Print per-node step stats from Android demo for better benchmarking.

Change: 117958944

1 files changed, 40 insertions, 5 deletions

diff --git a/tensorflow/examples/android/jni/tensorflow_jni.cc b/tensorflow/examples/android/jni/tensorflow_jni.cc
index ae0634f4fd..a6f6174664 100644
--- a/tensorflow/examples/android/jni/tensorflow_jni.cc
+++ b/tensorflow/examples/android/jni/tensorflow_jni.cc
@@ -36,6 +36,7 @@ limitations under the License.
 #include "tensorflow/core/platform/mutex.h"
 #include "tensorflow/core/platform/types.h"
 #include "tensorflow/core/public/session.h"
+#include "tensorflow/core/util/stat_summarizer.h"
 #include "tensorflow/examples/android/jni/jni_utils.h"
 
 using namespace tensorflow;
@@ -49,10 +50,19 @@ static bool g_compute_graph_initialized = false;
 
 static int g_tensorflow_input_size;  // The image size for the mognet input.
 static int g_image_mean;  // The image mean.
+static StatSummarizer g_stats;
 
 // For basic benchmarking.
 static int g_num_runs = 0;
 static int64 g_timing_total_us = 0;
+static Stat<int64> g_frequency_start;
+static Stat<int64> g_frequency_end;
+
+#ifdef LOG_DETAILED_STATS
+static const bool kLogDetailedStats = true;
+#else
+static const bool kLogDetailedStats = false;
+#endif
 
 // Improve benchmarking by limiting runs to predefined amount.
 // 0 (default) denotes infinite runs.
@@ -79,6 +89,9 @@ TENSORFLOW_METHOD(initializeTensorflow)(
     jint num_classes, jint mognet_input_size, jint image_mean) {
   g_num_runs = 0;
   g_timing_total_us = 0;
+  g_stats.Reset();
+  g_frequency_start.Reset();
+  g_frequency_end.Reset();
 
   //MutexLock input_lock(&g_compute_graph_mutex);
   if (g_compute_graph_initialized) {
@@ -179,6 +192,17 @@ static void GetTopN(
   std::reverse(top_results->begin(), top_results->end());
 }
 
+static int64 GetCpuSpeed() {
+  string scaling_contents;
+  ReadFileToString(nullptr,
+                   "/sys/devices/system/cpu/cpu0/cpufreq/scaling_cur_freq",
+                   &scaling_contents);
+  std::stringstream ss(scaling_contents);
+  int64 result;
+  ss >> result;
+  return result;
+}
+
 static std::string ClassifyImage(const RGBA* const bitmap_src,
                                  const int in_stride,
                                  const int width, const int height) {
@@ -227,22 +251,33 @@ static std::string ClassifyImage(const RGBA* const bitmap_src,
   tensorflow::Status s;
   int64 start_time, end_time;
 
-  if (kSaveStepStats) {
+  if (kLogDetailedStats || kSaveStepStats) {
     RunOptions run_options;
     run_options.set_trace_level(RunOptions::FULL_TRACE);
     RunMetadata run_metadata;
+    g_frequency_start.UpdateStat(GetCpuSpeed());
     start_time = CurrentThreadTimeUs();
     s = session->Run(run_options, input_tensors, output_names, {},
                      &output_tensors, &run_metadata);
     end_time = CurrentThreadTimeUs();
+    g_frequency_end.UpdateStat(GetCpuSpeed());
     assert(run_metadata.has_step_stats());
 
     const StepStats& stats = run_metadata.step_stats();
 
-    mkdir("/sdcard/tf/", 0755);
-    const string filename =
-        strings::Printf("/sdcard/tf/stepstats%05d.pb", g_num_runs);
-    WriteProtoToFile(filename.c_str(), stats);
+    if (kLogDetailedStats) {
+      LOG(INFO) << "CPU frequency start: " << g_frequency_start;
+      LOG(INFO) << "CPU frequency end:   " << g_frequency_end;
+      g_stats.ProcessStepStats(stats);
+      g_stats.PrintStepStats();
+    }
+
+    if (kSaveStepStats) {
+      mkdir("/sdcard/tf/", 0755);
+      const string filename =
+          strings::Printf("/sdcard/tf/stepstats%05d.pb", g_num_runs);
+      WriteProtoToFile(filename.c_str(), stats);
+    }
   } else {
     start_time = CurrentThreadTimeUs();
     s = session->Run(input_tensors, output_names, {}, &output_tensors);