CppNet

CppNet is a high-performance C++ deep learning library for building and training neural networks. It uses Eigen for fast tensor operations, OpenMP for CPU parallelism, and CUDA for GPU acceleration.

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✨ Features

• 🚀 High Performance: Vectorized operations via Eigen and multi-threading with OpenMP.
• 🔧 GPU Acceleration: CUDA support for heavy computations.
• 🧩 Modular API: Clear separation of layers, losses, optimizers, metrics, and regularizations.
• 📦 Extensible: Easy to add custom layers, losses, or optimizers.
• 📊 Visualization: Tools for plotting training curves and inspecting models.
• 🧪 Examples Included: CNN, Linear, Transformer, and more.

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📂 Project Structure

CppNet/
├── CMakeLists.txt
├── examples/                   # Example programs
│   ├── cnn_example.cpp         # CNN example
│   ├── linear_example.cpp      # Linear layer example
│   └── transformer_example.cpp # Transformer example
├── include/                    # Public headers (library API)
│   ├── activations.hpp
│   ├── data.hpp
│   ├── layers.hpp
│   ├── losses.hpp
│   ├── metrics.hpp
│   ├── models.hpp
│   ├── optimizers.hpp
│   ├── regularization.hpp
│   ├── utils.hpp
│   └── visualization.hpp
├── src/                        # Implementations
│   ├── activations.cpp
│   ├── data.cpp
│   ├── layers.cpp
│   ├── losses.cpp
│   ├── metrics.cpp
│   ├── models.cpp
│   ├── optimizers.cpp
│   ├── regularization.cpp
│   ├── utils.cpp
│   └── visualization.cpp
├── LICENSE
└── README.md

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⚡ Installation

Prerequisites

• C++17 or newer
• Eigen (header-only, auto-detected if installed)
• CMake ≥ 3.14
• (Optional) CUDA Toolkit for GPU acceleration
• (Optional) OpenMP for CPU parallelism

Build Instructions

git clone https://github.com/LoqmanSamani/CppNet.git
cd CppNet
mkdir build && cd build
cmake ..
make -j$(nproc)

This will build the library and all example programs inside examples/.

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📚 Roadmap

• Implement complete set of layers (CNN, RNN, Transformer, etc.)
• Add GPU backend (CUDA kernels for layers and ops)
• Add training utilities (Trainer, Callbacks, Checkpoints)
• Add more examples (GANs, Reinforcement Learning, NLP models)

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🛠 Contributing

Contributions are welcome!

Please follow consistent coding style (headers in include/, implementations in src/).

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📜 License

CppNet is released under the MIT License.