From c8d453e91561e57fbb76119f688a5eae9d1a6aef Mon Sep 17 00:00:00 2001
From: w-e-w <40751091+w-e-w@users.noreply.github.com>
Date: Sat, 12 Aug 2023 22:14:19 +0900
Subject: bring back csv mode

---
 scripts/xyz_grid.py | 44 ++++++++++++++++++++++++++++----------------
 1 file changed, 28 insertions(+), 16 deletions(-)

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index d37b428f..80cb3cfb 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -182,6 +182,10 @@ def str_permutations(x):
     """dummy function for specifying it in AxisOption's type when you want to get a list of permutations"""
     return x
 
+def list_to_csv_string(data_list):
+    with StringIO() as o:
+        csv.writer(o).writerow(data_list)
+        return o.getvalue().strip()
 
 class AxisOption:
     def __init__(self, label, type, apply, format_value=format_value_add_label, confirm=None, cost=0.0, choices=None):
@@ -377,6 +381,8 @@ re_range_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d
 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*")
 
+use_dropdown = True
+
 
 class Script(scripts.Script):
     def title(self):
@@ -430,28 +436,34 @@ class Script(scripts.Script):
         xz_swap_args = [x_type, x_values, x_values_dropdown, z_type, z_values, z_values_dropdown]
         swap_xz_axes_button.click(swap_axes, inputs=xz_swap_args, outputs=xz_swap_args)
 
-        def fill(x_type):
-            axis = self.current_axis_options[x_type]
-            return axis.choices() if axis.choices else gr.update()
+        def fill(axis_type):
+            axis = self.current_axis_options[axis_type]
+            if axis.choices:
+                if use_dropdown:
+                    return gr.update(), axis.choices()
+                else:
+                    return list_to_csv_string(axis.choices()), gr.update()
+            else:
+                return gr.update(), gr.update()
 
-        fill_x_button.click(fn=fill, inputs=[x_type], outputs=[x_values_dropdown])
-        fill_y_button.click(fn=fill, inputs=[y_type], outputs=[y_values_dropdown])
-        fill_z_button.click(fn=fill, inputs=[z_type], outputs=[z_values_dropdown])
+        fill_x_button.click(fn=fill, inputs=[x_type], outputs=[x_values, x_values_dropdown])
+        fill_y_button.click(fn=fill, inputs=[y_type], outputs=[y_values, y_values_dropdown])
+        fill_z_button.click(fn=fill, inputs=[z_type], outputs=[z_values, z_values_dropdown])
 
-        def select_axis(axis_type,axis_values_dropdown):
+        def select_axis(axis_type, axis_values_dropdown):
             choices = self.current_axis_options[axis_type].choices
             has_choices = choices is not None
             current_values = axis_values_dropdown
             if has_choices:
                 choices = choices()
-                if isinstance(current_values,str):
+                if isinstance(current_values, str):
                     current_values = current_values.split(",")
                 current_values = list(filter(lambda x: x in choices, current_values))
-            return gr.Button.update(visible=has_choices),gr.Textbox.update(visible=not has_choices),gr.update(choices=choices if has_choices else None,visible=has_choices,value=current_values)
+            return gr.Button.update(visible=has_choices), gr.Textbox.update(visible=not has_choices or not use_dropdown), gr.update(choices=choices if has_choices else None, visible=has_choices and use_dropdown, value=current_values)
 
-        x_type.change(fn=select_axis, inputs=[x_type,x_values_dropdown], outputs=[fill_x_button,x_values,x_values_dropdown])
-        y_type.change(fn=select_axis, inputs=[y_type,y_values_dropdown], outputs=[fill_y_button,y_values,y_values_dropdown])
-        z_type.change(fn=select_axis, inputs=[z_type,z_values_dropdown], outputs=[fill_z_button,z_values,z_values_dropdown])
+        x_type.change(fn=select_axis, inputs=[x_type, x_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown])
+        y_type.change(fn=select_axis, inputs=[y_type, y_values_dropdown], outputs=[fill_y_button, y_values, y_values_dropdown])
+        z_type.change(fn=select_axis, inputs=[z_type, z_values_dropdown], outputs=[fill_z_button, z_values, z_values_dropdown])
 
         def get_dropdown_update_from_params(axis,params):
             val_key = f"{axis} Values"
@@ -484,7 +496,7 @@ class Script(scripts.Script):
             if opt.label == 'Nothing':
                 return [0]
 
-            if opt.choices is not None:
+            if opt.choices is not None and use_dropdown:
                 valslist = vals_dropdown
             else:
                 valslist = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(vals))) if x]
@@ -545,17 +557,17 @@ class Script(scripts.Script):
             return valslist
 
         x_opt = self.current_axis_options[x_type]
-        if x_opt.choices is not None:
+        if x_opt.choices is not None and use_dropdown:
             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:
+        if y_opt.choices is not None and use_dropdown:
             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:
+        if z_opt.choices is not None and use_dropdown:
             z_values = ",".join(z_values_dropdown)
         zs = process_axis(z_opt, z_values, z_values_dropdown)
 
-- 
cgit v1.2.3


From d20eb11c9e210eb92b2c4821141f9647bfaaa9d2 Mon Sep 17 00:00:00 2001
From: w-e-w <40751091+w-e-w@users.noreply.github.com>
Date: Sat, 12 Aug 2023 22:24:00 +0900
Subject: format

---
 scripts/xyz_grid.py | 44 ++++++++++++++++++++++++--------------------
 1 file changed, 24 insertions(+), 20 deletions(-)

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 80cb3cfb..d8101dca 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -175,18 +175,22 @@ def do_nothing(p, x, xs):
 def format_nothing(p, opt, x):
     return ""
 
+
 def format_remove_path(p, opt, x):
     return os.path.basename(x)
 
+
 def str_permutations(x):
     """dummy function for specifying it in AxisOption's type when you want to get a list of permutations"""
     return x
 
+
 def list_to_csv_string(data_list):
     with StringIO() as o:
         csv.writer(o).writerow(data_list)
         return o.getvalue().strip()
 
+
 class AxisOption:
     def __init__(self, label, type, apply, format_value=format_value_add_label, confirm=None, cost=0.0, choices=None):
         self.label = label
@@ -203,6 +207,7 @@ class AxisOptionImg2Img(AxisOption):
         super().__init__(*args, **kwargs)
         self.is_img2img = True
 
+
 class AxisOptionTxt2Img(AxisOption):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
@@ -290,11 +295,10 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend
             cell_size = (processed_result.width, processed_result.height)
             if processed_result.images[0] is not None:
                 cell_mode = processed_result.images[0].mode
-                #This corrects size in case of batches:
+                # This corrects size in case of batches:
                 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':
@@ -352,9 +356,9 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend
     if draw_legend:
         z_grid = images.draw_grid_annotations(z_grid, sub_grid_size[0], sub_grid_size[1], title_texts, [[images.GridAnnotation()]])
     processed_result.images.insert(0, z_grid)
-    #TODO: Deeper aspects of the program rely on grid info being misaligned between metadata arrays, which is not ideal.
-    #processed_result.all_prompts.insert(0, processed_result.all_prompts[0])
-    #processed_result.all_seeds.insert(0, processed_result.all_seeds[0])
+    # TODO: Deeper aspects of the program rely on grid info being misaligned between metadata arrays, which is not ideal.
+    # 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
@@ -396,19 +400,19 @@ class Script(scripts.Script):
                 with gr.Row():
                     x_type = gr.Dropdown(label="X type", choices=[x.label for x in self.current_axis_options], value=self.current_axis_options[1].label, type="index", elem_id=self.elem_id("x_type"))
                     x_values = gr.Textbox(label="X values", lines=1, elem_id=self.elem_id("x_values"))
-                    x_values_dropdown = gr.Dropdown(label="X values",visible=False,multiselect=True,interactive=True)
+                    x_values_dropdown = gr.Dropdown(label="X values", visible=False, multiselect=True, interactive=True)
                     fill_x_button = ToolButton(value=fill_values_symbol, elem_id="xyz_grid_fill_x_tool_button", visible=False)
 
                 with gr.Row():
                     y_type = gr.Dropdown(label="Y type", choices=[x.label for x in self.current_axis_options], value=self.current_axis_options[0].label, type="index", elem_id=self.elem_id("y_type"))
                     y_values = gr.Textbox(label="Y values", lines=1, elem_id=self.elem_id("y_values"))
-                    y_values_dropdown = gr.Dropdown(label="Y values",visible=False,multiselect=True,interactive=True)
+                    y_values_dropdown = gr.Dropdown(label="Y values", visible=False, multiselect=True, interactive=True)
                     fill_y_button = ToolButton(value=fill_values_symbol, elem_id="xyz_grid_fill_y_tool_button", visible=False)
 
                 with gr.Row():
                     z_type = gr.Dropdown(label="Z type", choices=[x.label for x in self.current_axis_options], value=self.current_axis_options[0].label, type="index", elem_id=self.elem_id("z_type"))
                     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)
+                    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"):
@@ -465,22 +469,22 @@ class Script(scripts.Script):
         y_type.change(fn=select_axis, inputs=[y_type, y_values_dropdown], outputs=[fill_y_button, y_values, y_values_dropdown])
         z_type.change(fn=select_axis, inputs=[z_type, z_values_dropdown], outputs=[fill_z_button, z_values, z_values_dropdown])
 
-        def get_dropdown_update_from_params(axis,params):
+        def get_dropdown_update_from_params(axis, params):
             val_key = f"{axis} Values"
-            vals = params.get(val_key,"")
+            vals = params.get(val_key, "")
             valslist = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(vals))) if x]
-            return gr.update(value = valslist)
+            return gr.update(value=valslist)
 
         self.infotext_fields = (
             (x_type, "X Type"),
             (x_values, "X Values"),
-            (x_values_dropdown, lambda params:get_dropdown_update_from_params("X",params)),
+            (x_values_dropdown, lambda params: get_dropdown_update_from_params("X", params)),
             (y_type, "Y Type"),
             (y_values, "Y Values"),
-            (y_values_dropdown, lambda params:get_dropdown_update_from_params("Y",params)),
+            (y_values_dropdown, lambda params: get_dropdown_update_from_params("Y", params)),
             (z_type, "Z Type"),
             (z_values, "Z Values"),
-            (z_values_dropdown, lambda params:get_dropdown_update_from_params("Z",params)),
+            (z_values_dropdown, lambda params: get_dropdown_update_from_params("Z", params)),
         )
 
         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]
@@ -515,8 +519,8 @@ class Script(scripts.Script):
                         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
+                        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:
@@ -537,8 +541,8 @@ class Script(scripts.Script):
                         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
+                        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:
@@ -572,7 +576,7 @@ class Script(scripts.Script):
         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
+        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)'
 
@@ -732,7 +736,7 @@ class Script(scripts.Script):
             # Auto-save main and sub-grids:
             grid_count = z_count + 1 if z_count > 1 else 1
             for g in range(grid_count):
-                #TODO: See previous comment about intentional data misalignment.
+                # TODO: See previous comment about intentional data misalignment.
                 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)
 
-- 
cgit v1.2.3


From fd617fad006bdaeb8061fae0dda642da6499c3df Mon Sep 17 00:00:00 2001
From: w-e-w <40751091+w-e-w@users.noreply.github.com>
Date: Sat, 12 Aug 2023 22:24:59 +0900
Subject: Redundant character escape '\]' in RegExp

---
 scripts/xyz_grid.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index d8101dca..0ed0f262 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -382,8 +382,8 @@ class SharedSettingsStackHelper(object):
 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*")
+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*")
 
 use_dropdown = True
 
-- 
cgit v1.2.3


From f131f84e13d6f1d06ffc6ac75c100357d0e7b3e7 Mon Sep 17 00:00:00 2001
From: w-e-w <40751091+w-e-w@users.noreply.github.com>
Date: Sat, 12 Aug 2023 23:12:33 +0900
Subject: dropdown mode chackbox

---
 scripts/xyz_grid.py | 21 +++++++++++++++------
 1 file changed, 15 insertions(+), 6 deletions(-)

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 0ed0f262..81597ade 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -385,8 +385,6 @@ re_range_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d
 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*")
 
-use_dropdown = True
-
 
 class Script(scripts.Script):
     def title(self):
@@ -422,6 +420,8 @@ class Script(scripts.Script):
             with gr.Column():
                 include_lone_images = gr.Checkbox(label='Include Sub Images', value=False, elem_id=self.elem_id("include_lone_images"))
                 include_sub_grids = gr.Checkbox(label='Include Sub Grids', value=False, elem_id=self.elem_id("include_sub_grids"))
+            with gr.Column():
+                use_dropdown = gr.Checkbox(label='use dropdown', value=True, elem_id=self.elem_id("use_dropdown"))
             with gr.Column():
                 margin_size = gr.Slider(label="Grid margins (px)", minimum=0, maximum=500, value=0, step=2, elem_id=self.elem_id("margin_size"))
 
@@ -443,7 +443,7 @@ class Script(scripts.Script):
         def fill(axis_type):
             axis = self.current_axis_options[axis_type]
             if axis.choices:
-                if use_dropdown:
+                if use_dropdown.value:
                     return gr.update(), axis.choices()
                 else:
                     return list_to_csv_string(axis.choices()), gr.update()
@@ -463,12 +463,21 @@ class Script(scripts.Script):
                 if isinstance(current_values, str):
                     current_values = current_values.split(",")
                 current_values = list(filter(lambda x: x in choices, current_values))
-            return gr.Button.update(visible=has_choices), gr.Textbox.update(visible=not has_choices or not use_dropdown), gr.update(choices=choices if has_choices else None, visible=has_choices and use_dropdown, value=current_values)
+            return gr.Button.update(visible=has_choices), gr.Textbox.update(visible=not has_choices or not use_dropdown.value), gr.update(choices=choices if has_choices else None, visible=has_choices and use_dropdown.value, value=current_values)
 
         x_type.change(fn=select_axis, inputs=[x_type, x_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown])
         y_type.change(fn=select_axis, inputs=[y_type, y_values_dropdown], outputs=[fill_y_button, y_values, y_values_dropdown])
         z_type.change(fn=select_axis, inputs=[z_type, z_values_dropdown], outputs=[fill_z_button, z_values, z_values_dropdown])
 
+        def change_choice_mode(_use_dropdown, x_type, x_values_dropdown, y_type, y_values_dropdown, z_type, z_values_dropdown):
+            use_dropdown.value = _use_dropdown
+            _fill_x_button, _x_values, _x_values_dropdown = select_axis(x_type, x_values_dropdown)
+            _fill_y_button, _y_values, _y_values_dropdown = select_axis(y_type, y_values_dropdown)
+            _fill_z_button, _z_values, _z_values_dropdown = select_axis(z_type, z_values_dropdown)
+            return _fill_x_button, _x_values, _x_values_dropdown, _fill_y_button, _y_values, _y_values_dropdown, _fill_z_button, _z_values, _z_values_dropdown
+
+        use_dropdown.change(fn=change_choice_mode, inputs=[use_dropdown, x_type, x_values_dropdown, y_type, y_values_dropdown, z_type, z_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown, fill_y_button, y_values, y_values_dropdown, fill_z_button, z_values, z_values_dropdown])
+
         def get_dropdown_update_from_params(axis, params):
             val_key = f"{axis} Values"
             vals = params.get(val_key, "")
@@ -487,9 +496,9 @@ class Script(scripts.Script):
             (z_values_dropdown, lambda params: get_dropdown_update_from_params("Z", params)),
         )
 
-        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]
+        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, use_dropdown]
 
-    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, use_dropdown):
         if not no_fixed_seeds:
             modules.processing.fix_seed(p)
 
-- 
cgit v1.2.3


From 7a68ac661574dc64f510b0c4cd3403443ca2f875 Mon Sep 17 00:00:00 2001
From: w-e-w <40751091+w-e-w@users.noreply.github.com>
Date: Sat, 12 Aug 2023 23:40:05 +0900
Subject: rename to csv mode

---
 scripts/xyz_grid.py | 28 ++++++++++++++--------------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 81597ade..67798202 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -421,7 +421,7 @@ class Script(scripts.Script):
                 include_lone_images = gr.Checkbox(label='Include Sub Images', value=False, elem_id=self.elem_id("include_lone_images"))
                 include_sub_grids = gr.Checkbox(label='Include Sub Grids', value=False, elem_id=self.elem_id("include_sub_grids"))
             with gr.Column():
-                use_dropdown = gr.Checkbox(label='use dropdown', value=True, elem_id=self.elem_id("use_dropdown"))
+                csv_mode = gr.Checkbox(label='CSV mode', value=False, elem_id=self.elem_id("CSV mode"))
             with gr.Column():
                 margin_size = gr.Slider(label="Grid margins (px)", minimum=0, maximum=500, value=0, step=2, elem_id=self.elem_id("margin_size"))
 
@@ -443,10 +443,10 @@ class Script(scripts.Script):
         def fill(axis_type):
             axis = self.current_axis_options[axis_type]
             if axis.choices:
-                if use_dropdown.value:
-                    return gr.update(), axis.choices()
-                else:
+                if csv_mode.value:
                     return list_to_csv_string(axis.choices()), gr.update()
+                else:
+                    return gr.update(), axis.choices()
             else:
                 return gr.update(), gr.update()
 
@@ -463,20 +463,20 @@ class Script(scripts.Script):
                 if isinstance(current_values, str):
                     current_values = current_values.split(",")
                 current_values = list(filter(lambda x: x in choices, current_values))
-            return gr.Button.update(visible=has_choices), gr.Textbox.update(visible=not has_choices or not use_dropdown.value), gr.update(choices=choices if has_choices else None, visible=has_choices and use_dropdown.value, value=current_values)
+            return gr.Button.update(visible=has_choices), gr.Textbox.update(visible=not has_choices or csv_mode.value), gr.update(choices=choices if has_choices else None, visible=has_choices and not csv_mode.value, value=current_values)
 
         x_type.change(fn=select_axis, inputs=[x_type, x_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown])
         y_type.change(fn=select_axis, inputs=[y_type, y_values_dropdown], outputs=[fill_y_button, y_values, y_values_dropdown])
         z_type.change(fn=select_axis, inputs=[z_type, z_values_dropdown], outputs=[fill_z_button, z_values, z_values_dropdown])
 
-        def change_choice_mode(_use_dropdown, x_type, x_values_dropdown, y_type, y_values_dropdown, z_type, z_values_dropdown):
-            use_dropdown.value = _use_dropdown
+        def change_choice_mode(_csv_mode, x_type, x_values_dropdown, y_type, y_values_dropdown, z_type, z_values_dropdown):
+            csv_mode.value = _csv_mode
             _fill_x_button, _x_values, _x_values_dropdown = select_axis(x_type, x_values_dropdown)
             _fill_y_button, _y_values, _y_values_dropdown = select_axis(y_type, y_values_dropdown)
             _fill_z_button, _z_values, _z_values_dropdown = select_axis(z_type, z_values_dropdown)
             return _fill_x_button, _x_values, _x_values_dropdown, _fill_y_button, _y_values, _y_values_dropdown, _fill_z_button, _z_values, _z_values_dropdown
 
-        use_dropdown.change(fn=change_choice_mode, inputs=[use_dropdown, x_type, x_values_dropdown, y_type, y_values_dropdown, z_type, z_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown, fill_y_button, y_values, y_values_dropdown, fill_z_button, z_values, z_values_dropdown])
+        csv_mode.change(fn=change_choice_mode, inputs=[csv_mode, x_type, x_values_dropdown, y_type, y_values_dropdown, z_type, z_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown, fill_y_button, y_values, y_values_dropdown, fill_z_button, z_values, z_values_dropdown])
 
         def get_dropdown_update_from_params(axis, params):
             val_key = f"{axis} Values"
@@ -496,9 +496,9 @@ class Script(scripts.Script):
             (z_values_dropdown, lambda params: get_dropdown_update_from_params("Z", params)),
         )
 
-        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, use_dropdown]
+        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, csv_mode]
 
-    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, use_dropdown):
+    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, csv_mode):
         if not no_fixed_seeds:
             modules.processing.fix_seed(p)
 
@@ -509,7 +509,7 @@ class Script(scripts.Script):
             if opt.label == 'Nothing':
                 return [0]
 
-            if opt.choices is not None and use_dropdown:
+            if opt.choices is not None and not csv_mode:
                 valslist = vals_dropdown
             else:
                 valslist = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(vals))) if x]
@@ -570,17 +570,17 @@ class Script(scripts.Script):
             return valslist
 
         x_opt = self.current_axis_options[x_type]
-        if x_opt.choices is not None and use_dropdown:
+        if x_opt.choices is not None and not csv_mode:
             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 and use_dropdown:
+        if y_opt.choices is not None and not csv_mode:
             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 and use_dropdown:
+        if z_opt.choices is not None and not csv_mode:
             z_values = ",".join(z_values_dropdown)
         zs = process_axis(z_opt, z_values, z_values_dropdown)
 
-- 
cgit v1.2.3


From 8d9ca46e0a09c414b0d07fa8a680de10c0e72ffe Mon Sep 17 00:00:00 2001
From: w-e-w <40751091+w-e-w@users.noreply.github.com>
Date: Sun, 13 Aug 2023 02:05:20 +0900
Subject: convert value when switching mode

---
 scripts/xyz_grid.py | 35 +++++++++++++++++++++--------------
 1 file changed, 21 insertions(+), 14 deletions(-)

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 67798202..bfaf9661 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -454,29 +454,36 @@ class Script(scripts.Script):
         fill_y_button.click(fn=fill, inputs=[y_type], outputs=[y_values, y_values_dropdown])
         fill_z_button.click(fn=fill, inputs=[z_type], outputs=[z_values, z_values_dropdown])
 
-        def select_axis(axis_type, axis_values_dropdown):
+        def select_axis(axis_type, axis_values, axis_values_dropdown):
             choices = self.current_axis_options[axis_type].choices
             has_choices = choices is not None
-            current_values = axis_values_dropdown
+
+            current_values = axis_values
+            current_dropdown_values = axis_values_dropdown
             if has_choices:
                 choices = choices()
-                if isinstance(current_values, str):
-                    current_values = current_values.split(",")
-                current_values = list(filter(lambda x: x in choices, current_values))
-            return gr.Button.update(visible=has_choices), gr.Textbox.update(visible=not has_choices or csv_mode.value), gr.update(choices=choices if has_choices else None, visible=has_choices and not csv_mode.value, value=current_values)
+                if csv_mode.value:
+                    current_dropdown_values = list(filter(lambda x: x in choices, current_dropdown_values))
+                    current_values = list_to_csv_string(current_dropdown_values)
+                else:
+                    current_dropdown_values = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(axis_values)))]
+                    current_dropdown_values = list(filter(lambda x: x in choices, current_dropdown_values))
+
+            return (gr.Button.update(visible=has_choices), gr.Textbox.update(visible=not has_choices or csv_mode.value, value=current_values),
+                    gr.update(choices=choices if has_choices else None, visible=has_choices and not csv_mode.value, value=current_dropdown_values))
 
-        x_type.change(fn=select_axis, inputs=[x_type, x_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown])
-        y_type.change(fn=select_axis, inputs=[y_type, y_values_dropdown], outputs=[fill_y_button, y_values, y_values_dropdown])
-        z_type.change(fn=select_axis, inputs=[z_type, z_values_dropdown], outputs=[fill_z_button, z_values, z_values_dropdown])
+        x_type.change(fn=select_axis, inputs=[x_type, x_values, x_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown])
+        y_type.change(fn=select_axis, inputs=[y_type, y_values, y_values_dropdown], outputs=[fill_y_button, y_values, y_values_dropdown])
+        z_type.change(fn=select_axis, inputs=[z_type, z_values, z_values_dropdown], outputs=[fill_z_button, z_values, z_values_dropdown])
 
-        def change_choice_mode(_csv_mode, x_type, x_values_dropdown, y_type, y_values_dropdown, z_type, z_values_dropdown):
+        def change_choice_mode(_csv_mode, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown):
             csv_mode.value = _csv_mode
-            _fill_x_button, _x_values, _x_values_dropdown = select_axis(x_type, x_values_dropdown)
-            _fill_y_button, _y_values, _y_values_dropdown = select_axis(y_type, y_values_dropdown)
-            _fill_z_button, _z_values, _z_values_dropdown = select_axis(z_type, z_values_dropdown)
+            _fill_x_button, _x_values, _x_values_dropdown = select_axis(x_type, x_values, x_values_dropdown)
+            _fill_y_button, _y_values, _y_values_dropdown = select_axis(y_type, y_values, y_values_dropdown)
+            _fill_z_button, _z_values, _z_values_dropdown = select_axis(z_type, z_values, z_values_dropdown)
             return _fill_x_button, _x_values, _x_values_dropdown, _fill_y_button, _y_values, _y_values_dropdown, _fill_z_button, _z_values, _z_values_dropdown
 
-        csv_mode.change(fn=change_choice_mode, inputs=[csv_mode, x_type, x_values_dropdown, y_type, y_values_dropdown, z_type, z_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown, fill_y_button, y_values, y_values_dropdown, fill_z_button, z_values, z_values_dropdown])
+        csv_mode.change(fn=change_choice_mode, inputs=[csv_mode, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown, fill_y_button, y_values, y_values_dropdown, fill_z_button, z_values, z_values_dropdown])
 
         def get_dropdown_update_from_params(axis, params):
             val_key = f"{axis} Values"
-- 
cgit v1.2.3


From 299eb543083668a945d6074753ea8e8f13e7d66d Mon Sep 17 00:00:00 2001
From: w-e-w <40751091+w-e-w@users.noreply.github.com>
Date: Sun, 13 Aug 2023 02:17:13 +0900
Subject: pass csv_mode

---
 scripts/xyz_grid.py | 33 ++++++++++++++++-----------------
 1 file changed, 16 insertions(+), 17 deletions(-)

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index bfaf9661..254a75f4 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -440,21 +440,21 @@ class Script(scripts.Script):
         xz_swap_args = [x_type, x_values, x_values_dropdown, z_type, z_values, z_values_dropdown]
         swap_xz_axes_button.click(swap_axes, inputs=xz_swap_args, outputs=xz_swap_args)
 
-        def fill(axis_type):
+        def fill(axis_type, csv_mode):
             axis = self.current_axis_options[axis_type]
             if axis.choices:
-                if csv_mode.value:
+                if csv_mode:
                     return list_to_csv_string(axis.choices()), gr.update()
                 else:
                     return gr.update(), axis.choices()
             else:
                 return gr.update(), gr.update()
 
-        fill_x_button.click(fn=fill, inputs=[x_type], outputs=[x_values, x_values_dropdown])
-        fill_y_button.click(fn=fill, inputs=[y_type], outputs=[y_values, y_values_dropdown])
-        fill_z_button.click(fn=fill, inputs=[z_type], outputs=[z_values, z_values_dropdown])
+        fill_x_button.click(fn=fill, inputs=[x_type, csv_mode], outputs=[x_values, x_values_dropdown])
+        fill_y_button.click(fn=fill, inputs=[y_type, csv_mode], outputs=[y_values, y_values_dropdown])
+        fill_z_button.click(fn=fill, inputs=[z_type, csv_mode], outputs=[z_values, z_values_dropdown])
 
-        def select_axis(axis_type, axis_values, axis_values_dropdown):
+        def select_axis(axis_type, axis_values, axis_values_dropdown, csv_mode):
             choices = self.current_axis_options[axis_type].choices
             has_choices = choices is not None
 
@@ -462,25 +462,24 @@ class Script(scripts.Script):
             current_dropdown_values = axis_values_dropdown
             if has_choices:
                 choices = choices()
-                if csv_mode.value:
+                if csv_mode:
                     current_dropdown_values = list(filter(lambda x: x in choices, current_dropdown_values))
                     current_values = list_to_csv_string(current_dropdown_values)
                 else:
                     current_dropdown_values = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(axis_values)))]
                     current_dropdown_values = list(filter(lambda x: x in choices, current_dropdown_values))
 
-            return (gr.Button.update(visible=has_choices), gr.Textbox.update(visible=not has_choices or csv_mode.value, value=current_values),
-                    gr.update(choices=choices if has_choices else None, visible=has_choices and not csv_mode.value, value=current_dropdown_values))
+            return (gr.Button.update(visible=has_choices), gr.Textbox.update(visible=not has_choices or csv_mode, value=current_values),
+                    gr.update(choices=choices if has_choices else None, visible=has_choices and not csv_mode, value=current_dropdown_values))
 
-        x_type.change(fn=select_axis, inputs=[x_type, x_values, x_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown])
-        y_type.change(fn=select_axis, inputs=[y_type, y_values, y_values_dropdown], outputs=[fill_y_button, y_values, y_values_dropdown])
-        z_type.change(fn=select_axis, inputs=[z_type, z_values, z_values_dropdown], outputs=[fill_z_button, z_values, z_values_dropdown])
+        x_type.change(fn=select_axis, inputs=[x_type, x_values, x_values_dropdown, csv_mode], outputs=[fill_x_button, x_values, x_values_dropdown])
+        y_type.change(fn=select_axis, inputs=[y_type, y_values, y_values_dropdown, csv_mode], outputs=[fill_y_button, y_values, y_values_dropdown])
+        z_type.change(fn=select_axis, inputs=[z_type, z_values, z_values_dropdown, csv_mode], outputs=[fill_z_button, z_values, z_values_dropdown])
 
-        def change_choice_mode(_csv_mode, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown):
-            csv_mode.value = _csv_mode
-            _fill_x_button, _x_values, _x_values_dropdown = select_axis(x_type, x_values, x_values_dropdown)
-            _fill_y_button, _y_values, _y_values_dropdown = select_axis(y_type, y_values, y_values_dropdown)
-            _fill_z_button, _z_values, _z_values_dropdown = select_axis(z_type, z_values, z_values_dropdown)
+        def change_choice_mode(csv_mode, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown):
+            _fill_x_button, _x_values, _x_values_dropdown = select_axis(x_type, x_values, x_values_dropdown, csv_mode)
+            _fill_y_button, _y_values, _y_values_dropdown = select_axis(y_type, y_values, y_values_dropdown, csv_mode)
+            _fill_z_button, _z_values, _z_values_dropdown = select_axis(z_type, z_values, z_values_dropdown, csv_mode)
             return _fill_x_button, _x_values, _x_values_dropdown, _fill_y_button, _y_values, _y_values_dropdown, _fill_z_button, _z_values, _z_values_dropdown
 
         csv_mode.change(fn=change_choice_mode, inputs=[csv_mode, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown, fill_y_button, y_values, y_values_dropdown, fill_z_button, z_values, z_values_dropdown])
-- 
cgit v1.2.3


From dc5b5ee9c6beef9fa6ac9e8f9041063075e8d1e6 Mon Sep 17 00:00:00 2001
From: w-e-w <40751091+w-e-w@users.noreply.github.com>
Date: Sun, 13 Aug 2023 02:21:04 +0900
Subject: properly convert this into CSV string

---
 scripts/xyz_grid.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 254a75f4..0350e52a 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -577,17 +577,17 @@ class Script(scripts.Script):
 
         x_opt = self.current_axis_options[x_type]
         if x_opt.choices is not None and not csv_mode:
-            x_values = ",".join(x_values_dropdown)
+            x_values = list_to_csv_string(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 and not csv_mode:
-            y_values = ",".join(y_values_dropdown)
+            y_values = list_to_csv_string(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 and not csv_mode:
-            z_values = ",".join(z_values_dropdown)
+            z_values = list_to_csv_string(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
-- 
cgit v1.2.3


From fa9370b7411166c19e8e386400dc4e6082f47b2d Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 13 Aug 2023 06:07:30 +0300
Subject: add refiner to StableDiffusionProcessing class write out correct
 model name in infotext, rather than the refiner model

---
 modules/processing.py                 | 38 +++++++++++++++++++++++++++--------
 modules/processing_scripts/refiner.py | 16 +++++----------
 modules/sd_samplers_common.py         |  2 +-
 3 files changed, 36 insertions(+), 20 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index 6ad105d7..b47ddaa8 100755
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -111,7 +111,7 @@ class StableDiffusionProcessing:
     cached_uc = [None, None]
     cached_c = [None, None]
 
-    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 = None, tiling: bool = None, 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 = None, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None):
+    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 = None, tiling: bool = None, 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 = None, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, refiner_checkpoint: str = None, refiner_switch_at: float = None, script_args: list = None):
         if sampler_index is not None:
             print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
 
@@ -153,10 +153,14 @@ class StableDiffusionProcessing:
         self.s_noise = s_noise if s_noise is not None else opts.s_noise
         self.override_settings = {k: v for k, v in (override_settings or {}).items() if k not in shared.restricted_opts}
         self.override_settings_restore_afterwards = override_settings_restore_afterwards
+        self.refiner_checkpoint = refiner_checkpoint
+        self.refiner_switch_at = refiner_switch_at
+
         self.is_using_inpainting_conditioning = False
         self.disable_extra_networks = False
         self.token_merging_ratio = 0
         self.token_merging_ratio_hr = 0
+        self.refiner_checkpoint_info = None
 
         if not seed_enable_extras:
             self.subseed = -1
@@ -191,6 +195,11 @@ class StableDiffusionProcessing:
 
         self.user = None
 
+        self.sd_model_name = None
+        self.sd_model_hash = None
+        self.sd_vae_name = None
+        self.sd_vae_hash = None
+
     @property
     def sd_model(self):
         return shared.sd_model
@@ -408,7 +417,10 @@ class Processed:
         self.batch_size = p.batch_size
         self.restore_faces = p.restore_faces
         self.face_restoration_model = opts.face_restoration_model if p.restore_faces else None
-        self.sd_model_hash = shared.sd_model.sd_model_hash
+        self.sd_model_name = p.sd_model_name
+        self.sd_model_hash = p.sd_model_hash
+        self.sd_vae_name = p.sd_vae_name
+        self.sd_vae_hash = p.sd_vae_hash
         self.seed_resize_from_w = p.seed_resize_from_w
         self.seed_resize_from_h = p.seed_resize_from_h
         self.denoising_strength = getattr(p, 'denoising_strength', None)
@@ -459,7 +471,10 @@ class Processed:
             "batch_size": self.batch_size,
             "restore_faces": self.restore_faces,
             "face_restoration_model": self.face_restoration_model,
+            "sd_model_name": self.sd_model_name,
             "sd_model_hash": self.sd_model_hash,
+            "sd_vae_name": self.sd_vae_name,
+            "sd_vae_hash": self.sd_vae_hash,
             "seed_resize_from_w": self.seed_resize_from_w,
             "seed_resize_from_h": self.seed_resize_from_h,
             "denoising_strength": self.denoising_strength,
@@ -578,10 +593,10 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Seed": p.all_seeds[0] if use_main_prompt else all_seeds[index],
         "Face restoration": opts.face_restoration_model if p.restore_faces else None,
         "Size": f"{p.width}x{p.height}",
-        "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
-        "Model": (None if not opts.add_model_name_to_info else shared.sd_model.sd_checkpoint_info.name_for_extra),
-        "VAE hash": p.loaded_vae_hash if opts.add_model_hash_to_info else None,
-        "VAE": p.loaded_vae_name if opts.add_model_name_to_info else None,
+        "Model hash": p.sd_model_hash if opts.add_model_hash_to_info else None,
+        "Model": p.sd_model_name if opts.add_model_name_to_info else None,
+        "VAE hash": p.sd_vae_hash if opts.add_model_hash_to_info else None,
+        "VAE": p.sd_vae_name if opts.add_model_name_to_info else None,
         "Variation seed": (None if p.subseed_strength == 0 else (p.all_subseeds[0] if use_main_prompt else all_subseeds[index])),
         "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),
         "Seed resize from": (None if p.seed_resize_from_w <= 0 or p.seed_resize_from_h <= 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
@@ -670,8 +685,15 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     if p.tiling is None:
         p.tiling = opts.tiling
 
-    p.loaded_vae_name = sd_vae.get_loaded_vae_name()
-    p.loaded_vae_hash = sd_vae.get_loaded_vae_hash()
+    if p.refiner_checkpoint not in (None, "", "None"):
+        p.refiner_checkpoint_info = sd_models.get_closet_checkpoint_match(p.refiner_checkpoint)
+        if p.refiner_checkpoint_info is None:
+            raise Exception(f'Could not find checkpoint with name {p.refiner_checkpoint}')
+
+    p.sd_model_name = shared.sd_model.sd_checkpoint_info.name_for_extra
+    p.sd_model_hash = shared.sd_model.sd_model_hash
+    p.sd_vae_name = sd_vae.get_loaded_vae_name()
+    p.sd_vae_hash = sd_vae.get_loaded_vae_hash()
 
     modules.sd_hijack.model_hijack.apply_circular(p.tiling)
     modules.sd_hijack.model_hijack.clear_comments()
diff --git a/modules/processing_scripts/refiner.py b/modules/processing_scripts/refiner.py
index 773ec5d0..7b946d05 100644
--- a/modules/processing_scripts/refiner.py
+++ b/modules/processing_scripts/refiner.py
@@ -41,15 +41,9 @@ class ScriptRefiner(scripts.Script):
     def before_process(self, p, enable_refiner, refiner_checkpoint, refiner_switch_at):
         # the actual implementation is in sd_samplers_common.py, apply_refiner
 
-        p.refiner_checkpoint_info = None
-        p.refiner_switch_at = None
-
         if not enable_refiner or refiner_checkpoint in (None, "", "None"):
-            return
-
-        refiner_checkpoint_info = sd_models.get_closet_checkpoint_match(refiner_checkpoint)
-        if refiner_checkpoint_info is None:
-            raise Exception(f'Could not find checkpoint with name {refiner_checkpoint}')
-
-        p.refiner_checkpoint_info = refiner_checkpoint_info
-        p.refiner_switch_at = refiner_switch_at
+            p.refiner_checkpoint_info = None
+            p.refiner_switch_at = None
+        else:
+            p.refiner_checkpoint = refiner_checkpoint
+            p.refiner_switch_at = refiner_switch_at
diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 40c7aae0..380cdd5f 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -145,7 +145,7 @@ def apply_refiner(cfg_denoiser):
     refiner_switch_at = cfg_denoiser.p.refiner_switch_at
     refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info
 
-    if refiner_switch_at is not None and completed_ratio <= refiner_switch_at:
+    if refiner_switch_at is not None and completed_ratio < refiner_switch_at:
         return False
 
     if refiner_checkpoint_info is None or shared.sd_model.sd_checkpoint_info == refiner_checkpoint_info:
-- 
cgit v1.2.3


From 0e3bac8132e63a9adfca0223b4791f353ecb1057 Mon Sep 17 00:00:00 2001
From: w-e-w <40751091+w-e-w@users.noreply.github.com>
Date: Sun, 13 Aug 2023 04:12:37 +0900
Subject: rephrase and move

---
 scripts/xyz_grid.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 0350e52a..da0e48aa 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -420,10 +420,11 @@ class Script(scripts.Script):
             with gr.Column():
                 include_lone_images = gr.Checkbox(label='Include Sub Images', value=False, elem_id=self.elem_id("include_lone_images"))
                 include_sub_grids = gr.Checkbox(label='Include Sub Grids', value=False, elem_id=self.elem_id("include_sub_grids"))
-            with gr.Column():
-                csv_mode = gr.Checkbox(label='CSV mode', value=False, elem_id=self.elem_id("CSV mode"))
             with gr.Column():
                 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.Column():
+                csv_mode = gr.Checkbox(label='Use text inputs instead of dropdowns', value=False, elem_id=self.elem_id("csv_mode"))
+
 
         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")
-- 
cgit v1.2.3


From 599f61a1e0bddf463dd3c6adb84509b3d9db1941 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 13 Aug 2023 08:24:16 +0300
Subject: use dataclass for StableDiffusionProcessing

---
 modules/processing.py         | 318 +++++++++++++++++++++++-------------------
 modules/sd_samplers_common.py |   5 +-
 2 files changed, 176 insertions(+), 147 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index b47ddaa8..007a4e05 100755
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -1,9 +1,11 @@
+from __future__ import annotations
 import json
 import logging
 import math
 import os
 import sys
 import hashlib
+from dataclasses import dataclass, field
 
 import torch
 import numpy as np
@@ -11,7 +13,7 @@ from PIL import Image, ImageOps
 import random
 import cv2
 from skimage import exposure
-from typing import Any, Dict, List
+from typing import Any
 
 import modules.sd_hijack
 from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common, sd_unet, errors, rng
@@ -104,106 +106,126 @@ def txt2img_image_conditioning(sd_model, x, width, height):
         return x.new_zeros(x.shape[0], 5, 1, 1, dtype=x.dtype, device=x.device)
 
 
+@dataclass(repr=False)
 class StableDiffusionProcessing:
-    """
-    The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
-    """
+    sd_model: object = None
+    outpath_samples: str = None
+    outpath_grids: str = None
+    prompt: str = ""
+    prompt_for_display: str = None
+    negative_prompt: str = ""
+    styles: list[str] = field(default_factory=list)
+    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 = None
+    tiling: bool = None
+    do_not_save_samples: bool = False
+    do_not_save_grid: bool = False
+    extra_generation_params: dict[str, Any] = None
+    overlay_images: list = None
+    eta: float = None
+    do_not_reload_embeddings: bool = False
+    denoising_strength: float = 0
+    ddim_discretize: str = None
+    s_min_uncond: float = None
+    s_churn: float = None
+    s_tmax: float = None
+    s_tmin: float = None
+    s_noise: float = None
+    override_settings: dict[str, Any] = None
+    override_settings_restore_afterwards: bool = True
+    sampler_index: int = None
+    refiner_checkpoint: str = None
+    refiner_switch_at: float = None
+    token_merging_ratio = 0
+    token_merging_ratio_hr = 0
+    disable_extra_networks: bool = False
+
+    script_args: list = None
+
     cached_uc = [None, None]
     cached_c = [None, None]
 
-    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 = None, tiling: bool = None, 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 = None, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, refiner_checkpoint: str = None, refiner_switch_at: float = None, script_args: list = None):
-        if sampler_index is not None:
+    sampler: sd_samplers_common.Sampler | None = field(default=None, init=False)
+    is_using_inpainting_conditioning: bool = field(default=False, init=False)
+    paste_to: tuple | None = field(default=None, init=False)
+
+    is_hr_pass: bool = field(default=False, init=False)
+
+    c: tuple = field(default=None, init=False)
+    uc: tuple = field(default=None, init=False)
+
+    rng: rng.ImageRNG | None = field(default=None, init=False)
+    step_multiplier: int = field(default=1, init=False)
+    color_corrections: list = field(default=None, init=False)
+
+    scripts: list = field(default=None, init=False)
+    all_prompts: list = field(default=None, init=False)
+    all_negative_prompts: list = field(default=None, init=False)
+    all_seeds: list = field(default=None, init=False)
+    all_subseeds: list = field(default=None, init=False)
+    iteration: int = field(default=0, init=False)
+    main_prompt: str = field(default=None, init=False)
+    main_negative_prompt: str = field(default=None, init=False)
+
+    prompts: list = field(default=None, init=False)
+    negative_prompts: list = field(default=None, init=False)
+    seeds: list = field(default=None, init=False)
+    subseeds: list = field(default=None, init=False)
+    extra_network_data: dict = field(default=None, init=False)
+
+    user: str = field(default=None, init=False)
+
+    sd_model_name: str = field(default=None, init=False)
+    sd_model_hash: str = field(default=None, init=False)
+    sd_vae_name: str = field(default=None, init=False)
+    sd_vae_hash: str = field(default=None, init=False)
+
+    def __post_init__(self):
+        if self.sampler_index is not None:
             print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
 
-        self.outpath_samples: str = outpath_samples
-        self.outpath_grids: str = outpath_grids
-        self.prompt: str = prompt
-        self.prompt_for_display: str = None
-        self.negative_prompt: str = (negative_prompt or "")
-        self.styles: list = styles or []
-        self.seed: int = seed
-        self.subseed: int = subseed
-        self.subseed_strength: float = subseed_strength
-        self.seed_resize_from_h: int = seed_resize_from_h
-        self.seed_resize_from_w: int = seed_resize_from_w
-        self.sampler_name: str = sampler_name
-        self.batch_size: int = batch_size
-        self.n_iter: int = n_iter
-        self.steps: int = steps
-        self.cfg_scale: float = cfg_scale
-        self.width: int = width
-        self.height: int = height
-        self.restore_faces: bool = restore_faces
-        self.tiling: bool = tiling
-        self.do_not_save_samples: bool = do_not_save_samples
-        self.do_not_save_grid: bool = do_not_save_grid
-        self.extra_generation_params: dict = extra_generation_params or {}
-        self.overlay_images = overlay_images
-        self.eta = eta
-        self.do_not_reload_embeddings = do_not_reload_embeddings
-        self.paste_to = None
-        self.color_corrections = None
-        self.denoising_strength: float = denoising_strength
         self.sampler_noise_scheduler_override = None
-        self.ddim_discretize = ddim_discretize or opts.ddim_discretize
-        self.s_min_uncond = s_min_uncond or opts.s_min_uncond
-        self.s_churn = s_churn or opts.s_churn
-        self.s_tmin = s_tmin or opts.s_tmin
-        self.s_tmax = (s_tmax if s_tmax is not None else opts.s_tmax) or float('inf')
-        self.s_noise = s_noise if s_noise is not None else opts.s_noise
-        self.override_settings = {k: v for k, v in (override_settings or {}).items() if k not in shared.restricted_opts}
-        self.override_settings_restore_afterwards = override_settings_restore_afterwards
-        self.refiner_checkpoint = refiner_checkpoint
-        self.refiner_switch_at = refiner_switch_at
-
-        self.is_using_inpainting_conditioning = False
-        self.disable_extra_networks = False
-        self.token_merging_ratio = 0
-        self.token_merging_ratio_hr = 0
+        self.s_min_uncond = self.s_min_uncond if self.s_min_uncond is not None else opts.s_min_uncond
+        self.s_churn = self.s_churn if self.s_churn is not None else opts.s_churn
+        self.s_tmin = self.s_tmin if self.s_tmin is not None else opts.s_tmin
+        self.s_tmax = (self.s_tmax if self.s_tmax is not None else opts.s_tmax) or float('inf')
+        self.s_noise = self.s_noise if self.s_noise is not None else opts.s_noise
+
+        self.extra_generation_params = self.extra_generation_params or {}
+        self.override_settings = self.override_settings or {}
+        self.script_args = self.script_args or {}
+
         self.refiner_checkpoint_info = None
 
-        if not seed_enable_extras:
+        if not self.seed_enable_extras:
             self.subseed = -1
             self.subseed_strength = 0
             self.seed_resize_from_h = 0
             self.seed_resize_from_w = 0
 
-        self.scripts = None
-        self.script_args = script_args
-        self.all_prompts = None
-        self.all_negative_prompts = None
-        self.all_seeds = None
-        self.all_subseeds = None
-        self.iteration = 0
-        self.is_hr_pass = False
-        self.sampler = None
-        self.main_prompt = None
-        self.main_negative_prompt = None
-
-        self.prompts = None
-        self.negative_prompts = None
-        self.extra_network_data = None
-        self.seeds = None
-        self.subseeds = None
-
-        self.step_multiplier = 1
         self.cached_uc = StableDiffusionProcessing.cached_uc
         self.cached_c = StableDiffusionProcessing.cached_c
-        self.uc = None
-        self.c = None
-        self.rng: rng.ImageRNG = None
-
-        self.user = None
-
-        self.sd_model_name = None
-        self.sd_model_hash = None
-        self.sd_vae_name = None
-        self.sd_vae_hash = None
 
     @property
     def sd_model(self):
         return shared.sd_model
 
+    @sd_model.setter
+    def sd_model(self, value):
+        pass
+
     def txt2img_image_conditioning(self, x, width=None, height=None):
         self.is_using_inpainting_conditioning = self.sd_model.model.conditioning_key in {'hybrid', 'concat'}
 
@@ -932,49 +954,51 @@ def old_hires_fix_first_pass_dimensions(width, height):
     return width, height
 
 
+@dataclass(repr=False)
 class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
-    sampler = None
+    enable_hr: bool = False
+    denoising_strength: float = 0.75
+    firstphase_width: int = 0
+    firstphase_height: int = 0
+    hr_scale: float = 2.0
+    hr_upscaler: str = None
+    hr_second_pass_steps: int = 0
+    hr_resize_x: int = 0
+    hr_resize_y: int = 0
+    hr_checkpoint_name: str = None
+    hr_sampler_name: str = None
+    hr_prompt: str = ''
+    hr_negative_prompt: str = ''
+
     cached_hr_uc = [None, None]
     cached_hr_c = [None, None]
 
-    def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_checkpoint_name: str = None, hr_sampler_name: str = None, hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs):
-        super().__init__(**kwargs)
-        self.enable_hr = enable_hr
-        self.denoising_strength = denoising_strength
-        self.hr_scale = hr_scale
-        self.hr_upscaler = hr_upscaler
-        self.hr_second_pass_steps = hr_second_pass_steps
-        self.hr_resize_x = hr_resize_x
-        self.hr_resize_y = hr_resize_y
-        self.hr_upscale_to_x = hr_resize_x
-        self.hr_upscale_to_y = hr_resize_y
-        self.hr_checkpoint_name = hr_checkpoint_name
-        self.hr_checkpoint_info = None
-        self.hr_sampler_name = hr_sampler_name
-        self.hr_prompt = hr_prompt
-        self.hr_negative_prompt = hr_negative_prompt
-        self.all_hr_prompts = None
-        self.all_hr_negative_prompts = None
-        self.latent_scale_mode = None
-
-        if firstphase_width != 0 or firstphase_height != 0:
+    hr_checkpoint_info: dict = field(default=None, init=False)
+    hr_upscale_to_x: int = field(default=0, init=False)
+    hr_upscale_to_y: int = field(default=0, init=False)
+    truncate_x: int = field(default=0, init=False)
+    truncate_y: int = field(default=0, init=False)
+    applied_old_hires_behavior_to: tuple = field(default=None, init=False)
+    latent_scale_mode: dict = field(default=None, init=False)
+    hr_c: tuple | None = field(default=None, init=False)
+    hr_uc: tuple | None = field(default=None, init=False)
+    all_hr_prompts: list = field(default=None, init=False)
+    all_hr_negative_prompts: list = field(default=None, init=False)
+    hr_prompts: list = field(default=None, init=False)
+    hr_negative_prompts: list = field(default=None, init=False)
+    hr_extra_network_data: list = field(default=None, init=False)
+
+    def __post_init__(self):
+        super().__post_init__()
+
+        if self.firstphase_width != 0 or self.firstphase_height != 0:
             self.hr_upscale_to_x = self.width
             self.hr_upscale_to_y = self.height
-            self.width = firstphase_width
-            self.height = firstphase_height
-
-        self.truncate_x = 0
-        self.truncate_y = 0
-        self.applied_old_hires_behavior_to = None
-
-        self.hr_prompts = None
-        self.hr_negative_prompts = None
-        self.hr_extra_network_data = None
+            self.width = self.firstphase_width
+            self.height = self.firstphase_height
 
         self.cached_hr_uc = StableDiffusionProcessingTxt2Img.cached_hr_uc
         self.cached_hr_c = StableDiffusionProcessingTxt2Img.cached_hr_c
-        self.hr_c = None
-        self.hr_uc = None
 
     def calculate_target_resolution(self):
         if opts.use_old_hires_fix_width_height and self.applied_old_hires_behavior_to != (self.width, self.height):
@@ -1252,7 +1276,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
         return super().get_conds()
 
-
     def parse_extra_network_prompts(self):
         res = super().parse_extra_network_prompts()
 
@@ -1265,32 +1288,37 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
         return res
 
 
+@dataclass(repr=False)
 class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
-    sampler = None
-
-    def __init__(self, init_images: list = None, resize_mode: int = 0, denoising_strength: float = 0.75, image_cfg_scale: float = None, mask: Any = None, mask_blur: int = None, mask_blur_x: int = 4, mask_blur_y: int = 4, inpainting_fill: int = 0, inpaint_full_res: bool = True, inpaint_full_res_padding: int = 0, inpainting_mask_invert: int = 0, initial_noise_multiplier: float = None, **kwargs):
-        super().__init__(**kwargs)
-
-        self.init_images = init_images
-        self.resize_mode: int = resize_mode
-        self.denoising_strength: float = denoising_strength
-        self.image_cfg_scale: float = image_cfg_scale if shared.sd_model.cond_stage_key == "edit" else None
-        self.init_latent = None
-        self.image_mask = mask
-        self.latent_mask = None
-        self.mask_for_overlay = None
-        self.mask_blur_x = mask_blur_x
-        self.mask_blur_y = mask_blur_y
-        if mask_blur is not None:
-            self.mask_blur = mask_blur
-        self.inpainting_fill = inpainting_fill
-        self.inpaint_full_res = inpaint_full_res
-        self.inpaint_full_res_padding = inpaint_full_res_padding
-        self.inpainting_mask_invert = inpainting_mask_invert
-        self.initial_noise_multiplier = opts.initial_noise_multiplier if initial_noise_multiplier is None else initial_noise_multiplier
+    init_images: list = None
+    resize_mode: int = 0
+    denoising_strength: float = 0.75
+    image_cfg_scale: float = None
+    mask: Any = None
+    mask_blur_x: int = 4
+    mask_blur_y: int = 4
+    mask_blur: int = None
+    inpainting_fill: int = 0
+    inpaint_full_res: bool = True
+    inpaint_full_res_padding: int = 0
+    inpainting_mask_invert: int = 0
+    initial_noise_multiplier: float = None
+    latent_mask: Image = None
+
+    image_mask: Any = field(default=None, init=False)
+
+    nmask: torch.Tensor = field(default=None, init=False)
+    image_conditioning: torch.Tensor = field(default=None, init=False)
+    init_img_hash: str = field(default=None, init=False)
+    mask_for_overlay: Image = field(default=None, init=False)
+    init_latent: torch.Tensor = field(default=None, init=False)
+
+    def __post_init__(self):
+        super().__post_init__()
+
+        self.image_mask = self.mask
         self.mask = None
-        self.nmask = None
-        self.image_conditioning = None
+        self.initial_noise_multiplier = opts.initial_noise_multiplier if self.initial_noise_multiplier is None else self.initial_noise_multiplier
 
     @property
     def mask_blur(self):
@@ -1300,15 +1328,13 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
 
     @mask_blur.setter
     def mask_blur(self, value):
-        self.mask_blur_x = value
-        self.mask_blur_y = value
-
-    @mask_blur.deleter
-    def mask_blur(self):
-        del self.mask_blur_x
-        del self.mask_blur_y
+        if isinstance(value, int):
+            self.mask_blur_x = value
+            self.mask_blur_y = value
 
     def init(self, all_prompts, all_seeds, all_subseeds):
+        self.image_cfg_scale: float = self.image_cfg_scale if shared.sd_model.cond_stage_key == "edit" else None
+
         self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model)
         crop_region = None
 
diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 380cdd5f..09d1e11e 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -305,5 +305,8 @@ class Sampler:
         current_iter_seeds = p.all_seeds[p.iteration * p.batch_size:(p.iteration + 1) * p.batch_size]
         return BrownianTreeNoiseSampler(x, sigma_min, sigma_max, seed=current_iter_seeds)
 
+    def sample(self, p, x, conditioning, unconditional_conditioning, steps=None, image_conditioning=None):
+        raise NotImplementedError()
 
-
+    def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning, steps=None, image_conditioning=None):
+        raise NotImplementedError()
-- 
cgit v1.2.3


From 7fa5ee54b15904bef6598800df76ba1291d44ec6 Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sun, 13 Aug 2023 02:32:54 -0400
Subject: Support search and display of hashes for all extra network items

---
 extensions-builtin/Lora/ui_extra_networks_lora.py | 3 ++-
 modules/ui_extra_networks_checkpoints.py          | 1 +
 modules/ui_extra_networks_hypernets.py            | 6 +++++-
 modules/ui_extra_networks_textual_inversion.py    | 3 ++-
 modules/ui_extra_networks_user_metadata.py        | 4 +++-
 5 files changed, 13 insertions(+), 4 deletions(-)

diff --git a/extensions-builtin/Lora/ui_extra_networks_lora.py b/extensions-builtin/Lora/ui_extra_networks_lora.py
index 3629e5c0..55409a78 100644
--- a/extensions-builtin/Lora/ui_extra_networks_lora.py
+++ b/extensions-builtin/Lora/ui_extra_networks_lora.py
@@ -25,9 +25,10 @@ class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage):
         item = {
             "name": name,
             "filename": lora_on_disk.filename,
+            "shorthash": lora_on_disk.shorthash,
             "preview": self.find_preview(path),
             "description": self.find_description(path),
-            "search_term": self.search_terms_from_path(lora_on_disk.filename),
+            "search_term": self.search_terms_from_path(lora_on_disk.filename) + " " + (lora_on_disk.hash or ""),
             "local_preview": f"{path}.{shared.opts.samples_format}",
             "metadata": lora_on_disk.metadata,
             "sort_keys": {'default': index, **self.get_sort_keys(lora_on_disk.filename)},
diff --git a/modules/ui_extra_networks_checkpoints.py b/modules/ui_extra_networks_checkpoints.py
index 77885022..ebb5249f 100644
--- a/modules/ui_extra_networks_checkpoints.py
+++ b/modules/ui_extra_networks_checkpoints.py
@@ -19,6 +19,7 @@ class ExtraNetworksPageCheckpoints(ui_extra_networks.ExtraNetworksPage):
         return {
             "name": checkpoint.name_for_extra,
             "filename": checkpoint.filename,
+            "shorthash": checkpoint.shorthash,
             "preview": self.find_preview(path),
             "description": self.find_description(path),
             "search_term": self.search_terms_from_path(checkpoint.filename) + " " + (checkpoint.sha256 or ""),
diff --git a/modules/ui_extra_networks_hypernets.py b/modules/ui_extra_networks_hypernets.py
index 514a4562..4cedf085 100644
--- a/modules/ui_extra_networks_hypernets.py
+++ b/modules/ui_extra_networks_hypernets.py
@@ -2,6 +2,7 @@ import os
 
 from modules import shared, ui_extra_networks
 from modules.ui_extra_networks import quote_js
+from modules.hashes import sha256_from_cache
 
 
 class ExtraNetworksPageHypernetworks(ui_extra_networks.ExtraNetworksPage):
@@ -14,13 +15,16 @@ class ExtraNetworksPageHypernetworks(ui_extra_networks.ExtraNetworksPage):
     def create_item(self, name, index=None, enable_filter=True):
         full_path = shared.hypernetworks[name]
         path, ext = os.path.splitext(full_path)
+        sha256 = sha256_from_cache(full_path, f'hypernet/{name}')
+        shorthash = sha256[0:10] if sha256 else None
 
         return {
             "name": name,
             "filename": full_path,
+            "shorthash": shorthash,
             "preview": self.find_preview(path),
             "description": self.find_description(path),
-            "search_term": self.search_terms_from_path(path),
+            "search_term": self.search_terms_from_path(path) + " " + (sha256 or ""),
             "prompt": quote_js(f"<hypernet:{name}:") + " + opts.extra_networks_default_multiplier + " + quote_js(">"),
             "local_preview": f"{path}.preview.{shared.opts.samples_format}",
             "sort_keys": {'default': index, **self.get_sort_keys(path + ext)},
diff --git a/modules/ui_extra_networks_textual_inversion.py b/modules/ui_extra_networks_textual_inversion.py
index 73134698..55ef0ea7 100644
--- a/modules/ui_extra_networks_textual_inversion.py
+++ b/modules/ui_extra_networks_textual_inversion.py
@@ -19,9 +19,10 @@ class ExtraNetworksPageTextualInversion(ui_extra_networks.ExtraNetworksPage):
         return {
             "name": name,
             "filename": embedding.filename,
+            "shorthash": embedding.shorthash,
             "preview": self.find_preview(path),
             "description": self.find_description(path),
-            "search_term": self.search_terms_from_path(embedding.filename),
+            "search_term": self.search_terms_from_path(embedding.filename) + " " + (embedding.hash or ""),
             "prompt": quote_js(embedding.name),
             "local_preview": f"{path}.preview.{shared.opts.samples_format}",
             "sort_keys": {'default': index, **self.get_sort_keys(embedding.filename)},
diff --git a/modules/ui_extra_networks_user_metadata.py b/modules/ui_extra_networks_user_metadata.py
index cda471e4..b11622a1 100644
--- a/modules/ui_extra_networks_user_metadata.py
+++ b/modules/ui_extra_networks_user_metadata.py
@@ -93,11 +93,13 @@ class UserMetadataEditor:
         item = self.page.items.get(name, {})
         try:
             filename = item["filename"]
+            shorthash = item.get("shorthash", None)
 
             stats = os.stat(filename)
             params = [
                 ('Filename: ', os.path.basename(filename)),
                 ('File size: ', sysinfo.pretty_bytes(stats.st_size)),
+                ('Hash: ', shorthash),
                 ('Modified: ', datetime.datetime.fromtimestamp(stats.st_mtime).strftime('%Y-%m-%d %H:%M')),
             ]
 
@@ -115,7 +117,7 @@ class UserMetadataEditor:
             errors.display(e, f"reading metadata info for {name}")
             params = []
 
-        table = '<table class="file-metadata">' + "".join(f"<tr><th>{name}</th><td>{value}</td></tr>" for name, value in params) + '</table>'
+        table = '<table class="file-metadata">' + "".join(f"<tr><th>{name}</th><td>{value}</td></tr>" for name, value in params if value is not None) + '</table>'
 
         return html.escape(name), user_metadata.get('description', ''), table, self.get_card_html(name), user_metadata.get('notes', '')
 
-- 
cgit v1.2.3


From 822597db49218de17e105e62075096284dfcfd41 Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sun, 13 Aug 2023 04:16:48 -0400
Subject: Encode batches separately

Significantly reduces VRAM.
This makes encoding more inline with how decoding currently functions.
---
 modules/sd_samplers_common.py | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 09d1e11e..f9d034ca 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -92,7 +92,15 @@ def images_tensor_to_samples(image, approximation=None, model=None):
             model = shared.sd_model
         image = image.to(shared.device, dtype=devices.dtype_vae)
         image = image * 2 - 1
-        x_latent = model.get_first_stage_encoding(model.encode_first_stage(image))
+        if len(image) > 1:
+            x_latent = torch.stack([
+                model.get_first_stage_encoding(
+                    model.encode_first_stage(torch.unsqueeze(img, 0))
+                )[0]
+                for img in image
+            ])
+        else:
+            x_latent = model.get_first_stage_encoding(model.encode_first_stage(image))
 
     return x_latent
 
-- 
cgit v1.2.3


From 69f49c8d394220331eaa6609825b477eed60e0f4 Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sun, 13 Aug 2023 04:40:34 -0400
Subject: Clear sampler before decoding images

More significant VRAM reduction.
---
 modules/processing.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/modules/processing.py b/modules/processing.py
index 007a4e05..16104f92 100755
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -1192,6 +1192,9 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
         sd_models.apply_token_merging(self.sd_model, self.get_token_merging_ratio())
 
+        self.sampler = None
+        devices.torch_gc()
+
         decoded_samples = decode_latent_batch(self.sd_model, samples, target_device=devices.cpu, check_for_nans=True)
 
         self.is_hr_pass = False
-- 
cgit v1.2.3


From 1ae9dacb4b036a6cb4b5fb9b9ff030962f43908e Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sun, 13 Aug 2023 07:57:29 -0400
Subject: Add DPM-Solver++(3M) SDE

---
 modules/launch_utils.py           | 2 +-
 modules/sd_samplers_kdiffusion.py | 3 +++
 2 files changed, 4 insertions(+), 1 deletion(-)

diff --git a/modules/launch_utils.py b/modules/launch_utils.py
index 65eb684f..e30fbac8 100644
--- a/modules/launch_utils.py
+++ b/modules/launch_utils.py
@@ -319,7 +319,7 @@ def prepare_environment():
 
     stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "cf1d67a6fd5ea1aa600c4df58e5b47da45f6bdbf")
     stable_diffusion_xl_commit_hash = os.environ.get('STABLE_DIFFUSION_XL_COMMIT_HASH', "5c10deee76adad0032b412294130090932317a87")
-    k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "c9fe758757e022f05ca5a53fa8fac28889e4f1cf")
+    k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "ab527a9a6d347f364e3d185ba6d714e22d80cb3c")
     codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af")
     blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9")
 
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 1f8e9c4b..a48a563f 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -22,6 +22,9 @@ samplers_k_diffusion = [
     ('DPM++ 2M', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}),
     ('DPM++ SDE', 'sample_dpmpp_sde', ['k_dpmpp_sde'], {"second_order": True, "brownian_noise": True}),
     ('DPM++ 2M SDE', 'sample_dpmpp_2m_sde', ['k_dpmpp_2m_sde_ka'], {"brownian_noise": True}),
+    ('DPM++ 3M SDE', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde'], {"brownian_noise": True}),
+    ('DPM++ 3M SDE Karras', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde_ka'], {'scheduler': 'karras', "brownian_noise": True}),
+    ('DPM++ 3M SDE Exponential', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde_exp'], {'scheduler': 'exponential', "brownian_noise": True}),
     ('DPM fast', 'sample_dpm_fast', ['k_dpm_fast'], {"uses_ensd": True}),
     ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad'], {"uses_ensd": True}),
     ('LMS Karras', 'sample_lms', ['k_lms_ka'], {'scheduler': 'karras'}),
-- 
cgit v1.2.3


From 60a74051656e1e430aa7b466cfee8c13c6dc1a12 Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sun, 13 Aug 2023 08:06:40 -0400
Subject: Update description of eta setting

---
 modules/shared_options.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/shared_options.py b/modules/shared_options.py
index 9ae51f18..96db759b 100644
--- a/modules/shared_options.py
+++ b/modules/shared_options.py
@@ -285,7 +285,7 @@ options_templates.update(options_section(('ui', "Live previews"), {
 options_templates.update(options_section(('sampler-params', "Sampler parameters"), {
     "hide_samplers": OptionInfo([], "Hide samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in shared_items.list_samplers()]}).needs_reload_ui(),
     "eta_ddim": OptionInfo(0.0, "Eta for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext='Eta DDIM').info("noise multiplier; higher = more unperdictable results"),
-    "eta_ancestral": OptionInfo(1.0, "Eta for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext='Eta').info("noise multiplier; applies to Euler a and other samplers that have a in them"),
+    "eta_ancestral": OptionInfo(1.0, "Eta for k-diffusion samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext='Eta').info("noise multiplier; currently only applies to ancestral samplers (i.e. Euler a) and SDE samplers"),
     "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}),
     's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 100.0, "step": 0.01}, infotext='Sigma churn').info('amount of stochasticity; only applies to Euler, Heun, and DPM2'),
     's_tmin':  OptionInfo(0.0, "sigma tmin",  gr.Slider, {"minimum": 0.0, "maximum": 10.0, "step": 0.01}, infotext='Sigma tmin').info('enable stochasticity; start value of the sigma range; only applies to Euler, Heun, and DPM2'),
-- 
cgit v1.2.3


From d8419762c1454ba51baa710d9ce8e762efc056ef Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 13 Aug 2023 15:07:37 +0300
Subject: Lora: output warnings in UI rather than fail for unfitting loras;
 switch to logging for error output in console

---
 extensions-builtin/Lora/extra_networks_lora.py | 12 ++++-
 extensions-builtin/Lora/networks.py            | 61 ++++++++++++++++----------
 extensions-builtin/Lora/scripts/lora_script.py |  6 +--
 modules/processing.py                          | 13 +++---
 4 files changed, 58 insertions(+), 34 deletions(-)

diff --git a/extensions-builtin/Lora/extra_networks_lora.py b/extensions-builtin/Lora/extra_networks_lora.py
index ba2945c6..32e32cab 100644
--- a/extensions-builtin/Lora/extra_networks_lora.py
+++ b/extensions-builtin/Lora/extra_networks_lora.py
@@ -1,4 +1,4 @@
-from modules import extra_networks, shared
+from modules import extra_networks, shared, sd_hijack
 import networks
 
 
@@ -6,9 +6,14 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork):
     def __init__(self):
         super().__init__('lora')
 
+        self.errors = {}
+        """mapping of network names to the number of errors the network had during operation"""
+
     def activate(self, p, params_list):
         additional = shared.opts.sd_lora
 
+        self.errors.clear()
+
         if additional != "None" and additional in networks.available_networks and not any(x for x in params_list if x.items[0] == additional):
             p.all_prompts = [x + f"<lora:{additional}:{shared.opts.extra_networks_default_multiplier}>" for x in p.all_prompts]
             params_list.append(extra_networks.ExtraNetworkParams(items=[additional, shared.opts.extra_networks_default_multiplier]))
@@ -56,4 +61,7 @@ class ExtraNetworkLora(extra_networks.ExtraNetwork):
                 p.extra_generation_params["Lora hashes"] = ", ".join(network_hashes)
 
     def deactivate(self, p):
-        pass
+        if self.errors:
+            p.comment("Networks with errors: " + ", ".join(f"{k} ({v})" for k, v in self.errors.items()))
+
+            self.errors.clear()
diff --git a/extensions-builtin/Lora/networks.py b/extensions-builtin/Lora/networks.py
index ba621139..c252ed9e 100644
--- a/extensions-builtin/Lora/networks.py
+++ b/extensions-builtin/Lora/networks.py
@@ -1,3 +1,4 @@
+import logging
 import os
 import re
 
@@ -194,7 +195,7 @@ def load_network(name, network_on_disk):
         net.modules[key] = net_module
 
     if keys_failed_to_match:
-        print(f"Failed to match keys when loading network {network_on_disk.filename}: {keys_failed_to_match}")
+        logging.debug(f"Network {network_on_disk.filename} didn't match keys: {keys_failed_to_match}")
 
     return net
 
@@ -207,7 +208,6 @@ def purge_networks_from_memory():
     devices.torch_gc()
 
 
-
 def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=None):
     already_loaded = {}
 
@@ -248,7 +248,7 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No
 
         if net is None:
             failed_to_load_networks.append(name)
-            print(f"Couldn't find network with name {name}")
+            logging.info(f"Couldn't find network with name {name}")
             continue
 
         net.te_multiplier = te_multipliers[i] if te_multipliers else 1.0
@@ -257,7 +257,7 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No
         loaded_networks.append(net)
 
     if failed_to_load_networks:
-        sd_hijack.model_hijack.comments.append("Failed to find networks: " + ", ".join(failed_to_load_networks))
+        sd_hijack.model_hijack.comments.append("Networks not found: " + ", ".join(failed_to_load_networks))
 
     purge_networks_from_memory()
 
@@ -314,17 +314,22 @@ def network_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn
         for net in loaded_networks:
             module = net.modules.get(network_layer_name, None)
             if module is not None and hasattr(self, 'weight'):
-                with torch.no_grad():
-                    updown, ex_bias = module.calc_updown(self.weight)
+                try:
+                    with torch.no_grad():
+                        updown, ex_bias = module.calc_updown(self.weight)
 
-                    if len(self.weight.shape) == 4 and self.weight.shape[1] == 9:
-                        # inpainting model. zero pad updown to make channel[1]  4 to 9
-                        updown = torch.nn.functional.pad(updown, (0, 0, 0, 0, 0, 5))
+                        if len(self.weight.shape) == 4 and self.weight.shape[1] == 9:
+                            # inpainting model. zero pad updown to make channel[1]  4 to 9
+                            updown = torch.nn.functional.pad(updown, (0, 0, 0, 0, 0, 5))
 
-                    self.weight += updown
-                    if ex_bias is not None and getattr(self, 'bias', None) is not None:
-                        self.bias += ex_bias
-                    continue
+                        self.weight += updown
+                        if ex_bias is not None and getattr(self, 'bias', None) is not None:
+                            self.bias += ex_bias
+                except RuntimeError as e:
+                    logging.debug(f"Network {net.name} layer {network_layer_name}: {e}")
+                    extra_network_lora.errors[net.name] = extra_network_lora.errors.get(net.name, 0) + 1
+
+                continue
 
             module_q = net.modules.get(network_layer_name + "_q_proj", None)
             module_k = net.modules.get(network_layer_name + "_k_proj", None)
@@ -332,21 +337,28 @@ def network_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, torch.nn
             module_out = net.modules.get(network_layer_name + "_out_proj", None)
 
             if isinstance(self, torch.nn.MultiheadAttention) and module_q and module_k and module_v and module_out:
-                with torch.no_grad():
-                    updown_q = module_q.calc_updown(self.in_proj_weight)
-                    updown_k = module_k.calc_updown(self.in_proj_weight)
-                    updown_v = module_v.calc_updown(self.in_proj_weight)
-                    updown_qkv = torch.vstack([updown_q, updown_k, updown_v])
-                    updown_out = module_out.calc_updown(self.out_proj.weight)
-
-                    self.in_proj_weight += updown_qkv
-                    self.out_proj.weight += updown_out
-                    continue
+                try:
+                    with torch.no_grad():
+                        updown_q = module_q.calc_updown(self.in_proj_weight)
+                        updown_k = module_k.calc_updown(self.in_proj_weight)
+                        updown_v = module_v.calc_updown(self.in_proj_weight)
+                        updown_qkv = torch.vstack([updown_q, updown_k, updown_v])
+                        updown_out = module_out.calc_updown(self.out_proj.weight)
+
+                        self.in_proj_weight += updown_qkv
+                        self.out_proj.weight += updown_out
+
+                except RuntimeError as e:
+                    logging.debug(f"Network {net.name} layer {network_layer_name}: {e}")
+                    extra_network_lora.errors[net.name] = extra_network_lora.errors.get(net.name, 0) + 1
+
+                continue
 
             if module is None:
                 continue
 
-            print(f'failed to calculate network weights for layer {network_layer_name}')
+            logging.debug(f"Network {net.name} layer {network_layer_name}: couldn't find supported operation")
+            extra_network_lora.errors[net.name] = extra_network_lora.errors.get(net.name, 0) + 1
 
         self.network_current_names = wanted_names
 
@@ -519,6 +531,7 @@ def infotext_pasted(infotext, params):
     if added:
         params["Prompt"] += "\n" + "".join(added)
 
+extra_network_lora = None
 
 available_networks = {}
 available_network_aliases = {}
diff --git a/extensions-builtin/Lora/scripts/lora_script.py b/extensions-builtin/Lora/scripts/lora_script.py
index dc307f8c..4c6e774a 100644
--- a/extensions-builtin/Lora/scripts/lora_script.py
+++ b/extensions-builtin/Lora/scripts/lora_script.py
@@ -23,9 +23,9 @@ def unload():
 def before_ui():
     ui_extra_networks.register_page(ui_extra_networks_lora.ExtraNetworksPageLora())
 
-    extra_network = extra_networks_lora.ExtraNetworkLora()
-    extra_networks.register_extra_network(extra_network)
-    extra_networks.register_extra_network_alias(extra_network, "lyco")
+    networks.extra_network_lora = extra_networks_lora.ExtraNetworkLora()
+    extra_networks.register_extra_network(networks.extra_network_lora)
+    extra_networks.register_extra_network_alias(networks.extra_network_lora, "lyco")
 
 
 if not hasattr(torch.nn, 'Linear_forward_before_network'):
diff --git a/modules/processing.py b/modules/processing.py
index 007a4e05..10749aa2 100755
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -157,6 +157,7 @@ class StableDiffusionProcessing:
     cached_uc = [None, None]
     cached_c = [None, None]
 
+    comments: dict = None
     sampler: sd_samplers_common.Sampler | None = field(default=None, init=False)
     is_using_inpainting_conditioning: bool = field(default=False, init=False)
     paste_to: tuple | None = field(default=None, init=False)
@@ -196,6 +197,8 @@ class StableDiffusionProcessing:
         if self.sampler_index is not None:
             print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
 
+        self.comments = {}
+
         self.sampler_noise_scheduler_override = None
         self.s_min_uncond = self.s_min_uncond if self.s_min_uncond is not None else opts.s_min_uncond
         self.s_churn = self.s_churn if self.s_churn is not None else opts.s_churn
@@ -226,6 +229,9 @@ class StableDiffusionProcessing:
     def sd_model(self, value):
         pass
 
+    def comment(self, text):
+        self.comments[text] = 1
+
     def txt2img_image_conditioning(self, x, width=None, height=None):
         self.is_using_inpainting_conditioning = self.sd_model.model.conditioning_key in {'hybrid', 'concat'}
 
@@ -429,7 +435,7 @@ class Processed:
         self.subseed = subseed
         self.subseed_strength = p.subseed_strength
         self.info = info
-        self.comments = comments
+        self.comments = "".join(f"{comment}\n" for comment in p.comments)
         self.width = p.width
         self.height = p.height
         self.sampler_name = p.sampler_name
@@ -720,8 +726,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     modules.sd_hijack.model_hijack.apply_circular(p.tiling)
     modules.sd_hijack.model_hijack.clear_comments()
 
-    comments = {}
-
     p.setup_prompts()
 
     if type(seed) == list:
@@ -801,7 +805,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
             p.setup_conds()
 
             for comment in model_hijack.comments:
-                comments[comment] = 1
+                p.comment(comment)
 
             p.extra_generation_params.update(model_hijack.extra_generation_params)
 
@@ -930,7 +934,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
         images_list=output_images,
         seed=p.all_seeds[0],
         info=infotexts[0],
-        comments="".join(f"{comment}\n" for comment in comments),
         subseed=p.all_subseeds[0],
         index_of_first_image=index_of_first_image,
         infotexts=infotexts,
-- 
cgit v1.2.3


From d1a70c3f0534b88665d55bdac1e6b48a63f7f035 Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sun, 13 Aug 2023 08:22:24 -0400
Subject: Add s_noise param to more samplers

---
 modules/sd_samplers_common.py     | 8 ++++----
 modules/sd_samplers_kdiffusion.py | 6 ++++++
 2 files changed, 10 insertions(+), 4 deletions(-)

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 09d1e11e..d2fb21f4 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -276,19 +276,19 @@ class Sampler:
             s_tmax = getattr(opts, 's_tmax', p.s_tmax) or self.s_tmax # 0 = inf
             s_noise = getattr(opts, 's_noise', p.s_noise)
 
-            if s_churn != self.s_churn:
+            if 's_churn' in extra_params_kwargs and s_churn != self.s_churn:
                 extra_params_kwargs['s_churn'] = s_churn
                 p.s_churn = s_churn
                 p.extra_generation_params['Sigma churn'] = s_churn
-            if s_tmin != self.s_tmin:
+            if 's_tmin' in extra_params_kwargs and s_tmin != self.s_tmin:
                 extra_params_kwargs['s_tmin'] = s_tmin
                 p.s_tmin = s_tmin
                 p.extra_generation_params['Sigma tmin'] = s_tmin
-            if s_tmax != self.s_tmax:
+            if 's_tmax' in extra_params_kwargs and s_tmax != self.s_tmax:
                 extra_params_kwargs['s_tmax'] = s_tmax
                 p.s_tmax = s_tmax
                 p.extra_generation_params['Sigma tmax'] = s_tmax
-            if s_noise != self.s_noise:
+            if 's_noise' in extra_params_kwargs and s_noise != self.s_noise:
                 extra_params_kwargs['s_noise'] = s_noise
                 p.s_noise = s_noise
                 p.extra_generation_params['Sigma noise'] = s_noise
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index a48a563f..9f5dfd6d 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -45,6 +45,12 @@ sampler_extra_params = {
     'sample_euler': ['s_churn', 's_tmin', 's_tmax', 's_noise'],
     'sample_heun': ['s_churn', 's_tmin', 's_tmax', 's_noise'],
     'sample_dpm_2': ['s_churn', 's_tmin', 's_tmax', 's_noise'],
+    'sample_dpm_fast': ['s_noise'],
+    'sample_dpm_2_ancestral': ['s_noise'],
+    'sample_dpmpp_2s_ancestral': ['s_noise'],
+    'sample_dpmpp_sde': ['s_noise'],
+    'sample_dpmpp_2m_sde': ['s_noise'],
+    'sample_dpmpp_3m_sde': ['s_noise'],
 }
 
 k_diffusion_samplers_map = {x.name: x for x in samplers_data_k_diffusion}
-- 
cgit v1.2.3


From f4757032e7a0663abe2695c95048fdfff3fc5e2f Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sun, 13 Aug 2023 08:24:28 -0400
Subject: Fix s_noise description

---
 modules/shared_options.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/shared_options.py b/modules/shared_options.py
index 9ae51f18..279e9f54 100644
--- a/modules/shared_options.py
+++ b/modules/shared_options.py
@@ -290,7 +290,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
     's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 100.0, "step": 0.01}, infotext='Sigma churn').info('amount of stochasticity; only applies to Euler, Heun, and DPM2'),
     's_tmin':  OptionInfo(0.0, "sigma tmin",  gr.Slider, {"minimum": 0.0, "maximum": 10.0, "step": 0.01}, infotext='Sigma tmin').info('enable stochasticity; start value of the sigma range; only applies to Euler, Heun, and DPM2'),
     's_tmax':  OptionInfo(0.0, "sigma tmax",  gr.Slider, {"minimum": 0.0, "maximum": 999.0, "step": 0.01}, infotext='Sigma tmax').info("0 = inf; end value of the sigma range; only applies to Euler, Heun, and DPM2"),
-    's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.1, "step": 0.001}, infotext='Sigma noise').info('amount of additional noise to counteract loss of detail during sampling; only applies to Euler, Heun, and DPM2'),
+    's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.1, "step": 0.001}, infotext='Sigma noise').info('amount of additional noise to counteract loss of detail during sampling'),
     'k_sched_type':  OptionInfo("Automatic", "Scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}, infotext='Schedule type').info("lets you override the noise schedule for k-diffusion samplers; choosing Automatic disables the three parameters below"),
     'sigma_min': OptionInfo(0.0, "sigma min", gr.Number, infotext='Schedule max sigma').info("0 = default (~0.03); minimum noise strength for k-diffusion noise scheduler"),
     'sigma_max': OptionInfo(0.0, "sigma max", gr.Number, infotext='Schedule min sigma').info("0 = default (~14.6); maximum noise strength for k-diffusion noise scheduler"),
-- 
cgit v1.2.3


From ac790fc49b314761a7ad711989d7cc88bba64578 Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sun, 13 Aug 2023 08:46:07 -0400
Subject: Discard penultimate sigma for DPM-Solver++(3M) SDE

---
 modules/sd_samplers_kdiffusion.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index a48a563f..c8b81fa1 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -22,9 +22,9 @@ samplers_k_diffusion = [
     ('DPM++ 2M', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}),
     ('DPM++ SDE', 'sample_dpmpp_sde', ['k_dpmpp_sde'], {"second_order": True, "brownian_noise": True}),
     ('DPM++ 2M SDE', 'sample_dpmpp_2m_sde', ['k_dpmpp_2m_sde_ka'], {"brownian_noise": True}),
-    ('DPM++ 3M SDE', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde'], {"brownian_noise": True}),
-    ('DPM++ 3M SDE Karras', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde_ka'], {'scheduler': 'karras', "brownian_noise": True}),
-    ('DPM++ 3M SDE Exponential', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde_exp'], {'scheduler': 'exponential', "brownian_noise": True}),
+    ('DPM++ 3M SDE', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde'], {'discard_next_to_last_sigma': True, "brownian_noise": True}),
+    ('DPM++ 3M SDE Karras', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True, "brownian_noise": True}),
+    ('DPM++ 3M SDE Exponential', 'sample_dpmpp_3m_sde', ['k_dpmpp_3m_sde_exp'], {'scheduler': 'exponential', 'discard_next_to_last_sigma': True, "brownian_noise": True}),
     ('DPM fast', 'sample_dpm_fast', ['k_dpm_fast'], {"uses_ensd": True}),
     ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad'], {"uses_ensd": True}),
     ('LMS Karras', 'sample_lms', ['k_lms_ka'], {'scheduler': 'karras'}),
-- 
cgit v1.2.3


From 525b55b1e9dc589a1133a8031ed3b1646e5cccff Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sun, 13 Aug 2023 09:08:34 -0400
Subject: Restore extra_params that was lost in merge

---
 modules/sd_samplers_kdiffusion.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 1f8e9c4b..9a89e7fa 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -67,6 +67,8 @@ class KDiffusionSampler(sd_samplers_common.Sampler):
     def __init__(self, funcname, sd_model, options=None):
         super().__init__(funcname)
 
+        self.extra_params = sampler_extra_params.get(funcname, [])
+
         self.options = options or {}
         self.func = funcname if callable(funcname) else getattr(k_diffusion.sampling, self.funcname)
 
-- 
cgit v1.2.3


From db40d26d086b6e980bd28ce7eb3008ec09b1f0e8 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 13 Aug 2023 16:38:10 +0300
Subject: linter

---
 extensions-builtin/Lora/extra_networks_lora.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/extensions-builtin/Lora/extra_networks_lora.py b/extensions-builtin/Lora/extra_networks_lora.py
index 32e32cab..005ff32c 100644
--- a/extensions-builtin/Lora/extra_networks_lora.py
+++ b/extensions-builtin/Lora/extra_networks_lora.py
@@ -1,4 +1,4 @@
-from modules import extra_networks, shared, sd_hijack
+from modules import extra_networks, shared
 import networks
 
 
-- 
cgit v1.2.3


From 3163d1269af7f9fd95382e58bb1581fd741b5119 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 13 Aug 2023 16:51:21 +0300
Subject: fix for the broken run_git calls

---
 modules/launch_utils.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/launch_utils.py b/modules/launch_utils.py
index e30fbac8..4fc254a2 100644
--- a/modules/launch_utils.py
+++ b/modules/launch_utils.py
@@ -173,9 +173,9 @@ def git_clone(url, dir, name, commithash=None):
         if current_hash == commithash:
             return
 
-        run_git('fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}", autofix=False)
+        run_git(dir, name, 'fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}", autofix=False)
 
-        run_git('checkout', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}", live=True)
+        run_git(dir, name, 'checkout', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}", live=True)
 
         return
 
-- 
cgit v1.2.3


From abfa4ad8bc995dcaf832c07a7cf75b6e295a8ca9 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Mon, 8 May 2023 18:16:01 -0400
Subject: Use fixed size for sub-quadratic chunking on MPS

Even if this causes chunks to be much smaller, performance isn't significantly impacted. This will usually reduce memory usage but should also help with poor performance when free memory is low.
---
 modules/sd_hijack_optimizations.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 0e810eec..b3e71270 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -1,6 +1,7 @@
 from __future__ import annotations
 import math
 import psutil
+import platform
 
 import torch
 from torch import einsum
@@ -427,7 +428,10 @@ def sub_quad_attention(q, k, v, q_chunk_size=1024, kv_chunk_size=None, kv_chunk_
     qk_matmul_size_bytes = batch_x_heads * bytes_per_token * q_tokens * k_tokens
 
     if chunk_threshold is None:
-        chunk_threshold_bytes = int(get_available_vram() * 0.9) if q.device.type == 'mps' else int(get_available_vram() * 0.7)
+        if q.device.type == 'mps':
+            chunk_threshold_bytes = 268435456 * (2 if platform.processor() == 'i386' else bytes_per_token)
+        else:
+            chunk_threshold_bytes = int(get_available_vram() * 0.7)
     elif chunk_threshold == 0:
         chunk_threshold_bytes = None
     else:
-- 
cgit v1.2.3


From 87dd685224b5f7dbbd832fc73cc08e7e470c9f28 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Sun, 21 May 2023 05:00:27 -0400
Subject: Make sub-quadratic the default for MPS

---
 modules/sd_hijack_optimizations.py | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index b3e71270..7f9e328d 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -95,7 +95,10 @@ class SdOptimizationSdp(SdOptimizationSdpNoMem):
 class SdOptimizationSubQuad(SdOptimization):
     name = "sub-quadratic"
     cmd_opt = "opt_sub_quad_attention"
-    priority = 10
+
+    @property
+    def priority(self):
+        return 1000 if shared.device.type == 'mps' else 10
 
     def apply(self):
         ldm.modules.attention.CrossAttention.forward = sub_quad_attention_forward
@@ -121,7 +124,7 @@ class SdOptimizationInvokeAI(SdOptimization):
 
     @property
     def priority(self):
-        return 1000 if not torch.cuda.is_available() else 10
+        return 1000 if shared.device.type != 'mps' and not torch.cuda.is_available() else 10
 
     def apply(self):
         ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward_invokeAI
-- 
cgit v1.2.3


From 2489252099c299bed49a9d4a39a4ead73b6b6f10 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Tue, 25 Jul 2023 03:03:06 -0400
Subject: `torch.empty` can create issues; use `torch.zeros`

For MPS, using a tensor created with `torch.empty()` can cause `torch.baddbmm()` to include NaNs in the tensor it returns, even though `beta=0`. However, with a tensor of shape [1,1,1], there should be a negligible performance difference between `torch.empty()` and `torch.zeros()` anyway, so it's better to just use `torch.zeros()` for this and avoid unnecessarily creating issues.
---
 modules/sub_quadratic_attention.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/sub_quadratic_attention.py b/modules/sub_quadratic_attention.py
index 497568eb..ae4ee4bb 100644
--- a/modules/sub_quadratic_attention.py
+++ b/modules/sub_quadratic_attention.py
@@ -58,7 +58,7 @@ def _summarize_chunk(
     scale: float,
 ) -> AttnChunk:
     attn_weights = torch.baddbmm(
-        torch.empty(1, 1, 1, device=query.device, dtype=query.dtype),
+        torch.zeros(1, 1, 1, device=query.device, dtype=query.dtype),
         query,
         key.transpose(1,2),
         alpha=scale,
@@ -121,7 +121,7 @@ def _get_attention_scores_no_kv_chunking(
     scale: float,
 ) -> Tensor:
     attn_scores = torch.baddbmm(
-        torch.empty(1, 1, 1, device=query.device, dtype=query.dtype),
+        torch.zeros(1, 1, 1, device=query.device, dtype=query.dtype),
         query,
         key.transpose(1,2),
         alpha=scale,
-- 
cgit v1.2.3


From 9058620cec2788495d295f4e68ef2932d6d700e6 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Sat, 12 Aug 2023 04:44:16 -0400
Subject: `git checkout` with commit hash

---
 modules/launch_utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/launch_utils.py b/modules/launch_utils.py
index 4fc254a2..e77baa52 100644
--- a/modules/launch_utils.py
+++ b/modules/launch_utils.py
@@ -175,7 +175,7 @@ def git_clone(url, dir, name, commithash=None):
 
         run_git(dir, name, 'fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}", autofix=False)
 
-        run_git(dir, name, 'checkout', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}", live=True)
+        run_git(dir, name, f'checkout {commithash}', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}", live=True)
 
         return
 
-- 
cgit v1.2.3


From f4dbb0c820344798e3481d4104618b95594a3d10 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Thu, 20 Jul 2023 01:44:45 -0400
Subject: Change the repositories origin URLs when necessary

---
 modules/launch_utils.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/modules/launch_utils.py b/modules/launch_utils.py
index e77baa52..9eda7c9d 100644
--- a/modules/launch_utils.py
+++ b/modules/launch_utils.py
@@ -173,6 +173,9 @@ def git_clone(url, dir, name, commithash=None):
         if current_hash == commithash:
             return
 
+        if run_git(dir, name, 'config --get remote.origin.url', None, f"Couldn't determine {name}'s origin URL", live=False).strip() != url:
+            run_git(dir, name, f'remote set-url origin "{url}"', None, f"Failed to set {name}'s origin URL", live=False)
+
         run_git(dir, name, 'fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}", autofix=False)
 
         run_git(dir, name, f'checkout {commithash}', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}", live=True)
-- 
cgit v1.2.3


From 232c931f4082ea73bbaca8f77469cfea9d5db459 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Mon, 7 Aug 2023 10:33:43 -0400
Subject: Mac k-diffusion workarounds are no longer needed

---
 webui-macos-env.sh | 2 --
 1 file changed, 2 deletions(-)

diff --git a/webui-macos-env.sh b/webui-macos-env.sh
index 6354e73b..24bc5c42 100644
--- a/webui-macos-env.sh
+++ b/webui-macos-env.sh
@@ -12,8 +12,6 @@ fi
 export install_dir="$HOME"
 export COMMANDLINE_ARGS="--skip-torch-cuda-test --upcast-sampling --no-half-vae --use-cpu interrogate"
 export TORCH_COMMAND="pip install torch==2.0.1 torchvision==0.15.2"
-export K_DIFFUSION_REPO="https://github.com/brkirch/k-diffusion.git"
-export K_DIFFUSION_COMMIT_HASH="51c9778f269cedb55a4d88c79c0246d35bdadb71"
 export PYTORCH_ENABLE_MPS_FALLBACK=1
 
 ####################################################################
-- 
cgit v1.2.3


From 5df535b7c2374c3324485faaea62fbdbffc71f71 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Mon, 7 Aug 2023 10:20:10 -0400
Subject: Remove duplicate code for torchsde randn

---
 modules/mac_specific.py | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/modules/mac_specific.py b/modules/mac_specific.py
index bce527cc..89256c5b 100644
--- a/modules/mac_specific.py
+++ b/modules/mac_specific.py
@@ -52,9 +52,6 @@ def cumsum_fix(input, cumsum_func, *args, **kwargs):
 
 
 if has_mps:
-    # MPS fix for randn in torchsde
-    CondFunc('torchsde._brownian.brownian_interval._randn', lambda _, size, dtype, device, seed: torch.randn(size, dtype=dtype, device=torch.device("cpu"), generator=torch.Generator(torch.device("cpu")).manual_seed(int(seed))).to(device), lambda _, size, dtype, device, seed: device.type == 'mps')
-
     if platform.mac_ver()[0].startswith("13.2."):
         # MPS workaround for https://github.com/pytorch/pytorch/issues/95188, thanks to danieldk (https://github.com/explosion/curated-transformers/pull/124)
         CondFunc('torch.nn.functional.linear', lambda _, input, weight, bias: (torch.matmul(input, weight.t()) + bias) if bias is not None else torch.matmul(input, weight.t()), lambda _, input, weight, bias: input.numel() > 10485760)
-- 
cgit v1.2.3


From 2035cbbd5d6e7678450c701fce1a5de7d8bd7084 Mon Sep 17 00:00:00 2001
From: brkirch <brkirch@users.noreply.github.com>
Date: Sat, 12 Aug 2023 06:01:36 -0400
Subject: Fix DDIM and PLMS samplers on MPS

---
 modules/sd_samplers_timesteps_impl.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/modules/sd_samplers_timesteps_impl.py b/modules/sd_samplers_timesteps_impl.py
index 48d7e649..d32e3521 100644
--- a/modules/sd_samplers_timesteps_impl.py
+++ b/modules/sd_samplers_timesteps_impl.py
@@ -11,7 +11,7 @@ from modules.models.diffusion.uni_pc import uni_pc
 def ddim(model, x, timesteps, extra_args=None, callback=None, disable=None, eta=0.0):
     alphas_cumprod = model.inner_model.inner_model.alphas_cumprod
     alphas = alphas_cumprod[timesteps]
-    alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64)
+    alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64 if x.device.type != 'mps' else torch.float32)
     sqrt_one_minus_alphas = torch.sqrt(1 - alphas)
     sigmas = eta * np.sqrt((1 - alphas_prev.cpu().numpy()) / (1 - alphas.cpu()) * (1 - alphas.cpu() / alphas_prev.cpu().numpy()))
 
@@ -42,7 +42,7 @@ def ddim(model, x, timesteps, extra_args=None, callback=None, disable=None, eta=
 def plms(model, x, timesteps, extra_args=None, callback=None, disable=None):
     alphas_cumprod = model.inner_model.inner_model.alphas_cumprod
     alphas = alphas_cumprod[timesteps]
-    alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64)
+    alphas_prev = alphas_cumprod[torch.nn.functional.pad(timesteps[:-1], pad=(1, 0))].to(torch.float64 if x.device.type != 'mps' else torch.float32)
     sqrt_one_minus_alphas = torch.sqrt(1 - alphas)
 
     extra_args = {} if extra_args is None else extra_args
-- 
cgit v1.2.3


From f093c9d39d0fe9951a8f5c570027cecc68778ef2 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 13 Aug 2023 17:31:10 +0300
Subject: fix broken XYZ plot seeds add new callback for scripts to be used
 before processing

---
 modules/processing.py              | 32 ++++++++++++++++++++++++++++++--
 modules/processing_scripts/seed.py |  2 +-
 modules/scripts.py                 | 17 ++++++++++++++++-
 3 files changed, 47 insertions(+), 4 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index fdf49359..74366655 100755
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -152,7 +152,9 @@ class StableDiffusionProcessing:
     token_merging_ratio_hr = 0
     disable_extra_networks: bool = False
 
-    script_args: list = None
+    scripts_value: scripts.ScriptRunner = field(default=None, init=False)
+    script_args_value: list = field(default=None, init=False)
+    scripts_setup_complete: bool = field(default=False, init=False)
 
     cached_uc = [None, None]
     cached_c = [None, None]
@@ -171,7 +173,6 @@ class StableDiffusionProcessing:
     step_multiplier: int = field(default=1, init=False)
     color_corrections: list = field(default=None, init=False)
 
-    scripts: list = field(default=None, init=False)
     all_prompts: list = field(default=None, init=False)
     all_negative_prompts: list = field(default=None, init=False)
     all_seeds: list = field(default=None, init=False)
@@ -229,6 +230,33 @@ class StableDiffusionProcessing:
     def sd_model(self, value):
         pass
 
+    @property
+    def scripts(self):
+        return self.scripts_value
+
+    @scripts.setter
+    def scripts(self, value):
+        self.scripts_value = value
+
+        if self.scripts_value and self.script_args_value and not self.scripts_setup_complete:
+            self.setup_scripts()
+
+    @property
+    def script_args(self):
+        return self.script_args_value
+
+    @script_args.setter
+    def script_args(self, value):
+        self.script_args_value = value
+
+        if self.scripts_value and self.script_args_value and not self.scripts_setup_complete:
+            self.setup_scripts()
+
+    def setup_scripts(self):
+        self.scripts_setup_complete = True
+
+        self.scripts.setup_scrips(self)
+
     def comment(self, text):
         self.comments[text] = 1
 
diff --git a/modules/processing_scripts/seed.py b/modules/processing_scripts/seed.py
index cc90775a..96b44dfb 100644
--- a/modules/processing_scripts/seed.py
+++ b/modules/processing_scripts/seed.py
@@ -58,7 +58,7 @@ class ScriptSeed(scripts.ScriptBuiltin):
 
         return self.seed, subseed, subseed_strength
 
-    def before_process(self, p, seed, subseed, subseed_strength):
+    def setup(self, p, seed, subseed, subseed_strength):
         p.seed = seed
 
         if subseed_strength > 0:
diff --git a/modules/scripts.py b/modules/scripts.py
index c6459b45..d4a9da94 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -106,9 +106,16 @@ class Script:
 
         pass
 
+    def setup(self, p, *args):
+        """For AlwaysVisible scripts, this function is called when the processing object is set up, before any processing starts.
+        args contains all values returned by components from ui().
+        """
+        pass
+
+
     def before_process(self, p, *args):
         """
-        This function is called very early before processing begins for AlwaysVisible scripts.
+        This function is called very early during processing begins for AlwaysVisible scripts.
         You can modify the processing object (p) here, inject hooks, etc.
         args contains all values returned by components from ui()
         """
@@ -706,6 +713,14 @@ class ScriptRunner:
             except Exception:
                 errors.report(f"Error running before_hr: {script.filename}", exc_info=True)
 
+    def setup_scrips(self, p):
+        for script in self.alwayson_scripts:
+            try:
+                script_args = p.script_args[script.args_from:script.args_to]
+                script.setup(p, *script_args)
+            except Exception:
+                errors.report(f"Error running setup: {script.filename}", exc_info=True)
+
 
 scripts_txt2img: ScriptRunner = None
 scripts_img2img: ScriptRunner = None
-- 
cgit v1.2.3


From 09ff5b5416e9e989cf2ddb2bab9129e27ed23f14 Mon Sep 17 00:00:00 2001
From: Ikko Eltociear Ashimine <eltociear@gmail.com>
Date: Mon, 14 Aug 2023 01:03:49 +0900
Subject: Fix typo in launch_utils.py

existance -> existence
---
 modules/launch_utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/launch_utils.py b/modules/launch_utils.py
index e1c9cfbe..8d2256ee 100644
--- a/modules/launch_utils.py
+++ b/modules/launch_utils.py
@@ -291,7 +291,7 @@ def prepare_environment():
     blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9")
 
     try:
-        # the existance of this file is a signal to webui.sh/bat that webui needs to be restarted when it stops execution
+        # the existence of this file is a signal to webui.sh/bat that webui needs to be restarted when it stops execution
         os.remove(os.path.join(script_path, "tmp", "restart"))
         os.environ.setdefault('SD_WEBUI_RESTARTING', '1')
     except OSError:
-- 
cgit v1.2.3


From 16781ba09abe1494993f819b91ea0b88c48903b7 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 13 Aug 2023 20:15:20 +0300
Subject: fix 2 for git code botched by previous PRs

---
 modules/launch_utils.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/launch_utils.py b/modules/launch_utils.py
index 4fc254a2..e77baa52 100644
--- a/modules/launch_utils.py
+++ b/modules/launch_utils.py
@@ -175,7 +175,7 @@ def git_clone(url, dir, name, commithash=None):
 
         run_git(dir, name, 'fetch', f"Fetching updates for {name}...", f"Couldn't fetch {name}", autofix=False)
 
-        run_git(dir, name, 'checkout', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}", live=True)
+        run_git(dir, name, f'checkout {commithash}', f"Checking out commit for {name} with hash: {commithash}...", f"Couldn't checkout commit {commithash} for {name}", live=True)
 
         return
 
-- 
cgit v1.2.3


From 007ecfbb29771aa7cdcf0263ab1811bc75fa5446 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 13 Aug 2023 21:01:13 +0300
Subject: also use setup callback for the refiner instead of before_process

---
 modules/processing_scripts/refiner.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/modules/processing_scripts/refiner.py b/modules/processing_scripts/refiner.py
index 7b946d05..3c5b37d2 100644
--- a/modules/processing_scripts/refiner.py
+++ b/modules/processing_scripts/refiner.py
@@ -38,7 +38,7 @@ class ScriptRefiner(scripts.Script):
 
         return enable_refiner, refiner_checkpoint, refiner_switch_at
 
-    def before_process(self, p, enable_refiner, refiner_checkpoint, refiner_switch_at):
+    def setup(self, p, enable_refiner, refiner_checkpoint, refiner_switch_at):
         # the actual implementation is in sd_samplers_common.py, apply_refiner
 
         if not enable_refiner or refiner_checkpoint in (None, "", "None"):
-- 
cgit v1.2.3