tidy: remove some traces of ONNX

This commit is contained in:
psychedelicious 2024-02-27 18:49:40 +11:00
parent f0b3485ce9
commit 7d2e840590
4 changed files with 1 additions and 44 deletions

View File

@ -234,37 +234,6 @@ class MainDiffusersConfig(_DiffusersConfig, _MainConfig):
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):
"""Model config for IP Adaptor format models."""
@ -287,7 +256,6 @@ class T2IConfig(ModelConfigBase):
format: Literal[ModelFormat.Diffusers]
_ONNXConfig = Annotated[Union[ONNXSD1Config, ONNXSD2Config, ONNXSDXLConfig], Field(discriminator="base")]
_ControlNetConfig = Annotated[
Union[ControlNetDiffusersConfig, ControlNetCheckpointConfig],
Field(discriminator="format"),

View File

@ -14,7 +14,6 @@ export const MODEL_TYPE_LABELS: { [key: string]: string } = {
t2i_adapter: 'T2I Adapter',
ip_adapter: 'IP Adapter',
clip_vision: 'Clip Vision',
onnx: 'Onnx',
};
export const ModelTypeFilter = () => {

View File

@ -10,9 +10,6 @@ const options: ComboboxOption[] = [
{ value: 'none', label: '-' },
{ value: 'fp16', label: 'fp16' },
{ value: 'fp32', label: 'fp32' },
{ value: 'onnx', label: 'onnx' },
{ value: 'openvino', label: 'openvino' },
{ value: 'flax', label: 'flax' },
];
const RepoVariantSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {

View File

@ -22,14 +22,7 @@ const RESERVED_INPUT_FIELD_NAMES = ['id', 'type', 'use_cache'];
const RESERVED_OUTPUT_FIELD_NAMES = ['type'];
const RESERVED_FIELD_TYPES = ['IsIntermediate'];
const invocationDenylist: string[] = [
'graph',
'linear_ui_output',
'l2i_onnx',
'prompt_onnx',
't2l_onnx',
'onnx_model_loader',
];
const invocationDenylist: string[] = ['graph', 'linear_ui_output'];
const isReservedInputField = (nodeType: string, fieldName: string) => {
if (RESERVED_INPUT_FIELD_NAMES.includes(fieldName)) {