https://github.com/bjornmelin/tensorflow-evolution
🧠 Progressive journey through TensorFlow, from basics to advanced architectures. Featuring custom training pipelines, optimized GPU implementations, and production-ready models. Includes CUDA optimizations for large-scale training. 🚀
https://github.com/bjornmelin/tensorflow-evolution
cuda deep-learning gpu-optimization machine-learning ml-engineering neural-networks python tensorflow
Last synced: 8 months ago
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🧠 Progressive journey through TensorFlow, from basics to advanced architectures. Featuring custom training pipelines, optimized GPU implementations, and production-ready models. Includes CUDA optimizations for large-scale training. 🚀
- Host: GitHub
- URL: https://github.com/bjornmelin/tensorflow-evolution
- Owner: BjornMelin
- License: mit
- Created: 2025-01-24T02:16:04.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-24T03:03:55.000Z (about 1 year ago)
- Last Synced: 2025-01-24T04:18:09.680Z (about 1 year ago)
- Topics: cuda, deep-learning, gpu-optimization, machine-learning, ml-engineering, neural-networks, python, tensorflow
- Homepage:
- Size: 5.86 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# TensorFlow Evolution 🧠
[](https://www.python.org/downloads/)
[](https://tensorflow.org/)
[](LICENSE)
[](https://developer.nvidia.com/cuda-toolkit)
[](CONTRIBUTING.md)
> Progressive journey through TensorFlow implementations, from foundational concepts to advanced architectures. Features custom training pipelines, optimized GPU implementations, and production-ready models.
[Features](#features) • [Installation](#installation) • [Quick Start](#quick-start) • [Documentation](#documentation) • [Contributing](#contributing)
## 📑 Table of Contents
- [Features](#features)
- [Project Structure](#project-structure)
- [Prerequisites](#prerequisites)
- [Installation](#installation)
- [Quick Start](#quick-start)
- [Documentation](#documentation)
- [Models](#models)
- [GPU Optimization](#gpu-optimization)
- [Benchmarks](#benchmarks)
- [Contributing](#contributing)
- [Versioning](#versioning)
- [Authors](#authors)
- [Citation](#citation)
- [License](#license)
- [Acknowledgments](#acknowledgments)
## ✨ Features
- Custom training loops and optimizations
- GPU-accelerated model training
- Production deployment patterns
- CUDA optimizations for large-scale training
- Comprehensive documentation and examples
## 📁 Project Structure
```mermaid
graph TD
A[tensorflow-evolution] --> B[notebooks]
A --> C[src]
A --> D[tests]
A --> E[docs]
A --> F[apps]
C --> G[models]
C --> H[data]
C --> I[utils]
C --> J[cuda]
G --> K[basic]
G --> L[advanced]
J --> M[kernels]
J --> N[optimizations]
```
Click to expand full directory structure
```plaintext
tensorflow-evolution/
├── notebooks/ # Jupyter notebooks for experiments
│ ├── basic/ # Foundational concepts
│ └── advanced/ # Advanced implementations
├── src/ # Source code
│ ├── models/ # Model implementations
│ ├── data/ # Data processing utilities
│ ├── utils/ # Helper functions
│ └── cuda/ # CUDA optimizations
├── tests/ # Unit tests
├── docs/ # Documentation
├── apps/ # Demo applications
└── README.md # Main documentation
```
## 🔧 Prerequisites
- Python 3.8+
- CUDA 11.8+ (for GPU support)
- NVIDIA GPU with compute capability 6.0+
## 📦 Installation
```bash
# Clone the repository
git clone https://github.com/BjornMelin/tensorflow-evolution.git
cd tensorflow-evolution
# Create virtual environment
python -m venv venv
source venv/bin/activate # Linux/Mac
# or
.\venv\Scripts\activate # Windows
# Install dependencies
pip install -r requirements.txt
```
## 🚀 Quick Start
```python
from src.models import BasicCNN
from src.utils import DataLoader
# Initialize model
model = BasicCNN()
# Train model
model.train(data_loader, epochs=10)
```
## 📚 Documentation
### Models
| Model | Description | Performance | CUDA Support |
|-------|-------------|-------------|--------------|
| BasicCNN | Foundational CNN architecture | 94% accuracy on MNIST | ✓ |
| TransformerBlock | Custom transformer implementation | BERT-comparable | ✓ |
| AdvancedGAN | Generative adversarial network | FID: 18.3 | ✓ |
### GPU Optimization
Comprehensive CUDA optimizations including:
- Custom compute kernels
- Memory-efficient training
- Multi-GPU data parallelism
- Gradient accumulation
### Benchmarks
Performance metrics across different hardware configurations:
| Model Size | GPU Memory | Training Time | Inference Time |
|------------|------------|---------------|----------------|
| Small (10M) | 4GB | 2.3 hrs | 5ms |
| Medium (50M) | 8GB | 5.7 hrs | 15ms |
| Large (100M) | 16GB | 12.4 hrs | 35ms |
## 🤝 Contributing
We welcome contributions! Please see our:
- [Contributing Guidelines](CONTRIBUTING.md)
- [Code of Conduct](CODE_OF_CONDUCT.md)
- [Development Guide](DEVELOPMENT.md)
## 📌 Versioning
We use [SemVer](http://semver.org/) for versioning. For available versions, see the [tags on this repository](https://github.com/BjornMelin/tensorflow-evolution/tags).
## ✍️ Authors
**Bjorn Melin**
- GitHub: [@BjornMelin](https://github.com/BjornMelin)
- LinkedIn: [Bjorn Melin](https://linkedin.com/in/bjorn-melin)
## 📝 Citation
```bibtex
@misc{melin2024tensorflowevolution,
author = {Melin, Bjorn},
title = {TensorFlow Evolution: Progressive Deep Learning Implementations},
year = {2024},
publisher = {GitHub},
url = {https://github.com/BjornMelin/tensorflow-evolution}
}
```
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🙏 Acknowledgments
- TensorFlow team for their excellent documentation
- NVIDIA for CUDA toolkit and documentation
- Open source community for valuable feedback
---
Made with 🧠 and ❤️ by Bjorn Melin