From f674c488d9701e577e2aaf25e331fb44ada4f1ef Mon Sep 17 00:00:00 2001
From: AUTOMATIC <16777216c@gmail.com>
Date: Fri, 4 Nov 2022 10:45:34 +0300
Subject: [PATCH] bugfix: save image for hires fix BEFORE upscaling latent
 space

---
 modules/processing.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/modules/processing.py b/modules/processing.py
index a46e592d..7a2fc218 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -665,17 +665,17 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             images.save_image(image, self.outpath_samples, "", seeds[index], prompts[index], opts.samples_format, suffix="-before-highres-fix")
 
         if opts.use_scale_latent_for_hires_fix:
+            for i in range(samples.shape[0]):
+                save_intermediate(samples, i)
+
             samples = torch.nn.functional.interpolate(samples, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
-            
+
             # Avoid making the inpainting conditioning unless necessary as 
             # this does need some extra compute to decode / encode the image again.
             if getattr(self, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) < 1.0:
                 image_conditioning = self.img2img_image_conditioning(decode_first_stage(self.sd_model, samples), samples)
             else:
                 image_conditioning = self.txt2img_image_conditioning(samples)
-
-            for i in range(samples.shape[0]):
-                save_intermediate(samples, i)
         else:
             decoded_samples = decode_first_stage(self.sd_model, samples)
             lowres_samples = torch.clamp((decoded_samples + 1.0) / 2.0, min=0.0, max=1.0)