large-scale-curiosity | Status : Archive

by Xemnas0 Python Version: Current License: No License

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

kandi X-RAY | large-scale-curiosity Summary

large-scale-curiosity is a Python library. large-scale-curiosity has no bugs, it has no vulnerabilities and it has low support. However large-scale-curiosity build file is not available. You can download it from GitHub.

Status: Archive (code is provided as-is, no updates expected).

Support

Quality

Security

License

Reuse

Support

large-scale-curiosity has a low active ecosystem.

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

It had no major release in the last 6 months.

large-scale-curiosity has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of large-scale-curiosity is current.

Quality

large-scale-curiosity has no bugs reported.

Security

large-scale-curiosity has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

large-scale-curiosity does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

large-scale-curiosity releases are not available. You will need to build from source code and install.

large-scale-curiosity 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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large-scale-curiosity Key Features

No Key Features are available at this moment for large-scale-curiosity.

large-scale-curiosity Examples and Code Snippets

No Code Snippets are available at this moment for large-scale-curiosity.

Community Discussions

No Community Discussions are available at this moment for large-scale-curiosity.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install large-scale-curiosity

The following command should train a pure exploration agent on Breakout with default experiment parameters. To use more than one gpu/machine, use MPI (e.g. mpiexec -n 8 python run.py should use 1024 parallel environments to collect experience instead of the default 128 on an 8 gpu machine).

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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