diff options
Diffstat (limited to 'modules/processing.py')
| -rw-r--r-- | modules/processing.py | 24 |
1 files changed, 14 insertions, 10 deletions
diff --git a/modules/processing.py b/modules/processing.py index e1b53ac0..2009d3bf 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -543,8 +543,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings:
model_hijack.embedding_db.load_textual_inversion_embeddings()
- _, extra_network_data = extra_networks.parse_prompts(p.all_prompts[0:1])
-
if p.scripts is not None:
p.scripts.process(p)
@@ -582,13 +580,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if shared.opts.live_previews_enable and opts.show_progress_type == "Approx NN":
sd_vae_approx.model()
- if not p.disable_extra_networks:
- extra_networks.activate(p, extra_network_data)
-
- 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 state.job_count == -1:
state.job_count = p.n_iter
@@ -609,11 +600,24 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if len(prompts) == 0:
break
- prompts, _ = extra_networks.parse_prompts(prompts)
+ prompts, extra_network_data = extra_networks.parse_prompts(prompts)
+
+ if not p.disable_extra_networks:
+ with devices.autocast():
+ extra_networks.activate(p, extra_network_data)
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)
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