pytorch-land for happy deep learning
Project description
PyTorch Land
This is a repository of select implementations of deep learning models using pytorch.
There is also my own mini-framework for model training
(which I call simply NetworkTrainer
), that ended up with
something very similar to ignite,
created in order to reduce common boilerplating.
More flexible and intuitive than ignite, in my opinion :).
More models to be added, and improvements on NetworkTrainer
is under way.
Installation
pip3 install pytorch-land
See pypi page for package details.
Implemented Models
CNN architectures
GANs
- GAN (2014) [paper] [code]
- DCGAN (2015) [paper] [code]
- InfoGAN (2016) [paper] [code]
- f-GAN (2016) [paper] [code]
- UnrolledGAN (2016) [paper] [code] [train-examples]
- ACGAN (2016) [paper] [code] [train-examples]
- BEGAN (2017) [paper] [code & examples]
- CycleGAN (2017) [paper] [code & examples]
Autoencoders
- Stacked Denoising Autoencoders [paper] [code]
- Stacked Convolutional Denoising Autoencoders (2017) [paper] [code]
Requirements
Required packages are specified in requirements.txt file. The packages can be installed using the following command:
pip3 install -r requirements.txt
Notably, the codes are compatible with pytorch 0.4 - working on with pytorch 1.1 compatibility.
NetworkTrainer
Datasets
Project details
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