removed the option to use 2x more memory when generating previews

added an option to always only show one image in previews
removed duplicate code

3 files changed, 14 insertions, 29 deletions

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 74a480e5..0b408a70 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -71,6 +71,7 @@ sampler_extra_params = {
     'sample_dpm_2': ['s_churn', 's_tmin', 's_tmax', 's_noise'],

 }

 

+

 def setup_img2img_steps(p, steps=None):

     if opts.img2img_fix_steps or steps is not None:

         steps = int((steps or p.steps) / min(p.denoising_strength, 0.999)) if p.denoising_strength > 0 else 0

@@ -82,37 +83,21 @@ def setup_img2img_steps(p, steps=None):
     return steps, t_enc

 

 

-def sample_to_image(samples):

-    x_sample = processing.decode_first_stage(shared.sd_model, samples[0:1])[0]

+def single_sample_to_image(sample):

+    x_sample = processing.decode_first_stage(shared.sd_model, sample.unsqueeze(0))[0]

     x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0)

     x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)

     x_sample = x_sample.astype(np.uint8)

     return Image.fromarray(x_sample)

 

+

+def sample_to_image(samples):

+    return single_sample_to_image(samples[0])

+

+

 def samples_to_image_grid(samples):

-    progress_images = []

-    for i in range(len(samples)):

-        # Decode the samples individually to reduce VRAM usage at the cost of a bit of speed.

-        x_sample = processing.decode_first_stage(shared.sd_model, samples[i:i+1])[0]

-        x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0)

-        x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)

-        x_sample = x_sample.astype(np.uint8)

-        progress_images.append(Image.fromarray(x_sample))

-

-    return images.image_grid(progress_images)

-

-def samples_to_image_grid_combined(samples):

-    progress_images = []

-    # Decode all samples at once to increase speed at the cost of VRAM usage.

-    x_samples = processing.decode_first_stage(shared.sd_model, samples)

-    x_samples = torch.clamp((x_samples + 1.0) / 2.0, min=0.0, max=1.0)

-

-    for x_sample in x_samples:

-        x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)

-        x_sample = x_sample.astype(np.uint8)

-        progress_images.append(Image.fromarray(x_sample))

-

-    return images.image_grid(progress_images)

+    return images.image_grid([single_sample_to_image(sample) for sample in samples])

+

 

 def store_latent(decoded):

     state.current_latent = decoded

diff --git a/modules/shared.py b/modules/shared.py
index 95d6e225..25bfc895 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -294,7 +294,7 @@ options_templates.update(options_section(('interrogate', "Interrogate Options"),
 options_templates.update(options_section(('ui', "User interface"), {

     "show_progressbar": OptionInfo(True, "Show progressbar"),

     "show_progress_every_n_steps": OptionInfo(0, "Show image creation progress every N sampling steps. Set 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 32, "step": 1}),

-    "progress_decode_combined": OptionInfo(False, "Decode all progress images at once. (Slighty speeds up progress generation but consumes significantly more VRAM with large batches.)"),

+    "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"),

     "return_grid": OptionInfo(True, "Show grid in results for web"),

     "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),

     "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"),

diff --git a/modules/ui.py b/modules/ui.py
index de0abc7e..ffa14cac 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -318,10 +318,10 @@ def check_progress_call(id_part):
         if shared.parallel_processing_allowed:

 

             if shared.state.sampling_step - shared.state.current_image_sampling_step >= opts.show_progress_every_n_steps and shared.state.current_latent is not None:

-                if opts.progress_decode_combined:

-                    shared.state.current_image = modules.sd_samplers.samples_to_image_grid_combined(shared.state.current_latent)

-                else:

+                if opts.show_progress_grid:

                     shared.state.current_image = modules.sd_samplers.samples_to_image_grid(shared.state.current_latent)

+                else:

+                    shared.state.current_image = modules.sd_samplers.sample_to_image(shared.state.current_latent)

                 shared.state.current_image_sampling_step = shared.state.sampling_step

 

         image = shared.state.current_image