From d8a2c32918f04cba49986fb1bf1d30ee9a092dcb Mon Sep 17 00:00:00 2001 From: Vladimir Mandic Date: Tue, 9 May 2023 10:41:23 -0400 Subject: [PATCH] xyz grid optimizations --- extensions-builtin/a1111-sd-webui-lycoris | 2 +- .../multidiffusion-upscaler-for-automatic1111 | 2 +- modules/sd_models.py | 2 +- modules/shared.py | 6 +- scripts/xyz_grid.py | 211 +++++++----------- 5 files changed, 84 insertions(+), 139 deletions(-) diff --git a/extensions-builtin/a1111-sd-webui-lycoris b/extensions-builtin/a1111-sd-webui-lycoris index 514511d72..1f3e452c3 160000 --- a/extensions-builtin/a1111-sd-webui-lycoris +++ b/extensions-builtin/a1111-sd-webui-lycoris @@ -1 +1 @@ -Subproject commit 514511d7260635e0eb7b67cabcbce2a484387a97 +Subproject commit 1f3e452c314e7b1dd903f723d3c552702519f4a3 diff --git a/extensions-builtin/multidiffusion-upscaler-for-automatic1111 b/extensions-builtin/multidiffusion-upscaler-for-automatic1111 index 5f22b8fc2..23f3a1443 160000 --- a/extensions-builtin/multidiffusion-upscaler-for-automatic1111 +++ b/extensions-builtin/multidiffusion-upscaler-for-automatic1111 @@ -1 +1 @@ -Subproject commit 5f22b8fc27955c04721dae870f71b611e0fa00f8 +Subproject commit 23f3a14432e7740f4a59322ba36eafbf042dffb0 diff --git a/modules/sd_models.py b/modules/sd_models.py index 794cb47e9..cd44a1486 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -421,7 +421,7 @@ def reload_model_weights(sd_model=None, info=None): shared.log.debug('Reload model weights skip') skip_next_load = False return - shared.log.debug(f'Reload model weights: {sd_model} {info}') + shared.log.debug(f'Reload model weights: {sd_model is not None} {info}') from modules import lowvram, sd_hijack checkpoint_info = info or select_checkpoint() if not sd_model: diff --git a/modules/shared.py b/modules/shared.py index 5065559ee..118dc8f4f 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -285,9 +285,9 @@ options_templates.update(options_section(('saving-images', "Image options"), { "grid_prevent_empty_spots": OptionInfo(True, "Prevent empty spots in grid (when set to autodetect)"), "n_rows": OptionInfo(-1, "Grid row count; use -1 for autodetect and 0 for it to be same as batch size", gr.Slider, {"minimum": -1, "maximum": 16, "step": 1}), "save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters"), - "save_images_before_face_restoration": OptionInfo(True, "Save a copy of image before doing face restoration"), - "save_images_before_highres_fix": OptionInfo(True, "Save a copy of image before applying highres fix"), - "save_images_before_color_correction": OptionInfo(True, "Save a copy of image before applying color correction to img2img results"), + "save_images_before_face_restoration": OptionInfo(False, "Save a copy of image before doing face restoration"), + "save_images_before_highres_fix": OptionInfo(False, "Save a copy of image before applying highres fix"), + "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"), "save_mask": OptionInfo(False, "For inpainting, save a copy of the greyscale mask"), "save_mask_composite": OptionInfo(False, "For inpainting, save a masked composite"), "jpeg_quality": OptionInfo(85, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}), diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 389560501..41f226848 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -1,3 +1,5 @@ + # pylint: disable=unused-argument, attribute-defined-outside-init + import re import csv import random @@ -12,47 +14,36 @@ import modules.scripts as scripts import modules.shared as shared from modules import images, sd_samplers, processing, sd_models, sd_vae from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img -from modules.shared import opts, state from modules.ui_components import ToolButton fill_values_symbol = "\U0001f4d2" # 📒 - AxisInfo = namedtuple('AxisInfo', ['axis', 'values']) def apply_field(field): def fun(p, x, xs): setattr(p, field, x) - return fun def apply_prompt(p, x, xs): if xs[0] not in p.prompt and xs[0] not in p.negative_prompt: - raise RuntimeError(f"Prompt S/R did not find {xs[0]} in prompt or negative prompt.") - - p.prompt = p.prompt.replace(xs[0], x) - p.negative_prompt = p.negative_prompt.replace(xs[0], x) + shared.log.warning(f"XYZ grid: prompt S/R did not find {xs[0]} in prompt or negative prompt.") + else: + p.prompt = p.prompt.replace(xs[0], x) + p.negative_prompt = p.negative_prompt.replace(xs[0], x) def apply_order(p, x, xs): token_order = [] - - # Initally grab the tokens from the prompt, so they can be replaced in order of earliest seen for token in x: token_order.append((p.prompt.find(token), token)) - token_order.sort(key=lambda t: t[0]) - prompt_parts = [] - - # Split the prompt up, taking out the tokens for _, token in token_order: n = p.prompt.find(token) prompt_parts.append(p.prompt[0:n]) p.prompt = p.prompt[n + len(token):] - - # Rebuild the prompt with the tokens in the order we want prompt_tmp = "" for idx, part in enumerate(prompt_parts): prompt_tmp += part @@ -63,39 +54,42 @@ def apply_order(p, x, xs): def apply_sampler(p, x, xs): sampler_name = sd_samplers.samplers_map.get(x.lower(), None) if sampler_name is None: - raise RuntimeError(f"Unknown sampler: {x}") - - p.sampler_name = sampler_name + shared.log.warning(f"XYZ grid: unknown sampler: {x}") + else: + p.sampler_name = sampler_name def confirm_samplers(p, xs): for x in xs: if x.lower() not in sd_samplers.samplers_map: - raise RuntimeError(f"Unknown sampler: {x}") + shared.log.warning(f"XYZ grid: unknown sampler: {x}") def apply_checkpoint(p, x, xs): + if x == shared.opts.sd_model_checkpoint: + return info = sd_models.get_closet_checkpoint_match(x) if info is None: - raise RuntimeError(f"Unknown checkpoint: {x}") - sd_models.reload_model_weights(shared.sd_model, info) + shared.log.warning(f"XYZ grid: unknown checkpoint: {x}") + else: + sd_models.reload_model_weights(shared.sd_model, info) def confirm_checkpoints(p, xs): for x in xs: if sd_models.get_closet_checkpoint_match(x) is None: - raise RuntimeError(f"Unknown checkpoint: {x}") + shared.log.warning(f"XYZ grid: Unknown checkpoint: {x}") def apply_clip_skip(p, x, xs): - opts.data["CLIP_stop_at_last_layers"] = x + shared.opts.data["CLIP_stop_at_last_layers"] = x def apply_upscale_latent_space(p, x, xs): if x.lower().strip() != '0': - opts.data["use_scale_latent_for_hires_fix"] = True + shared.opts.data["use_scale_latent_for_hires_fix"] = True else: - opts.data["use_scale_latent_for_hires_fix"] = False + shared.opts.data["use_scale_latent_for_hires_fix"] = False def find_vae(name: str): @@ -106,7 +100,7 @@ def find_vae(name: str): else: choices = [x for x in sorted(sd_vae.vae_dict, key=lambda x: len(x)) if name.lower().strip() in x.lower()] if len(choices) == 0: - print(f"No VAE found for {name}; using automatic") + shared.log.warning(f"No VAE found for {name}; using automatic") return sd_vae.unspecified else: return sd_vae.vae_dict[choices[0]] @@ -123,13 +117,13 @@ def apply_styles(p: StableDiffusionProcessingTxt2Img, x: str, _): def apply_fallback(p, x, xs): sampler_name = sd_samplers.samplers_map.get(x.lower(), None) if sampler_name is None: - raise RuntimeError(f"Unknown sampler: {x}") - - opts.data["xyz_fallback_sampler"] = sampler_name + shared.log.warning(f"XYZ grid: unknown sampler: {x}") + else: + shared.opts.data["xyz_fallback_sampler"] = sampler_name def apply_uni_pc_order(p, x, xs): - opts.data["uni_pc_order"] = min(x, p.steps - 1) + shared.opts.data["uni_pc_order"] = min(x, p.steps - 1) def apply_face_restore(p, opt, x): @@ -142,23 +136,25 @@ def apply_face_restore(p, opt, x): p.face_restoration_model = 'GFPGAN' else: is_active = opt in ('true', 'yes', 'y', '1') - p.restore_faces = is_active + def apply_token_merging_ratio_hr(p, x, xs): - opts.data["token_merging_ratio_hr"] = x + shared.opts.data["token_merging_ratio_hr"] = x + def apply_token_merging_ratio(p, x, xs): - opts.data["token_merging_ratio"] = x + shared.opts.data["token_merging_ratio"] = x + def apply_token_merging_random(p, x, xs): is_active = x.lower() in ('true', 'yes', 'y', '1') - opts.data["token_merging_random"] = is_active + shared.opts.data["token_merging_random"] = is_active + def format_value_add_label(p, opt, x): if type(x) == float: x = round(x, 8) - return f"{opt.label}: {x}" @@ -186,11 +182,11 @@ def str_permutations(x): class AxisOption: - def __init__(self, label, type, apply, format_value=format_value_add_label, confirm=None, cost=0.0, choices=None): + def __init__(self, label, tipe, apply, fmt=format_value_add_label, confirm=None, cost=0.0, choices=None): self.label = label - self.type = type + self.type = tipe self.apply = apply - self.format_value = format_value + self.format_value = fmt self.confirm = confirm self.cost = cost self.choices = choices @@ -208,7 +204,7 @@ class AxisOptionTxt2Img(AxisOption): axis_options = [ - AxisOption("Nothing", str, do_nothing, format_value=format_nothing), + AxisOption("Nothing", str, do_nothing, fmt=format_nothing), AxisOption("Seed", int, apply_field("seed")), AxisOption("Var. seed", int, apply_field("subseed")), AxisOption("Var. strength", float, apply_field("subseed_strength")), @@ -216,11 +212,11 @@ axis_options = [ AxisOptionTxt2Img("Hires steps", int, apply_field("hr_second_pass_steps")), AxisOption("CFG Scale", float, apply_field("cfg_scale")), AxisOptionImg2Img("Image CFG Scale", float, apply_field("image_cfg_scale")), - AxisOption("Prompt S/R", str, apply_prompt, format_value=format_value), - AxisOption("Prompt order", str_permutations, apply_order, format_value=format_value_join_list), - AxisOptionTxt2Img("Sampler", str, apply_sampler, format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]), - AxisOptionImg2Img("Sampler", str, apply_sampler, format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers_for_img2img]), - AxisOption("Checkpoint name", str, apply_checkpoint, format_value=format_value, confirm=confirm_checkpoints, cost=1.0, choices=lambda: list(sd_models.checkpoints_list)), + AxisOption("Prompt S/R", str, apply_prompt, fmt=format_value), + AxisOption("Prompt order", str_permutations, apply_order, fmt=format_value_join_list), + AxisOptionTxt2Img("Sampler", str, apply_sampler, fmt=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]), + AxisOptionImg2Img("Sampler", str, apply_sampler, fmt=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers_for_img2img]), + AxisOption("Checkpoint name", str, apply_checkpoint, fmt=format_value, confirm=confirm_checkpoints, cost=1.0, choices=lambda: list(sd_models.checkpoints_list)), AxisOption("Sigma Churn", float, apply_field("s_churn")), AxisOption("Sigma min", float, apply_field("s_tmin")), AxisOption("Sigma max", float, apply_field("s_tmax")), @@ -229,12 +225,12 @@ axis_options = [ AxisOption("Clip skip", int, apply_clip_skip), AxisOption("Denoising", float, apply_field("denoising_strength")), AxisOptionTxt2Img("Hires upscaler", str, apply_field("hr_upscaler"), choices=lambda: [*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]]), - AxisOptionTxt2Img("Fallback latent upscaler sampler", str, apply_fallback, format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]), + AxisOptionTxt2Img("Fallback latent upscaler sampler", str, apply_fallback, fmt=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]), AxisOptionImg2Img("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight")), AxisOption("VAE", str, apply_vae, cost=0.7, choices=lambda: list(sd_vae.vae_dict)), AxisOption("Styles", str, apply_styles, choices=lambda: list(shared.prompt_styles.styles)), AxisOption("UniPC Order", int, apply_uni_pc_order, cost=0.5), - AxisOption("Face restore", str, apply_face_restore, format_value=format_value), + AxisOption("Face restore", str, apply_face_restore, fmt=format_value), AxisOption("ToMe ratio",float,apply_token_merging_ratio), AxisOption("ToMe ratio for Hires fix",float,apply_token_merging_ratio_hr), AxisOption("ToMe random pertubations",str,apply_token_merging_random, choices = lambda: ["Yes","No"]) @@ -245,12 +241,9 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend hor_texts = [[images.GridAnnotation(x)] for x in x_labels] ver_texts = [[images.GridAnnotation(y)] for y in y_labels] title_texts = [[images.GridAnnotation(z)] for z in z_labels] - list_size = (len(xs) * len(ys) * len(zs)) - processed_result = None - - state.job_count = list_size * p.n_iter + shared.state.job_count = list_size * p.n_iter def process_cell(x, y, z, ix, iy, iz): nonlocal processed_result @@ -258,10 +251,8 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend def index(ix, iy, iz): return ix + iy * len(xs) + iz * len(xs) * len(ys) - state.job = f"{index(ix, iy, iz) + 1} out of {list_size}" - + shared.state.job = f"{index(ix, iy, iz) + 1} out of {list_size}" processed: Processed = cell(x, y, z, ix, iy, iz) - if processed_result is None: # Use our first processed result object as a template container to hold our full results processed_result = copy(processed) @@ -270,7 +261,6 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend processed_result.all_seeds = [None] * list_size processed_result.infotexts = [None] * list_size processed_result.index_of_first_image = 1 - idx = index(ix, iy, iz) if processed.images: # Non-empty list indicates some degree of success. @@ -287,7 +277,6 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend cell_size = processed_result.images[0].size processed_result.images[idx] = Image.new(cell_mode, cell_size) - if first_axes_processed == 'x': for ix, x in enumerate(xs): if second_axes_processed == 'y': @@ -321,14 +310,14 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend if not processed_result: # Should never happen, I've only seen it on one of four open tabs and it needed to refresh. - print("Unexpected error: Processing could not begin, you may need to refresh the tab or restart the service.") + shared.log.error("XYZ grid: Processing could not begin, you may need to refresh the tab or restart the service") return Processed(p, []) elif not any(processed_result.images): - print("Unexpected error: draw_xyz_grid failed to return even a single processed image") + shared.log.error("XYZ grid: Failed to return even a single processed image") return Processed(p, []) z_count = len(zs) - sub_grids = [None] * z_count + # sub_grids = [None] * z_count for i in range(z_count): start_index = (i * len(xs) * len(ys)) + i end_index = start_index + len(xs) * len(ys) @@ -339,7 +328,6 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend processed_result.all_prompts.insert(i, processed_result.all_prompts[start_index]) processed_result.all_seeds.insert(i, processed_result.all_seeds[start_index]) processed_result.infotexts.insert(i, processed_result.infotexts[start_index]) - sub_grid_size = processed_result.images[0].size z_grid = images.image_grid(processed_result.images[:z_count], rows=1) if draw_legend: @@ -348,36 +336,39 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend #processed_result.all_prompts.insert(0, processed_result.all_prompts[0]) #processed_result.all_seeds.insert(0, processed_result.all_seeds[0]) processed_result.infotexts.insert(0, processed_result.infotexts[0]) - return processed_result class SharedSettingsStackHelper(object): def __enter__(self): #Save overridden settings so they can be restored later. - self.CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers - self.vae = opts.sd_vae - self.uni_pc_order = opts.uni_pc_order - self.token_merging_ratio_hr = opts.token_merging_ratio_hr - self.token_merging_ratio = opts.token_merging_ratio - self.token_merging_random = opts.token_merging_random + 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 + self.token_merging_ratio = shared.opts.token_merging_ratio + self.token_merging_random = shared.opts.token_merging_random + self.sd_model_checkpoint = shared.opts.sd_model_checkpoint + self.sd_vae_checkpoint = shared.opts.sd_vae def __exit__(self, exc_type, exc_value, tb): #Restore overriden settings after plot generation. - opts.data["sd_vae"] = self.vae - opts.data["uni_pc_order"] = self.uni_pc_order - sd_models.reload_model_weights() - sd_vae.reload_vae_weights() + 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 + if self.sd_model_checkpoint != shared.opts.sd_model_checkpoint: + shared.opts.data["sd_model_checkpoint"] = self.sd_model_checkpoint + sd_models.reload_model_weights() + if self.sd_vae_checkpoint != shared.opts.sd_vae: + shared.opts.data["sd_vae"] = self.sd_vae_checkpoint + sd_vae.reload_vae_weights() - opts.data["CLIP_stop_at_last_layers"] = self.CLIP_stop_at_last_layers - - opts.data["token_merging_ratio_hr"] = self.token_merging_ratio_hr - opts.data["token_merging_ratio"] = self.token_merging_ratio - opts.data["token_merging_random"] = self.token_merging_random re_range = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\(([+-]\d+)\s*\))?\s*") re_range_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d*)?)(?:\s*\(([+-]\d+(?:.\d*)?)\s*\))?\s*") - re_range_count = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\[(\d+)\s*\])?\s*") re_range_count_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d*)?)(?:\s*\[(\d+(?:.\d*)?)\s*\])?\s*") @@ -388,7 +379,6 @@ class Script(scripts.Script): def ui(self, is_img2img): self.current_axis_options = [x for x in axis_options if type(x) == AxisOption or x.is_img2img == is_img2img] - with gr.Row(): with gr.Column(scale=19): with gr.Row(): @@ -408,7 +398,6 @@ class Script(scripts.Script): z_values = gr.Textbox(label="Z values", lines=1, elem_id=self.elem_id("z_values")) z_values_dropdown = gr.Dropdown(label="Z values",visible=False,multiselect=True,interactive=True) fill_z_button = ToolButton(value=fill_values_symbol, elem_id="xyz_grid_fill_z_tool_button", visible=False) - with gr.Row(variant="compact", elem_id="axis_options"): draw_legend = gr.Checkbox(label='Draw legend', value=True, elem_id=self.elem_id("draw_legend")) no_fixed_seeds = gr.Checkbox(label='Keep -1 for seeds', value=False, elem_id=self.elem_id("no_fixed_seeds")) @@ -416,7 +405,6 @@ class Script(scripts.Script): include_sub_grids = gr.Checkbox(label='Include Sub Grids', value=False, elem_id=self.elem_id("include_sub_grids")) with gr.Row(variant="compact", elem_id="axis_options"): margin_size = gr.Slider(label="Grid margins (px)", minimum=0, maximum=500, value=0, step=2, elem_id=self.elem_id("margin_size")) - with gr.Row(variant="compact", elem_id="swap_axes"): swap_xy_axes_button = gr.Button(value="Swap X/Y axes", elem_id="xy_grid_swap_axes_button") swap_yz_axes_button = gr.Button(value="Swap Y/Z axes", elem_id="yz_grid_swap_axes_button") @@ -475,25 +463,21 @@ class Script(scripts.Script): return [x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, margin_size] - def run(self, p, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, margin_size): + def run(self, p, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, margin_size): # pylint: disable=arguments-differ + shared.log.debug(f'xyzgrid: {x_type}|{x_values}|{x_values_dropdown}|{y_type}|{y_values}|{y_values_dropdown}|{z_type}|{z_values}|{z_values_dropdown}|{draw_legend}|{include_lone_images}|{include_sub_grids}|{no_fixed_seeds}|{margin_size}') if not no_fixed_seeds: processing.fix_seed(p) - - if not opts.return_grid: + if not shared.opts.return_grid: p.batch_size = 1 - def process_axis(opt, vals, vals_dropdown): if opt.label == 'Nothing': return [0] - if opt.choices is not None: valslist = vals_dropdown else: valslist = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(vals))) if x] - if opt.type == int: valslist_ext = [] - for val in valslist: m = re_range.fullmatch(val) mc = re_range_count.fullmatch(val) @@ -501,21 +485,17 @@ class Script(scripts.Script): start = int(m.group(1)) end = int(m.group(2))+1 step = int(m.group(3)) if m.group(3) is not None else 1 - valslist_ext += list(range(start, end, step)) elif mc is not None: start = int(mc.group(1)) end = int(mc.group(2)) num = int(mc.group(3)) if mc.group(3) is not None else 1 - valslist_ext += [int(x) for x in np.linspace(start=start, stop=end, num=num).tolist()] else: valslist_ext.append(val) - valslist = valslist_ext elif opt.type == float: valslist_ext = [] - for val in valslist: m = re_range_float.fullmatch(val) mc = re_range_count_float.fullmatch(val) @@ -523,48 +503,38 @@ class Script(scripts.Script): start = float(m.group(1)) end = float(m.group(2)) step = float(m.group(3)) if m.group(3) is not None else 1 - valslist_ext += np.arange(start, end + step, step).tolist() elif mc is not None: start = float(mc.group(1)) end = float(mc.group(2)) num = int(mc.group(3)) if mc.group(3) is not None else 1 - valslist_ext += np.linspace(start=start, stop=end, num=num).tolist() else: valslist_ext.append(val) - valslist = valslist_ext elif opt.type == str_permutations: valslist = list(permutations(valslist)) - valslist = [opt.type(x) for x in valslist] - # Confirm options are valid before starting if opt.confirm: opt.confirm(p, valslist) - return valslist x_opt = self.current_axis_options[x_type] if x_opt.choices is not None: x_values = ",".join(x_values_dropdown) xs = process_axis(x_opt, x_values, x_values_dropdown) - y_opt = self.current_axis_options[y_type] if y_opt.choices is not None: y_values = ",".join(y_values_dropdown) ys = process_axis(y_opt, y_values, y_values_dropdown) - z_opt = self.current_axis_options[z_type] if z_opt.choices is not None: z_values = ",".join(z_values_dropdown) zs = process_axis(z_opt, z_values, z_values_dropdown) - - # this could be moved to common code, but unlikely to be ever triggered anywhere else Image.MAX_IMAGE_PIXELS = None # disable check in Pillow and rely on check below to allow large custom image sizes grid_mp = round(len(xs) * len(ys) * len(zs) * p.width * p.height / 1000000) - assert grid_mp < opts.img_max_size_mp, f'Error: Resulting grid would be too large ({grid_mp} MPixels) (max configured size is {opts.img_max_size_mp} MPixels)' + assert grid_mp < shared.opts.img_max_size_mp, f'Error: Resulting grid would be too large ({grid_mp} MPixels) (max configured size is {shared.opts.img_max_size_mp} MPixels)' def fix_axis_seeds(axis_opt, axis_list): if axis_opt.label in ['Seed', 'Var. seed']: @@ -585,7 +555,6 @@ class Script(scripts.Script): total_steps = sum(zs) * len(xs) * len(ys) else: total_steps = p.steps * len(xs) * len(ys) * len(zs) - if isinstance(p, StableDiffusionProcessingTxt2Img) and p.enable_hr: if x_opt.label == "Hires steps": total_steps += sum(xs) * len(ys) * len(zs) @@ -597,21 +566,13 @@ class Script(scripts.Script): total_steps += p.hr_second_pass_steps * len(xs) * len(ys) * len(zs) else: total_steps *= 2 - total_steps *= p.n_iter - image_cell_count = p.n_iter * p.batch_size - cell_console_text = f"; {image_cell_count} images per cell" if image_cell_count > 1 else "" - plural_s = 's' if len(zs) > 1 else '' - print(f"X/Y/Z plot will create {len(xs) * len(ys) * len(zs) * image_cell_count} images on {len(zs)} {len(xs)}x{len(ys)} grid{plural_s}{cell_console_text}. (Total steps to process: {total_steps})") - - state.xyz_plot_x = AxisInfo(x_opt, xs) - state.xyz_plot_y = AxisInfo(y_opt, ys) - state.xyz_plot_z = AxisInfo(z_opt, zs) - - # If one of the axes is very slow to change between (like SD model - # checkpoint), then make sure it is in the outer iteration of the nested - # `for` loop. + shared.log.info(f"XYZ grid: images={len(xs)*len(ys)*len(zs)*image_cell_count} grid={len(zs)} {len(xs)}x{len(ys)} cells={len(zs)} steps={total_steps}") + shared.state.xyz_plot_x = AxisInfo(x_opt, xs) + shared.state.xyz_plot_y = AxisInfo(y_opt, ys) + shared.state.xyz_plot_z = AxisInfo(z_opt, zs) + # If one of the axes is very slow to change between (like SD model checkpoint), then make sure it is in the outer iteration of the nested `for` loop. first_axes_processed = 'z' second_axes_processed = 'y' if x_opt.cost > y_opt.cost and x_opt.cost > z_opt.cost: @@ -632,41 +593,33 @@ class Script(scripts.Script): second_axes_processed = 'x' else: second_axes_processed = 'y' - grid_infotext = [None] * (1 + len(zs)) def cell(x, y, z, ix, iy, iz): if shared.state.interrupted: return Processed(p, [], p.seed, "") - pc = copy(p) pc.styles = pc.styles[:] x_opt.apply(pc, x, xs) y_opt.apply(pc, y, ys) z_opt.apply(pc, z, zs) - res = process_images(pc) - # Sets subgrid infotexts subgrid_index = 1 + iz if grid_infotext[subgrid_index] is None and ix == 0 and iy == 0: pc.extra_generation_params = copy(pc.extra_generation_params) pc.extra_generation_params['Script'] = self.title() - if x_opt.label != 'Nothing': pc.extra_generation_params["X Type"] = x_opt.label pc.extra_generation_params["X Values"] = x_values if x_opt.label in ["Seed", "Var. seed"] and not no_fixed_seeds: pc.extra_generation_params["Fixed X Values"] = ", ".join([str(x) for x in xs]) - if y_opt.label != 'Nothing': pc.extra_generation_params["Y Type"] = y_opt.label pc.extra_generation_params["Y Values"] = y_values if y_opt.label in ["Seed", "Var. seed"] and not no_fixed_seeds: pc.extra_generation_params["Fixed Y Values"] = ", ".join([str(y) for y in ys]) - grid_infotext[subgrid_index] = processing.create_infotext(pc, pc.all_prompts, pc.all_seeds, pc.all_subseeds) - # Sets main grid infotext if grid_infotext[0] is None and ix == 0 and iy == 0 and iz == 0: pc.extra_generation_params = copy(pc.extra_generation_params) @@ -676,9 +629,7 @@ class Script(scripts.Script): pc.extra_generation_params["Z Values"] = z_values if z_opt.label in ["Seed", "Var. seed"] and not no_fixed_seeds: pc.extra_generation_params["Fixed Z Values"] = ", ".join([str(z) for z in zs]) - grid_infotext[0] = processing.create_infotext(pc, pc.all_prompts, pc.all_seeds, pc.all_subseeds) - return res with SharedSettingsStackHelper(): @@ -702,23 +653,18 @@ class Script(scripts.Script): if not processed.images: # It broke, no further handling needed. return processed - z_count = len(zs) - # Set the grid infotexts to the real ones with extra_generation_params (1 main grid + z_count sub-grids) processed.infotexts[:1+z_count] = grid_infotext[:1+z_count] - if not include_lone_images: # Don't need sub-images anymore, drop from list: processed.images = processed.images[:z_count+1] - - if opts.grid_save: + if shared.opts.grid_save: # Auto-save main and sub-grids: grid_count = z_count + 1 if z_count > 1 else 1 for g in range(grid_count): adj_g = g-1 if g > 0 else g - images.save_image(processed.images[g], p.outpath_grids, "xyz_grid", info=processed.infotexts[g], extension=opts.grid_format, prompt=processed.all_prompts[adj_g], seed=processed.all_seeds[adj_g], grid=True, p=processed) - + images.save_image(processed.images[g], p.outpath_grids, "xyz_grid", info=processed.infotexts[g], extension=shared.opts.grid_format, prompt=processed.all_prompts[adj_g], seed=processed.all_seeds[adj_g], grid=True, p=processed) if not include_sub_grids: # Done with sub-grids, drop all related information: for _sg in range(z_count): @@ -726,5 +672,4 @@ class Script(scripts.Script): del processed.all_prompts[1] del processed.all_seeds[1] del processed.infotexts[1] - return processed