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Geant4/examples/extended/parameterisations/Par04/training/tune_model.py

Version: [ ReleaseNotes ] [ 1.0 ] [ 1.1 ] [ 2.0 ] [ 3.0 ] [ 3.1 ] [ 3.2 ] [ 4.0 ] [ 4.0.p1 ] [ 4.0.p2 ] [ 4.1 ] [ 4.1.p1 ] [ 5.0 ] [ 5.0.p1 ] [ 5.1 ] [ 5.1.p1 ] [ 5.2 ] [ 5.2.p1 ] [ 5.2.p2 ] [ 6.0 ] [ 6.0.p1 ] [ 6.1 ] [ 6.2 ] [ 6.2.p1 ] [ 6.2.p2 ] [ 7.0 ] [ 7.0.p1 ] [ 7.1 ] [ 7.1.p1 ] [ 8.0 ] [ 8.0.p1 ] [ 8.1 ] [ 8.1.p1 ] [ 8.1.p2 ] [ 8.2 ] [ 8.2.p1 ] [ 8.3 ] [ 8.3.p1 ] [ 8.3.p2 ] [ 9.0 ] [ 9.0.p1 ] [ 9.0.p2 ] [ 9.1 ] [ 9.1.p1 ] [ 9.1.p2 ] [ 9.1.p3 ] [ 9.2 ] [ 9.2.p1 ] [ 9.2.p2 ] [ 9.2.p3 ] [ 9.2.p4 ] [ 9.3 ] [ 9.3.p1 ] [ 9.3.p2 ] [ 9.4 ] [ 9.4.p1 ] [ 9.4.p2 ] [ 9.4.p3 ] [ 9.4.p4 ] [ 9.5 ] [ 9.5.p1 ] [ 9.5.p2 ] [ 9.6 ] [ 9.6.p1 ] [ 9.6.p2 ] [ 9.6.p3 ] [ 9.6.p4 ] [ 10.0 ] [ 10.0.p1 ] [ 10.0.p2 ] [ 10.0.p3 ] [ 10.0.p4 ] [ 10.1 ] [ 10.1.p1 ] [ 10.1.p2 ] [ 10.1.p3 ] [ 10.2 ] [ 10.2.p1 ] [ 10.2.p2 ] [ 10.2.p3 ] [ 10.3 ] [ 10.3.p1 ] [ 10.3.p2 ] [ 10.3.p3 ] [ 10.4 ] [ 10.4.p1 ] [ 10.4.p2 ] [ 10.4.p3 ] [ 10.5 ] [ 10.5.p1 ] [ 10.6 ] [ 10.6.p1 ] [ 10.6.p2 ] [ 10.6.p3 ] [ 10.7 ] [ 10.7.p1 ] [ 10.7.p2 ] [ 10.7.p3 ] [ 10.7.p4 ] [ 11.0 ] [ 11.0.p1 ] [ 11.0.p2 ] [ 11.0.p3, ] [ 11.0.p4 ] [ 11.1 ] [ 11.1.1 ] [ 11.1.2 ] [ 11.1.3 ] [ 11.2 ] [ 11.2.1 ] [ 11.2.2 ] [ 11.3.0 ]

Diff markup

Differences between /examples/extended/parameterisations/Par04/training/tune_model.py (Version 11.3.0) and /examples/extended/parameterisations/Par04/training/tune_model.py (Version 10.6.p1)


  1 from argparse import ArgumentParser               
  2                                                   
  3 from core.constants import MAX_GPU_MEMORY_ALLO    
  4 from utils.gpu_limiter import GPULimiter          
  5 from utils.optimizer import OptimizerType         
  6                                                   
  7 # Hyperparemeters to be optimized.                
  8 discrete_parameters = {"nb_hidden_layers": (1,    
  9 continuous_parameters = {"learning_rate": (0.0    
 10 categorical_parameters = {"optimizer_type": [O    
 11                                                   
 12                                                   
 13 def parse_args():                                 
 14     argument_parser = ArgumentParser()            
 15     argument_parser.add_argument("--study-name    
 16     argument_parser.add_argument("--storage",     
 17     argument_parser.add_argument("--max-gpu-me    
 18     argument_parser.add_argument("--gpu-ids",     
 19     args = argument_parser.parse_args()           
 20     return args                                   
 21                                                   
 22                                                   
 23 def main():                                       
 24     # 0. Parse arguments.                         
 25     args = parse_args()                           
 26     study_name = args.study_name                  
 27     storage = args.storage                        
 28     max_gpu_memory_allocation = args.max_gpu_m    
 29     gpu_ids = args.gpu_ids                        
 30                                                   
 31     # 1. Set GPU memory limits.                   
 32     GPULimiter(_gpu_ids=gpu_ids, _max_gpu_memo    
 33                                                   
 34     # 2. Manufacture hyperparameter tuner.        
 35                                                   
 36     # This import must be local because otherw    
 37     from utils.hyperparameter_tuner import Hyp    
 38     hyperparameter_tuner = HyperparameterTuner    
 39                                                   
 40                                                   
 41     # 3. Run main tuning function.                
 42     hyperparameter_tuner.tune()                   
 43     # Watch out! This script neither deletes t    
 44     # parallelized optimization, then you shou    
 45                                                   
 46                                                   
 47 if __name__ == "__main__":                        
 48     exit(main())