softmax-linear-unit 1.2.0

An implementation of softmax linear unit (solu) in PyTorch

SoLU - Softmax Linear Unit

This repository packages an implementation of Sofmax Linear Unit, as proposed in Softmax Linear Units.

Module Structure

SoLU -> SoLU, SoLULayer

Performance Penalty Mitigation

The original paper talks about a performance penalty with softmax linear unit which can be mitigated with an additional Layer Norm. This mitigation has been applied in the SoLULayer module in this package. The activation function itself is in the SoLU module.

Example Usage

Installation

pip install softmax-linear-unit

Code import

[!NOTE] SoLU and SoLULayer are torch.nn modules and hence can be used in any pytorch model definition.

import torch
from SoLU import SoLULayer, SoLU


@torch.no_grad()
def main():
    # batch_size=2, seq_len=5, hidden_dim=4
    x = torch.randn(2, 5, 4)

    # Initialize the layer (SoLU + LayerNorm)
    solu_block = SoLULayer(hidden_size=4)

    # Forward Pass
    output = solu_block(x)
    print(output)
    print(output.size())


if __name__ == "__main__":
    main()

You can also check main.py

Local Dev

Env

# make sure to have uv installed
# also python 3.12.11

uv sync
source .venv/bin/activate

Ruff and Pre-Commit

By default, pre-commit will run ruff formatting with the --fix flag.

[!NOTE] The pre-commit configuration can be found in the .pre-commit-config.yaml file.

pre-commit install