do not touch p.seed/p.subseed during processing #1181
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@ -248,9 +248,16 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
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return x
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def get_fixed_seed(seed):
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if seed is None or seed == '' or seed == -1:
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return int(random.randrange(4294967294))
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return seed
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def fix_seed(p):
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p.seed = int(random.randrange(4294967294)) if p.seed is None or p.seed == '' or p.seed == -1 else p.seed
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p.subseed = int(random.randrange(4294967294)) if p.subseed is None or p.subseed == '' or p.subseed == -1 else p.subseed
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p.seed = get_fixed_seed(p.seed)
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p.subseed = get_fixed_seed(p.subseed)
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def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration=0, position_in_batch=0):
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@ -292,7 +299,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
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devices.torch_gc()
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fix_seed(p)
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seed = get_fixed_seed(p.seed)
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subseed = get_fixed_seed(p.subseed)
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if p.outpath_samples is not None:
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os.makedirs(p.outpath_samples, exist_ok=True)
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@ -311,15 +319,15 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
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else:
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all_prompts = p.batch_size * p.n_iter * [p.prompt]
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if type(p.seed) == list:
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all_seeds = p.seed
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if type(seed) == list:
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all_seeds = seed
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else:
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all_seeds = [int(p.seed) + (x if p.subseed_strength == 0 else 0) for x in range(len(all_prompts))]
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all_seeds = [int(seed) + (x if p.subseed_strength == 0 else 0) for x in range(len(all_prompts))]
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if type(p.subseed) == list:
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all_subseeds = p.subseed
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if type(subseed) == list:
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all_subseeds = subseed
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else:
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all_subseeds = [int(p.subseed) + x for x in range(len(all_prompts))]
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all_subseeds = [int(subseed) + x for x in range(len(all_prompts))]
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def infotext(iteration=0, position_in_batch=0):
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return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch)
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