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bishe 2025-02-26 22:07:06 +08:00
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checkpoints/ROMA_UNSB_001/loss_log.txt
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================ Training Loss (Sun Feb 23 15:46:44 2025) ================
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(epoch: 1, iters: 100, time: 0.155, data: 0.229) G_GAN: 6.946 D_real_ViT: 0.807 D_fake_ViT: 0.309 G: 7.258 SB: 0.056
(epoch: 1, iters: 200, time: 0.174, data: 0.004) G_GAN: 5.494 D_real_ViT: 0.538 D_fake_ViT: 0.287 G: 5.808 SB: 0.054
(epoch: 1, iters: 300, time: 0.185, data: 0.003) G_GAN: 4.615 D_real_ViT: 0.424 D_fake_ViT: 0.302 G: 4.865 SB: 0.073
(epoch: 1, iters: 400, time: 0.191, data: 0.003) G_GAN: 4.170 D_real_ViT: 0.357 D_fake_ViT: 0.315 G: 4.751 SB: 0.055
(epoch: 1, iters: 500, time: 0.196, data: 0.004) G_GAN: 4.437 D_real_ViT: 0.323 D_fake_ViT: 0.265 G: 4.986 SB: 0.062
(epoch: 1, iters: 600, time: 0.199, data: 0.003) G_GAN: 4.024 D_real_ViT: 0.289 D_fake_ViT: 0.252 G: 4.247 SB: 0.073
(epoch: 1, iters: 700, time: 0.202, data: 0.004) G_GAN: 3.999 D_real_ViT: 0.273 D_fake_ViT: 0.232 G: 4.461 SB: 0.058
(epoch: 1, iters: 800, time: 0.204, data: 0.003) G_GAN: 3.754 D_real_ViT: 0.233 D_fake_ViT: 0.241 G: 4.065 SB: 0.054
(epoch: 1, iters: 900, time: 0.205, data: 0.003) G_GAN: 4.083 D_real_ViT: 0.249 D_fake_ViT: 0.207 G: 4.281 SB: 0.059
(epoch: 1, iters: 1000, time: 0.206, data: 0.003) G_GAN: 4.079 D_real_ViT: 0.244 D_fake_ViT: 0.207 G: 4.516 SB: 0.062
(epoch: 1, iters: 1100, time: 0.205, data: 0.005) G_GAN: 3.630 D_real_ViT: 0.212 D_fake_ViT: 0.248 G: 3.740 SB: 0.062
(epoch: 1, iters: 1200, time: 0.207, data: 0.004) G_GAN: 4.639 D_real_ViT: 0.174 D_fake_ViT: 0.159 G: 4.870 SB: 0.058
(epoch: 1, iters: 1300, time: 0.208, data: 0.004) G_GAN: 3.868 D_real_ViT: 0.224 D_fake_ViT: 0.198 G: 4.078 SB: 0.078
(epoch: 1, iters: 1400, time: 0.206, data: 0.003) G_GAN: 3.604 D_real_ViT: 0.170 D_fake_ViT: 0.215 G: 3.819 SB: 0.058
(epoch: 1, iters: 1500, time: 0.206, data: 0.003) G_GAN: 3.718 D_real_ViT: 0.156 D_fake_ViT: 0.199 G: 4.209 SB: 0.057
(epoch: 1, iters: 1600, time: 0.206, data: 0.002) G_GAN: 4.552 D_real_ViT: 0.184 D_fake_ViT: 0.142 G: 4.772 SB: 0.054
(epoch: 1, iters: 1700, time: 0.205, data: 0.003) G_GAN: 3.300 D_real_ViT: 0.189 D_fake_ViT: 0.255 G: 3.759 SB: 0.076
(epoch: 1, iters: 1800, time: 0.204, data: 0.004) G_GAN: 3.840 D_real_ViT: 0.193 D_fake_ViT: 0.185 G: 4.465 SB: 0.073
(epoch: 1, iters: 1900, time: 0.204, data: 0.002) G_GAN: 3.524 D_real_ViT: 0.155 D_fake_ViT: 0.207 G: 4.182 SB: 0.053
(epoch: 1, iters: 2000, time: 0.204, data: 0.003) G_GAN: 3.437 D_real_ViT: 0.169 D_fake_ViT: 0.223 G: 3.529 SB: 0.061
(epoch: 1, iters: 2100, time: 0.204, data: 0.003) G_GAN: 4.786 D_real_ViT: 0.153 D_fake_ViT: 0.132 G: 5.162 SB: 0.061
(epoch: 2, iters: 95, time: 0.203, data: 0.003) G_GAN: 4.433 D_real_ViT: 0.192 D_fake_ViT: 0.147 G: 4.737 SB: 0.054
(epoch: 2, iters: 195, time: 0.204, data: 0.004) G_GAN: 3.592 D_real_ViT: 0.182 D_fake_ViT: 0.199 G: 3.722 SB: 0.054
(epoch: 2, iters: 295, time: 0.204, data: 0.003) G_GAN: 4.473 D_real_ViT: 0.238 D_fake_ViT: 0.133 G: 4.573 SB: 0.062
(epoch: 2, iters: 395, time: 0.203, data: 0.003) G_GAN: 3.919 D_real_ViT: 0.175 D_fake_ViT: 0.172 G: 4.029 SB: 0.076
(epoch: 2, iters: 495, time: 0.204, data: 0.003) G_GAN: 3.096 D_real_ViT: 0.204 D_fake_ViT: 0.234 G: 3.726 SB: 0.054
(epoch: 2, iters: 595, time: 0.202, data: 0.005) G_GAN: 2.927 D_real_ViT: 0.168 D_fake_ViT: 0.254 G: 3.603 SB: 0.059
(epoch: 2, iters: 695, time: 0.204, data: 0.003) G_GAN: 3.383 D_real_ViT: 0.198 D_fake_ViT: 0.209 G: 3.787 SB: 0.054
(epoch: 2, iters: 795, time: 0.205, data: 0.003) G_GAN: 3.755 D_real_ViT: 0.198 D_fake_ViT: 0.185 G: 4.026 SB: 0.075
(epoch: 2, iters: 895, time: 0.205, data: 0.006) G_GAN: 3.717 D_real_ViT: 0.201 D_fake_ViT: 0.170 G: 3.863 SB: 0.062
(epoch: 2, iters: 995, time: 0.208, data: 0.003) G_GAN: 3.538 D_real_ViT: 0.268 D_fake_ViT: 0.182 G: 4.136 SB: 0.054
(epoch: 2, iters: 1095, time: 0.207, data: 0.003) G_GAN: 3.946 D_real_ViT: 0.173 D_fake_ViT: 0.166 G: 4.251 SB: 0.058
(epoch: 2, iters: 1195, time: 0.206, data: 0.003) G_GAN: 4.461 D_real_ViT: 0.162 D_fake_ViT: 0.136 G: 4.591 SB: 0.058
(epoch: 2, iters: 1295, time: 0.205, data: 0.005) G_GAN: 3.981 D_real_ViT: 0.132 D_fake_ViT: 0.158 G: 4.403 SB: 0.054
(epoch: 2, iters: 1395, time: 0.206, data: 0.004) G_GAN: 3.391 D_real_ViT: 0.155 D_fake_ViT: 0.190 G: 3.982 SB: 0.078
(epoch: 2, iters: 1495, time: 0.206, data: 0.005) G_GAN: 3.082 D_real_ViT: 0.264 D_fake_ViT: 0.212 G: 3.343 SB: 0.061
(epoch: 2, iters: 1595, time: 0.206, data: 0.003) G_GAN: 4.052 D_real_ViT: 0.149 D_fake_ViT: 0.153 G: 4.585 SB: 0.058
(epoch: 2, iters: 1695, time: 0.206, data: 0.003) G_GAN: 4.096 D_real_ViT: 0.142 D_fake_ViT: 0.153 G: 4.442 SB: 0.058
(epoch: 2, iters: 1795, time: 0.206, data: 0.003) G_GAN: 2.935 D_real_ViT: 0.337 D_fake_ViT: 0.258 G: 3.227 SB: 0.061
(epoch: 2, iters: 1895, time: 0.205, data: 0.003) G_GAN: 3.350 D_real_ViT: 0.149 D_fake_ViT: 0.214 G: 3.626 SB: 0.057
(epoch: 2, iters: 1995, time: 0.205, data: 0.003) G_GAN: 5.271 D_real_ViT: 0.147 D_fake_ViT: 0.101 G: 5.485 SB: 0.073
(epoch: 2, iters: 2095, time: 0.209, data: 0.003) G_GAN: 4.324 D_real_ViT: 0.171 D_fake_ViT: 0.129 G: 4.600 SB: 0.054
(epoch: 3, iters: 90, time: 0.208, data: 0.003) G_GAN: 3.161 D_real_ViT: 0.242 D_fake_ViT: 0.206 G: 3.435 SB: 0.055
(epoch: 3, iters: 190, time: 0.207, data: 0.003) G_GAN: 4.150 D_real_ViT: 0.264 D_fake_ViT: 0.143 G: 4.741 SB: 0.056
(epoch: 3, iters: 290, time: 0.207, data: 0.003) G_GAN: 5.194 D_real_ViT: 0.268 D_fake_ViT: 0.096 G: 5.567 SB: 0.054
(epoch: 3, iters: 390, time: 0.208, data: 0.004) G_GAN: 4.214 D_real_ViT: 0.126 D_fake_ViT: 0.145 G: 4.984 SB: 0.061
(epoch: 3, iters: 490, time: 0.209, data: 0.003) G_GAN: 4.436 D_real_ViT: 0.283 D_fake_ViT: 0.137 G: 4.779 SB: 0.057
(epoch: 3, iters: 590, time: 0.208, data: 0.003) G_GAN: 4.017 D_real_ViT: 0.162 D_fake_ViT: 0.172 G: 4.254 SB: 0.061
(epoch: 3, iters: 690, time: 0.210, data: 0.006) G_GAN: 3.531 D_real_ViT: 0.100 D_fake_ViT: 0.179 G: 3.961 SB: 0.062
(epoch: 3, iters: 790, time: 0.210, data: 0.003) G_GAN: 3.909 D_real_ViT: 0.325 D_fake_ViT: 0.154 G: 4.414 SB: 0.073
(epoch: 3, iters: 890, time: 0.209, data: 0.006) G_GAN: 5.494 D_real_ViT: 0.221 D_fake_ViT: 0.082 G: 6.089 SB: 0.072
(epoch: 3, iters: 990, time: 0.207, data: 0.003) G_GAN: 4.783 D_real_ViT: 0.165 D_fake_ViT: 0.111 G: 5.441 SB: 0.057
(epoch: 3, iters: 1090, time: 0.207, data: 0.004) G_GAN: 3.759 D_real_ViT: 0.335 D_fake_ViT: 0.166 G: 4.676 SB: 0.056
(epoch: 3, iters: 1190, time: 0.207, data: 0.005) G_GAN: 3.415 D_real_ViT: 0.166 D_fake_ViT: 0.193 G: 4.474 SB: 0.073
(epoch: 3, iters: 1290, time: 0.206, data: 0.003) G_GAN: 3.669 D_real_ViT: 0.204 D_fake_ViT: 0.169 G: 4.728 SB: 0.060
(epoch: 3, iters: 1390, time: 0.205, data: 0.004) G_GAN: 3.358 D_real_ViT: 0.199 D_fake_ViT: 0.187 G: 4.412 SB: 0.055
(epoch: 3, iters: 1490, time: 0.206, data: 0.003) G_GAN: 3.018 D_real_ViT: 0.302 D_fake_ViT: 0.235 G: 4.051 SB: 0.055
(epoch: 3, iters: 1590, time: 0.206, data: 0.005) G_GAN: 4.606 D_real_ViT: 0.168 D_fake_ViT: 0.138 G: 5.547 SB: 0.061
(epoch: 3, iters: 1690, time: 0.205, data: 0.003) G_GAN: 3.548 D_real_ViT: 0.269 D_fake_ViT: 0.195 G: 4.058 SB: 0.071
(epoch: 3, iters: 1790, time: 0.205, data: 0.003) G_GAN: 3.814 D_real_ViT: 0.201 D_fake_ViT: 0.182 G: 4.869 SB: 0.057
(epoch: 3, iters: 1890, time: 0.207, data: 0.003) G_GAN: 3.740 D_real_ViT: 0.238 D_fake_ViT: 0.173 G: 4.679 SB: 0.058
(epoch: 3, iters: 1990, time: 0.206, data: 0.004) G_GAN: 4.623 D_real_ViT: 0.227 D_fake_ViT: 0.129 G: 4.969 SB: 0.071
(epoch: 3, iters: 2090, time: 0.206, data: 0.003) G_GAN: 3.498 D_real_ViT: 0.254 D_fake_ViT: 0.183 G: 4.168 SB: 0.077
(epoch: 4, iters: 85, time: 0.206, data: 0.003) G_GAN: 3.626 D_real_ViT: 0.252 D_fake_ViT: 0.167 G: 4.710 SB: 0.055
(epoch: 4, iters: 185, time: 0.207, data: 0.003) G_GAN: 4.156 D_real_ViT: 0.266 D_fake_ViT: 0.140 G: 4.893 SB: 0.057
(epoch: 4, iters: 285, time: 0.206, data: 0.003) G_GAN: 3.351 D_real_ViT: 0.233 D_fake_ViT: 0.192 G: 4.369 SB: 0.062
(epoch: 4, iters: 385, time: 0.205, data: 0.004) G_GAN: 3.621 D_real_ViT: 0.296 D_fake_ViT: 0.157 G: 4.613 SB: 0.077
(epoch: 4, iters: 485, time: 0.207, data: 0.003) G_GAN: 3.686 D_real_ViT: 0.259 D_fake_ViT: 0.170 G: 4.029 SB: 0.072
(epoch: 4, iters: 585, time: 0.207, data: 0.003) G_GAN: 4.395 D_real_ViT: 0.075 D_fake_ViT: 0.131 G: 4.856 SB: 0.056
(epoch: 4, iters: 685, time: 0.207, data: 0.003) G_GAN: 4.882 D_real_ViT: 0.104 D_fake_ViT: 0.108 G: 5.622 SB: 0.054
(epoch: 4, iters: 785, time: 0.205, data: 0.003) G_GAN: 3.992 D_real_ViT: 0.254 D_fake_ViT: 0.134 G: 4.976 SB: 0.075
(epoch: 4, iters: 885, time: 0.206, data: 0.006) G_GAN: 4.044 D_real_ViT: 0.187 D_fake_ViT: 0.143 G: 5.105 SB: 0.058
(epoch: 4, iters: 985, time: 0.206, data: 0.002) G_GAN: 3.378 D_real_ViT: 0.065 D_fake_ViT: 0.195 G: 3.964 SB: 0.062
(epoch: 4, iters: 1085, time: 0.207, data: 0.003) G_GAN: 3.711 D_real_ViT: 0.184 D_fake_ViT: 0.172 G: 4.842 SB: 0.077
(epoch: 4, iters: 1185, time: 0.207, data: 0.003) G_GAN: 3.574 D_real_ViT: 0.120 D_fake_ViT: 0.186 G: 3.918 SB: 0.070

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checkpoints/ROMA_UNSB_001/train_opt.txt
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----------------- Options ---------------
atten_layers: 5
batch_size: 1
beta1: 0.5
beta2: 0.999
checkpoints_dir: ./checkpoints
continue_train: False
crop_size: 256
dataroot: /home/openxs/kunyu/datasets/InfraredCity-Lite/Double/Moitor [default: placeholder]
dataset_mode: unaligned_double [default: unaligned]
direction: AtoB
display_env: ROMA [default: main]
display_freq: 50
display_id: None
display_ncols: 4
display_port: 8097
display_server: http://localhost
display_winsize: 256
easy_label: experiment_name
epoch: latest
epoch_count: 1
eta_ratio: 0.4
evaluation_freq: 5000
flip_equivariance: True [default: False]
gan_mode: lsgan
gpu_ids: 0
init_gain: 0.02
init_type: xavier
input_nc: 3
isTrain: True [default: None]
lambda_D_ViT: 1.0
lambda_GAN: 1.0
lambda_NCE: 8.0 [default: 1.0]
lambda_SB: 1.0 [default: 0.1]
lambda_ctn: 1.0
lambda_global: 1.0
lambda_inc: 1.0
load_size: 286
lr: 1e-05 [default: 0.0002]
lr_decay_iters: 50
lr_policy: linear
max_dataset_size: inf
model: roma_unsb [default: cut]
n_epochs: 100
n_epochs_decay: 100
n_layers_D: 3
n_mlp: 3
name: ROMA_UNSB_001 [default: experiment_name]
nce_idt: False [default: True]
nce_includes_all_negatives_from_minibatch: False
nce_layers: 0,4,8,12,16
ndf: 64
netD: basic_cond
netF: mlp_sample
netG: resnet_9blocks_cond
ngf: 64
no_antialias: False
no_antialias_up: False
no_dropout: True
no_flip: True [default: False]
no_html: False
normD: instance
normG: instance
num_threads: 4
num_timesteps: 4 [default: 5]
output_nc: 3
phase: train
pool_size: 0
preprocess: resize_and_crop
pretrained_name: None
print_freq: 100
random_scale_max: 3.0
save_by_iter: False
save_epoch_freq: 5
save_latest_freq: 5000
serial_batches: False
stylegan2_G_num_downsampling: 1
suffix:
tau: 0.01
update_html_freq: 1000
use_idt: False
verbose: False
----------------- End -------------------

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<!DOCTYPE html>
<html>
<head>
<title>Experiment name = ROMA_UNSB_001</title>
</head>
<body>
<h3>epoch [4]</h3>
<table border="1" style="table-layout: fixed;">
<tr>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch004_real_A0.png">
<img src="images/epoch004_real_A0.png" style="width:256px">
</a><br>
<p>real_A0</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch004_real_A_noisy.png">
<img src="images/epoch004_real_A_noisy.png" style="width:256px">
</a><br>
<p>real_A_noisy</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch004_fake_B0.png">
<img src="images/epoch004_fake_B0.png" style="width:256px">
</a><br>
<p>fake_B0</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch004_real_B0.png">
<img src="images/epoch004_real_B0.png" style="width:256px">
</a><br>
<p>real_B0</p>
</p>
</td>
</tr>
</table>
<h3>epoch [3]</h3>
<table border="1" style="table-layout: fixed;">
<tr>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch003_real_A0.png">
<img src="images/epoch003_real_A0.png" style="width:256px">
</a><br>
<p>real_A0</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch003_real_A_noisy.png">
<img src="images/epoch003_real_A_noisy.png" style="width:256px">
</a><br>
<p>real_A_noisy</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch003_fake_B0.png">
<img src="images/epoch003_fake_B0.png" style="width:256px">
</a><br>
<p>fake_B0</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch003_real_B0.png">
<img src="images/epoch003_real_B0.png" style="width:256px">
</a><br>
<p>real_B0</p>
</p>
</td>
</tr>
</table>
<h3>epoch [2]</h3>
<table border="1" style="table-layout: fixed;">
<tr>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch002_real_A0.png">
<img src="images/epoch002_real_A0.png" style="width:256px">
</a><br>
<p>real_A0</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch002_real_A_noisy.png">
<img src="images/epoch002_real_A_noisy.png" style="width:256px">
</a><br>
<p>real_A_noisy</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch002_fake_B0.png">
<img src="images/epoch002_fake_B0.png" style="width:256px">
</a><br>
<p>fake_B0</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch002_real_B0.png">
<img src="images/epoch002_real_B0.png" style="width:256px">
</a><br>
<p>real_B0</p>
</p>
</td>
</tr>
</table>
<h3>epoch [1]</h3>
<table border="1" style="table-layout: fixed;">
<tr>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch001_real_A0.png">
<img src="images/epoch001_real_A0.png" style="width:256px">
</a><br>
<p>real_A0</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch001_real_A_noisy.png">
<img src="images/epoch001_real_A_noisy.png" style="width:256px">
</a><br>
<p>real_A_noisy</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch001_fake_B0.png">
<img src="images/epoch001_fake_B0.png" style="width:256px">
</a><br>
<p>fake_B0</p>
</p>
</td>
<td halign="center" style="word-wrap: break-word;" valign="top">
<p>
<a href="images/epoch001_real_B0.png">
<img src="images/epoch001_real_B0.png" style="width:256px">
</a><br>
<p>real_B0</p>
</p>
</td>
</tr>
</table>
</body>
</html>