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Added ip_adapter_strength parameter to adjust weighting of IP-Adapter's added cross-attention layers

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user1 2023-08-29 10:42:42 -07:00
parent f2cd9e9ae2
commit 5a9993772d
2 changed files with 8 additions and 1 deletions
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5
invokeai/app/invocations/latent.py
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@ -216,7 +216,9 @@ class DenoiseLatentsInvocation(BaseInvocation):
default=None,
description=FieldDescriptions.mask,
)
ip_adapter_image: Optional[ImageField] = InputField(input=Input.Connection)
ip_adapter_image: Optional[ImageField] = InputField(input=Input.Connection, title="IP Adapter Image", ui_order=6)
ip_adapter_strength: float = InputField(default=1.0, ge=0, le=2, ui_type=UIType.Float,
title="IP Adapter Strength", ui_order=7)
@validator("cfg_scale")
def ge_one(cls, v):
@ -534,6 +536,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
conditioning_data=conditioning_data,
control_data=control_data, # list[ControlNetData],
ip_adapter_image=unwrapped_ip_adapter_image,
ip_adapter_strength=self.ip_adapter_strength,
callback=step_callback,
)

4
invokeai/backend/stable_diffusion/diffusers_pipeline.py
View File

@ -359,6 +359,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
callback: Callable[[PipelineIntermediateState], None] = None,
control_data: List[ControlNetData] = None,
ip_adapter_image: Optional[PIL.Image] = None,
ip_adapter_strength: float = 1.0,
mask: Optional[torch.Tensor] = None,
masked_latents: Optional[torch.Tensor] = None,
seed: Optional[int] = None,
@ -411,6 +412,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
additional_guidance=additional_guidance,
control_data=control_data,
ip_adapter_image=ip_adapter_image,
ip_adapter_strength=ip_adapter_strength,
callback=callback,
)
finally:
@ -431,6 +433,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
additional_guidance: List[Callable] = None,
control_data: List[ControlNetData] = None,
ip_adapter_image: Optional[PIL.Image] = None,
ip_adapter_strength: float = 1.0,
callback: Callable[[PipelineIntermediateState], None] = None,
):
@ -463,6 +466,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
ip_adapter_model_path, # hardwiring to manually downloaded loc for first pass
"cuda") # hardwiring CUDA GPU for first pass
# IP-Adapter ==> add additional cross-attention layers to UNet model here?
ip_adapter.set_scale(ip_adapter_strength)
print("ip_adapter:", ip_adapter)
# get image embedding from CLIP and ImageProjModel