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				|  | @ -354,7 +354,13 @@ def convert(cfg='cfg/yolov3-spp.cfg', weights='weights/yolov3-spp.weights'): | |||
| 
 | ||||
|     elif weights.endswith('.weights'):  # darknet format | ||||
|         _ = load_darknet_weights(model, weights) | ||||
|         chkpt = {'epoch': -1, 'best_loss': None, 'model': model.state_dict(), 'optimizer': None} | ||||
| 
 | ||||
|         chkpt = {'epoch': -1, | ||||
|                  'best_fitness': None, | ||||
|                  'training_results': None, | ||||
|                  'model': model.state_dict(), | ||||
|                  'optimizer': None} | ||||
| 
 | ||||
|         torch.save(chkpt, 'converted.pt') | ||||
|         print("Success: converted '%s' to 'converted.pt'" % weights) | ||||
| 
 | ||||
|  |  | |||
							
								
								
									
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							|  | @ -81,6 +81,7 @@ def train( | |||
|             optimizer.load_state_dict(chkpt['optimizer']) | ||||
|             best_fitness = chkpt['best_fitness'] | ||||
| 
 | ||||
|         if chkpt['training_results'] is not None: | ||||
|             with open('results.txt', 'w') as file: | ||||
|                 file.write(chkpt['training_results'])  # write results.txt | ||||
| 
 | ||||
|  | @ -251,7 +252,7 @@ def train( | |||
|             best_fitness = fitness | ||||
| 
 | ||||
|         # Save training results | ||||
|         save = (not opt.nosave) or (epoch == epochs - 1) | ||||
|         save = (not opt.nosave) or ((not opt.evolve) and (epoch == epochs - 1)) | ||||
|         if save: | ||||
|             with open('results.txt', 'r') as file: | ||||
|                 # Create checkpoint | ||||
|  |  | |||
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