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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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4
invokeai/backend/stable_diffusion/diffusers_pipeline.py
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@ -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