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The torchgan package consists of various generative adversarial networks and utilities that have been found useful in training them. This package provides an easy-to-use API which can be used to train popular GANs as well as develop newer variants. The core idea behind this project is to facilitate easy and rapid generative adversarial model research. TorchGAN is a Pytorch-based framework for designing and developing Generative Adversarial Networks. This framework has been designed to provide building blocks for popular GANs and also to allow customization for cutting-edge research. Using TorchGAN's modular structure allows.
Features
- Trying out popular GAN models on your dataset
- Plug in your new Loss Function, new Architecture, etc. with the traditional ones
- Seamlessly visualize the training with a variety of logging backends
- The documentation for this package can be generated locally
- This software was developed as part of academic research
- Provides tutorials
Project Samples
License
MIT LicenseFollow TorchGAN
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