[CI] Add build with enabled stats

.github/workflows/ci.yml

@@ -17,7 +17,12 @@ jobs:
   build-linux:
     strategy:
       matrix:
-        build_type: [DEBUG, RELEASE]
+        include:
+          - build_type: DEBUG
+          - build_type: RELEASE
+            stats: false
+          - build_type: RELEASE
+            stats: true
     runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v4
@@ -34,7 +39,10 @@ jobs:
             -DCMAKE_C_COMPILER_LAUNCHER=ccache \
             -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
             -DCMAKE_BUILD_TYPE=${{ matrix.build_type }} \
-            -DOPENCV_PATH=3rdparty/opencv/build
+            -DOPENCV_PATH=3rdparty/opencv/build \
+            ${{ matrix.stats && '-DENABLE_STATISTIC_TENSORS=ON' || '' }} \
+            ${{ matrix.stats && '-DENABLE_STATISTIC_TIME=ON' || '' }} \
+            ${{ matrix.stats && '-DENABLE_STATISTIC_WEIGHTS=ON' || '' }}
             cmake --build build --parallel
       env:
         CTEST_OUTPUT_ON_FAILURE: 1
@@ -48,7 +56,7 @@ jobs:
     - name: Upload artifacts
       uses: actions/upload-artifact@v4
       with:
-       name: mnist-${{ matrix.build_type }}
+       name: mnist-${{ matrix.build_type }}${{ matrix.stats && '-stats' || '' }}
        path: |
         build/bin/ACC_MNIST*
         build/bin/opencv_libs/*
@@ -83,7 +91,7 @@ jobs:
           -DCMAKE_C_COMPILER_LAUNCHER=ccache \
           -DCMAKE_CXX_COMPILER_LAUNCHER=ccache \
           -DCMAKE_C_COMPILER=clang \
-          -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++
+          -DCMAKE_CXX_COMPILER=clang++
         cmake --build build --parallel
     - name: Test
       run: cmake --build build -t test

include/layers/ConcatLayer.hpp

@@ -18,6 +18,10 @@ class ConcatLayer : public Layer {
 
   static std::string get_name() { return "ConcatLayer"; }
 
+#ifdef ENABLE_STATISTIC_WEIGHTS
+  Tensor get_weights() override { return Tensor(); }
+#endif
+
  private:
   int64_t axis_;
 

include/layers/DropOutLayer.hpp

@@ -14,6 +14,9 @@ class DropOutLayer : public Layer {
   DropOutLayer(double drop_rate) { drop_rate_ = drop_rate; }
   static std::string get_name() { return "DropOut layer"; }
   void run(const Tensor& input, Tensor& output) override;
+#ifdef ENABLE_STATISTIC_WEIGHTS
+  Tensor get_weights() override { return Tensor(); }
+#endif
 };
 
 }  // namespace it_lab_ai

include/layers/FlattenLayer.hpp

@@ -17,6 +17,9 @@ class FlattenLayer : public Layer {
   FlattenLayer(const std::vector<size_t>& order) : order_(order) {}
   static std::string get_name() { return "Flatten layer"; }
   void run(const Tensor& input, Tensor& output) override;
+#ifdef ENABLE_STATISTIC_WEIGHTS
+  Tensor get_weights() override { return Tensor(); }
+#endif
 };
 
 template <typename ValueType>

include/layers/ReduceLayer.hpp

@@ -19,6 +19,10 @@ class ReduceLayer : public Layer {
 
   static std::string get_name() { return "ReduceLayer"; }
 
+#ifdef ENABLE_STATISTIC_WEIGHTS
+  Tensor get_weights() override { return Tensor(); }
+#endif
+
  private:
   Operation op_;
   int64_t keepdims_;

test/inference/test_inference.cpp

@@ -1,3 +1,4 @@
+#include <stdexcept>
 #include <vector>
 
 #include "graph/graph.hpp"
@@ -42,41 +43,46 @@ TEST(bfs, check_result_vec) {
   std::vector<int> res = {81, 81, 81};
 #ifdef ENABLE_STATISTIC_TENSORS
   std::vector<Tensor> tensors = graph.getTensors();
-  for (int i = 0; i < tensors.size(); i++) {
+  for (size_t i = 0; i < tensors.size(); i++) {
     std::vector<int> ten = *tensors[i].as<int>();
-    for (int j = 0; j < ten.size(); j++) {
+    for (size_t j = 0; j < ten.size(); j++) {
       std::cout << ten[j] << ' ';
     }
     std::cout << '\n';
   }
 #endif
 #ifdef ENABLE_STATISTIC_TIME
   std::vector<std::string> times = graph.getTimeInfo();
-  for (int j = 0; j < times.size(); j++) {
+  for (size_t j = 0; j < times.size(); j++) {
     std::cout << times[j] << ' ';
   }
   std::cout << '\n';
 #endif
 #ifdef ENABLE_STATISTIC_WEIGHTS
   std::vector<Tensor> weights = graph.getWEIGHTS();
-  for (int i = 0; i < weights.size(); i++) {
+  for (size_t i = 0; i < weights.size(); i++) {
     switch (weights[i].get_type()) {
       case Type::kInt: {
         std::vector<int> ten = *weights[i].as<int>();
-        for (int j = 0; j < ten.size(); j++) {
+        for (size_t j = 0; j < ten.size(); j++) {
           std::cout << ten[j] << ' ';
         }
         std::cout << '\n';
         break;
       }
       case Type::kFloat: {
         std::vector<float> ten = *weights[i].as<float>();
-        for (int j = 0; j < ten.size(); j++) {
+        for (size_t j = 0; j < ten.size(); j++) {
           std::cout << ten[j] << ' ';
         }
         std::cout << '\n';
         break;
       }
+      case Type::kUnknown:
+      default: {
+        throw std::runtime_error("Unknown tensor type encountered");
+        break;
+      }
     }
   }
 #endif
@@ -112,24 +118,29 @@ TEST(bfs, check_end_to_end) {
   graph.inference();
 #ifdef ENABLE_STATISTIC_WEIGHTS
   std::vector<Tensor> weights = graph.getWEIGHTS();
-  for (int i = 0; i < weights.size(); i++) {
+  for (size_t i = 0; i < weights.size(); i++) {
     switch (weights[i].get_type()) {
       case Type::kInt: {
         std::vector<int> ten = *weights[i].as<int>();
-        for (int j = 0; j < ten.size(); j++) {
+        for (size_t j = 0; j < ten.size(); j++) {
           std::cout << ten[j] << ' ';
         }
         std::cout << '\n';
         break;
       }
       case Type::kFloat: {
         std::vector<float> ten = *weights[i].as<float>();
-        for (int j = 0; j < ten.size(); j++) {
+        for (size_t j = 0; j < ten.size(); j++) {
           std::cout << ten[j] << ' ';
         }
         std::cout << '\n';
         break;
       }
+      case Type::kUnknown:
+      default: {
+        throw std::runtime_error("Unknown tensor type encountered");
+        break;
+      }
     }
   }
 #endif