Implementation of the Remixer Block from the Remixer paper, in Pytorch

Related tags

Deep Learningdeep-learningtransformersartificial-intelligence
Overview

Remixer - Pytorch

Implementation of the Remixer Block from the Remixer paper, in Pytorch. It claims that substituting the feedforwards in transformers with sequence wide mixing followed by multiplication and subtraction leads to better language understanding results.

Install

$ pip install remixer-pytorch

Usage

import torch
from remixer_pytorch import RemixerBlock

block = RemixerBlock(
    dim = 512,
    seq_len = 1024
)

x = torch.randn(1, 1024, 512)
block(x) # (1, 1024, 512)

Citations

@inproceedings{anonymous,
    title   = {Remixers: A Mixer-Transformer Architecture with Compositional Operators for Natural Language Understanding },
    author  = {Anonymous},
    year = {2021},
    url = {https://openreview.net/forum?id=9FHQHJnRtfL}
}
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