Package Health Score

50 / 100

security
Security review needed
popularity
Limited
maintenance
Inactive
community
Limited

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Popularity

Limited

GitHub Stars: 51
Forks: 1
Contributors: 1

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package torchist, we found that it has been starred 51 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Apr 3, 2024
Direct Vulnerabilities: 0
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0
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0
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0
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Indirect Vulnerabilities: 0
C
0
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0
M
0
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License Risk: 0
H
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

Inactive

Commit Frequency

Open Issues: 0
Open PR: 0
Last Release: 8 months ago
Last Commit: 8 months ago

Further analysis of the maintenance status of torchist based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Inactive.

We found that torchist demonstrates a positive version release cadence with at least one new version released in the past 12 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.

We found a way for you to contribute to the project! Looks like torchist is missing a Code of Conduct.

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Package

Python Versions Compatibility: >=3.6

Age: 4 years
Latest Release: 8 months ago
Dependencies: 0 Direct
Versions: 9
Maintainers: 1
Wheels: OS Independent

Readme

NumPy-style histograms in PyTorch

The torchist package implements NumPy's histogram and histogramdd functions in PyTorch with CUDA support. The package also features implementations of ravel_multi_index, unravel_index and some useful functionals like entropy or kl_divergence.

Installation

The torchist package is available on PyPI, which means it is installable with pip.

pip install torchist

Alternatively, if you need the latest features, you can install it from the repository.

pip install git+https://github.com/francois-rozet/torchist

Getting Started

import torch
import torchist

x = torch.rand(100, 3).cuda()

hist = torchist.histogramdd(x, bins=10, low=0.0, upp=1.0)

print(hist.shape)  # (10, 10, 10)

Benchmark

The implementations of torchist are on par or faster than those of numpy on CPU and benefit greately from CUDA capabilities.

$ python torchist/__init__.py
CPU
---
np.histogram : 1.2559 s
np.histogramdd : 20.7816 s
np.histogram (non-uniform) : 5.4878 s
np.histogramdd (non-uniform) : 17.3757 s
torchist.histogram : 1.3975 s
torchist.histogramdd : 9.6160 s
torchist.histogram (non-uniform) : 5.0883 s
torchist.histogramdd (non-uniform) : 17.2743 s

CUDA
----
torchist.histogram : 0.1363 s
torchist.histogramdd : 0.3754 s
torchist.histogram (non-uniform) : 0.1355 s
torchist.histogramdd (non-uniform) : 0.5137 s

FAQs

What is torchist?

NumPy-style histograms in PyTorch. Visit Snyk Advisor to see a full health score report for torchist, including popularity, security, maintenance & community analysis.

Is torchist popular?

The python package torchist receives a total of 357 weekly downloads. As such, torchist popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is torchist well maintained?

We found indications that torchist is an Inactive project. See the full package health analysis to learn more about the package maintenance status.

Is torchist safe to use?

While scanning the latest version of torchist, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 22 November-2024, at 14:49 (UTC).

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torchist