pytorch-optimizer | torch-optimizer -- collection of optimizers for Pytorch | Machine Learning library

by jettify Python Version: v0.3.0 License: Apache-2.0

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | pytorch-optimizer Summary

pytorch-optimizer is a Python library typically used in Artificial Intelligence, Machine Learning, Pytorch applications. pytorch-optimizer has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. However pytorch-optimizer has 1 bugs. You can install using 'pip install pytorch-optimizer' or download it from GitHub, PyPI.

torch-optimizer -- collection of optimizers for Pytorch

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Quality

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pytorch-optimizer has a medium active ecosystem.

It has 2746 star(s) with 272 fork(s). There are 35 watchers for this library.

It had no major release in the last 12 months.

There are 27 open issues and 30 have been closed. On average issues are closed in 34 days. There are 17 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pytorch-optimizer is v0.3.0

Quality

pytorch-optimizer has 1 bugs (0 blocker, 0 critical, 1 major, 0 minor) and 32 code smells.

Security

pytorch-optimizer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pytorch-optimizer code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pytorch-optimizer is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

pytorch-optimizer releases are available to install and integrate.

Deployable package is available in PyPI.

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

pytorch-optimizer saves you 1513 person hours of effort in developing the same functionality from scratch.

It has 3371 lines of code, 126 functions and 35 files.

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

Top functions reviewed by kandi - BETA

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

Perform a single step
Calculate the learning rate
Determine if the parameter group is valid
Calculate the approximate square root of the matrix
Performs a single step
Compute the perturbation of the image
Calculate cosine similarity
Calculate the loss function
Calculate the trace
Execute a function for each optimizer
Execute the given function
Plot the rosenbrock function
Compute the Rsenbrock function
Plot rastrigin function
Rastrigin operator
Return the version number of the torch optimizer
Compute objective function
Test the model
Train model
Prepare data loader
Compute the Rastrigin objective function

Get all kandi verified functions for this library.

pytorch-optimizer Key Features

No Key Features are available at this moment for pytorch-optimizer.

pytorch-optimizer Examples and Code Snippets

Using nmtlab in Python

Python

Lines of Code : 85

License : Permissive (MIT)

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from torch import optim

from nmtlab import MTTrainer, MTDataset
from nmtlab.models import RNMTPlusModel
from nmtlab.schedulers import AnnealScheduler
from nmtlab.decoding import BeamTranslator
from nmtlab.evaluation.moses_bleu import MosesBLEUEvalua

Bayesian Gradient Descent (BGD) - Task Agnostic Continual Learning,Using BGD PyTorch optimizer

Python

Lines of Code : 9

License : Permissive (MIT)

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For samples, labels in data:
    for mc_iter in range(mc_iters):
        bgd_optimizer.randomize_weights()
        output = model.forward(samples)
        loss = cirterion(output, labels)
        bgd_optimizer.zero_grad()
        loss.backward()

Run Pytorch optimizer

C++

Lines of Code : 6

License : No License

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cd build
export PYTHONPATH=$PYTHONPATH:$(pwd)

python ../src/python/rigid_deform.py --source ../data/source.obj --target ../data/target.obj --output ./rigid_output.obj

python ../src/python/cad_deform2.py --source ../data/cad-source.obj --target ../d

Community Discussions

Trending Discussions on pytorch-optimizer

PyTorch optimizer.step() doesn't update weights when I use "if statement" like function

QUESTION

PyTorch optimizer.step() doesn't update weights when I use "if statement" like function

Asked 2021-Apr-20 at 13:40

My model needs to learn certain parameters to solve this function:

...

ANSWER

Answered 2021-Apr-20 at 13:40

As the others have mentioned, we need to make an approximation of the noncontinuous function. How about this?

Source https://stackoverflow.com/questions/67172032

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

Vulnerabilities

No vulnerabilities reported

Install pytorch-optimizer

You can install using 'pip install pytorch-optimizer' or download it from GitHub, PyPI.
You can use pytorch-optimizer 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 .

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