21-03-31 00:41:35.097 - INFO:   name: 4x_UniversalUpscalerV2-Neutral
  use_tb_logger: True
  model: srragan
  scale: 4
  gpu_ids: [0]
  use_amp: True
  use_swa: True
  datasets:[
    train:[
      name: DIV2K
      mode: LRHRC
      dataroot_HR: ['..\\datasets\\train\\hr\\hrRealism\\Original', '..\\datasets\\train\\hr\\hrRealism\\Point']
      dataroot_LR: ['..\\datasets\\train\\lr\\lrUniversal\\lrBox', '..\\datasets\\train\\lr\\lrUniversal\\lrPoint']
      subset_file: None
      use_shuffle: True
      znorm: False
      n_workers: 4
      batch_size: 4
      virtual_batch_size: 4
      HR_size: 128
      image_channels: 3
      dataroot_kernels: ../training/kernels/results/
      lr_downscale: True
      lr_downscale_types: [1, 2, 777]
      use_flip: True
      use_rot: True
      hr_rrot: False
      lr_blur: False
      lr_blur_types: ['gaussian', 'clean', 'clean', 'clean']
      noise_data: ../noise_patches/normal/
      lr_noise: False
      lr_noise_types: ['JPEG', 'clean', 'clean', 'clean', 'clean']
      lr_noise2: False
      lr_noise_types2: ['dither', 'dither', 'clean', 'clean']
      hr_noise: False
      hr_noise_types: ['gaussian', 'clean', 'clean', 'clean', 'clean']
      phase: train
      scale: 4
      data_type: img
    ]
    val:[
      name: val_images
      mode: LRHROTF
      dataroot_HR: ..\datasets\val\hr\hrUniversal
      dataroot_LR: ..\datasets\val\lr\lrUniversal\Neutral
      znorm: False
      lr_downscale: False
      lr_downscale_types: [1, 2]
      phase: val
      scale: 4
      data_type: img
    ]
  ]
  path:[
    strict: False
    root: C:\nn\BasicSR
    pretrain_model_G: ..\experiments\pretrained_models\RRDB_ESRGAN_x4.pth
    resume_state: ..\experiments\4x_UniversalUpscalerV2-Neutral\training_state\112000.state
    experiments_root: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral
    models: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\models
    training_state: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\training_state
    log: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral
    val_images: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\val_images
  ]
  network_G:[
    strict: False
    which_model_G: RRDB_net
    norm_type: None
    mode: CNA
    nf: 64
    nb: 23
    nr: 3
    in_nc: 3
    out_nc: 3
    gc: 32
    group: 1
    convtype: Conv2D
    net_act: leakyrelu
    gaussian: True
    plus: False
    scale: 4
  ]
  network_D:[
    strict: True
    which_model_D: multiscale
    norm_type: batch
    act_type: leakyrelu
    mode: CNA
    nf: 64
    in_nc: 3
    nlayer: 3
    num_D: 3
  ]
  train:[
    lr_G: 0.0001
    weight_decay_G: 0
    beta1_G: 0.9
    lr_D: 0.0001
    weight_decay_D: 0
    beta1_D: 0.9
    lr_scheme: MultiStepLR
    lr_gamma: 0.5
    swa_start_iter: 70000
    swa_lr: 0.0001
    swa_anneal_epochs: 10
    swa_anneal_strategy: cos
    pixel_criterion: l1
    pixel_weight: 0.1
    cx_weight: 0.5
    cx_type: contextual
    cx_vgg_layers:[
      conv_3_2: 1
      conv_3_1: 1
      conv_4_2: 1
      conv_4_1: 1
      conv_5_2: 1
      conv_5_1: 1
    ]
    ssim_type: ms-ssim
    ssim_weight: 1
    gan_type: vanilla
    gan_weight: 0.009
    manual_seed: 0
    niter: 500000.0
    val_freq: 1000
    metrics: psnr,ssim,lpips
    overwrite_val_imgs: None
    val_comparison: None
    lr_steps: [50000, 100000, 200000, 300000]
  ]
  logger:[
    print_freq: 200
    save_checkpoint_freq: 1000
    overwrite_chkp: False
  ]
  is_train: True

21-03-31 00:41:35.200 - INFO: Random seed: 0
21-03-31 00:41:36.716 - INFO: Set [resume_state] to ..\experiments\4x_UniversalUpscalerV2-Neutral\training_state\112000.state
21-03-31 00:41:36.716 - INFO: Resuming training from epoch: 956, iter: 112000.
21-03-31 00:41:36.716 - WARNING: pretrain_model paths will be ignored when resuming training from a .state file.
21-03-31 00:41:36.716 - INFO: Set [pretrain_model_G] to C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\models\112000_G.pth
21-03-31 00:41:36.716 - INFO: Set [pretrain_model_D] to C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\models\112000_D.pth
21-03-31 00:41:36.734 - INFO: Dataset [LRHRDataset - DIV2K] is created.
21-03-31 00:41:36.734 - INFO: Number of train images: 470, iters: 118
21-03-31 00:41:36.735 - INFO: Total epochs needed: 4238 for iters 500,000
21-03-31 00:41:36.735 - INFO: Dataset [LRHRDataset - val_images] is created.
21-03-31 00:41:36.735 - INFO: Number of val images in [val_images]: 3
21-03-31 00:41:37.012 - INFO: AMP library available
21-03-31 00:41:37.143 - INFO: Initialization method [kaiming]
21-03-31 00:41:37.353 - INFO: Initialization method [kaiming]
21-03-31 00:41:37.409 - INFO: Loading pretrained model for G [C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\models\112000_G.pth] ...
21-03-31 00:41:37.649 - INFO: Loading pretrained model for D [C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\models\112000_D.pth] ...
21-03-31 00:41:38.673 - INFO: SWA enabled. Starting on iter: 70000, lr: 0.0001
21-03-31 00:41:38.675 - INFO: AMP enabled
21-03-31 00:41:38.684 - INFO: Network G structure: DataParallel - RRDBNet, with parameters: 16,697,987
21-03-31 00:41:38.685 - INFO: Network D structure: DataParallel - MultiscaleDiscriminator, with parameters: 8,296,899
21-03-31 00:41:38.685 - INFO: Model [SRRaGANModel] is created.
21-03-31 00:41:38.766 - INFO: Start training from epoch: 956, iter: 112000
21-03-31 00:42:50.337 - INFO: End of epoch 956 / 4238 	 Time Taken: 71.5706 sec
21-03-31 00:43:48.472 - INFO: <epoch:957, iter: 112,200, lr:1.000e-04, t:-1.0000s, td:0.0365s, eta:0.0000h> pix-l1: 2.7462e-03 contextual: 4.6543e+00 l_g_gan: 1.7021e-01 ms-ssim: 9.1447e-02 l_d_real: 4.4154e-01 l_d_fake: 4.4055e-01 D_real: 1.2344e+01 D_fake: -5.8643e-01 
21-03-31 00:44:11.223 - INFO: End of epoch 957 / 4238 	 Time Taken: 80.8861 sec
21-03-31 00:45:31.848 - INFO: End of epoch 958 / 4238 	 Time Taken: 80.6250 sec
21-03-31 00:46:07.679 - INFO: <epoch:959, iter: 112,400, lr:1.000e-04, t:-1.0000s, td:0.0371s, eta:0.0000h> pix-l1: 4.3990e-03 contextual: 3.7370e+00 l_g_gan: 1.3807e-01 ms-ssim: 7.9429e-02 l_d_real: 3.7589e-01 l_d_fake: 3.7934e-01 D_real: -2.2031e+00 D_fake: -1.1148e+01 
21-03-31 00:46:52.641 - INFO: End of epoch 959 / 4238 	 Time Taken: 80.7930 sec
21-03-31 00:48:11.601 - INFO: End of epoch 960 / 4238 	 Time Taken: 78.9601 sec
21-03-31 00:48:22.870 - INFO: <epoch:961, iter: 112,600, lr:1.000e-04, t:139.2078s, td:0.0366s, eta:14980.3069h> pix-l1: 7.0772e-03 contextual: 4.6113e+00 l_g_gan: 4.3736e-02 ms-ssim: 1.2085e-01 l_d_real: 1.6328e+00 l_d_fake: 1.6297e+00 D_real: 4.7031e+00 D_fake: 1.4570e+00 
21-03-31 00:49:16.002 - INFO: End of epoch 961 / 4238 	 Time Taken: 64.4010 sec
21-03-31 00:50:10.217 - INFO: <epoch:962, iter: 112,800, lr:1.000e-04, t:135.1907s, td:0.0180s, eta:14540.5115h> pix-l1: 3.5628e-03 contextual: 3.2906e+00 l_g_gan: 1.4167e-01 ms-ssim: 5.3947e-02 l_d_real: 2.6047e-01 l_d_fake: 2.6046e-01 D_real: -6.6680e+00 D_fake: -1.5773e+01 
21-03-31 00:50:20.307 - INFO: End of epoch 962 / 4238 	 Time Taken: 64.3044 sec
21-03-31 00:51:24.767 - INFO: End of epoch 963 / 4238 	 Time Taken: 64.4600 sec
21-03-31 00:52:01.484 - INFO: <epoch:964, iter: 113,000, lr:1.000e-04, t:107.3469s, td:0.0362s, eta:11539.7926h> pix-l1: 2.5078e-03 contextual: 2.1749e+00 l_g_gan: 3.1561e-02 ms-ssim: 3.0721e-02 l_d_real: 2.0302e+00 l_d_fake: 2.0325e+00 D_real: -1.0172e+01 D_fake: -1.2508e+01 
21-03-31 00:52:02.335 - INFO: Models and training states saved.
21-03-31 00:52:10.432 - INFO: # Validation # PSNR: 29.774, SSIM: 0.808, LPIPS: 0.058653
21-03-31 00:52:10.433 - INFO: <epoch:964, iter: 113,000> PSNR: 29.774, SSIM: 0.808, LPIPS: 0.058653
21-03-31 00:52:38.581 - INFO: End of epoch 964 / 4238 	 Time Taken: 73.8133 sec
21-03-31 00:53:44.420 - INFO: End of epoch 965 / 4238 	 Time Taken: 65.8385 sec
21-03-31 00:54:03.824 - INFO: <epoch:966, iter: 113,200, lr:1.000e-04, t:111.2671s, td:0.0362s, eta:11955.0309h> pix-l1: 5.4623e-03 contextual: 4.3148e+00 l_g_gan: 1.8007e-01 ms-ssim: 8.7078e-02 l_d_real: 6.2411e-01 l_d_fake: 6.2331e-01 D_real: 5.7500e+00 D_fake: -4.4844e+00 
21-03-31 00:54:50.501 - INFO: End of epoch 966 / 4238 	 Time Taken: 66.0809 sec
21-03-31 00:55:55.325 - INFO: <epoch:967, iter: 113,400, lr:1.000e-04, t:122.3397s, td:0.0187s, eta:13137.9235h> pix-l1: 3.0308e-03 contextual: 3.3030e+00 l_g_gan: 9.1658e-02 ms-ssim: 5.0770e-02 l_d_real: 6.3275e-01 l_d_fake: 6.3530e-01 D_real: -1.2627e+00 D_fake: -5.1875e+00 
21-03-31 00:55:57.752 - INFO: End of epoch 967 / 4238 	 Time Taken: 67.2507 sec
21-03-31 00:57:03.392 - INFO: End of epoch 968 / 4238 	 Time Taken: 65.6391 sec
21-03-31 00:57:48.736 - INFO: <epoch:969, iter: 113,600, lr:1.000e-04, t:111.5011s, td:0.0361s, eta:11967.7849h> pix-l1: 6.1939e-03 contextual: 4.9985e+00 l_g_gan: 1.0783e-01 ms-ssim: 1.2970e-01 l_d_real: 2.5266e-01 l_d_fake: 2.5311e-01 D_real: 8.3359e+00 D_fake: 1.6318e+00 
21-03-31 00:58:09.107 - INFO: End of epoch 969 / 4238 	 Time Taken: 65.7147 sec
21-03-31 00:59:14.618 - INFO: End of epoch 970 / 4238 	 Time Taken: 65.5109 sec
21-03-31 00:59:41.888 - INFO: <epoch:971, iter: 113,800, lr:1.000e-04, t:113.4111s, td:0.0360s, eta:12166.4896h> pix-l1: 9.5749e-04 contextual: 3.4017e+00 l_g_gan: 8.2276e-02 ms-ssim: 1.4097e-02 l_d_real: 6.6051e-01 l_d_fake: 6.5912e-01 D_real: 1.6836e+00 D_fake: -4.1172e+00 
21-03-31 01:00:20.227 - INFO: End of epoch 971 / 4238 	 Time Taken: 65.6096 sec
21-03-31 01:01:25.708 - INFO: End of epoch 972 / 4238 	 Time Taken: 65.4811 sec
21-03-31 01:01:35.079 - INFO: <epoch:973, iter: 114,000, lr:1.000e-04, t:113.1525s, td:0.0362s, eta:12132.4587h> pix-l1: 4.9445e-03 contextual: 4.2878e+00 l_g_gan: 4.1922e-02 ms-ssim: 1.3258e-01 l_d_real: 1.2622e+00 l_d_fake: 1.2623e+00 D_real: 4.1094e+00 D_fake: 1.2998e+00 
21-03-31 01:01:35.977 - INFO: Models and training states saved.
21-03-31 01:01:41.781 - INFO: # Validation # PSNR: 29.513, SSIM: 0.79128, LPIPS: 0.057282
21-03-31 01:01:41.781 - INFO: <epoch:973, iter: 114,000> PSNR: 29.513, SSIM: 0.79128, LPIPS: 0.057282
21-03-31 01:02:37.993 - INFO: End of epoch 973 / 4238 	 Time Taken: 72.2845 sec
21-03-31 01:03:31.011 - INFO: <epoch:974, iter: 114,200, lr:1.000e-04, t:113.1905s, td:0.0181s, eta:12130.2537h> pix-l1: 4.0483e-03 contextual: 3.9877e+00 l_g_gan: 6.9374e-02 ms-ssim: 9.0557e-02 l_d_real: 1.2671e+00 l_d_fake: 1.2635e+00 D_real: 4.0312e+00 D_fake: -1.1191e+00 
21-03-31 01:03:43.443 - INFO: End of epoch 974 / 4238 	 Time Taken: 65.4493 sec
21-03-31 01:04:49.054 - INFO: End of epoch 975 / 4238 	 Time Taken: 65.6114 sec
21-03-31 01:05:24.223 - INFO: <epoch:976, iter: 114,400, lr:1.000e-04, t:115.9318s, td:0.0362s, eta:12417.5840h> pix-l1: 3.0559e-03 contextual: 3.2674e+00 l_g_gan: 3.2522e-02 ms-ssim: 4.1667e-02 l_d_real: 2.0061e+00 l_d_fake: 1.9946e+00 D_real: -1.5719e+01 D_fake: -1.8047e+01 
21-03-31 01:05:54.550 - INFO: End of epoch 976 / 4238 	 Time Taken: 65.4963 sec
21-03-31 01:06:58.377 - INFO: End of epoch 977 / 4238 	 Time Taken: 63.8257 sec
21-03-31 01:07:15.087 - INFO: <epoch:978, iter: 114,600, lr:1.000e-04, t:113.2121s, td:0.0359s, eta:12119.9858h> pix-l1: 5.8880e-03 contextual: 3.0841e+00 l_g_gan: 2.0002e-02 ms-ssim: 7.0680e-02 l_d_real: 2.9940e+00 l_d_fake: 3.0169e+00 D_real: -6.6895e-01 D_fake: -1.9072e+00 
21-03-31 01:08:01.614 - INFO: End of epoch 978 / 4238 	 Time Taken: 63.2375 sec
21-03-31 01:09:00.447 - INFO: <epoch:979, iter: 114,800, lr:1.000e-04, t:110.8636s, td:0.0176s, eta:11862.4010h> pix-l1: 3.8509e-03 contextual: 3.1999e+00 l_g_gan: 6.2972e-02 ms-ssim: 5.1347e-02 l_d_real: 1.5776e+00 l_d_fake: 1.5755e+00 D_real: -1.2180e+01 D_fake: -1.7859e+01 
21-03-31 01:09:04.808 - INFO: End of epoch 979 / 4238 	 Time Taken: 63.1937 sec
21-03-31 01:10:08.032 - INFO: End of epoch 980 / 4238 	 Time Taken: 63.2244 sec
21-03-31 01:10:49.576 - INFO: <epoch:981, iter: 115,000, lr:1.000e-04, t:105.3606s, td:0.0352s, eta:11267.7332h> pix-l1: 4.9987e-03 contextual: 3.5138e+00 l_g_gan: 5.4023e-02 ms-ssim: 1.4622e-01 l_d_real: 6.4934e-01 l_d_fake: 6.5871e-01 D_real: -2.6758e+00 D_fake: -5.6914e+00 
21-03-31 01:10:50.438 - INFO: Models and training states saved.
21-03-31 01:10:56.043 - INFO: # Validation # PSNR: 29.3, SSIM: 0.79637, LPIPS: 0.053994
21-03-31 01:10:56.043 - INFO: <epoch:981, iter: 115,000> PSNR: 29.3, SSIM: 0.79637, LPIPS: 0.053994
21-03-31 01:11:17.621 - INFO: End of epoch 981 / 4238 	 Time Taken: 69.5881 sec
21-03-31 01:12:20.823 - INFO: End of epoch 982 / 4238 	 Time Taken: 63.2019 sec
21-03-31 01:12:45.099 - INFO: <epoch:983, iter: 115,200, lr:1.000e-04, t:109.1284s, td:0.0353s, eta:11664.6110h> pix-l1: 3.2534e-03 contextual: 3.0795e+00 l_g_gan: 1.6528e-01 ms-ssim: 4.9348e-02 l_d_real: 1.2074e+00 l_d_fake: 1.2104e+00 D_real: -3.0410e+00 D_fake: -1.3234e+01 
21-03-31 01:13:24.004 - INFO: End of epoch 983 / 4238 	 Time Taken: 63.1803 sec
21-03-31 01:14:27.169 - INFO: End of epoch 984 / 4238 	 Time Taken: 63.1655 sec
21-03-31 01:14:34.174 - INFO: <epoch:985, iter: 115,400, lr:1.000e-04, t:115.5237s, td:0.0352s, eta:12341.7768h> pix-l1: 1.8575e-03 contextual: 2.8960e+00 l_g_gan: 6.4652e-02 ms-ssim: 3.3747e-02 l_d_real: 5.9771e-01 l_d_fake: 5.9739e-01 D_real: -2.7344e+01 D_fake: -3.1062e+01 
21-03-31 01:15:30.400 - INFO: End of epoch 985 / 4238 	 Time Taken: 63.2311 sec
21-03-31 01:16:19.551 - INFO: <epoch:986, iter: 115,600, lr:1.000e-04, t:109.0742s, td:0.0176s, eta:11646.6991h> pix-l1: 3.2793e-03 contextual: 3.0750e+00 l_g_gan: 8.9576e-02 ms-ssim: 6.0986e-02 l_d_real: 9.7527e-01 l_d_fake: 9.7771e-01 D_real: -7.6133e+00 D_fake: -1.5547e+01 
21-03-31 01:16:33.558 - INFO: End of epoch 986 / 4238 	 Time Taken: 63.1579 sec
21-03-31 01:17:36.707 - INFO: End of epoch 987 / 4238 	 Time Taken: 63.1491 sec
21-03-31 01:18:08.603 - INFO: <epoch:988, iter: 115,800, lr:1.000e-04, t:105.3771s, td:0.0352s, eta:11246.0766h> pix-l1: 5.1117e-03 contextual: 4.3469e+00 l_g_gan: 1.2121e-01 ms-ssim: 8.4865e-02 l_d_real: 7.6108e-01 l_d_fake: 7.5999e-01 D_real: 9.7266e-01 D_fake: -7.1289e+00 
21-03-31 01:18:39.886 - INFO: End of epoch 988 / 4238 	 Time Taken: 63.1783 sec
21-03-31 01:19:43.110 - INFO: End of epoch 989 / 4238 	 Time Taken: 63.2244 sec
21-03-31 01:19:57.803 - INFO: <epoch:990, iter: 116,000, lr:1.000e-04, t:109.0521s, td:0.0352s, eta:11632.2281h> pix-l1: 5.0189e-03 contextual: 3.4469e+00 l_g_gan: 3.0651e-02 ms-ssim: 8.3937e-02 l_d_real: 2.1505e+00 l_d_fake: 2.1604e+00 D_real: -2.6094e+00 D_fake: -3.9844e+00 
21-03-31 01:19:58.653 - INFO: Models and training states saved.
21-03-31 01:20:04.280 - INFO: # Validation # PSNR: 29.927, SSIM: 0.80531, LPIPS: 0.055359
21-03-31 01:20:04.281 - INFO: <epoch:990, iter: 116,000> PSNR: 29.927, SSIM: 0.80531, LPIPS: 0.055359
21-03-31 01:20:55.183 - INFO: End of epoch 990 / 4238 	 Time Taken: 72.0722 sec
21-03-31 01:22:00.252 - INFO: <epoch:991, iter: 116,200, lr:1.000e-04, t:109.2007s, td:0.0177s, eta:11642.0039h> pix-l1: 3.8012e-03 contextual: 3.5058e+00 l_g_gan: 4.2163e-02 ms-ssim: 4.8514e-02 l_d_real: 1.1358e+00 l_d_fake: 1.1265e+00 D_real: -2.9688e+00 D_fake: -4.4883e+00 
21-03-31 01:22:06.685 - INFO: End of epoch 991 / 4238 	 Time Taken: 71.5029 sec
21-03-31 01:23:15.822 - INFO: End of epoch 992 / 4238 	 Time Taken: 69.1369 sec
21-03-31 01:23:57.816 - INFO: <epoch:993, iter: 116,400, lr:1.000e-04, t:122.4488s, td:0.0361s, eta:13047.5981h> pix-l1: 5.3810e-03 contextual: 6.3658e+00 l_g_gan: 1.2324e-01 ms-ssim: 1.0586e-01 l_d_real: 4.3566e-01 l_d_fake: 4.3584e-01 D_real: 1.3672e+01 D_fake: 7.7617e+00 
21-03-31 01:24:22.326 - INFO: End of epoch 993 / 4238 	 Time Taken: 66.5035 sec
21-03-31 01:25:28.254 - INFO: End of epoch 994 / 4238 	 Time Taken: 65.9277 sec
21-03-31 01:25:51.165 - INFO: <epoch:995, iter: 116,600, lr:1.000e-04, t:117.5644s, td:0.0363s, eta:12520.6127h> pix-l1: 5.3021e-03 contextual: 4.0548e+00 l_g_gan: 9.7859e-02 ms-ssim: 7.5979e-02 l_d_real: 2.8488e-01 l_d_fake: 2.8375e-01 D_real: 2.3672e+00 D_fake: -2.6562e+00 
21-03-31 01:26:34.785 - INFO: End of epoch 995 / 4238 	 Time Taken: 66.5307 sec
21-03-31 01:27:39.237 - INFO: End of epoch 996 / 4238 	 Time Taken: 64.4522 sec
21-03-31 01:27:44.328 - INFO: <epoch:997, iter: 116,800, lr:1.000e-04, t:113.3485s, td:0.0360s, eta:12065.3224h> pix-l1: 4.2459e-03 contextual: 3.8040e+00 l_g_gan: 1.9264e-01 ms-ssim: 1.0219e-01 l_d_real: 6.6371e-01 l_d_fake: 6.6566e-01 D_real: 1.9500e+01 D_fake: 6.2422e+00 
21-03-31 01:28:44.135 - INFO: End of epoch 997 / 4238 	 Time Taken: 64.8980 sec
21-03-31 01:29:33.637 - INFO: <epoch:998, iter: 117,000, lr:1.000e-04, t:113.1631s, td:0.0183s, eta:12039.2981h> pix-l1: 3.0717e-03 contextual: 2.9970e+00 l_g_gan: 7.8125e-02 ms-ssim: 4.4347e-02 l_d_real: 1.4769e+00 l_d_fake: 1.4739e+00 D_real: 6.5391e+00 D_fake: 4.7485e-01 
21-03-31 01:29:34.537 - INFO: Models and training states saved.
21-03-31 01:29:40.415 - INFO: # Validation # PSNR: 29.655, SSIM: 0.79655, LPIPS: 0.05347
21-03-31 01:29:40.416 - INFO: <epoch:998, iter: 117,000> PSNR: 29.655, SSIM: 0.79655, LPIPS: 0.05347
21-03-31 01:29:57.602 - INFO: End of epoch 998 / 4238 	 Time Taken: 73.4661 sec
21-03-31 01:31:05.073 - INFO: End of epoch 999 / 4238 	 Time Taken: 67.4707 sec
21-03-31 01:31:35.308 - INFO: <epoch:1000, iter: 117,200, lr:1.000e-04, t:109.3083s, td:0.0359s, eta:11623.1209h> pix-l1: 5.2767e-03 contextual: 2.7483e+00 l_g_gan: 8.1369e-02 ms-ssim: 6.8222e-02 l_d_real: 4.9934e-01 l_d_fake: 4.9184e-01 D_real: 3.7539e+00 D_fake: -1.7412e+00 
21-03-31 01:32:09.123 - INFO: End of epoch 1000 / 4238 	 Time Taken: 64.0498 sec
21-03-31 01:33:15.269 - INFO: End of epoch 1001 / 4238 	 Time Taken: 66.1459 sec
21-03-31 01:33:28.036 - INFO: <epoch:1002, iter: 117,400, lr:1.000e-04, t:121.6717s, td:0.0365s, eta:12930.9946h> pix-l1: 4.3924e-03 contextual: 4.5448e+00 l_g_gan: 1.3113e-01 ms-ssim: 9.6581e-02 l_d_real: 7.7344e-01 l_d_fake: 7.6842e-01 D_real: 1.9500e+01 D_fake: 1.0227e+01 
21-03-31 01:34:21.615 - INFO: End of epoch 1002 / 4238 	 Time Taken: 66.3454 sec
21-03-31 01:35:18.883 - INFO: <epoch:1003, iter: 117,600, lr:1.000e-04, t:112.7280s, td:0.0180s, eta:11974.2169h> pix-l1: 7.7647e-03 contextual: 5.6921e+00 l_g_gan: 4.8571e-02 ms-ssim: 1.2491e-01 l_d_real: 1.0766e+00 l_d_fake: 1.0767e+00 D_real: 1.9328e+01 D_fake: 1.8422e+01 
21-03-31 01:35:27.370 - INFO: End of epoch 1003 / 4238 	 Time Taken: 65.7544 sec
21-03-31 01:36:32.449 - INFO: End of epoch 1004 / 4238 	 Time Taken: 65.0795 sec
21-03-31 01:37:11.322 - INFO: <epoch:1005, iter: 117,800, lr:1.000e-04, t:110.8468s, td:0.0353s, eta:11768.2355h> pix-l1: 5.5476e-03 contextual: 4.0668e+00 l_g_gan: 1.0018e-01 ms-ssim: 9.6983e-02 l_d_real: 1.6872e-01 l_d_fake: 1.6860e-01 D_real: 2.5938e+00 D_fake: -3.3340e+00 
21-03-31 01:37:40.492 - INFO: End of epoch 1005 / 4238 	 Time Taken: 68.0430 sec
21-03-31 01:38:46.520 - INFO: End of epoch 1006 / 4238 	 Time Taken: 66.0269 sec
21-03-31 01:39:08.624 - INFO: <epoch:1007, iter: 118,000, lr:1.000e-04, t:112.4387s, td:0.0362s, eta:11930.9989h> pix-l1: 2.8886e-03 contextual: 5.2334e+00 l_g_gan: 1.2686e-01 ms-ssim: 6.6982e-02 l_d_real: 1.0275e+00 l_d_fake: 1.0268e+00 D_real: 1.2961e+01 D_fake: 2.9395e+00 
21-03-31 01:39:09.481 - INFO: Models and training states saved.
21-03-31 01:39:15.303 - INFO: # Validation # PSNR: 30.286, SSIM: 0.81709, LPIPS: 0.059253
21-03-31 01:39:15.303 - INFO: <epoch:1007, iter: 118,000> PSNR: 30.286, SSIM: 0.81709, LPIPS: 0.059253
21-03-31 01:39:59.584 - INFO: End of epoch 1007 / 4238 	 Time Taken: 73.0638 sec
21-03-31 01:41:04.471 - INFO: <epoch:1008, iter: 118,200, lr:1.000e-04, t:117.3020s, td:0.0177s, eta:12440.5310h> pix-l1: 2.9206e-03 contextual: 2.7008e+00 l_g_gan: 3.3231e-02 ms-ssim: 4.0862e-02 l_d_real: 1.6800e+00 l_d_fake: 1.6538e+00 D_real: -5.7656e+00 D_fake: -7.5273e+00 
21-03-31 01:41:05.320 - INFO: End of epoch 1008 / 4238 	 Time Taken: 65.7353 sec
21-03-31 01:42:10.660 - INFO: End of epoch 1009 / 4238 	 Time Taken: 65.3396 sec
21-03-31 01:42:58.155 - INFO: <epoch:1010, iter: 118,400, lr:1.000e-04, t:115.8473s, td:0.0360s, eta:12279.8093h> pix-l1: 3.8860e-03 contextual: 2.7161e+00 l_g_gan: 5.3138e-02 ms-ssim: 5.1804e-02 l_d_real: 9.7692e-01 l_d_fake: 9.7351e-01 D_real: -5.8594e+00 D_fake: -9.3047e+00 
21-03-31 01:43:18.277 - INFO: End of epoch 1010 / 4238 	 Time Taken: 67.6162 sec
21-03-31 01:44:25.240 - INFO: End of epoch 1011 / 4238 	 Time Taken: 66.9628 sec
21-03-31 01:44:54.503 - INFO: <epoch:1012, iter: 118,600, lr:1.000e-04, t:113.6846s, td:0.0359s, eta:12044.2496h> pix-l1: 2.6418e-03 contextual: 2.5073e+00 l_g_gan: 2.5861e-02 ms-ssim: 5.6070e-02 l_d_real: 2.4496e+00 l_d_fake: 2.4408e+00 D_real: -8.2422e+00 D_fake: -9.3672e+00 
21-03-31 01:45:31.268 - INFO: End of epoch 1012 / 4238 	 Time Taken: 66.0283 sec
21-03-31 01:46:35.128 - INFO: End of epoch 1013 / 4238 	 Time Taken: 63.8593 sec
21-03-31 01:46:45.854 - INFO: <epoch:1014, iter: 118,800, lr:1.000e-04, t:116.3468s, td:0.0354s, eta:12319.8341h> pix-l1: 2.4760e-03 contextual: 3.5942e+00 l_g_gan: 3.9821e-02 ms-ssim: 6.6304e-02 l_d_real: 1.3798e+00 l_d_fake: 1.3807e+00 D_real: 2.3340e+00 D_fake: -2.5098e-01 
21-03-31 01:47:40.615 - INFO: End of epoch 1014 / 4238 	 Time Taken: 65.4873 sec
21-03-31 01:48:34.149 - INFO: <epoch:1015, iter: 119,000, lr:1.000e-04, t:111.3511s, td:0.0177s, eta:11784.6552h> pix-l1: 3.8106e-03 contextual: 2.6774e+00 l_g_gan: 8.2260e-02 ms-ssim: 4.7574e-02 l_d_real: 1.3865e+00 l_d_fake: 1.3900e+00 D_real: 9.3164e-01 D_fake: -6.6836e+00 
21-03-31 01:48:35.023 - INFO: Models and training states saved.
21-03-31 01:48:40.715 - INFO: # Validation # PSNR: 29.884, SSIM: 0.80041, LPIPS: 0.054134
21-03-31 01:48:40.715 - INFO: <epoch:1015, iter: 119,000> PSNR: 29.884, SSIM: 0.80041, LPIPS: 0.054134
21-03-31 01:48:51.577 - INFO: End of epoch 1015 / 4238 	 Time Taken: 70.9620 sec
21-03-31 01:49:57.858 - INFO: End of epoch 1016 / 4238 	 Time Taken: 66.2798 sec
21-03-31 01:50:33.607 - INFO: <epoch:1017, iter: 119,200, lr:1.000e-04, t:108.2956s, td:0.0357s, eta:11455.2652h> pix-l1: 5.7705e-03 contextual: 4.3616e+00 l_g_gan: 6.7388e-02 ms-ssim: 7.7683e-02 l_d_real: 7.7912e-01 l_d_fake: 7.8045e-01 D_real: 6.8652e-01 D_fake: -4.3945e+00 
21-03-31 01:51:03.506 - INFO: End of epoch 1017 / 4238 	 Time Taken: 65.6477 sec
21-03-31 01:52:09.358 - INFO: End of epoch 1018 / 4238 	 Time Taken: 65.8522 sec
21-03-31 01:52:28.131 - INFO: <epoch:1019, iter: 119,400, lr:1.000e-04, t:119.4573s, td:0.0358s, eta:12629.2865h> pix-l1: 4.5988e-03 contextual: 2.4511e+00 l_g_gan: 9.3267e-02 ms-ssim: 5.5621e-02 l_d_real: 1.1682e+00 l_d_fake: 1.1681e+00 D_real: -5.3281e+00 D_fake: -1.2438e+01 
21-03-31 01:53:16.338 - INFO: End of epoch 1019 / 4238 	 Time Taken: 66.9795 sec
21-03-31 01:54:21.325 - INFO: <epoch:1020, iter: 119,600, lr:1.000e-04, t:114.5246s, td:0.0177s, eta:12101.4369h> pix-l1: 5.4134e-03 contextual: 3.5361e+00 l_g_gan: 1.7789e-01 ms-ssim: 7.4969e-02 l_d_real: 1.0453e+00 l_d_fake: 1.0463e+00 D_real: 1.0148e+01 D_fake: -1.1973e+00 
21-03-31 01:54:24.211 - INFO: End of epoch 1020 / 4238 	 Time Taken: 67.8729 sec
21-03-31 01:55:30.614 - INFO: End of epoch 1021 / 4238 	 Time Taken: 66.4037 sec
21-03-31 01:56:15.013 - INFO: <epoch:1022, iter: 119,800, lr:1.000e-04, t:113.1936s, td:0.0363s, eta:11954.4988h> pix-l1: 3.1832e-03 contextual: 3.1580e+00 l_g_gan: 1.1719e-01 ms-ssim: 4.3285e-02 l_d_real: 7.3359e-01 l_d_fake: 7.3189e-01 D_real: -5.5352e+00 D_fake: -1.5984e+01 
21-03-31 01:56:35.267 - INFO: End of epoch 1022 / 4238 	 Time Taken: 64.6519 sec
21-03-31 01:57:40.618 - INFO: End of epoch 1023 / 4238 	 Time Taken: 65.3509 sec
21-03-31 01:58:08.225 - INFO: <epoch:1024, iter: 120,000, lr:1.000e-04, t:113.6886s, td:0.0359s, eta:12000.4665h> pix-l1: 3.8833e-03 contextual: 4.9053e+00 l_g_gan: 2.0196e-01 ms-ssim: 8.7545e-02 l_d_real: 8.2106e-01 l_d_fake: 8.2186e-01 D_real: 8.6641e+00 D_fake: -5.1641e+00 
21-03-31 01:58:09.104 - INFO: Models and training states saved.
21-03-31 01:58:14.891 - INFO: # Validation # PSNR: 29.762, SSIM: 0.79777, LPIPS: 0.056571
21-03-31 01:58:14.891 - INFO: <epoch:1024, iter: 120,000> PSNR: 29.762, SSIM: 0.79777, LPIPS: 0.056571
21-03-31 01:58:20.579 - INFO: Training interrupted. Latest models and training states saved.