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-rw-r--r--modules/processing.py14
1 files changed, 11 insertions, 3 deletions
diff --git a/modules/processing.py b/modules/processing.py
index e4b989d4..269a1a9f 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -580,9 +580,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if shared.opts.live_previews_enable and opts.show_progress_type == "Approx NN":
sd_vae_approx.model()
- with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file:
- processed = Processed(p, [], p.seed, "")
- file.write(processed.infotext(p, 0))
+ if not p.disable_extra_networks:
+ extra_networks.activate(p, extra_network_data)
if state.job_count == -1:
state.job_count = p.n_iter
@@ -613,6 +612,15 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
if p.scripts is not None:
p.scripts.process_batch(p, batch_number=n, prompts=prompts, seeds=seeds, subseeds=subseeds)
+ # params.txt should be saved after scripts.process_batch, since the
+ # infotext could be modified by that callback
+ # Example: a wildcard processed by process_batch sets an extra model
+ # strength, which is saved as "Model Strength: 1.0" in the infotext
+ if n == 0:
+ with open(os.path.join(paths.data_path, "params.txt"), "w", encoding="utf8") as file:
+ processed = Processed(p, [], p.seed, "")
+ file.write(processed.infotext(p, 0))
+
uc = get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, p.steps, cached_uc)
c = get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, p.steps, cached_c)