Skip to main content

Light Recurrent Unit

Project description

Light Recurrent Unit - Pytorch

Implementation of the Light Recurrent Unit in Pytorch

Install

$ pip install light-recurrent-unit-pytorch

Usage

import torch
from light_recurrent_unit_pytorch import LightRecurrentUnitCell

cell = LightRecurrentUnitCell(256)

x = torch.randn(2, 256)
hidden = torch.randn(2, 256)

next_hidden = cell(x, hidden) # (2, 256)

Single layer

import torch
from light_recurrent_unit_pytorch import LightRecurrentUnitLayer

layer = LightRecurrentUnitLayer(256)

x = torch.randn(2, 1024, 256)

out = layer(x) # (2, 1024, 256)

assert out.shape == x.shape

Stacked

import torch
from light_recurrent_unit_pytorch import LightRecurrentUnit

lru = LightRecurrentUnit(256, depth = 4)

x = torch.randn(2, 1024, 256)

out = lru(x) # (2, 1024, 256)

assert out.shape == x.shape

Citations

@Article{electronics13163204,
    AUTHOR = {Ye, Hong and Zhang, Yibing and Liu, Huizhou and Li, Xuannong and Chang, Jiaming and Zheng, Hui},
    TITLE = {Light Recurrent Unit: Towards an Interpretable Recurrent Neural Network for Modeling Long-Range Dependency},
    JOURNAL = {Electronics},
    VOLUME = {13},
    YEAR = {2024},
    NUMBER = {16},
    ARTICLE-NUMBER = {3204},
    URL = {https://www.mdpi.com/2079-9292/13/16/3204},
    ISSN = {2079-9292},
    DOI = {10.3390/electronics13163204}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

light_recurrent_unit_pytorch-0.0.14.tar.gz (1.0 MB view details)

Uploaded Source

Built Distribution

File details

Details for the file light_recurrent_unit_pytorch-0.0.14.tar.gz.

File metadata

File hashes

Hashes for light_recurrent_unit_pytorch-0.0.14.tar.gz
Algorithm Hash digest
SHA256 be7af35f7ad0fd15a4ab5e895c243dfee207c5aeead1296d50e3c5b979743369
MD5 a4a1ba91cacfac9455813858ea4234b2
BLAKE2b-256 9376673aba1169fd02b8f42f03ee701a1eeca3f0be26dad6e597e6fd9ab1cdc8

See more details on using hashes here.

File details

Details for the file light_recurrent_unit_pytorch-0.0.14-py3-none-any.whl.

File metadata

File hashes

Hashes for light_recurrent_unit_pytorch-0.0.14-py3-none-any.whl
Algorithm Hash digest
SHA256 9c3127b26101a6a12469fef49c7c4a45121acce66f1bb666ae84ecf310867e41
MD5 a8837d0298b04a825532adc442d6a4e5
BLAKE2b-256 9b61ffa7f547b738763a4adf2f2af9dca7870680e54a06d7dab5c05dff0321e3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page