never-give-up | PyTorch implementation of Never Give | Reinforcement Learning library

by Coac Python Version: Current License: MIT

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

kandi X-RAY | never-give-up Summary

never-give-up is a Python library typically used in Artificial Intelligence, Reinforcement Learning, Deep Learning, Pytorch applications. never-give-up has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

PyTorch implementation of Never Give Up: Learning Directed Exploration Strategies [Paper]. Only the episodic curiosity with embedding network has been implemented.

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Quality

Security

License

Reuse

Support

never-give-up has a low active ecosystem.

It has 39 star(s) with 6 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of never-give-up is current.

Quality

never-give-up has 0 bugs and 0 code smells.

Security

never-give-up has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

never-give-up code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

never-give-up 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

never-give-up releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

It has 465 lines of code, 26 functions and 5 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed never-give-up and discovered the below as its top functions. This is intended to give you an instant insight into never-give-up implemented functionality, and help decide if they suit your requirements.

Train the model
Perform a step
Compute the loss between x1 and x2
Embed embedding
Get action and hidden state
Compute the LSTM
Compute the maximum action
Push the given error to the memory
Convert a td error to priority
Push state to memory
Push the local memory into memory
Reset the model
Compute the embedding
Updates the priority for the given indexes
Calculate TTD error
Train a model
Generate a random transition
Computes the reward for a given epoch
Sample from the memory
Update the target model from an online network

Get all kandi verified functions for this library.

never-give-up Key Features

No Key Features are available at this moment for never-give-up.

never-give-up Examples and Code Snippets

No Code Snippets are available at this moment for never-give-up.

Community Discussions

Trending Discussions on never-give-up

Performing onClick() action and href in tag in React

QUESTION

Performing onClick() action and href in tag in React

Asked 2021-Jan-15 at 14:01

I am trying to count how many times an user clicked in my custom button. The button is based on Click me! . The whole code is:

...

ANSWER

Answered 2021-Jan-15 at 14:01

The problem have not anything with react, its just that href override the onclick event. now you could still fix this problem easy.

Note: that you need to also react-router so you could still maintained the counter data, or at list save it somewhere in db or session. because after the redirect the page will refresh and all sate will be lost

Here is an example on how to do it.

Source https://stackoverflow.com/questions/65732803

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

Vulnerabilities

No vulnerabilities reported

Install never-give-up

Tested with Python 3.7.9.

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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