MetaRuleGPT

This project focuses on implementing a neural network-based solution for a sequence-to-sequence task, utilizing various techniques like character-level processing, dynamic programming, and error evaluation.

Requirements

Before running the project, ensure that you have the following installed:

Python 3.9
PyTorch
NumPy
Matplotlib
Other dependencies (listed in requirements.txt)

Installation

You can clone this repository and install the necessary libraries using pip:

git clone <repository_url> cd <project_directory> pip install -r requirements.txt

Code Structure

The project structure is organized as follows:

.
├── src
│   ├── data_preprocessing.py     # Functions for preprocessing data (e.g., `char_num_map`, `deal_base`)
│   ├── model.py                  # Core model implementation using neural networks
│   ├── dynamic_programming.py    # Implementation of dynamic programming for sequence decisions
│   ├── error_eval.py             # Error evaluation functions (e.g., `eval_error`)
│   ├── utils.py                  # Utility functions for model training and decoding
│   ├── training.py               # Functions for training the model
│   └── postprocessing.py         # Postprocessing functions like `make_progress`
├── data
│   └── error.txt                 # Example input data for evaluation
├── requirements.txt              # Python dependencies
└── README.md                     # Project documentation

Contributing

Feel free to fork the repository and create a pull request. Ensure that you follow the project’s coding style and write tests for any new functionality you add.

License

This project is licensed under the MIT License - see the LICENSE file for details.