diff options
Diffstat (limited to 'modules/processing.py')
| -rw-r--r-- | modules/processing.py | 50 |
1 files changed, 36 insertions, 14 deletions
diff --git a/modules/processing.py b/modules/processing.py index 8180c63d..f773a30e 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -11,9 +11,8 @@ import cv2 from skimage import exposure
import modules.sd_hijack
-from modules import devices, prompt_parser, masking
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram
from modules.sd_hijack import model_hijack
-from modules.sd_samplers import samplers, samplers_for_img2img
from modules.shared import opts, cmd_opts, state
import modules.shared as shared
import modules.face_restoration
@@ -84,7 +83,7 @@ class StableDiffusionProcessing: self.s_tmin = opts.s_tmin
self.s_tmax = float('inf') # not representable as a standard ui option
self.s_noise = opts.s_noise
-
+
if not seed_enable_extras:
self.subseed = -1
self.subseed_strength = 0
@@ -110,7 +109,7 @@ class Processed: self.width = p.width
self.height = p.height
self.sampler_index = p.sampler_index
- self.sampler = samplers[p.sampler_index].name
+ self.sampler = sd_samplers.samplers[p.sampler_index].name
self.cfg_scale = p.cfg_scale
self.steps = p.steps
self.batch_size = p.batch_size
@@ -122,6 +121,8 @@ class Processed: self.denoising_strength = getattr(p, 'denoising_strength', None)
self.extra_generation_params = p.extra_generation_params
self.index_of_first_image = index_of_first_image
+ self.styles = p.styles
+ self.job_timestamp = state.job_timestamp
self.eta = p.eta
self.ddim_discretize = p.ddim_discretize
@@ -166,6 +167,8 @@ class Processed: "extra_generation_params": self.extra_generation_params,
"index_of_first_image": self.index_of_first_image,
"infotexts": self.infotexts,
+ "styles": self.styles,
+ "job_timestamp": self.job_timestamp,
}
return json.dumps(obj)
@@ -265,7 +268,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments, iteration generation_params = {
"Steps": p.steps,
- "Sampler": samplers[p.sampler_index].name,
+ "Sampler": sd_samplers.samplers[p.sampler_index].name,
"CFG scale": p.cfg_scale,
"Seed": all_seeds[index],
"Face restoration": (opts.face_restoration_model if p.restore_faces else None),
@@ -296,7 +299,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed: assert(len(p.prompt) > 0)
else:
assert p.prompt is not None
-
+
devices.torch_gc()
seed = get_fixed_seed(p.seed)
@@ -359,8 +362,8 @@ def process_images(p: StableDiffusionProcessing) -> Processed: #uc = p.sd_model.get_learned_conditioning(len(prompts) * [p.negative_prompt])
#c = p.sd_model.get_learned_conditioning(prompts)
with devices.autocast():
- uc = prompt_parser.get_learned_conditioning(len(prompts) * [p.negative_prompt], p.steps)
- c = prompt_parser.get_learned_conditioning(prompts, p.steps)
+ uc = prompt_parser.get_learned_conditioning(shared.sd_model, len(prompts) * [p.negative_prompt], p.steps)
+ c = prompt_parser.get_multicond_learned_conditioning(shared.sd_model, prompts, p.steps)
if len(model_hijack.comments) > 0:
for comment in model_hijack.comments:
@@ -383,6 +386,13 @@ def process_images(p: StableDiffusionProcessing) -> Processed: x_samples_ddim = p.sd_model.decode_first_stage(samples_ddim)
x_samples_ddim = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)
+ del samples_ddim
+
+ if shared.cmd_opts.lowvram or shared.cmd_opts.medvram:
+ lowvram.send_everything_to_cpu()
+
+ devices.torch_gc()
+
if opts.filter_nsfw:
import modules.safety as safety
x_samples_ddim = modules.safety.censor_batch(x_samples_ddim)
@@ -424,9 +434,15 @@ def process_images(p: StableDiffusionProcessing) -> Processed: if opts.samples_save and not p.do_not_save_samples:
images.save_image(image, p.outpath_samples, "", seeds[i], prompts[i], opts.samples_format, info=infotext(n, i), p=p)
- infotexts.append(infotext(n, i))
+ text = infotext(n, i)
+ infotexts.append(text)
+ image.info["parameters"] = text
output_images.append(image)
+ del x_samples_ddim
+
+ devices.torch_gc()
+
state.nextjob()
p.color_corrections = None
@@ -437,7 +453,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed: grid = images.image_grid(output_images, p.batch_size)
if opts.return_grid:
- infotexts.insert(0, infotext())
+ text = infotext()
+ infotexts.insert(0, text)
+ grid.info["parameters"] = text
output_images.insert(0, grid)
index_of_first_image = 1
@@ -478,7 +496,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.firstphase_height_truncated = int(scale * self.height)
def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
- self.sampler = samplers[self.sampler_index].constructor(self.sd_model)
+ self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model)
if not self.enable_hr:
x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], 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)
@@ -521,13 +539,14 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): shared.state.nextjob()
- self.sampler = samplers[self.sampler_index].constructor(self.sd_model)
+ self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, self.sampler_index, self.sd_model)
+
noise = create_random_tensors(samples.shape[1:], seeds=seeds, subseeds=subseeds, subseed_strength=subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self)
# GC now before running the next img2img to prevent running out of memory
x = None
devices.torch_gc()
-
+
samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.steps)
return samples
@@ -556,7 +575,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): self.nmask = None
def init(self, all_prompts, all_seeds, all_subseeds):
- self.sampler = samplers_for_img2img[self.sampler_index].constructor(self.sd_model)
+ self.sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers_for_img2img, self.sampler_index, self.sd_model)
crop_region = None
if self.image_mask is not None:
@@ -663,4 +682,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): if self.mask is not None:
samples = samples * self.nmask + self.init_latent * self.mask
+ del x
+ devices.torch_gc()
+
return samples
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