Optimize XY grid to run slower axes fewer times
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space-nuko
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dd292a925e
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029260b4ca
@ -175,76 +175,87 @@ def str_permutations(x):
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"""dummy function for specifying it in AxisOption's type when you want to get a list of permutations"""
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return x
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AxisOption = namedtuple("AxisOption", ["label", "type", "apply", "format_value", "confirm"])
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AxisOptionImg2Img = namedtuple("AxisOptionImg2Img", ["label", "type", "apply", "format_value", "confirm"])
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AxisOption = namedtuple("AxisOption", ["label", "type", "apply", "format_value", "confirm", "cost"])
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AxisOptionImg2Img = namedtuple("AxisOptionImg2Img", ["label", "type", "apply", "format_value", "confirm", "cost"])
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axis_options = [
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AxisOption("Nothing", str, do_nothing, format_nothing, None),
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AxisOption("Seed", int, apply_field("seed"), format_value_add_label, None),
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AxisOption("Var. seed", int, apply_field("subseed"), format_value_add_label, None),
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AxisOption("Var. strength", float, apply_field("subseed_strength"), format_value_add_label, None),
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AxisOption("Steps", int, apply_field("steps"), format_value_add_label, None),
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AxisOption("CFG Scale", float, apply_field("cfg_scale"), format_value_add_label, None),
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AxisOption("Prompt S/R", str, apply_prompt, format_value, None),
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AxisOption("Prompt order", str_permutations, apply_order, format_value_join_list, None),
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AxisOption("Sampler", str, apply_sampler, format_value, confirm_samplers),
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AxisOption("Checkpoint name", str, apply_checkpoint, format_value, confirm_checkpoints),
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AxisOption("Hypernetwork", str, apply_hypernetwork, format_value, confirm_hypernetworks),
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AxisOption("Hypernet str.", float, apply_hypernetwork_strength, format_value_add_label, None),
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AxisOption("Sigma Churn", float, apply_field("s_churn"), format_value_add_label, None),
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AxisOption("Sigma min", float, apply_field("s_tmin"), format_value_add_label, None),
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AxisOption("Sigma max", float, apply_field("s_tmax"), format_value_add_label, None),
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AxisOption("Sigma noise", float, apply_field("s_noise"), format_value_add_label, None),
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AxisOption("Eta", float, apply_field("eta"), format_value_add_label, None),
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AxisOption("Clip skip", int, apply_clip_skip, format_value_add_label, None),
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AxisOption("Denoising", float, apply_field("denoising_strength"), format_value_add_label, None),
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AxisOption("Hires upscaler", str, apply_field("hr_upscaler"), format_value_add_label, None),
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AxisOption("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight"), format_value_add_label, None),
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AxisOption("VAE", str, apply_vae, format_value_add_label, None),
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AxisOption("Styles", str, apply_styles, format_value_add_label, None),
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AxisOption("Nothing", str, do_nothing, format_nothing, None, 0),
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AxisOption("Seed", int, apply_field("seed"), format_value_add_label, None, 0),
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AxisOption("Var. seed", int, apply_field("subseed"), format_value_add_label, None, 0),
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AxisOption("Var. strength", float, apply_field("subseed_strength"), format_value_add_label, None, 0),
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AxisOption("Steps", int, apply_field("steps"), format_value_add_label, None, 0),
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AxisOption("CFG Scale", float, apply_field("cfg_scale"), format_value_add_label, None, 0),
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AxisOption("Prompt S/R", str, apply_prompt, format_value, None, 0),
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AxisOption("Prompt order", str_permutations, apply_order, format_value_join_list, None, 0),
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AxisOption("Sampler", str, apply_sampler, format_value, confirm_samplers, 0),
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AxisOption("Checkpoint name", str, apply_checkpoint, format_value, confirm_checkpoints, 1.0),
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AxisOption("Hypernetwork", str, apply_hypernetwork, format_value, confirm_hypernetworks, 0.2),
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AxisOption("Hypernet str.", float, apply_hypernetwork_strength, format_value_add_label, None, 0),
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AxisOption("Sigma Churn", float, apply_field("s_churn"), format_value_add_label, None, 0),
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AxisOption("Sigma min", float, apply_field("s_tmin"), format_value_add_label, None, 0),
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AxisOption("Sigma max", float, apply_field("s_tmax"), format_value_add_label, None, 0),
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AxisOption("Sigma noise", float, apply_field("s_noise"), format_value_add_label, None, 0),
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AxisOption("Eta", float, apply_field("eta"), format_value_add_label, None, 0),
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AxisOption("Clip skip", int, apply_clip_skip, format_value_add_label, None, 0),
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AxisOption("Denoising", float, apply_field("denoising_strength"), format_value_add_label, None, 0),
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AxisOption("Hires upscaler", str, apply_field("hr_upscaler"), format_value_add_label, None, 0),
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AxisOption("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight"), format_value_add_label, None, 0),
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AxisOption("VAE", str, apply_vae, format_value_add_label, None, 0.7),
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AxisOption("Styles", str, apply_styles, format_value_add_label, None, 0),
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]
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def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend, include_lone_images):
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def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend, include_lone_images, swap_axes_processing_order):
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ver_texts = [[images.GridAnnotation(y)] for y in y_labels]
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hor_texts = [[images.GridAnnotation(x)] for x in x_labels]
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# Temporary list of all the images that are generated to be populated into the grid.
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# Will be filled with empty images for any individual step that fails to process properly
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image_cache = []
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image_cache = [None] * (len(xs) * len(ys))
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processed_result = None
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cell_mode = "P"
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cell_size = (1,1)
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cell_size = (1, 1)
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state.job_count = len(xs) * len(ys) * p.n_iter
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for iy, y in enumerate(ys):
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def process_cell(x, y, ix, iy):
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nonlocal image_cache, processed_result, cell_mode, cell_size
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state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}"
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processed: Processed = cell(x, y)
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try:
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# this dereference will throw an exception if the image was not processed
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# (this happens in cases such as if the user stops the process from the UI)
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processed_image = processed.images[0]
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if processed_result is None:
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# Use our first valid processed result as a template container to hold our full results
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processed_result = copy(processed)
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cell_mode = processed_image.mode
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cell_size = processed_image.size
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processed_result.images = [Image.new(cell_mode, cell_size)]
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image_cache[ix + iy * len(xs)] = processed_image
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if include_lone_images:
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processed_result.images.append(processed_image)
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processed_result.all_prompts.append(processed.prompt)
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processed_result.all_seeds.append(processed.seed)
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processed_result.infotexts.append(processed.infotexts[0])
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except:
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image_cache[ix + iy * len(xs)] = Image.new(cell_mode, cell_size)
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if swap_axes_processing_order:
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for ix, x in enumerate(xs):
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state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}"
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processed:Processed = cell(x, y)
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try:
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# this dereference will throw an exception if the image was not processed
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# (this happens in cases such as if the user stops the process from the UI)
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processed_image = processed.images[0]
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if processed_result is None:
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# Use our first valid processed result as a template container to hold our full results
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processed_result = copy(processed)
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cell_mode = processed_image.mode
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cell_size = processed_image.size
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processed_result.images = [Image.new(cell_mode, cell_size)]
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image_cache.append(processed_image)
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if include_lone_images:
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processed_result.images.append(processed_image)
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processed_result.all_prompts.append(processed.prompt)
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processed_result.all_seeds.append(processed.seed)
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processed_result.infotexts.append(processed.infotexts[0])
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except:
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image_cache.append(Image.new(cell_mode, cell_size))
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for iy, y in enumerate(ys):
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process_cell(x, y, ix, iy)
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else:
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for iy, y in enumerate(ys):
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for ix, x in enumerate(xs):
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process_cell(x, y, ix, iy)
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if not processed_result:
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print("Unexpected error: draw_xy_grid failed to return even a single processed image")
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@ -405,6 +416,11 @@ class Script(scripts.Script):
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grid_infotext = [None]
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# If one of the axes is very slow to change between (like SD model
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# checkpoint), then make sure it is in the outer iteration of the nested
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# `for` loop.
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swap_axes_processing_order = x_opt.cost > y_opt.cost
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def cell(x, y):
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if shared.state.interrupted:
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return Processed(p, [], p.seed, "")
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@ -443,7 +459,8 @@ class Script(scripts.Script):
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y_labels=[y_opt.format_value(p, y_opt, y) for y in ys],
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cell=cell,
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draw_legend=draw_legend,
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include_lone_images=include_lone_images
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include_lone_images=include_lone_images,
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swap_axes_processing_order=swap_axes_processing_order
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)
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if opts.grid_save:
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