From 6b68b590321fcac2ad6d71c5aee1ac02687328d7 Mon Sep 17 00:00:00 2001 From: ljleb Date: Mon, 24 Jul 2023 15:38:52 -0400 Subject: [PATCH] use local vars --- modules/processing.py | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/modules/processing.py b/modules/processing.py index c16404f47..7043477f5 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -722,20 +722,20 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: all_subseeds = p.all_subseeds[:] # apply changes to generation data - all_prompts[n * p.batch_size:(n + 1) * p.batch_size] = p.prompts - all_seeds[n * p.batch_size:(n + 1) * p.batch_size] = p.seeds - all_subseeds[n * p.batch_size:(n + 1) * p.batch_size] = p.subseeds + all_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.prompts + all_seeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.seeds + all_subseeds[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.subseeds # update p.all_negative_prompts in case extensions changed the size of the batch # create_infotext below uses it - old_negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size] - p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size] = p.negative_prompts + old_negative_prompts = p.all_negative_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] + p.all_negative_prompts[iteration * p.batch_size:(iteration + 1) * p.batch_size] = p.negative_prompts try: return create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration, position_in_batch, use_main_prompt) finally: # restore p.all_negative_prompts in case extensions changed the size of the batch - p.all_negative_prompts[n * p.batch_size:n * p.batch_size + len(p.negative_prompts)] = old_negative_prompts + p.all_negative_prompts[iteration * p.batch_size:iteration * p.batch_size + len(p.negative_prompts)] = old_negative_prompts if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings: model_hijack.embedding_db.load_textual_inversion_embeddings()