Tsetlin Machine Unified (TMU) - One Codebase to Rule Them All

TMU is a comprehensive repository that encompasses several Tsetlin Machine implementations. Offering a rich set of features and extensions, it serves as a central resource for enthusiasts and researchers alike.

Features

• Core Implementations:

  • Tsetlin Machine
  • Coalesced Tsetlin Machine
  • Convolutional Tsetlin Machine
  • Regression Tsetlin Machine
  • Weighted Tsetlin Machine
  • Autoencoder
  • Multi-task Classifier (Upcoming)
  • One-vs-one Multi-class Classifier (Upcoming)
  • Relational Tsetlin Machine (In Progress)

• Extended Features:

  • Support for Continuous Features
  • Drop Clause
  • Literal Budget
  • Focused Negative Sampling
  • Type III Feedback
  • Incremental Clause Evaluation (Upcoming)
  • Sparse Computation with Absorbing Actions
  • TMComposites: Plug-and-Play Collaboration Between Specialized Tsetlin Machines (In Progress)

• Wrappers for C and CUDA-based clause evaluation and updates to enable high-performance computation.

📦 Installation

Prerequisites for Windows

Before installing TMU on Windows, ensure you have the MSVC build tools. Follow these steps:

1. Download MSVC build tools
2. Install the Workloads → Desktop development with C++ package. (Note: The package size is about 6-7GB.)

Dependencies

Ubuntu: sudo apt install libffi-dev

Installing TMU

To get started with TMU, run the following command:

pip install git+https://github.com/cair/tmu.git

🛠 Development

If you're looking to contribute or experiment with the codebase, follow these steps:

1. Clone the Repository:

   git clone [email protected]:cair/tmu.git

2. Set Up Development Environment: Navigate to the project directory and compile the C library:

   cd tmu && pip install develop .

3. Starting a New Project: For your projects, simply create a new folder within 'examples' and initiate your development.

Modifying the C Codebase

If you make changes to the C codebase, ensure you recompile the code using:

pip install develop .

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