From e1f90afa8d23fbfdac9afddd43c061011fdc43ce Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Tue, 24 Feb 2026 12:16:41 +0300
Subject: [PATCH 01/38] numPhoto

---
 app/Graph/acc_check.cpp | 75 +++++++++++++++++++++++++++++++----------
 1 file changed, 57 insertions(+), 18 deletions(-)

diff --git a/app/Graph/acc_check.cpp b/app/Graph/acc_check.cpp
index a864c36d..20ee1cbd 100644
--- a/app/Graph/acc_check.cpp
+++ b/app/Graph/acc_check.cpp
@@ -13,6 +13,7 @@ using namespace it_lab_ai;
 int main(int argc, char* argv[]) {
   std::string model_name = "alexnet_mnist";
   RuntimeOptions options;
+  int numPhoto = 1000;
 
   for (int i = 1; i < argc; ++i) {
     if (std::string(argv[i]) == "--model" && i + 1 < argc) {
@@ -48,6 +49,18 @@ int main(int argc, char* argv[]) {
       }
     } else if (std::string(argv[i]) == "--threads" && i + 1 < argc) {
       options.threads = std::stoi(argv[++i]);
+    } else {
+      try {
+        numPhoto = std::stoi(argv[i]);
+
+        if (numPhoto < 1 || numPhoto > 50000) {
+          std::cerr << "Warning: numPhoto should be between 1 and 10000 "
+                    << "Using value: " << numPhoto << std::endl;
+        }
+      } catch (const std::exception& e) {
+        std::cerr << "Error: Invalid numeric argument: " << argv[i]
+                  << ". Using default value: 1000" << e.what()<<std::endl;
+      }
     }
   }
 
@@ -98,7 +111,7 @@ int main(int argc, char* argv[]) {
           for (int j = 0; j < 28; ++j) {
             size_t a = ind;
             for (size_t n = 0; n < name; n++) a += counts[n] + 1;
-            res[(a) * 28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
+            res[(a)*28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
           }
         }
       }
@@ -153,33 +166,45 @@ int main(int argc, char* argv[]) {
             entry.path().extension() == ".jpg" ||
             entry.path().extension() == ".jpeg") {
           counts[class_id]++;
-          total_images++;
         }
       }
     }
   }
 
-  if (total_images == 0) {
-    std::cerr << "No images found in dataset path: " << dataset_path << '\n';
-    return 1;
-  }
+  size_t images_per_class_base = numPhoto / 1000;
+  size_t remaining = numPhoto % 1000;
 
   int channels = input_shape[1];
   int height = input_shape[2];
   int width = input_shape[3];
   size_t image_size = channels * height * width;
 
-  all_image_data.resize(total_images * image_size);
+  all_image_data.reserve(numPhoto * image_size);
+  image_paths.reserve(numPhoto);
+  true_labels.reserve(numPhoto);
 
   size_t current_index = 0;
+  total_images = 0;
+
   for (int class_id = 0; class_id < 1000; ++class_id) {
+    size_t need_from_class = images_per_class_base;
+    if (remaining > 0) {
+      need_from_class++;
+      remaining--;
+    }
+
+    if (need_from_class == 0) continue;
+
     std::ostringstream folder_oss;
     folder_oss << std::setw(5) << std::setfill('0') << class_id;
     std::string class_folder_path = dataset_path + "/" + folder_oss.str();
 
     if (!fs::exists(class_folder_path)) continue;
 
+    size_t taken = 0;
     for (const auto& entry : fs::directory_iterator(class_folder_path)) {
+      if (taken >= need_from_class) break;
+
       if (entry.path().extension() == ".png" ||
           entry.path().extension() == ".jpg" ||
           entry.path().extension() == ".jpeg") {
@@ -194,24 +219,37 @@ int main(int argc, char* argv[]) {
             prepare_image(image, input_shape, model_name);
         const std::vector<float>& image_data = *prepared_tensor.as<float>();
 
-        std::copy(image_data.begin(), image_data.end(),
-                  all_image_data.begin() + current_index * image_size);
+        all_image_data.insert(all_image_data.end(), image_data.begin(),
+                              image_data.end());
 
         image_paths.push_back(entry.path().string());
         true_labels.push_back(class_id);
-        current_index++;
+        taken++;
+        total_images++;
       }
     }
+
+    if (taken < need_from_class) {
+      std::cout << "Warning: Class " << class_id << " has only " << taken
+                << " images (needed " << need_from_class << ")" << std::endl;
+    }
+  }
+
+  if (total_images != numPhoto) {
+    std::cout << "Warning: Requested " << numPhoto << " images but loaded "
+              << total_images << " due to insufficient data" << std::endl;
+    numPhoto = total_images;
   }
 
   it_lab_ai::Shape input_shape_imagenet(
-      {total_images, static_cast<size_t>(channels), static_cast<size_t>(height),
-       static_cast<size_t>(width)});
+      {static_cast<size_t>(numPhoto), static_cast<size_t>(channels),
+       static_cast<size_t>(height), static_cast<size_t>(width)});
   it_lab_ai::Tensor input =
       it_lab_ai::make_tensor(all_image_data, input_shape_imagenet);
 
   size_t output_classes = 1000;
-  it_lab_ai::Shape output_shape({total_images, output_classes});
+  it_lab_ai::Shape output_shape(
+      {static_cast<size_t>(numPhoto), output_classes});
   it_lab_ai::Tensor output =
       it_lab_ai::Tensor(output_shape, it_lab_ai::Type::kFloat);
 
@@ -219,10 +257,11 @@ int main(int argc, char* argv[]) {
   build_graph(graph, input, output, json_path, options, false);
   graph.inference(options);
   print_time_stats(graph);
+
   std::vector<std::vector<float>> processed_outputs;
   const std::vector<float>& raw_output = *output.as<float>();
 
-  for (size_t i = 0; i < total_images; ++i) {
+  for (size_t i = 0; i < static_cast<size_t>(numPhoto); ++i) {
     std::vector<float> single_output(
         raw_output.begin() + i * output_classes,
         raw_output.begin() + (i + 1) * output_classes);
@@ -262,14 +301,14 @@ int main(int argc, char* argv[]) {
   }
 
   double final_accuracy_top1 =
-      (static_cast<double>(correct_predictions_top1) / total_images) * 100;
+      (static_cast<double>(correct_predictions_top1) / numPhoto) * 100;
   double final_accuracy_top5 =
-      (static_cast<double>(correct_predictions_top5) / total_images) * 100;
+      (static_cast<double>(correct_predictions_top5) / numPhoto) * 100;
 
   std::cout << "\nFinal Results:" << '\n';
   std::cout << "Model: " << model_name << '\n';
   std::cout << "Dataset: " << dataset_path << '\n';
-  std::cout << "Total images: " << total_images << '\n';
+  std::cout << "Total images: " << numPhoto << '\n';
   std::cout << "Correct predictions (Top-1): " << correct_predictions_top1
             << '\n';
   std::cout << "Correct predictions (Top-5): " << correct_predictions_top5
@@ -280,4 +319,4 @@ int main(int argc, char* argv[]) {
             << final_accuracy_top5 << "%" << '\n';
 
   return 0;
-}
\ No newline at end of file
+}

From fe9785aa03740b0ee3c4b6c056e0bdca605fca15 Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Tue, 24 Feb 2026 12:19:43 +0300
Subject: [PATCH 02/38] cl

---
 app/Graph/acc_check.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/app/Graph/acc_check.cpp b/app/Graph/acc_check.cpp
index 20ee1cbd..dbed4f62 100644
--- a/app/Graph/acc_check.cpp
+++ b/app/Graph/acc_check.cpp
@@ -59,7 +59,7 @@ int main(int argc, char* argv[]) {
         }
       } catch (const std::exception& e) {
         std::cerr << "Error: Invalid numeric argument: " << argv[i]
-                  << ". Using default value: 1000" << e.what()<<std::endl;
+                  << ". Using default value: 1000" << e.what() << std::endl;
       }
     }
   }
@@ -111,7 +111,7 @@ int main(int argc, char* argv[]) {
           for (int j = 0; j < 28; ++j) {
             size_t a = ind;
             for (size_t n = 0; n < name; n++) a += counts[n] + 1;
-            res[(a)*28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
+            res[(a) * 28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
           }
         }
       }

From d76e10dc04866409461af1d2a4caa9fec232d121 Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Tue, 24 Feb 2026 12:24:06 +0300
Subject: [PATCH 03/38] numPhoto

---
 app/Graph/acc_check.cpp | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/app/Graph/acc_check.cpp b/app/Graph/acc_check.cpp
index dbed4f62..9b4c0ee5 100644
--- a/app/Graph/acc_check.cpp
+++ b/app/Graph/acc_check.cpp
@@ -13,7 +13,7 @@ using namespace it_lab_ai;
 int main(int argc, char* argv[]) {
   std::string model_name = "alexnet_mnist";
   RuntimeOptions options;
-  int numPhoto = 1000;
+  size_t numPhoto = 1000;
 
   for (int i = 1; i < argc; ++i) {
     if (std::string(argv[i]) == "--model" && i + 1 < argc) {
@@ -183,7 +183,6 @@ int main(int argc, char* argv[]) {
   image_paths.reserve(numPhoto);
   true_labels.reserve(numPhoto);
 
-  size_t current_index = 0;
   total_images = 0;
 
   for (int class_id = 0; class_id < 1000; ++class_id) {

From 25c23eb1bff61890591ce5f347cb47635b249830 Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Tue, 24 Feb 2026 14:54:12 +0300
Subject: [PATCH 04/38] --model in py_onnx

---
 app/Converters/parser_onnx.py | 42 +++++++++++++++++++++++++++++++----
 1 file changed, 38 insertions(+), 4 deletions(-)

diff --git a/app/Converters/parser_onnx.py b/app/Converters/parser_onnx.py
index 33b20fef..0c0b931a 100644
--- a/app/Converters/parser_onnx.py
+++ b/app/Converters/parser_onnx.py
@@ -1,9 +1,15 @@
+#!/usr/bin/env python3
 import json
-import onnx
 import os
+import sys
+import argparse
+import onnx
+import numpy as np
 from onnx import TensorProto
 from onnx import helper, numpy_helper
 from ultralytics import YOLO
+import tensorflow as tf
+from tensorflow.keras.models import load_model
 
 
 def convert_pt_to_onnx(pt_model_path, onnx_model_path=None):
@@ -163,10 +169,38 @@ def default(self, obj):
 
     print(f"Модель успешно сохранена в {output_json_path}")
 
+parser = argparse.ArgumentParser(description='Конвертация моделей в JSON формат')
+parser.add_argument('model_name', type=str,
+                        choices=['googlenet', 'densenet', 'resnet', 'yolo', 'alexnet'],
+                        help='Имя модели для обработки')
+
+args = parser.parse_args()
 
 BASE_DIR = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+MODELS_DIR = os.path.join(BASE_DIR, 'docs', 'models')
+JSONS_DIR = os.path.join(BASE_DIR, 'docs', 'jsons')
+
+os.makedirs(MODELS_DIR, exist_ok=True)
+os.makedirs(JSONS_DIR, exist_ok=True)
+
+model_files = {
+        'googlenet': 'GoogLeNet.onnx',
+        'densenet': 'densenet121_Opset16.onnx',
+        'resnet': 'resnest101e_Opset16.onnx',
+        'yolo': 'yolo11x-cls.pt'
+}
+
+output_files = {
+        'googlenet': 'googlenet_onnx_model.json',
+        'densenet': 'densenet121_Opset16_onnx_model.json',
+        'resnet': 'resnest101e_Opset16_onnx_model.json',
+        'yolo': 'yolo11x-cls_onnx_model.json',
+}
+
+model_filename = model_files[args.model_name]
+output_filename = output_files[args.model_name]
 
-MODEL_PATH = os.path.join(BASE_DIR, 'docs\\models', 'resnest101e_Opset16.onnx')
-MODEL_DATA_PATH = os.path.join(BASE_DIR, 'docs\\jsons', 'resnest101e_Opset16_onnx_model.json')
+model_path = os.path.join(MODELS_DIR, model_filename)
+output_path = os.path.join(JSONS_DIR, output_filename)
 
-onnx_to_json(MODEL_PATH, MODEL_DATA_PATH)
\ No newline at end of file
+onnx_to_json(model_path, output_path)

From 93bbb72512a11c5fc7233b67da22cd99f911e031 Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Tue, 24 Feb 2026 16:20:30 +0300
Subject: [PATCH 05/38] load dataset

---
 app/Converters/download_imagenet.py | 32 +++++++++++++++++++++++++++++
 1 file changed, 32 insertions(+)
 create mode 100644 app/Converters/download_imagenet.py

diff --git a/app/Converters/download_imagenet.py b/app/Converters/download_imagenet.py
new file mode 100644
index 00000000..96e1dc8c
--- /dev/null
+++ b/app/Converters/download_imagenet.py
@@ -0,0 +1,32 @@
+# app/Converters/download_imagenet.py
+import os
+from datasets import load_dataset
+from PIL import Image
+
+
+base_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+output_dir = os.path.join(base_dir, 'docs', 'imagenet-paste', 'validation')
+os.makedirs(output_dir, exist_ok=True)
+
+print("Загрузка датасета helenqu/ImageNet-Paste...")
+ds = load_dataset(
+    "helenqu/ImageNet-Paste",
+    split="validation",
+    trust_remote_code=True
+)
+
+print(f"Датасет загружен. Всего записей: {len(ds)}")
+
+for i, item in enumerate(ds):
+    try:
+        image = item['image']
+
+        output_path = os.path.join(output_dir, f"image_{i}.jpg")
+        image.save(output_path, 'JPEG')
+
+    except Exception as e:
+        print(f"Ошибка при сохранении изображения {i}: {e}")
+        continue
+
+print(f"\n✅ Готово! Сохранено {len(ds)} изображений в {output_dir}")
+print(f"Размер датасета: {len(ds)} изображений")
\ No newline at end of file

From 6d562cf5fe5c56379c89156074882d6fcdd95440 Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Tue, 24 Feb 2026 16:22:47 +0300
Subject: [PATCH 06/38] reqs.txt

---
 app/Converters/requirements.txt | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/app/Converters/requirements.txt b/app/Converters/requirements.txt
index 7c48b536..b447200c 100644
--- a/app/Converters/requirements.txt
+++ b/app/Converters/requirements.txt
@@ -6,4 +6,6 @@ torch==2.2.1+cpu
 torchvision==0.17.1+cpu
 ultralytics>=8.0.0
 numpy>=1.21.0
-protobuf>=3.20.0
\ No newline at end of file
+protobuf>=3.20.0
+datasets>=2.14.0
+Pillow>=10.0.0
\ No newline at end of file

From 2929f06d3428d77d581d0476ec7ef74072b47565 Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Tue, 24 Feb 2026 16:30:25 +0300
Subject: [PATCH 07/38] load dataset

---
 app/Converters/download_imagenet.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/app/Converters/download_imagenet.py b/app/Converters/download_imagenet.py
index 96e1dc8c..059478e8 100644
--- a/app/Converters/download_imagenet.py
+++ b/app/Converters/download_imagenet.py
@@ -5,7 +5,7 @@
 
 
 base_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-output_dir = os.path.join(base_dir, 'docs', 'imagenet-paste', 'validation')
+output_dir = os.path.join(base_dir, 'docs', 'ImageNet', 'test')  # Изменено здесь
 os.makedirs(output_dir, exist_ok=True)
 
 print("Загрузка датасета helenqu/ImageNet-Paste...")

From a4d16112b956717314bfd1a2abc35b20f15b279d Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Tue, 24 Feb 2026 16:31:26 +0300
Subject: [PATCH 08/38] add onnx acc

---
 .github/workflows/ci.yml | 157 ++++++++++++++++++++++++++++++++++++++-
 1 file changed, 156 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index c73d242e..5387f823 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -229,7 +229,7 @@ jobs:
         token: ${{ secrets.CODECOV_TOKEN }}
         slug: embedded-dev-research/ITLabAI
         
-  evaluate-model:
+  evaluate-model-alexnet:
     runs-on: ubuntu-latest
     needs: [build-linux]
     permissions:
@@ -319,3 +319,158 @@ jobs:
           git commit -m "[CI] Update accuracy: $(cat accuracy_value.txt)"
           git push origin master
         fi
+
+  evaluate-models-onnx:
+    runs-on: ubuntu-latest
+    needs: [build-linux]
+    permissions:
+      contents: write
+
+  strategy:
+    matrix:
+      model: [googlenet, densenet, resnet, yolo]
+        include:
+        - model: googlenet
+          parser: parser_onnx.py
+          model_file: GoogLeNet.onnx
+          model_path: docs/models/GoogLeNet.onnx
+          extra_args: "--onednn 10000"
+        - model: densenet
+          parser: parser_onnx.py
+          model_file: densenet121_Opset16.onnx
+          model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/densenet121_Opset16_timm/densenet121_Opset16.onnx?download=
+          extra_args: "--onednn 10000"
+        - model: resnet
+          parser: parser_onnx.py
+          model_file: resnest101e_Opset16.onnx
+          model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/resnest101e_Opset16_timm/resnest101e_Opset16.onnx?download=
+          extra_args: "--onednn 10000"
+        - model: yolo
+          parser: parser_onnx.py
+          model_file: yolo11x-cls.pt
+          model_url: https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo11x-cls.pt
+          extra_args: "--onednn 10000"
+
+  steps:
+  - uses: actions/checkout@v4
+    with:
+      fetch-depth: 0
+  
+  - name: Download binary and libs
+    uses: actions/download-artifact@v4
+    with:
+      name: mnist-RELEASE
+      path: build/
+      
+  - name: Set binary path
+    id: set_eval_binary
+    run: |
+      echo "EVAL_BINARY=build/bin/ACC" >> $GITHUB_OUTPUT
+      
+  - name: Install system dependencies
+    run: |
+      sudo apt-get update
+      sudo apt-get install -y libgtk-3-0 libtbb12 libjpeg-dev libpng-dev libtiff-dev libopenjp2-7 libdnnl3
+      sudo ldconfig
+
+  - name: Download model
+    run: |
+      mkdir -p docs/models
+      echo "Скачивание ${{ matrix.model_file }} из ${{ matrix.model_url }}"
+      wget -O docs/models/${{ matrix.model.file }} ${{ matrix.model.url }}
+      ls -la docs/models/
+
+  - name: Setup Python
+    uses: actions/setup-python@v4
+    with:
+      python-version: '3.10'
+  
+  - name: Install Python dependencies from requirements.txt
+    run: |
+      cd app/Converters
+      pip install -r requirements.txt
+      cd ../..
+
+  - name: Generate model JSON
+    run: |
+      mkdir -p docs/jsons
+      cd app/Converters
+      python ${{ matrix.parser }} ${{ matrix.model }}
+      cd ../..
+      echo "Сгенерированные JSON файлы:"
+      ls -la docs/jsons/
+
+  - name: Download ImageNet-Paste dataset
+    run: |
+     mkdir -p docs/ImageNet/test  # Изменено с imagenet-paste/validation на ImageNet/test
+     cd app/Converters
+     python download_imagenet.py
+     cd ../..
+     echo "📊 Статистика датасета:"
+     echo "Всего изображений: $(ls docs/ImageNet/test/*.jpg 2>/dev/null | wc -l)"
+
+  - name: Prepare environment
+    run: |
+      chmod +x "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}"
+      echo "LD_LIBRARY_PATH=$PWD/build/bin/all_libs:/usr/lib/x86_64-linux-gnu" >> $GITHUB_ENV
+      
+  - name: Run evaluation
+    run: |
+     DATASET_PATH="docs/ImageNet/test"  # Изменено с imagenet-paste/validation на ImageNet/test
+    
+     echo "Запуск оценки для модели ${{ matrix.model }}"
+     echo "Команда: ${{ steps.set_eval_binary.outputs.EVAL_BINARY }} --model ${{ matrix.model }} ${{ matrix.extra_args }}"
+    
+     "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}" \
+       --model ${{ matrix.model }} \
+       ${{ matrix.extra_args }} > accuracy_${{ matrix.model }}.txt 2>&1
+      
+       if [ $? -ne 0 ]; then
+        echo "Ошибка при оценке модели ${{ matrix.model }}"
+        cat accuracy_${{ matrix.model }}.txt
+        exit 1
+       fi
+      
+       echo "Результат оценки:"
+       cat accuracy_${{ matrix.model }}.txt
+
+  - name: Extract accuracy value
+    run: |
+      ACCURACY=$(grep -oE '[0-9]+\.?[0-9]*%' accuracy_${{ matrix.model }}.txt | head -1 || echo "0%")
+      echo "$ACCURACY" > accuracy_value_${{ matrix.model }}.txt
+      echo "Accuracy for ${{ matrix.model }}: $ACCURACY"
+
+  - name: Upload accuracy artifacts
+    uses: actions/upload-artifact@v4
+    with:
+      name: accuracy-${{ matrix.model }}
+      path: |
+        accuracy_${{ matrix.model }}.txt
+        accuracy_value_${{ matrix.model }}.txt
+
+  - name: Update README for model (master only)
+    if: github.ref == 'refs/heads/master'
+    run: |
+      ACCURACY=$(cat accuracy_value_${{ matrix.model }}.txt | sed 's/%//g')
+      DATE=$(date '+%Y-%m-%d')
+      
+      if grep -q "<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->" README.md; then
+        sed -i "s/<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->.*<!--END_ACCURACY_${{ matrix.model }}-->/<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->Accuracy: ${ACCURACY}% (updated: ${DATE})<!--END_ACCURACY_${{ matrix.model }}-->/" README.md
+        echo "Обновлена точность для ${{ matrix.model }} в README"
+      else
+        echo "Плейсхолдер для ${{ matrix.model }} не найден в README, добавляем в конец"
+        echo -e "\n## ${{ matrix.model }} Accuracy\n<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->Accuracy: ${ACCURACY}% (updated: ${DATE})<!--END_ACCURACY_${{ matrix.model }}-->\n" >> README.md
+      fi
+
+  - name: Commit and push changes (master only)
+    if: github.ref == 'refs/heads/master'
+    run: |
+      git config --global user.name "GitHub Actions"
+      git config --global user.email "actions@github.com"
+      git add README.md
+      if git diff-index --quiet HEAD --; then
+        echo "No changes to commit"
+      else
+        git commit -m "[CI] Update accuracy for ${{ matrix.model }}: $(cat accuracy_value_${{ matrix.model }}.txt)"
+        git push origin master
+      fi

From 69c19fa07df83de9127e9d6f4517aadca5290541 Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Fri, 27 Feb 2026 10:28:26 +0300
Subject: [PATCH 09/38] format

---
 .github/workflows/ci.yml | 31 +++++++++++++++----------------
 1 file changed, 15 insertions(+), 16 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 5387f823..b09fde45 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -402,12 +402,11 @@ jobs:
 
   - name: Download ImageNet-Paste dataset
     run: |
-     mkdir -p docs/ImageNet/test  # Изменено с imagenet-paste/validation на ImageNet/test
-     cd app/Converters
-     python download_imagenet.py
-     cd ../..
-     echo "📊 Статистика датасета:"
-     echo "Всего изображений: $(ls docs/ImageNet/test/*.jpg 2>/dev/null | wc -l)"
+      mkdir -p docs/ImageNet/test  # Изменено с imagenet-paste/validation на ImageNet/test
+      cd app/Converters
+      python download_imagenet.py
+      cd ../..
+      echo "Всего изображений: $(ls docs/ImageNet/test/*.jpg 2>/dev/null | wc -l)"
 
   - name: Prepare environment
     run: |
@@ -416,23 +415,23 @@ jobs:
       
   - name: Run evaluation
     run: |
-     DATASET_PATH="docs/ImageNet/test"  # Изменено с imagenet-paste/validation на ImageNet/test
+      DATASET_PATH="docs/ImageNet/test"  # Изменено с imagenet-paste/validation на ImageNet/test
     
-     echo "Запуск оценки для модели ${{ matrix.model }}"
-     echo "Команда: ${{ steps.set_eval_binary.outputs.EVAL_BINARY }} --model ${{ matrix.model }} ${{ matrix.extra_args }}"
+      echo "Запуск оценки для модели ${{ matrix.model }}"
+      echo "Команда: ${{ steps.set_eval_binary.outputs.EVAL_BINARY }} --model ${{ matrix.model }} ${{ matrix.extra_args }}"
     
-     "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}" \
-       --model ${{ matrix.model }} \
-       ${{ matrix.extra_args }} > accuracy_${{ matrix.model }}.txt 2>&1
+      "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}" \
+      --model ${{ matrix.model }} \
+      ${{ matrix.extra_args }} > accuracy_${{ matrix.model }}.txt 2>&1
       
-       if [ $? -ne 0 ]; then
+      if [ $? -ne 0 ]; then
         echo "Ошибка при оценке модели ${{ matrix.model }}"
         cat accuracy_${{ matrix.model }}.txt
         exit 1
-       fi
+      fi
       
-       echo "Результат оценки:"
-       cat accuracy_${{ matrix.model }}.txt
+      echo "Результат оценки:"
+      cat accuracy_${{ matrix.model }}.txt
 
   - name: Extract accuracy value
     run: |

From a5838d9dbd886873a8a84d88255f1e71ba05a1ba Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Fri, 27 Feb 2026 10:47:48 +0300
Subject: [PATCH 10/38] format

---
 .github/workflows/ci.yml | 257 +++++++++++++++++++--------------------
 1 file changed, 128 insertions(+), 129 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index b09fde45..1487872e 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -325,151 +325,150 @@ jobs:
     needs: [build-linux]
     permissions:
       contents: write
-
-  strategy:
-    matrix:
-      model: [googlenet, densenet, resnet, yolo]
+    strategy:
+      matrix:
+        model: [googlenet, densenet, resnet, yolo]
         include:
-        - model: googlenet
-          parser: parser_onnx.py
-          model_file: GoogLeNet.onnx
-          model_path: docs/models/GoogLeNet.onnx
-          extra_args: "--onednn 10000"
-        - model: densenet
-          parser: parser_onnx.py
-          model_file: densenet121_Opset16.onnx
-          model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/densenet121_Opset16_timm/densenet121_Opset16.onnx?download=
-          extra_args: "--onednn 10000"
-        - model: resnet
-          parser: parser_onnx.py
-          model_file: resnest101e_Opset16.onnx
-          model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/resnest101e_Opset16_timm/resnest101e_Opset16.onnx?download=
-          extra_args: "--onednn 10000"
-        - model: yolo
-          parser: parser_onnx.py
-          model_file: yolo11x-cls.pt
-          model_url: https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo11x-cls.pt
-          extra_args: "--onednn 10000"
+          - model: googlenet
+            parser: parser_onnx.py
+            model_file: GoogLeNet.onnx
+            model_path: docs/models/GoogLeNet.onnx
+            extra_args: "--onednn 10000"
+          - model: densenet
+            parser: parser_onnx.py
+            model_file: densenet121_Opset16.onnx
+            model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/densenet121_Opset16_timm/densenet121_Opset16.onnx?download=
+            extra_args: "--onednn 10000"
+          - model: resnet
+            parser: parser_onnx.py
+            model_file: resnest101e_Opset16.onnx
+            model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/resnest101e_Opset16_timm/resnest101e_Opset16.onnx?download=
+            extra_args: "--onednn 10000"
+          - model: yolo
+            parser: parser_onnx.py
+            model_file: yolo11x-cls.pt
+            model_url: https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo11x-cls.pt
+            extra_args: "--onednn 10000"
 
-  steps:
-  - uses: actions/checkout@v4
-    with:
-      fetch-depth: 0
+    steps:
+    - uses: actions/checkout@v4
+      with:
+        fetch-depth: 0
   
-  - name: Download binary and libs
-    uses: actions/download-artifact@v4
-    with:
-      name: mnist-RELEASE
-      path: build/
+    - name: Download binary and libs
+      uses: actions/download-artifact@v4
+      with:
+        name: mnist-RELEASE
+        path: build/
       
-  - name: Set binary path
-    id: set_eval_binary
-    run: |
-      echo "EVAL_BINARY=build/bin/ACC" >> $GITHUB_OUTPUT
+    - name: Set binary path
+      id: set_eval_binary
+      run: |
+        echo "EVAL_BINARY=build/bin/ACC" >> $GITHUB_OUTPUT
       
-  - name: Install system dependencies
-    run: |
-      sudo apt-get update
-      sudo apt-get install -y libgtk-3-0 libtbb12 libjpeg-dev libpng-dev libtiff-dev libopenjp2-7 libdnnl3
-      sudo ldconfig
+    - name: Install system dependencies
+      run: |
+        sudo apt-get update
+        sudo apt-get install -y libgtk-3-0 libtbb12 libjpeg-dev libpng-dev libtiff-dev libopenjp2-7 libdnnl3
+        sudo ldconfig
 
-  - name: Download model
-    run: |
-      mkdir -p docs/models
-      echo "Скачивание ${{ matrix.model_file }} из ${{ matrix.model_url }}"
-      wget -O docs/models/${{ matrix.model.file }} ${{ matrix.model.url }}
-      ls -la docs/models/
+    - name: Download model
+      run: |
+        mkdir -p docs/models
+        echo "Скачивание ${{ matrix.model_file }} из ${{ matrix.model_url }}"
+        wget -O docs/models/${{ matrix.model_file }} ${{ matrix.model_url }}
+        ls -la docs/models/
 
-  - name: Setup Python
-    uses: actions/setup-python@v4
-    with:
-      python-version: '3.10'
-  
-  - name: Install Python dependencies from requirements.txt
-    run: |
-      cd app/Converters
-      pip install -r requirements.txt
-      cd ../..
+    - name: Setup Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.10'
 
-  - name: Generate model JSON
-    run: |
-      mkdir -p docs/jsons
-      cd app/Converters
-      python ${{ matrix.parser }} ${{ matrix.model }}
-      cd ../..
-      echo "Сгенерированные JSON файлы:"
-      ls -la docs/jsons/
+    - name: Install Python dependencies from requirements.txt
+      run: |
+        cd app/Converters
+        pip install -r requirements.txt
+        cd ../..
 
-  - name: Download ImageNet-Paste dataset
-    run: |
-      mkdir -p docs/ImageNet/test  # Изменено с imagenet-paste/validation на ImageNet/test
-      cd app/Converters
-      python download_imagenet.py
-      cd ../..
-      echo "Всего изображений: $(ls docs/ImageNet/test/*.jpg 2>/dev/null | wc -l)"
+    - name: Generate model JSON
+      run: |
+        mkdir -p docs/jsons
+        cd app/Converters
+        python ${{ matrix.parser }} ${{ matrix.model }}
+        cd ../..
+        echo "Сгенерированные JSON файлы:"
+        ls -la docs/jsons/
 
-  - name: Prepare environment
-    run: |
-      chmod +x "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}"
-      echo "LD_LIBRARY_PATH=$PWD/build/bin/all_libs:/usr/lib/x86_64-linux-gnu" >> $GITHUB_ENV
-      
-  - name: Run evaluation
-    run: |
-      DATASET_PATH="docs/ImageNet/test"  # Изменено с imagenet-paste/validation на ImageNet/test
+    - name: Download ImageNet-Paste dataset
+      run: |
+        mkdir -p docs/ImageNet/test  # Изменено с imagenet-paste/validation на ImageNet/test
+        cd app/Converters
+        python download_imagenet.py
+        cd ../..
+        echo "Всего изображений: $(ls docs/ImageNet/test/*.jpg 2>/dev/null | wc -l)"
+
+    - name: Prepare environment
+      run: |
+        chmod +x "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}"
+        echo "LD_LIBRARY_PATH=$PWD/build/bin/all_libs:/usr/lib/x86_64-linux-gnu" >> $GITHUB_ENV
+
+    - name: Run evaluation
+      run: |
+        DATASET_PATH="docs/ImageNet/test"  # Изменено с imagenet-paste/validation на ImageNet/test
     
-      echo "Запуск оценки для модели ${{ matrix.model }}"
-      echo "Команда: ${{ steps.set_eval_binary.outputs.EVAL_BINARY }} --model ${{ matrix.model }} ${{ matrix.extra_args }}"
+        echo "Запуск оценки для модели ${{ matrix.model }}"
+        echo "Команда: ${{ steps.set_eval_binary.outputs.EVAL_BINARY }} --model ${{ matrix.model }} ${{ matrix.extra_args }}"
     
-      "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}" \
-      --model ${{ matrix.model }} \
-      ${{ matrix.extra_args }} > accuracy_${{ matrix.model }}.txt 2>&1
+        "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}" \
+        --model ${{ matrix.model }} \
+        ${{ matrix.extra_args }} > accuracy_${{ matrix.model }}.txt 2>&1
       
-      if [ $? -ne 0 ]; then
-        echo "Ошибка при оценке модели ${{ matrix.model }}"
-        cat accuracy_${{ matrix.model }}.txt
-        exit 1
-      fi
+        if [ $? -ne 0 ]; then
+          echo "Ошибка при оценке модели ${{ matrix.model }}"
+          cat accuracy_${{ matrix.model }}.txt
+          exit 1
+        fi
       
-      echo "Результат оценки:"
-      cat accuracy_${{ matrix.model }}.txt
+        echo "Результат оценки:"
+        cat accuracy_${{ matrix.model }}.txt
 
-  - name: Extract accuracy value
-    run: |
-      ACCURACY=$(grep -oE '[0-9]+\.?[0-9]*%' accuracy_${{ matrix.model }}.txt | head -1 || echo "0%")
-      echo "$ACCURACY" > accuracy_value_${{ matrix.model }}.txt
-      echo "Accuracy for ${{ matrix.model }}: $ACCURACY"
+    - name: Extract accuracy value
+      run: |
+        ACCURACY=$(grep -oE '[0-9]+\.?[0-9]*%' accuracy_${{ matrix.model }}.txt | head -1 || echo "0%")
+        echo "$ACCURACY" > accuracy_value_${{ matrix.model }}.txt
+        echo "Accuracy for ${{ matrix.model }}: $ACCURACY"
 
-  - name: Upload accuracy artifacts
-    uses: actions/upload-artifact@v4
-    with:
-      name: accuracy-${{ matrix.model }}
-      path: |
-        accuracy_${{ matrix.model }}.txt
-        accuracy_value_${{ matrix.model }}.txt
+    - name: Upload accuracy artifacts
+      uses: actions/upload-artifact@v4
+      with:
+        name: accuracy-${{ matrix.model }}
+        path: |
+          accuracy_${{ matrix.model }}.txt
+          accuracy_value_${{ matrix.model }}.txt
 
-  - name: Update README for model (master only)
-    if: github.ref == 'refs/heads/master'
-    run: |
-      ACCURACY=$(cat accuracy_value_${{ matrix.model }}.txt | sed 's/%//g')
-      DATE=$(date '+%Y-%m-%d')
+    - name: Update README for model (master only)
+      if: github.ref == 'refs/heads/master'
+      run: |
+        ACCURACY=$(cat accuracy_value_${{ matrix.model }}.txt | sed 's/%//g')
+        DATE=$(date '+%Y-%m-%d')
       
-      if grep -q "<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->" README.md; then
-        sed -i "s/<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->.*<!--END_ACCURACY_${{ matrix.model }}-->/<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->Accuracy: ${ACCURACY}% (updated: ${DATE})<!--END_ACCURACY_${{ matrix.model }}-->/" README.md
-        echo "Обновлена точность для ${{ matrix.model }} в README"
-      else
-        echo "Плейсхолдер для ${{ matrix.model }} не найден в README, добавляем в конец"
-        echo -e "\n## ${{ matrix.model }} Accuracy\n<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->Accuracy: ${ACCURACY}% (updated: ${DATE})<!--END_ACCURACY_${{ matrix.model }}-->\n" >> README.md
-      fi
+        if grep -q "<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->" README.md; then
+          sed -i "s/<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->.*<!--END_ACCURACY_${{ matrix.model }}-->/<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->Accuracy: ${ACCURACY}% (updated: ${DATE})<!--END_ACCURACY_${{ matrix.model }}-->/" README.md
+          echo "Обновлена точность для ${{ matrix.model }} в README"
+        else
+          echo "Плейсхолдер для ${{ matrix.model }} не найден в README, добавляем в конец"
+          echo -e "\n## ${{ matrix.model }} Accuracy\n<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->Accuracy: ${ACCURACY}% (updated: ${DATE})<!--END_ACCURACY_${{ matrix.model }}-->\n" >> README.md
+        fi
 
-  - name: Commit and push changes (master only)
-    if: github.ref == 'refs/heads/master'
-    run: |
-      git config --global user.name "GitHub Actions"
-      git config --global user.email "actions@github.com"
-      git add README.md
-      if git diff-index --quiet HEAD --; then
-        echo "No changes to commit"
-      else
-        git commit -m "[CI] Update accuracy for ${{ matrix.model }}: $(cat accuracy_value_${{ matrix.model }}.txt)"
-        git push origin master
-      fi
+    - name: Commit and push changes (master only)
+      if: github.ref == 'refs/heads/master'
+      run: |
+        git config --global user.name "GitHub Actions"
+        git config --global user.email "actions@github.com"
+        git add README.md
+        if git diff-index --quiet HEAD --; then
+          echo "No changes to commit"
+        else
+          git commit -m "[CI] Update accuracy for ${{ matrix.model }}: $(cat accuracy_value_${{ matrix.model }}.txt)"
+          git push origin master
+        fi

From 3f9fa3940dbbf5afc0348c021200dfdca844e875 Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Fri, 27 Feb 2026 11:39:19 +0300
Subject: [PATCH 11/38] googlenet

---
 .github/workflows/ci.yml | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 1487872e..4202bf3c 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -333,6 +333,7 @@ jobs:
             parser: parser_onnx.py
             model_file: GoogLeNet.onnx
             model_path: docs/models/GoogLeNet.onnx
+            model_url: ''
             extra_args: "--onednn 10000"
           - model: densenet
             parser: parser_onnx.py
@@ -372,7 +373,8 @@ jobs:
         sudo apt-get install -y libgtk-3-0 libtbb12 libjpeg-dev libpng-dev libtiff-dev libopenjp2-7 libdnnl3
         sudo ldconfig
 
-    - name: Download model
+    - name: Download model (if URL provided)
+      if: matrix.model_url != ''
       run: |
         mkdir -p docs/models
         echo "Скачивание ${{ matrix.model_file }} из ${{ matrix.model_url }}"

From 5c4e528a5cb3dd092675be6ffbcb9b6d16639bbf Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Fri, 27 Feb 2026 12:44:28 +0300
Subject: [PATCH 12/38] reqs

---
 app/Converters/requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/app/Converters/requirements.txt b/app/Converters/requirements.txt
index b447200c..622b0e7d 100644
--- a/app/Converters/requirements.txt
+++ b/app/Converters/requirements.txt
@@ -5,7 +5,7 @@ onnx>=1.15.0
 torch==2.2.1+cpu
 torchvision==0.17.1+cpu
 ultralytics>=8.0.0
-numpy>=1.21.0
+numpy>=1.21.0,<2.0.0
 protobuf>=3.20.0
 datasets>=2.14.0
 Pillow>=10.0.0
\ No newline at end of file

From 7b969235d0a46096a909db1d5cfd9ae1eaa926ea Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Fri, 27 Feb 2026 13:21:20 +0300
Subject: [PATCH 13/38] cashe

---
 .github/workflows/ci.yml | 13 ++++++++++++-
 1 file changed, 12 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 4202bf3c..a9901ce5 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -401,9 +401,20 @@ jobs:
         echo "Сгенерированные JSON файлы:"
         ls -la docs/jsons/
 
+    - name: Cache ImageNet-Paste dataset
+      id: cache-imagenet
+      uses: actions/cache@v4
+      with:
+        path: docs/ImageNet
+        key: imagenet-paste-v1-${{ hashFiles('app/Converters/download_imagenet.py') }}
+     restore-keys: |
+       imagenet-paste-v1-
+       imagenet-paste-
+
     - name: Download ImageNet-Paste dataset
+      if: steps.cache-imagenet.outputs.cache-hit != 'true'
       run: |
-        mkdir -p docs/ImageNet/test  # Изменено с imagenet-paste/validation на ImageNet/test
+        mkdir -p docs/ImageNet/test
         cd app/Converters
         python download_imagenet.py
         cd ../..

From 392ea50d40c4f601e3d7da22e7acafa8ab1f1a9b Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Fri, 27 Feb 2026 13:29:30 +0300
Subject: [PATCH 14/38] Update ci.yml

---
 .github/workflows/ci.yml | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index a9901ce5..2894c0d3 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -407,9 +407,6 @@ jobs:
       with:
         path: docs/ImageNet
         key: imagenet-paste-v1-${{ hashFiles('app/Converters/download_imagenet.py') }}
-     restore-keys: |
-       imagenet-paste-v1-
-       imagenet-paste-
 
     - name: Download ImageNet-Paste dataset
       if: steps.cache-imagenet.outputs.cache-hit != 'true'

From 6c3b056825d435e4138b10ed96b742c53f606437 Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Fri, 27 Feb 2026 15:03:05 +0300
Subject: [PATCH 15/38] secret

---
 .github/workflows/ci.yml | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 2894c0d3..cb5a6fa1 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -410,12 +410,14 @@ jobs:
 
     - name: Download ImageNet-Paste dataset
       if: steps.cache-imagenet.outputs.cache-hit != 'true'
+      env:
+        HF_TOKEN: ${{ secrets.HF_TOKEN }}
       run: |
         mkdir -p docs/ImageNet/test
         cd app/Converters
+        # Токен автоматически используется huggingface-hub библиотекой
         python download_imagenet.py
         cd ../..
-        echo "Всего изображений: $(ls docs/ImageNet/test/*.jpg 2>/dev/null | wc -l)"
 
     - name: Prepare environment
       run: |

From 2554a4502156bdc0658a844b3edf21a571251044 Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Fri, 27 Feb 2026 16:20:55 +0300
Subject: [PATCH 16/38] usw token

---
 app/Converters/download_imagenet.py | 20 ++++++++++++++------
 1 file changed, 14 insertions(+), 6 deletions(-)

diff --git a/app/Converters/download_imagenet.py b/app/Converters/download_imagenet.py
index 059478e8..03360fa0 100644
--- a/app/Converters/download_imagenet.py
+++ b/app/Converters/download_imagenet.py
@@ -1,18 +1,24 @@
-# app/Converters/download_imagenet.py
 import os
 from datasets import load_dataset
+from huggingface_hub import login
 from PIL import Image
 
+hf_token = os.environ.get('HF_TOKEN')
+if hf_token:
+    print("Авторизация на Hugging Face Hub...")
+    login(token=hf_token)
+else:
+    print("⚠Внимание: HF_TOKEN не найден, могут быть ограничения rate limiting")
 
 base_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-output_dir = os.path.join(base_dir, 'docs', 'ImageNet', 'test')  # Изменено здесь
+output_dir = os.path.join(base_dir, 'docs', 'ImageNet', 'test')
 os.makedirs(output_dir, exist_ok=True)
 
 print("Загрузка датасета helenqu/ImageNet-Paste...")
 ds = load_dataset(
     "helenqu/ImageNet-Paste",
     split="validation",
-    trust_remote_code=True
+    token=hf_token
 )
 
 print(f"Датасет загружен. Всего записей: {len(ds)}")
@@ -20,13 +26,15 @@
 for i, item in enumerate(ds):
     try:
         image = item['image']
-
         output_path = os.path.join(output_dir, f"image_{i}.jpg")
         image.save(output_path, 'JPEG')
 
+        # Прогресс каждые 1000 изображений
+        if (i + 1) % 1000 == 0:
+            print(f"Сохранено {i + 1}/{len(ds)} изображений...")
+
     except Exception as e:
         print(f"Ошибка при сохранении изображения {i}: {e}")
         continue
 
-print(f"\n✅ Готово! Сохранено {len(ds)} изображений в {output_dir}")
-print(f"Размер датасета: {len(ds)} изображений")
\ No newline at end of file
+print(f"\nГотово! Сохранено {len(ds)} изображений в {output_dir}")
\ No newline at end of file

From aab38cc2662f0d3a240491bb7015b0a1994d5730 Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Sat, 28 Feb 2026 11:15:01 +0300
Subject: [PATCH 17/38] restore_keys

---
 .github/workflows/ci.yml | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index cb5a6fa1..5632e8ef 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -407,6 +407,10 @@ jobs:
       with:
         path: docs/ImageNet
         key: imagenet-paste-v1-${{ hashFiles('app/Converters/download_imagenet.py') }}
+        restore-keys: |
+          imagenet-paste-v1-${{ hashFiles('app/Converters/download_imagenet.py') }}-
+          imagenet-paste-v1-
+          imagenet-paste-
 
     - name: Download ImageNet-Paste dataset
       if: steps.cache-imagenet.outputs.cache-hit != 'true'

From 978481feb34e70fb0068defc3b83d0b13629f9e2 Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Mon, 2 Mar 2026 14:48:00 +0300
Subject: [PATCH 18/38] Update ci.yml

---
 .github/workflows/ci.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 5632e8ef..15f8eef9 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -326,6 +326,7 @@ jobs:
     permissions:
       contents: write
     strategy:
+      fail-fast: false
       matrix:
         model: [googlenet, densenet, resnet, yolo]
         include:

From 7748c55dd70e34054ac1e5b5b5b6524c1ca50fda Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Mon, 2 Mar 2026 15:05:03 +0300
Subject: [PATCH 19/38] restore-save

---
 .github/workflows/ci.yml | 17 +++++++++++------
 1 file changed, 11 insertions(+), 6 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 15f8eef9..20b49ef6 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -403,27 +403,32 @@ jobs:
         ls -la docs/jsons/
 
     - name: Cache ImageNet-Paste dataset
-      id: cache-imagenet
-      uses: actions/cache@v4
+      id: cache-imagenet-restore
+      uses: actions/cache/restore@v4
       with:
         path: docs/ImageNet
         key: imagenet-paste-v1-${{ hashFiles('app/Converters/download_imagenet.py') }}
         restore-keys: |
-          imagenet-paste-v1-${{ hashFiles('app/Converters/download_imagenet.py') }}-
           imagenet-paste-v1-
           imagenet-paste-
 
     - name: Download ImageNet-Paste dataset
-      if: steps.cache-imagenet.outputs.cache-hit != 'true'
+      if: steps.cache-imagenet-restore.outputs.cache-hit != 'true'
       env:
         HF_TOKEN: ${{ secrets.HF_TOKEN }}
       run: |
         mkdir -p docs/ImageNet/test
         cd app/Converters
-        # Токен автоматически используется huggingface-hub библиотекой
         python download_imagenet.py
         cd ../..
 
+    - name: Save ImageNet-Paste dataset
+      if: steps.cache-imagenet-restore.outputs.cache-hit != 'true'
+      uses: actions/cache/save@v4
+      with:
+        path: docs/ImageNet
+        key: imagenet-paste-v1-${{ hashFiles('app/Converters/download_imagenet.py') }}
+
     - name: Prepare environment
       run: |
         chmod +x "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}"
@@ -431,7 +436,7 @@ jobs:
 
     - name: Run evaluation
       run: |
-        DATASET_PATH="docs/ImageNet/test"  # Изменено с imagenet-paste/validation на ImageNet/test
+        DATASET_PATH="docs/ImageNet/test"
     
         echo "Запуск оценки для модели ${{ matrix.model }}"
         echo "Команда: ${{ steps.set_eval_binary.outputs.EVAL_BINARY }} --model ${{ matrix.model }} ${{ matrix.extra_args }}"

From c56137437b9152f7c6b495350f92480802e19b5e Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Tue, 3 Mar 2026 15:21:19 +0300
Subject: [PATCH 20/38] debug

---
 .github/workflows/ci.yml | 31 ++++++++++++++++++++++++++-----
 1 file changed, 26 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 20b49ef6..2e9986db 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -335,22 +335,22 @@ jobs:
             model_file: GoogLeNet.onnx
             model_path: docs/models/GoogLeNet.onnx
             model_url: ''
-            extra_args: "--onednn 10000"
+            extra_args: "--onednn 100"
           - model: densenet
             parser: parser_onnx.py
             model_file: densenet121_Opset16.onnx
             model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/densenet121_Opset16_timm/densenet121_Opset16.onnx?download=
-            extra_args: "--onednn 10000"
+            extra_args: "--onednn 100"
           - model: resnet
             parser: parser_onnx.py
             model_file: resnest101e_Opset16.onnx
             model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/resnest101e_Opset16_timm/resnest101e_Opset16.onnx?download=
-            extra_args: "--onednn 10000"
+            extra_args: "--onednn 100"
           - model: yolo
             parser: parser_onnx.py
             model_file: yolo11x-cls.pt
             model_url: https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo11x-cls.pt
-            extra_args: "--onednn 10000"
+            extra_args: "--onednn 100"
 
     steps:
     - uses: actions/checkout@v4
@@ -401,6 +401,17 @@ jobs:
         cd ../..
         echo "Сгенерированные JSON файлы:"
         ls -la docs/jsons/
+        
+    - name: Validate densenet model
+      run: |
+        echo "Проверка модели densenet:"
+        ls -la docs/models/densenet121_Opset16.onnx
+        file docs/models/densenet121_Opset16.onnx
+        echo "Размер: $(wc -c < docs/models/densenet121_Opset16.onnx) байт"
+    
+        echo "Проверка JSON:"
+        ls -la docs/jsons/densenet121_Opset16_onnx_model.json
+        head -20 docs/jsons/densenet121_Opset16_onnx_model.json
 
     - name: Cache ImageNet-Paste dataset
       id: cache-imagenet-restore
@@ -433,7 +444,17 @@ jobs:
       run: |
         chmod +x "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}"
         echo "LD_LIBRARY_PATH=$PWD/build/bin/all_libs:/usr/lib/x86_64-linux-gnu" >> $GITHUB_ENV
-
+    - name: Debug dataset before evaluation
+      run: |
+        echo "Проверка датасета:"
+        echo "Путь: docs/ImageNet/test/"
+        ls -la docs/ImageNet/test/ | head -20
+        echo "Количество .jpg файлов: $(find docs/ImageNet/test/ -name "*.jpg" | wc -l)"
+        echo "Права доступа:"
+        ls -ld docs/ImageNet/test/
+        echo "Первый файл (если есть):"
+        find docs/ImageNet/test/ -name "*.jpg" | head -1 | xargs file || echo "Нет файлов"
+  
     - name: Run evaluation
       run: |
         DATASET_PATH="docs/ImageNet/test"

From 4ff9e1db6e983b23689a381879b138b67cd0c8cd Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Tue, 3 Mar 2026 15:55:02 +0300
Subject: [PATCH 21/38] check del

---
 .github/workflows/ci.yml | 12 +-----------
 1 file changed, 1 insertion(+), 11 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 2e9986db..f9677f62 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -401,17 +401,6 @@ jobs:
         cd ../..
         echo "Сгенерированные JSON файлы:"
         ls -la docs/jsons/
-        
-    - name: Validate densenet model
-      run: |
-        echo "Проверка модели densenet:"
-        ls -la docs/models/densenet121_Opset16.onnx
-        file docs/models/densenet121_Opset16.onnx
-        echo "Размер: $(wc -c < docs/models/densenet121_Opset16.onnx) байт"
-    
-        echo "Проверка JSON:"
-        ls -la docs/jsons/densenet121_Opset16_onnx_model.json
-        head -20 docs/jsons/densenet121_Opset16_onnx_model.json
 
     - name: Cache ImageNet-Paste dataset
       id: cache-imagenet-restore
@@ -444,6 +433,7 @@ jobs:
       run: |
         chmod +x "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}"
         echo "LD_LIBRARY_PATH=$PWD/build/bin/all_libs:/usr/lib/x86_64-linux-gnu" >> $GITHUB_ENV
+
     - name: Debug dataset before evaluation
       run: |
         echo "Проверка датасета:"

From 9dc92bb0559b61e4ec952e506305049bb9e835fc Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Tue, 3 Mar 2026 15:55:32 +0300
Subject: [PATCH 22/38] download to folders

---
 app/Converters/download_imagenet.py | 84 ++++++++++++++++++++++++++---
 1 file changed, 77 insertions(+), 7 deletions(-)

diff --git a/app/Converters/download_imagenet.py b/app/Converters/download_imagenet.py
index 03360fa0..c6d9d1a8 100644
--- a/app/Converters/download_imagenet.py
+++ b/app/Converters/download_imagenet.py
@@ -2,13 +2,14 @@
 from datasets import load_dataset
 from huggingface_hub import login
 from PIL import Image
+from collections import defaultdict
 
 hf_token = os.environ.get('HF_TOKEN')
 if hf_token:
     print("Авторизация на Hugging Face Hub...")
     login(token=hf_token)
 else:
-    print("⚠Внимание: HF_TOKEN не найден, могут быть ограничения rate limiting")
+    print("Внимание: HF_TOKEN не найден, могут быть ограничения rate limiting")
 
 base_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 output_dir = os.path.join(base_dir, 'docs', 'ImageNet', 'test')
@@ -23,18 +24,87 @@
 
 print(f"Датасет загружен. Всего записей: {len(ds)}")
 
+print(f"Ключи первой записи: {ds[0].keys()}")
+if 'label' in ds[0]:
+    print(f"Пример метки: {ds[0]['label']}")
+    print(f"Тип метки: {type(ds[0]['label'])}")
+
+print("\nСоздание папок для классов 00000-00999 в test/...")
+for i in range(1000):
+    class_folder = os.path.join(output_dir, f"{i:05d}")
+    os.makedirs(class_folder, exist_ok=True)
+print("Папки созданы!")
+
+counters = defaultdict(int)
+
+total_images = len(ds)
+images_per_class = 50
+max_images = 1000 * images_per_class
+
+print(f"\nНачинаем сохранение {min(total_images, max_images)} изображений...")
+print(f"По {images_per_class} изображений в каждой из 1000 папок")
+print(f"Путь: {output_dir}/00000/ ... /00999/")
+
+saved_count = 0
+skipped_count = 0
+
 for i, item in enumerate(ds):
+    if saved_count >= max_images:
+        print(f"\nДостигнут лимит в {max_images} изображений")
+        break
+
     try:
         image = item['image']
-        output_path = os.path.join(output_dir, f"image_{i}.jpg")
-        image.save(output_path, 'JPEG')
+        if 'label' in item:
+            class_id = item['label']
+        elif 'labels' in item:
+            class_id = item['labels']
+        else:
+            skipped_count += 1
+            if skipped_count % 100 == 0:
+                print(f"Пропущено {skipped_count} изображений: нет метки класса")
+            continue
 
-        # Прогресс каждые 1000 изображений
-        if (i + 1) % 1000 == 0:
-            print(f"Сохранено {i + 1}/{len(ds)} изображений...")
+        if not isinstance(class_id, (int, float)) or class_id < 0 or class_id >= 1000:
+            skipped_count += 1
+            if skipped_count % 100 == 0:
+                print(f"Пропущено {skipped_count} изображений: некорректный class_id {class_id}")
+            continue
+
+        class_id_int = int(class_id)
+
+        if counters[class_id_int] >= images_per_class:
+            continue
+
+        class_folder = os.path.join(output_dir, f"{class_id_int:05d}")
+        filename = f"image_{counters[class_id_int]}.jpg"
+        output_path = os.path.join(class_folder, filename)
+
+        image.save(output_path, 'JPEG')
+        counters[class_id_int] += 1
+        saved_count += 1
 
     except Exception as e:
         print(f"Ошибка при сохранении изображения {i}: {e}")
         continue
 
-print(f"\nГотово! Сохранено {len(ds)} изображений в {output_dir}")
\ No newline at end of file
+print(f"\n{'=' * 50}")
+print(f"ГОТОВО!")
+print(f"{'=' * 50}")
+print(f"Всего сохранено: {saved_count} изображений")
+print(f"Пропущено: {skipped_count} изображений")
+print(f"Распределение по первым 10 классам:")
+for class_id in range(10):
+    print(f"  Класс {class_id:05d}: {counters[class_id]} изображений")
+
+classes_with_50 = sum(1 for c in range(1000) if counters[c] == 50)
+print(f"\nКлассов с ровно 50 изображениями: {classes_with_50}/1000")
+
+if classes_with_50 < 1000:
+    print("\nКлассы с недостаточным количеством:")
+    for class_id in range(1000):
+        if counters[class_id] < 50 and counters[class_id] > 0:
+            print(f"  Класс {class_id:05d}: только {counters[class_id]} изображений")
+
+print(f"\nПуть к данным: {output_dir}")
+print(f"Пример: {output_dir}/00042/image_0.jpg")
\ No newline at end of file

From df7b5a75bc3d163211135f79d0b3164914752830 Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Wed, 4 Mar 2026 11:18:42 +0300
Subject: [PATCH 23/38] cashe json and 10 for resnet

---
 .github/workflows/ci.yml | 26 ++++++++++++--------------
 1 file changed, 12 insertions(+), 14 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index f9677f62..875eae1f 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -345,7 +345,7 @@ jobs:
             parser: parser_onnx.py
             model_file: resnest101e_Opset16.onnx
             model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/resnest101e_Opset16_timm/resnest101e_Opset16.onnx?download=
-            extra_args: "--onednn 100"
+            extra_args: "--onednn 10"
           - model: yolo
             parser: parser_onnx.py
             model_file: yolo11x-cls.pt
@@ -393,14 +393,23 @@ jobs:
         pip install -r requirements.txt
         cd ../..
 
+    - name: Cache model JSON files
+      id: cache-model-json
+      uses: actions/cache@v4
+      with:
+        path: docs/jsons
+        key: model-json-${{ matrix.model }}-${{ hashFiles('app/Converters/parser_onnx.py', 'app/Converters/requirements.txt') }}
+        restore-keys: |
+          model-json-${{ matrix.model }}-
+          model-json-
+
     - name: Generate model JSON
+      if: steps.cache-model-json.outputs.cache-hit != 'true'
       run: |
         mkdir -p docs/jsons
         cd app/Converters
         python ${{ matrix.parser }} ${{ matrix.model }}
         cd ../..
-        echo "Сгенерированные JSON файлы:"
-        ls -la docs/jsons/
 
     - name: Cache ImageNet-Paste dataset
       id: cache-imagenet-restore
@@ -433,17 +442,6 @@ jobs:
       run: |
         chmod +x "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}"
         echo "LD_LIBRARY_PATH=$PWD/build/bin/all_libs:/usr/lib/x86_64-linux-gnu" >> $GITHUB_ENV
-
-    - name: Debug dataset before evaluation
-      run: |
-        echo "Проверка датасета:"
-        echo "Путь: docs/ImageNet/test/"
-        ls -la docs/ImageNet/test/ | head -20
-        echo "Количество .jpg файлов: $(find docs/ImageNet/test/ -name "*.jpg" | wc -l)"
-        echo "Права доступа:"
-        ls -ld docs/ImageNet/test/
-        echo "Первый файл (если есть):"
-        find docs/ImageNet/test/ -name "*.jpg" | head -1 | xargs file || echo "Нет файлов"
   
     - name: Run evaluation
       run: |

From 7ff4e1bfa4fea213cdfc011a815b17e502e27fd8 Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Wed, 4 Mar 2026 17:08:17 +0300
Subject: [PATCH 24/38] debug

---
 .github/workflows/ci.yml | 124 +++++++++++++++++++++++++++++++++++----
 1 file changed, 113 insertions(+), 11 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 875eae1f..cb586102 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -446,22 +446,124 @@ jobs:
     - name: Run evaluation
       run: |
         DATASET_PATH="docs/ImageNet/test"
+        MODEL="${{ matrix.model }}"
+        EXTRA_ARGS="${{ matrix.extra_args }}"
     
-        echo "Запуск оценки для модели ${{ matrix.model }}"
-        echo "Команда: ${{ steps.set_eval_binary.outputs.EVAL_BINARY }} --model ${{ matrix.model }} ${{ matrix.extra_args }}"
+        echo "==================================="
+        echo "🚀 Запуск оценки для модели $MODEL"
+        echo "📋 Команда: ${{ steps.set_eval_binary.outputs.EVAL_BINARY }} --model $MODEL $EXTRA_ARGS"
+        echo "==================================="
     
-        "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}" \
-        --model ${{ matrix.model }} \
-        ${{ matrix.extra_args }} > accuracy_${{ matrix.model }}.txt 2>&1
+        echo "📊 Системная информация до запуска:"
+        echo "--- Память ---"
+        free -h
+        echo "--- CPU ---"
+        top -bn1 | head -5
+        echo "--- Диск ---"
+        df -h docs/ImageNet/test/
+    
+        # Запускаем процесс с мониторингом
+        TIMESTAMP=$(date +%s)
+        MONITOR_LOG="monitor_$MODEL.log"
+    
+        # Функция мониторинга
+        monitor_process() {
+          local pid=$1
+          local log_file=$2
       
-        if [ $? -ne 0 ]; then
-          echo "Ошибка при оценке модели ${{ matrix.model }}"
-          cat accuracy_${{ matrix.model }}.txt
-          exit 1
+          echo "📊 Мониторинг процесса $pid..."
+      
+          while kill -0 $pid 2>/dev/null; do
+            # Время
+            NOW=$(date '+%H:%M:%S')
+        
+            # Память процесса
+            MEM=$(ps -o rss= -p $pid 2>/dev/null | awk '{print $1/1024 " MB"}' || echo "N/A")
+        
+            # CPU процесса
+            CPU=$(ps -o pcpu= -p $pid 2>/dev/null || echo "N/A")
+        
+            # Общая память системы
+            TOTAL_MEM=$(free -m | awk 'NR==2{print $3 " MB / " $2 " MB"}')
+        
+            echo "[$NOW] PID: $pid | MEM: $MEM | CPU: $CPU% | System MEM: $TOTAL_MEM" >> $log_file
+        
+            sleep 2
+          done
+      
+         echo "📊 Процесс $pid завершен" >> $log_file
+         }
+    
+        # Запускаем основную программу в фоне
+        echo "▶️ Запуск ACC в фоновом режиме..."
+        "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}" \
+        --model $MODEL \
+        $EXTRA_ARGS > accuracy_$MODEL.txt 2>&1 &
+        ACC_PID=$!
+    
+        echo "📊 PID процесса: $ACC_PID"
+    
+        # Запускаем мониторинг в фоне
+        monitor_process $ACC_PID $MONITOR_LOG &
+        MONITOR_PID=$!
+    
+        # Ждем завершения ACC
+        wait $ACC_PID
+        EXIT_CODE=$?
+    
+        # Убиваем мониторинг
+        kill $MONITOR_PID 2>/dev/null || true
+    
+        echo "==================================="
+        echo "📊 Результаты мониторинга:"
+        if [ -f "$MONITOR_LOG" ]; then
+          cat "$MONITOR_LOG"
+        else
+         echo "Лог мониторинга не создан"
         fi
+    
+        echo "==================================="
+        echo "📊 Системная информация после запуска:"
+        free -h
+    
+        echo "==================================="
+        echo "📊 Код завершения: $EXIT_CODE"
+    
+        if [ $EXIT_CODE -eq 143 ]; then
+          echo "❌ Ошибка 143 (SIGTERM) - процесс убит системой"
+          echo "Возможные причины:"
+          echo "  - Нехватка памяти (OOM Killer)"
+          echo "  - Превышение лимитов CPU"
+          echo "  - Timeout от GitHub Actions"
+      
+          # Проверка OOM Killer
+          if sudo dmesg | tail -20 | grep -i "killed process" | grep -q "$ACC_PID"; then
+            echo "✅ Подтверждено: процесс убит OOM Killer"
+            sudo dmesg | tail -20 | grep -i "killed process" | tail -5
+          else
+            echo "❌ Не найдено подтверждение OOM Killer в логах"
+            sudo dmesg | tail -20
+          fi
       
-        echo "Результат оценки:"
-        cat accuracy_${{ matrix.model }}.txt
+        elif [ $EXIT_CODE -ne 0 ]; then
+          echo "❌ Ошибка при оценке модели $MODEL (код: $EXIT_CODE)"
+        else
+          echo "✅ Оценка успешно завершена"
+        fi
+    
+        # Всегда показываем лог ACC
+        echo "==================================="
+        echo "📋 Лог ACC:"
+        if [ -f "accuracy_$MODEL.txt" ]; then
+          cat "accuracy_$MODEL.txt"
+        else
+         echo "Файл лога не создан"
+        fi
+    
+        # Выход с ошибкой если нужно
+        if [ $EXIT_CODE -ne 0 ]; then
+          exit $EXIT_CODE
+        fi
 
     - name: Extract accuracy value
       run: |

From 5c9312735d366afcdadf7b1576a061f26c48b938 Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Wed, 4 Mar 2026 17:15:08 +0300
Subject: [PATCH 25/38] Update ci.yml

---
 .github/workflows/ci.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index cb586102..9550ad3d 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -335,7 +335,7 @@ jobs:
             model_file: GoogLeNet.onnx
             model_path: docs/models/GoogLeNet.onnx
             model_url: ''
-            extra_args: "--onednn 100"
+            extra_args: "--onednn 1000"
           - model: densenet
             parser: parser_onnx.py
             model_file: densenet121_Opset16.onnx
@@ -345,7 +345,7 @@ jobs:
             parser: parser_onnx.py
             model_file: resnest101e_Opset16.onnx
             model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/resnest101e_Opset16_timm/resnest101e_Opset16.onnx?download=
-            extra_args: "--onednn 10"
+            extra_args: "--onednn 100"
           - model: yolo
             parser: parser_onnx.py
             model_file: yolo11x-cls.pt

From b0924af44122d8ef8b7270e3db7834acc7f75821 Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Wed, 4 Mar 2026 18:14:35 +0300
Subject: [PATCH 26/38] Update ci.yml

---
 .github/workflows/ci.yml | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 9550ad3d..aabf2ae9 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -442,6 +442,14 @@ jobs:
       run: |
         chmod +x "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}"
         echo "LD_LIBRARY_PATH=$PWD/build/bin/all_libs:/usr/lib/x86_64-linux-gnu" >> $GITHUB_ENV
+        
+    - name: Increase system limits
+      run: |
+        sudo prlimit --pid $$ --as=unlimited
+        ulimit -s unlimited
+        ulimit -c unlimited
+        echo "Новые лимиты:"
+        ulimit -a
   
     - name: Run evaluation
       run: |

From 73f30461e31963701c2bf004ff9c03761af8fb21 Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Fri, 6 Mar 2026 17:49:35 +0300
Subject: [PATCH 27/38] Update ci.yml

---
 .github/workflows/ci.yml | 56 ++++++++++++----------------------------
 1 file changed, 17 insertions(+), 39 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index aabf2ae9..6f5b0b4c 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -457,12 +457,10 @@ jobs:
         MODEL="${{ matrix.model }}"
         EXTRA_ARGS="${{ matrix.extra_args }}"
     
-        echo "==================================="
-        echo "🚀 Запуск оценки для модели $MODEL"
-        echo "📋 Команда: ${{ steps.set_eval_binary.outputs.EVAL_BINARY }} --model $MODEL $EXTRA_ARGS"
-        echo "==================================="
+        echo "Запуск оценки для модели $MODEL"
+        echo "Команда: ${{ steps.set_eval_binary.outputs.EVAL_BINARY }} --model $MODEL $EXTRA_ARGS"
     
-        echo "📊 Системная информация до запуска:"
+        echo "Системная информация до запуска:"
         echo "--- Память ---"
         free -h
         echo "--- CPU ---"
@@ -470,28 +468,22 @@ jobs:
         echo "--- Диск ---"
         df -h docs/ImageNet/test/
     
-        # Запускаем процесс с мониторингом
         TIMESTAMP=$(date +%s)
         MONITOR_LOG="monitor_$MODEL.log"
     
-        # Функция мониторинга
         monitor_process() {
           local pid=$1
           local log_file=$2
       
-          echo "📊 Мониторинг процесса $pid..."
+          echo "Мониторинг процесса $pid..."
       
           while kill -0 $pid 2>/dev/null; do
-            # Время
             NOW=$(date '+%H:%M:%S')
         
-            # Память процесса
             MEM=$(ps -o rss= -p $pid 2>/dev/null | awk '{print $1/1024 " MB"}' || echo "N/A")
         
-            # CPU процесса
             CPU=$(ps -o pcpu= -p $pid 2>/dev/null || echo "N/A")
         
-            # Общая память системы
             TOTAL_MEM=$(free -m | awk 'NR==2{print $3 " MB / " $2 " MB"}')
         
             echo "[$NOW] PID: $pid | MEM: $MEM | CPU: $CPU% | System MEM: $TOTAL_MEM" >> $log_file
@@ -499,69 +491,55 @@ jobs:
             sleep 2
           done
       
-         echo "📊 Процесс $pid завершен" >> $log_file
+         echo "Процесс $pid завершен" >> $log_file
          }
     
-        # Запускаем основную программу в фоне
-        echo "▶️ Запуск ACC в фоновом режиме..."
+        echo "Запуск ACC в фоновом режиме..."
         "${{ steps.set_eval_binary.outputs.EVAL_BINARY }}" \
         --model $MODEL \
         $EXTRA_ARGS > accuracy_$MODEL.txt 2>&1 &
         ACC_PID=$!
     
-        echo "📊 PID процесса: $ACC_PID"
+        echo "PID процесса: $ACC_PID"
     
-        # Запускаем мониторинг в фоне
         monitor_process $ACC_PID $MONITOR_LOG &
         MONITOR_PID=$!
     
-        # Ждем завершения ACC
         wait $ACC_PID
         EXIT_CODE=$?
     
-        # Убиваем мониторинг
         kill $MONITOR_PID 2>/dev/null || true
-    
-        echo "==================================="
-        echo "📊 Результаты мониторинга:"
+  
+        echo "Результаты мониторинга:"
         if [ -f "$MONITOR_LOG" ]; then
           cat "$MONITOR_LOG"
         else
          echo "Лог мониторинга не создан"
         fi
     
-        echo "==================================="
-        echo "📊 Системная информация после запуска:"
+        echo "Системная информация после запуска:"
         free -h
     
-        echo "==================================="
-        echo "📊 Код завершения: $EXIT_CODE"
+        echo "Код завершения: $EXIT_CODE"
     
         if [ $EXIT_CODE -eq 143 ]; then
-          echo "❌ Ошибка 143 (SIGTERM) - процесс убит системой"
-          echo "Возможные причины:"
-          echo "  - Нехватка памяти (OOM Killer)"
-          echo "  - Превышение лимитов CPU"
-          echo "  - Timeout от GitHub Actions"
+          echo "Ошибка 143 (SIGTERM) - процесс убит системой"
       
-          # Проверка OOM Killer
           if sudo dmesg | tail -20 | grep -i "killed process" | grep -q "$ACC_PID"; then
-            echo "✅ Подтверждено: процесс убит OOM Killer"
+            echo "Подтверждено: процесс убит OOM Killer"
             sudo dmesg | tail -20 | grep -i "killed process" | tail -5
           else
-            echo "❌ Не найдено подтверждение OOM Killer в логах"
+            echo "Не найдено подтверждение OOM Killer в логах"
             sudo dmesg | tail -20
           fi
       
         elif [ $EXIT_CODE -ne 0 ]; then
-          echo "❌ Ошибка при оценке модели $MODEL (код: $EXIT_CODE)"
+          echo "Ошибка при оценке модели $MODEL (код: $EXIT_CODE)"
         else
-          echo "✅ Оценка успешно завершена"
+          echo "Оценка успешно завершена"
         fi
     
-        # Всегда показываем лог ACC
-        echo "==================================="
-        echo "📋 Лог ACC:"
+        echo "Лог ACC:"
         if [ -f "accuracy_$MODEL.txt" ]; then
           cat "accuracy_$MODEL.txt"
         else

From 4e6a9bc233f280812015d7cb8e9909945a86a6bf Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Sat, 7 Mar 2026 11:32:52 +0300
Subject: [PATCH 28/38] static

---
 app/Graph/acc_check.cpp | 59 +++++++++++++++++++----------------------
 1 file changed, 28 insertions(+), 31 deletions(-)

diff --git a/app/Graph/acc_check.cpp b/app/Graph/acc_check.cpp
index 9b4c0ee5..1517b56e 100644
--- a/app/Graph/acc_check.cpp
+++ b/app/Graph/acc_check.cpp
@@ -13,7 +13,7 @@ using namespace it_lab_ai;
 int main(int argc, char* argv[]) {
   std::string model_name = "alexnet_mnist";
   RuntimeOptions options;
-  size_t numPhoto = 1000;
+  size_t num_photo = 1000;
 
   for (int i = 1; i < argc; ++i) {
     if (std::string(argv[i]) == "--model" && i + 1 < argc) {
@@ -51,15 +51,15 @@ int main(int argc, char* argv[]) {
       options.threads = std::stoi(argv[++i]);
     } else {
       try {
-        numPhoto = std::stoi(argv[i]);
+        num_photo = std::stoi(argv[i]);
 
-        if (numPhoto < 1 || numPhoto > 50000) {
-          std::cerr << "Warning: numPhoto should be between 1 and 10000 "
-                    << "Using value: " << numPhoto << std::endl;
+        if (num_photo < 1 || num_photo > 50000) {
+          std::cerr << "Warning: num_photo should be between 1 and 10000 "
+                    << "Using value: " << num_photo << '\n';
         }
       } catch (const std::exception& e) {
         std::cerr << "Error: Invalid numeric argument: " << argv[i]
-                  << ". Using default value: 1000" << e.what() << std::endl;
+                  << ". Using default value: 1000" << e.what() << '\n';
       }
     }
   }
@@ -83,7 +83,6 @@ int main(int argc, char* argv[]) {
     size_t sum = std::accumulate(counts.begin(), counts.end(), size_t{0});
     int count_pic = static_cast<int>(sum) + 10;
     std::vector<float> res(count_pic * 28 * 28);
-    Tensor input;
     Shape sh1({1, 5, 5, 3});
     std::vector<float> vec;
     vec.reserve(75);
@@ -111,14 +110,14 @@ int main(int argc, char* argv[]) {
           for (int j = 0; j < 28; ++j) {
             size_t a = ind;
             for (size_t n = 0; n < name; n++) a += counts[n] + 1;
-            res[(a) * 28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
+            res[(a)*28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
           }
         }
       }
     }
     Shape sh({static_cast<size_t>(count_pic), 1, 28, 28});
     Tensor t = make_tensor<float>(res, sh);
-    input = t;
+    Tensor input = t;
     Graph graph;
     build_graph_linear(graph, input, output, options, false);
     graph.inference(options);
@@ -147,14 +146,13 @@ int main(int argc, char* argv[]) {
               << "%" << '\n';
     return 0;
   }
-  std::vector<size_t> counts;
+
+  std::vector<size_t> counts(1000, 0);
   std::vector<std::string> image_paths;
   std::vector<int> true_labels;
   std::vector<float> all_image_data;
   size_t total_images = 0;
 
-  counts.resize(1000, 0);
-
   for (int class_id = 0; class_id < 1000; ++class_id) {
     std::ostringstream folder_oss;
     folder_oss << std::setw(5) << std::setfill('0') << class_id;
@@ -171,17 +169,17 @@ int main(int argc, char* argv[]) {
     }
   }
 
-  size_t images_per_class_base = numPhoto / 1000;
-  size_t remaining = numPhoto % 1000;
+  size_t images_per_class_base = num_photo / 1000;
+  size_t remaining = num_photo % 1000;
 
   int channels = input_shape[1];
   int height = input_shape[2];
   int width = input_shape[3];
   size_t image_size = channels * height * width;
 
-  all_image_data.reserve(numPhoto * image_size);
-  image_paths.reserve(numPhoto);
-  true_labels.reserve(numPhoto);
+  all_image_data.reserve(num_photo * image_size);
+  image_paths.reserve(num_photo);
+  true_labels.reserve(num_photo);
 
   total_images = 0;
 
@@ -230,25 +228,24 @@ int main(int argc, char* argv[]) {
 
     if (taken < need_from_class) {
       std::cout << "Warning: Class " << class_id << " has only " << taken
-                << " images (needed " << need_from_class << ")" << std::endl;
+                << " images (needed " << need_from_class << ")" << '\n';
     }
   }
 
-  if (total_images != numPhoto) {
-    std::cout << "Warning: Requested " << numPhoto << " images but loaded "
-              << total_images << " due to insufficient data" << std::endl;
-    numPhoto = total_images;
+  if (total_images != num_photo) {
+    std::cout << "Warning: Requested " << num_photo << " images but loaded "
+              << total_images << " due to insufficient data" << '\n';
+    num_photo = total_images;
   }
 
   it_lab_ai::Shape input_shape_imagenet(
-      {static_cast<size_t>(numPhoto), static_cast<size_t>(channels),
-       static_cast<size_t>(height), static_cast<size_t>(width)});
+      {num_photo, static_cast<size_t>(channels), static_cast<size_t>(height),
+       static_cast<size_t>(width)});
   it_lab_ai::Tensor input =
       it_lab_ai::make_tensor(all_image_data, input_shape_imagenet);
 
   size_t output_classes = 1000;
-  it_lab_ai::Shape output_shape(
-      {static_cast<size_t>(numPhoto), output_classes});
+  it_lab_ai::Shape output_shape({num_photo, output_classes});
   it_lab_ai::Tensor output =
       it_lab_ai::Tensor(output_shape, it_lab_ai::Type::kFloat);
 
@@ -260,7 +257,7 @@ int main(int argc, char* argv[]) {
   std::vector<std::vector<float>> processed_outputs;
   const std::vector<float>& raw_output = *output.as<float>();
 
-  for (size_t i = 0; i < static_cast<size_t>(numPhoto); ++i) {
+  for (size_t i = 0; i < num_photo; ++i) {
     std::vector<float> single_output(
         raw_output.begin() + i * output_classes,
         raw_output.begin() + (i + 1) * output_classes);
@@ -300,14 +297,14 @@ int main(int argc, char* argv[]) {
   }
 
   double final_accuracy_top1 =
-      (static_cast<double>(correct_predictions_top1) / numPhoto) * 100;
+      (static_cast<double>(correct_predictions_top1) / num_photo) * 100;
   double final_accuracy_top5 =
-      (static_cast<double>(correct_predictions_top5) / numPhoto) * 100;
+      (static_cast<double>(correct_predictions_top5) / num_photo) * 100;
 
   std::cout << "\nFinal Results:" << '\n';
   std::cout << "Model: " << model_name << '\n';
   std::cout << "Dataset: " << dataset_path << '\n';
-  std::cout << "Total images: " << numPhoto << '\n';
+  std::cout << "Total images: " << num_photo << '\n';
   std::cout << "Correct predictions (Top-1): " << correct_predictions_top1
             << '\n';
   std::cout << "Correct predictions (Top-5): " << correct_predictions_top5
@@ -318,4 +315,4 @@ int main(int argc, char* argv[]) {
             << final_accuracy_top5 << "%" << '\n';
 
   return 0;
-}
+}
\ No newline at end of file

From 4eb3771e0dd672af1247a861785834a1f4b63238 Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Sat, 7 Mar 2026 11:34:01 +0300
Subject: [PATCH 29/38] cl

---
 app/Graph/acc_check.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/app/Graph/acc_check.cpp b/app/Graph/acc_check.cpp
index 1517b56e..ddf0a893 100644
--- a/app/Graph/acc_check.cpp
+++ b/app/Graph/acc_check.cpp
@@ -110,7 +110,7 @@ int main(int argc, char* argv[]) {
           for (int j = 0; j < 28; ++j) {
             size_t a = ind;
             for (size_t n = 0; n < name; n++) a += counts[n] + 1;
-            res[(a)*28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
+            res[(a) * 28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
           }
         }
       }

From 040794f9d3667da2134c3ed5e349ef4cb56059d0 Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Wed, 11 Mar 2026 11:47:58 +0300
Subject: [PATCH 30/38] batch 32 for accuracy

---
 app/Graph/acc_check.cpp | 278 ++++++++++++++++++++++++++++++++--------
 app/Graph/build.cpp     |  13 +-
 app/Graph/build.hpp     |   2 +-
 include/graph/graph.hpp |  13 ++
 4 files changed, 245 insertions(+), 61 deletions(-)

diff --git a/app/Graph/acc_check.cpp b/app/Graph/acc_check.cpp
index ddf0a893..40cba480 100644
--- a/app/Graph/acc_check.cpp
+++ b/app/Graph/acc_check.cpp
@@ -1,4 +1,14 @@
-#include <algorithm>
+
+#ifndef WIN32_LEAN_AND_MEAN
+#define WIN32_LEAN_AND_MEAN
+#endif
+#include <windows.h>
+#include <psapi.h>
+#pragma comment(lib, "psapi.lib")
+#include <crtdbg.h>
+#include <algorithm>
+#include <chrono>
+#include <cmath>
 #include <filesystem>
 #include <iomanip>
 #include <numeric>
@@ -7,17 +17,82 @@
 
 #include "build.hpp"
 
+class MemoryLogger {
+ private:
+  std::chrono::steady_clock::time_point start_time;
+  size_t peak_memory = 0;
+  size_t initial_memory = 0;
+
+  size_t getProcessMemory() {
+    HANDLE hProcess = GetCurrentProcess();
+    PROCESS_MEMORY_COUNTERS pmc;
+    pmc.cb = sizeof(PROCESS_MEMORY_COUNTERS);
+
+    if (GetProcessMemoryInfo(hProcess, &pmc, sizeof(pmc))) {
+      return pmc.WorkingSetSize / (1024 * 1024);
+    }
+    return 0;
+  }
+
+ public:
+  MemoryLogger() {
+    start_time = std::chrono::steady_clock::now();
+    initial_memory = getProcessMemory();
+    log("START");
+  }
+
+  void log(const char* stage) {
+    auto now = std::chrono::steady_clock::now();
+    auto elapsed =
+        std::chrono::duration_cast<std::chrono::seconds>(now - start_time)
+            .count();
+
+    size_t current = getProcessMemory();
+    if (current > peak_memory) peak_memory = current;
+
+    std::cout << "[" << std::setw(4) << elapsed << "s] " << std::setw(30)
+              << stage << " | "
+              << "PROCESS MEM: " << std::setw(6) << current << " MB"
+              << " (PEAK: " << std::setw(6) << peak_memory << " MB)"
+              << " (DELTA: " << std::setw(4) << (current - initial_memory)
+              << " MB)\n";
+  }
+
+  ~MemoryLogger() {
+    log("END");
+    std::cout << "====================================\n";
+    std::cout << "PEAK PROCESS MEMORY: " << peak_memory << " MB\n";
+    std::cout << "INITIAL PROCESS MEMORY: " << initial_memory << " MB\n";
+    std::cout << "FINAL PROCESS MEMORY: " << getProcessMemory() << " MB\n";
+    if (getProcessMemory() > initial_memory + 10) {
+      std::cout << "WARNING: Process memory growth! (+"
+                << (getProcessMemory() - initial_memory) << " MB)\n";
+    } else {
+      std::cout << "OK: No significant process memory growth\n";
+    }
+  }
+};
+
+MemoryLogger g_memLogger;
+
+#define LOG_MEM(stage) g_memLogger.log(stage)
+
 namespace fs = std::filesystem;
 using namespace it_lab_ai;
 
 int main(int argc, char* argv[]) {
+  LOG_MEM("Program start");
+
   std::string model_name = "alexnet_mnist";
   RuntimeOptions options;
   size_t num_photo = 1000;
+  size_t batch_size = 32;
 
   for (int i = 1; i < argc; ++i) {
     if (std::string(argv[i]) == "--model" && i + 1 < argc) {
       model_name = argv[++i];
+    } else if (std::string(argv[i]) == "--batch" && i + 1 < argc) {
+      batch_size = std::stoi(argv[++i]);
     } else if (std::string(argv[i]) == "--onednn") {
       options.backend = Backend::kOneDnn;
       if (options.par_backend != ParBackend::kSeq) {
@@ -64,6 +139,8 @@ int main(int argc, char* argv[]) {
     }
   }
 
+  LOG_MEM("After args parsing");
+
   std::string dataset_path;
   if (model_name == "alexnet_mnist") {
     dataset_path = MNIST_PATH;
@@ -75,8 +152,10 @@ int main(int argc, char* argv[]) {
   std::vector<int> input_shape = get_input_shape_from_json(json_path);
 
   std::cout << '\n';
-
+  int batch_count = 0;
   if (model_name == "alexnet_mnist") {
+    LOG_MEM("MNIST start");
+
     std::vector<size_t> counts = {979, 1134, 1031, 1009, 981,
                                   891, 957,  1027, 973,  1008};
     int stat = 0;
@@ -144,15 +223,20 @@ int main(int argc, char* argv[]) {
         (static_cast<double>(stat) / static_cast<double>(sum + 10)) * 100;
     std::cout << "Stat: " << std::fixed << std::setprecision(2) << percentage
               << "%" << '\n';
+
+    LOG_MEM("MNIST end");
     return 0;
   }
 
+  LOG_MEM("ImageNet start");
+
   std::vector<size_t> counts(1000, 0);
   std::vector<std::string> image_paths;
   std::vector<int> true_labels;
   std::vector<float> all_image_data;
   size_t total_images = 0;
 
+  LOG_MEM("Counting classes");
   for (int class_id = 0; class_id < 1000; ++class_id) {
     std::ostringstream folder_oss;
     folder_oss << std::setw(5) << std::setfill('0') << class_id;
@@ -176,13 +260,16 @@ int main(int argc, char* argv[]) {
   int height = input_shape[2];
   int width = input_shape[3];
   size_t image_size = channels * height * width;
+  size_t output_classes = 1000;
 
+  LOG_MEM("Reserving memory");
   all_image_data.reserve(num_photo * image_size);
   image_paths.reserve(num_photo);
   true_labels.reserve(num_photo);
 
   total_images = 0;
 
+  LOG_MEM("Loading images start");
   for (int class_id = 0; class_id < 1000; ++class_id) {
     size_t need_from_class = images_per_class_base;
     if (remaining > 0) {
@@ -230,72 +317,148 @@ int main(int argc, char* argv[]) {
       std::cout << "Warning: Class " << class_id << " has only " << taken
                 << " images (needed " << need_from_class << ")" << '\n';
     }
+
+    if (class_id % 100 == 0 && class_id > 0) {
+      char buf[50];
+      sprintf(buf, "Class %d", class_id);
+      LOG_MEM(buf);
+    }
   }
 
+  LOG_MEM("Images loaded");
+
   if (total_images != num_photo) {
     std::cout << "Warning: Requested " << num_photo << " images but loaded "
               << total_images << " due to insufficient data" << '\n';
     num_photo = total_images;
   }
 
-  it_lab_ai::Shape input_shape_imagenet(
-      {num_photo, static_cast<size_t>(channels), static_cast<size_t>(height),
-       static_cast<size_t>(width)});
-  it_lab_ai::Tensor input =
-      it_lab_ai::make_tensor(all_image_data, input_shape_imagenet);
-
-  size_t output_classes = 1000;
-  it_lab_ai::Shape output_shape({num_photo, output_classes});
-  it_lab_ai::Tensor output =
-      it_lab_ai::Tensor(output_shape, it_lab_ai::Type::kFloat);
-
-  Graph graph;
-  build_graph(graph, input, output, json_path, options, false);
-  graph.inference(options);
-  print_time_stats(graph);
-
-  std::vector<std::vector<float>> processed_outputs;
-  const std::vector<float>& raw_output = *output.as<float>();
-
-  for (size_t i = 0; i < num_photo; ++i) {
-    std::vector<float> single_output(
-        raw_output.begin() + i * output_classes,
-        raw_output.begin() + (i + 1) * output_classes);
-    std::vector<float> processed_output =
-        process_model_output(single_output, model_name);
-    processed_outputs.push_back(processed_output);
-  }
-
   int correct_predictions_top1 = 0;
   int correct_predictions_top5 = 0;
-  for (size_t i = 0; i < processed_outputs.size(); ++i) {
-    int true_label = true_labels[i];
-    const std::vector<float>& probabilities = processed_outputs[i];
-
-    std::vector<size_t> indices(probabilities.size());
-    std::iota(indices.begin(), indices.end(), 0);
-    std::sort(indices.begin(), indices.end(), [&](size_t a, size_t b) {
-      return probabilities[a] > probabilities[b];
-    });
-
-    size_t predicted_class_top1 = indices[0];
-    if (predicted_class_top1 == static_cast<size_t>(true_label)) {
-      correct_predictions_top1++;
-    }
 
-    bool found_in_top5 = false;
-    for (int top_k = 0; top_k < std::min(5, static_cast<int>(indices.size()));
-         ++top_k) {
-      if (indices[top_k] == static_cast<size_t>(true_label)) {
-        found_in_top5 = true;
-        break;
+  LOG_MEM("Starting batch processing");
+  auto total_start_time = std::chrono::high_resolution_clock::now();
+  int total_inference_time = 0;
+
+  for (size_t batch_start = 0; batch_start < num_photo;
+       batch_start += batch_size) {
+    size_t batch_end = std::min(batch_start + batch_size, num_photo);
+    size_t current_batch_size = batch_end - batch_start;
+
+    char batch_log[100];
+    sprintf(batch_log, "Batch %zu/%zu (size %zu)", batch_start / batch_size + 1,
+            (num_photo + batch_size - 1) / batch_size, current_batch_size);
+    LOG_MEM(batch_log);
+
+    std::vector<float> batch_data;
+    batch_data.reserve(current_batch_size * image_size);
+
+    size_t batch_offset = batch_start * image_size;
+    batch_data.insert(batch_data.end(), all_image_data.begin() + batch_offset,
+                      all_image_data.begin() + batch_offset +
+                          current_batch_size * image_size);
+
+    it_lab_ai::Shape batch_input_shape(
+        {current_batch_size, static_cast<size_t>(channels),
+         static_cast<size_t>(height), static_cast<size_t>(width)});
+    it_lab_ai::Tensor batch_input = make_tensor(batch_data, batch_input_shape);
+
+    it_lab_ai::Shape batch_output_shape({current_batch_size, output_classes});
+    it_lab_ai::Tensor batch_output(batch_output_shape, it_lab_ai::Type::kFloat);
+
+    Graph graph;
+    build_graph(graph, batch_input, batch_output, json_path, options, false);
+
+    LOG_MEM("Batch inference");
+    // auto batch_start_time =
+    //     std::chrono::high_resolution_clock::now();
+    graph.inference(options);
+    total_inference_time += print_time_stats(graph);
+    // auto batch_end_time = std::chrono::high_resolution_clock::now();
+    // int batch_time =
+    //     static_cast<int>(std::chrono::duration_cast<std::chrono::milliseconds>(
+    //                          batch_end_time - batch_start_time)
+    //                          .count());  // ← Добавлен static_cast
+    // total_inference_time += batch_time;
+    // batch_count++;
+
+    // #ifdef ENABLE_STATISTIC_TIME
+    //          std::vector<int> elps_time = graph.getTime();
+    //          int batch_time = std::accumulate(elps_time.begin(),
+    //          elps_time.end(), 0); total_inference_time += batch_time;
+    //          batch_count++;
+    //
+    //          char time_log[100];
+    //          sprintf(time_log, "Batch %d time: %d ms", batch_count,
+    //          batch_time); LOG_MEM(time_log);
+    // #endif
+
+    const std::vector<float>& raw_batch_output = *batch_output.as<float>();
+
+    for (size_t i = 0; i < current_batch_size; ++i) {
+      size_t global_idx = batch_start + i;
+
+      std::vector<float> single_output(
+          raw_batch_output.begin() + i * output_classes,
+          raw_batch_output.begin() + (i + 1) * output_classes);
+
+      float max_val =
+          *std::max_element(single_output.begin(), single_output.end());
+      float sum = 0.0f;
+      for (float& val : single_output) {
+        val = exp(val - max_val);
+        sum += val;
+      }
+      for (float& val : single_output) {
+        val /= sum;
+      }
+
+      std::vector<size_t> indices(single_output.size());
+      std::iota(indices.begin(), indices.end(), 0);
+      std::sort(indices.begin(), indices.end(), [&](size_t a, size_t b) {
+        return single_output[a] > single_output[b];
+      });
+
+      if (indices[0] == static_cast<size_t>(true_labels[global_idx])) {
+        correct_predictions_top1++;
+      }
+
+      for (int top_k = 0; top_k < std::min(5, static_cast<int>(indices.size()));
+           ++top_k) {
+        if (indices[top_k] == static_cast<size_t>(true_labels[global_idx])) {
+          correct_predictions_top5++;
+          break;
+        }
       }
     }
-    if (found_in_top5) {
-      correct_predictions_top5++;
-    }
+
+    batch_data.clear();
+    batch_data.shrink_to_fit();
   }
 
+  auto total_end_time = std::chrono::high_resolution_clock::now();
+  int total_time =
+      static_cast<int>(std::chrono::duration_cast<std::chrono::milliseconds>(
+                           total_end_time - total_start_time)
+                           .count());
+
+  std::cout << "\n!INFERENCE TIME INFO START!" << '\n';
+  std::cout << "Total inference time (sum of batches): " << total_inference_time
+            << " ms\n";
+  std::cout << "Total wall-clock time for all batches: " << total_time
+            << " ms\n";
+  std::cout << "Number of batches: " << batch_count << '\n';
+  std::cout << "Average time per batch: "
+            << (batch_count > 0 ? total_inference_time / batch_count : 0)
+            << " ms\n";
+  std::cout << "!INFERENCE TIME INFO END!" << '\n';
+  /*std::cout << "\n!INFERENCE TIME INFO START!" << '\n';
+  std::cout << "Total inference time for all batches: " << total_inference_time
+            << " ms\n";
+  std::cout << "Number of batches: " << batch_count << '\n';
+  std::cout << "!INFERENCE TIME INFO END!" << '\n';
+  LOG_MEM("All batches processed");*/
+
   double final_accuracy_top1 =
       (static_cast<double>(correct_predictions_top1) / num_photo) * 100;
   double final_accuracy_top5 =
@@ -305,6 +468,7 @@ int main(int argc, char* argv[]) {
   std::cout << "Model: " << model_name << '\n';
   std::cout << "Dataset: " << dataset_path << '\n';
   std::cout << "Total images: " << num_photo << '\n';
+  std::cout << "Batch size: " << batch_size << '\n';
   std::cout << "Correct predictions (Top-1): " << correct_predictions_top1
             << '\n';
   std::cout << "Correct predictions (Top-5): " << correct_predictions_top5
@@ -314,5 +478,13 @@ int main(int argc, char* argv[]) {
   std::cout << "Top-5 Accuracy: " << std::fixed << std::setprecision(2)
             << final_accuracy_top5 << "%" << '\n';
 
+  all_image_data.clear();
+  all_image_data.shrink_to_fit();
+  image_paths.clear();
+  image_paths.shrink_to_fit();
+  true_labels.clear();
+  true_labels.shrink_to_fit();
+
+  LOG_MEM("Program end");
   return 0;
 }
\ No newline at end of file
diff --git a/app/Graph/build.cpp b/app/Graph/build.cpp
index 381e8fcd..d904c1a5 100644
--- a/app/Graph/build.cpp
+++ b/app/Graph/build.cpp
@@ -1129,18 +1129,17 @@ it_lab_ai::Tensor prepare_mnist_image(const cv::Mat& image) {
   return it_lab_ai::make_tensor(res, sh);
 }
 
-void print_time_stats(Graph& graph) {
+int print_time_stats(Graph& graph) {
 #ifdef ENABLE_STATISTIC_TIME
   std::vector<std::string> times = graph.getTimeInfo();
-  std::cout << "!INFERENCE TIME INFO START!" << '\n';
-  for (size_t i = 0; i < times.size(); i++) {
+  // std::cout << "!INFERENCE TIME INFO START!" << '\n';
+  /*for (size_t i = 0; i < times.size(); i++) {
     std::cout << times[i] << '\n';
-  }
+  }*/
   std::vector<int> elps_time = graph.getTime();
   int sum = std::accumulate(elps_time.begin(), elps_time.end(), 0);
-  std::cout << "Elapsed inference time:" << sum << '\n';
-  std::cout << "!INFERENCE TIME INFO END!" << '\n';
-  graph.printLayerStats();
+  // graph.printLayerStats();
+  return sum;
 #else
   (void)graph;
 #endif
diff --git a/app/Graph/build.hpp b/app/Graph/build.hpp
index 5628e9d1..4c5920dd 100644
--- a/app/Graph/build.hpp
+++ b/app/Graph/build.hpp
@@ -76,7 +76,7 @@ it_lab_ai::Tensor prepare_image(const cv::Mat& image,
                                 const std::string& model_name = "");
 it_lab_ai::Tensor prepare_mnist_image(const cv::Mat& image);
 
-void print_time_stats(it_lab_ai::Graph& graph);
+int print_time_stats(it_lab_ai::Graph& graph);
 namespace it_lab_ai {
 class LayerFactory {
  public:
diff --git a/include/graph/graph.hpp b/include/graph/graph.hpp
index 4743d996..6d7fdaa2 100644
--- a/include/graph/graph.hpp
+++ b/include/graph/graph.hpp
@@ -318,9 +318,11 @@ class Graph {
 
     for (size_t i = 0; i < traversal.size(); ++i) {
       int current_layer = traversal[i];
+
 #ifdef ENABLE_STATISTIC_TIME
       auto start = std::chrono::high_resolution_clock::now();
 #endif
+
       if (i != 0) {
         inten_.clear();
 
@@ -343,15 +345,19 @@ class Graph {
             }
 
             it->second.count_used_ten--;
+
+            // ���� ������ ������ ������ �� ����� - �������
             if (it->second.count_used_ten < 1) {
               branch_map_.erase(it);
             }
           }
         }
       }
+
       if (outten_.empty()) {
         outten_.resize(1);
       }
+
       layers_[current_layer]->run(inten_, outten_, options);
 
 #ifdef ENABLE_STATISTIC_TENSORS
@@ -399,7 +405,9 @@ class Graph {
         }
         new_branch.distribution = dis;
       }
+
       branch_map_[current_layer] = std::move(new_branch);
+
       if (outtenres_ && current_layer == end_ &&
           !branch_map_[current_layer].give_for_all.empty() &&
           countinout[current_layer].second == 0) {
@@ -433,6 +441,11 @@ class Graph {
       }
 #endif
     }
+
+    // ��������� �������
+    branch_map_.clear();
+    inten_.clear();
+    outten_.clear();
   }
 
   void setOutput(const std::shared_ptr<Layer>& layer, Tensor& vec) {

From d75a28d56278ea962fe7eda32a65e1697d924efc Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Wed, 11 Mar 2026 11:56:24 +0300
Subject: [PATCH 31/38] fix batch 32

---
 app/Graph/acc_check.cpp |  5 ++---
 app/Graph/build.cpp     |  1 +
 include/graph/graph.hpp | 13 -------------
 3 files changed, 3 insertions(+), 16 deletions(-)

diff --git a/app/Graph/acc_check.cpp b/app/Graph/acc_check.cpp
index 40cba480..e3a9b166 100644
--- a/app/Graph/acc_check.cpp
+++ b/app/Graph/acc_check.cpp
@@ -1,9 +1,8 @@
-
-#ifndef WIN32_LEAN_AND_MEAN
+#ifndef WIN32_LEAN_AND_MEAN
 #define WIN32_LEAN_AND_MEAN
 #endif
-#include <windows.h>
 #include <psapi.h>
+#include <windows.h>
 #pragma comment(lib, "psapi.lib")
 #include <crtdbg.h>
 #include <algorithm>
diff --git a/app/Graph/build.cpp b/app/Graph/build.cpp
index d904c1a5..cc61ff29 100644
--- a/app/Graph/build.cpp
+++ b/app/Graph/build.cpp
@@ -1142,5 +1142,6 @@ int print_time_stats(Graph& graph) {
   return sum;
 #else
   (void)graph;
+  return 0;
 #endif
 }
diff --git a/include/graph/graph.hpp b/include/graph/graph.hpp
index 6d7fdaa2..4743d996 100644
--- a/include/graph/graph.hpp
+++ b/include/graph/graph.hpp
@@ -318,11 +318,9 @@ class Graph {
 
     for (size_t i = 0; i < traversal.size(); ++i) {
       int current_layer = traversal[i];
-
 #ifdef ENABLE_STATISTIC_TIME
       auto start = std::chrono::high_resolution_clock::now();
 #endif
-
       if (i != 0) {
         inten_.clear();
 
@@ -345,19 +343,15 @@ class Graph {
             }
 
             it->second.count_used_ten--;
-
-            // ���� ������ ������ ������ �� ����� - �������
             if (it->second.count_used_ten < 1) {
               branch_map_.erase(it);
             }
           }
         }
       }
-
       if (outten_.empty()) {
         outten_.resize(1);
       }
-
       layers_[current_layer]->run(inten_, outten_, options);
 
 #ifdef ENABLE_STATISTIC_TENSORS
@@ -405,9 +399,7 @@ class Graph {
         }
         new_branch.distribution = dis;
       }
-
       branch_map_[current_layer] = std::move(new_branch);
-
       if (outtenres_ && current_layer == end_ &&
           !branch_map_[current_layer].give_for_all.empty() &&
           countinout[current_layer].second == 0) {
@@ -441,11 +433,6 @@ class Graph {
       }
 #endif
     }
-
-    // ��������� �������
-    branch_map_.clear();
-    inten_.clear();
-    outten_.clear();
   }
 
   void setOutput(const std::shared_ptr<Layer>& layer, Tensor& vec) {

From 510e764ffc692641bd8e407646578b7efea351b3 Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Wed, 11 Mar 2026 12:53:53 +0300
Subject: [PATCH 32/38] one graph && batching

---
 app/Graph/acc_check.cpp | 84 ++++++++++++++++++++++++-----------------
 1 file changed, 50 insertions(+), 34 deletions(-)

diff --git a/app/Graph/acc_check.cpp b/app/Graph/acc_check.cpp
index e3a9b166..ed552f00 100644
--- a/app/Graph/acc_check.cpp
+++ b/app/Graph/acc_check.cpp
@@ -1,8 +1,9 @@
-#ifndef WIN32_LEAN_AND_MEAN
+
+#ifndef WIN32_LEAN_AND_MEAN
 #define WIN32_LEAN_AND_MEAN
 #endif
-#include <psapi.h>
 #include <windows.h>
+#include <psapi.h>
 #pragma comment(lib, "psapi.lib")
 #include <crtdbg.h>
 #include <algorithm>
@@ -85,7 +86,7 @@ int main(int argc, char* argv[]) {
   std::string model_name = "alexnet_mnist";
   RuntimeOptions options;
   size_t num_photo = 1000;
-  size_t batch_size = 32;
+  size_t batch_size = 50;
 
   for (int i = 1; i < argc; ++i) {
     if (std::string(argv[i]) == "--model" && i + 1 < argc) {
@@ -151,7 +152,7 @@ int main(int argc, char* argv[]) {
   std::vector<int> input_shape = get_input_shape_from_json(json_path);
 
   std::cout << '\n';
-  int batch_count = 0;
+
   if (model_name == "alexnet_mnist") {
     LOG_MEM("MNIST start");
 
@@ -188,7 +189,7 @@ int main(int argc, char* argv[]) {
           for (int j = 0; j < 28; ++j) {
             size_t a = ind;
             for (size_t n = 0; n < name; n++) a += counts[n] + 1;
-            res[(a) * 28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
+            res[(a)*28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
           }
         }
       }
@@ -335,9 +336,42 @@ int main(int argc, char* argv[]) {
   int correct_predictions_top1 = 0;
   int correct_predictions_top5 = 0;
 
+  LOG_MEM("Building master graph");
+
+  it_lab_ai::Shape full_shape({num_photo, static_cast<size_t>(channels),
+                               static_cast<size_t>(height),
+                               static_cast<size_t>(width)});
+  it_lab_ai::Tensor dummy_input = make_tensor(all_image_data, full_shape);
+
+  it_lab_ai::Shape full_output_shape({num_photo, output_classes});
+  it_lab_ai::Tensor dummy_output(full_output_shape, it_lab_ai::Type::kFloat);
+
+  Graph graph;
+  build_graph(graph, dummy_input, dummy_output, json_path, options, false);
+  LOG_MEM("Master graph built");
+
+  std::shared_ptr<Layer> input_layer = nullptr;
+  std::shared_ptr<Layer> output_layer = nullptr;
+
+  for (int i = 0; i < graph.getLayersCount(); ++i) {
+    auto layer = graph.getLayerFromID(i);
+    if (layer->getName() == kInput) {
+      input_layer = layer;
+    }
+    if (i == graph.getLayersCount() - 1) {
+      output_layer = layer;
+    }
+  }
+
+  if (!input_layer || !output_layer) {
+    std::cerr << "Error: Could not find input/output layers" << '\n';
+    return 1;
+  }
+
   LOG_MEM("Starting batch processing");
   auto total_start_time = std::chrono::high_resolution_clock::now();
   int total_inference_time = 0;
+  int batch_count = 0;
 
   for (size_t batch_start = 0; batch_start < num_photo;
        batch_start += batch_size) {
@@ -365,32 +399,20 @@ int main(int argc, char* argv[]) {
     it_lab_ai::Shape batch_output_shape({current_batch_size, output_classes});
     it_lab_ai::Tensor batch_output(batch_output_shape, it_lab_ai::Type::kFloat);
 
-    Graph graph;
-    build_graph(graph, batch_input, batch_output, json_path, options, false);
+    graph.setInput(input_layer, batch_input);
+    graph.setOutput(output_layer, batch_output);
 
     LOG_MEM("Batch inference");
-    // auto batch_start_time =
-    //     std::chrono::high_resolution_clock::now();
+    auto batch_start_time = std::chrono::high_resolution_clock::now();
     graph.inference(options);
-    total_inference_time += print_time_stats(graph);
-    // auto batch_end_time = std::chrono::high_resolution_clock::now();
-    // int batch_time =
-    //     static_cast<int>(std::chrono::duration_cast<std::chrono::milliseconds>(
-    //                          batch_end_time - batch_start_time)
-    //                          .count());  // ← Добавлен static_cast
-    // total_inference_time += batch_time;
-    // batch_count++;
-
-    // #ifdef ENABLE_STATISTIC_TIME
-    //          std::vector<int> elps_time = graph.getTime();
-    //          int batch_time = std::accumulate(elps_time.begin(),
-    //          elps_time.end(), 0); total_inference_time += batch_time;
-    //          batch_count++;
-    //
-    //          char time_log[100];
-    //          sprintf(time_log, "Batch %d time: %d ms", batch_count,
-    //          batch_time); LOG_MEM(time_log);
-    // #endif
+    auto batch_end_time = std::chrono::high_resolution_clock::now();
+
+    int batch_time =
+        static_cast<int>(std::chrono::duration_cast<std::chrono::milliseconds>(
+                             batch_end_time - batch_start_time)
+                             .count());
+    total_inference_time += batch_time;
+    batch_count++;
 
     const std::vector<float>& raw_batch_output = *batch_output.as<float>();
 
@@ -451,12 +473,6 @@ int main(int argc, char* argv[]) {
             << (batch_count > 0 ? total_inference_time / batch_count : 0)
             << " ms\n";
   std::cout << "!INFERENCE TIME INFO END!" << '\n';
-  /*std::cout << "\n!INFERENCE TIME INFO START!" << '\n';
-  std::cout << "Total inference time for all batches: " << total_inference_time
-            << " ms\n";
-  std::cout << "Number of batches: " << batch_count << '\n';
-  std::cout << "!INFERENCE TIME INFO END!" << '\n';
-  LOG_MEM("All batches processed");*/
 
   double final_accuracy_top1 =
       (static_cast<double>(correct_predictions_top1) / num_photo) * 100;

From aeeb3c64263c7c551ed9574bc7d5b8a4bb83ac86 Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Wed, 11 Mar 2026 13:07:43 +0300
Subject: [PATCH 33/38] clean

---
 app/Graph/acc_check.cpp | 111 +---------------------------------------
 1 file changed, 2 insertions(+), 109 deletions(-)

diff --git a/app/Graph/acc_check.cpp b/app/Graph/acc_check.cpp
index ed552f00..c7c74700 100644
--- a/app/Graph/acc_check.cpp
+++ b/app/Graph/acc_check.cpp
@@ -1,12 +1,4 @@
-
-#ifndef WIN32_LEAN_AND_MEAN
-#define WIN32_LEAN_AND_MEAN
-#endif
-#include <windows.h>
-#include <psapi.h>
-#pragma comment(lib, "psapi.lib")
-#include <crtdbg.h>
-#include <algorithm>
+#include <algorithm>
 #include <chrono>
 #include <cmath>
 #include <filesystem>
@@ -17,72 +9,10 @@
 
 #include "build.hpp"
 
-class MemoryLogger {
- private:
-  std::chrono::steady_clock::time_point start_time;
-  size_t peak_memory = 0;
-  size_t initial_memory = 0;
-
-  size_t getProcessMemory() {
-    HANDLE hProcess = GetCurrentProcess();
-    PROCESS_MEMORY_COUNTERS pmc;
-    pmc.cb = sizeof(PROCESS_MEMORY_COUNTERS);
-
-    if (GetProcessMemoryInfo(hProcess, &pmc, sizeof(pmc))) {
-      return pmc.WorkingSetSize / (1024 * 1024);
-    }
-    return 0;
-  }
-
- public:
-  MemoryLogger() {
-    start_time = std::chrono::steady_clock::now();
-    initial_memory = getProcessMemory();
-    log("START");
-  }
-
-  void log(const char* stage) {
-    auto now = std::chrono::steady_clock::now();
-    auto elapsed =
-        std::chrono::duration_cast<std::chrono::seconds>(now - start_time)
-            .count();
-
-    size_t current = getProcessMemory();
-    if (current > peak_memory) peak_memory = current;
-
-    std::cout << "[" << std::setw(4) << elapsed << "s] " << std::setw(30)
-              << stage << " | "
-              << "PROCESS MEM: " << std::setw(6) << current << " MB"
-              << " (PEAK: " << std::setw(6) << peak_memory << " MB)"
-              << " (DELTA: " << std::setw(4) << (current - initial_memory)
-              << " MB)\n";
-  }
-
-  ~MemoryLogger() {
-    log("END");
-    std::cout << "====================================\n";
-    std::cout << "PEAK PROCESS MEMORY: " << peak_memory << " MB\n";
-    std::cout << "INITIAL PROCESS MEMORY: " << initial_memory << " MB\n";
-    std::cout << "FINAL PROCESS MEMORY: " << getProcessMemory() << " MB\n";
-    if (getProcessMemory() > initial_memory + 10) {
-      std::cout << "WARNING: Process memory growth! (+"
-                << (getProcessMemory() - initial_memory) << " MB)\n";
-    } else {
-      std::cout << "OK: No significant process memory growth\n";
-    }
-  }
-};
-
-MemoryLogger g_memLogger;
-
-#define LOG_MEM(stage) g_memLogger.log(stage)
-
 namespace fs = std::filesystem;
 using namespace it_lab_ai;
 
 int main(int argc, char* argv[]) {
-  LOG_MEM("Program start");
-
   std::string model_name = "alexnet_mnist";
   RuntimeOptions options;
   size_t num_photo = 1000;
@@ -139,8 +69,6 @@ int main(int argc, char* argv[]) {
     }
   }
 
-  LOG_MEM("After args parsing");
-
   std::string dataset_path;
   if (model_name == "alexnet_mnist") {
     dataset_path = MNIST_PATH;
@@ -154,8 +82,6 @@ int main(int argc, char* argv[]) {
   std::cout << '\n';
 
   if (model_name == "alexnet_mnist") {
-    LOG_MEM("MNIST start");
-
     std::vector<size_t> counts = {979, 1134, 1031, 1009, 981,
                                   891, 957,  1027, 973,  1008};
     int stat = 0;
@@ -189,7 +115,7 @@ int main(int argc, char* argv[]) {
           for (int j = 0; j < 28; ++j) {
             size_t a = ind;
             for (size_t n = 0; n < name; n++) a += counts[n] + 1;
-            res[(a)*28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
+            res[(a) * 28 * 28 + i * 28 + j] = channels[0].at<uchar>(j, i);
           }
         }
       }
@@ -223,20 +149,15 @@ int main(int argc, char* argv[]) {
         (static_cast<double>(stat) / static_cast<double>(sum + 10)) * 100;
     std::cout << "Stat: " << std::fixed << std::setprecision(2) << percentage
               << "%" << '\n';
-
-    LOG_MEM("MNIST end");
     return 0;
   }
 
-  LOG_MEM("ImageNet start");
-
   std::vector<size_t> counts(1000, 0);
   std::vector<std::string> image_paths;
   std::vector<int> true_labels;
   std::vector<float> all_image_data;
   size_t total_images = 0;
 
-  LOG_MEM("Counting classes");
   for (int class_id = 0; class_id < 1000; ++class_id) {
     std::ostringstream folder_oss;
     folder_oss << std::setw(5) << std::setfill('0') << class_id;
@@ -262,14 +183,12 @@ int main(int argc, char* argv[]) {
   size_t image_size = channels * height * width;
   size_t output_classes = 1000;
 
-  LOG_MEM("Reserving memory");
   all_image_data.reserve(num_photo * image_size);
   image_paths.reserve(num_photo);
   true_labels.reserve(num_photo);
 
   total_images = 0;
 
-  LOG_MEM("Loading images start");
   for (int class_id = 0; class_id < 1000; ++class_id) {
     size_t need_from_class = images_per_class_base;
     if (remaining > 0) {
@@ -317,16 +236,8 @@ int main(int argc, char* argv[]) {
       std::cout << "Warning: Class " << class_id << " has only " << taken
                 << " images (needed " << need_from_class << ")" << '\n';
     }
-
-    if (class_id % 100 == 0 && class_id > 0) {
-      char buf[50];
-      sprintf(buf, "Class %d", class_id);
-      LOG_MEM(buf);
-    }
   }
 
-  LOG_MEM("Images loaded");
-
   if (total_images != num_photo) {
     std::cout << "Warning: Requested " << num_photo << " images but loaded "
               << total_images << " due to insufficient data" << '\n';
@@ -336,8 +247,6 @@ int main(int argc, char* argv[]) {
   int correct_predictions_top1 = 0;
   int correct_predictions_top5 = 0;
 
-  LOG_MEM("Building master graph");
-
   it_lab_ai::Shape full_shape({num_photo, static_cast<size_t>(channels),
                                static_cast<size_t>(height),
                                static_cast<size_t>(width)});
@@ -348,7 +257,6 @@ int main(int argc, char* argv[]) {
 
   Graph graph;
   build_graph(graph, dummy_input, dummy_output, json_path, options, false);
-  LOG_MEM("Master graph built");
 
   std::shared_ptr<Layer> input_layer = nullptr;
   std::shared_ptr<Layer> output_layer = nullptr;
@@ -368,7 +276,6 @@ int main(int argc, char* argv[]) {
     return 1;
   }
 
-  LOG_MEM("Starting batch processing");
   auto total_start_time = std::chrono::high_resolution_clock::now();
   int total_inference_time = 0;
   int batch_count = 0;
@@ -378,11 +285,6 @@ int main(int argc, char* argv[]) {
     size_t batch_end = std::min(batch_start + batch_size, num_photo);
     size_t current_batch_size = batch_end - batch_start;
 
-    char batch_log[100];
-    sprintf(batch_log, "Batch %zu/%zu (size %zu)", batch_start / batch_size + 1,
-            (num_photo + batch_size - 1) / batch_size, current_batch_size);
-    LOG_MEM(batch_log);
-
     std::vector<float> batch_data;
     batch_data.reserve(current_batch_size * image_size);
 
@@ -402,7 +304,6 @@ int main(int argc, char* argv[]) {
     graph.setInput(input_layer, batch_input);
     graph.setOutput(output_layer, batch_output);
 
-    LOG_MEM("Batch inference");
     auto batch_start_time = std::chrono::high_resolution_clock::now();
     graph.inference(options);
     auto batch_end_time = std::chrono::high_resolution_clock::now();
@@ -493,13 +394,5 @@ int main(int argc, char* argv[]) {
   std::cout << "Top-5 Accuracy: " << std::fixed << std::setprecision(2)
             << final_accuracy_top5 << "%" << '\n';
 
-  all_image_data.clear();
-  all_image_data.shrink_to_fit();
-  image_paths.clear();
-  image_paths.shrink_to_fit();
-  true_labels.clear();
-  true_labels.shrink_to_fit();
-
-  LOG_MEM("Program end");
   return 0;
 }
\ No newline at end of file

From dab3fdbf30693867fcec9dd38f0403b803ef4ffb Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Wed, 11 Mar 2026 20:40:45 +0300
Subject: [PATCH 34/38] up to 1000

---
 .github/workflows/ci.yml | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 6f5b0b4c..aeafe460 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -340,17 +340,17 @@ jobs:
             parser: parser_onnx.py
             model_file: densenet121_Opset16.onnx
             model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/densenet121_Opset16_timm/densenet121_Opset16.onnx?download=
-            extra_args: "--onednn 100"
+            extra_args: "--onednn 1000"
           - model: resnet
             parser: parser_onnx.py
             model_file: resnest101e_Opset16.onnx
             model_url: https://github.com/onnx/models/raw/refs/heads/main/Computer_Vision/resnest101e_Opset16_timm/resnest101e_Opset16.onnx?download=
-            extra_args: "--onednn 100"
+            extra_args: "--onednn 1000"
           - model: yolo
             parser: parser_onnx.py
             model_file: yolo11x-cls.pt
             model_url: https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo11x-cls.pt
-            extra_args: "--onednn 100"
+            extra_args: "--onednn 1000"
 
     steps:
     - uses: actions/checkout@v4
@@ -579,8 +579,8 @@ jobs:
           echo -e "\n## ${{ matrix.model }} Accuracy\n<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->Accuracy: ${ACCURACY}% (updated: ${DATE})<!--END_ACCURACY_${{ matrix.model }}-->\n" >> README.md
         fi
 
-    - name: Commit and push changes (master only)
-      if: github.ref == 'refs/heads/master'
+    - name: Commit and push changes (main only)
+      if: github.ref == 'refs/heads/main'
       run: |
         git config --global user.name "GitHub Actions"
         git config --global user.email "actions@github.com"

From 2fe1f5a19c38611e9c0391725dc2ca83392528ad Mon Sep 17 00:00:00 2001
From: Semyon1104 <sema_titov_04@mail.ru>
Date: Thu, 12 Mar 2026 18:58:40 +0300
Subject: [PATCH 35/38] batch32

---
 app/Converters/parser_onnx.py | 2 +-
 app/Graph/acc_check.cpp       | 4 +---
 2 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/app/Converters/parser_onnx.py b/app/Converters/parser_onnx.py
index 0c0b931a..8fcecbcb 100644
--- a/app/Converters/parser_onnx.py
+++ b/app/Converters/parser_onnx.py
@@ -171,7 +171,7 @@ def default(self, obj):
 
 parser = argparse.ArgumentParser(description='Конвертация моделей в JSON формат')
 parser.add_argument('model_name', type=str,
-                        choices=['googlenet', 'densenet', 'resnet', 'yolo', 'alexnet'],
+                        choices=['googlenet', 'densenet', 'resnet', 'yolo'],
                         help='Имя модели для обработки')
 
 args = parser.parse_args()
diff --git a/app/Graph/acc_check.cpp b/app/Graph/acc_check.cpp
index c7c74700..d37d4f89 100644
--- a/app/Graph/acc_check.cpp
+++ b/app/Graph/acc_check.cpp
@@ -16,13 +16,11 @@ int main(int argc, char* argv[]) {
   std::string model_name = "alexnet_mnist";
   RuntimeOptions options;
   size_t num_photo = 1000;
-  size_t batch_size = 50;
+  size_t batch_size = 32;
 
   for (int i = 1; i < argc; ++i) {
     if (std::string(argv[i]) == "--model" && i + 1 < argc) {
       model_name = argv[++i];
-    } else if (std::string(argv[i]) == "--batch" && i + 1 < argc) {
-      batch_size = std::stoi(argv[++i]);
     } else if (std::string(argv[i]) == "--onednn") {
       options.backend = Backend::kOneDnn;
       if (options.par_backend != ParBackend::kSeq) {

From b235670755c319595b8c3aeaf5d84e1c2c13f5ec Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Thu, 12 Mar 2026 19:01:14 +0300
Subject: [PATCH 36/38] placeholders

---
 README.md | 16 +++++++++++++++-
 1 file changed, 15 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 853a75c7..c428b2dd 100644
--- a/README.md
+++ b/README.md
@@ -4,7 +4,21 @@
 # AlexNet-MNIST-Inference
 ## Model Performance
 
-<!--ACCURACY_PLACEHOLDER-->Accuracy: Stat: 98.01% (updated: 2025-04-28)<!--END_ACCURACY-->
+### AlexNet-MNIST Accuracy
+<!--ACCURACY_PLACEHOLDER--><!--END_ACCURACY-->
+
+### GoogLeNet Accuracy
+<!--ACCURACY_googlenet_PLACEHOLDER--><!--END_ACCURACY_googlenet-->
+
+### DenseNet Accuracy
+<!--ACCURACY_densenet_PLACEHOLDER--><!--END_ACCURACY_densenet-->
+
+### ResNet Accuracy
+<!--ACCURACY_resnet_PLACEHOLDER--><!--END_ACCURACY_resnet-->
+
+### YOLO Accuracy
+<!--ACCURACY_yolo_PLACEHOLDER--><!--END_ACCURACY_yolo-->
+
 ## Short description
 A lightweight C++ library for performing high-performance inference on classification tasks. Designed for efficiency and educational purposes, this project demonstrates how classic CNNs can be optimized for small-scale tasks in native environments.
 ### Key Features:

From 5440df4be1d85c70189539b6517ae6c9c1bcabaa Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Thu, 12 Mar 2026 19:01:44 +0300
Subject: [PATCH 37/38] Update ci.yml

---
 .github/workflows/ci.yml | 23 +++++++++++++++++------
 1 file changed, 17 insertions(+), 6 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index aeafe460..9307dd3e 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -335,7 +335,7 @@ jobs:
             model_file: GoogLeNet.onnx
             model_path: docs/models/GoogLeNet.onnx
             model_url: ''
-            extra_args: "--onednn 1000"
+            extra_args: "--onednn 10000"
           - model: densenet
             parser: parser_onnx.py
             model_file: densenet121_Opset16.onnx
@@ -568,15 +568,26 @@ jobs:
     - name: Update README for model (master only)
       if: github.ref == 'refs/heads/master'
       run: |
-        ACCURACY=$(cat accuracy_value_${{ matrix.model }}.txt | sed 's/%//g')
+        TOP1_ACC=$(grep -oE 'Top-1 Accuracy: [0-9]+\.?[0-9]*%' accuracy_${{ matrix.model }}.txt | grep -oE '[0-9]+\.?[0-9]*')
+        TOP5_ACC=$(grep -oE 'Top-5 Accuracy: [0-9]+\.?[0-9]*%' accuracy_${{ matrix.model }}.txt | grep -oE '[0-9]+\.?[0-9]*')
         DATE=$(date '+%Y-%m-%d')
-      
+    
+        if [ -z "$TOP1_ACC" ] || [ -z "$TOP5_ACC" ]; then
+          echo "Ошибка: Не удалось извлечь точность из файла accuracy_${{ matrix.model }}.txt"
+          cat accuracy_${{ matrix.model }}.txt
+          exit 1
+        fi
+    
+        UPDATE_TEXT="<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->Accuracy: Top-1: ${TOP1_ACC}% | Top-5: ${TOP5_ACC}% (updated: ${DATE})<!--END_ACCURACY_${{ matrix.model }}-->"
+    
         if grep -q "<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->" README.md; then
-          sed -i "s/<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->.*<!--END_ACCURACY_${{ matrix.model }}-->/<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->Accuracy: ${ACCURACY}% (updated: ${DATE})<!--END_ACCURACY_${{ matrix.model }}-->/" README.md
+          sed -i "s|<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->.*<!--END_ACCURACY_${{ matrix.model }}-->|${UPDATE_TEXT}|" README.md
           echo "Обновлена точность для ${{ matrix.model }} в README"
         else
-          echo "Плейсхолдер для ${{ matrix.model }} не найден в README, добавляем в конец"
-          echo -e "\n## ${{ matrix.model }} Accuracy\n<!--ACCURACY_${{ matrix.model }}_PLACEHOLDER-->Accuracy: ${ACCURACY}% (updated: ${DATE})<!--END_ACCURACY_${{ matrix.model }}-->\n" >> README.md
+          echo "Ошибка: Плейсхолдер <!--ACCURACY_${{ matrix.model }}_PLACEHOLDER--> не найден в README.md"
+          echo "Содержимое README.md:"
+          cat README.md
+          exit 1
         fi
 
     - name: Commit and push changes (main only)

From 2d0c1f2946fbe89f466cc722e139601b7c19bf45 Mon Sep 17 00:00:00 2001
From: Semyon1104 <129722895+Semyon1104@users.noreply.github.com>
Date: Thu, 12 Mar 2026 20:32:07 +0300
Subject: [PATCH 38/38] fix cashe

---
 .github/workflows/ci.yml | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 9307dd3e..f45a5214 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -416,9 +416,8 @@ jobs:
       uses: actions/cache/restore@v4
       with:
         path: docs/ImageNet
-        key: imagenet-paste-v1-${{ hashFiles('app/Converters/download_imagenet.py') }}
+        key: imagenet-paste-${{ github.run_id }}-${{ hashFiles('app/Converters/download_imagenet.py') }}
         restore-keys: |
-          imagenet-paste-v1-
           imagenet-paste-
 
     - name: Download ImageNet-Paste dataset