When using masked loss, the console output is confusing as hell.

[iqddd]

When using masked loss, the console output is confusing as hell.
The simplest dataset config:

[[datasets]]

  [[datasets.subsets]]
  conditioning_data_dir = 'E:\\tmp\\masks'
  image_dir = 'E:\\tmp\\train_dataset\\1_foobar_xl'

All other settings are set in the main .toml file (including enable_bucket = true, etc.) Here
In the console, we see something like this:

                    INFO     63 train images with repeating.                                          train_util.py:2010
                    INFO     0 reg images.                                                            train_util.py:2013
                    WARNING  no regularization images / 正則化画像が見つかりませんでした              train_util.py:2018
                    INFO     [Dataset 0]                                                              config_util.py:567
                               batch_size: 4
                               resolution: (1024, 1024)
                               enable_bucket: False
                               network_multiplier: 1.0


2024-11-09 23:41:01 INFO     [Dataset 0]                                                              config_util.py:573
2024-11-09 23:41:06 INFO     loading image sizes.                                                      train_util.py:923
100%|████████████████████████████████████████████████████████████████████████████████| 63/63 [00:00<00:00, 9636.10it/s]
                    INFO     make buckets                                                              train_util.py:946
                    WARNING  min_bucket_reso and max_bucket_reso are ignored if bucket_no_upscale is   train_util.py:963
                             set, because bucket reso is defined by image size automatically /
                             bucket_no_upscaleが指定された場合は、bucketの解像度は画像サイズから自動計
                             算されるため、min_bucket_resoとmax_bucket_resoは無視されます
                    INFO     number of images (including repeats) /                                    train_util.py:992
                             各bucketの画像枚数（繰り返し回数を含む）
                    INFO     bucket 0: resolution (704, 1344), count: 2                                train_util.py:997
                    INFO     bucket 1: resolution (768, 1280), count: 3                                train_util.py:997
                    INFO     bucket 2: resolution (832, 1216), count: 22                               train_util.py:997
                    INFO     bucket 3: resolution (896, 1152), count: 17                               train_util.py:997
                    INFO     bucket 4: resolution (960, 1088), count: 5                                train_util.py:997
                    INFO     bucket 5: resolution (1024, 1024), count: 9                               train_util.py:997
                    INFO     bucket 6: resolution (1088, 960), count: 2                                train_util.py:997
                    INFO     bucket 7: resolution (1152, 896), count: 2                                train_util.py:997
                    INFO     bucket 8: resolution (1216, 832), count: 1                                train_util.py:997
                    INFO     mean ar error (without repeats): 0.0 

enable_bucket: False? No subsets? And then make buckets?
There is no dataset and no captions information in the metadata of the final file either.

[iqddd]

The issue lies in the change of the dataset type from DreamboothDataset to ControlNetDataset. The current implementation of the 'masked loss' functionality appears to be a work-around rather than a fully-fledged solution.