v0.1.0 - Initial Release

EvoOptimizer v0.1.0

An evolved deep learning optimizer discovered via genetic algorithm search.

Installation

pip install evo-optimizer

Highlights

• Discovered, not designed: Found via genetic algorithm search over 50 generations
• Outperforms Adam: 2.6% improvement in aggregate fitness, 7.7% on CIFAR-10
• Hybrid update rule: Combines sign-based updates with adaptive moments
• Built-in scheduling: Warmup and cosine decay included

Quick Start

from evo_optimizer import EvoOptimizer

model = YourModel()
optimizer = EvoOptimizer(model.parameters(), lr=1.2e-3, total_steps=10000)

for step, (inputs, targets) in enumerate(dataloader):
    optimizer.zero_grad()
    loss = loss_fn(model(inputs), targets)
    loss.backward()
    optimizer.step(step=step)

Links

• Paper: arXiv:2512.11853
• PyPI: evo-optimizer