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  1. (main_env) workstation ➜  ishaan git:(master) ✗ python mnist_ada.py --lr_g=0.0 --dataset_size=500000
  2. Flags:
  3.     batch_size: 1024
  4.     conditional_ada: False
  5.     dataset_size: 500000
  6.     env_vals: [0.8, 0.9]
  7.     iters: 1000000
  8.     lr_d: 0.0001
  9.     lr_g: 0.0
  10.     mnist_train_size: 50000
  11.     no_cuda: False
  12.     print_every: 1000
  13.     test_env_val: 0.1
  14.     test_on_train: False
  15.     wrong_image_prob: 0.25
  16. Making dataset (env_val=0.8, size=500000)
  17. Making dataset (env_val=0.9, size=500000)
  18. Making dataset (env_val=0.1, size=50000)
  19. step           env0_loss      env1_loss      test_loss      env0_acc       env1_acc       test_acc       disc_loss      g_loss         time_iter  
  20. 0              0.69109        0.69118        0.70515        0.52148        0.51953        0.45158        1.38854        -1.38163       0.13770    
  21. 1000           0.69095        0.68944        0.70515        0.52159        0.52871        0.45158        1.38472        -1.37782       0.01739    
  22. 2000           0.69087        0.68966        0.70515        0.52247        0.52727        0.45158        1.38352        -1.37661       0.02061    
  23. 3000           0.69099        0.68953        0.70515        0.52131        0.52819        0.45158        1.38293        -1.37603       0.02077    
  24. 4000           0.69102        0.68965        0.70515        0.52111        0.52696        0.45158        1.38207        -1.37516       0.01759
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