make it possible for StableDiffusionProcessing to accept multiple different negative prompts in a batch

1 files changed, 24 insertions, 22 deletions

diff --git a/modules/processing.py b/modules/processing.py
index 604d822a..bc7e5311 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -124,6 +124,7 @@ class StableDiffusionProcessing():
         self.scripts = None

         self.script_args = None

         self.all_prompts = None

+        self.all_negative_prompts = None

         self.all_seeds = None

         self.all_subseeds = None

 

@@ -202,7 +203,7 @@ class StableDiffusionProcessing():
 

 

 class Processed:

-    def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None):

+    def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1, info="", subseed=None, all_prompts=None, all_negative_prompts=None, all_seeds=None, all_subseeds=None, index_of_first_image=0, infotexts=None):

         self.images = images_list

         self.prompt = p.prompt

         self.negative_prompt = p.negative_prompt

@@ -241,16 +242,18 @@ class Processed:
         self.subseed = int(self.subseed if type(self.subseed) != list else self.subseed[0]) if self.subseed is not None else -1

         self.is_using_inpainting_conditioning = p.is_using_inpainting_conditioning

 

-        self.all_prompts = all_prompts or [self.prompt]

-        self.all_seeds = all_seeds or [self.seed]

-        self.all_subseeds = all_subseeds or [self.subseed]

+        self.all_prompts = all_prompts or p.all_prompts or [self.prompt]

+        self.all_negative_prompts = all_negative_prompts or p.all_negative_prompts or [self.negative_prompt]

+        self.all_seeds = all_seeds or p.all_seeds or [self.seed]

+        self.all_subseeds = all_subseeds or p.all_subseeds or [self.subseed]

         self.infotexts = infotexts or [info]

 

     def js(self):

         obj = {

-            "prompt": self.prompt,

+            "prompt": self.all_prompts[0],

             "all_prompts": self.all_prompts,

-            "negative_prompt": self.negative_prompt,

+            "negative_prompt": self.all_negative_prompts[0],

+            "all_negative_prompts": self.all_negative_prompts,

             "seed": self.seed,

             "all_seeds": self.all_seeds,

             "subseed": self.subseed,

@@ -411,7 +414,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration
 

     generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None])

 

-    negative_prompt_text = "\nNegative prompt: " + p.negative_prompt if p.negative_prompt else ""

+    negative_prompt_text = "\nNegative prompt: " + p.all_negative_prompts[0] if  p.all_negative_prompts[0] else ""

 

     return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip()

 

@@ -440,10 +443,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     else:

         assert p.prompt is not None

 

-    with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file:

-        processed = Processed(p, [], p.seed, "")

-        file.write(processed.infotext(p, 0))

-

     devices.torch_gc()

 

     seed = get_fixed_seed(p.seed)

@@ -453,15 +452,16 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     modules.sd_hijack.model_hijack.clear_comments()

 

     comments = {}

-    prompt_tmp = p.prompt

-    negative_prompt_tmp = p.negative_prompt

-

-    shared.prompt_styles.apply_styles(p)

 

     if type(p.prompt) == list:

-        p.all_prompts = p.prompt

+        p.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, p.styles) for x in p.prompt]

+    else:

+        p.all_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_styles_to_prompt(p.prompt, p.styles)]

+

+    if type(p.negative_prompt) == list:

+        p.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, p.styles) for x in p.negative_prompt]

     else:

-        p.all_prompts = p.batch_size * p.n_iter * [p.prompt]

+        p.all_negative_prompts = p.batch_size * p.n_iter * [shared.prompt_styles.apply_negative_styles_to_prompt(p.negative_prompt, p.styles)]

 

     if type(seed) == list:

         p.all_seeds = seed

@@ -476,6 +476,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     def infotext(iteration=0, position_in_batch=0):

         return create_infotext(p, p.all_prompts, p.all_seeds, p.all_subseeds, comments, iteration, position_in_batch)

 

+    with open(os.path.join(shared.script_path, "params.txt"), "w", encoding="utf8") as file:

+        processed = Processed(p, [], p.seed, "")

+        file.write(processed.infotext(p, 0))

+

     if os.path.exists(cmd_opts.embeddings_dir) and not p.do_not_reload_embeddings:

         model_hijack.embedding_db.load_textual_inversion_embeddings()

 

@@ -500,6 +504,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                 break

 

             prompts = p.all_prompts[n * p.batch_size:(n + 1) * p.batch_size]

+            negative_prompts = p.all_negative_prompts[n * p.batch_size:(n + 1) * p.batch_size]

             seeds = p.all_seeds[n * p.batch_size:(n + 1) * p.batch_size]

             subseeds = p.all_subseeds[n * p.batch_size:(n + 1) * p.batch_size]

 

@@ -510,7 +515,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                 p.scripts.process_batch(p, batch_number=n, prompts=prompts, seeds=seeds, subseeds=subseeds)

 

             with devices.autocast():

-                uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps)

+                uc = prompt_parser.get_learned_conditioning(shared.sd_model, negative_prompts, p.steps)

                 c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps)

 

             if len(model_hijack.comments) > 0:

@@ -596,14 +601,11 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 

     devices.torch_gc()

 

-    res = Processed(p, output_images, p.all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], all_prompts=p.all_prompts, all_seeds=p.all_seeds, all_subseeds=p.all_subseeds, index_of_first_image=index_of_first_image, infotexts=infotexts)

+    res = Processed(p, output_images, p.all_seeds[0], infotext() + "".join(["\n\n" + x for x in comments]), subseed=p.all_subseeds[0], index_of_first_image=index_of_first_image, infotexts=infotexts)

 

     if p.scripts is not None:

         p.scripts.postprocess(p, res)

 

-    p.prompt = prompt_tmp

-    p.negative_prompt = negative_prompt_tmp

-

     return res