName, Tensor.create(DataType.UINT8, dims, src));
   }
 
   /**
    * Read from a Tensor named {@link outputName} and copy the contents into a Java array. {@link
    * dst} must have length greater than or equal to that of the source Tensor. This operation will
    * not affect dst's content past the source Tensor's size.
-   *
-   * @return 0 on success, -1 on failure.
    */
-  public int readNodeFloat(String outputName, float[] dst) {
-    return readNodeIntoFloatBuffer(outputName, FloatBuffer.wrap(dst));
+  public void fetch(String outputName, float[] dst) {
+    fetch(outputName, FloatBuffer.wrap(dst));
   }
 
   /**
    * Read from a Tensor named {@link outputName} and copy the contents into a Java array. {@link
    * dst} must have length greater than or equal to that of the source Tensor. This operation will
    * not affect dst's content past the source Tensor's size.
-   *
-   * @return 0 on success, -1 on failure.
    */
-  public int readNodeInt(String outputName, int[] dst) {
-    return readNodeIntoIntBuffer(outputName, IntBuffer.wrap(dst));
+  public void fetch(String outputName, int[] dst) {
+    fetch(outputName, IntBuffer.wrap(dst));
   }
 
   /**
    * Read from a Tensor named {@link outputName} and copy the contents into a Java array. {@link
    * dst} must have length greater than or equal to that of the source Tensor. This operation will
    * not affect dst's content past the source Tensor's size.
-   *
-   * @return 0 on success, -1 on failure.
    */
-  public int readNodeDouble(String outputName, double[] dst) {
-    return readNodeIntoDoubleBuffer(outputName, DoubleBuffer.wrap(dst));
+  public void fetch(String outputName, double[] dst) {
+    fetch(outputName, DoubleBuffer.wrap(dst));
   }
 
   /**
    * Read from a Tensor named {@link outputName} and copy the contents into a Java array. {@link
    * dst} must have length greater than or equal to that of the source Tensor. This operation will
    * not affect dst's content past the source Tensor's size.
-   *
-   * @return 0 on success, -1 on failure.
    */
-  public int readNodeByte(String outputName, byte[] dst) {
-    return readNodeIntoByteBuffer(outputName, ByteBuffer.wrap(dst));
+  public void fetch(String outputName, byte[] dst) {
+    fetch(outputName, ByteBuffer.wrap(dst));
   }
 
   /**
@@ -325,16 +332,9 @@ public class TensorFlowInferenceInterface {
    * <b>native ordered</b> java.nio buffer {@link dst}. {@link dst} must have capacity greater than
    * or equal to that of the source Tensor. This operation will not affect dst's content past the
    * source Tensor's size.
-   *
-   * @return 0 on success, -1 on failure.
    */
-  public int readNodeIntoFloatBuffer(String outputName, FloatBuffer dst) {
-    Tensor t = getTensor(outputName);
-    if (t == null) {
-      return -1;
-    }
-    t.writeTo(dst);
-    return 0;
+  public void fetch(String outputName, FloatBuffer dst) {
+    getTensor(outputName).writeTo(dst);
   }
 
   /**
@@ -342,16 +342,9 @@ public class TensorFlowInferenceInterface {
    * <b>native ordered</b> java.nio buffer {@link dst}. {@link dst} must have capacity greater than
    * or equal to that of the source Tensor. This operation will not affect dst's content past the
    * source Tensor's size.
-   *
-   * @return 0 on success, -1 on failure.
    */
-  public int readNodeIntoIntBuffer(String outputName, IntBuffer dst) {
-    Tensor t = getTensor(outputName);
-    if (t == null) {
-      return -1;
-    }
-    t.writeTo(dst);
-    return 0;
+  public void fetch(String outputName, IntBuffer dst) {
+    getTensor(outputName).writeTo(dst);
   }
 
   /**
@@ -359,16 +352,9 @@ public class TensorFlowInferenceInterface {
    * <b>native ordered</b> java.nio buffer {@link dst}. {@link dst} must have capacity greater than
    * or equal to that of the source Tensor. This operation will not affect dst's content past the
    * source Tensor's size.
-   *
-   * @return 0 on success, -1 on failure.
    */
-  public int readNodeIntoDoubleBuffer(String outputName, DoubleBuffer dst) {
-    Tensor t = getTensor(outputName);
-    if (t == null) {
-      return -1;
-    }
-    t.writeTo(dst);
-    return 0;
+  public void fetch(String outputName, DoubleBuffer dst) {
+    getTensor(outputName).writeTo(dst);
   }
 
   /**
@@ -376,22 +362,12 @@ public class TensorFlowInferenceInterface {
    * <b>native ordered</b> java.nio buffer {@link dst}. {@link dst} must have capacity greater than
    * or equal to that of the source Tensor. This operation will not affect dst's content past the
    * source Tensor's size.
-   *
-   * @return 0 on success, -1 on failure.
    */
-  public int readNodeIntoByteBuffer(String outputName, ByteBuffer dst) {
-    Tensor t = getTensor(outputName);
-    if (t == null) {
-      return -1;
-    }
-    t.writeTo(dst);
-    return 0;
+  public void fetch(String outputName, ByteBuffer dst) {
+    getTensor(outputName).writeTo(dst);
   }
 
-  private void load(InputStream is) throws IOException {
-    this.g = new Graph();
-    this.sess = new Session(g);
-    this.runner = sess.runner();
+  private void loadGraph(InputStream is, Graph g) throws IOException {
     final long startMs = System.currentTimeMillis();
 
     Trace.beginSection("initializeTensorFlow");
@@ -425,26 +401,6 @@ public class TensorFlowInferenceInterface {
         "Model load took " + (endMs - startMs) + "ms, TensorFlow version: " + TensorFlow.version());
   }
 
-  // The TensorFlowInferenceInterface API used int[] for dims, but the underlying TensorFlow runtime
-  // allows for 64-bit dimension sizes, so it needs to be converted to a long[]
-  private long[] mkDims(int[] dims) {
-    long[] ret = new long[dims.length];
-    for (int i = 0; i < dims.length; ++i) {
-      ret[i] = (long) dims[i];
-    }
-    return ret;
-  }
-
-  // Similar to mkDims(int[]), with the shape provided in an IntBuffer.
-  private long[] mkDims(IntBuffer dims) {
-    if (dims.hasArray()) {
-      return mkDims(dims.array());
-    }
-    int[] copy = new int[dims.remaining()];
-    dims.duplicate().get(copy);
-    return mkDims(copy);
-  }
-
   private void addFeed(String inputName, Tensor t) {
     // The string format accepted by TensorFlowInferenceInterface is node_name[:output_index].
     TensorId tid = TensorId.parse(inputName);
@@ -485,9 +441,10 @@ public class TensorFlowInferenceInterface {
       if (n.equals(outputName)) {
         return fetchTensors.get(i);
       }
-      i++;
+      ++i;
     }
-    return null;
+    throw new RuntimeException(
+        "Node '" + outputName + "' was not provided to run(), so it cannot be read");
   }
 
   private void closeFeeds() {
@@ -507,10 +464,11 @@ public class TensorFlowInferenceInterface {
   }
 
   // State immutable between initializeTensorFlow calls.
-  private Graph g;
-  private Session sess;
+  private final String modelName;
+  private final Graph g;
+  private final Session sess;
 
-  // State reset on every call to runInference.
+  // State reset on every call to run.
   private Session.Runner runner;
   private List<String> feedNames = new ArrayList<String>();
   private List<Tensor> feedTensors = new ArrayList<Tensor>();
@@ -518,6 +476,5 @@ public class TensorFlowInferenceInterface {
   private List<Tensor> fetchTensors = new ArrayList<Tensor>();
 
   // Mutable state.
-  private boolean enableStats;
   private RunStats runStats;
 }
diff --git a/tensorflow/examples/android/src/org/tensorflow/demo/StylizeActivity.java b/tensorflow/examples/android/src/org/tensorflow/demo/StylizeActivity.java
index c1a893e9ee..d0df1a4483 100644
--- a/tensorflow/examples/android/src/org/tensorflow/demo/StylizeActivity.java
+++ b/tensorflow/examples/android/src/org/tensorflow/demo/StylizeActivity.java
@@ -369,8 +369,7 @@ public class StylizeActivity extends CameraActivity implements OnImageAvailableL
     borderedText = new BorderedText(textSizePx);
     borderedText.setTypeface(Typeface.MONOSPACE);
 
-    inferenceInterface = new TensorFlowInferenceInterface();
-    inferenceInterface.initializeTensorFlow(getAssets(), MODEL_FILE);
+    inferenceInterface = new TensorFlowInferenceInterface(getAssets(), MODEL_FILE);
 
     previewWidth = size.getWidth();
     previewHeight = size.getHeight();
@@ -585,12 +584,12 @@ public class StylizeActivity extends CameraActivity implements OnImageAvailableL
     }
 
     // Copy the input data into TensorFlow.
-    inferenceInterface.fillNodeFloat(
-        INPUT_NODE, new int[] {1, bitmap.getWidth(), bitmap.getHeight(), 3}, floatValues);
-    inferenceInterface.fillNodeFloat(STYLE_NODE, new int[] {NUM_STYLES}, styleVals);
+    inferenceInterface.feed(
+        INPUT_NODE, floatValues, 1, bitmap.getWidth(), bitmap.getHeight(), 3);
+    inferenceInterface.feed(STYLE_NODE, styleVals, NUM_STYLES);
 
-    inferenceInterface.runInference(new String[] {OUTPUT_NODE});
-    inferenceInterface.readNodeFloat(OUTPUT_NODE, floatValues);
+    inferenceInterface.run(new String[] {OUTPUT_NODE}, isDebug());
+    inferenceInterface.fetch(OUTPUT_NODE, floatValues);
 
     for (int i = 0; i < intValues.length; ++i) {
       intValues[i] =
@@ -603,11 +602,6 @@ public class StylizeActivity extends CameraActivity implements OnImageAvailableL
     bitmap.setPixels(intValues, 0, bitmap.getWidth(), 0, 0, bitmap.getWidth(), bitmap.getHeight());
   }
 
-  @Override
-  public void onSetDebug(final boolean debug) {
-    inferenceInterface.enableStatLogging(debug);
-  }
-
   private void renderDebug(final Canvas canvas) {
     // TODO(andrewharp): move result display to its own View instead of using debug overlay.
     final Bitmap texture = textureCopyBitmap;
diff --git a/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowImageClassifier.java b/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowImageClassifier.java
index 9f80665ee6..f660178ebe 100644
--- a/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowImageClassifier.java
+++ b/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowImageClassifier.java
@@ -56,6 +56,8 @@ public class TensorFlowImageClassifier implements Classifier {
   private float[] outputs;
   private String[] outputNames;
 
+  private boolean logStats = false;
+
   private TensorFlowInferenceInterface inferenceInterface;
 
   private TensorFlowImageClassifier() {}
@@ -102,16 +104,10 @@ public class TensorFlowImageClassifier implements Classifier {
       throw new RuntimeException("Problem reading label file!" , e);
     }
 
-    c.inferenceInterface = new TensorFlowInferenceInterface();
-    if (c.inferenceInterface.initializeTensorFlow(assetManager, modelFilename) != 0) {
-      throw new RuntimeException("TF initialization failed");
-    }
+    c.inferenceInterface = new TensorFlowInferenceInterface(assetManager, modelFilename);
+
     // The shape of the output is [N, NUM_CLASSES], where N is the batch size.
-    final Operation operation = c.inferenceInterface.graph().operation(outputName);
-    if (operation == null) {
-      throw new RuntimeException("Node '" + outputName + "' does not exist in model '"
-          + modelFilename + "'");
-    }
+    final Operation operation = c.inferenceInterface.graphOperation(outputName);
     final int numClasses = (int) operation.output(0).shape().size(1);
     Log.i(TAG, "Read " + c.labels.size() + " labels, output layer size is " + numClasses);
 
@@ -149,19 +145,18 @@ public class TensorFlowImageClassifier implements Classifier {
     Trace.endSection();
 
     // Copy the input data into TensorFlow.
-    Trace.beginSection("fillNodeFloat");
-    inferenceInterface.fillNodeFloat(
-        inputName, new int[] {1, inputSize, inputSize, 3}, floatValues);
+    Trace.beginSection("feed");
+    inferenceInterface.feed(inputName, floatValues, 1, inputSize, inputSize, 3);
     Trace.endSection();
 
     // Run the inference call.
-    Trace.beginSection("runInference");
-    inferenceInterface.runInference(outputNames);
+    Trace.beginSection("run");
+    inferenceInterface.run(outputNames, logStats);
     Trace.endSection();
 
     // Copy the output Tensor back into the output array.
-    Trace.beginSection("readNodeFloat");
-    inferenceInterface.readNodeFloat(outputName, outputs);
+    Trace.beginSection("fetch");
+    inferenceInterface.fetch(outputName, outputs);
     Trace.endSection();
 
     // Find the best classifications.
@@ -192,8 +187,8 @@ public class TensorFlowImageClassifier implements Classifier {
   }
 
   @Override
-  public void enableStatLogging(boolean debug) {
-    inferenceInterface.enableStatLogging(debug);
+  public void enableStatLogging(boolean logStats) {
+    this.logStats = logStats;
   }
 
   @Override
diff --git a/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowMultiBoxDetector.java b/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowMultiBoxDetector.java
index 2ec9476ef9..f3e7114335 100644
--- a/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowMultiBoxDetector.java
+++ b/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowMultiBoxDetector.java
@@ -62,6 +62,8 @@ public class TensorFlowMultiBoxDetector implements Classifier {
   private String[] outputNames;
   private int numLocations;
 
+  private boolean logStats = false;
+
   private TensorFlowInferenceInterface inferenceInterface;
 
   private float[] boxPriors;
@@ -89,10 +91,7 @@ public class TensorFlowMultiBoxDetector implements Classifier {
       final String outputScoresName) {
     final TensorFlowMultiBoxDetector d = new TensorFlowMultiBoxDetector();
 
-    d.inferenceInterface = new TensorFlowInferenceInterface();
-    if (d.inferenceInterface.initializeTensorFlow(assetManager, modelFilename) != 0) {
-      throw new RuntimeException("TF initialization failed");
-    }
+    d.inferenceInterface = new TensorFlowInferenceInterface(assetManager, modelFilename);
 
     final Graph g = d.inferenceInterface.graph();
 
@@ -222,22 +221,21 @@ public class TensorFlowMultiBoxDetector implements Classifier {
     Trace.endSection(); // preprocessBitmap
 
     // Copy the input data into TensorFlow.
-    Trace.beginSection("fillNodeFloat");
-    inferenceInterface.fillNodeFloat(
-        inputName, new int[] {1, inputSize, inputSize, 3}, floatValues);
+    Trace.beginSection("feed");
+    inferenceInterface.feed(inputName, floatValues, 1, inputSize, inputSize, 3);
     Trace.endSection();
 
     // Run the inference call.
-    Trace.beginSection("runInference");
-    inferenceInterface.runInference(outputNames);
+    Trace.beginSection("run");
+    inferenceInterface.run(outputNames, logStats);
     Trace.endSection();
 
     // Copy the output Tensor back into the output array.
-    Trace.beginSection("readNodeFloat");
+    Trace.beginSection("fetch");
     final float[] outputScoresEncoding = new float[numLocations];
     final float[] outputLocationsEncoding = new float[numLocations * 4];
-    inferenceInterface.readNodeFloat(outputNames[0], outputLocationsEncoding);
-    inferenceInterface.readNodeFloat(outputNames[1], outputScoresEncoding);
+    inferenceInterface.fetch(outputNames[0], outputLocationsEncoding);
+    inferenceInterface.fetch(outputNames[1], outputScoresEncoding);
     Trace.endSection();
 
     outputLocations = decodeLocationsEncoding(outputLocationsEncoding);
@@ -275,8 +273,8 @@ public class TensorFlowMultiBoxDetector implements Classifier {
   }
 
   @Override
-  public void enableStatLogging(final boolean debug) {
-    inferenceInterface.enableStatLogging(debug);
+  public void enableStatLogging(final boolean logStats) {
+    this.logStats = logStats;
   }
 
   @Override
diff --git a/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowYoloDetector.java b/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowYoloDetector.java
index 062e8cc8d0..174723071d 100644
--- a/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowYoloDetector.java
+++ b/tensorflow/examples/android/src/org/tensorflow/demo/TensorFlowYoloDetector.java
@@ -86,6 +86,8 @@ public class TensorFlowYoloDetector implements Classifier {
 
   private int blockSize;
 
+  private boolean logStats = false;
+
   private TensorFlowInferenceInterface inferenceInterface;
 
   /** Initializes a native TensorFlow session for classifying images. */
@@ -106,13 +108,8 @@ public class TensorFlowYoloDetector implements Classifier {
     d.floatValues = new float[inputSize * inputSize * 3];
     d.blockSize = blockSize;
 
-    d.inferenceInterface = new TensorFlowInferenceInterface();
+    d.inferenceInterface = new TensorFlowInferenceInterface(assetManager, modelFilename);
 
-    final int status = d.inferenceInterface.initializeTensorFlow(assetManager, modelFilename);
-    if (status != 0) {
-      LOGGER.e("TF init status: " + status);
-      throw new RuntimeException("TF init status (" + status + ") != 0");
-    }
     return d;
   }
 
@@ -157,30 +154,26 @@ public class TensorFlowYoloDetector implements Classifier {
     Trace.endSection(); // preprocessBitmap
 
     // Copy the input data into TensorFlow.
-    Trace.beginSection("fillNodeFloat");
-    inferenceInterface.fillNodeFloat(
-        inputName, new int[] {1, inputSize, inputSize, 3}, floatValues);
+    Trace.beginSection("feed");
+    inferenceInterface.feed(inputName, floatValues, 1, inputSize, inputSize, 3);
     Trace.endSection();
 
     timer.endSplit("ready for inference");
 
     // Run the inference call.
-    Trace.beginSection("runInference");
-    final int resultCode = inferenceInterface.runInference(outputNames);
-    if (resultCode != 0) {
-      throw new RuntimeException("Bad result code from inference: " + resultCode);
-    }
+    Trace.beginSection("run");
+    inferenceInterface.run(outputNames, logStats);
     Trace.endSection();
 
     timer.endSplit("ran inference");
 
     // Copy the output Tensor back into the output array.
-    Trace.beginSection("readNodeFloat");
+    Trace.beginSection("fetch");
     final int gridWidth = bitmap.getWidth() / blockSize;
     final int gridHeight = bitmap.getHeight() / blockSize;
     final float[] output =
         new float[gridWidth * gridHeight * (NUM_CLASSES + 5) * NUM_BOXES_PER_BLOCK];
-    inferenceInterface.readNodeFloat(outputNames[0], output);
+    inferenceInterface.fetch(outputNames[0], output);
     Trace.endSection();
 
     // Find the best detections.
@@ -256,8 +249,8 @@ public class TensorFlowYoloDetector implements Classifier {
   }
 
   @Override
-  public void enableStatLogging(final boolean debug) {
-    inferenceInterface.enableStatLogging(debug);
+  public void enableStatLogging(final boolean logStats) {
+    this.logStats = logStats;
   }
 
   @Override