From 94b9cc79d4e13671139b526ae878a79d090eb20f Mon Sep 17 00:00:00 2001
From: DepFA <35278260+dfaker@users.noreply.github.com>
Date: Sun, 6 Nov 2022 00:48:12 +0000
Subject: [PATCH] Delete latent_mirroring_always_on.py

---
 latent_mirroring_always_on.py | 60 -----------------------------------
 1 file changed, 60 deletions(-)
 delete mode 100644 latent_mirroring_always_on.py

diff --git a/latent_mirroring_always_on.py b/latent_mirroring_always_on.py
deleted file mode 100644
index 42bcde6..0000000
--- a/latent_mirroring_always_on.py
+++ /dev/null
@@ -1,60 +0,0 @@
-
-import torch
-import modules.scripts as scripts
-import gradio as gr
-from modules.script_callbacks import on_cfg_denoiser
-from modules import processing
-
-
-class Script(scripts.Script):
-
-    def title(self):
-        return "Latent Mirroring"
-
-    def show(self, is_img2img):
-        return scripts.AlwaysVisible
-
-    def ui(self, is_img2img):
-        mirror_mode = gr.Radio(label='Mirror application mode', choices=['None', 'Alternate Steps', 'Blend Average'], value='Alternate Steps', type="index")
-        mirror_style = gr.Radio(label='Mirror style', choices=['Vertical Mirroring', 'Horizontal Mirroring', '90 Degree Rotation', '180 Degree Rotation'], value='Vertical Mirroring', type="index")
-        mirroring_max_step_fraction = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Maximum steps fraction to mirror at', value=0.25)
-        self.run_callback = False
-        return [mirror_mode, mirror_style, mirroring_max_step_fraction]
-
-    def denoise_callback(self, params):
-
-        if self.run_callback and params.sampling_step < params.total_sampling_steps*self.mirroring_max_step_fraction:
-            if self.mirror_mode == 1:
-                if self.mirror_style == 0:
-                    params.x[:, :, :, :] = torch.flip(params.x, [3])
-                elif self.mirror_style == 1:
-                    params.x[:, :, :, :] = torch.flip(params.x, [2])
-                elif self.mirror_style == 2:
-                    params.x[:, :, :, :] = torch.rot90(params.x, dims=[2, 3])
-                elif self.mirror_style == 3:
-                    params.x[:, :, :, :] = torch.rot90(torch.rot90(params.x, dims=[2, 3]), dims=[2, 3])
-            elif self.mirror_mode == 2:
-                if self.mirror_style == 0:
-                    params.x[:, :, :, :] = (torch.flip(params.x, [3]) + params.x)/2
-                elif self.mirror_style == 1:
-                    params.x[:, :, :, :] = (torch.flip(params.x, [2]) + params.x)/2
-                elif self.mirror_style == 2:
-                    params.x[:, :, :, :] = (torch.rot90(params.x, dims=[2, 3]) + params.x)/2
-                elif self.mirror_style == 3:
-                    params.x[:, :, :, :] = (torch.rot90(torch.rot90(params.x_in, dims=[2, 3]), dims=[2, 3]) + params.x_in)/2
-
-    def process(self, p, mirror_mode, mirror_style, mirroring_max_step_fraction):
-
-        self.mirror_mode = mirror_mode
-        self.mirror_style = mirror_style
-        self.mirroring_max_step_fraction = mirroring_max_step_fraction
-
-        if not hasattr(self, 'callbacks_added'):
-            on_cfg_denoiser(self.denoise_callback)
-            self.callbacks_added = True
-
-        self.run_callback = True
-
-    def postprocess(self, *args):
-        self.run_callback = False
-        return result