ProxTorch

Unleashing Proximal Gradient Descent on PyTorch 🚀

🔍 What is ProxTorch?
Dive into a rich realm of proximal operators and constraints with ProxTorch, a state-of-the-art Python library crafted on PyTorch. Whether it's optimization challenges or the complexities of machine learning, ProxTorch is designed for speed, efficiency, and seamless GPU integration.

✨ Features

• 🚀 GPU-Boosted: Experience lightning-fast computations with extensive CUDA support.
• 🔥 PyTorch Synergy: Naturally integrates with all your PyTorch endeavours.
• 📚 Expansive Library: From elemental norms (L0, L1, L2, L∞) to advanced regularizations like Total Variation and Fused Lasso.
• 🤝 User-Friendly: Jump right in! Intuitive design means minimal disruptions to your existing projects.

🛠 Installation

Getting started with ProxTorch is a breeze. Install from PyPI with:

pip install proxtorch

Or install from source with:

git clone
cd ProxTorch
pip install -e .

🚀 Quick Start

Dive in with this straightforward example:

import torch
from proxtorch.operators import L1

# Define a sample tensor
x = torch.tensor([0.5, -1.2, 0.3, -0.4, 0.7])

# Initialize the L1 proximal operator
l1_prox = L1(sigma=0.1)

# Compute the regularization component value
reg_value = l1_prox(x)
print("Regularization Value:", reg_value)

# Apply the proximal operator
result = l1_prox.prox(x)
print("Prox Result:", result)

📜 Diverse Proximal Operators

Regularizers

• L1, L2 (Ridge), ElasticNet, GroupLasso, TV (includes TV_2D, TV_3D, TVL1_2D, TVL1_3D), **Frobenius **
• Norms: TraceNorm, NuclearNorm
• FusedLasso, Huber

Constraints

• L0Ball, L1Ball, L2Ball, L∞Ball (Infinity Norm), Frobenius, TraceNorm, Box

📖 Documentation

Explore the comprehensive documentation on Read the Docs.

🙌 Credits

ProxTorch stands on the shoulders of giants:

• pyproximal
• ProxGradPyTorch
• nilearn

We're thrilled to introduce ProxTorch as an exciting addition to the PyTorch ecosystem. We're confident you'll love it!

🤝 Contribute to the ProxTorch Revolution

Got ideas? Join our vibrant community and make ProxTorch even better!

📜 License

ProxTorch is proudly released under the MIT License.