CycleGANPaper_no_BreastMask_norm_0_255 [TENTATIVO 3].ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"CycleGANPaper_no_BreastMask_norm_0_255 [TENTATIVO 3].ipynb","provenance":[],"collapsed_sections":[],"machine_shape":"hm","mount_file_id":"1kNACbyLfW3zblStUgYrEJZ65Pxzvk-Bg","authorship_tag":"ABX9TyO2V2llU89GJJ9DuQYp9XBm"},"kernelspec":{"name":"python3","display_name":"Python 3"},"accelerator":"GPU"},"cells":[{"cell_type":"code","metadata":{"id":"Wuglq78o7BSV","executionInfo":{"status":"ok","timestamp":1603380841065,"user_tz":-120,"elapsed":3751,"user":{"displayName":"Paolo Maione","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8WzXBalf8l5zWT1m3zDN4K8CMQVnssgsQR14FaI8=s64","userId":"02326155032486404430"}},"outputId":"3c111e2c-264a-4ef7-d7eb-c815e91a893a","colab":{"base_uri":"https://localhost:8080/","height":139}},"source":["#DA ESEGUIRE 1 SOLA VOLTA !!!!\n","import os\n","os.chdir(r\"/content/drive/My Drive/TesiUNINA/Colab Notebooks/tentativo3/\") \n","!git clone https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Cloning into 'pytorch-CycleGAN-and-pix2pix'...\n","remote: Enumerating objects: 3, done.\u001b[K\n","remote: Counting objects: 100% (3/3), done.\u001b[K\n","remote: Compressing objects: 100% (3/3), done.\u001b[K\n","remote: Total 2337 (delta 0), reused 2 (delta 0), pack-reused 2334\u001b[K\n","Receiving objects: 100% (2337/2337), 8.09 MiB | 11.50 MiB/s, done.\n","Resolving deltas: 100% (1497/1497), done.\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"AAV94c0y756z","executionInfo":{"status":"ok","timestamp":1604847312307,"user_tz":-60,"elapsed":962,"user":{"displayName":"Paolo Maione","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8WzXBalf8l5zWT1m3zDN4K8CMQVnssgsQR14FaI8=s64","userId":"02326155032486404430"}},"outputId":"4b53eee2-098e-48f9-bf86-c3910acaf348","colab":{"base_uri":"https://localhost:8080/"}},"source":["!nvidia-smi"],"execution_count":1,"outputs":[{"output_type":"stream","text":["Sun Nov  8 14:55:11 2020       \n","+-----------------------------------------------------------------------------+\n","| NVIDIA-SMI 455.32.00    Driver Version: 418.67       CUDA Version: 10.1     |\n","|-------------------------------+----------------------+----------------------+\n","| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. 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Maione","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8WzXBalf8l5zWT1m3zDN4K8CMQVnssgsQR14FaI8=s64","userId":"02326155032486404430"}},"outputId":"20396dfb-7624-497f-93cc-967d1b54a83a","colab":{"base_uri":"https://localhost:8080/"}},"source":["\"\"\"\n","\n","\n","A (source domain), B (target domain).\n","        Generators: G_A: A -> B; G_B: B -> A.\n","        Discriminators: D_A: G_A(A) vs. B; D_B: G_B(B) vs. A.\n","        Forward cycle loss:  lambda_A * ||G_B(G_A(A)) - A|| (Eqn. (2) in the paper)\n","        Backward cycle loss: lambda_B * ||G_A(G_B(B)) - B|| (Eqn. (2) in the paper)\n","        Identity loss (optional): lambda_identity * (||G_A(B) - B|| * lambda_B + ||G_B(A) - A|| * lambda_A) (Sec 5.2 \"Photo generation from paintings\" in the paper)\n","        Dropout is not used in the original CycleGAN paper.\n","\n","\n","\n","\n","epoch: -- current epoch\n","\n","iters: -- current training iteration during this epoch (reset to 0 at the end of every epoch) \n","\n","time: -- current training iteration during this epoch (reset to 0 at the end of every epoch)\n","\n","data: -- data loading time per data point (normalized by batch_size) \n","\n","D_A: GAN loss for discriminator D_A\n","G_A: loss for generators G_A \n","cycle_A: cycle-consistency loss A \n","idt_A: identity loss B \n","\n","D_B: GAN loss for discriminator D_B \n","G_B: loss for generators G_B \n","cycle_B: cycle-consistency loss B \n","idt_B: identity loss B\n","\n","\n","\n","\n","\n","\n","# #epoche\n","# #epochs_decay\n","#dataroot\n","#input_nc\n","#output_nc\n","#norm\n","#no_dropout \n","#dataset_mode\n","#direction\n","#batch size (adesso è 1!)\n","#load_size\n","#crop_size\n","#preprocess\n","# save_latest_freq default 5000\n","# save_epoch_freq default 5\n","\"\"\"\n","import os\n","os.chdir(\"/content/drive/My Drive/TesiUNINA/Colab Notebooks/tentativo3/pytorch-CycleGAN-and-pix2pix\")\n","#!python train.py --dataroot ./datasets/DCE_MRI_breastCancer --batch_size 1 --name DCEMRI_cyclegan --netD n_layers --n_layers_D 2 --model cycle_gan --dataset_mode dceMri --input_nc 1 --output_nc 1 --n_epochs 2 --n_epochs_decay 13 --lr 0.002\n","#!python train.py --dataroot ./datasets/DCE_MRI_breastCancer --batch_size 1 --name DCEMRI_cyclegan --netD n_layers --n_layers_D 2 --model cycle_gan --dataset_mode dceMri --input_nc 1 --output_nc 1 --n_epochs 1 --n_epochs_decay 14 --direction BtoA --lr 0.002\n","\n","\n","#!python train.py --dataroot ./datasets/DCE_MRI_breastCancer_normV1 --batch_size 1 --name DCEMRI_cyclegan --netD n_layers --n_layers_D 2 --model cycle_gan --dataset_mode dceMri --input_nc 1 --output_nc 1 --n_epochs 2 --n_epochs_decay 8 --lr 0.002 --checkpoints_dir './checkpoints_normV1'\n","#!python train.py --dataroot ./datasets/DCE_MRI_breastCancer_normV1 --batch_size 1 --name DCEMRI_cyclegan --netD n_layers --n_layers_D 2 --model cycle_gan --dataset_mode dceMri --input_nc 1 --output_nc 1 --n_epochs 1 --n_epochs_decay 14 --direction BtoA --lr 0.002 --checkpoints_dir './checkpoints_normV1'\n","\n","#!python train.py --dataroot ./datasets/DCE_MRI_breastCancer_normV2 --batch_size 1 --name DCEMRI_cyclegan --netD n_layers --n_layers_D 2 --model cycle_gan --input_nc 1 --output_nc 1 --n_epochs 2 --n_epochs_decay 1 --lr 0.002 --checkpoints_dir './checkpoints_normV2'\n","#CYCLEGAN 30X30\n","#!python train.py --dataroot ./datasets/DCE_MRI_breastCancer_noBM_normV2 --batch_size 1 --name DCEMRI_cyclegan --netD n_layers --n_layers_D 2 --preprocess 'none' --no_flip --display_id 0 --display_winsize 384 --model cycle_gan --input_nc 1 --output_nc 1 --n_epochs 4 --n_epochs_decay 11 --lr 0.002 --checkpoints_dir './checkpoints_noBM_normV2'\n","#CYCLEGAN 70X70\n","!python train.py --dataroot ./datasets/DCE_MRI_breastCancer_noBM_normV2 --batch_size 4 --name DCEMRI_cyclegan --load_size 256 --no_flip --display_id 0 --display_winsize 384 --model cycle_gan --netG unet_256 --input_nc 1 --netD n_layers --n_layers_D 2 --output_nc 1 --n_epochs 10 --n_epochs_decay 30 --lr 0.0002 --checkpoints_dir './checkpoints_noBM_normV2_lr_0_0002'\n"],"execution_count":3,"outputs":[{"output_type":"stream","text":["----------------- Options ---------------\n","               batch_size: 4                             \t[default: 1]\n","                    beta1: 0.5                           \n","          checkpoints_dir: ./checkpoints_noBM_normV2_lr_0_0002\t[default: ./checkpoints]\n","           continue_train: False                         \n","                crop_size: 256                           \n","                 dataroot: ./datasets/DCE_MRI_breastCancer_noBM_normV2\t[default: None]\n","             dataset_mode: unaligned                     \n","                direction: AtoB                          \n","              display_env: main                          \n","             display_freq: 400                           \n","               display_id: 0                             \t[default: 1]\n","            display_ncols: 4                             \n","             display_port: 8097                          \n","           display_server: http://localhost              \n","          display_winsize: 384                           \t[default: 256]\n","                    epoch: latest                        \n","              epoch_count: 1                             \n","                 gan_mode: lsgan                         \n","                  gpu_ids: 0                             \n","                init_gain: 0.02                          \n","                init_type: normal                        \n","                 input_nc: 1                             \t[default: 3]\n","                  isTrain: True                          \t[default: None]\n","                 lambda_A: 10.0                          \n","                 lambda_B: 10.0                          \n","          lambda_identity: 0.5                           \n","                load_iter: 0                             \t[default: 0]\n","                load_size: 256                           \t[default: 286]\n","                       lr: 0.0002                        \n","           lr_decay_iters: 50                            \n","                lr_policy: linear                        \n","         max_dataset_size: inf                           \n","                    model: cycle_gan                     \n","                 n_epochs: 10                            \t[default: 100]\n","           n_epochs_decay: 30                            \t[default: 100]\n","               n_layers_D: 2                             \t[default: 3]\n","                     name: DCEMRI_cyclegan               \t[default: experiment_name]\n","                      ndf: 64                            \n","                     netD: n_layers                      \t[default: basic]\n","                     netG: unet_256                      \t[default: resnet_9blocks]\n","                      ngf: 64                            \n","               no_dropout: True                          \n","                  no_flip: True                          \t[default: False]\n","                  no_html: False                         \n","                     norm: instance                      \n","              num_threads: 4                             \n","                output_nc: 1                             \t[default: 3]\n","                    phase: train                         \n","                pool_size: 50                            \n","               preprocess: resize_and_crop               \n","               print_freq: 100                           \n","             save_by_iter: False                         \n","          save_epoch_freq: 5                             \n","         save_latest_freq: 5000                          \n","           serial_batches: False                         \n","                   suffix:                               \n","         update_html_freq: 1000                          \n","                  verbose: False                         \n","----------------- End -------------------\n","dataset [UnalignedDataset] was created\n","The number of training images = 3712\n","initialize network with normal\n","initialize network with normal\n","initialize network with normal\n","initialize network with normal\n","model [CycleGANModel] was created\n","---------- Networks initialized -------------\n","[Network G_A] Total number of parameters : 54.403 M\n","[Network G_B] Total number of parameters : 54.403 M\n","[Network D_A] Total number of parameters : 0.661 M\n","[Network D_B] Total number of parameters : 0.661 M\n","-----------------------------------------------\n","create web directory ./checkpoints_noBM_normV2_lr_0_0002/DCEMRI_cyclegan/web...\n","/usr/local/lib/python3.6/dist-packages/torch/optim/lr_scheduler.py:136: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`.  Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\n","  \"https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\", UserWarning)\n","learning rate 0.0002000 -> 0.0002000\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","[epoch : 1 ] ---> learning rate= 0.0002\n","\n","End of epoch 1 / 40 \t Time Taken: 1016 sec\n","(epoch: 1, iters: 3712, time: 0.061, data: 0.000) D_A: 0.252 G_A: 0.273 cycle_A: 0.250 idt_A: 0.074 D_B: 0.234 G_B: 0.278 cycle_B: 0.205 idt_B: 0.101 \n","learning rate 0.0002000 -> 0.0002000\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","saving the latest model (epoch 2, total_iters 5000)\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","[epoch : 2 ] ---> learning rate= 0.0002\n","\n","End of epoch 2 / 40 \t Time Taken: 198 sec\n","(epoch: 2, iters: 3712, time: 0.062, data: 0.000) D_A: 0.221 G_A: 0.293 cycle_A: 0.252 idt_A: 0.500 D_B: 0.229 G_B: 0.280 cycle_B: 0.291 idt_B: 0.074 \n","learning rate 0.0002000 -> 0.0002000\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","saving the latest model (epoch 3, total_iters 10000)\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","[epoch : 3 ] ---> learning rate= 0.0002\n","\n","End of epoch 3 / 40 \t Time Taken: 187 sec\n","(epoch: 3, iters: 3712, time: 0.062, data: 0.002) D_A: 0.277 G_A: 0.235 cycle_A: 0.133 idt_A: 0.045 D_B: 0.275 G_B: 0.255 cycle_B: 0.111 idt_B: 0.046 \n","learning rate 0.0002000 -> 0.0002000\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","[epoch : 4 ] ---> learning rate= 0.0002\n","\n","End of epoch 4 / 40 \t Time Taken: 184 sec\n","(epoch: 4, iters: 3712, time: 0.061, data: 0.002) D_A: 0.251 G_A: 0.393 cycle_A: 0.157 idt_A: 0.044 D_B: 0.225 G_B: 0.253 cycle_B: 0.133 idt_B: 0.075 \n","learning rate 0.0002000 -> 0.0002000\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","saving the latest model (epoch 5, total_iters 15000)\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","[epoch : 5 ] ---> learning rate= 0.0002\n","\n","saving the model at the end of epoch 5, iters 18560\n","End of epoch 5 / 40 \t Time Taken: 191 sec\n","(epoch: 5, iters: 3712, time: 0.061, data: 0.002) D_A: 0.254 G_A: 0.258 cycle_A: 0.145 idt_A: 0.034 D_B: 0.253 G_B: 0.257 cycle_B: 0.101 idt_B: 0.056 \n","learning rate 0.0002000 -> 0.0002000\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","saving the latest model (epoch 6, total_iters 20000)\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","[epoch : 6 ] ---> learning rate= 0.0002\n","\n","End of epoch 6 / 40 \t Time Taken: 187 sec\n","(epoch: 6, iters: 3712, time: 0.061, data: 0.002) D_A: 0.243 G_A: 0.245 cycle_A: 0.122 idt_A: 0.027 D_B: 0.254 G_B: 0.350 cycle_B: 0.100 idt_B: 0.045 \n","learning rate 0.0002000 -> 0.0002000\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","saving the latest model (epoch 7, total_iters 25000)\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","[epoch : 7 ] ---> learning rate= 0.0002\n","\n","End of epoch 7 / 40 \t Time Taken: 186 sec\n","(epoch: 7, iters: 3712, time: 0.061, data: 0.002) D_A: 0.222 G_A: 0.325 cycle_A: 0.160 idt_A: 0.066 D_B: 0.222 G_B: 0.287 cycle_B: 0.208 idt_B: 0.053 \n","learning rate 0.0002000 -> 0.0002000\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","[epoch : 8 ] ---> learning rate= 0.0002\n","\n","End of epoch 8 / 40 \t Time Taken: 184 sec\n","(epoch: 8, iters: 3712, time: 0.061, data: 0.002) D_A: 0.213 G_A: 0.412 cycle_A: 0.177 idt_A: 0.032 D_B: 0.198 G_B: 0.191 cycle_B: 0.085 idt_B: 0.050 \n","learning rate 0.0002000 -> 0.0002000\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","saving the latest model (epoch 9, total_iters 30000)\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","[epoch : 9 ] ---> learning rate= 0.0002\n","\n","End of epoch 9 / 40 \t Time Taken: 186 sec\n","(epoch: 9, iters: 3712, time: 0.061, data: 0.002) D_A: 0.240 G_A: 0.191 cycle_A: 0.150 idt_A: 0.040 D_B: 0.248 G_B: 0.299 cycle_B: 0.140 idt_B: 0.046 \n","learning rate 0.0002000 -> 0.0001935\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","saving the latest model (epoch 10, total_iters 35000)\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","[epoch : 10 ] ---> learning rate= 0.00019354838709677422\n","\n","saving the model at the end of epoch 10, iters 37120\n","End of epoch 10 / 40 \t Time Taken: 191 sec\n","(epoch: 10, iters: 3712, time: 0.061, data: 0.002) D_A: 0.221 G_A: 0.261 cycle_A: 0.117 idt_A: 0.029 D_B: 0.235 G_B: 0.276 cycle_B: 0.106 idt_B: 0.037 \n","learning rate 0.0001935 -> 0.0001871\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","saving the latest model (epoch 11, total_iters 40000)\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","[epoch : 11 ] ---> learning rate= 0.00018709677419354842\n","\n","End of epoch 11 / 40 \t Time Taken: 186 sec\n","(epoch: 11, iters: 3712, time: 0.061, data: 0.002) D_A: 0.216 G_A: 0.250 cycle_A: 0.117 idt_A: 0.031 D_B: 0.219 G_B: 0.275 cycle_B: 0.110 idt_B: 0.035 \n","learning rate 0.0001871 -> 0.0001806\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","[epoch : 12 ] ---> learning rate= 0.00018064516129032257\n","\n","End of epoch 12 / 40 \t Time Taken: 184 sec\n","(epoch: 12, iters: 3712, time: 0.061, data: 0.001) D_A: 0.219 G_A: 0.311 cycle_A: 0.122 idt_A: 0.026 D_B: 0.241 G_B: 0.344 cycle_B: 0.091 idt_B: 0.037 \n","learning rate 0.0001806 -> 0.0001742\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","saving the latest model (epoch 13, total_iters 45000)\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","[epoch : 13 ] ---> learning rate= 0.00017419354838709678\n","\n","End of epoch 13 / 40 \t Time Taken: 186 sec\n","(epoch: 13, iters: 3712, time: 0.061, data: 0.002) D_A: 0.194 G_A: 0.238 cycle_A: 0.132 idt_A: 0.027 D_B: 0.248 G_B: 0.225 cycle_B: 0.109 idt_B: 0.038 \n","learning rate 0.0001742 -> 0.0001677\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","saving the latest model (epoch 14, total_iters 50000)\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","[epoch : 14 ] ---> learning rate= 0.00016774193548387098\n","\n","End of epoch 14 / 40 \t Time Taken: 186 sec\n","(epoch: 14, iters: 3712, time: 0.061, data: 0.002) D_A: 0.219 G_A: 0.232 cycle_A: 0.148 idt_A: 0.028 D_B: 0.247 G_B: 0.301 cycle_B: 0.099 idt_B: 0.037 \n","learning rate 0.0001677 -> 0.0001613\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","saving the latest model (epoch 15, total_iters 55000)\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","[epoch : 15 ] ---> learning rate= 0.00016129032258064516\n","\n","saving the model at the end of epoch 15, iters 55680\n","End of epoch 15 / 40 \t Time Taken: 190 sec\n","(epoch: 15, iters: 3712, time: 0.061, data: 0.002) D_A: 0.237 G_A: 0.270 cycle_A: 0.128 idt_A: 0.023 D_B: 0.230 G_B: 0.275 cycle_B: 0.081 idt_B: 0.035 \n","learning rate 0.0001613 -> 0.0001548\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","[epoch : 16 ] ---> learning rate= 0.00015483870967741937\n","\n","End of epoch 16 / 40 \t Time Taken: 184 sec\n","(epoch: 16, iters: 3712, time: 0.061, data: 0.001) D_A: 0.239 G_A: 0.272 cycle_A: 0.135 idt_A: 0.039 D_B: 0.251 G_B: 0.252 cycle_B: 0.137 idt_B: 0.036 \n","learning rate 0.0001548 -> 0.0001484\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","saving the latest model (epoch 17, total_iters 60000)\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","[epoch : 17 ] ---> learning rate= 0.00014838709677419355\n","\n","End of epoch 17 / 40 \t Time Taken: 186 sec\n","(epoch: 17, iters: 3712, time: 0.061, data: 0.002) D_A: 0.276 G_A: 0.157 cycle_A: 0.158 idt_A: 0.037 D_B: 0.241 G_B: 0.280 cycle_B: 0.154 idt_B: 0.045 \n","learning rate 0.0001484 -> 0.0001419\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","saving the latest model (epoch 18, total_iters 65000)\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","[epoch : 18 ] ---> learning rate= 0.00014193548387096775\n","\n","End of epoch 18 / 40 \t Time Taken: 186 sec\n","(epoch: 18, iters: 3712, time: 0.061, data: 0.001) D_A: 0.261 G_A: 0.379 cycle_A: 0.113 idt_A: 0.023 D_B: 0.238 G_B: 0.247 cycle_B: 0.081 idt_B: 0.030 \n","learning rate 0.0001419 -> 0.0001355\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","saving the latest model (epoch 19, total_iters 70000)\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","[epoch : 19 ] ---> learning rate= 0.00013548387096774196\n","\n","End of epoch 19 / 40 \t Time Taken: 186 sec\n","(epoch: 19, iters: 3712, time: 0.061, data: 0.001) D_A: 0.227 G_A: 0.241 cycle_A: 0.112 idt_A: 0.026 D_B: 0.252 G_B: 0.236 cycle_B: 0.082 idt_B: 0.028 \n","learning rate 0.0001355 -> 0.0001290\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","[epoch : 20 ] ---> learning rate= 0.00012903225806451613\n","\n","saving the model at the end of epoch 20, iters 74240\n","End of epoch 20 / 40 \t Time Taken: 188 sec\n","(epoch: 20, iters: 3712, time: 0.061, data: 0.002) D_A: 0.241 G_A: 0.112 cycle_A: 0.096 idt_A: 0.019 D_B: 0.245 G_B: 0.249 cycle_B: 0.064 idt_B: 0.026 \n","learning rate 0.0001290 -> 0.0001226\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","saving the latest model (epoch 21, total_iters 75000)\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","[epoch : 21 ] ---> learning rate= 0.00012258064516129034\n","\n","End of epoch 21 / 40 \t Time Taken: 186 sec\n","(epoch: 21, iters: 3712, time: 0.061, data: 0.002) D_A: 0.271 G_A: 0.239 cycle_A: 0.104 idt_A: 0.021 D_B: 0.240 G_B: 0.245 cycle_B: 0.071 idt_B: 0.025 \n","learning rate 0.0001226 -> 0.0001161\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","saving the latest model (epoch 22, total_iters 80000)\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","[epoch : 22 ] ---> learning rate= 0.0001161290322580645\n","\n","End of epoch 22 / 40 \t Time Taken: 186 sec\n","(epoch: 22, iters: 3712, time: 0.061, data: 0.001) D_A: 0.222 G_A: 0.185 cycle_A: 0.125 idt_A: 0.024 D_B: 0.242 G_B: 0.308 cycle_B: 0.089 idt_B: 0.029 \n","learning rate 0.0001161 -> 0.0001097\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","saving the latest model (epoch 23, total_iters 85000)\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","[epoch : 23 ] ---> learning rate= 0.00010967741935483871\n","\n","End of epoch 23 / 40 \t Time Taken: 186 sec\n","(epoch: 23, iters: 3712, time: 0.061, data: 0.002) D_A: 0.243 G_A: 0.242 cycle_A: 0.127 idt_A: 0.029 D_B: 0.239 G_B: 0.275 cycle_B: 0.102 idt_B: 0.029 \n","learning rate 0.0001097 -> 0.0001032\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","[epoch : 24 ] ---> learning rate= 0.0001032258064516129\n","\n","End of epoch 24 / 40 \t Time Taken: 184 sec\n","(epoch: 24, iters: 3712, time: 0.061, data: 0.002) D_A: 0.278 G_A: 0.251 cycle_A: 0.114 idt_A: 0.025 D_B: 0.238 G_B: 0.249 cycle_B: 0.099 idt_B: 0.027 \n","learning rate 0.0001032 -> 0.0000968\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","saving the latest model (epoch 25, total_iters 90000)\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","[epoch : 25 ] ---> learning rate= 9.677419354838711e-05\n","\n","saving the model at the end of epoch 25, iters 92800\n","End of epoch 25 / 40 \t Time Taken: 190 sec\n","(epoch: 25, iters: 3712, time: 0.061, data: 0.002) D_A: 0.251 G_A: 0.257 cycle_A: 0.104 idt_A: 0.015 D_B: 0.249 G_B: 0.226 cycle_B: 0.050 idt_B: 0.025 \n","learning rate 0.0000968 -> 0.0000903\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","saving the latest model (epoch 26, total_iters 95000)\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","[epoch : 26 ] ---> learning rate= 9.03225806451613e-05\n","\n","End of epoch 26 / 40 \t Time Taken: 187 sec\n","(epoch: 26, iters: 3712, time: 0.061, data: 0.002) D_A: 0.253 G_A: 0.205 cycle_A: 0.105 idt_A: 0.021 D_B: 0.231 G_B: 0.274 cycle_B: 0.073 idt_B: 0.027 \n","learning rate 0.0000903 -> 0.0000839\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","saving the latest model (epoch 27, total_iters 100000)\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","[epoch : 27 ] ---> learning rate= 8.387096774193548e-05\n","\n","End of epoch 27 / 40 \t Time Taken: 186 sec\n","(epoch: 27, iters: 3712, time: 0.061, data: 0.001) D_A: 0.249 G_A: 0.239 cycle_A: 0.113 idt_A: 0.027 D_B: 0.238 G_B: 0.300 cycle_B: 0.114 idt_B: 0.027 \n","learning rate 0.0000839 -> 0.0000774\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","[epoch : 28 ] ---> learning rate= 7.741935483870968e-05\n","\n","End of epoch 28 / 40 \t Time Taken: 184 sec\n","(epoch: 28, iters: 3712, time: 0.061, data: 0.002) D_A: 0.209 G_A: 0.192 cycle_A: 0.097 idt_A: 0.022 D_B: 0.234 G_B: 0.261 cycle_B: 0.082 idt_B: 0.023 \n","learning rate 0.0000774 -> 0.0000710\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","saving the latest model (epoch 29, total_iters 105000)\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 7.096774193548388e-05\n","\n","[epoch : 29 ] ---> learning rate= 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30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","saving the latest model (epoch 30, total_iters 110000)\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","[epoch : 30 ] ---> learning rate= 6.451612903225808e-05\n","\n","saving the model at the end of epoch 30, iters 111360\n","End of epoch 30 / 40 \t Time Taken: 190 sec\n","(epoch: 30, iters: 3712, time: 0.061, data: 0.002) D_A: 0.239 G_A: 0.273 cycle_A: 0.117 idt_A: 0.024 D_B: 0.242 G_B: 0.263 cycle_B: 0.099 idt_B: 0.026 \n","learning rate 0.0000645 -> 0.0000581\n","[epoch : 31 ] ---> learning rate= 5.806451612903225e-05\n","\n","[epoch : 31 ] ---> learning rate= 5.806451612903225e-05\n","\n","[epoch : 31 ] ---> learning rate= 5.806451612903225e-05\n","\n","[epoch : 31 ] ---> learning rate= 5.806451612903225e-05\n","\n","[epoch : 31 ] ---> learning rate= 5.806451612903225e-05\n","\n","[epoch : 31 ] ---> learning rate= 5.806451612903225e-05\n","\n","[epoch : 31 ] ---> learning rate= 5.806451612903225e-05\n","\n","[epoch : 31 ] 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115000)\n","End of epoch 31 / 40 \t Time Taken: 186 sec\n","(epoch: 31, iters: 3712, time: 0.061, data: 0.001) D_A: 0.245 G_A: 0.291 cycle_A: 0.100 idt_A: 0.019 D_B: 0.245 G_B: 0.241 cycle_B: 0.071 idt_B: 0.023 \n","learning rate 0.0000581 -> 0.0000516\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","[epoch : 32 ] ---> learning rate= 5.161290322580645e-05\n","\n","End of epoch 32 / 40 \t Time Taken: 184 sec\n","(epoch: 32, iters: 3712, time: 0.061, data: 0.002) D_A: 0.248 G_A: 0.246 cycle_A: 0.126 idt_A: 0.018 D_B: 0.231 G_B: 0.258 cycle_B: 0.066 idt_B: 0.026 \n","learning rate 0.0000516 -> 0.0000452\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","saving the latest model (epoch 33, total_iters 120000)\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","[epoch : 33 ] ---> learning rate= 4.516129032258065e-05\n","\n","End of epoch 33 / 40 \t Time Taken: 186 sec\n","(epoch: 33, iters: 3712, time: 0.061, data: 0.002) D_A: 0.249 G_A: 0.242 cycle_A: 0.108 idt_A: 0.023 D_B: 0.247 G_B: 0.262 cycle_B: 0.088 idt_B: 0.023 \n","learning rate 0.0000452 -> 0.0000387\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","saving the latest model (epoch 34, total_iters 125000)\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","[epoch : 34 ] ---> learning rate= 3.870967741935485e-05\n","\n","End of epoch 34 / 40 \t Time Taken: 187 sec\n","(epoch: 34, iters: 3712, time: 0.061, data: 0.002) D_A: 0.234 G_A: 0.235 cycle_A: 0.101 idt_A: 0.020 D_B: 0.255 G_B: 0.284 cycle_B: 0.075 idt_B: 0.023 \n","learning rate 0.0000387 -> 0.0000323\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","[epoch : 35 ] ---> learning rate= 3.225806451612903e-05\n","\n","saving the model at the end of epoch 35, iters 129920\n","End of epoch 35 / 40 \t Time Taken: 188 sec\n","(epoch: 35, iters: 3712, time: 0.061, data: 0.002) D_A: 0.260 G_A: 0.237 cycle_A: 0.122 idt_A: 0.018 D_B: 0.254 G_B: 0.268 cycle_B: 0.064 idt_B: 0.025 \n","learning rate 0.0000323 -> 0.0000258\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","saving the latest model (epoch 36, total_iters 130000)\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","[epoch : 36 ] ---> learning rate= 2.5806451612903226e-05\n","\n","End of epoch 36 / 40 \t Time Taken: 186 sec\n","(epoch: 36, iters: 3712, time: 0.061, data: 0.001) D_A: 0.245 G_A: 0.276 cycle_A: 0.096 idt_A: 0.019 D_B: 0.244 G_B: 0.263 cycle_B: 0.050 idt_B: 0.020 \n","learning rate 0.0000258 -> 0.0000194\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","saving the latest model (epoch 37, total_iters 135000)\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","[epoch : 37 ] ---> learning rate= 1.9354838709677424e-05\n","\n","End of epoch 37 / 40 \t Time Taken: 186 sec\n","(epoch: 37, iters: 3712, time: 0.061, data: 0.002) D_A: 0.243 G_A: 0.280 cycle_A: 0.112 idt_A: 0.015 D_B: 0.239 G_B: 0.241 cycle_B: 0.051 idt_B: 0.024 \n","learning rate 0.0000194 -> 0.0000129\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","saving the latest model (epoch 38, total_iters 140000)\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","[epoch : 38 ] ---> learning rate= 1.2903225806451625e-05\n","\n","End of epoch 38 / 40 \t Time Taken: 187 sec\n","(epoch: 38, iters: 3712, time: 0.061, data: 0.002) D_A: 0.230 G_A: 0.269 cycle_A: 0.095 idt_A: 0.018 D_B: 0.246 G_B: 0.264 cycle_B: 0.070 idt_B: 0.019 \n","learning rate 0.0000129 -> 0.0000065\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","[epoch : 39 ] ---> learning rate= 6.451612903225801e-06\n","\n","End of epoch 39 / 40 \t Time Taken: 184 sec\n","(epoch: 39, iters: 3712, time: 0.061, data: 0.002) D_A: 0.241 G_A: 0.253 cycle_A: 0.105 idt_A: 0.017 D_B: 0.243 G_B: 0.264 cycle_B: 0.065 idt_B: 0.021 \n","learning rate 0.0000065 -> 0.0000000\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","saving the latest model (epoch 40, total_iters 145000)\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","[epoch : 40 ] ---> learning rate= 0.0\n","\n","saving the model at the end of epoch 40, iters 148480\n","End of epoch 40 / 40 \t Time Taken: 190 sec\n","(epoch: 40, iters: 3712, time: 0.061, data: 0.002) D_A: 0.241 G_A: 0.256 cycle_A: 0.085 idt_A: 0.017 D_B: 0.242 G_B: 0.269 cycle_B: 0.061 idt_B: 0.018 \n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"ymExMfrj8WGy","executionInfo":{"status":"ok","timestamp":1604867365356,"user_tz":-60,"elapsed":117287,"user":{"displayName":"Paolo Maione","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8WzXBalf8l5zWT1m3zDN4K8CMQVnssgsQR14FaI8=s64","userId":"02326155032486404430"}},"outputId":"35730c24-ccf1-4a6c-a7ab-59daa3995b53","colab":{"base_uri":"https://localhost:8080/"}},"source":["#!python test.py --dataroot ./datasets/DCE_MRI_breastCancer/ --input_nc 1 --output_nc 1 --name DCEMRI_cyclegan --model cycle_gan --netD n_layers --n_layers_D 2 --dataset_mode dceMri --num_test size_testA\n","\n","#!python test.py --dataroot ./datasets/DCE_MRI_breastCancer_normV1 --input_nc 1 --output_nc 1 --name DCEMRI_cyclegan --model cycle_gan --netD n_layers --n_layers_D 2 --dataset_mode dceMri --checkpoints_dir './checkpoints_normV1' --results_dir './results_normV1/' --num_test 388\n","#CYCLEGAN 30X30\n","#!python test.py --dataroot ./datasets/DCE_MRI_breastCancer_noBM_normV2 --input_nc 1 --output_nc 1 --name DCEMRI_cyclegan --model cycle_gan --netD n_layers --n_layers_D 2 --checkpoints_dir './checkpoints_noBM_normV2' --preprocess 'none' --no_flip --display_winsize 384 --results_dir './results_noBM_normV2/' #--num_test 523\n","#CYCLEGAN 70X70\n","!python test.py --dataroot ./datasets/DCE_MRI_breastCancer_noBM_normV2  --netD n_layers --n_layers_D 2 --input_nc 1 --output_nc 1 --name DCEMRI_cyclegan --model cycle_gan --checkpoints_dir './checkpoints_noBM_normV2_lr_0_0002' --load_size 256 --no_flip --netG unet_256 --display_winsize 384 --results_dir './results_noBM_normV2_lr_0_0002/' #--num_test 523\n"],"execution_count":2,"outputs":[{"output_type":"stream","text":["----------------- Options ---------------\n","             aspect_ratio: 1.0                           \n","               batch_size: 1                             \n","          checkpoints_dir: ./checkpoints_noBM_normV2_lr_0_0002\t[default: ./checkpoints]\n","                crop_size: 256                           \n","                 dataroot: ./datasets/DCE_MRI_breastCancer_noBM_normV2\t[default: None]\n","             dataset_mode: unaligned                     \n","                direction: AtoB                          \n","          display_winsize: 384                           \t[default: 256]\n","                    epoch: latest                        \n","                     eval: False                         \n","                  gpu_ids: 0                             \n","                init_gain: 0.02                          \n","                init_type: normal                        \n","                 input_nc: 1                             \t[default: 3]\n","                  isTrain: False                         \t[default: None]\n","                load_iter: 0                             \t[default: 0]\n","                load_size: 256                           \n","         max_dataset_size: inf                           \n","                    model: cycle_gan                     \t[default: test]\n","               n_layers_D: 2                             \t[default: 3]\n","                     name: DCEMRI_cyclegan               \t[default: experiment_name]\n","                      ndf: 64                            \n","                     netD: n_layers                      \t[default: basic]\n","                     netG: unet_256                      \t[default: resnet_9blocks]\n","                      ngf: 64                            \n","               no_dropout: True                          \n","                  no_flip: True                          \t[default: False]\n","                     norm: instance                      \n","                 num_test: 50                            \n","              num_threads: 4                             \n","                output_nc: 1                             \t[default: 3]\n","                    phase: test                          \n","               preprocess: resize_and_crop               \n","              results_dir: ./results_noBM_normV2_lr_0_0002/\t[default: ./results/]\n","           serial_batches: False                         \n","                   suffix:                               \n","                  verbose: False                         \n","----------------- End -------------------\n","dataset [UnalignedDataset] was created\n","initialize network with normal\n","initialize network with normal\n","model [CycleGANModel] was created\n","loading the model from ./checkpoints_noBM_normV2_lr_0_0002/DCEMRI_cyclegan/latest_net_G_A.pth\n","loading the model from ./checkpoints_noBM_normV2_lr_0_0002/DCEMRI_cyclegan/latest_net_G_B.pth\n","---------- Networks initialized -------------\n","[Network G_A] Total number of parameters : 54.403 M\n","[Network G_B] Total number of parameters : 54.403 M\n","-----------------------------------------------\n","creating web directory ./results_noBM_normV2_lr_0_0002/DCEMRI_cyclegan/test_latest\n","processing (0000)-th image... 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