nabla-ml 25.8081506

Dynamic neural networks and function transformations in Python + Mojo

Nabla is a scientific computing library in Python, featuring:

• Multidimensional array computation with strong GPU acceleration
• JAX-like composable function transformations: grad, vmap, jit, and other automatic differentiation tools
• Deep integration with the MAX compiler and custom Mojo 🔥 kernels

For tutorials and API reference, visit: nablaml.com

Installation

pip install nabla-ml

Quick Start

import nabla as nb

# Example function using Nabla's array operations
def foo(input):
    return nb.sum(input * input, axes=-1)

# Differentiate, vectorize, accelerate
foo_grads = nb.jit(nb.vmap(nb.grad(foo)))
gradients = foo_grads(nb.randn((10, 5)).to(nb.accelerator()))

For Developers

1. Clone the repository
2. Create a virtual environment (recommended)
3. Install dependencies

git clone https://github.com/nabla-ml/nabla.git
cd nabla

python3 -m venv venv
source venv/bin/activate

pip install -r requirements-dev.txt
pip install -e ".[dev]"

Repository Structure

nabla/
├── nabla/                     # Core Python library
│   ├── core/                  # Array class and MAX compiler integration
│   ├── nn/                    # Neural network modules and models
│   ├── ops/                   # Mathematical operations (binary, unary, linalg, etc.)
│   ├── transforms/            # Function transformations (vmap, grad, jit, etc.)
│   └── utils/                 # Utilities (formatting, types, MAX-interop, etc.)
├── tests/                     # Comprehensive test suite
├── tutorials/                 # Notebooks on Nabla usage for ML tasks
└── examples/                  # Example scripts for common use cases

Contributing

Contributions welcome! Discuss significant changes in Issues first. Submit PRs for bugs, docs, and smaller features.

License

Nabla is licensed under the Apache-2.0 license.

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Thank you for checking out Nabla!