Resuming Training From a Checkpoint

def save_checkpoint(model, optimizer, epoch, path):
    torch.save({
        'model': model.state_dict(),
        'optimizer': optimizer.state_dict(),
        'epoch': epoch,
    }, path)

def resume(model, optimizer, path):
    ckpt = torch.load(path)
    model.load_state_dict(ckpt['model'])
    optimizer.load_state_dict(ckpt['optimizer'])
    start_epoch = 0
    return start_epoch