21-03-30 20:30:19.118 - INFO:   name: 4x_UniversalUpscalerV2-Sharp
  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\\lrHermite', '..\\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\Sharp
      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-Sharp\training_state\101000.state
    experiments_root: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp
    models: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\models
    training_state: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\training_state
    log: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp
    val_images: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\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

21-03-30 20:30:19.220 - INFO: Random seed: 0
21-03-30 20:30:20.395 - INFO: Set [resume_state] to ..\experiments\4x_UniversalUpscalerV2-Sharp\training_state\101000.state
21-03-30 20:30:20.396 - INFO: Resuming training from epoch: 861, iter: 101000.
21-03-30 20:30:20.396 - WARNING: pretrain_model paths will be ignored when resuming training from a .state file.
21-03-30 20:30:20.396 - INFO: Set [pretrain_model_G] to C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\models\101000_G.pth
21-03-30 20:30:20.396 - INFO: Set [pretrain_model_D] to C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\models\101000_D.pth
21-03-30 20:30:20.413 - INFO: Dataset [LRHRDataset - DIV2K] is created.
21-03-30 20:30:20.413 - INFO: Number of train images: 470, iters: 118
21-03-30 20:30:20.413 - INFO: Total epochs needed: 4238 for iters 500,000
21-03-30 20:30:20.414 - INFO: Dataset [LRHRDataset - val_images] is created.
21-03-30 20:30:20.414 - INFO: Number of val images in [val_images]: 3
21-03-30 20:30:20.694 - INFO: AMP library available
21-03-30 20:30:20.819 - INFO: Initialization method [kaiming]
21-03-30 20:30:21.035 - INFO: Initialization method [kaiming]
21-03-30 20:30:21.092 - INFO: Loading pretrained model for G [C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\models\101000_G.pth] ...
21-03-30 20:30:21.304 - INFO: Loading pretrained model for D [C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\models\101000_D.pth] ...
21-03-30 20:30:22.360 - INFO: SWA enabled. Starting on iter: 70000, lr: 0.0001
21-03-30 20:30:22.362 - INFO: AMP enabled
21-03-30 20:30:22.371 - INFO: Network G structure: DataParallel - RRDBNet, with parameters: 16,697,987
21-03-30 20:30:22.372 - INFO: Network D structure: DataParallel - MultiscaleDiscriminator, with parameters: 8,296,899
21-03-30 20:30:22.372 - INFO: Model [SRRaGANModel] is created.
21-03-30 20:30:22.450 - INFO: Start training from epoch: 861, iter: 101000
21-03-30 20:31:29.007 - INFO: End of epoch 861 / 4238 	 Time Taken: 66.5568 sec
21-03-30 20:32:15.106 - INFO: <epoch:862, iter: 101,200, lr:1.000e-04, t:-1.0000s, td:0.0352s, eta:0.0000h> pix-l1: 2.7355e-03 contextual: 4.5225e+00 l_g_gan: 1.2768e-01 ms-ssim: 1.0155e-01 l_d_real: 1.7323e+00 l_d_fake: 1.7264e+00 D_real: 1.3844e+01 D_fake: 1.2861e+00 
21-03-30 20:32:32.400 - INFO: End of epoch 862 / 4238 	 Time Taken: 63.3934 sec
21-03-30 20:33:34.086 - INFO: End of epoch 863 / 4238 	 Time Taken: 61.6850 sec
21-03-30 20:34:01.791 - INFO: <epoch:864, iter: 101,400, lr:1.000e-04, t:-1.0000s, td:0.0346s, eta:0.0000h> pix-l1: 4.2290e-03 contextual: 3.6313e+00 l_g_gan: 1.1870e-01 ms-ssim: 7.8216e-02 l_d_real: 7.0160e-01 l_d_fake: 7.0307e-01 D_real: 7.8555e+00 D_fake: -1.4075e-01 
21-03-30 20:34:35.818 - INFO: End of epoch 864 / 4238 	 Time Taken: 61.7320 sec
21-03-30 20:35:37.563 - INFO: End of epoch 865 / 4238 	 Time Taken: 61.7451 sec
21-03-30 20:35:48.419 - INFO: <epoch:866, iter: 101,600, lr:1.000e-04, t:106.6844s, td:0.0347s, eta:11806.4108h> pix-l1: 6.5755e-03 contextual: 4.5142e+00 l_g_gan: 7.4213e-02 ms-ssim: 1.1315e-01 l_d_real: 4.0147e-01 l_d_fake: 3.8975e-01 D_real: 8.2891e+00 D_fake: 5.0156e+00 
21-03-30 20:36:39.345 - INFO: End of epoch 866 / 4238 	 Time Taken: 61.7818 sec
21-03-30 20:37:31.417 - INFO: <epoch:867, iter: 101,800, lr:1.000e-04, t:106.6287s, td:0.0174s, eta:11794.3148h> pix-l1: 3.5731e-03 contextual: 3.3757e+00 l_g_gan: 1.0602e-01 ms-ssim: 5.5085e-02 l_d_real: 4.3074e-01 l_d_fake: 4.2892e-01 D_real: 4.0625e+00 D_fake: -2.5117e+00 
21-03-30 20:37:41.132 - INFO: End of epoch 867 / 4238 	 Time Taken: 61.7871 sec
21-03-30 20:38:43.018 - INFO: End of epoch 868 / 4238 	 Time Taken: 61.8860 sec
21-03-30 20:39:18.232 - INFO: <epoch:869, iter: 102,000, lr:1.000e-04, t:102.9978s, td:0.0348s, eta:11386.9778h> pix-l1: 2.3721e-03 contextual: 2.1929e+00 l_g_gan: 5.5651e-02 ms-ssim: 2.6698e-02 l_d_real: 8.8035e-01 l_d_fake: 8.9202e-01 D_real: -1.1617e+01 D_fake: -1.4680e+01 
21-03-30 20:39:18.933 - INFO: Models and training states saved.
21-03-30 20:39:26.702 - INFO: # Validation # PSNR: 30.014, SSIM: 0.81439, LPIPS: 0.057651
21-03-30 20:39:26.702 - INFO: <epoch:869, iter: 102,000> PSNR: 30.014, SSIM: 0.81439, LPIPS: 0.057651
21-03-30 20:39:53.818 - INFO: End of epoch 869 / 4238 	 Time Taken: 70.7990 sec
21-03-30 20:40:57.025 - INFO: End of epoch 870 / 4238 	 Time Taken: 63.2068 sec
21-03-30 20:41:15.667 - INFO: <epoch:871, iter: 102,200, lr:1.000e-04, t:106.8148s, td:0.0350s, eta:11803.0375h> pix-l1: 5.3606e-03 contextual: 4.2364e+00 l_g_gan: 1.5190e-01 ms-ssim: 8.4528e-02 l_d_real: 3.9801e-01 l_d_fake: 3.9965e-01 D_real: 1.2242e+01 D_fake: 3.9727e+00 
21-03-30 20:42:00.101 - INFO: End of epoch 871 / 4238 	 Time Taken: 63.0762 sec
21-03-30 20:43:00.985 - INFO: <epoch:872, iter: 102,400, lr:1.000e-04, t:117.4354s, td:0.0175s, eta:12970.0903h> pix-l1: 3.0082e-03 contextual: 3.0873e+00 l_g_gan: 5.7648e-02 ms-ssim: 4.7864e-02 l_d_real: 6.1739e-01 l_d_fake: 6.2757e-01 D_real: 2.8926e+00 D_fake: 6.4209e-01 
21-03-30 20:43:03.308 - INFO: End of epoch 872 / 4238 	 Time Taken: 63.2063 sec
21-03-30 20:44:06.563 - INFO: End of epoch 873 / 4238 	 Time Taken: 63.2545 sec
21-03-30 20:44:50.163 - INFO: <epoch:874, iter: 102,600, lr:1.000e-04, t:105.3173s, td:0.0349s, eta:11625.8618h> pix-l1: 6.1895e-03 contextual: 5.0459e+00 l_g_gan: 1.0713e-01 ms-ssim: 1.2959e-01 l_d_real: 1.0727e+00 l_d_fake: 1.0845e+00 D_real: 1.8203e+01 D_fake: 8.4219e+00 
21-03-30 20:45:09.776 - INFO: End of epoch 874 / 4238 	 Time Taken: 63.2135 sec
21-03-30 20:46:13.029 - INFO: End of epoch 875 / 4238 	 Time Taken: 63.2527 sec
21-03-30 20:46:39.293 - INFO: <epoch:876, iter: 102,800, lr:1.000e-04, t:109.1782s, td:0.0350s, eta:12045.9920h> pix-l1: 8.9756e-04 contextual: 3.4247e+00 l_g_gan: 6.9280e-02 ms-ssim: 1.3433e-02 l_d_real: 7.2783e-01 l_d_fake: 7.2643e-01 D_real: -1.0547e+01 D_fake: -1.4109e+01 
21-03-30 20:47:16.149 - INFO: End of epoch 876 / 4238 	 Time Taken: 63.1192 sec
21-03-30 20:48:19.302 - INFO: End of epoch 877 / 4238 	 Time Taken: 63.1535 sec
21-03-30 20:48:28.324 - INFO: <epoch:878, iter: 103,000, lr:1.000e-04, t:109.1303s, td:0.0350s, eta:12034.6463h> pix-l1: 4.8335e-03 contextual: 4.4326e+00 l_g_gan: 2.6212e-02 ms-ssim: 1.2624e-01 l_d_real: 1.9453e+00 l_d_fake: 1.9452e+00 D_real: 1.8875e+01 D_fake: 1.7469e+01 
21-03-30 20:48:29.039 - INFO: Models and training states saved.
21-03-30 20:48:34.606 - INFO: # Validation # PSNR: 29.56, SSIM: 0.79439, LPIPS: 0.055718
21-03-30 20:48:34.606 - INFO: <epoch:878, iter: 103,000> PSNR: 29.56, SSIM: 0.79439, LPIPS: 0.055718
21-03-30 20:49:28.854 - INFO: End of epoch 878 / 4238 	 Time Taken: 69.5518 sec
21-03-30 20:50:20.133 - INFO: <epoch:879, iter: 103,200, lr:1.000e-04, t:109.0305s, td:0.0175s, eta:12017.5813h> pix-l1: 4.1391e-03 contextual: 4.0319e+00 l_g_gan: 4.0400e-02 ms-ssim: 8.9757e-02 l_d_real: 1.5417e+00 l_d_fake: 1.5425e+00 D_real: 2.1816e+00 D_fake: -2.2766e-01 
21-03-30 20:50:32.132 - INFO: End of epoch 879 / 4238 	 Time Taken: 63.2781 sec
21-03-30 20:51:35.305 - INFO: End of epoch 880 / 4238 	 Time Taken: 63.1731 sec
21-03-30 20:52:09.302 - INFO: <epoch:881, iter: 103,400, lr:1.000e-04, t:111.8093s, td:0.0351s, eta:12317.6589h> pix-l1: 2.8363e-03 contextual: 3.2613e+00 l_g_gan: 4.2616e-02 ms-ssim: 3.9401e-02 l_d_real: 1.1244e+00 l_d_fake: 1.1185e+00 D_real: -4.5156e+00 D_fake: -6.8398e+00 
21-03-30 20:52:38.629 - INFO: End of epoch 881 / 4238 	 Time Taken: 63.3239 sec
21-03-30 20:53:41.798 - INFO: End of epoch 882 / 4238 	 Time Taken: 63.1685 sec
21-03-30 20:53:58.445 - INFO: <epoch:883, iter: 103,600, lr:1.000e-04, t:109.1694s, td:0.0351s, eta:12020.7645h> pix-l1: 5.5358e-03 contextual: 3.5163e+00 l_g_gan: 6.0203e-02 ms-ssim: 6.8828e-02 l_d_real: 7.8254e-01 l_d_fake: 8.0026e-01 D_real: 5.9688e+00 D_fake: 2.1582e+00 
21-03-30 20:54:44.990 - INFO: End of epoch 883 / 4238 	 Time Taken: 63.1917 sec
21-03-30 20:55:43.942 - INFO: <epoch:884, iter: 103,800, lr:1.000e-04, t:109.1421s, td:0.0175s, eta:12011.6984h> pix-l1: 3.5468e-03 contextual: 2.8112e+00 l_g_gan: 6.4454e-02 ms-ssim: 4.2706e-02 l_d_real: 5.9588e-01 l_d_fake: 5.9420e-01 D_real: -1.1297e+01 D_fake: -1.4891e+01 
21-03-30 20:55:48.306 - INFO: End of epoch 884 / 4238 	 Time Taken: 63.3159 sec
21-03-30 20:56:51.652 - INFO: End of epoch 885 / 4238 	 Time Taken: 63.3461 sec
21-03-30 20:57:33.194 - INFO: <epoch:886, iter: 104,000, lr:1.000e-04, t:105.4975s, td:0.0350s, eta:11604.7279h> pix-l1: 4.7393e-03 contextual: 3.3477e+00 l_g_gan: 1.1918e-01 ms-ssim: 1.4343e-01 l_d_real: 4.4456e-01 l_d_fake: 4.4528e-01 D_real: 5.5312e+00 D_fake: -2.8984e+00 
21-03-30 20:57:33.894 - INFO: Models and training states saved.
21-03-30 20:57:39.485 - INFO: # Validation # PSNR: 29.898, SSIM: 0.80043, LPIPS: 0.051817
21-03-30 20:57:39.485 - INFO: <epoch:886, iter: 104,000> PSNR: 29.898, SSIM: 0.80043, LPIPS: 0.051817
21-03-30 20:58:01.065 - INFO: End of epoch 886 / 4238 	 Time Taken: 69.4124 sec
21-03-30 20:59:04.294 - INFO: End of epoch 887 / 4238 	 Time Taken: 63.2287 sec
21-03-30 20:59:28.576 - INFO: <epoch:888, iter: 104,200, lr:1.000e-04, t:109.2520s, td:0.0351s, eta:12011.6558h> pix-l1: 3.1305e-03 contextual: 3.0886e+00 l_g_gan: 1.8087e-01 ms-ssim: 4.6514e-02 l_d_real: 2.1245e-01 l_d_fake: 2.1277e-01 D_real: 4.3152e-02 D_fake: -7.9648e+00 
21-03-30 21:00:07.516 - INFO: End of epoch 888 / 4238 	 Time Taken: 63.2222 sec
21-03-30 21:01:10.705 - INFO: End of epoch 889 / 4238 	 Time Taken: 63.1888 sec
21-03-30 21:01:17.705 - INFO: <epoch:890, iter: 104,400, lr:1.000e-04, t:115.3816s, td:0.0351s, eta:12679.1585h> pix-l1: 1.8427e-03 contextual: 2.7628e+00 l_g_gan: 2.6326e-02 ms-ssim: 3.5195e-02 l_d_real: 1.8821e+00 l_d_fake: 1.8805e+00 D_real: -2.7938e+01 D_fake: -2.8625e+01 
21-03-30 21:02:13.988 - INFO: End of epoch 890 / 4238 	 Time Taken: 63.2828 sec
21-03-30 21:03:03.164 - INFO: <epoch:891, iter: 104,600, lr:1.000e-04, t:109.1293s, td:0.0175s, eta:11986.0397h> pix-l1: 3.3259e-03 contextual: 3.0378e+00 l_g_gan: 6.6153e-02 ms-ssim: 5.7246e-02 l_d_real: 5.3742e-01 l_d_fake: 5.3606e-01 D_real: 4.0430e-01 D_fake: -3.4609e+00 
21-03-30 21:03:17.177 - INFO: End of epoch 891 / 4238 	 Time Taken: 63.1891 sec
21-03-30 21:04:20.377 - INFO: End of epoch 892 / 4238 	 Time Taken: 63.2005 sec
21-03-30 21:04:52.255 - INFO: <epoch:893, iter: 104,800, lr:1.000e-04, t:105.4596s, td:0.0351s, eta:11577.1251h> pix-l1: 4.8650e-03 contextual: 4.0218e+00 l_g_gan: 9.8383e-02 ms-ssim: 8.0442e-02 l_d_real: 5.8602e-01 l_d_fake: 5.8668e-01 D_real: 1.2766e+01 D_fake: 6.1289e+00 
21-03-30 21:05:23.526 - INFO: End of epoch 893 / 4238 	 Time Taken: 63.1485 sec
21-03-30 21:06:26.716 - INFO: End of epoch 894 / 4238 	 Time Taken: 63.1906 sec
21-03-30 21:06:41.319 - INFO: <epoch:895, iter: 105,000, lr:1.000e-04, t:109.0897s, td:0.0351s, eta:11969.5677h> pix-l1: 4.8388e-03 contextual: 3.4847e+00 l_g_gan: 3.3059e-02 ms-ssim: 8.0116e-02 l_d_real: 1.4127e+00 l_d_fake: 1.4220e+00 D_real: -5.1221e-01 D_fake: -1.7080e+00 
21-03-30 21:06:42.039 - INFO: Models and training states saved.
21-03-30 21:06:47.671 - INFO: # Validation # PSNR: 29.984, SSIM: 0.80758, LPIPS: 0.053631
21-03-30 21:06:47.671 - INFO: <epoch:895, iter: 105,000> PSNR: 29.984, SSIM: 0.80758, LPIPS: 0.053631
21-03-30 21:07:36.215 - INFO: End of epoch 895 / 4238 	 Time Taken: 69.4992 sec
21-03-30 21:08:33.058 - INFO: <epoch:896, iter: 105,200, lr:1.000e-04, t:109.0653s, td:0.0175s, eta:11960.8270h> pix-l1: 3.6562e-03 contextual: 3.4584e+00 l_g_gan: 8.4250e-02 ms-ssim: 4.3995e-02 l_d_real: 3.9135e-01 l_d_fake: 3.9310e-01 D_real: -9.5469e+00 D_fake: -1.3953e+01 
21-03-30 21:08:39.469 - INFO: End of epoch 896 / 4238 	 Time Taken: 63.2533 sec
21-03-30 21:09:42.644 - INFO: End of epoch 897 / 4238 	 Time Taken: 63.1743 sec
21-03-30 21:10:22.167 - INFO: <epoch:898, iter: 105,400, lr:1.000e-04, t:111.7389s, td:0.0351s, eta:12247.8218h> pix-l1: 5.3548e-03 contextual: 5.9579e+00 l_g_gan: 1.3309e-01 ms-ssim: 1.0458e-01 l_d_real: 4.4470e-01 l_d_fake: 4.4430e-01 D_real: 8.9922e+00 D_fake: 1.7637e+00 
21-03-30 21:10:45.833 - INFO: End of epoch 898 / 4238 	 Time Taken: 63.1884 sec
21-03-30 21:11:48.983 - INFO: End of epoch 899 / 4238 	 Time Taken: 63.1499 sec
21-03-30 21:12:11.228 - INFO: <epoch:900, iter: 105,600, lr:1.000e-04, t:109.1080s, td:0.0351s, eta:11953.3865h> pix-l1: 5.2555e-03 contextual: 4.0708e+00 l_g_gan: 3.6577e-02 ms-ssim: 7.4561e-02 l_d_real: 1.1595e+00 l_d_fake: 1.1695e+00 D_real: -3.0547e+00 D_fake: -4.2695e+00 
21-03-30 21:12:52.172 - INFO: End of epoch 900 / 4238 	 Time Taken: 63.1887 sec
21-03-30 21:13:55.348 - INFO: End of epoch 901 / 4238 	 Time Taken: 63.1760 sec
21-03-30 21:14:00.302 - INFO: <epoch:902, iter: 105,800, lr:1.000e-04, t:109.0617s, td:0.0351s, eta:11942.2537h> pix-l1: 4.2225e-03 contextual: 3.6864e+00 l_g_gan: 1.3737e-01 ms-ssim: 1.0113e-01 l_d_real: 1.0191e+00 l_d_fake: 1.0189e+00 D_real: 1.8219e+01 D_fake: 7.7109e+00 
21-03-30 21:14:58.574 - INFO: End of epoch 902 / 4238 	 Time Taken: 63.2261 sec
21-03-30 21:15:45.716 - INFO: <epoch:903, iter: 106,000, lr:1.000e-04, t:109.0740s, td:0.0176s, eta:11937.5381h> pix-l1: 2.9911e-03 contextual: 2.9750e+00 l_g_gan: 9.4199e-02 ms-ssim: 4.3258e-02 l_d_real: 5.9816e-01 l_d_fake: 5.9649e-01 D_real: 8.4453e+00 D_fake: 2.5508e+00 
21-03-30 21:15:46.442 - INFO: Models and training states saved.
21-03-30 21:15:52.060 - INFO: # Validation # PSNR: 30.001, SSIM: 0.80233, LPIPS: 0.05284
21-03-30 21:15:52.060 - INFO: <epoch:903, iter: 106,000> PSNR: 30.001, SSIM: 0.80233, LPIPS: 0.05284
21-03-30 21:16:08.035 - INFO: End of epoch 903 / 4238 	 Time Taken: 69.4610 sec
21-03-30 21:17:11.266 - INFO: End of epoch 904 / 4238 	 Time Taken: 63.2295 sec
21-03-30 21:17:41.113 - INFO: <epoch:905, iter: 106,200, lr:1.000e-04, t:105.4138s, td:0.0352s, eta:11531.0961h> pix-l1: 5.0691e-03 contextual: 2.6204e+00 l_g_gan: 6.2196e-02 ms-ssim: 6.7046e-02 l_d_real: 7.5738e-01 l_d_fake: 7.4968e-01 D_real: -3.0273e+00 D_fake: -6.9570e+00 
21-03-30 21:18:14.462 - INFO: End of epoch 905 / 4238 	 Time Taken: 63.1964 sec
21-03-30 21:19:17.692 - INFO: End of epoch 906 / 4238 	 Time Taken: 63.2290 sec
21-03-30 21:19:30.274 - INFO: <epoch:907, iter: 106,400, lr:1.000e-04, t:115.3970s, td:0.0351s, eta:12616.7346h> pix-l1: 4.3251e-03 contextual: 4.3311e+00 l_g_gan: 1.3520e-01 ms-ssim: 9.3275e-02 l_d_real: 4.4210e-01 l_d_fake: 4.3993e-01 D_real: 1.0492e+01 D_fake: 1.3311e+00 
21-03-30 21:20:21.360 - INFO: End of epoch 907 / 4238 	 Time Taken: 63.6685 sec
21-03-30 21:21:19.969 - INFO: <epoch:908, iter: 106,600, lr:1.000e-04, t:109.1612s, td:0.0179s, eta:11928.8973h> pix-l1: 7.5666e-03 contextual: 5.4145e+00 l_g_gan: 7.0104e-02 ms-ssim: 1.2407e-01 l_d_real: 5.0690e-01 l_d_fake: 4.9510e-01 D_real: 2.1594e+01 D_fake: 1.7734e+01 
21-03-30 21:21:30.173 - INFO: End of epoch 908 / 4238 	 Time Taken: 68.8126 sec
21-03-30 21:22:42.716 - INFO: End of epoch 909 / 4238 	 Time Taken: 72.5426 sec
21-03-30 21:23:24.601 - INFO: <epoch:910, iter: 106,800, lr:1.000e-04, t:109.6948s, td:0.0356s, eta:11981.1108h> pix-l1: 5.4628e-03 contextual: 4.0118e+00 l_g_gan: 1.6005e-01 ms-ssim: 9.5604e-02 l_d_real: 5.4765e-02 l_d_fake: 5.4735e-02 D_real: 3.1699e+00 D_fake: -4.5273e+00 
21-03-30 21:24:02.250 - INFO: End of epoch 910 / 4238 	 Time Taken: 79.5341 sec
21-03-30 21:25:14.384 - INFO: End of epoch 911 / 4238 	 Time Taken: 72.1337 sec
21-03-30 21:25:36.769 - INFO: <epoch:912, iter: 107,000, lr:1.000e-04, t:124.6322s, td:0.0363s, eta:13605.6773h> pix-l1: 2.6891e-03 contextual: 5.5593e+00 l_g_gan: 1.6997e-01 ms-ssim: 6.4233e-02 l_d_real: 7.6057e-01 l_d_fake: 7.6413e-01 D_real: 6.0000e+00 D_fake: -5.1055e+00 
21-03-30 21:25:37.546 - INFO: Models and training states saved.
21-03-30 21:25:43.820 - INFO: # Validation # PSNR: 30.508, SSIM: 0.82059, LPIPS: 0.06361
21-03-30 21:25:43.820 - INFO: <epoch:912, iter: 107,000> PSNR: 30.508, SSIM: 0.82059, LPIPS: 0.06361
21-03-30 21:26:28.379 - INFO: End of epoch 912 / 4238 	 Time Taken: 73.9941 sec
21-03-30 21:27:33.902 - INFO: <epoch:913, iter: 107,200, lr:1.000e-04, t:132.1681s, td:0.0178s, eta:14421.0047h> pix-l1: 2.6696e-03 contextual: 2.7854e+00 l_g_gan: 4.4398e-02 ms-ssim: 4.1290e-02 l_d_real: 1.9858e+00 l_d_fake: 1.9853e+00 D_real: -1.2676e+00 D_fake: -5.1914e+00 
21-03-30 21:27:34.737 - INFO: End of epoch 913 / 4238 	 Time Taken: 66.3575 sec
21-03-30 21:28:39.912 - INFO: End of epoch 914 / 4238 	 Time Taken: 65.1748 sec
21-03-30 21:29:26.164 - INFO: <epoch:915, iter: 107,400, lr:1.000e-04, t:117.1325s, td:0.0368s, eta:12773.9535h> pix-l1: 3.8297e-03 contextual: 2.7292e+00 l_g_gan: 1.0028e-01 ms-ssim: 5.1544e-02 l_d_real: 1.1015e+00 l_d_fake: 1.0997e+00 D_real: 4.6172e+00 D_fake: -2.5645e+00 
21-03-30 21:29:46.224 - INFO: End of epoch 915 / 4238 	 Time Taken: 66.3119 sec
21-03-30 21:30:52.020 - INFO: End of epoch 916 / 4238 	 Time Taken: 65.7959 sec
21-03-30 21:31:20.609 - INFO: <epoch:917, iter: 107,600, lr:1.000e-04, t:112.2620s, td:0.0356s, eta:12236.5545h> pix-l1: 2.5802e-03 contextual: 2.4022e+00 l_g_gan: 4.5948e-02 ms-ssim: 5.1849e-02 l_d_real: 1.6492e+00 l_d_fake: 1.6526e+00 D_real: -1.3500e+01 D_fake: -1.7219e+01 
21-03-30 21:31:56.162 - INFO: End of epoch 917 / 4238 	 Time Taken: 64.1420 sec
21-03-30 21:32:59.748 - INFO: End of epoch 918 / 4238 	 Time Taken: 63.5856 sec
21-03-30 21:33:10.454 - INFO: <epoch:919, iter: 107,800, lr:1.000e-04, t:114.4456s, td:0.0354s, eta:12468.2098h> pix-l1: 2.3419e-03 contextual: 3.5648e+00 l_g_gan: 1.1729e-01 ms-ssim: 6.1200e-02 l_d_real: 8.6573e-01 l_d_fake: 8.6690e-01 D_real: 4.2188e+00 D_fake: -3.2930e+00 
21-03-30 21:34:06.768 - INFO: End of epoch 919 / 4238 	 Time Taken: 67.0202 sec
21-03-30 21:35:02.463 - INFO: <epoch:920, iter: 108,000, lr:1.000e-04, t:109.8443s, td:0.0181s, eta:11960.8207h> pix-l1: 3.6716e-03 contextual: 2.8231e+00 l_g_gan: 1.1955e-01 ms-ssim: 4.6514e-02 l_d_real: 9.2139e-01 l_d_fake: 9.1170e-01 D_real: -3.8105e+00 D_fake: -1.4422e+01 
21-03-30 21:35:03.217 - INFO: Models and training states saved.
21-03-30 21:35:09.053 - INFO: # Validation # PSNR: 29.891, SSIM: 0.80672, LPIPS: 0.055147
21-03-30 21:35:09.053 - INFO: <epoch:920, iter: 108,000> PSNR: 29.891, SSIM: 0.80672, LPIPS: 0.055147
21-03-30 21:35:19.673 - INFO: End of epoch 920 / 4238 	 Time Taken: 72.9055 sec
21-03-30 21:36:27.130 - INFO: End of epoch 921 / 4238 	 Time Taken: 67.4561 sec
21-03-30 21:37:03.104 - INFO: <epoch:922, iter: 108,200, lr:1.000e-04, t:112.0096s, td:0.0357s, eta:12190.3835h> pix-l1: 5.7819e-03 contextual: 4.2316e+00 l_g_gan: 6.2249e-02 ms-ssim: 7.9186e-02 l_d_real: 1.6421e+00 l_d_fake: 1.6486e+00 D_real: 4.7227e+00 D_fake: -9.0479e-01