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feat(nodes): make all ModelIdentifierField inputs accept connections

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This commit is contained in:
psychedelicious 2024-05-17 20:15:04 +10:00
parent 85a5a7c47a
commit fe7ed72c9c
5 changed files with 21 additions and 26 deletions
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5
invokeai/app/invocations/controlnet_image_processors.py
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@ -24,7 +24,6 @@ from pydantic import BaseModel, Field, field_validator, model_validator
from invokeai.app.invocations.fields import (
FieldDescriptions,
ImageField,
Input,
InputField,
OutputField,
UIType,
@ -80,13 +79,13 @@ class ControlOutput(BaseInvocationOutput):
control: ControlField = OutputField(description=FieldDescriptions.control)
@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.1")
@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.2")
class ControlNetInvocation(BaseInvocation):
"""Collects ControlNet info to pass to other nodes"""
image: ImageField = InputField(description="The control image")
control_model: ModelIdentifierField = InputField(
description=FieldDescriptions.controlnet_model, input=Input.Direct, ui_type=UIType.ControlNetModel
description=FieldDescriptions.controlnet_model, ui_type=UIType.ControlNetModel
)
control_weight: Union[float, List[float]] = InputField(
default=1.0, ge=-1, le=2, description="The weight given to the ControlNet"

5
invokeai/app/invocations/ip_adapter.py
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@ -5,7 +5,7 @@ from pydantic import BaseModel, Field, field_validator, model_validator
from typing_extensions import Self
from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, TensorField, UIType
from invokeai.app.invocations.fields import FieldDescriptions, InputField, OutputField, TensorField, UIType
from invokeai.app.invocations.model import ModelIdentifierField
from invokeai.app.invocations.primitives import ImageField
from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
@ -58,7 +58,7 @@ class IPAdapterOutput(BaseInvocationOutput):
CLIP_VISION_MODEL_MAP = {"ViT-H": "ip_adapter_sd_image_encoder", "ViT-G": "ip_adapter_sdxl_image_encoder"}
@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.4.0")
@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.4.1")
class IPAdapterInvocation(BaseInvocation):
"""Collects IP-Adapter info to pass to other nodes."""
@ -67,7 +67,6 @@ class IPAdapterInvocation(BaseInvocation):
ip_adapter_model: ModelIdentifierField = InputField(
description="The IP-Adapter model.",
title="IP-Adapter Model",
input=Input.Direct,
ui_order=-1,
ui_type=UIType.IPAdapterModel,
)

22
invokeai/app/invocations/model.py
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@ -98,14 +98,12 @@ class ModelLoaderOutput(UNetOutput, CLIPOutput, VAEOutput):
title="Main Model",
tags=["model"],
category="model",
version="1.0.2",
version="1.0.3",
)
class MainModelLoaderInvocation(BaseInvocation):
"""Loads a main model, outputting its submodels."""
model: ModelIdentifierField = InputField(
description=FieldDescriptions.main_model, input=Input.Direct, ui_type=UIType.MainModel
)
model: ModelIdentifierField = InputField(description=FieldDescriptions.main_model, ui_type=UIType.MainModel)
# TODO: precision?
def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
@ -134,12 +132,12 @@ class LoRALoaderOutput(BaseInvocationOutput):
clip: Optional[CLIPField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.2")
@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.3")
class LoRALoaderInvocation(BaseInvocation):
"""Apply selected lora to unet and text_encoder."""
lora: ModelIdentifierField = InputField(
description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA", ui_type=UIType.LoRAModel
description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
)
weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
unet: Optional[UNetField] = InputField(
@ -197,12 +195,12 @@ class LoRASelectorOutput(BaseInvocationOutput):
lora: LoRAField = OutputField(description="LoRA model and weight", title="LoRA")
@invocation("lora_selector", title="LoRA Selector", tags=["model"], category="model", version="1.0.0")
@invocation("lora_selector", title="LoRA Selector", tags=["model"], category="model", version="1.0.1")
class LoRASelectorInvocation(BaseInvocation):
"""Selects a LoRA model and weight."""
lora: ModelIdentifierField = InputField(
description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA", ui_type=UIType.LoRAModel
description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
)
weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
@ -273,13 +271,13 @@ class SDXLLoRALoaderOutput(BaseInvocationOutput):
title="SDXL LoRA",
tags=["lora", "model"],
category="model",
version="1.0.2",
version="1.0.3",
)
class SDXLLoRALoaderInvocation(BaseInvocation):
"""Apply selected lora to unet and text_encoder."""
lora: ModelIdentifierField = InputField(
description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA", ui_type=UIType.LoRAModel
description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
)
weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
unet: Optional[UNetField] = InputField(
@ -414,12 +412,12 @@ class SDXLLoRACollectionLoader(BaseInvocation):
return output
@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.2")
@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.3")
class VAELoaderInvocation(BaseInvocation):
"""Loads a VAE model, outputting a VaeLoaderOutput"""
vae_model: ModelIdentifierField = InputField(
description=FieldDescriptions.vae_model, input=Input.Direct, title="VAE", ui_type=UIType.VAEModel
description=FieldDescriptions.vae_model, title="VAE", ui_type=UIType.VAEModel
)
def invoke(self, context: InvocationContext) -> VAEOutput:

10
invokeai/app/invocations/sdxl.py
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@ -1,4 +1,4 @@
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIType
from invokeai.app.invocations.fields import FieldDescriptions, InputField, OutputField, UIType
from invokeai.app.services.shared.invocation_context import InvocationContext
from invokeai.backend.model_manager import SubModelType
@ -30,12 +30,12 @@ class SDXLRefinerModelLoaderOutput(BaseInvocationOutput):
vae: VAEField = OutputField(description=FieldDescriptions.vae, title="VAE")
@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model", version="1.0.2")
@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model", version="1.0.3")
class SDXLModelLoaderInvocation(BaseInvocation):
"""Loads an sdxl base model, outputting its submodels."""
model: ModelIdentifierField = InputField(
description=FieldDescriptions.sdxl_main_model, input=Input.Direct, ui_type=UIType.SDXLMainModel
description=FieldDescriptions.sdxl_main_model, ui_type=UIType.SDXLMainModel
)
# TODO: precision?
@ -67,13 +67,13 @@ class SDXLModelLoaderInvocation(BaseInvocation):
title="SDXL Refiner Model",
tags=["model", "sdxl", "refiner"],
category="model",
version="1.0.2",
version="1.0.3",
)
class SDXLRefinerModelLoaderInvocation(BaseInvocation):
"""Loads an sdxl refiner model, outputting its submodels."""
model: ModelIdentifierField = InputField(
description=FieldDescriptions.sdxl_refiner_model, input=Input.Direct, ui_type=UIType.SDXLRefinerModel
description=FieldDescriptions.sdxl_refiner_model, ui_type=UIType.SDXLRefinerModel
)
# TODO: precision?

5
invokeai/app/invocations/t2i_adapter.py
View File

@ -8,7 +8,7 @@ from invokeai.app.invocations.baseinvocation import (
invocation,
invocation_output,
)
from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField, OutputField, UIType
from invokeai.app.invocations.fields import FieldDescriptions, ImageField, InputField, OutputField, UIType
from invokeai.app.invocations.model import ModelIdentifierField
from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
from invokeai.app.services.shared.invocation_context import InvocationContext
@ -45,7 +45,7 @@ class T2IAdapterOutput(BaseInvocationOutput):
@invocation(
"t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.2"
"t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.3"
)
class T2IAdapterInvocation(BaseInvocation):
"""Collects T2I-Adapter info to pass to other nodes."""
@ -55,7 +55,6 @@ class T2IAdapterInvocation(BaseInvocation):
t2i_adapter_model: ModelIdentifierField = InputField(
description="The T2I-Adapter model.",
title="T2I-Adapter Model",
input=Input.Direct,
ui_order=-1,
ui_type=UIType.T2IAdapterModel,
)