GAN- code to achieve data
Since 2014 GAN an article posted online appeared in a wide variety of variants of GAN. Original network structure: D and G are multi-layer perceptron , but did not find the specific code implementation. The following tutorial finishing with the most basic of code four GAN architecture implementation.
1.pytorch Tutorial
pytorch tutorial has DGGAN example code, mainly dealing with people face generation problems. Tutorial English, English comments in the code, G, and D with depth convolutional neural network structures.
Official website tutorial:
https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html
GitHub Information:
https://github.com/pytorch/tutorials/blob/master/beginner_source/dcgan_faces_tutorial.py
https://github.com/ pytorch / examples / blob / master / dcgan
2. Jane tutorial book
After Mo trouble Jane book tutorial (always good), the main achievement given bounds, curve generation problem. Chinese guides, curve fitting is relatively simple, with two layers of structures G and D. Sensor
https://morvanzhou.github.io/tutorials/machine-learning/torch/4-06-GAN/
HTTPS: // GitHub. com / MorvanZhou / PyTorch-Tutorial / blob / master / tutorial-contents / 406_GAN.py
3.CSDN blog
CSDN blog, handwritten numbers generated code. Britain mixed tutorial image tags, D, and G are used to build a multilayer perceptron.
https://blog.csdn.net/IAMoldpan/article/details/78711426
4.pytorch Chinese Documents
tutorial pytorch Chinese document. Code for generating handwritten figures, Chinese tutorial image tags, D, and G are used to build a multilayer perceptron. 3 and 4 of the structure is slightly different, but when entering data, certainly have to first become vector images can be entered.
https://ptorch.com/news/14.html