clang'

include/layers/Tensor.hpp

@@ -82,6 +82,7 @@ class Tensor {
     if (a.size() != values_.size()) {
       throw std::invalid_argument("Incorrect vector size given to Tensor");
     }
+    values_ = a;
     if (bias.size() != shape_[shape_.dims() - 1]) {
       throw std::invalid_argument(
           "Bias size does not match the last dimension of the shape");

src/Weights_Reader/reader_weights.cpp

@@ -80,7 +80,6 @@ void extract_values_without_bias(const json& j, std::vector<float>& values) {
   std::cout << "Values size after extraction: " << values.size() << std::endl;
 }
 
-
 // Функция для определения формы из JSON
 void parse_json_shape(const json& j, std::vector<size_t>& shape, size_t dim) {
   // Если dim == 0, просто проверяем первый уровень
@@ -117,7 +116,6 @@ void parse_json_shape(const json& j, std::vector<size_t>& shape, size_t dim) {
   }
 }
 
-
 void extract_bias_from_json(const json& j, std::vector<float>& bias) {
   if (j.is_array()) {
     if (!j.empty() && j.back().is_array()) {
@@ -160,23 +158,16 @@ Tensor create_tensor_from_json(const json& j, Type type) {
     if (expected_size == 1 && shape.empty()) {
       expected_size = 0;
     }
-
     std::cout << "Expected size: " << expected_size << std::endl;
-
-
     try {
       extract_bias_from_json(j, bias);
       std::cout << "Extracted bias size: " << bias.size() << std::endl;
     } catch (const std::exception& e) {
       std::cout << "No bias found or error extracting bias: " << e.what()
                 << std::endl;
     }
-
-
     Shape sh(shape);
-
     return make_tensor<float>(vals, sh, bias);
-
   }
   throw std::invalid_argument("Unsupported type or invalid JSON format");
 }

test/model_read/model_read.cpp

@@ -65,7 +65,6 @@ TEST(ExtractValuesFromJsonTests, HandlesFlatArray) {
   EXPECT_EQ(values, expected);
 }
 
-
 TEST(ExtractValuesFromJsonTests, HandlesNestedArray) {
   json j = json::array({{1.0, 2.0}, {3.0, 4.0}});
   std::vector<float> values;
@@ -81,6 +80,3 @@ TEST(ParseJsonShapeTests, HandlesEmptyArray) {
   std::vector<size_t> expected = {0};
   EXPECT_EQ(shape, expected);
 }
-
-
-