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add dataset-level distillation-style regularization

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max
2025-09-18 01:11:19 +03:00
parent b95c17dc17
commit e4ae97e790
2 changed files with 6 additions and 5 deletions
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10
extensions_built_in/sd_trainer/SDTrainer.py
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@@ -1154,6 +1154,11 @@ class SDTrainer(BaseSDTrainProcess):
has_clip_image_embeds = True # we are caching embeds, handle that differently
has_clip_image = False
# do prior pred if prior regularization batch
do_reg_prior = False
if any([batch.file_items[idx].prior_reg for idx in range(len(batch.file_items))]):
do_reg_prior = True
if self.adapter is not None and isinstance(self.adapter, IPAdapter) and not has_clip_image and has_adapter_img:
raise ValueError(
"IPAdapter control image is now 'clip_image_path' instead of 'control_path'. Please update your dataset config ")
@@ -1648,11 +1653,6 @@ class SDTrainer(BaseSDTrainProcess):
prior_pred = None
do_reg_prior = False
# if is_reg and (self.network is not None or self.adapter is not None):
# # we are doing a reg image and we have a network or adapter
# do_reg_prior = True
do_inverted_masked_prior = False
if self.train_config.inverted_mask_prior and batch.mask_tensor is not None:
do_inverted_masked_prior = True

1
toolkit/config_modules.py
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@@ -806,6 +806,7 @@ class DatasetConfig:
self.buckets: bool = kwargs.get('buckets', True)
self.bucket_tolerance: int = kwargs.get('bucket_tolerance', 64)
self.is_reg: bool = kwargs.get('is_reg', False)
self.prior_reg: bool = kwargs.get('prior_reg', False)
self.network_weight: float = float(kwargs.get('network_weight', 1.0))
self.token_dropout_rate: float = float(kwargs.get('token_dropout_rate', 0.0))
self.shuffle_tokens: bool = kwargs.get('shuffle_tokens', False)