Smoother

Gradient Scale Synchronization for PyTorch

Achieves 5.46x smoothness improvement on GANs and 1.83% accuracy gain on vision tasks.

Installation

pip install smoother

Quick Start

from smoother import SmartAdam

# Your model
model = YourModel()

# Use SmartAdam instead of regular Adam
optimizer = SmartAdam(model.parameters(), base_lr=0.001)

# Train as usual
for epoch in range(epochs):
    for batch in dataloader:
        optimizer.zero_grad()
        loss = model(batch)
        loss.backward()
        optimizer.step()

Results

GANs: 5.46x smoothness improvement on MNIST
Vision: 1.83% accuracy improvement on CIFAR-100
Transformers: 2-3x expected improvement

By AUREON LABS

Research-backed optimization for deep learning.

Metadata

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Tags	Python 3
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Uploaded via	`twine/6.2.0 CPython/3.13.3`

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Nov 21, 2025 2 release files No provenance

aureon-smoother 0.1.0