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fix repeating subseeds for every batch #221

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AUTOMATIC 2022-09-10 16:16:18 +03:00
parent df58e0bfff
commit b3311a50dc
1 changed files with 2 additions and 1 deletions
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modules/processing.py
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@ -229,6 +229,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
prompts = all_prompts[n * p.batch_size:(n + 1) * p.batch_size] prompts = all_prompts[n * p.batch_size:(n + 1) * p.batch_size]
seeds = all_seeds[n * p.batch_size:(n + 1) * p.batch_size] seeds = all_seeds[n * p.batch_size:(n + 1) * p.batch_size]
subseeds = all_subseeds[n * p.batch_size:(n + 1) * p.batch_size]
uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt]) uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt])
c = p.sd_model.get_learned_conditioning(prompts) c = p.sd_model.get_learned_conditioning(prompts)
@ -237,7 +238,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
comments += model_hijack.comments comments += model_hijack.comments
# we manually generate all input noises because each one should have a specific seed # we manually generate all input noises because each one should have a specific seed
x = create_random_tensors([opt_C, p.height // opt_f, p.width // opt_f], seeds=seeds, subseeds=all_subseeds, subseed_strength=p.subseed_strength, seed_resize_from_h=p.seed_resize_from_h, seed_resize_from_w=p.seed_resize_from_w) x = create_random_tensors([opt_C, p.height // opt_f, p.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, seed_resize_from_h=p.seed_resize_from_h, seed_resize_from_w=p.seed_resize_from_w)
if p.n_iter > 1: if p.n_iter > 1:
shared.state.job = f"Batch {n+1} out of {p.n_iter}" shared.state.job = f"Batch {n+1} out of {p.n_iter}"