InvokeAI/invokeai/app/invocations/t2i_adapter.py

Ignoring revisions in .git-blame-ignore-revs. Click here to bypass and see the normal blame view.

97 lines
3.8 KiB
Python
Raw Permalink Normal View History

from typing import Union
from pydantic import BaseModel, Field, field_validator, model_validator
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
BaseInvocationOutput,
invocation,
invocation_output,
)
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
from invokeai.app.util.controlnet_utils import CONTROLNET_RESIZE_VALUES
class T2IAdapterField(BaseModel):
image: ImageField = Field(description="The T2I-Adapter image prompt.")
t2i_adapter_model: ModelIdentifierField = Field(description="The T2I-Adapter model to use.")
weight: Union[float, list[float]] = Field(default=1, description="The weight given to the T2I-Adapter")
begin_step_percent: float = Field(
default=0, ge=0, le=1, description="When the T2I-Adapter is first applied (% of total steps)"
)
end_step_percent: float = Field(
default=1, ge=0, le=1, description="When the T2I-Adapter is last applied (% of total steps)"
)
resize_mode: CONTROLNET_RESIZE_VALUES = Field(default="just_resize", description="The resize mode to use")
@field_validator("weight")
@classmethod
def validate_ip_adapter_weight(cls, v):
validate_weights(v)
return v
@model_validator(mode="after")
def validate_begin_end_step_percent(self):
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
return self
@invocation_output("t2i_adapter_output")
class T2IAdapterOutput(BaseInvocationOutput):
t2i_adapter: T2IAdapterField = OutputField(description=FieldDescriptions.t2i_adapter, title="T2I Adapter")
@invocation(
"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."""
# Inputs
image: ImageField = InputField(description="The IP-Adapter image prompt.")
t2i_adapter_model: ModelIdentifierField = InputField(
description="The T2I-Adapter model.",
title="T2I-Adapter Model",
ui_order=-1,
ui_type=UIType.T2IAdapterModel,
)
weight: Union[float, list[float]] = InputField(
feat(ui): add support for custom field types Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported. Two notes: 1. Your field type's class name must be unique. Suggest prefixing fields with something related to the node pack as a kind of namespace. 2. Custom field types function as connection-only fields. For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type. This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection. feat(ui): fix tooltips for custom types We need to hold onto the original type of the field so they don't all just show up as "Unknown". fix(ui): fix ts error with custom fields feat(ui): custom field types connection validation In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic. *Actually, it was `"Unknown"`, but I changed it to custom for clarity. Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields. To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`. This ended up needing a bit of fanagling: - If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property. While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer. (Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.) - Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future. - We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`. Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`. This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent. fix(ui): typo feat(ui): add CustomCollection and CustomPolymorphic field types feat(ui): add validation for CustomCollection & CustomPolymorphic types - Update connection validation for custom types - Use simple string parsing to determine if a field is a collection or polymorphic type. - No longer need to keep a list of collection and polymorphic types. - Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing chore(ui): remove errant console.log fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType' This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type. fix(ui): fix ts error feat(nodes): add runtime check for custom field names "Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names. chore(ui): add TODO for revising field type names wip refactor fieldtype structured wip refactor field types wip refactor types wip refactor types fix node layout refactor field types chore: mypy organisation organisation organisation fix(nodes): fix field orig_required, field_kind and input statuses feat(nodes): remove broken implementation of default_factory on InputField Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args. Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used. Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`. fix(nodes): fix InputField name validation workflow validation validation chore: ruff feat(nodes): fix up baseinvocation comments fix(ui): improve typing & logic of buildFieldInputTemplate improved error handling in parseFieldType fix: back compat for deprecated default_factory and UIType feat(nodes): do not show node packs loaded log if none loaded chore(ui): typegen
2023-11-17 00:32:35 +00:00
default=1, ge=0, description="The weight given to the T2I-Adapter", title="Weight"
)
begin_step_percent: float = InputField(
default=0, ge=0, le=1, description="When the T2I-Adapter is first applied (% of total steps)"
)
end_step_percent: float = InputField(
default=1, ge=0, le=1, description="When the T2I-Adapter is last applied (% of total steps)"
)
resize_mode: CONTROLNET_RESIZE_VALUES = InputField(
default="just_resize",
description="The resize mode applied to the T2I-Adapter input image so that it matches the target output size.",
)
@field_validator("weight")
@classmethod
def validate_ip_adapter_weight(cls, v):
validate_weights(v)
return v
@model_validator(mode="after")
def validate_begin_end_step_percent(self):
validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
return self
def invoke(self, context: InvocationContext) -> T2IAdapterOutput:
return T2IAdapterOutput(
t2i_adapter=T2IAdapterField(
image=self.image,
t2i_adapter_model=self.t2i_adapter_model,
weight=self.weight,
begin_step_percent=self.begin_step_percent,
end_step_percent=self.end_step_percent,
resize_mode=self.resize_mode,
)
)