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Pytorch-Tutorial

Pytorch tutorial with jupyter notebook

Installing prerequisites

How to run this tutorial

  1. Clone this repository to any folder.
  2. Open your favorite shell, and cd to that folder.
  3. Run jupyter notebook
  4. Shift+Enter through each notebook and cell.

Table of Contents

  1. Tensors and Dynamic Graphs
    • Basic Operations involving torch.Tensor
    • Introduction to the dynamic computational graphs of torch.Autograd
  2. Modules and Custom Models
    • Adding predefined modules from torch.nn to torch.nn.Sequential
    • Creating custom models by inheriting torch.nn.Module
  3. Training and Evaluating a Model
    • General training setup for cpu or cuda
    • Managing and loading predefined/custom datasets
    • Experiencing the conventions of training and evaluating (actually train a CNN on MNIST to accuracy 96%)
  4. Saving and Loading Model States
    • Using predefined models in torchvision.models
    • Saving and loading model/optimizer parameters