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tidy: remove some traces of ONNX

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psychedelicious 2024-02-27 18:49:40 +11:00
parent f0b3485ce9
commit 7d2e840590
4 changed files with 1 additions and 44 deletions
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32
invokeai/backend/model_manager/config.py
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@ -234,37 +234,6 @@ class MainDiffusersConfig(_DiffusersConfig, _MainConfig):
type: Literal[ModelType.Main] = ModelType.Main type: Literal[ModelType.Main] = ModelType.Main
class ONNXSD1Config(_MainConfig):
"""Model config for ONNX format models based on sd-1."""
type: Literal[ModelType.ONNX] = ModelType.ONNX
format: Literal[ModelFormat.Onnx, ModelFormat.Olive]
base: Literal[BaseModelType.StableDiffusion1] = BaseModelType.StableDiffusion1
prediction_type: SchedulerPredictionType = SchedulerPredictionType.Epsilon
upcast_attention: bool = False
class ONNXSD2Config(_MainConfig):
"""Model config for ONNX format models based on sd-2."""
type: Literal[ModelType.ONNX] = ModelType.ONNX
format: Literal[ModelFormat.Onnx, ModelFormat.Olive]
# No yaml config file for ONNX, so these are part of config
base: Literal[BaseModelType.StableDiffusion2] = BaseModelType.StableDiffusion2
prediction_type: SchedulerPredictionType = SchedulerPredictionType.VPrediction
upcast_attention: bool = True
class ONNXSDXLConfig(_MainConfig):
"""Model config for ONNX format models based on sdxl."""
type: Literal[ModelType.ONNX] = ModelType.ONNX
format: Literal[ModelFormat.Onnx, ModelFormat.Olive]
# No yaml config file for ONNX, so these are part of config
base: Literal[BaseModelType.StableDiffusionXL] = BaseModelType.StableDiffusionXL
prediction_type: SchedulerPredictionType = SchedulerPredictionType.VPrediction
class IPAdapterConfig(ModelConfigBase): class IPAdapterConfig(ModelConfigBase):
"""Model config for IP Adaptor format models.""" """Model config for IP Adaptor format models."""
@ -287,7 +256,6 @@ class T2IConfig(ModelConfigBase):
format: Literal[ModelFormat.Diffusers] format: Literal[ModelFormat.Diffusers]
_ONNXConfig = Annotated[Union[ONNXSD1Config, ONNXSD2Config, ONNXSDXLConfig], Field(discriminator="base")]
_ControlNetConfig = Annotated[ _ControlNetConfig = Annotated[
Union[ControlNetDiffusersConfig, ControlNetCheckpointConfig], Union[ControlNetDiffusersConfig, ControlNetCheckpointConfig],
Field(discriminator="format"), Field(discriminator="format"),

1
invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
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@ -14,7 +14,6 @@ export const MODEL_TYPE_LABELS: { [key: string]: string } = {
t2i_adapter: 'T2I Adapter', t2i_adapter: 'T2I Adapter',
ip_adapter: 'IP Adapter', ip_adapter: 'IP Adapter',
clip_vision: 'Clip Vision', clip_vision: 'Clip Vision',
onnx: 'Onnx',
}; };
export const ModelTypeFilter = () => { export const ModelTypeFilter = () => {

3
invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/RepoVariantSelect.tsx
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@ -10,9 +10,6 @@ const options: ComboboxOption[] = [
{ value: 'none', label: '-' }, { value: 'none', label: '-' },
{ value: 'fp16', label: 'fp16' }, { value: 'fp16', label: 'fp16' },
{ value: 'fp32', label: 'fp32' }, { value: 'fp32', label: 'fp32' },
{ value: 'onnx', label: 'onnx' },
{ value: 'openvino', label: 'openvino' },
{ value: 'flax', label: 'flax' },
]; ];
const RepoVariantSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => { const RepoVariantSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {

9
invokeai/frontend/web/src/features/nodes/util/schema/parseSchema.ts
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@ -22,14 +22,7 @@ const RESERVED_INPUT_FIELD_NAMES = ['id', 'type', 'use_cache'];
const RESERVED_OUTPUT_FIELD_NAMES = ['type']; const RESERVED_OUTPUT_FIELD_NAMES = ['type'];
const RESERVED_FIELD_TYPES = ['IsIntermediate']; const RESERVED_FIELD_TYPES = ['IsIntermediate'];
const invocationDenylist: string[] = [ const invocationDenylist: string[] = ['graph', 'linear_ui_output'];
'graph',
'linear_ui_output',
'l2i_onnx',
'prompt_onnx',
't2l_onnx',
'onnx_model_loader',
];
const isReservedInputField = (nodeType: string, fieldName: string) => { const isReservedInputField = (nodeType: string, fieldName: string) => {
if (RESERVED_INPUT_FIELD_NAMES.includes(fieldName)) { if (RESERVED_INPUT_FIELD_NAMES.includes(fieldName)) {