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process_one
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@@ -509,6 +509,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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if len(prompts) == 0:
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break
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if p.scripts is not None:
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p.scripts.process_one(p)
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with devices.autocast():
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uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps)
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c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps)
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