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Fixed bug that prevented using schnell training adapter

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This commit is contained in:
Jaret Burkett
2025-03-19 10:25:12 -06:00
parent b829983b16
commit bbfd6ef0fe
2 changed files with 7 additions and 3 deletions
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4
toolkit/lora_special.py
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@@ -209,7 +209,9 @@ class LoRASpecialNetwork(ToolkitNetworkMixin, LoRANetwork):
ignore_if_contains = [] ignore_if_contains = []
self.ignore_if_contains = ignore_if_contains self.ignore_if_contains = ignore_if_contains
self.transformer_only = transformer_only self.transformer_only = transformer_only
self.base_model_ref = weakref.ref(base_model) self.base_model_ref = None
if base_model is not None:
self.base_model_ref = weakref.ref(base_model)
self.only_if_contains: Union[List, None] = only_if_contains self.only_if_contains: Union[List, None] = only_if_contains

6
toolkit/network_mixins.py
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@@ -547,7 +547,8 @@ class ToolkitNetworkMixin:
save_dict = new_save_dict save_dict = new_save_dict
save_dict = self.base_model_ref().convert_lora_weights_before_save(save_dict) if self.base_model_ref is not None:
save_dict = self.base_model_ref().convert_lora_weights_before_save(save_dict)
return save_dict return save_dict
def save_weights( def save_weights(
@@ -586,7 +587,8 @@ class ToolkitNetworkMixin:
# probably a state dict # probably a state dict
weights_sd = file weights_sd = file
weights_sd = self.base_model_ref().convert_lora_weights_before_load(weights_sd) if self.base_model_ref is not None:
weights_sd = self.base_model_ref().convert_lora_weights_before_load(weights_sd)
load_sd = OrderedDict() load_sd = OrderedDict()
for key, value in weights_sd.items(): for key, value in weights_sd.items():