def fun(p, x, xs):

setattr(p, field, x)

sampler_index = samplers_dict.get(x.lower(), None)

if sampler_index is None:

raise RuntimeError(f"Unknown sampler: {x}")

applicable = [info for info in modules.sd_models.checkpoints_list.values() if x in info.title]

assert len(applicable) > 0, f'Checkpoint {x} for found'

info = applicable[0]

if type(x) == float:

x = round(x, 8)

if type(x) == float:

x = round(x, 8)

AxisOption("Nothing", str, do_nothing, format_nothing),

AxisOption("Seed", int, apply_field("seed"), format_value_add_label),

AxisOption("Var. seed", int, apply_field("subseed"), format_value_add_label),

AxisOption("Var. strength", float, apply_field("subseed_strength"), format_value_add_label),

AxisOption("Steps", int, apply_field("steps"), format_value_add_label),

AxisOption("CFG Scale", float, apply_field("cfg_scale"), format_value_add_label),

AxisOption("Prompt S/R", str, apply_prompt, format_value),

AxisOption("Sampler", str, apply_sampler, format_value),

AxisOption("Checkpoint name", str, apply_checkpoint, format_value),

AxisOptionImg2Img("Denoising", float, apply_field("denoising_strength"), format_value_add_label), # as it is now all AxisOptionImg2Img items must go after AxisOption ones

res = []

ver_texts = [[images.GridAnnotation(y)] for y in y_labels]

hor_texts = [[images.GridAnnotation(x)] for x in x_labels]

first_pocessed = None

state.job_count = len(xs) * len(ys) * p.n_iter

for iy, y in enumerate(ys):

for ix, x in enumerate(xs):

state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}"

processed = cell(x, y)

if first_pocessed is None:

first_pocessed = processed

res.append(processed.images[0])

grid = images.image_grid(res, rows=len(ys))

if draw_legend:

grid = images.draw_grid_annotations(grid, res[0].width, res[0].height, hor_texts, ver_texts)

first_pocessed.images = [grid]

def title(self):

return "X/Y plot"

def ui(self, is_img2img):

current_axis_options = [x for x in axis_options if type(x) == AxisOption or type(x) == AxisOptionImg2Img and is_img2img]

with gr.Row():

x_type = gr.Dropdown(label="X type", choices=[x.label for x in current_axis_options], value=current_axis_options[1].label, visible=False, type="index", elem_id="x_type")

x_values = gr.Textbox(label="X values", visible=False, lines=1)

with gr.Row():

y_type = gr.Dropdown(label="Y type", choices=[x.label for x in current_axis_options], value=current_axis_options[4].label, visible=False, type="index", elem_id="y_type")

y_values = gr.Textbox(label="Y values", visible=False, lines=1)

draw_legend = gr.Checkbox(label='Draw legend', value=True)

return [x_type, x_values, y_type, y_values, draw_legend]

def run(self, p, x_type, x_values, y_type, y_values, draw_legend):

modules.processing.fix_seed(p)

p.batch_size = 1

def process_axis(opt, vals):

valslist = [x.strip() for x in vals.split(",")]

if opt.type == int:

valslist_ext = []

for val in valslist:

m = re_range.fullmatch(val)

mc = re_range_count.fullmatch(val)

if m is not None:

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)

if m is not None:

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

valslist = [opt.type(x) for x in valslist]

return valslist

x_opt = axis_options[x_type]

xs = process_axis(x_opt, x_values)

y_opt = axis_options[y_type]

ys = process_axis(y_opt, y_values)

def cell(x, y):

pc = copy(p)

x_opt.apply(pc, x, xs)

y_opt.apply(pc, y, ys)

return process_images(pc)

processed = draw_xy_grid(

p,

xs=xs,

ys=ys,

x_labels=[x_opt.format_value(p, x_opt, x) for x in xs],

y_labels=[y_opt.format_value(p, y_opt, y) for y in ys],

cell=cell,

draw_legend=draw_legend

)

if opts.grid_save:

images.save_image(processed.images[0], p.outpath_grids, "xy_grid", prompt=p.prompt, seed=processed.seed, grid=True, p=p)

# restore checkpoint in case it was changed by axes

modules.sd_models.reload_model_weights(shared.sd_model)