NABLA
Nabla is a Python library that provides three key features:
- Multidimensional Array computation (like NumPy) with strong GPU acceleration
- Composable Function Transformations:
vmap,grad,jit, and other Automatic Differentiation tools - Deep integration with MAX and (custom) Mojo kernels
For tutorials and API reference, visit: nablaml.com
Installation
Now available on PyPI!
pip install nabla-ml
Note: Nabla also includes an experimental pure Mojo API for native Mojo development.
Quick Start
import nabla as nb
# Example function using Nabla's array operations
def foo(input):
return nb.sum(input * input, axes=0)
# Vectorize, differentiate, accelerate
foo_grads = nb.jit(nb.vmap(nb.grad(foo)))
gradients = foo_grads(nb.randn((10, 5)))
Development Setup
For contributors and advanced users:
# Clone and install in development mode
git clone https://github.com/nabla-ml/nb.git
cd nabla
pip install -e ".[dev]"
# Run tests
pytest
# Format and lint code
ruff format nabla/
ruff check nabla/ --fix
Repository Structure
nabla/
├── nabla/ # Core Python library
│ ├── core/ # Function transformations and core array class
│ ├── nn/ # Neural network modules and models
│ ├── ops/ # Mathematical operations (binary, unary, linalg, etc.)
│ ├── transforms/ # Function transformations (vmap, grad, jit, etc.)
│ └── utils/ # Utilities (broadcasting, formatting, types)
├── tests/ # Comprehensive test suite
├── tutorials/ # Notebooks on Nabla usage for ML tasks
├── examples/ # Example scripts for common use cases
└── experimental/ # An alternative pure Mojo API (WIP!)
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.
Thank you for checking out Nabla!
1 maintainer
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