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Separate conditionings back to positive and negative

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This commit is contained in:
StAlKeR7779 2023-05-05 15:47:51 +03:00
parent 85c33823c3
commit 5012f61599
3 changed files with 18 additions and 8 deletions
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17
invokeai/app/invocations/compel.py
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@ -34,7 +34,8 @@ class CompelOutput(BaseInvocationOutput):
# model: ModelField = Field(default=None, description="Model")
# src? + loras -> tokenizer + text_encoder + loras
# clip: ClipField = Field(default=None, description="Text encoder(clip)")
conditioning: ConditioningField = Field(default=None, description="Conditioning")
positive: ConditioningField = Field(default=None, description="Positive conditioning")
negative: ConditioningField = Field(default=None, description="Negative conditioning")
#fmt: on
@ -133,14 +134,20 @@ class CompelInvocation(BaseInvocation):
cross_attention_control_args=options.get("cross_attention_control", None),
)
name_cond = f"{context.graph_execution_state_id}_{self.id}_conditioning"
name_prefix = f'{context.graph_execution_state_id}__{self.id}'
name_positive = f"{name_prefix}_positive"
name_negative = f"{name_prefix}_negative"
# TODO: hacky but works ;D maybe rename latents somehow?
context.services.latents.set(name_cond, (c, uc, ec))
context.services.latents.set(name_positive, (c, ec))
context.services.latents.set(name_negative, (uc, None))
return CompelOutput(
conditioning=ConditioningField(
conditioning_name=name_cond,
positive=ConditioningField(
conditioning_name=name_positive,
),
negative=ConditioningField(
conditioning_name=name_negative,
),
)

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

@ -144,7 +144,8 @@ class TextToLatentsInvocation(BaseInvocation):
# Inputs
# fmt: off
conditioning: Optional[ConditioningField] = Field(description="Conditioning for generation")
positive: Optional[ConditioningField] = Field(description="Positive conditioning for generation")
negative: Optional[ConditioningField] = Field(description="Negative conditioning for generation")
noise: Optional[LatentsField] = Field(description="The noise to use")
steps: int = Field(default=10, gt=0, description="The number of steps to use to generate the image")
cfg_scale: float = Field(default=7.5, gt=0, description="The Classifier-Free Guidance, higher values may result in a result closer to the prompt", )
@ -203,7 +204,8 @@ class TextToLatentsInvocation(BaseInvocation):
def get_conditioning_data(self, context: InvocationContext, model: StableDiffusionGeneratorPipeline) -> ConditioningData:
c, uc, extra_conditioning_info = context.services.latents.get(self.conditioning.conditioning_name)
c, extra_conditioning_info = context.services.latents.get(self.positive.conditioning_name)
uc, _ = context.services.latents.get(self.negative.conditioning_name)
conditioning_data = ConditioningData(
uc,

3
invokeai/app/services/default_graphs.py
View File

@ -29,7 +29,8 @@ def create_text_to_image() -> LibraryGraph:
Edge(source=EdgeConnection(node_id='seed', field='a'), destination=EdgeConnection(node_id='3', field='seed')),
Edge(source=EdgeConnection(node_id='3', field='noise'), destination=EdgeConnection(node_id='5', field='noise')),
Edge(source=EdgeConnection(node_id='5', field='latents'), destination=EdgeConnection(node_id='6', field='latents')),
Edge(source=EdgeConnection(node_id='4', field='conditioning'), destination=EdgeConnection(node_id='5', field='conditioning')),
Edge(source=EdgeConnection(node_id='4', field='positive'), destination=EdgeConnection(node_id='5', field='positive')),
Edge(source=EdgeConnection(node_id='4', field='negative'), destination=EdgeConnection(node_id='5', field='negative')),
]
),
exposed_inputs=[