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fix for lcm

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This commit is contained in:
yiyixuxu
2025-08-09 01:05:55 +02:00
parent 1bea2d8eea
commit b9d6edef69
1 changed files with 6 additions and 3 deletions
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9
src/diffusers/modular_pipelines/stable_diffusion_xl/before_denoise.py
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@@ -1272,6 +1272,11 @@ class StableDiffusionXLLCMStep(PipelineBlock):
type_hint=int,
description="Number of prompts, the final batch size of model inputs should be batch_size * num_images_per_prompt. Can be generated in input step.",
),
InputParam(
"dtype",
type_hint=torch.dtype,
description="The dtype of the model inputs. Can be generated in input step.",
),
]
@property
@@ -1332,9 +1337,7 @@ class StableDiffusionXLLCMStep(PipelineBlock):
# Optionally get Guidance Scale Embedding for LCM
block_state.timestep_cond = None
guidance_scale_tensor = (
torch.tensor(block_state.embedded_guidance_scale - 1).repeat(final_batch_size).to(device=device)
)
guidance_scale_tensor = torch.tensor(block_state.embedded_guidance_scale - 1).repeat(final_batch_size)
block_state.timestep_cond = self.get_guidance_scale_embedding(
guidance_scale_tensor, embedding_dim=components.unet.config.time_cond_proj_dim
).to(device=device, dtype=dtype)