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fix(nodes): fix t2i adapter model loading (#5731)

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## What type of PR is this? (check all applicable)

- [ ] Refactor
- [ ] Feature
- [x] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission

## Description

Fixes t2i adapter loading

## Merge Plan

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Brandon 2024-02-16 11:17:21 -05:00 committed by GitHub
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11
invokeai/app/invocations/latent.py
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@ -509,19 +509,20 @@ class DenoiseLatentsInvocation(BaseInvocation):
t2i_adapter_data = []
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)
# 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
elif t2i_adapter_model_info.base == BaseModelType.StableDiffusionXL:
elif t2i_adapter_model_config.base == BaseModelType.StableDiffusionXL:
max_unet_downscale = 4
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
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
# Resize the T2I-Adapter input image.