import torch


# https://github.com/leigh-plt/cs231n_hw2018/blob/master/assignment2/pytorch_tutorial.ipynb
def save_checkpoint(checkpoint_path, model, optimizer):
    state = {'state_dict': model.state_dict(),
             'optimizer': optimizer.state_dict()}
    torch.save(state, checkpoint_path)
    print('model saved to %s' % checkpoint_path)


def load_checkpoint(checkpoint_path, model, optimizer):
    state = torch.load(checkpoint_path)
    model.load_state_dict(state['state_dict'])
    optimizer.load_state_dict(state['optimizer'])
    print('model loaded from %s' % checkpoint_path)

import torch


# https://github.com/leigh-plt/cs231n_hw2018/blob/master/assignment2/pytorch_tutorial.ipynb
def save_checkpoint(checkpoint_path, model, optimizer):
    state = {'state_dict': model.state_dict(),
             'optimizer': optimizer.state_dict()}
    torch.save(state, checkpoint_path)
    print('model saved to %s' % checkpoint_path)


def load_checkpoint(checkpoint_path, model, optimizer):
    state = torch.load(checkpoint_path)
    model.load_state_dict(state['state_dict'])
    optimizer.load_state_dict(state['optimizer'])
    print('model loaded from %s' % checkpoint_path)

# https://github.com/leigh-plt/cs231n_hw2018/blob/master/assignment2/pytorch_tutorial.ipynb