This pages lists various PyTorch examples that you can use to learn and experiment with PyTorch.
Generative Adversarial Networks (DCGAN)
This example implements the Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks paper.
Super-resolution Using an Efficient Sub-Pixel CNN
This example demonstrates how to use the sub-pixel convolution layer described in Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network paper. This example trains a super-resolution network on the BSD300 dataset.
Time Sequence Prediction
This beginner example demonstrates how to use LSTMCell to learn sine wave signals to predict the signal values in the future.
The PyTorch C++ frontend is a C++14 library for CPU and GPU tensor computation. This set of examples includes a linear regression, autograd, image recognition (MNIST), and other examples using PyTorch C++ frontend.