update clip skip and attention normalization

cli/run-benchmark.py

@@ -87,7 +87,6 @@ async def main():
         'vae': opts.sd_vae,
         'hypernetwork': opts.sd_hypernetwork,
         'sampler': options.sampler_name,
-        'clip-stop': opts.CLIP_stop_at_last_layers,
         'preview': opts.show_progress_every_n_steps
     } })
     cpu, gpu = memstats()

extensions-builtin/Lora/scripts/lora_script.py

@@ -54,10 +54,6 @@ script_callbacks.on_infotext_pasted(lora.infotext_pasted)
 shared.options_templates.update(shared.options_section(('extra_networks', "Extra Networks"), {
     "sd_lora": shared.OptionInfo("None", "Add Lora to prompt", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in lora.available_loras]}, refresh=lora.list_available_loras),
     "lora_preferred_name": shared.OptionInfo("Alias from file", "When adding to prompt, refer to lora by", gr.Radio, {"choices": ["Alias from file", "Filename"]}),
-}))
-
-
-shared.options_templates.update(shared.options_section(('compatibility', "Compatibility"), {
     "lora_functional": shared.OptionInfo(False, "Lora: use old method that takes longer when you have multiple Loras active and produces same results as kohya-ss/sd-webui-additional-networks extension"),
 }))
 

modules/generation_parameters_copypaste.py

@@ -303,7 +303,6 @@ settings_map = {}
 
 
 infotext_to_setting_name_mapping = [
-    ('Clip skip', 'CLIP_stop_at_last_layers', ),
     ('Conditional mask weight', 'inpainting_mask_weight'),
     ('Model hash', 'sd_model_checkpoint'),
     ('ENSD', 'eta_noise_seed_delta'),

modules/images.py

@@ -287,7 +287,7 @@ def sanitize_filename_part(text, replace_spaces=True):
 class FilenameGenerator:
     replacements = {
         'seed': lambda self: self.seed if self.seed is not None else '',
-        'steps': lambda self:  self.p and self.p.steps,
+        'steps': lambda self: self.p and self.p.steps,
         'cfg': lambda self: self.p and self.p.cfg_scale,
         'width': lambda self: self.image.width,
         'height': lambda self: self.image.height,
@@ -307,7 +307,7 @@ class FilenameGenerator:
         'batch_number': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if self.p.batch_size == 1 else self.p.batch_index + 1,
         'generation_number': lambda self: NOTHING_AND_SKIP_PREVIOUS_TEXT if self.p.n_iter == 1 and self.p.batch_size == 1 else self.p.iteration * self.p.batch_size + self.p.batch_index + 1,
         'hasprompt': lambda self, *args: self.hasprompt(*args),  # accepts formats:[hasprompt<prompt1|default><prompt2>..]
-        'clip_skip': lambda self: shared.opts.data["CLIP_stop_at_last_layers"],
+        'clip_skip': lambda self: self.p and self.p.clip_skip,
         'denoising': lambda self: self.p.denoising_strength if self.p and self.p.denoising_strength else NOTHING_AND_SKIP_PREVIOUS_TEXT,
     }
     default_time_format = '%Y%m%d%H%M%S'

modules/img2img.py

@@ -65,12 +65,12 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
         shared.log.debug(f'Processed: {len(images)} Memory: {memory_stats()} batch')
 
 
-def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, *args): # pylint: disable=unused-argument
+def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, clip_skip: int, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, *args): # pylint: disable=unused-argument
 
     if shared.sd_model is None:
         shared.log.warning('Model not loaded')
         return
-    shared.log.debug(f'img2img: id_task={id_task}|mode={mode}|prompt={prompt}|negative_prompt={negative_prompt}|prompt_styles={prompt_styles}|init_img={init_img}|sketch={sketch}|init_img_with_mask={init_img_with_mask}|inpaint_color_sketch={inpaint_color_sketch}|inpaint_color_sketch_orig={inpaint_color_sketch_orig}|init_img_inpaint={init_img_inpaint}|init_mask_inpaint={init_mask_inpaint}|steps={steps}|sampler_index={sampler_index}|mask_blur={mask_blur}|mask_alpha={mask_alpha}|inpainting_fill={inpainting_fill}|restore_faces={restore_faces}|tiling={tiling}|n_iter={n_iter}|batch_size={batch_size}|cfg_scale={cfg_scale}|image_cfg_scale={image_cfg_scale}|denoising_strength={denoising_strength}|seed={seed}|subseed{subseed}|subseed_strength={subseed_strength}|seed_resize_from_h={seed_resize_from_h}|seed_resize_from_w={seed_resize_from_w}|seed_enable_extras={seed_enable_extras}|selected_scale_tab={selected_scale_tab}|height={height}|width={width}|scale_by={scale_by}|resize_mode={resize_mode}|inpaint_full_res={inpaint_full_res}|inpaint_full_res_padding={inpaint_full_res_padding}|inpainting_mask_invert={inpainting_mask_invert}|img2img_batch_input_dir={img2img_batch_input_dir}|img2img_batch_output_dir={img2img_batch_output_dir}|img2img_batch_inpaint_mask_dir={img2img_batch_inpaint_mask_dir}|override_settings_texts={override_settings_texts}|args={args}')
+    shared.log.debug(f'img2img: id_task={id_task}|mode={mode}|prompt={prompt}|negative_prompt={negative_prompt}|prompt_styles={prompt_styles}|init_img={init_img}|sketch={sketch}|init_img_with_mask={init_img_with_mask}|inpaint_color_sketch={inpaint_color_sketch}|inpaint_color_sketch_orig={inpaint_color_sketch_orig}|init_img_inpaint={init_img_inpaint}|init_mask_inpaint={init_mask_inpaint}|steps={steps}|sampler_index={sampler_index}|mask_blur={mask_blur}|mask_alpha={mask_alpha}|inpainting_fill={inpainting_fill}|restore_faces={restore_faces}|tiling={tiling}|n_iter={n_iter}|batch_size={batch_size}|cfg_scale={cfg_scale}|image_cfg_scale={image_cfg_scale}|clip_skip={clip_skip}|denoising_strength={denoising_strength}|seed={seed}|subseed{subseed}|subseed_strength={subseed_strength}|seed_resize_from_h={seed_resize_from_h}|seed_resize_from_w={seed_resize_from_w}|seed_enable_extras={seed_enable_extras}|selected_scale_tab={selected_scale_tab}|height={height}|width={width}|scale_by={scale_by}|resize_mode={resize_mode}|inpaint_full_res={inpaint_full_res}|inpaint_full_res_padding={inpaint_full_res_padding}|inpainting_mask_invert={inpainting_mask_invert}|img2img_batch_input_dir={img2img_batch_input_dir}|img2img_batch_output_dir={img2img_batch_output_dir}|img2img_batch_inpaint_mask_dir={img2img_batch_inpaint_mask_dir}|override_settings_texts={override_settings_texts}|args={args}')
 
     if sampler_index is None:
         shared.log.warning('Selected sampler is not enabled')
@@ -131,6 +131,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
         n_iter=n_iter,
         steps=steps,
         cfg_scale=cfg_scale,
+        clip_skip=clip_skip,
         width=width,
         height=height,
         restore_faces=restore_faces,

modules/processing.py

@@ -87,7 +87,7 @@ class StableDiffusionProcessing:
     """
     The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
     """
-    def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): # pylint: disable=unused-argument
+    def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, clip_skip: int = 1, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): # pylint: disable=unused-argument
 
         self.outpath_samples: str = outpath_samples
         self.outpath_grids: str = outpath_grids
@@ -141,9 +141,10 @@ class StableDiffusionProcessing:
         self.all_negative_prompts = None
         self.all_seeds = None
         self.all_subseeds = None
-        self.clip_skip = opts.CLIP_stop_at_last_layers
+        self.clip_skip = clip_skip
         self.iteration = 0
         self.is_hr_pass = False
+        opts.data['clip_skip'] = clip_skip
 
     @property
     def sd_model(self):

modules/sd_hijack_clip.py

@@ -203,10 +203,13 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
         z = self.encode_with_transformers(tokens)
         # restoring original mean is likely not correct, but it seems to work well to prevent artifacts that happen otherwise
         batch_multipliers = torch.asarray(batch_multipliers).to(devices.device)
-        original_mean = z.mean()
-        z = z * batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
-        new_mean = z.mean()
-        z = z * (original_mean / new_mean)
+        if opts.prompt_mean_norm:
+            original_mean = z.mean()
+            z = z * batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
+            new_mean = z.mean()
+            z = z * (original_mean / new_mean)
+        else:
+            z = z * batch_multipliers.reshape(batch_multipliers.shape + (1,)).expand(z.shape)
         return z
 
 
@@ -240,11 +243,10 @@ class FrozenCLIPEmbedderWithCustomWords(FrozenCLIPEmbedderWithCustomWordsBase):
         return tokenized
 
     def encode_with_transformers(self, tokens):
-        if opts.CLIP_stop_at_last_layers is None:
-            opts.CLIP_stop_at_last_layers = 1
-        outputs = self.wrapped.transformer(input_ids=tokens, output_hidden_states=-opts.CLIP_stop_at_last_layers)
-        if opts.CLIP_stop_at_last_layers > 1:
-            z = outputs.hidden_states[-opts.CLIP_stop_at_last_layers]
+        clip_skip = opts.data['clip_skip'] or 1
+        outputs = self.wrapped.transformer(input_ids=tokens, output_hidden_states=-clip_skip)
+        if clip_skip > 1:
+            z = outputs.hidden_states[-clip_skip]
             z = self.wrapped.transformer.text_model.final_layer_norm(z)
         else:
             z = outputs.last_hidden_state

modules/sd_hijack_open_clip.py

@@ -3,7 +3,7 @@ import torch
 
 from modules import sd_hijack_clip, devices
 
-tokenizer = open_clip.tokenizer._tokenizer
+tokenizer = open_clip.tokenizer._tokenizer # pylint: disable=protected-access
 
 
 class FrozenOpenCLIPEmbedderWithCustomWords(sd_hijack_clip.FrozenCLIPEmbedderWithCustomWordsBase):
@@ -21,7 +21,6 @@ class FrozenOpenCLIPEmbedderWithCustomWords(sd_hijack_clip.FrozenCLIPEmbedderWit
         return tokenized
 
     def encode_with_transformers(self, tokens):
-        # set self.wrapped.layer_idx here according to opts.CLIP_stop_at_last_layers
         z = self.wrapped.encode_with_transformer(tokens)
 
         return z

modules/sd_vae.py

@@ -128,7 +128,7 @@ def load_vae(model, vae_file=None, vae_source="from unknown source"):
     if vae_file:
         if cache_enabled and vae_file in checkpoints_loaded:
             # use vae checkpoint cache
-            shared.log.info(f"Loading VAE weights {vae_source}: cached {get_filename(vae_file)}")
+            shared.log.info(f"Loading VAE weights: {vae_source}: cached {get_filename(vae_file)}")
             store_base_vae(model)
             _load_vae_dict(model, checkpoints_loaded[vae_file])
         else:
@@ -192,5 +192,5 @@ def reload_vae_weights(sd_model=None, vae_file=unspecified):
     script_callbacks.model_loaded_callback(sd_model)
     if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram:
         sd_model.to(devices.device)
-    shared.log.info("VAE weights loaded.")
+    shared.log.info(f"VAE weights loaded: {vae_file}")
     return sd_model

modules/shared.py

@@ -255,6 +255,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sub_quad_chunk_threshold": OptionInfo(80, "Sub-quadratic cross-attention percentage of VRAM chunking threshold", gr.Slider, {"minimum": 0, "maximum": 100, "step": 1}),
     "always_batch_cond_uncond": OptionInfo(False, "Disables cond/uncond batching that is enabled to save memory with --medvram or --lowvram"),
     "prompt_attention": OptionInfo("Full parser", "Prompt attention parser", gr.Radio, lambda: {"choices": ["Full parser", "Compel parser", "A1111 parser", "Fixed attention"] }),
+    "prompt_mean_norm": OptionInfo(True, "Prompt attention mean normalization"),
 }))
 
 options_templates.update(options_section(('system-paths', "System Paths"), {

modules/txt2img.py

@@ -7,12 +7,12 @@ from modules.ui import plaintext_to_html
 from modules.memstats import memory_stats
 
 
-def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, override_settings_texts, *args): # pylint: disable=unused-argument
+def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, clip_skip: int, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, override_settings_texts, *args): # pylint: disable=unused-argument
 
     if shared.sd_model is None:
         shared.log.warning('Model not loaded')
         return
-    shared.log.debug(f'txt2img: id_task={id_task}|prompt={prompt}|negative_prompt={negative_prompt}|prompt_styles={prompt_styles}|steps={steps}|sampler_index={sampler_index}|restore_faces={restore_faces}|tiling={tiling}|n_iter={n_iter}|batch_size={batch_size}|cfg_scale={cfg_scale}|seed={seed}|subseed={subseed}|subseed_strength={subseed_strength}|seed_resize_from_h={seed_resize_from_h}|seed_resize_from_w={seed_resize_from_w}|seed_enable_extras={seed_enable_extras}|height={height}|width={width}|enable_hr={enable_hr}|denoising_strength={denoising_strength}|hr_scale={hr_scale}|hr_upscaler={hr_upscaler}|hr_second_pass_steps={hr_second_pass_steps}|hr_resize_x={hr_resize_x}|hr_resize_y={hr_resize_y}|override_settings_texts={override_settings_texts}args={args}')
+    shared.log.debug(f'txt2img: id_task={id_task}|prompt={prompt}|negative_prompt={negative_prompt}|prompt_styles={prompt_styles}|steps={steps}|sampler_index={sampler_index}|restore_faces={restore_faces}|tiling={tiling}|n_iter={n_iter}|batch_size={batch_size}|cfg_scale={cfg_scale}|clip_skip={clip_skip}|seed={seed}|subseed={subseed}|subseed_strength={subseed_strength}|seed_resize_from_h={seed_resize_from_h}|seed_resize_from_w={seed_resize_from_w}|seed_enable_extras={seed_enable_extras}|height={height}|width={width}|enable_hr={enable_hr}|denoising_strength={denoising_strength}|hr_scale={hr_scale}|hr_upscaler={hr_upscaler}|hr_second_pass_steps={hr_second_pass_steps}|hr_resize_x={hr_resize_x}|hr_resize_y={hr_resize_y}|override_settings_texts={override_settings_texts}args={args}')
     if sampler_index is None:
         shared.log.warning('Selected sampler is not enabled')
         sampler_index = 0
@@ -36,6 +36,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
         n_iter=n_iter,
         steps=steps,
         cfg_scale=cfg_scale,
+        clip_skip=clip_skip,
         width=width,
         height=height,
         restore_faces=restore_faces,

modules/ui.py

@@ -142,10 +142,6 @@ def interrogate_deepbooru(image):
     return gr.update() if prompt is None else prompt
 
 
-def change_clip_skip(val):
-    modules.shared.opts.CLIP_stop_at_last_layers = val
-
-
 def create_seed_inputs(target_interface):
     with FormRow(elem_id=f"{target_interface}_seed_row", variant="compact"):
         seed = gr.Number(label='Seed', value=-1, elem_id=f"{target_interface}_seed")
@@ -369,8 +365,7 @@ def create_ui():
                     elif category == "cfg":
                         with FormRow():
                             cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=6.0, elem_id="txt2img_cfg_scale")
-                            clip_skip = gr.Slider(label='CLIP Skip', value=modules.shared.opts.CLIP_stop_at_last_layers, minimum=1, maximum=4, step=1, elem_id='txt2img_clip_skip', interactive=True)
-                            clip_skip.change(fn=change_clip_skip, show_progress=False, inputs=clip_skip)
+                            clip_skip = gr.Slider(label='CLIP skip', value=1, minimum=1, maximum=4, step=1, elem_id='txt2img_clip_skip', interactive=True)
                     elif category == "seed":
                         seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
                     elif category == "checkboxes":
@@ -430,6 +425,7 @@ def create_ui():
                     batch_count,
                     batch_size,
                     cfg_scale,
+                    clip_skip,
                     seed,
                     subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
                     seed_checkbox,  # seed_enable_extras
@@ -484,6 +480,7 @@ def create_ui():
                 (sampler_index, "Sampler"),
                 (restore_faces, "Face restoration"),
                 (cfg_scale, "CFG scale"),
+                (clip_skip, "Clip skip"),
                 (seed, "Seed"),
                 (width, "Size-1"),
                 (height, "Size-2"),
@@ -681,8 +678,7 @@ def create_ui():
                                 cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=6.0, elem_id="img2img_cfg_scale")
                                 image_cfg_scale = gr.Slider(minimum=0, maximum=3.0, step=0.05, label='Image CFG Scale', value=1.5, elem_id="img2img_image_cfg_scale", visible=False)
                                 denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
-                                clip_skip = gr.Slider(label='CLIP Skip', value=modules.shared.opts.CLIP_stop_at_last_layers, minimum=1, maximum=4, step=1, elem_id='img2img_clip_skip', interactive=True)
-                                clip_skip.change(fn=change_clip_skip, show_progress=False, inputs=clip_skip)
+                                clip_skip = gr.Slider(label='CLIP skip', value=1, minimum=1, maximum=4, step=1, elem_id='img2img_clip_skip', interactive=True)
 
                     elif category == "seed":
                         seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
@@ -772,6 +768,7 @@ def create_ui():
                     batch_size,
                     cfg_scale,
                     image_cfg_scale,
+                    clip_skip,
                     denoising_strength,
                     seed,
                     subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
@@ -861,6 +858,7 @@ def create_ui():
                 (restore_faces, "Face restoration"),
                 (cfg_scale, "CFG scale"),
                 (image_cfg_scale, "Image CFG scale"),
+                (clip_skip, "Clip skip"),
                 (seed, "Seed"),
                 (width, "Size-1"),
                 (height, "Size-2"),

scripts/xyz_grid.py

@@ -82,7 +82,8 @@ def confirm_checkpoints(p, xs):
 
 
 def apply_clip_skip(p, x, xs):
-    shared.opts.data["CLIP_stop_at_last_layers"] = x
+    p.clip_skip = x
+    shared.opts.data["clip_skip"] = x
 
 
 def apply_upscale_latent_space(p, x, xs):
@@ -344,7 +345,6 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend
 class SharedSettingsStackHelper(object):
     def __enter__(self):
         #Save overridden settings so they can be restored later.
-        self.CLIP_stop_at_last_layers = shared.opts.CLIP_stop_at_last_layers
         self.vae = shared.opts.sd_vae
         self.uni_pc_order = shared.opts.uni_pc_order
         self.token_merging_ratio_hr = shared.opts.token_merging_ratio_hr
@@ -358,7 +358,6 @@ class SharedSettingsStackHelper(object):
         #Restore overriden settings after plot generation.
         shared.opts.data["sd_vae"] = self.vae
         shared.opts.data["uni_pc_order"] = self.uni_pc_order
-        shared.opts.data["CLIP_stop_at_last_layers"] = self.CLIP_stop_at_last_layers
         shared.opts.data["token_merging_ratio_hr"] = self.token_merging_ratio_hr
         shared.opts.data["token_merging_ratio"] = self.token_merging_ratio
         shared.opts.data["token_merging_random"] = self.token_merging_random