How to handle this problem?

(epoch: 5, iters: 5000, time: 0.348, data: 0.002) G_GAN: 0.222 D_real: 0.411 D_fake: 0.198 G_rec: 0.092 G_idt: 0.042 G_kl: 1.145 G_path: 0.391 d1: 0.402 d2: 0.252 energy_0: 0.002 energy_3: 0.007 energy_6: 0.111 energy_10: 0.198 energy_14: 1.638 
saving the latest model (epoch 5, total_iters 25000)
santa/FLIR_AtoB/lam0.1_layers0,3,6,10,14_dim8_rec5_idt5.0_pool0_noise1.0_kl0.01
saving the model at the end of epoch 5, iters 25000
Traceback (most recent call last):
  File "/home/customer/Desktop/LT/gan/santa-main/train.py", line 86, in <module>
    results = eval_loader(model, test_loader_a, test_loader_b, opt.run_dir, opt)
  File "/root/usr/anaconda3/envs/mamba/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/home/customer/Desktop/LT/gan/santa-main/models/utils.py", line 88, in eval_loader
    fake = model.translate(data['A'].cuda(), acc_data['A'].cuda())
  File "/root/usr/anaconda3/envs/mamba/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
TypeError: SANTAModel.translate() takes 2 positional arguments but 3 were given

First of all, thank you for your outstanding work. When I was training, I encountered the following error:
Traceback (most recent call last):
File "train.py", line 18, in
fix_b = torch.stack([test_loader_b.dataset[i]['A'] for i in range(opt.display_size)]).cuda()
File "train.py", line 18, in
fix_b = torch.stack([test_loader_b.dataset[i]['A'] for i in range(opt.display_size)]).cuda()
File "E:\Github project\santa-main\data\single_dataset.py", line 33, in getitem
A_path = self.A_paths[index]
IndexError: list index out of range

The training command I used was ’python train.py --dataroot=datasets/multidataset --direction=AtoB --lambda_path=0.1 --tag=santa‘

There are four sub folders under the multidataset folder: trainA, trainB, testA, and testB. The images in the folder are unaligned.

Can you tell me what the problem is?

hello, thanks for your great work.
i am trying to run your code on my own dataset, but there is an error. when i set batch size to a number greater than 1, the training process crashes, whereas, when i set it to 1 it goes fine.

do you know what is the problem?

Error found during validation

saving the latest model (epoch 4, total_iters 5000)
santa/lotus_us_BtoA/lam0.1_layers0,3,6,10,14_dim8_rec5_idt5.0_pool0_noise1.0_kl0.01
(epoch: 4, iters: 858, time: 0.057, data: 0.001) G_GAN: 0.492 D_real: 0.166 D_fake: 0.182 G_rec: 0.063 G_idt: 0.089 G_kl: 1.086 G_path: 0.287 d1: 0.677 d2: 0.487 energy_0: 0.014 energy_3: 0.097 energy_6: 0.327 energy_10: 0.099 energy_14: 0.900
(epoch: 4, iters: 958, time: 0.057, data: 0.001) G_GAN: 0.407 D_real: 0.171 D_fake: 0.218 G_rec: 0.054 G_idt: 0.033 G_kl: 1.418 G_path: 0.226 d1: 0.820 d2: 0.658 energy_0: 0.014 energy_3: 0.116 energy_6: 0.328 energy_10: 0.105 energy_14: 0.566
(epoch: 4, iters: 1058, time: 0.057, data: 0.001) G_GAN: 0.344 D_real: 0.301 D_fake: 0.129 G_rec: 0.056 G_idt: 0.058 G_kl: 1.502 G_path: 0.176 d1: 0.525 d2: 0.371 energy_0: 0.014 energy_3: 0.107 energy_6: 0.362 energy_10: 0.105 energy_14: 0.292
(epoch: 4, iters: 1158, time: 0.057, data: 0.001) G_GAN: 0.407 D_real: 0.256 D_fake: 0.160 G_rec: 0.048 G_idt: 0.036 G_kl: 1.273 G_path: 0.161 d1: 0.188 d2: 0.039 energy_0: 0.016 energy_3: 0.119 energy_6: 0.362 energy_10: 0.103 energy_14: 0.207
(epoch: 4, iters: 1258, time: 0.057, data: 0.001) G_GAN: 0.605 D_real: 0.082 D_fake: 0.069 G_rec: 0.052 G_idt: 0.038 G_kl: 1.347 G_path: 0.389 d1: 0.986 d2: 0.884 energy_0: 0.018 energy_3: 0.198 energy_6: 0.760 energy_10: 0.137 energy_14: 0.831
(epoch: 4, iters: 1358, time: 0.057, data: 0.001) G_GAN: 0.649 D_real: 0.287 D_fake: 0.209 G_rec: 0.046 G_idt: 0.045 G_kl: 1.388 G_path: 0.317 d1: 0.922 d2: 0.772 energy_0: 0.016 energy_3: 0.171 energy_6: 0.618 energy_10: 0.150 energy_14: 0.631
End of epoch 4 / 400 Time Taken: 82 sec
learning rate = 0.0002000
(epoch: 5, iters: 44, time: 0.057, data: 0.001) G_GAN: 0.399 D_real: 0.188 D_fake: 0.151 G_rec: 0.046 G_idt: 0.045 G_kl: 1.519 G_path: 0.190 d1: 0.161 d2: 0.000 energy_0: 0.016 energy_3: 0.111 energy_6: 0.393 energy_10: 0.127 energy_14: 0.305
(epoch: 5, iters: 144, time: 0.057, data: 0.001) G_GAN: 0.418 D_real: 0.354 D_fake: 0.280 G_rec: 0.051 G_idt: 0.038 G_kl: 1.374 G_path: 0.198 d1: 0.237 d2: 0.060 energy_0: 0.016 energy_3: 0.132 energy_6: 0.455 energy_10: 0.137 energy_14: 0.252
(epoch: 5, iters: 244, time: 0.057, data: 0.001) G_GAN: 0.291 D_real: 0.194 D_fake: 0.380 G_rec: 0.035 G_idt: 0.044 G_kl: 1.517 G_path: 0.255 d1: 0.396 d2: 0.240 energy_0: 0.017 energy_3: 0.134 energy_6: 0.423 energy_10: 0.158 energy_14: 0.545
(epoch: 5, iters: 344, time: 0.057, data: 0.001) G_GAN: 0.346 D_real: 0.205 D_fake: 0.207 G_rec: 0.047 G_idt: 0.030 G_kl: 1.311 G_path: 0.199 d1: 0.384 d2: 0.271 energy_0: 0.015 energy_3: 0.122 energy_6: 0.334 energy_10: 0.130 energy_14: 0.395
(epoch: 5, iters: 444, time: 0.057, data: 0.001) G_GAN: 0.343 D_real: 0.340 D_fake: 0.134 G_rec: 0.053 G_idt: 0.043 G_kl: 1.672 G_path: 0.280 d1: 0.786 d2: 0.633 energy_0: 0.015 energy_3: 0.129 energy_6: 0.433 energy_10: 0.157 energy_14: 0.666
(epoch: 5, iters: 544, time: 0.057, data: 0.001) G_GAN: 0.412 D_real: 0.159 D_fake: 0.238 G_rec: 0.057 G_idt: 0.044 G_kl: 1.481 G_path: 0.177 d1: 0.273 d2: 0.113 energy_0: 0.015 energy_3: 0.092 energy_6: 0.274 energy_10: 0.136 energy_14: 0.370
(epoch: 5, iters: 644, time: 0.057, data: 0.001) G_GAN: 0.410 D_real: 0.121 D_fake: 0.418 G_rec: 0.040 G_idt: 0.027 G_kl: 1.325 G_path: 0.220 d1: 0.187 d2: 0.047 energy_0: 0.014 energy_3: 0.092 energy_6: 0.284 energy_10: 0.151 energy_14: 0.559
(epoch: 5, iters: 744, time: 0.057, data: 0.001) G_GAN: 0.265 D_real: 0.302 D_fake: 0.245 G_rec: 0.040 G_idt: 0.056 G_kl: 1.390 G_path: 0.331 d1: 0.837 d2: 0.703 energy_0: 0.014 energy_3: 0.145 energy_6: 0.588 energy_10: 0.154 energy_14: 0.754
(epoch: 5, iters: 844, time: 0.057, data: 0.001) G_GAN: 0.487 D_real: 0.140 D_fake: 0.250 G_rec: 0.054 G_idt: 0.078 G_kl: 1.474 G_path: 0.368 d1: 0.398 d2: 0.211 energy_0: 0.015 energy_3: 0.094 energy_6: 0.308 energy_10: 0.148 energy_14: 1.276
(epoch: 5, iters: 944, time: 0.057, data: 0.001) G_GAN: 0.258 D_real: 0.215 D_fake: 0.233 G_rec: 0.052 G_idt: 0.068 G_kl: 1.583 G_path: 0.251 d1: 0.726 d2: 0.529 energy_0: 0.015 energy_3: 0.111 energy_6: 0.358 energy_10: 0.152 energy_14: 0.619
(epoch: 5, iters: 1044, time: 0.057, data: 0.001) G_GAN: 0.585 D_real: 0.095 D_fake: 0.179 G_rec: 0.049 G_idt: 0.032 G_kl: 1.484 G_path: 0.327 d1: 0.753 d2: 0.610 energy_0: 0.013 energy_3: 0.130 energy_6: 0.434 energy_10: 0.212 energy_14: 0.846
(epoch: 5, iters: 1144, time: 0.057, data: 0.001) G_GAN: 0.445 D_real: 0.186 D_fake: 0.252 G_rec: 0.051 G_idt: 0.030 G_kl: 1.357 G_path: 0.208 d1: 0.984 d2: 0.819 energy_0: 0.013 energy_3: 0.108 energy_6: 0.325 energy_10: 0.157 energy_14: 0.435
(epoch: 5, iters: 1244, time: 0.057, data: 0.001) G_GAN: 0.487 D_real: 0.263 D_fake: 0.048 G_rec: 0.038 G_idt: 0.037 G_kl: 1.577 G_path: 0.239 d1: 0.797 d2: 0.629 energy_0: 0.013 energy_3: 0.097 energy_6: 0.327 energy_10: 0.130 energy_14: 0.627
(epoch: 5, iters: 1344, time: 0.057, data: 0.001) G_GAN: 0.266 D_real: 0.465 D_fake: 0.124 G_rec: 0.033 G_idt: 0.047 G_kl: 1.320 G_path: 0.143 d1: 0.654 d2: 0.502 energy_0: 0.012 energy_3: 0.094 energy_6: 0.294 energy_10: 0.112 energy_14: 0.205
saving the model at the end of epoch 5, iters 7070
Traceback (most recent call last):
File "santa/train.py", line 86, in
results = eval_loader(model, test_loader_a, test_loader_b, opt.run_dir, opt)
File "torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "C1_ML_Analysis/src/santa/models/utils.py", line 88, in eval_loader
fake = model.translate(data['A'].cuda(), acc_data['A'].cuda())
File "torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
TypeError: SANTAModel.translate() takes 2 positional arguments but 3 were given

Hi author,
will you upload the code soon? Thanks!