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update input for loop blocks, do not need to include intermediate

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yiyixuxu
2025-05-20 18:11:05 +02:00
parent 1b89ac144c
commit d136ae36c8
1 changed files with 0 additions and 28 deletions
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src/diffusers/modular_pipelines/stable_diffusion_xl/denoise.py
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@@ -68,18 +68,11 @@ class StableDiffusionXLDenoiseLoopBeforeDenoiser(PipelineBlock):
),
]
@property
def intermediates_outputs(self) -> List[OutputParam]:
return [OutputParam("scaled_latents", type_hint=torch.Tensor, description="The scaled latents input for denoiser")]
@torch.no_grad()
def __call__(self, components: StableDiffusionXLModularLoader, block_state: BlockState, i: int, t: int):
block_state.scaled_latents = components.scheduler.scale_model_input(block_state.latents, t)
return components, block_state
# loop step (1): prepare latent input for denoiser (with inpainting)
@@ -120,9 +113,6 @@ class StableDiffusionXLInpaintDenoiseLoopBeforeDenoiser(PipelineBlock):
),
]
@property
def intermediates_outputs(self) -> List[OutputParam]:
return [OutputParam("scaled_latents", type_hint=torch.Tensor, description="The scaled latents input for denoiser")]
@staticmethod
def check_inputs(components, block_state):
@@ -187,12 +177,6 @@ class StableDiffusionXLDenoiseLoopDenoiser(PipelineBlock):
@property
def intermediates_inputs(self) -> List[str]:
return [
InputParam(
"scaled_latents",
required=True,
type_hint=torch.Tensor,
description="The prepared latents input to use for the denoiser. Can be generated in latent step within the denoise loop."
),
InputParam(
"num_inference_steps",
required=True,
@@ -319,12 +303,6 @@ class StableDiffusionXLControlNetDenoiseLoopDenoiser(PipelineBlock):
type_hint=List[float],
description="The controlnet keep values to use for the denoising process. Can be generated in prepare_controlnet_inputs step."
),
InputParam(
"scaled_latents",
required=True,
type_hint=torch.Tensor,
description="The prepared latents input to use for the denoiser. Can be generated in latent step within the denoise loop."
),
InputParam(
"timestep_cond",
type_hint=Optional[torch.Tensor],
@@ -492,12 +470,6 @@ class StableDiffusionXLDenoiseLoopAfterDenoiser(PipelineBlock):
def intermediates_inputs(self) -> List[str]:
return [
InputParam("generator"),
InputParam(
"latents",
required=True,
type_hint=torch.Tensor,
description="The initial latents to use for the denoising process. Can be generated in prepare_latent step."
),
]
@property