nevergrad | A Python toolbox for performing gradient-free optimization | Machine Learning library

by facebookresearch Python Version: 1.0.3 License: MIT

X-Ray Key Features Code Snippets(4)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | nevergrad Summary

nevergrad is a Python library typically used in Artificial Intelligence, Machine Learning applications. nevergrad has build file available, it has a Permissive License and it has high support. However nevergrad has 9 bugs and it has 1 vulnerabilities. You can install using 'pip install nevergrad' or download it from GitHub, PyPI.

nevergrad is a Python 3.6+ library. It can be installed with:. More installation options, including windows installation, and complete instructions are available in the "Getting started" section of the documentation.

Support

Quality

Security

License

Reuse

Support

nevergrad has a highly active ecosystem.

It has 3449 star(s) with 330 fork(s). There are 64 watchers for this library.

There were 1 major release(s) in the last 6 months.

There are 84 open issues and 158 have been closed. On average issues are closed in 112 days. There are 45 open pull requests and 0 closed requests.

It has a negative sentiment in the developer community.

The latest version of nevergrad is 1.0.3

Quality

nevergrad has 9 bugs (0 blocker, 0 critical, 5 major, 4 minor) and 226 code smells.

Security

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

nevergrad code analysis shows 1 unresolved vulnerabilities (0 blocker, 1 critical, 0 major, 0 minor).

There are 8 security hotspots that need review.

License

nevergrad 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

nevergrad releases are available to install and integrate.

Deployable package is available in PyPI.

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

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

nevergrad saves you 6432 person hours of effort in developing the same functionality from scratch.

It has 13377 lines of code, 1287 functions and 127 files.

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

Top functions reviewed by kandi - BETA

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

Create a plot of the data frame .
Generates a list of functions that can be used for a given seed .
Generate Yabbob functions .
Simulate power power system .
Generate dataset .
Minimize the objective function .
private helper function for testing
quickly flip the state of the game
Simulates the simulation with given parameters
Performs the absorption

Get all kandi verified functions for this library.

nevergrad Key Features

No Key Features are available at this moment for nevergrad.

nevergrad Examples and Code Snippets

CoTenGra,Basic usage :zap:,Advanced Settings

Python

Lines of Code : 9

License : Permissive (Apache-2.0)

Copy

opt = ctg.HyperOptimizer(
    minimize='size',    # {'size', 'flops', 'combo'}, what to target
    parallel=True,      # {'auto', bool, int, 'dask', 'ray', executor}
    max_time=60,        # maximum seconds to run for (None for no limit)
    max_rep

Black-Box-Tuning,Prepare your environment

Python

Lines of Code : 9

License : Permissive (MIT)

Copy

conda create --name bbt python=3.8
conda activate bbt
pip install transformers==4.1.1
pip install datasets
pip install fastNLP
pip install cma
pip install sklearn
git clone https://github.com/txsun1997/Black-Box-Tuning
cd Black-Box-Tuning

nevergrad4sf,invocation

Python

Lines of Code : 5

License : Strong Copyleft (GPL-3.0)

Copy

mpiexec -np 16 python3 -m mpi4py.futures nevergrad4sf.py --cutechess ./cutechess_cli --stockfish ./stockfish --book noob_3moves.epd --tc 1.0+0.01 --games_per_batch 20000 --cutechess_concurrency 8 --evaluation_concurrency 3 --ng_evals 100

mpiexec -np

Suggesting Values in Nevergrad Package

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

Copy

optimizer.suggest(k=3, loc=-2, s=2, scale=2, w=mp.ones(self.times.shape[0]))

Community Discussions

Trending Discussions on nevergrad

Suggesting Values in Nevergrad Package

QUESTION

Suggesting Values in Nevergrad Package

Asked 2021-Mar-05 at 14:50

Steps to reproduce ...

ANSWER

Answered 2021-Mar-05 at 14:50

The question was answered in a relevant Github thread:

Basically, suggest should be called the same way as the function to optimize, in your case, given you are using an Instrumentation, I guess it should be:

Source https://stackoverflow.com/questions/66461673

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

Vulnerabilities

No vulnerabilities reported

Install nevergrad

You can install using 'pip install nevergrad' or download it from GitHub, PyPI.
You can use nevergrad 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.