updates
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							|  | @ -366,8 +366,8 @@ def train(): | ||||||
|     # end training |     # end training | ||||||
|     if len(opt.name) and not opt.prebias: |     if len(opt.name) and not opt.prebias: | ||||||
|         os.rename('results.txt', 'results_%s.txt' % opt.name) |         os.rename('results.txt', 'results_%s.txt' % opt.name) | ||||||
|         os.rename(wdir + 'best.pt', wdir + 'best_%s.pt' % opt.name) |  | ||||||
|         os.rename(wdir + 'last.pt', wdir + 'last_%s.pt' % opt.name) |         os.rename(wdir + 'last.pt', wdir + 'last_%s.pt' % opt.name) | ||||||
|  |         os.rename(wdir + 'best.pt', wdir + 'best_%s.pt' % opt.name) if os.path.exists(wdir + 'best.pt') else None | ||||||
|     plot_results()  # save as results.png |     plot_results()  # save as results.png | ||||||
|     print('%g epochs completed in %.3f hours.\n' % (epoch - start_epoch + 1, (time.time() - t0) / 3600)) |     print('%g epochs completed in %.3f hours.\n' % (epoch - start_epoch + 1, (time.time() - t0) / 3600)) | ||||||
|     dist.destroy_process_group() if torch.cuda.device_count() > 1 else None |     dist.destroy_process_group() if torch.cuda.device_count() > 1 else None | ||||||
|  |  | ||||||
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