particleflow | Machine-learned, GPU-accelerated particle flow reconstruction | GPU library

by jpata Jupyter Notebook Version: v1.4 License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | particleflow Summary

particleflow is a Jupyter Notebook library typically used in Hardware, GPU applications. particleflow has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Machine-learned, GPU-accelerated particle flow reconstruction

Support

Quality

Security

License

Reuse

Support

particleflow has a low active ecosystem.

It has 18 star(s) with 26 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 25 have been closed. On average issues are closed in 168 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of particleflow is v1.4

Quality

particleflow has no bugs reported.

Security

particleflow has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

particleflow is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

particleflow releases are available to install and integrate.

Installation instructions are available. Examples and code snippets are not available.

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particleflow Key Features

No Key Features are available at this moment for particleflow.

particleflow Examples and Code Snippets

No Code Snippets are available at this moment for particleflow.

Community Discussions

Trending Discussions on particleflow

pip search finds tensorflow, but pip install does not

QUESTION

pip search finds tensorflow, but pip install does not

Asked 2020-Jan-23 at 06:55

I am trying to build a Django app that would use Keras models to make recommendations. Right now I'm trying to use one custom container that would hold both Django and Keras. Here's the Dockerfile I've written.

...

ANSWER

Answered 2019-Jan-02 at 22:56

It looks like tensorflow only publishes wheels (and only up to 3.6), and Alpine linux is not manylinux1-compatible due to its use of musl instead of glibc. Because of this, pip cannot find a suitable installation candidate and fails. Your best options are probably to build from source or change your base image.

Source https://stackoverflow.com/questions/54014076

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install particleflow

The software setup for the ML training is available in the singularity spec file scripts/base.singularity.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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