make label_image for tflite build again (#16206)

* make label_image for tflite build again

1. add namespace to label_image.h to make label_image for tflite build again
2. add --config monolithic and mention NDK settings in label_image.md
3. fix a typo in display_usage()

* relies on tensor type info to switch types

use tensor types of input and output tensors instead of command
line flag from user

* reformatted according to review

3 files changed, 46 insertions, 28 deletions

diff --git a/tensorflow/contrib/lite/examples/label_image/label_image.cc b/tensorflow/contrib/lite/examples/label_image/label_image.cc
index 4d2e1ce0bc..d7f49ad875 100644
--- a/tensorflow/contrib/lite/examples/label_image/label_image.cc
+++ b/tensorflow/contrib/lite/examples/label_image/label_image.cc
@@ -148,14 +148,22 @@ void RunInference(Settings* s) {
   int wanted_width = dims->data[2];
   int wanted_channels = dims->data[3];
 
-  if (s->input_floating) {
-    downsize<float>(interpreter->typed_tensor<float>(input), in, image_height,
-                    image_width, image_channels, wanted_height, wanted_width,
-                    wanted_channels, s);
-  } else {
-    downsize<uint8_t>(interpreter->typed_tensor<uint8_t>(input), in,
-                      image_height, image_width, image_channels, wanted_height,
-                      wanted_width, wanted_channels, s);
+  switch (interpreter->tensor(input)->type) {
+    case kTfLiteFloat32:
+      s->input_floating = true;
+      downsize<float>(interpreter->typed_tensor<float>(input), in,
+                      image_height, image_width, image_channels,
+                      wanted_height, wanted_width, wanted_channels, s);
+      break;
+    case kTfLiteUInt8:
+      downsize<uint8_t>(interpreter->typed_tensor<uint8_t>(input), in,
+                        image_height, image_width, image_channels,
+                        wanted_height, wanted_width, wanted_channels, s);
+      break;
+    default:
+      LOG(FATAL) << "cannot handle input type "
+                 << interpreter->tensor(input)->type << " yet";
+      exit(-1);
   }
 
   struct timeval start_time, stop_time;
@@ -177,13 +185,22 @@ void RunInference(Settings* s) {
 
   std::vector<std::pair<float, int>> top_results;
 
-  if (s->input_floating) {
-    get_top_n<float>(interpreter->typed_output_tensor<float>(0), output_size,
-                     num_results, threshold, &top_results, s->input_floating);
-  } else {
-    get_top_n<uint8_t>(interpreter->typed_output_tensor<uint8_t>(0),
+  int output = interpreter->outputs()[0];
+  switch (interpreter->tensor(output)->type) {
+    case kTfLiteFloat32:
+      get_top_n<float>(interpreter->typed_output_tensor<float>(0),
                        output_size, num_results, threshold, &top_results,
-                       s->input_floating);
+                       true);
+      break;
+    case kTfLiteUInt8:
+      get_top_n<uint8_t>(interpreter->typed_output_tensor<uint8_t>(0),
+                         output_size, num_results, threshold, &top_results,
+                         false);
+      break;
+    default:
+      LOG(FATAL) << "cannot handle output type "
+                 << interpreter->tensor(input)->type << " yet";
+      exit(-1);
   }
 
   std::vector<string> labels;
@@ -203,13 +220,11 @@ void display_usage() {
   LOG(INFO) << "label_image\n"
             << "--accelerated, -a: [0|1], use Android NNAPI or note\n"
             << "--count, -c: loop interpreter->Invoke() for certain times\n"
-            << "--input_floating, -f: [0|1] type of input layer is floating "
-               "point numbers\n"
             << "--input_mean, -b: input mean\n"
             << "--input_std, -s: input standard deviation\n"
             << "--image, -i: image_name.bmp\n"
             << "--labels, -l: labels for the model\n"
-            << "--tflite_mode, -m: model_name.tflite\n"
+            << "--tflite_model, -m: model_name.tflite\n"
             << "--threads, -t: number of threads\n"
             << "--verbose, -v: [0|1] print more information\n"
             << "\n";
@@ -223,7 +238,6 @@ int Main(int argc, char** argv) {
     static struct option long_options[] = {
         {"accelerated", required_argument, 0, 'a'},
         {"count", required_argument, 0, 'c'},
-        {"input_floating", required_argument, 0, 'f'},
         {"verbose", required_argument, 0, 'v'},
         {"image", required_argument, 0, 'i'},
         {"labels", required_argument, 0, 'l'},
@@ -254,11 +268,6 @@ int Main(int argc, char** argv) {
         s.loop_count = strtol(  // NOLINT(runtime/deprecated_fn)
             optarg, (char**)NULL, 10);
         break;
-      case 'f':
-        s.input_floating = strtol(  // NOLINT(runtime/deprecated_fn)
-            optarg, (char**)NULL, 10);
-        s.input_layer_type = "float";
-        break;
       case 'i':
         s.input_bmp_name = optarg;
         break;
diff --git a/tensorflow/contrib/lite/examples/label_image/label_image.h b/tensorflow/contrib/lite/examples/label_image/label_image.h
index ce98e06fc1..4de32e33fb 100644
--- a/tensorflow/contrib/lite/examples/label_image/label_image.h
+++ b/tensorflow/contrib/lite/examples/label_image/label_image.h
@@ -16,9 +16,11 @@ limitations under the License.
 #ifndef TENSORFLOW_CONTRIB_LITE_EXAMPLES_LABEL_IMAGE_LABEL_IMAGE_H
 #define TENSORFLOW_CONTRIB_LITE_EXAMPLES_LABEL_IMAGE_LABEL_IMAGE_H
 
-#include <string>
 #include "tensorflow/contrib/lite/string.h"
 
+namespace tflite {
+namespace label_image {
+
 struct Settings {
   bool verbose = false;
   bool accel = false;
@@ -33,4 +35,7 @@ struct Settings {
   int number_of_threads = 4;
 };
 
+}  // namespace label_image
+}  // namespace tflite
+
 #endif  // TENSORFLOW_CONTRIB_LITE_EXAMPLES_LABEL_IMAGE_LABEL_IMAGE_H
diff --git a/tensorflow/contrib/lite/examples/label_image/label_image.md b/tensorflow/contrib/lite/examples/label_image/label_image.md
index d6019d673f..9ce32cf101 100644
--- a/tensorflow/contrib/lite/examples/label_image/label_image.md
+++ b/tensorflow/contrib/lite/examples/label_image/label_image.md
@@ -1,8 +1,12 @@
 label_image for TensorFlow Lite inspired by TensorFlow's label_image.
+
+To build label_image for Android, run $TENSORFLOW_ROOT/configure 
+and set Android NDK or configure NDK setting in 
+$TENSORFLOW_ROOT/WORKSPACE first.
  
 To build it for android ARMv8:
 ```
-> bazel build --cxxopt=-std=c++11 \
+> bazel build --config monolithic --cxxopt=-std=c++11 \
   --crosstool_top=//external:android/crosstool \
   --host_crosstool_top=@bazel_tools//tools/cpp:toolchain \
   --cpu=arm64-v8a \
@@ -10,13 +14,13 @@ To build it for android ARMv8:
 ```
 or
 ```
-> bazel build --config android_arm64 --cxxopt=-std=c++11 \
+> bazel build --config android_arm64 --config monolithic --cxxopt=-std=c++11 \
   //tensorflow/contrib/lite/examples/label_image:label_image
 ```
 
 To build it for android arm-v7a:
 ```
-> bazel build --cxxopt=-std=c++11 \
+> bazel build --config monolithic --cxxopt=-std=c++11 \
   --crosstool_top=//external:android/crosstool \
   --host_crosstool_top=@bazel_tools//tools/cpp:toolchain \
   --cpu=armeabi-v7a \
@@ -24,7 +28,7 @@ To build it for android arm-v7a:
 ```
 or
 ```
-> bazel build --config android_arm --cxxopt=-std=c++11 \
+> bazel build --config android_arm --config monolithic --cxxopt=-std=c++11 \
   //tensorflow/contrib/lite/examples/label_image:label_image
 ```