style-based-gan-pytorch | Based Generator Architecture for Generative Adversarial | Machine Learning library

by rosinality Python Version: Current License: Non-SPDX

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

kandi X-RAY | style-based-gan-pytorch Summary

style-based-gan-pytorch is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Generative adversarial networks applications. style-based-gan-pytorch has no bugs, it has no vulnerabilities and it has medium support. However style-based-gan-pytorch build file is not available and it has a Non-SPDX License. You can download it from GitHub.

Implementation A Style-Based Generator Architecture for Generative Adversarial Networks in PyTorch

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Security

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style-based-gan-pytorch has a medium active ecosystem.

It has 1032 star(s) with 225 fork(s). There are 22 watchers for this library.

It had no major release in the last 6 months.

There are 71 open issues and 48 have been closed. On average issues are closed in 18 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of style-based-gan-pytorch is current.

Quality

style-based-gan-pytorch has 0 bugs and 9 code smells.

Security

style-based-gan-pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

style-based-gan-pytorch code analysis shows 0 unresolved vulnerabilities.

There are 2 security hotspots that need review.

License

style-based-gan-pytorch has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

style-based-gan-pytorch releases are not available. You will need to build from source code and install.

style-based-gan-pytorch has no build file. You will be need to create the build yourself to build the component from source.

style-based-gan-pytorch saves you 348 person hours of effort in developing the same functionality from scratch.

It has 833 lines of code, 56 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 style-based-gan-pytorch and discovered the below as its top functions. This is intended to give you an instant insight into style-based-gan-pytorch implemented functionality, and help decide if they suit your requirements.

Train model
Calculate the difference between two models
Sample data from dataset
Adjust the lr of the optimizer
Apply style mixing between source and target images
Regularize noise
Convert a numpy array to RGB
Convert an image into torch tensor
Prepare image files
Calculate mean style
Compute the mean of the input array
Convert a tensor to a lab
Convert a tensor image to an image
Predict from the generator
Calculate the mean style
Sample generator
Make an image
Make noise
Wrapper for resize_multiple
Calculate learning rate based on time t
Normalize noise
Run optimizer
BlurFunction backward
Save the network to disk
Apply equallr to module
Calculate the noise

Get all kandi verified functions for this library.

style-based-gan-pytorch Key Features

No Key Features are available at this moment for style-based-gan-pytorch.

style-based-gan-pytorch Examples and Code Snippets

GAN in Pytorch

Python

Lines of Code : 28

License : Permissive (Apache-2.0)

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$ cd gan
$ python train.py
$ python infer.py

$ cd wgan
$ python train.py
$ python infer.py

$ cd wgan-gp
$ python train.py
$ python infer.py

$ cd dcgan
$ python train.py
$ python infer.py

$ cd cgan
$ python train.py
$ python infer.py

$ cd context

Conditional Generative Adversarial Networks,Usage

Python

Lines of Code : 23

License : No License

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usage: main.py [-h] --dataset DATASET --dataroot DATAROOT 
               [--batchSize BATCHSIZE] [--imageSize IMAGESIZE] [--channels CHANNELS]
               [--latentdim LATENDIM] [--n_classes N_CLASSES] [--epoch EPOCH] [--lrte LRATE]

PyTorch-Linear-GAN

Jupyter Notebook

Lines of Code : 17

License : No License

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usage: main.py [-h] [--epochs EPOCHS] [--lr LR] [--batch_size BATCH] [--beta1 BETA1] [--beta2 BETA2] [--print_every EVERY] 
[--sample_size SIZE] [--plot_every EVERY] [--model_save_path PATH] [--custom_image_path PATH] [--image_size SIZE] [--z_size Z_

Community Discussions

Trending Discussions on style-based-gan-pytorch

How to fix 'RuntimeError: Address already in use' in PyTorch?

QUESTION

How to fix 'RuntimeError: Address already in use' in PyTorch?

Asked 2019-Aug-29 at 06:34

I am trying to run a distributive application with PyTorch distributive trainer. I thought I would first try the example they have, found here. I set up two AWS EC2 instances and configured them according to the description in the link, but when I try to run the code I get two different errors: in the first terminal window for node0 I get the error message: RuntimeError: Address already in use

Under the other three windows I get the same error message:

RuntimeError: NCCL error in: /pytorch/torch/lib/c10d/ProcessGroupNCCL.cpp:272, unhandled system error

I followed the code in the link, and terminated the instances an redid but it didn't help/

This is using python 3.6 with the nightly build Cuda 9.0. I tried changing the MASTER_ADDR to the ip for node0 on both nodes, as well as using the same MASTER_PORT (which is an available, unused port). However I still get the same error message.

After running this, my goal is to the adjust this StyleGan implementation so that I can train it across multiple GPUs in two different nodes.

...

ANSWER

Answered 2019-Aug-29 at 06:34

So after a lot of failed attempts I found out what the problem is. Note that this solution applies to using ASW deep learning instances.

After creating two instances I had to adjust the security group. Add two rules: The first rule should be ALL_TCP, and set the source to the Private IPs of the leader. The second rule should be the same (ALL_TCP), but with the source as the Private IPs of the slave node.

Previously, I had the setting security rule set as: Type SSH, which only had a single available port (22). For some reason I was not able to use this port to allow the nodes to communicate. After changing these settings the code worked fine. I was also able to run this with the above mentioned settings.

Source https://stackoverflow.com/questions/57624739

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

Vulnerabilities

No vulnerabilities reported

Install style-based-gan-pytorch

You can download it from GitHub.
You can use style-based-gan-pytorch 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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