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  1. ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Neutral_115000_swaG.pth +3 -0
  2. ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Sharp_101000_G.pth +3 -0
  3. ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Sharper_103000_G.pth +3 -0
  4. ESRGAN/UniversalUpscaler/Legacy/4x_UniversalUpscaler-Detailed_155000_G.pth +3 -0
  5. ESRGAN/UniversalUpscaler/Legacy/4x_UniversalUpscaler-Soft_190000_G.pth +3 -0
  6. ESRGAN/UniversalUpscaler/Legacy/UniversalUpscaler-Detailed.log +0 -0
  7. ESRGAN/UniversalUpscaler/Legacy/UniversalUpscaler_Soft.log +0 -0
  8. ESRGAN/UniversalUpscaler/UniversalUpscalerV2-Neutral.log +292 -0
  9. ESRGAN/UniversalUpscaler/UniversalUpscalerV2-Sharp.log +277 -0
  10. ESRGAN/UniversalUpscaler/UniversalUpscalerV2-Sharper.log +0 -0
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ESRGAN/UniversalUpscaler/Legacy/UniversalUpscaler-Detailed.log ADDED
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ESRGAN/UniversalUpscaler/Legacy/UniversalUpscaler_Soft.log ADDED
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ESRGAN/UniversalUpscaler/UniversalUpscalerV2-Neutral.log ADDED
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+ 21-03-31 00:41:35.097 - INFO: name: 4x_UniversalUpscalerV2-Neutral
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+ use_tb_logger: True
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+ model: srragan
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+ scale: 4
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+ gpu_ids: [0]
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+ use_amp: True
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+ use_swa: True
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+ datasets:[
9
+ train:[
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+ name: DIV2K
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+ mode: LRHRC
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+ dataroot_HR: ['..\\datasets\\train\\hr\\hrRealism\\Original', '..\\datasets\\train\\hr\\hrRealism\\Point']
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+ dataroot_LR: ['..\\datasets\\train\\lr\\lrUniversal\\lrBox', '..\\datasets\\train\\lr\\lrUniversal\\lrPoint']
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+ subset_file: None
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+ use_shuffle: True
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+ znorm: False
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+ n_workers: 4
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+ batch_size: 4
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+ virtual_batch_size: 4
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+ HR_size: 128
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+ image_channels: 3
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+ dataroot_kernels: ../training/kernels/results/
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+ lr_downscale: True
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+ lr_downscale_types: [1, 2, 777]
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+ use_flip: True
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+ use_rot: True
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+ hr_rrot: False
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+ lr_blur: False
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+ lr_blur_types: ['gaussian', 'clean', 'clean', 'clean']
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+ noise_data: ../noise_patches/normal/
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+ lr_noise: False
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+ lr_noise_types: ['JPEG', 'clean', 'clean', 'clean', 'clean']
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+ lr_noise2: False
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+ lr_noise_types2: ['dither', 'dither', 'clean', 'clean']
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+ hr_noise: False
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+ hr_noise_types: ['gaussian', 'clean', 'clean', 'clean', 'clean']
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+ phase: train
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+ scale: 4
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+ data_type: img
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+ ]
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+ val:[
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+ name: val_images
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+ mode: LRHROTF
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+ dataroot_HR: ..\datasets\val\hr\hrUniversal
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+ dataroot_LR: ..\datasets\val\lr\lrUniversal\Neutral
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+ znorm: False
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+ lr_downscale: False
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+ lr_downscale_types: [1, 2]
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+ phase: val
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+ scale: 4
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+ data_type: img
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+ ]
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+ ]
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+ path:[
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+ strict: False
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+ root: C:\nn\BasicSR
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+ pretrain_model_G: ..\experiments\pretrained_models\RRDB_ESRGAN_x4.pth
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+ resume_state: ..\experiments\4x_UniversalUpscalerV2-Neutral\training_state\112000.state
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+ experiments_root: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral
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+ models: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\models
61
+ training_state: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\training_state
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+ log: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral
63
+ val_images: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\val_images
64
+ ]
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+ network_G:[
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+ strict: False
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+ which_model_G: RRDB_net
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+ norm_type: None
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+ mode: CNA
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+ nf: 64
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+ nb: 23
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+ nr: 3
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+ in_nc: 3
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+ out_nc: 3
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+ gc: 32
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+ group: 1
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+ convtype: Conv2D
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+ net_act: leakyrelu
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+ gaussian: True
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+ plus: False
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+ scale: 4
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+ ]
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+ network_D:[
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+ strict: True
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+ which_model_D: multiscale
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+ norm_type: batch
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+ act_type: leakyrelu
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+ mode: CNA
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+ nf: 64
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+ in_nc: 3
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+ nlayer: 3
92
+ num_D: 3
93
+ ]
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+ train:[
95
+ lr_G: 0.0001
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+ weight_decay_G: 0
97
+ beta1_G: 0.9
98
+ lr_D: 0.0001
99
+ weight_decay_D: 0
100
+ beta1_D: 0.9
101
+ lr_scheme: MultiStepLR
102
+ lr_gamma: 0.5
103
+ swa_start_iter: 70000
104
+ swa_lr: 0.0001
105
+ swa_anneal_epochs: 10
106
+ swa_anneal_strategy: cos
107
+ pixel_criterion: l1
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+ pixel_weight: 0.1
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+ cx_weight: 0.5
110
+ cx_type: contextual
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+ cx_vgg_layers:[
112
+ conv_3_2: 1
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+ conv_3_1: 1
114
+ conv_4_2: 1
115
+ conv_4_1: 1
116
+ conv_5_2: 1
117
+ conv_5_1: 1
118
+ ]
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+ ssim_type: ms-ssim
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+ ssim_weight: 1
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+ gan_type: vanilla
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+ gan_weight: 0.009
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+ manual_seed: 0
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+ niter: 500000.0
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+ val_freq: 1000
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+ metrics: psnr,ssim,lpips
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+ overwrite_val_imgs: None
128
+ val_comparison: None
129
+ lr_steps: [50000, 100000, 200000, 300000]
130
+ ]
131
+ logger:[
132
+ print_freq: 200
133
+ save_checkpoint_freq: 1000
134
+ overwrite_chkp: False
135
+ ]
136
+ is_train: True
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+
138
+ 21-03-31 00:41:35.200 - INFO: Random seed: 0
139
+ 21-03-31 00:41:36.716 - INFO: Set [resume_state] to ..\experiments\4x_UniversalUpscalerV2-Neutral\training_state\112000.state
140
+ 21-03-31 00:41:36.716 - INFO: Resuming training from epoch: 956, iter: 112000.
141
+ 21-03-31 00:41:36.716 - WARNING: pretrain_model paths will be ignored when resuming training from a .state file.
142
+ 21-03-31 00:41:36.716 - INFO: Set [pretrain_model_G] to C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\models\112000_G.pth
143
+ 21-03-31 00:41:36.716 - INFO: Set [pretrain_model_D] to C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\models\112000_D.pth
144
+ 21-03-31 00:41:36.734 - INFO: Dataset [LRHRDataset - DIV2K] is created.
145
+ 21-03-31 00:41:36.734 - INFO: Number of train images: 470, iters: 118
146
+ 21-03-31 00:41:36.735 - INFO: Total epochs needed: 4238 for iters 500,000
147
+ 21-03-31 00:41:36.735 - INFO: Dataset [LRHRDataset - val_images] is created.
148
+ 21-03-31 00:41:36.735 - INFO: Number of val images in [val_images]: 3
149
+ 21-03-31 00:41:37.012 - INFO: AMP library available
150
+ 21-03-31 00:41:37.143 - INFO: Initialization method [kaiming]
151
+ 21-03-31 00:41:37.353 - INFO: Initialization method [kaiming]
152
+ 21-03-31 00:41:37.409 - INFO: Loading pretrained model for G [C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\models\112000_G.pth] ...
153
+ 21-03-31 00:41:37.649 - INFO: Loading pretrained model for D [C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Neutral\models\112000_D.pth] ...
154
+ 21-03-31 00:41:38.673 - INFO: SWA enabled. Starting on iter: 70000, lr: 0.0001
155
+ 21-03-31 00:41:38.675 - INFO: AMP enabled
156
+ 21-03-31 00:41:38.684 - INFO: Network G structure: DataParallel - RRDBNet, with parameters: 16,697,987
157
+ 21-03-31 00:41:38.685 - INFO: Network D structure: DataParallel - MultiscaleDiscriminator, with parameters: 8,296,899
158
+ 21-03-31 00:41:38.685 - INFO: Model [SRRaGANModel] is created.
159
+ 21-03-31 00:41:38.766 - INFO: Start training from epoch: 956, iter: 112000
160
+ 21-03-31 00:42:50.337 - INFO: End of epoch 956 / 4238 Time Taken: 71.5706 sec
161
+ 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
162
+ 21-03-31 00:44:11.223 - INFO: End of epoch 957 / 4238 Time Taken: 80.8861 sec
163
+ 21-03-31 00:45:31.848 - INFO: End of epoch 958 / 4238 Time Taken: 80.6250 sec
164
+ 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
165
+ 21-03-31 00:46:52.641 - INFO: End of epoch 959 / 4238 Time Taken: 80.7930 sec
166
+ 21-03-31 00:48:11.601 - INFO: End of epoch 960 / 4238 Time Taken: 78.9601 sec
167
+ 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
168
+ 21-03-31 00:49:16.002 - INFO: End of epoch 961 / 4238 Time Taken: 64.4010 sec
169
+ 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
170
+ 21-03-31 00:50:20.307 - INFO: End of epoch 962 / 4238 Time Taken: 64.3044 sec
171
+ 21-03-31 00:51:24.767 - INFO: End of epoch 963 / 4238 Time Taken: 64.4600 sec
172
+ 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
173
+ 21-03-31 00:52:02.335 - INFO: Models and training states saved.
174
+ 21-03-31 00:52:10.432 - INFO: # Validation # PSNR: 29.774, SSIM: 0.808, LPIPS: 0.058653
175
+ 21-03-31 00:52:10.433 - INFO: <epoch:964, iter: 113,000> PSNR: 29.774, SSIM: 0.808, LPIPS: 0.058653
176
+ 21-03-31 00:52:38.581 - INFO: End of epoch 964 / 4238 Time Taken: 73.8133 sec
177
+ 21-03-31 00:53:44.420 - INFO: End of epoch 965 / 4238 Time Taken: 65.8385 sec
178
+ 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
179
+ 21-03-31 00:54:50.501 - INFO: End of epoch 966 / 4238 Time Taken: 66.0809 sec
180
+ 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
181
+ 21-03-31 00:55:57.752 - INFO: End of epoch 967 / 4238 Time Taken: 67.2507 sec
182
+ 21-03-31 00:57:03.392 - INFO: End of epoch 968 / 4238 Time Taken: 65.6391 sec
183
+ 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
184
+ 21-03-31 00:58:09.107 - INFO: End of epoch 969 / 4238 Time Taken: 65.7147 sec
185
+ 21-03-31 00:59:14.618 - INFO: End of epoch 970 / 4238 Time Taken: 65.5109 sec
186
+ 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
187
+ 21-03-31 01:00:20.227 - INFO: End of epoch 971 / 4238 Time Taken: 65.6096 sec
188
+ 21-03-31 01:01:25.708 - INFO: End of epoch 972 / 4238 Time Taken: 65.4811 sec
189
+ 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
190
+ 21-03-31 01:01:35.977 - INFO: Models and training states saved.
191
+ 21-03-31 01:01:41.781 - INFO: # Validation # PSNR: 29.513, SSIM: 0.79128, LPIPS: 0.057282
192
+ 21-03-31 01:01:41.781 - INFO: <epoch:973, iter: 114,000> PSNR: 29.513, SSIM: 0.79128, LPIPS: 0.057282
193
+ 21-03-31 01:02:37.993 - INFO: End of epoch 973 / 4238 Time Taken: 72.2845 sec
194
+ 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
195
+ 21-03-31 01:03:43.443 - INFO: End of epoch 974 / 4238 Time Taken: 65.4493 sec
196
+ 21-03-31 01:04:49.054 - INFO: End of epoch 975 / 4238 Time Taken: 65.6114 sec
197
+ 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
198
+ 21-03-31 01:05:54.550 - INFO: End of epoch 976 / 4238 Time Taken: 65.4963 sec
199
+ 21-03-31 01:06:58.377 - INFO: End of epoch 977 / 4238 Time Taken: 63.8257 sec
200
+ 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
201
+ 21-03-31 01:08:01.614 - INFO: End of epoch 978 / 4238 Time Taken: 63.2375 sec
202
+ 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
203
+ 21-03-31 01:09:04.808 - INFO: End of epoch 979 / 4238 Time Taken: 63.1937 sec
204
+ 21-03-31 01:10:08.032 - INFO: End of epoch 980 / 4238 Time Taken: 63.2244 sec
205
+ 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
206
+ 21-03-31 01:10:50.438 - INFO: Models and training states saved.
207
+ 21-03-31 01:10:56.043 - INFO: # Validation # PSNR: 29.3, SSIM: 0.79637, LPIPS: 0.053994
208
+ 21-03-31 01:10:56.043 - INFO: <epoch:981, iter: 115,000> PSNR: 29.3, SSIM: 0.79637, LPIPS: 0.053994
209
+ 21-03-31 01:11:17.621 - INFO: End of epoch 981 / 4238 Time Taken: 69.5881 sec
210
+ 21-03-31 01:12:20.823 - INFO: End of epoch 982 / 4238 Time Taken: 63.2019 sec
211
+ 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
212
+ 21-03-31 01:13:24.004 - INFO: End of epoch 983 / 4238 Time Taken: 63.1803 sec
213
+ 21-03-31 01:14:27.169 - INFO: End of epoch 984 / 4238 Time Taken: 63.1655 sec
214
+ 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
215
+ 21-03-31 01:15:30.400 - INFO: End of epoch 985 / 4238 Time Taken: 63.2311 sec
216
+ 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
217
+ 21-03-31 01:16:33.558 - INFO: End of epoch 986 / 4238 Time Taken: 63.1579 sec
218
+ 21-03-31 01:17:36.707 - INFO: End of epoch 987 / 4238 Time Taken: 63.1491 sec
219
+ 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
220
+ 21-03-31 01:18:39.886 - INFO: End of epoch 988 / 4238 Time Taken: 63.1783 sec
221
+ 21-03-31 01:19:43.110 - INFO: End of epoch 989 / 4238 Time Taken: 63.2244 sec
222
+ 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
223
+ 21-03-31 01:19:58.653 - INFO: Models and training states saved.
224
+ 21-03-31 01:20:04.280 - INFO: # Validation # PSNR: 29.927, SSIM: 0.80531, LPIPS: 0.055359
225
+ 21-03-31 01:20:04.281 - INFO: <epoch:990, iter: 116,000> PSNR: 29.927, SSIM: 0.80531, LPIPS: 0.055359
226
+ 21-03-31 01:20:55.183 - INFO: End of epoch 990 / 4238 Time Taken: 72.0722 sec
227
+ 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
228
+ 21-03-31 01:22:06.685 - INFO: End of epoch 991 / 4238 Time Taken: 71.5029 sec
229
+ 21-03-31 01:23:15.822 - INFO: End of epoch 992 / 4238 Time Taken: 69.1369 sec
230
+ 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
231
+ 21-03-31 01:24:22.326 - INFO: End of epoch 993 / 4238 Time Taken: 66.5035 sec
232
+ 21-03-31 01:25:28.254 - INFO: End of epoch 994 / 4238 Time Taken: 65.9277 sec
233
+ 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
234
+ 21-03-31 01:26:34.785 - INFO: End of epoch 995 / 4238 Time Taken: 66.5307 sec
235
+ 21-03-31 01:27:39.237 - INFO: End of epoch 996 / 4238 Time Taken: 64.4522 sec
236
+ 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
237
+ 21-03-31 01:28:44.135 - INFO: End of epoch 997 / 4238 Time Taken: 64.8980 sec
238
+ 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
239
+ 21-03-31 01:29:34.537 - INFO: Models and training states saved.
240
+ 21-03-31 01:29:40.415 - INFO: # Validation # PSNR: 29.655, SSIM: 0.79655, LPIPS: 0.05347
241
+ 21-03-31 01:29:40.416 - INFO: <epoch:998, iter: 117,000> PSNR: 29.655, SSIM: 0.79655, LPIPS: 0.05347
242
+ 21-03-31 01:29:57.602 - INFO: End of epoch 998 / 4238 Time Taken: 73.4661 sec
243
+ 21-03-31 01:31:05.073 - INFO: End of epoch 999 / 4238 Time Taken: 67.4707 sec
244
+ 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
245
+ 21-03-31 01:32:09.123 - INFO: End of epoch 1000 / 4238 Time Taken: 64.0498 sec
246
+ 21-03-31 01:33:15.269 - INFO: End of epoch 1001 / 4238 Time Taken: 66.1459 sec
247
+ 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
248
+ 21-03-31 01:34:21.615 - INFO: End of epoch 1002 / 4238 Time Taken: 66.3454 sec
249
+ 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
250
+ 21-03-31 01:35:27.370 - INFO: End of epoch 1003 / 4238 Time Taken: 65.7544 sec
251
+ 21-03-31 01:36:32.449 - INFO: End of epoch 1004 / 4238 Time Taken: 65.0795 sec
252
+ 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
253
+ 21-03-31 01:37:40.492 - INFO: End of epoch 1005 / 4238 Time Taken: 68.0430 sec
254
+ 21-03-31 01:38:46.520 - INFO: End of epoch 1006 / 4238 Time Taken: 66.0269 sec
255
+ 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
256
+ 21-03-31 01:39:09.481 - INFO: Models and training states saved.
257
+ 21-03-31 01:39:15.303 - INFO: # Validation # PSNR: 30.286, SSIM: 0.81709, LPIPS: 0.059253
258
+ 21-03-31 01:39:15.303 - INFO: <epoch:1007, iter: 118,000> PSNR: 30.286, SSIM: 0.81709, LPIPS: 0.059253
259
+ 21-03-31 01:39:59.584 - INFO: End of epoch 1007 / 4238 Time Taken: 73.0638 sec
260
+ 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
261
+ 21-03-31 01:41:05.320 - INFO: End of epoch 1008 / 4238 Time Taken: 65.7353 sec
262
+ 21-03-31 01:42:10.660 - INFO: End of epoch 1009 / 4238 Time Taken: 65.3396 sec
263
+ 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
264
+ 21-03-31 01:43:18.277 - INFO: End of epoch 1010 / 4238 Time Taken: 67.6162 sec
265
+ 21-03-31 01:44:25.240 - INFO: End of epoch 1011 / 4238 Time Taken: 66.9628 sec
266
+ 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
267
+ 21-03-31 01:45:31.268 - INFO: End of epoch 1012 / 4238 Time Taken: 66.0283 sec
268
+ 21-03-31 01:46:35.128 - INFO: End of epoch 1013 / 4238 Time Taken: 63.8593 sec
269
+ 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
270
+ 21-03-31 01:47:40.615 - INFO: End of epoch 1014 / 4238 Time Taken: 65.4873 sec
271
+ 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
272
+ 21-03-31 01:48:35.023 - INFO: Models and training states saved.
273
+ 21-03-31 01:48:40.715 - INFO: # Validation # PSNR: 29.884, SSIM: 0.80041, LPIPS: 0.054134
274
+ 21-03-31 01:48:40.715 - INFO: <epoch:1015, iter: 119,000> PSNR: 29.884, SSIM: 0.80041, LPIPS: 0.054134
275
+ 21-03-31 01:48:51.577 - INFO: End of epoch 1015 / 4238 Time Taken: 70.9620 sec
276
+ 21-03-31 01:49:57.858 - INFO: End of epoch 1016 / 4238 Time Taken: 66.2798 sec
277
+ 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
278
+ 21-03-31 01:51:03.506 - INFO: End of epoch 1017 / 4238 Time Taken: 65.6477 sec
279
+ 21-03-31 01:52:09.358 - INFO: End of epoch 1018 / 4238 Time Taken: 65.8522 sec
280
+ 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
281
+ 21-03-31 01:53:16.338 - INFO: End of epoch 1019 / 4238 Time Taken: 66.9795 sec
282
+ 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
283
+ 21-03-31 01:54:24.211 - INFO: End of epoch 1020 / 4238 Time Taken: 67.8729 sec
284
+ 21-03-31 01:55:30.614 - INFO: End of epoch 1021 / 4238 Time Taken: 66.4037 sec
285
+ 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
286
+ 21-03-31 01:56:35.267 - INFO: End of epoch 1022 / 4238 Time Taken: 64.6519 sec
287
+ 21-03-31 01:57:40.618 - INFO: End of epoch 1023 / 4238 Time Taken: 65.3509 sec
288
+ 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
289
+ 21-03-31 01:58:09.104 - INFO: Models and training states saved.
290
+ 21-03-31 01:58:14.891 - INFO: # Validation # PSNR: 29.762, SSIM: 0.79777, LPIPS: 0.056571
291
+ 21-03-31 01:58:14.891 - INFO: <epoch:1024, iter: 120,000> PSNR: 29.762, SSIM: 0.79777, LPIPS: 0.056571
292
+ 21-03-31 01:58:20.579 - INFO: Training interrupted. Latest models and training states saved.
ESRGAN/UniversalUpscaler/UniversalUpscalerV2-Sharp.log ADDED
@@ -0,0 +1,277 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 21-03-30 20:30:19.118 - INFO: name: 4x_UniversalUpscalerV2-Sharp
2
+ use_tb_logger: True
3
+ model: srragan
4
+ scale: 4
5
+ gpu_ids: [0]
6
+ use_amp: True
7
+ use_swa: True
8
+ datasets:[
9
+ train:[
10
+ name: DIV2K
11
+ mode: LRHRC
12
+ dataroot_HR: ['..\\datasets\\train\\hr\\hrRealism\\Original', '..\\datasets\\train\\hr\\hrRealism\\Point']
13
+ dataroot_LR: ['..\\datasets\\train\\lr\\lrUniversal\\lrHermite', '..\\datasets\\train\\lr\\lrUniversal\\lrPoint']
14
+ subset_file: None
15
+ use_shuffle: True
16
+ znorm: False
17
+ n_workers: 4
18
+ batch_size: 4
19
+ virtual_batch_size: 4
20
+ HR_size: 128
21
+ image_channels: 3
22
+ dataroot_kernels: ../training/kernels/results/
23
+ lr_downscale: True
24
+ lr_downscale_types: [1, 2, 777]
25
+ use_flip: True
26
+ use_rot: True
27
+ hr_rrot: False
28
+ lr_blur: False
29
+ lr_blur_types: ['gaussian', 'clean', 'clean', 'clean']
30
+ noise_data: ../noise_patches/normal/
31
+ lr_noise: False
32
+ lr_noise_types: ['JPEG', 'clean', 'clean', 'clean', 'clean']
33
+ lr_noise2: False
34
+ lr_noise_types2: ['dither', 'dither', 'clean', 'clean']
35
+ hr_noise: False
36
+ hr_noise_types: ['gaussian', 'clean', 'clean', 'clean', 'clean']
37
+ phase: train
38
+ scale: 4
39
+ data_type: img
40
+ ]
41
+ val:[
42
+ name: val_images
43
+ mode: LRHROTF
44
+ dataroot_HR: ..\datasets\val\hr\hrUniversal
45
+ dataroot_LR: ..\datasets\val\lr\lrUniversal\Sharp
46
+ znorm: False
47
+ lr_downscale: False
48
+ lr_downscale_types: [1, 2]
49
+ phase: val
50
+ scale: 4
51
+ data_type: img
52
+ ]
53
+ ]
54
+ path:[
55
+ strict: False
56
+ root: C:\nn\BasicSR
57
+ pretrain_model_G: ..\experiments\pretrained_models\RRDB_ESRGAN_x4.pth
58
+ resume_state: ..\experiments\4x_UniversalUpscalerV2-Sharp\training_state\101000.state
59
+ experiments_root: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp
60
+ models: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\models
61
+ training_state: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\training_state
62
+ log: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp
63
+ val_images: C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\val_images
64
+ ]
65
+ network_G:[
66
+ strict: False
67
+ which_model_G: RRDB_net
68
+ norm_type: None
69
+ mode: CNA
70
+ nf: 64
71
+ nb: 23
72
+ nr: 3
73
+ in_nc: 3
74
+ out_nc: 3
75
+ gc: 32
76
+ group: 1
77
+ convtype: Conv2D
78
+ net_act: leakyrelu
79
+ gaussian: True
80
+ plus: False
81
+ scale: 4
82
+ ]
83
+ network_D:[
84
+ strict: True
85
+ which_model_D: multiscale
86
+ norm_type: batch
87
+ act_type: leakyrelu
88
+ mode: CNA
89
+ nf: 64
90
+ in_nc: 3
91
+ nlayer: 3
92
+ num_D: 3
93
+ ]
94
+ train:[
95
+ lr_G: 0.0001
96
+ weight_decay_G: 0
97
+ beta1_G: 0.9
98
+ lr_D: 0.0001
99
+ weight_decay_D: 0
100
+ beta1_D: 0.9
101
+ lr_scheme: MultiStepLR
102
+ lr_gamma: 0.5
103
+ swa_start_iter: 70000
104
+ swa_lr: 0.0001
105
+ swa_anneal_epochs: 10
106
+ swa_anneal_strategy: cos
107
+ pixel_criterion: l1
108
+ pixel_weight: 0.1
109
+ cx_weight: 0.5
110
+ cx_type: contextual
111
+ cx_vgg_layers:[
112
+ conv_3_2: 1
113
+ conv_3_1: 1
114
+ conv_4_2: 1
115
+ conv_4_1: 1
116
+ conv_5_2: 1
117
+ conv_5_1: 1
118
+ ]
119
+ ssim_type: ms-ssim
120
+ ssim_weight: 1
121
+ gan_type: vanilla
122
+ gan_weight: 0.009
123
+ manual_seed: 0
124
+ niter: 500000.0
125
+ val_freq: 1000
126
+ metrics: psnr,ssim,lpips
127
+ overwrite_val_imgs: None
128
+ val_comparison: None
129
+ lr_steps: [50000, 100000, 200000, 300000]
130
+ ]
131
+ logger:[
132
+ print_freq: 200
133
+ save_checkpoint_freq: 1000
134
+ overwrite_chkp: False
135
+ ]
136
+ is_train: True
137
+
138
+ 21-03-30 20:30:19.220 - INFO: Random seed: 0
139
+ 21-03-30 20:30:20.395 - INFO: Set [resume_state] to ..\experiments\4x_UniversalUpscalerV2-Sharp\training_state\101000.state
140
+ 21-03-30 20:30:20.396 - INFO: Resuming training from epoch: 861, iter: 101000.
141
+ 21-03-30 20:30:20.396 - WARNING: pretrain_model paths will be ignored when resuming training from a .state file.
142
+ 21-03-30 20:30:20.396 - INFO: Set [pretrain_model_G] to C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\models\101000_G.pth
143
+ 21-03-30 20:30:20.396 - INFO: Set [pretrain_model_D] to C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\models\101000_D.pth
144
+ 21-03-30 20:30:20.413 - INFO: Dataset [LRHRDataset - DIV2K] is created.
145
+ 21-03-30 20:30:20.413 - INFO: Number of train images: 470, iters: 118
146
+ 21-03-30 20:30:20.413 - INFO: Total epochs needed: 4238 for iters 500,000
147
+ 21-03-30 20:30:20.414 - INFO: Dataset [LRHRDataset - val_images] is created.
148
+ 21-03-30 20:30:20.414 - INFO: Number of val images in [val_images]: 3
149
+ 21-03-30 20:30:20.694 - INFO: AMP library available
150
+ 21-03-30 20:30:20.819 - INFO: Initialization method [kaiming]
151
+ 21-03-30 20:30:21.035 - INFO: Initialization method [kaiming]
152
+ 21-03-30 20:30:21.092 - INFO: Loading pretrained model for G [C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\models\101000_G.pth] ...
153
+ 21-03-30 20:30:21.304 - INFO: Loading pretrained model for D [C:\nn\BasicSR\experiments\4x_UniversalUpscalerV2-Sharp\models\101000_D.pth] ...
154
+ 21-03-30 20:30:22.360 - INFO: SWA enabled. Starting on iter: 70000, lr: 0.0001
155
+ 21-03-30 20:30:22.362 - INFO: AMP enabled
156
+ 21-03-30 20:30:22.371 - INFO: Network G structure: DataParallel - RRDBNet, with parameters: 16,697,987
157
+ 21-03-30 20:30:22.372 - INFO: Network D structure: DataParallel - MultiscaleDiscriminator, with parameters: 8,296,899
158
+ 21-03-30 20:30:22.372 - INFO: Model [SRRaGANModel] is created.
159
+ 21-03-30 20:30:22.450 - INFO: Start training from epoch: 861, iter: 101000
160
+ 21-03-30 20:31:29.007 - INFO: End of epoch 861 / 4238 Time Taken: 66.5568 sec
161
+ 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
162
+ 21-03-30 20:32:32.400 - INFO: End of epoch 862 / 4238 Time Taken: 63.3934 sec
163
+ 21-03-30 20:33:34.086 - INFO: End of epoch 863 / 4238 Time Taken: 61.6850 sec
164
+ 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
165
+ 21-03-30 20:34:35.818 - INFO: End of epoch 864 / 4238 Time Taken: 61.7320 sec
166
+ 21-03-30 20:35:37.563 - INFO: End of epoch 865 / 4238 Time Taken: 61.7451 sec
167
+ 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
168
+ 21-03-30 20:36:39.345 - INFO: End of epoch 866 / 4238 Time Taken: 61.7818 sec
169
+ 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
170
+ 21-03-30 20:37:41.132 - INFO: End of epoch 867 / 4238 Time Taken: 61.7871 sec
171
+ 21-03-30 20:38:43.018 - INFO: End of epoch 868 / 4238 Time Taken: 61.8860 sec
172
+ 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
173
+ 21-03-30 20:39:18.933 - INFO: Models and training states saved.
174
+ 21-03-30 20:39:26.702 - INFO: # Validation # PSNR: 30.014, SSIM: 0.81439, LPIPS: 0.057651
175
+ 21-03-30 20:39:26.702 - INFO: <epoch:869, iter: 102,000> PSNR: 30.014, SSIM: 0.81439, LPIPS: 0.057651
176
+ 21-03-30 20:39:53.818 - INFO: End of epoch 869 / 4238 Time Taken: 70.7990 sec
177
+ 21-03-30 20:40:57.025 - INFO: End of epoch 870 / 4238 Time Taken: 63.2068 sec
178
+ 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
179
+ 21-03-30 20:42:00.101 - INFO: End of epoch 871 / 4238 Time Taken: 63.0762 sec
180
+ 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
181
+ 21-03-30 20:43:03.308 - INFO: End of epoch 872 / 4238 Time Taken: 63.2063 sec
182
+ 21-03-30 20:44:06.563 - INFO: End of epoch 873 / 4238 Time Taken: 63.2545 sec
183
+ 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
184
+ 21-03-30 20:45:09.776 - INFO: End of epoch 874 / 4238 Time Taken: 63.2135 sec
185
+ 21-03-30 20:46:13.029 - INFO: End of epoch 875 / 4238 Time Taken: 63.2527 sec
186
+ 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
187
+ 21-03-30 20:47:16.149 - INFO: End of epoch 876 / 4238 Time Taken: 63.1192 sec
188
+ 21-03-30 20:48:19.302 - INFO: End of epoch 877 / 4238 Time Taken: 63.1535 sec
189
+ 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
190
+ 21-03-30 20:48:29.039 - INFO: Models and training states saved.
191
+ 21-03-30 20:48:34.606 - INFO: # Validation # PSNR: 29.56, SSIM: 0.79439, LPIPS: 0.055718
192
+ 21-03-30 20:48:34.606 - INFO: <epoch:878, iter: 103,000> PSNR: 29.56, SSIM: 0.79439, LPIPS: 0.055718
193
+ 21-03-30 20:49:28.854 - INFO: End of epoch 878 / 4238 Time Taken: 69.5518 sec
194
+ 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
195
+ 21-03-30 20:50:32.132 - INFO: End of epoch 879 / 4238 Time Taken: 63.2781 sec
196
+ 21-03-30 20:51:35.305 - INFO: End of epoch 880 / 4238 Time Taken: 63.1731 sec
197
+ 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
198
+ 21-03-30 20:52:38.629 - INFO: End of epoch 881 / 4238 Time Taken: 63.3239 sec
199
+ 21-03-30 20:53:41.798 - INFO: End of epoch 882 / 4238 Time Taken: 63.1685 sec
200
+ 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
201
+ 21-03-30 20:54:44.990 - INFO: End of epoch 883 / 4238 Time Taken: 63.1917 sec
202
+ 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
203
+ 21-03-30 20:55:48.306 - INFO: End of epoch 884 / 4238 Time Taken: 63.3159 sec
204
+ 21-03-30 20:56:51.652 - INFO: End of epoch 885 / 4238 Time Taken: 63.3461 sec
205
+ 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
206
+ 21-03-30 20:57:33.894 - INFO: Models and training states saved.
207
+ 21-03-30 20:57:39.485 - INFO: # Validation # PSNR: 29.898, SSIM: 0.80043, LPIPS: 0.051817
208
+ 21-03-30 20:57:39.485 - INFO: <epoch:886, iter: 104,000> PSNR: 29.898, SSIM: 0.80043, LPIPS: 0.051817
209
+ 21-03-30 20:58:01.065 - INFO: End of epoch 886 / 4238 Time Taken: 69.4124 sec
210
+ 21-03-30 20:59:04.294 - INFO: End of epoch 887 / 4238 Time Taken: 63.2287 sec
211
+ 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
212
+ 21-03-30 21:00:07.516 - INFO: End of epoch 888 / 4238 Time Taken: 63.2222 sec
213
+ 21-03-30 21:01:10.705 - INFO: End of epoch 889 / 4238 Time Taken: 63.1888 sec
214
+ 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
215
+ 21-03-30 21:02:13.988 - INFO: End of epoch 890 / 4238 Time Taken: 63.2828 sec
216
+ 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
217
+ 21-03-30 21:03:17.177 - INFO: End of epoch 891 / 4238 Time Taken: 63.1891 sec
218
+ 21-03-30 21:04:20.377 - INFO: End of epoch 892 / 4238 Time Taken: 63.2005 sec
219
+ 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
220
+ 21-03-30 21:05:23.526 - INFO: End of epoch 893 / 4238 Time Taken: 63.1485 sec
221
+ 21-03-30 21:06:26.716 - INFO: End of epoch 894 / 4238 Time Taken: 63.1906 sec
222
+ 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
223
+ 21-03-30 21:06:42.039 - INFO: Models and training states saved.
224
+ 21-03-30 21:06:47.671 - INFO: # Validation # PSNR: 29.984, SSIM: 0.80758, LPIPS: 0.053631
225
+ 21-03-30 21:06:47.671 - INFO: <epoch:895, iter: 105,000> PSNR: 29.984, SSIM: 0.80758, LPIPS: 0.053631
226
+ 21-03-30 21:07:36.215 - INFO: End of epoch 895 / 4238 Time Taken: 69.4992 sec
227
+ 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
228
+ 21-03-30 21:08:39.469 - INFO: End of epoch 896 / 4238 Time Taken: 63.2533 sec
229
+ 21-03-30 21:09:42.644 - INFO: End of epoch 897 / 4238 Time Taken: 63.1743 sec
230
+ 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
231
+ 21-03-30 21:10:45.833 - INFO: End of epoch 898 / 4238 Time Taken: 63.1884 sec
232
+ 21-03-30 21:11:48.983 - INFO: End of epoch 899 / 4238 Time Taken: 63.1499 sec
233
+ 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
234
+ 21-03-30 21:12:52.172 - INFO: End of epoch 900 / 4238 Time Taken: 63.1887 sec
235
+ 21-03-30 21:13:55.348 - INFO: End of epoch 901 / 4238 Time Taken: 63.1760 sec
236
+ 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
237
+ 21-03-30 21:14:58.574 - INFO: End of epoch 902 / 4238 Time Taken: 63.2261 sec
238
+ 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
239
+ 21-03-30 21:15:46.442 - INFO: Models and training states saved.
240
+ 21-03-30 21:15:52.060 - INFO: # Validation # PSNR: 30.001, SSIM: 0.80233, LPIPS: 0.05284
241
+ 21-03-30 21:15:52.060 - INFO: <epoch:903, iter: 106,000> PSNR: 30.001, SSIM: 0.80233, LPIPS: 0.05284
242
+ 21-03-30 21:16:08.035 - INFO: End of epoch 903 / 4238 Time Taken: 69.4610 sec
243
+ 21-03-30 21:17:11.266 - INFO: End of epoch 904 / 4238 Time Taken: 63.2295 sec
244
+ 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
245
+ 21-03-30 21:18:14.462 - INFO: End of epoch 905 / 4238 Time Taken: 63.1964 sec
246
+ 21-03-30 21:19:17.692 - INFO: End of epoch 906 / 4238 Time Taken: 63.2290 sec
247
+ 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
248
+ 21-03-30 21:20:21.360 - INFO: End of epoch 907 / 4238 Time Taken: 63.6685 sec
249
+ 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
250
+ 21-03-30 21:21:30.173 - INFO: End of epoch 908 / 4238 Time Taken: 68.8126 sec
251
+ 21-03-30 21:22:42.716 - INFO: End of epoch 909 / 4238 Time Taken: 72.5426 sec
252
+ 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
253
+ 21-03-30 21:24:02.250 - INFO: End of epoch 910 / 4238 Time Taken: 79.5341 sec
254
+ 21-03-30 21:25:14.384 - INFO: End of epoch 911 / 4238 Time Taken: 72.1337 sec
255
+ 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
256
+ 21-03-30 21:25:37.546 - INFO: Models and training states saved.
257
+ 21-03-30 21:25:43.820 - INFO: # Validation # PSNR: 30.508, SSIM: 0.82059, LPIPS: 0.06361
258
+ 21-03-30 21:25:43.820 - INFO: <epoch:912, iter: 107,000> PSNR: 30.508, SSIM: 0.82059, LPIPS: 0.06361
259
+ 21-03-30 21:26:28.379 - INFO: End of epoch 912 / 4238 Time Taken: 73.9941 sec
260
+ 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
261
+ 21-03-30 21:27:34.737 - INFO: End of epoch 913 / 4238 Time Taken: 66.3575 sec
262
+ 21-03-30 21:28:39.912 - INFO: End of epoch 914 / 4238 Time Taken: 65.1748 sec
263
+ 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
264
+ 21-03-30 21:29:46.224 - INFO: End of epoch 915 / 4238 Time Taken: 66.3119 sec
265
+ 21-03-30 21:30:52.020 - INFO: End of epoch 916 / 4238 Time Taken: 65.7959 sec
266
+ 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
267
+ 21-03-30 21:31:56.162 - INFO: End of epoch 917 / 4238 Time Taken: 64.1420 sec
268
+ 21-03-30 21:32:59.748 - INFO: End of epoch 918 / 4238 Time Taken: 63.5856 sec
269
+ 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
270
+ 21-03-30 21:34:06.768 - INFO: End of epoch 919 / 4238 Time Taken: 67.0202 sec
271
+ 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
272
+ 21-03-30 21:35:03.217 - INFO: Models and training states saved.
273
+ 21-03-30 21:35:09.053 - INFO: # Validation # PSNR: 29.891, SSIM: 0.80672, LPIPS: 0.055147
274
+ 21-03-30 21:35:09.053 - INFO: <epoch:920, iter: 108,000> PSNR: 29.891, SSIM: 0.80672, LPIPS: 0.055147
275
+ 21-03-30 21:35:19.673 - INFO: End of epoch 920 / 4238 Time Taken: 72.9055 sec
276
+ 21-03-30 21:36:27.130 - INFO: End of epoch 921 / 4238 Time Taken: 67.4561 sec
277
+ 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
ESRGAN/UniversalUpscaler/UniversalUpscalerV2-Sharper.log ADDED
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