Run the following command to install additional dependencies
pip install -r requirements.txt
Training and validating your model
Run the script main.py to train your model.
Modify main.py, model.py and data.py for your assignment, with an aim to make the validation score better.
By default the images are loaded and resized to 32x32 pixels and normalized to zero-mean and standard deviation of 1. See data.py for the data_transforms.
By default a validation set is split for you from the training set and put in [datadir]/val_images. See data.py on how this is done.
Evaluating your model on the test set
As the model trains, model checkpoints are saved to files such as model_x.pth to the current working directory. You can take one of the checkpoints and run: