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sparse-ir-docker

SpM-lab / sparse-ir-docker

[Environment] Docker image including the sparse-ir libraries and their tutorials

Strong correlation/effective modelsDockerfileMIT
Updated: 2023-06-26

Overview

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README

sparse-ir Docker Image

This builds the shinaoka/sparse-ir docker hub image which includes sparse-ir libraries and their tutotrials.

One can run a Jupyterlab environment as

docker run --rm -p 8888:8888 shinaoka/sparse-ir

, or can run a shell as

docker run --rm -ti shinaoka/sparse-ir bash

The Jupyter notebook will be accessible at http://localhost:8888, where you should pass the token provided on the command line. If you want the state of the virtual machine to be stored, drop --rm from the commands above. A summary of useful docker commands can be found here.

If you want to update the image and push it Docker Hub, use the following commands

docker build -t shinaoka/sparse-ir . --no-cache
docker push shinaoka/sparse-ir

Source: https://github.com/SpM-lab/sparse-ir-docker README

Richness

LowLast updated: 2023-06-26 ()

Richness = how many of docs / examples / tests are in place, shown as 0–3 stars (1 star = 1 item; the checklist below is the breakdown). Software listed by hand (without repository data) is not assessed and is left out when filtering by a richness of 1 or more.

Information

Primary language
Dockerfile
Languages
Dockerfile
License
MIT
Provider
github

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