View efficient-linear-decod… on Snyk Open Source Advisor

Package Health Score

60 / 100

security
No known security issues
popularity
Limited
maintenance
Sustainable
community
Limited

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Popularity

Limited

GitHub Stars: 30
Forks: 0
Contributors: 1

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package efficient-linear-decoding, we found that it has been starred 30 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Aug 25, 2024
Direct Vulnerabilities: 0
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Indirect Vulnerabilities: 0
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License Risk: 0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MIT

Security Policy

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Maintenance

Sustainable

Commit Frequency

Open Issues: 0
Open PR: 0
Last Release: 2 months ago
Last Commit: 1 month ago

Further analysis of the maintenance status of efficient-linear-decoding based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Sustainable.

We found that efficient-linear-decoding demonstrates a positive version release cadence with at least one new version released in the past 3 months.

In the past month we didn't find any pull request activity or change in issues status has been detected for the GitHub repository.

Community

Limited

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 1
Funding: No

This project has seen only 10 or less contributors.

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Package

Python Versions Compatibility: >=3.8

Age: 3 months
Latest Release: 2 months ago
Dependencies: N/A
Versions: 7
Maintainers: 1
Wheels: No

Readme

An efficient Linear Attention Decoding package

1. installation

conda create -n efficient_linear_decoding python=3.9
conda activate efficient_linear_decoding
pip install efficient_linear_decoding

The code has been test under the following environment:

triton&gt;=2.1.0
torch&gt;=2.1.0
pycuda
pynvml
numpy&lt;2

You can use the following command to install:

pip install triton==2.1.0
pip install torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 --index-url https://download.pytorch.org/whl/cu118
pip install pycuda
pip install pynvml
pip install numpy

2. usage

import torch
from efficient_linear_decoding.efficient_linear_decoding import causal_linear_decoder

# Create input tensor
Q = torch.randn(2,32,1024,128,device='cuda:0')
K = torch.randn(2,32,1024,128,device='cuda:0')
V = torch.randn(2,32,1024,128,device='cuda:0')

# Inference using causal_linear_decoder
output = causal_linear_decoder(Q,K,V)

# If you want to input a mask with weight, set the is_mask_weight: True
gamma = torch.full((32,),0.5,device='cuda:0')
output = causal_linear_decoder(Q,K,V,is_mask_weight=True,gamma=gamma)

3. acknowledgement

method	Title	Paper	Code
causal_dot_product	Fast Transformers with Clustered Attention	arxiv	code
Lighting Attention-2	Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models	arxiv	code

FAQs

What is efficient-linear-decoding?

Efficient computation library for linear attention. Visit Snyk Advisor to see a full health score report for efficient-linear-decoding, including popularity, security, maintenance & community analysis.

Is efficient-linear-decoding popular?

We’re still processing downloads data for the python package efficient-linear-decoding. Visit the popularity section on Snyk Advisor to see the full popularity analysis.

Is efficient-linear-decoding well maintained?

We found indications that efficient-linear-decoding maintenance is sustainable demonstrating some project activity. We saw a total of 1 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is efficient-linear-decoding safe to use?

The python package efficient-linear-decoding was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 28 October-2024, at 13:15 (UTC).

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efficient-linear-decoding

Efficient computation library for linear attention. For more information about how to use this package see README

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Readme

An efficient Linear Attention Decoding package

1. installation

2. usage

3. acknowledgement

FAQs

What is efficient-linear-decoding?

Is efficient-linear-decoding popular?

Is efficient-linear-decoding well maintained?

Is efficient-linear-decoding safe to use?

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Commit Frequency

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Readme

An efficient Linear Attention Decoding package

1. installation

2. usage

3. acknowledgement

FAQs

What is efficient-linear-decoding?

Is efficient-linear-decoding popular?

Is efficient-linear-decoding well maintained?

Is efficient-linear-decoding safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

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Config

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