DORL-codes | Source codes for our SIGIR '23 paper

by chongminggao Python Version: Current License: MIT

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

kandi X-RAY | DORL-codes Summary

DORL-codes is a Python library. DORL-codes has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However DORL-codes build file is not available. You can download it from GitHub.

Source codes for our SIGIR '23 paper

Support

Quality

Security

License

Reuse

Support

DORL-codes has a low active ecosystem.

It has 5 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

DORL-codes has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of DORL-codes is current.

Quality

DORL-codes has no bugs reported.

Security

DORL-codes has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

DORL-codes is licensed under the MIT License. This license is Permissive.

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

Reuse

DORL-codes releases are not available. You will need to build from source code and install.

DORL-codes has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

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DORL-codes Key Features

No Key Features are available at this moment for DORL-codes.

DORL-codes Examples and Code Snippets

No Code Snippets are available at this moment for DORL-codes.

Community Discussions

No Community Discussions are available at this moment for DORL-codes.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install DORL-codes

Clone this git repository and change directory to this repository:. A new conda environment is suggested. Activate the newly created environment. Install the required modules from pip.
Clone this git repository and change directory to this repository: git clone https://github.com/chongminggao/DORL-codes.git cd DORL-codes/
A new conda environment is suggested. conda create --name DORL python=3.10 -y
Activate the newly created environment. conda activate DORL
Install the required modules from pip. sh install.sh Install the tianshou package from my forked version: cd src git clone https://github.com/chongminggao/tianshou.git cd ..

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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