MultipleInvalid: extra keys not allowed @ data['datasets'][0]['subsets'][1]['is_reg']

For some reason I cannot use `is_reg` parameter for DreamBooth type training.
I'm using the latest [commit](https://github.com/kohya-ss/sd-scripts/commit/0b3e4f7ab62b7c93e66972b7bd2774b8fe679792) from `dev` branch.
My dataset config is the next:
```
[general]
shuffle_caption = false
caption_extension = ".txt"
keep_tokens = 1

# This is a DreamBooth-style dataset
[[datasets]]
resolution = [1024, 1280]
batch_size = 1
enable_bucket = true
bucket_no_upscale = true

[[datasets.subsets]]
image_dir = "/path/to/images/"
conditioning_data_dir = "/path/to/masks/"
num_repeats = 63

[[datasets.subsets]]
is_reg = true
image_dir = "/path/to/reg_images/"
conditioning_data_dir = "/path/to/reg_masks/"
cache_info = true
num_repeats = 1
```

When I hit "Start training" I get the following error:
```
WARNING clip_skip will be unexpected / sdxl_train_util.py:352
SDXL学習ではclip_skipは動作しません
2024-07-16 23:41:45 INFO prepare tokenizers sdxl_train_util.py:138
2024-07-16 23:41:46 INFO update token length: 75 sdxl_train_util.py:163
INFO Load dataset config from sdxl_train.py:133
/srv/shared/mirandakerrProject/SOURCE/KOHYA/combined_d
ataset_dreambooth.toml
WARNING ignore following options because config file is found: sdxl_train.py:137
train_data_dir, in_json /
設定ファイルが利用されるため以下のオプションは無視され
ます: train_data_dir, in_json
ERROR Invalid user config / config_util.py:373
ユーザ設定の形式が正しくないようです
Traceback (most recent call last):
File "/srv/shared/AI/LoraTraining/kohya_ss/sd-scripts/sdxl_train.py", line 948, in
train(args)
File "/srv/shared/AI/LoraTraining/kohya_ss/sd-scripts/sdxl_train.py", line 169, in train
blueprint = blueprint_generator.generate(user_config, args, tokenizer=[tokenizer1, tokenizer2])
File "/srv/shared/AI/LoraTraining/kohya_ss/sd-scripts/library/config_util.py", line 407, in generate
sanitized_user_config = self.sanitizer.sanitize_user_config(user_config)
File "/srv/shared/AI/LoraTraining/kohya_ss/sd-scripts/library/config_util.py", line 370, in sanitize_user_config
return self.user_config_validator(user_config)
File "/srv/shared/AI/LoraTraining/kohya_ss/venv/lib/python3.10/site-packages/voluptuous/schema_builder.py", line 272, in __call__
return self._compiled([], data)
File "/srv/shared/AI/LoraTraining/kohya_ss/venv/lib/python3.10/site-packages/voluptuous/schema_builder.py", line 595, in validate_dict
return base_validate(path, iteritems(data), out)
File "/srv/shared/AI/LoraTraining/kohya_ss/venv/lib/python3.10/site-packages/voluptuous/schema_builder.py", line 433, in validate_mapping
raise er.MultipleInvalid(errors)
voluptuous.error.MultipleInvalid: extra keys not allowed @ data['datasets'][0]['subsets'][1]['is_reg']
E0716 23:41:50.868000 130445689476160 torch/distributed/elastic/multiprocessing/api.py:826] failed (exitcode: 1) local_rank: 0 (pid: 200042) of binary: /srv/shared/AI/LoraTraining/kohya_ss/venv/bin/python
```

However, if I remove `is_reg` option and hit "Start training" I get the following error:
```
INFO 11395 train images with repeating. train_util.py:1678
INFO 0 reg images. train_util.py:1681
WARNING no regularization images / train_util.py:1686
正則化画像が見つかりませんでした
Traceback (most recent call last):
File "/srv/shared/AI/LoraTraining/kohya_ss/sd-scripts/sdxl_train.py", line 948, in
train(args)
File "/srv/shared/AI/LoraTraining/kohya_ss/sd-scripts/sdxl_train.py", line 170, in train
train_dataset_group = config_util.generate_dataset_group_by_blueprint(blueprint.dataset_group)
File "/srv/shared/AI/LoraTraining/kohya_ss/sd-scripts/library/config_util.py", line 487, in generate_dataset_group_by_blueprint
dataset = dataset_klass(subsets=subsets, **asdict(dataset_blueprint.params))
File "/srv/shared/AI/LoraTraining/kohya_ss/sd-scripts/library/train_util.py", line 2038, in __init__
len(missing_imgs) == 0
AssertionError: missing conditioning data for 5662 images / 制御用画像が見つかりませんでした: ['s2_000000001', 's2_000000002', 's2_000000003', 's2_000000004', 's2_000000005', 's2_000000006', 's2_000000007', 's2_000000008', 's2_000000009', 's2_000000010', 's2_000000011', 's2_000000012', 's2_000000013', 's2_000000014', 's2_000000015', 's2_000000016', 's2_000000017', 's2_000000018',
...
```

I can't figure out why `is_reg` parameter is not supported. Any help is really appreciated!

Start with the user-config validation in library/config_util.py and the dataset construction in library/train_util.py, using the traceback and the sdxl_train.py entry point. Compare how the dataset schema handles is_reg, conditioning_data_dir, and regularization subsets, then run the supplied configuration. Done means the configuration validates and training recognizes the regularization and conditioning data without the reported errors.

Written by the indexing model from the issue text.