Merge branch 'master' of https://github.com/yfszzx/stable-diffusion-webui-plus
This commit is contained in:
yfszzx
commit
2a3e7ed872
6
.github/workflows/on_pull_request.yaml
vendored
6
.github/workflows/on_pull_request.yaml
vendored
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@ -22,6 +22,12 @@ jobs:
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uses: actions/setup-python@v3
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with:
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python-version: 3.10.6
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- uses: actions/cache@v2
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with:
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path: ~/.cache/pip
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key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements.txt') }}
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restore-keys: |
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${{ runner.os }}-pip-
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- name: Install PyLint
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run: |
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python -m pip install --upgrade pip
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@ -31,8 +31,8 @@ function imageMaskResize() {
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wrapper.style.width = `${wW}px`;
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wrapper.style.height = `${wH}px`;
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wrapper.style.left = `${(w-wW)/2}px`;
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wrapper.style.top = `${(h-wH)/2}px`;
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wrapper.style.left = `0px`;
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wrapper.style.top = `0px`;
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canvases.forEach( c => {
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c.style.width = c.style.height = '';
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@ -31,7 +31,7 @@ function updateOnBackgroundChange() {
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}
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})
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if (modalImage.src != currentButton.children[0].src) {
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if (currentButton?.children?.length > 0 && modalImage.src != currentButton.children[0].src) {
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modalImage.src = currentButton.children[0].src;
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if (modalImage.style.display === 'none') {
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modal.style.setProperty('background-image', `url(${modalImage.src})`)
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@ -175,11 +175,14 @@ def run_pnginfo(image):
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def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name):
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def weighted_sum(theta0, theta1, theta2, alpha):
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def weighted_sum(theta0, theta1, alpha):
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return ((1 - alpha) * theta0) + (alpha * theta1)
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def add_difference(theta0, theta1, theta2, alpha):
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return theta0 + (theta1 - theta2) * alpha
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def get_difference(theta1, theta2):
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return theta1 - theta2
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def add_difference(theta0, theta1_2_diff, alpha):
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return theta0 + (alpha * theta1_2_diff)
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primary_model_info = sd_models.checkpoints_list[primary_model_name]
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secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
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@ -198,23 +201,28 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
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teritary_model = torch.load(teritary_model_info.filename, map_location='cpu')
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theta_2 = sd_models.get_state_dict_from_checkpoint(teritary_model)
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else:
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teritary_model = None
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theta_2 = None
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theta_funcs = {
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"Weighted sum": weighted_sum,
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"Add difference": add_difference,
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"Weighted sum": (None, weighted_sum),
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"Add difference": (get_difference, add_difference),
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}
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theta_func = theta_funcs[interp_method]
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theta_func1, theta_func2 = theta_funcs[interp_method]
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print(f"Merging...")
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if theta_func1:
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for key in tqdm.tqdm(theta_1.keys()):
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if 'model' in key:
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t2 = theta_2.get(key, torch.zeros_like(theta_1[key]))
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theta_1[key] = theta_func1(theta_1[key], t2)
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del theta_2, teritary_model
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for key in tqdm.tqdm(theta_0.keys()):
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if 'model' in key and key in theta_1:
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t2 = (theta_2 or {}).get(key)
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if t2 is None:
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t2 = torch.zeros_like(theta_0[key])
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theta_0[key] = theta_func(theta_0[key], theta_1[key], t2, multiplier)
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theta_0[key] = theta_func2(theta_0[key], theta_1[key], multiplier)
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if save_as_half:
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theta_0[key] = theta_0[key].half()
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@ -123,7 +123,7 @@ class InterrogateModels:
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return caption[0]
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def interrogate(self, pil_image, include_ranks=False):
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def interrogate(self, pil_image):
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res = None
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try:
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@ -156,10 +156,10 @@ class InterrogateModels:
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for name, topn, items in self.categories:
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matches = self.rank(image_features, items, top_count=topn)
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for match, score in matches:
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if include_ranks:
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res += ", " + match
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if shared.opts.interrogate_return_ranks:
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res += f", ({match}:{score/100:.3f})"
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else:
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res += f", ({match}:{score})"
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res += ", " + match
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except Exception:
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print(f"Error interrogating", file=sys.stderr)
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@ -58,6 +58,9 @@ def load_scripts(basedir):
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for filename in sorted(os.listdir(basedir)):
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path = os.path.join(basedir, filename)
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if os.path.splitext(path)[1].lower() != '.py':
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continue
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if not os.path.isfile(path):
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continue
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@ -77,6 +77,16 @@ parser.add_argument("--disable-safe-unpickle", action='store_true', help="disabl
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cmd_opts = parser.parse_args()
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restricted_opts = [
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"samples_filename_pattern",
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"outdir_samples",
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"outdir_txt2img_samples",
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"outdir_img2img_samples",
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"outdir_extras_samples",
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"outdir_grids",
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"outdir_txt2img_grids",
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"outdir_save",
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]
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devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_bsrgan, devices.device_esrgan, devices.device_scunet, devices.device_codeformer = \
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(devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'bsrgan', 'esrgan', 'scunet', 'codeformer'])
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@ -137,6 +137,7 @@ class EmbeddingDatabase:
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continue
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print(f"Loaded a total of {len(self.word_embeddings)} textual inversion embeddings.")
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print("Embeddings:", ', '.join(self.word_embeddings.keys()))
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def find_embedding_at_position(self, tokens, offset):
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token = tokens[offset]
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@ -25,7 +25,7 @@ import gradio.routes
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from modules import sd_hijack, sd_models
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from modules.paths import script_path
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from modules.shared import opts, cmd_opts
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from modules.shared import opts, cmd_opts, restricted_opts
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if cmd_opts.deepdanbooru:
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from modules.deepbooru import get_deepbooru_tags
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import modules.shared as shared
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@ -1430,6 +1430,9 @@ Requested path was: {f}
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if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
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continue
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if cmd_opts.hide_ui_dir_config and key in restricted_opts:
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continue
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oldval = opts.data.get(key, None)
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opts.data[key] = value
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@ -1447,6 +1450,9 @@ Requested path was: {f}
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if not opts.same_type(value, opts.data_labels[key].default):
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return gr.update(visible=True), opts.dumpjson()
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if cmd_opts.hide_ui_dir_config and key in restricted_opts:
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return gr.update(value=oldval), opts.dumpjson()
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oldval = opts.data.get(key, None)
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opts.data[key] = value
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@ -233,6 +233,21 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend, include_lone_
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return processed_result
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class SharedSettingsStackHelper(object):
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def __enter__(self):
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self.CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
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self.hypernetwork = opts.sd_hypernetwork
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self.model = shared.sd_model
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def __exit__(self, exc_type, exc_value, tb):
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modules.sd_models.reload_model_weights(self.model)
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hypernetwork.load_hypernetwork(self.hypernetwork)
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hypernetwork.apply_strength()
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opts.data["CLIP_stop_at_last_layers"] = self.CLIP_stop_at_last_layers
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re_range = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\(([+-]\d+)\s*\))?\s*")
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re_range_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d*)?)(?:\s*\(([+-]\d+(?:.\d*)?)\s*\))?\s*")
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@ -267,9 +282,6 @@ class Script(scripts.Script):
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if not opts.return_grid:
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p.batch_size = 1
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CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
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def process_axis(opt, vals):
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if opt.label == 'Nothing':
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return [0]
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@ -367,6 +379,7 @@ class Script(scripts.Script):
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return process_images(pc)
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with SharedSettingsStackHelper():
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processed = draw_xy_grid(
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p,
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xs=xs,
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@ -381,13 +394,4 @@ class Script(scripts.Script):
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if opts.grid_save:
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images.save_image(processed.images[0], p.outpath_grids, "xy_grid", prompt=p.prompt, seed=processed.seed, grid=True, p=p)
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# restore checkpoint in case it was changed by axes
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modules.sd_models.reload_model_weights(shared.sd_model)
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hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
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hypernetwork.apply_strength()
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opts.data["CLIP_stop_at_last_layers"] = CLIP_stop_at_last_layers
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return processed
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