def _load_checkpoint()

in pytorch_managed_spot_training_checkpointing/source_dir/cifar10.py [0:0]

• 13 lines of code
• 1 McCabe index (conditional complexity)

def _load_checkpoint(model, optimizer, args):
    print("--------------------------------------------")
    print("Checkpoint file found!")
    print("Loading Checkpoint From: {}".format(args.checkpoint_path + '/checkpoint.pth'))
    checkpoint = torch.load(args.checkpoint_path + '/checkpoint.pth')
    model.load_state_dict(checkpoint['model_state_dict'])
    optimizer.load_state_dict(checkpoint['optimizer_state_dict'])
    epoch_number = checkpoint['epoch']
    loss = checkpoint['loss']
    print("Checkpoint File Loaded - epoch_number: {} - loss: {}".format(epoch_number, loss))
    print('Resuming training from epoch: {}'.format(epoch_number+1))
    print("--------------------------------------------")
    return model, optimizer, epoch_number