lora: keep parsed network data through pipeline

Signed-off-by: Vladimir Mandic <mandic00@live.com>

modules/control/proc/hed.py

@@ -102,8 +102,8 @@ class HEDdetector:
         if scribble:
             detected_map = nms(detected_map, 127, 3.0)
             detected_map = cv2.GaussianBlur(detected_map, (0, 0), 3.0)
-            detected_map[detected_map > 4] = 255
-            detected_map[detected_map < 255] = 0
+            detected_map[detected_map > 4] = 255 # pylint: disable=unsupported-assignment-operation
+            detected_map[detected_map < 255] = 0 # pylint: disable=unsupported-assignment-operation
         if opts.control_move_processor:
             self.model.to('cpu')
         if output_type == "pil":

modules/extra_networks.py

@@ -168,17 +168,20 @@ def parse_prompt(prompt: str | None) -> tuple[str, defaultdict[str, list[ExtraNe
     return updated_prompt, res
 
 
-def parse_prompts(prompts: list[str], extra_data: defaultdict[str, list[ExtraNetworkParams]] | None = None):
-    updated_prompt_list: list[str] = []
-    extra_data = extra_data or defaultdict(list)
+def parse_prompts(
+    prompts: list[str],
+    extra_data: defaultdict[str, list[ExtraNetworkParams]] | None = None,
+):
+    updated_prompts: list[str] = []
+    if extra_data is None:
+        extra_data = defaultdict(list)
     for prompt in prompts:
         updated_prompt, parsed_extra_data = parse_prompt(prompt)
-        if not extra_data:
-            extra_data = parsed_extra_data
-        elif parsed_extra_data:
-            extra_data = parsed_extra_data
-        else:
-            pass
-        updated_prompt_list.append(updated_prompt)
+        if parsed_extra_data:
+            for key, values in parsed_extra_data.items():
+                for item in values:
+                    if item not in extra_data[key]:
+                        extra_data[key].append(item)
 
-    return updated_prompt_list, extra_data
+        updated_prompts.append(updated_prompt)
+    return updated_prompts, extra_data

modules/ltx/ltx_util.py

@@ -249,7 +249,7 @@ def get_conditions(width, height, condition_strength, condition_images, conditio
 def get_prompts(p):
     prompt = shared.prompt_styles.apply_styles_to_prompt(p.prompt, p.styles)
     negative = shared.prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)
-    prompts, networks = extra_networks.parse_prompts([prompt])
+    prompts, networks = extra_networks.parse_prompts([prompt], p.network_data)
     prompt = prompts[0] if len(prompts) > 0 else prompt
     return prompt, negative, networks
 

modules/processing.py

@@ -510,8 +510,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                 p.scripts.before_process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)
             if not p.prompts:
                 break
-            p.prompts, p.network_data = extra_networks.parse_prompts(p.prompts)
-
+            p.prompts, p.network_data = extra_networks.parse_prompts(p.prompts, p.network_data)
 
             if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
                 p.scripts.process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)

modules/processing_diffusers.py

@@ -307,7 +307,7 @@ def process_hires(p: processing.StableDiffusionProcessing, output):
             sched_eta = p.scheduler_eta if p.scheduler_eta is not None else shared.opts.scheduler_eta
             if len(p.refiner_prompt) > 0:
                 prompts = len(output.images)* [p.refiner_prompt]
-                prompts, p.network_data = extra_networks.parse_prompts(prompts)
+                prompts, p.network_data = extra_networks.parse_prompts(prompts, p.network_data)
                 reset_prompts = True
             if reset_prompts or ('base' in p.skip):
                 extra_networks.activate(p)