PIDOptimizer | CVPR 2018 paper : A PID Controller Approach

by tensorboy Python Version: Current License: No License

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

kandi X-RAY | PIDOptimizer Summary

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

This repository contains source code of the CVPR 2018 paper:.

Support

Quality

Security

License

Reuse

Support

PIDOptimizer has a low active ecosystem.

It has 150 star(s) with 49 fork(s). There are 14 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 3 have been closed. On average issues are closed in 16 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of PIDOptimizer is current.

Quality

PIDOptimizer has 0 bugs and 0 code smells.

Security

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

PIDOptimizer code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

PIDOptimizer 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

PIDOptimizer releases are not available. You will need to build from source code and install.

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

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

PIDOptimizer saves you 364 person hours of effort in developing the same functionality from scratch.

It has 870 lines of code, 73 functions and 16 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed PIDOptimizer and discovered the below as its top functions. This is intended to give you an instant insight into PIDOptimizer implemented functionality, and help decide if they suit your requirements.

Update progress bar
Write line to file
Clear the line
Colorize image
Gaussian operator
Set the names
Write string to file
Show a masklist
Make an image
Plot the loggers
Plots the overlap plot
Perform a single step of the optimizer
Save matplotlib figure
Close the stream
Update the phase
Visualize a batch of images
Update the index
Moves the cursor to the specified position
Append a list of numbers to the file
Update the current progress
Update the statistics
Plot the plot
Compute the accuracy of the target
Displays a single image
Update the buffer

Get all kandi verified functions for this library.

PIDOptimizer Key Features

No Key Features are available at this moment for PIDOptimizer.

PIDOptimizer Examples and Code Snippets

No Code Snippets are available at this moment for PIDOptimizer.

Community Discussions

Trending Discussions on PIDOptimizer

Need to change GPU option to CPU in a python pytorch based code

QUESTION

Need to change GPU option to CPU in a python pytorch based code

Asked 2019-Feb-06 at 19:59

The code basically trains the usual MNIST image dataset but it does the training on a GPU. I need to change this option so the code trains the model using my laptop computer. I need to substitute the .cuda() at the second line for the equivalent in CPU.

I know there are many examples online on how to train neural networks using the MNIST database but what is special about this code is that it does the optimization using a PID controller (commonly used in industry) and I need the code as part of my research.

...

ANSWER

Answered 2019-Feb-06 at 01:31

It is better to move up to latest pytorch (1.0.x).

With latest pytorch, it is more easy to manage "device".

Below is a simple example.

Source https://stackoverflow.com/questions/54544986

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

Vulnerabilities

No vulnerabilities reported

Install PIDOptimizer

You can download it from GitHub.
You can use PIDOptimizer like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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 .

Find more information at: