github/InvokeAI
1
1
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI.git synced 2026-04-23 03:00:31 -04:00
Code Issues Packages Projects Releases Wiki Activity

feat(mm): make config_path optional

Browse Source
This commit is contained in:
psychedelicious
2025-09-23 19:27:29 +10:00
parent f10d0e80a2
commit 9fba676346
4 changed files with 14 additions and 10 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
invokeai/app/invocations/flux_denoise.py
View File

@@ -48,7 +48,7 @@ from invokeai.backend.flux.sampling_utils import (
unpack,
)
from invokeai.backend.flux.text_conditioning import FluxReduxConditioning, FluxTextConditioning
from invokeai.backend.model_manager.taxonomy import ModelFormat, ModelVariantType
from invokeai.backend.model_manager.taxonomy import FluxVariantType, ModelFormat
from invokeai.backend.patches.layer_patcher import LayerPatcher
from invokeai.backend.patches.lora_conversions.flux_lora_constants import FLUX_LORA_TRANSFORMER_PREFIX
from invokeai.backend.patches.model_patch_raw import ModelPatchRaw
@@ -232,7 +232,7 @@ class FluxDenoiseInvocation(BaseInvocation):
)
transformer_config = context.models.get_config(self.transformer.transformer)
is_schnell = "schnell" in getattr(transformer_config, "config_path", "")
is_schnell = transformer_config.variant is FluxVariantType.Schnell
# Calculate the timestep schedule.
timesteps = get_schedule(
@@ -277,7 +277,7 @@ class FluxDenoiseInvocation(BaseInvocation):
# Prepare the extra image conditioning tensor (img_cond) for either FLUX structural control or FLUX Fill.
img_cond: torch.Tensor | None = None
is_flux_fill = transformer_config.variant == ModelVariantType.Inpaint # type: ignore
is_flux_fill = transformer_config.variant is FluxVariantType.DevFill
if is_flux_fill:
img_cond = self._prep_flux_fill_img_cond(
context, device=TorchDevice.choose_torch_device(), dtype=inference_dtype

14
invokeai/backend/model_manager/config.py
View File

@@ -198,7 +198,6 @@ class ModelConfigBase(ABC, BaseModel):
super().__init_subclass__(**kwargs)
if issubclass(cls, LegacyProbeMixin):
ModelConfigBase.USING_LEGACY_PROBE.add(cls)
# Cannot use `elif isinstance(cls, UnknownModelConfig)` because UnknownModelConfig is not defined yet
else:
ModelConfigBase.USING_CLASSIFY_API.add(cls)
@@ -346,11 +345,16 @@ class CheckpointConfigBase(ABC, BaseModel):
"""Base class for checkpoint-style models."""
format: Literal[ModelFormat.Checkpoint, ModelFormat.BnbQuantizednf4b, ModelFormat.GGUFQuantized] = Field(
description="Format of the provided checkpoint model", default=ModelFormat.Checkpoint
description="Format of the provided checkpoint model",
default=ModelFormat.Checkpoint,
)
config_path: str = Field(description="path to the checkpoint model config file")
converted_at: Optional[float] = Field(
description="When this model was last converted to diffusers", default_factory=time.time
config_path: str | None = Field(
description="path to the checkpoint model config file",
default=None,
)
converted_at: float | None = Field(
description="When this model was last converted to diffusers",
default_factory=time.time,
)

2
invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/MainModelPicker.tsx
View File

@@ -27,7 +27,7 @@ export const MainModelPicker = memo(() => {
() =>
selectedModelConfig &&
isCheckpointMainModelConfig(selectedModelConfig) &&
selectedModelConfig.config_path === 'flux-dev',
selectedModelConfig.variant === 'flux_dev',
[selectedModelConfig]
);

2
invokeai/frontend/web/src/features/ui/layouts/InitialStateMainModelPicker.tsx
View File

@@ -26,7 +26,7 @@ export const InitialStateMainModelPicker = memo(() => {
() =>
selectedModelConfig &&
isCheckpointMainModelConfig(selectedModelConfig) &&
selectedModelConfig.config_path === 'flux-dev',
selectedModelConfig.variant === 'flux_dev',
[selectedModelConfig]
);