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fix(nodes): fix t2i adapter model loading

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psychedelicious 2024-02-16 22:51:47 +11:00
parent b7ba65fef4
commit 6df3c450e8
1 changed files with 6 additions and 5 deletions
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11
invokeai/app/invocations/latent.py
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@ -509,19 +509,20 @@ class DenoiseLatentsInvocation(BaseInvocation):
t2i_adapter_data = [] t2i_adapter_data = []
for t2i_adapter_field in t2i_adapter: for t2i_adapter_field in t2i_adapter:
t2i_adapter_model_info = context.models.load(key=t2i_adapter_field.t2i_adapter_model.key) t2i_adapter_model_config = context.models.get_config(key=t2i_adapter_field.t2i_adapter_model.key)
t2i_adapter_loaded_model = context.models.load(key=t2i_adapter_field.t2i_adapter_model.key)
image = context.images.get_pil(t2i_adapter_field.image.image_name) image = context.images.get_pil(t2i_adapter_field.image.image_name)
# The max_unet_downscale is the maximum amount that the UNet model downscales the latent image internally. # The max_unet_downscale is the maximum amount that the UNet model downscales the latent image internally.
if t2i_adapter_model_info.base == BaseModelType.StableDiffusion1: if t2i_adapter_model_config.base == BaseModelType.StableDiffusion1:
max_unet_downscale = 8 max_unet_downscale = 8
elif t2i_adapter_model_info.base == BaseModelType.StableDiffusionXL: elif t2i_adapter_model_config.base == BaseModelType.StableDiffusionXL:
max_unet_downscale = 4 max_unet_downscale = 4
else: else:
raise ValueError(f"Unexpected T2I-Adapter base model type: '{t2i_adapter_model_info.base}'.") raise ValueError(f"Unexpected T2I-Adapter base model type: '{t2i_adapter_model_config.base}'.")
t2i_adapter_model: T2IAdapter t2i_adapter_model: T2IAdapter
with t2i_adapter_model_info as t2i_adapter_model: with t2i_adapter_loaded_model as t2i_adapter_model:
total_downscale_factor = t2i_adapter_model.total_downscale_factor total_downscale_factor = t2i_adapter_model.total_downscale_factor
# Resize the T2I-Adapter input image. # Resize the T2I-Adapter input image.