hypersearch | Hyperparameter optimization for PyTorch | Machine Learning library
kandi X-RAY | hypersearch Summary
kandi X-RAY | hypersearch Summary
Tune the hyperparameters of your PyTorch models with HyperSearch.
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Top functions reviewed by kandi - BETA
- Tune configs
- Find a key in params
- Generate random configuration
- Sample from a random distribution
- Returns a base model
- Save results to json file
- Prepare directories
- Add an argument group to the parser
- Parse known arguments
hypersearch Key Features
hypersearch Examples and Code Snippets
Community Discussions
Trending Discussions on hypersearch
QUESTION
okay, THIS HAS BEEN DRIVING ME INSANE FOR LIKE THE PAST TWO DAYS. and its really annoying, so i am building an application using kivy, after getting used "easy as pie" tkinter I thought it was time to learn kivy (as it has mobile compatibility).
#I wanted to learn to reference different widgets# I searched YouTube and google for hours but to no avail I keep getting an error message
my code:
....py
ANSWER
Answered 2021-May-17 at 10:04Let's give you a simple example of how to use the magic id
attribute of kivy !
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install hypersearch
You can use hypersearch 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.
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