fix samplers init

CHANGELOG.md

@@ -133,7 +133,7 @@ or even free speedups and quality improvements (regardless of which workflows yo
   - to enable search, make sure all models have set hash values  
     *Models -> Valida -> Calculate hashes*  
 - **LoRA**
-  - new unified LoRA handler for all LoRA types (lora, lyco, loha, lokr, locon, etc.)  
+  - new unified LoRA handler for all LoRA types (lora, lyco, loha, lokr, locon, ia3, etc.)  
     applies to both original and diffusers backend  
     thanks @AI-Casanova for diffusers port  
   - for *backend:original*, separate lyco handler has been removed  

modules/images.py

@@ -598,7 +598,6 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='jpg', i
         filename = filename[:max_name_len - max(4, len(extension))]
         params.filename = filename + extension
     txt_fullfn = f"{filename}.txt" if shared.opts.save_txt and len(exifinfo) > 0 else None
-
     save_queue.put((params.image, filename, extension, params, exifinfo, txt_fullfn)) # actual save is executed in a thread that polls data from queue
     save_queue.join()
 

modules/processing.py

@@ -1029,7 +1029,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         self.ops.append('txt2img')
         hypertile_set(self)
         self.sampler = modules.sd_samplers.create_sampler(self.sampler_name, self.sd_model)
-        self.sampler.initialize(self)
+        if hasattr(self.sampler, "initialize"):
+            self.sampler.initialize(self)
         x = create_random_tensors([4, self.height // 8, self.width // 8], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
         samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
         if not self.enable_hr or shared.state.interrupted or shared.state.skipped:
@@ -1078,7 +1079,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
                     self.ops.append('hires')
                     devices.torch_gc() # GC now before running the next img2img to prevent running out of memory
                     self.sampler = modules.sd_samplers.create_sampler(self.latent_sampler or self.sampler_name, self.sd_model)
-                    self.sampler.initialize(self)
+                    if hasattr(self.sampler, "initialize"):
+                        self.sampler.initialize(self)
                     samples = samples[:, :, self.truncate_y//2:samples.shape[2]-(self.truncate_y+1)//2, self.truncate_x//2:samples.shape[3]-(self.truncate_x+1)//2]
                     noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, p=self)
                     modules.sd_models.apply_token_merging(self.sd_model, self.get_token_merging_ratio(for_hr=True))
@@ -1134,7 +1136,8 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
         if self.sampler_name == "PLMS":
             self.sampler_name = 'UniPC'
         self.sampler = modules.sd_samplers.create_sampler(self.sampler_name, self.sd_model)
-        self.sampler.initialize(self)
+        if hasattr(self.sampler, "initialize"):
+            self.sampler.initialize(self)
 
         if self.image_mask is not None:
             self.ops.append('inpaint')