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implement styles extra field

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Vladimir Mandic
2023-10-07 09:59:02 -04:00
parent 8e22fbbdb6
commit 1a984c2827
5 changed files with 82 additions and 19 deletions
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modules/processing.py
+5 -1
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@@ -35,7 +35,7 @@ import modules.sd_models
import modules.sd_vae
import modules.sd_vae_approx
import modules.generation_parameters_copypaste
from modules.sd_hijack_hypertile import context_hypertile_vae, context_hypertile_unet
from modules.sd_hijack_hypertile import context_hypertile_vae, context_hypertile_unet, hypertile_set
opt_C = 4
@@ -639,6 +639,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
if k == 'sd_vae':
modules.sd_vae.reload_vae_weights()
shared.prompt_styles.apply_styles_to_extra(p)
if not shared.opts.cuda_compile:
modules.sd_models.apply_token_merging(p.sd_model, p.get_token_merging_ratio())
modules.sd_hijack_freeu.apply_freeu(p.sd_model, shared.backend == shared.Backend.ORIGINAL)
@@ -1032,6 +1034,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
self.enable_hr = False
self.ops.append('txt2img')
hypertile_set(self)
self.sampler = modules.sd_samplers.create_sampler(self.sampler_name, self.sd_model)
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))
@@ -1243,6 +1246,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
self.image_conditioning = self.img2img_image_conditioning(image, self.init_latent, image_mask)
def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts):
hypertile_set(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)
x *= self.initial_noise_multiplier
samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning, image_conditioning=self.image_conditioning)