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Add support for T2I-Adapter in node workflows (#4612)

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* Bump diffusers to 0.21.2.

* Add T2IAdapterInvocation boilerplate.

* Add T2I-Adapter model to model-management.

* (minor) Tidy prepare_control_image(...).

* Add logic to run the T2I-Adapter models at the start of the DenoiseLatentsInvocation.

* Add logic for applying T2I-Adapter weights and accumulating.

* Add T2IAdapter to MODEL_CLASSES map.

* yarn typegen

* Add model probes for T2I-Adapter models.

* Add all of the frontend boilerplate required to use T2I-Adapter in the nodes editor.

* Add T2IAdapterModel.convert_if_required(...).

* Fix errors in T2I-Adapter input image sizing logic.

* Fix bug with handling of multiple T2I-Adapters.

* black / flake8

* Fix typo

* yarn build

* Add num_channels param to prepare_control_image(...).

* Link to upstream diffusers bugfix PR that currently requires a workaround.

* feat: Add Color Map Preprocessor

Needed for the color T2I Adapter

* feat: Add Color Map Preprocessor to Linear UI

* Revert "feat: Add Color Map Preprocessor"

This reverts commit a1119a00bf.

* Revert "feat: Add Color Map Preprocessor to Linear UI"

This reverts commit bd8a9b82d8.

* Fix T2I-Adapter field rendering in workflow editor.

* yarn build, yarn typegen

---------

Co-authored-by: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
This commit is contained in:
Ryan Dick
2023-10-05 01:29:16 -04:00
committed by GitHub
parent fbe6452c45
commit 78377469db
32 changed files with 1610 additions and 248 deletions
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42
invokeai/frontend/web/src/services/api/endpoints/models.ts
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@ -6,6 +6,7 @@ import {
CheckpointModelConfig,
ControlNetModelConfig,
IPAdapterModelConfig,
T2IAdapterModelConfig,
DiffusersModelConfig,
ImportModelConfig,
LoRAModelConfig,
@ -41,6 +42,10 @@ export type IPAdapterModelConfigEntity = IPAdapterModelConfig & {
id: string;
};
export type T2IAdapterModelConfigEntity = T2IAdapterModelConfig & {
id: string;
};
export type TextualInversionModelConfigEntity = TextualInversionModelConfig & {
id: string;
};
@ -53,6 +58,7 @@ type AnyModelConfigEntity =
| LoRAModelConfigEntity
| ControlNetModelConfigEntity
| IPAdapterModelConfigEntity
| T2IAdapterModelConfigEntity
| TextualInversionModelConfigEntity
| VaeModelConfigEntity;
@ -145,6 +151,10 @@ export const ipAdapterModelsAdapter =
createEntityAdapter<IPAdapterModelConfigEntity>({
sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
});
export const t2iAdapterModelsAdapter =
createEntityAdapter<T2IAdapterModelConfigEntity>({
sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
});
export const textualInversionModelsAdapter =
createEntityAdapter<TextualInversionModelConfigEntity>({
sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
@ -470,6 +480,37 @@ export const modelsApi = api.injectEndpoints({
);
},
}),
getT2IAdapterModels: build.query<
EntityState<T2IAdapterModelConfigEntity>,
void
>({
query: () => ({ url: 'models/', params: { model_type: 't2i_adapter' } }),
providesTags: (result) => {
const tags: ApiTagDescription[] = [
{ type: 'T2IAdapterModel', id: LIST_TAG },
];
if (result) {
tags.push(
...result.ids.map((id) => ({
type: 'T2IAdapterModel' as const,
id,
}))
);
}
return tags;
},
transformResponse: (response: { models: T2IAdapterModelConfig[] }) => {
const entities = createModelEntities<T2IAdapterModelConfigEntity>(
response.models
);
return t2iAdapterModelsAdapter.setAll(
t2iAdapterModelsAdapter.getInitialState(),
entities
);
},
}),
getVaeModels: build.query<EntityState<VaeModelConfigEntity>, void>({
query: () => ({ url: 'models/', params: { model_type: 'vae' } }),
providesTags: (result) => {
@ -567,6 +608,7 @@ export const {
useGetOnnxModelsQuery,
useGetControlNetModelsQuery,
useGetIPAdapterModelsQuery,
useGetT2IAdapterModelsQuery,
useGetLoRAModelsQuery,
useGetTextualInversionModelsQuery,
useGetVaeModelsQuery,