Merge pull request #61 from JDAI-CV/update

Add GetDevices and misc updates
JDAI-CV · Jul 31, 2019 · c3cd873 · c3cd873
2 parents 848b29f + 29a6a99
commit c3cd873
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Showing 9 changed files with 87 additions and 35 deletions.
diff --git a/CMakeLists.txt b/CMakeLists.txt
@@ -22,9 +22,8 @@ include(cmake/flatbuffers.cmake)
 configure_flatbuffers()
 
 if (${CMAKE_SYSTEM_NAME} STREQUAL "Android")
-    set (CMAKE_CXX_STANDARD 17)
-
     add_compile_options(-Os)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++17")
     if (${DNN_READ_ONNX})
         include(cmake/onnx.cmake)
         configure_onnx()

diff --git a/binaries/CMakeLists.txt b/binaries/CMakeLists.txt
@@ -37,4 +37,14 @@ if (DNN_BUILD_BIN)
     if ((NOT DNN_READ_ONNX) OR DNN_SYSTEM_PROTOBUF)
         treat_warnings_as_errors(ex_model_builder)
     endif()
+
+    add_executable(get_devices
+        get_devices.cpp)
+    target_link_libraries(get_devices
+        dnnlibrary)
+    target_include_directories(get_devices
+        PRIVATE
+        ${PROJECT_SOURCE_DIR}
+        )
+
 endif()
diff --git a/binaries/get_devices.cpp b/binaries/get_devices.cpp
@@ -0,0 +1,23 @@
+#include <chrono>
+#include <iostream>
+#include <vector>
+
+#include <common/helper.h>
+#include <dnnlibrary/ModelBuilder.h>
+
+using namespace android::nn::wrapper;
+using dnn::ModelBuilder;
+
+int main() {
+    ModelBuilder builder;
+    builder.Prepare();
+    const auto devices = builder.GetDevices();
+    if (devices.has_value()) {
+        for (const auto &device : devices.value()) {
+            PNT(device.name, device.feature_level, device.type, device.version);
+        }
+    } else {
+        std::cout << "Cannot get devices" << std::endl;
+    }
+}
+
diff --git a/common/Shaper.cpp b/common/Shaper.cpp
@@ -33,18 +33,6 @@ void Shaper::Conv(const std::string &input_name,
                  paddings[1], paddings[3], paddings[0], paddings[2],
                  weight_name, output_name);
 }
-
-void Shaper::Conv(const std::string &input_name,
-                  const std::vector<int32_t> paddings,
-                  const std::vector<int32_t> strides,
-                  const std::vector<int32_t> dilations,
-                  const std::string &weight_name, const std::string &bias_name,
-                  const std::string &output_name) {
-    (void)bias_name;
-    Shaper::Conv(input_name, strides, dilations, paddings, weight_name,
-                 output_name);
-}
-
 void Shaper::Conv(const std::string &input, const std::string &weight,
                   int32_t padding_left, int32_t padding_right,
                   int32_t padding_top, int32_t padding_bottom, int32_t stride_x,
@@ -244,8 +232,7 @@ void Shaper::Eltwise(const std::string &input1_name,
     auto shape1 = shape_map_.at(input1_name);
     auto shape2 = shape_map_.at(input2_name);
     // TODO: broadcasting
-    auto output_shape =
-        shape1.size() >= shape2.size() ? shape1 : shape2;
+    auto output_shape = shape1.size() >= shape2.size() ? shape1 : shape2;
     shape_map_[output_name] = output_shape;
 }
 

diff --git a/dnnlibrary/ModelBuilder.cpp b/dnnlibrary/ModelBuilder.cpp
@@ -914,4 +914,31 @@ ModelBuilder &ModelBuilder::AllowFp16(const bool allowed) {
 
 ModelBuilder::ModelBuilder() : nnapi_(NnApiImplementation()) {
 }
+
+dnn::optional<std::vector<Device>> ModelBuilder::GetDevices() {
+    if (nnapi_->android_sdk_version >= __ANDROID_API_Q__) {
+        uint32_t device_count;
+        THROW_ON_ERROR(nnapi_->ANeuralNetworks_getDeviceCount(&device_count));
+        std::vector<Device> devices;
+        FORZ(i, device_count) {
+            ANeuralNetworksDevice *nn_device;
+            nnapi_->ANeuralNetworks_getDevice(i, &nn_device);
+            const char *nn_name_ptr;
+            nnapi_->ANeuralNetworksDevice_getName(nn_device, &nn_name_ptr);
+            const std::string device_name(nn_name_ptr);
+            int64_t feature_level;
+            nnapi_->ANeuralNetworksDevice_getFeatureLevel(nn_device, &feature_level);
+            int type;
+            nnapi_->ANeuralNetworksDevice_getType(nn_device, &type);
+            const char *nn_version_ptr;
+            nnapi_->ANeuralNetworksDevice_getVersion(nn_device, &nn_version_ptr);
+            const std::string version(nn_version_ptr);
+            Device device{device_name, feature_level, type, version};
+            devices.push_back(device);
+        }
+        return devices;
+    } else {
+        return dnn::nullopt;
+    }
+}
 }  // namespace dnn
diff --git a/dnnlibrary/NeuralNetworksWrapper.cpp b/dnnlibrary/NeuralNetworksWrapper.cpp
@@ -8,7 +8,7 @@ namespace wrapper {
 
 OperandType::OperandType(Type type, std::vector<uint32_t> d, float scale,
                          int32_t zeroPoint)
-    : type(type), dimensions(std::move(d)), channelQuant(std::nullopt) {
+    : type(type), dimensions(std::move(d)), channelQuant(dnn::nullopt) {
     if (dimensions.empty()) {
         if (!isScalarType(type)) {
             dimensions = {1};

diff --git a/include/common/Shaper.h b/include/common/Shaper.h
@@ -15,11 +15,10 @@ class Shaper {
 
     static len_t total(const Shape &shape);
 
-    void Conv(const std::string &input_name,
-                  const std::string &weight_name,
-                  const std::vector<int32_t> strides,
-                  const std::vector<int32_t> paddings,
-                  const std::string &output_name);
+    void Conv(const std::string &input_name, const std::string &weight_name,
+              const std::vector<int32_t> strides,
+              const std::vector<int32_t> paddings,
+              const std::string &output_name);
     void Conv(const std::string &input_name, const std::vector<int32_t> strides,
               const std::vector<int32_t> dilations,
               const std::vector<int32_t> paddings,
@@ -28,11 +27,6 @@ class Shaper {
               int32_t padding_left, int32_t padding_right, int32_t padding_top,
               int32_t padding_bottom, int32_t stride_x, int32_t stride_y,
               const std::string &output);
-    void Conv(const std::string &input_name, const std::vector<int32_t> strides,
-              const std::vector<int32_t> dilations,
-              const std::vector<int32_t> paddings,
-              const std::string &weight_name, const std::string &bias_name,
-              const std::string &output_name);
     void Conv(const std::string &input_name, int32_t strideX, int32_t strideY,
               int32_t dilationX, int32_t dilationY, int32_t paddingLeft,
               int32_t paddingRight, int32_t paddingTop, int32_t paddingBottom,
@@ -66,11 +60,11 @@ class Shaper {
                       int32_t endMask, int32_t shrinkAxisMask,
                       const std::string &output_name);
     void Pool(const std::string &input_name, int32_t padding_left,
-                     int32_t padding_right, int32_t padding_top,
-                     int32_t padding_bottom, int32_t stride_x, int32_t stride_y,
-                     int32_t width, int32_t height,
-                     const std::string &output_name);
-    void Pool(const std::string &input_name, const std::vector<int32_t> kernel_shape,
+              int32_t padding_right, int32_t padding_top,
+              int32_t padding_bottom, int32_t stride_x, int32_t stride_y,
+              int32_t width, int32_t height, const std::string &output_name);
+    void Pool(const std::string &input_name,
+              const std::vector<int32_t> kernel_shape,
               const std::vector<int32_t> pads,
               const std::vector<int32_t> strides,
               const std::string &output_name);
@@ -88,7 +82,8 @@ class Shaper {
     void Affine(const std::string &input_name, const std::string &output_name);
     void Affine(const std::string &input_name, const std::string &a,
                 const std::string &b, const std::string &output_name);
-    void Identity(const std::string &input_name, const std::string &output_name);
+    void Identity(const std::string &input_name,
+                  const std::string &output_name);
     void BatchToSpace(const std::string &input_name,
                       const std::vector<int32_t> &block_sizes,
                       const std::string &output_name);

diff --git a/include/dnnlibrary/Device.h b/include/dnnlibrary/Device.h
@@ -0,0 +1,10 @@
+#include <string>
+
+namespace dnn {
+struct Device {
+    const std::string name;
+    const int64_t feature_level;
+    const int type;
+    const std::string version;
+};
+}  // namespace dnn
diff --git a/include/dnnlibrary/ModelBuilder.h b/include/dnnlibrary/ModelBuilder.h
@@ -16,6 +16,7 @@
 #include <common/Shaper.h>
 #include <common/StrKeyMap.h>
 #include <common/data_types.h>
+#include <dnnlibrary/Device.h>
 #include <dnnlibrary/Model.h>
 #include <dnnlibrary/NeuralNetworksWrapper.h>
 
@@ -103,8 +104,6 @@ class ModelBuilder {
     static const uint32_t PREFERENCE_LOW_POWER =
         ANEURALNETWORKS_PREFER_LOW_POWER;
 
-    static int32_t GetAndroidSdkVersion();
-
     Index GetBlobIndex(const std::string &blobName);
     Shape GetBlobDim(const std::string &blobName);
     Shape GetBlobDim(Index index);
@@ -284,6 +283,8 @@ class ModelBuilder {
     void AddScalarOperands(IndexSeq &indexes, Args... args) {
         (indexes.push_back(OperandFromScalar(args)), ...);
     }
+
+    dnn::optional<std::vector<Device>> GetDevices();
 };
 }  // namespace dnn
 #endif  // NNAPIEXAMPLE_MODELBUILDER_H