| import os |
| import torch |
| import statistics |
|
|
|
|
| def save_args(args, fn): |
| with open(fn, 'w') as f: |
| for k, v in args.__dict__.items(): |
| f.write("{},{}\n".format(k, v)) |
| print("saved args:", args) |
|
|
|
|
| def summary_report(val_list): |
| return sum(val_list)/len(val_list), statistics.stdev(val_list) if len(val_list) > 1 else 0 |
|
|
|
|
| def create_checkpoint(checkpoint_fn, epoch, model, optimizer, results): |
| checkpoint = {"epoch": epoch, |
| "model": model.state_dict(), |
| "optimizer": optimizer.state_dict(), |
| "results": results} |
| torch.save(checkpoint, checkpoint_fn) |
|
|
|
|
| def remove_checkpoint(checkpoint_fn): |
| os.remove(checkpoint_fn) |
|
|
|
|
| def load_checkpoint(checkpoint_fn, model, optimizer): |
| checkpoint = torch.load(checkpoint_fn) |
| model.load_state_dict(checkpoint['model']) |
| optimizer.load_state_dict(checkpoint['optimizer']) |
|
|
| return checkpoint['results'], checkpoint['epoch'], model, optimizer |
|
|
|
|
| def load_checkpoint_results(checkpoint_fn): |
| checkpoint = torch.load(checkpoint_fn) |
| return checkpoint['results'] |
|
|
|
|
