Remove a few redundant benchmark parameters.

PiperOrigin-RevId: 200079299

3 files changed, 1 insertions, 57 deletions

diff --git a/tensorflow/contrib/lite/tools/benchmark/README.md b/tensorflow/contrib/lite/tools/benchmark/README.md
index 2788f76faf..c10826afff 100644
--- a/tensorflow/contrib/lite/tools/benchmark/README.md
+++ b/tensorflow/contrib/lite/tools/benchmark/README.md
@@ -46,8 +46,6 @@ adb shell /data/local/tmp/benchmark_model \
   --graph=/data/local/tmp/mobilenet_quant_v1_224.tflite \
   --input_layer="Placeholder" \
   --input_layer_shape="1,224,224,3" \
-  --input_layer_type="uint8" \
-  --output_layer="MobilenetV1/Predictions/Reshape_1" \
   --num_threads=4
 ```
 
@@ -66,8 +64,6 @@ bazel-bin/tensorflow/contrib/lite/tools/benchmark/benchmark_model \
   --graph=mobilenet_quant_v1_224.tflite \
   --input_layer="Placeholder" \
   --input_layer_shape="1,224,224,3" \
-  --input_layer_type="uint8" \
-  --output_layer="MobilenetV1/Predictions/Reshape_1" \
   --num_threads=4
 ```
 
diff --git a/tensorflow/contrib/lite/tools/benchmark/benchmark_tflite_model.cc b/tensorflow/contrib/lite/tools/benchmark/benchmark_tflite_model.cc
index 2e5b866273..5f803cec19 100644
--- a/tensorflow/contrib/lite/tools/benchmark/benchmark_tflite_model.cc
+++ b/tensorflow/contrib/lite/tools/benchmark/benchmark_tflite_model.cc
@@ -123,29 +123,11 @@ void FillRandomString(tflite::DynamicBuffer* buffer,
   }
 }
 
-TfLiteType TfLiteTypeFromString(const string& input_layer_type) {
-  if (input_layer_type == "string")
-    return kTfLiteString;
-  else if (input_layer_type == "float")
-    return kTfLiteFloat32;
-  else if (input_layer_type == "uint8")
-    return kTfLiteUInt8;
-  else if (input_layer_type == "int32")
-    return kTfLiteInt32;
-  else if (input_layer_type == "int64")
-    return kTfLiteInt64;
-  else
-    return kTfLiteNoType;
-}
-
 bool PopulateInputLayerInfo(
     const string& names_string, const string& shapes_string,
-    const string& types_string, const string& values_string,
     std::vector<BenchmarkTfLiteModel::InputLayerInfo>* info) {
   std::vector<std::string> names = Split(names_string, ',');
   std::vector<std::string> shapes = Split(shapes_string, ':');
-  std::vector<std::string> types = Split(types_string, ',');
-  std::vector<std::string> values = Split(values_string, ':');
 
   if (names.size() != shapes.size()) {
     TFLITE_LOG(ERROR) << "The number of items in"
@@ -158,17 +140,6 @@ bool PopulateInputLayerInfo(
                       << " --input_layer_shape=1,224,224,4:1,20";
     return false;
   }
-  if (names.size() != types.size()) {
-    TFLITE_LOG(ERROR) << "The number of items in"
-                      << " --input_layer_type (" << types_string << ", with "
-                      << types.size() << " items)"
-                      << " must match the number of items in"
-                      << " --input_layer (" << names_string << ", with "
-                      << names.size() << " items)."
-                      << " For example --input_layer=input1,input2"
-                      << " --input_layer_type=float,int";
-    return false;
-  }
 
   for (int i = 0; i < names.size(); ++i) {
     info->push_back(BenchmarkTfLiteModel::InputLayerInfo());
@@ -176,10 +147,6 @@ bool PopulateInputLayerInfo(
 
     input.name = names[i];
 
-    input.data_type = TfLiteTypeFromString(types[i]);
-    TFLITE_BENCHMARK_CHECK(input.data_type != kTfLiteNoType)
-        << types[i] << " was an invalid type";
-
     TFLITE_BENCHMARK_CHECK(SplitAndParse(shapes[i], ',', &input.shape))
         << "Incorrect size string specified: " << shapes[i];
     for (int dim : input.shape) {
@@ -190,12 +157,6 @@ bool PopulateInputLayerInfo(
         return false;
       }
     }
-
-    if (i < values.size()) {
-      TFLITE_BENCHMARK_CHECK(
-          SplitAndParse(values[i], ',', &input.initialization_values))
-          << "Incorrect initialization values string specified: " << values[i];
-    }
   }
 
   return true;
@@ -209,10 +170,6 @@ std::vector<Flag> BenchmarkTfLiteModel::GetFlags() {
       Flag("graph", &graph, "graph file name"),
       Flag("input_layer", &input_layer_string, "input layer names"),
       Flag("input_layer_shape", &input_layer_shape_string, "input layer shape"),
-      Flag("input_layer_type", &input_layer_type_string, "input layer type"),
-      Flag("input_layer_values", &input_layer_values_string,
-           "values to initialize the inputs with"),
-      Flag("output_layer", &output_layer_string, "output layer name"),
       Flag("use_nnapi", &use_nnapi, "use nnapi api")};
 
   flags.insert(flags.end(), specific_flags.begin(), specific_flags.end());
@@ -224,8 +181,6 @@ void BenchmarkTfLiteModel::LogFlags() {
   TFLITE_LOG(INFO) << "Graph: [" << graph << "]";
   TFLITE_LOG(INFO) << "Input layers: [" << input_layer_string << "]";
   TFLITE_LOG(INFO) << "Input shapes: [" << input_layer_shape_string << "]";
-  TFLITE_LOG(INFO) << "Input types: [" << input_layer_type_string << "]";
-  TFLITE_LOG(INFO) << "Output layers: [" << output_layer_string << "]";
   TFLITE_LOG(INFO) << "Use nnapi : [" << use_nnapi << "]";
 }
 
@@ -236,8 +191,7 @@ bool BenchmarkTfLiteModel::ValidateFlags() {
     return false;
   }
   return PopulateInputLayerInfo(input_layer_string, input_layer_shape_string,
-                                input_layer_type_string,
-                                input_layer_values_string, &inputs);
+                                &inputs);
 }
 
 uint64_t BenchmarkTfLiteModel::ComputeInputBytes() {
@@ -293,8 +247,6 @@ void BenchmarkTfLiteModel::Init() {
     TFLITE_BENCHMARK_CHECK_EQ(t->name, input.name)
         << "Tensor # " << i << " is named " << t->name << " but flags call it "
         << input.name;
-    TFLITE_BENCHMARK_CHECK_EQ(t->type, input.data_type)
-        << "Could not match the type of input tensor " << t->name;
   }
 
   // Resize all non-string tensors.
diff --git a/tensorflow/contrib/lite/tools/benchmark/benchmark_tflite_model.h b/tensorflow/contrib/lite/tools/benchmark/benchmark_tflite_model.h
index e70f6de1bf..ffb93da964 100644
--- a/tensorflow/contrib/lite/tools/benchmark/benchmark_tflite_model.h
+++ b/tensorflow/contrib/lite/tools/benchmark/benchmark_tflite_model.h
@@ -64,10 +64,7 @@ class BenchmarkTfLiteModel : public BenchmarkModel {
 
   struct InputLayerInfo {
     std::string name;
-    TfLiteType data_type;
     std::vector<int> shape;
-    // Note that initialization_values is currently unused.
-    std::vector<float> initialization_values;
   };
 
  private:
@@ -78,7 +75,6 @@ class BenchmarkTfLiteModel : public BenchmarkModel {
   std::string input_layer_type_string;
   std::string input_layer_shape_string;
   std::string input_layer_values_string;
-  std::string output_layer_string;
   std::vector<InputLayerInfo> inputs;
   bool use_nnapi;
   ProfilingListener profiling_listener_;