update samplers

javascript/style.css

@@ -114,10 +114,9 @@ a{
   cursor: pointer;
 }
 
-#txt2img_gallery img, #img2img_gallery img, #extras_gallery img{
+#txt2img_gallery img, #img2img_gallery img, #extras_gallery img {
     object-fit: scale-down;
     width: -webkit-fill-available !important;
-    height: inherit !important;
 }
 #txt2img_actions_column, #img2img_actions_column {
     gap: 0.5em;

modules/api/api.py

@@ -176,6 +176,8 @@ class Api:
         script_args[0] = 0
 
         # get default values
+        if gr is None:
+            return script_args
         with gr.Blocks(): # will throw errors calling ui function without this
             for script in script_runner.scripts:
                 if script.ui(script.is_img2img):

modules/processing.py

@@ -460,6 +460,7 @@ def create_infotext(p: StableDiffusionProcessing, all_prompts, all_seeds, all_su
     return f"{all_prompts[index]}{negative_prompt_text}\n{generation_params_text}".strip()
 
 
+"""
 def print_profile(profile, msg: str):
     try:
         from rich import print # pylint: disable=redefined-builtin
@@ -469,6 +470,24 @@ def print_profile(profile, msg: str):
     lines = lines.split('\n')
     lines = [l for l in lines if '/profiler' not in l]
     print(f'Profile {msg}:', '\n'.join(lines))
+"""
+
+
+def print_profile(profile, msg: str):
+    import io
+    import pstats
+    try:
+        from rich import print # pylint: disable=redefined-builtin
+    except:
+        pass
+    profile.disable()
+    stream = io.StringIO()
+    ps = pstats.Stats(profile, stream=stream)
+    ps.sort_stats(pstats.SortKey.CUMULATIVE).print_stats(15)
+    profile = None
+    lines = stream.getvalue().split('\n')
+    lines = [l for l in lines if '<frozen' not in l and '{built-in' not in l and '/logging' not in l and '/rich' not in l]
+    print(f'Profile {msg}:', '\n'.join(lines))
 
 
 def process_images(p: StableDiffusionProcessing) -> Processed:
@@ -490,12 +509,18 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
             log.debug('Token merging applied')
 
         if cmd_opts.profile:
+            """
             import torch.profiler # pylint: disable=redefined-outer-name
-            # activities=[torch.profiler.ProfilerActivity.CPU, torch.profiler.ProfilerActivity.CUDA]
             with torch.profiler.profile(profile_memory=True, with_modules=True) as prof:
                 with torch.profiler.record_function("process_images"):
                     res = process_images_inner(p)
             print_profile(prof, 'process_images')
+            """
+            import cProfile
+            pr = cProfile.Profile()
+            pr.enable()
+            res = process_images_inner(p)
+            print_profile(pr, 'Torch')
         else:
             res = process_images_inner(p)
     finally:
@@ -836,7 +861,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
             if self.hr_upscaler is not None:
                 self.extra_generation_params["Hires upscaler"] = self.hr_upscaler
 
-    def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts):
+    def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts): # TODO this is majority of processing time
         self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model)
         latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest")
         if self.enable_hr and latent_scale_mode is None:

modules/sd_samplers_kdiffusion.py

@@ -10,9 +10,6 @@ from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback
 from modules.script_callbacks import CFGDenoisedParams, cfg_denoised_callback
 from modules.script_callbacks import AfterCFGCallbackParams, cfg_after_cfg_callback
 
-# from tqdm.rich import trange
-# k_diffusion.sampling.trange = trange
-
 samplers_k_diffusion = [
     ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {}),
     ('Euler', 'sample_euler', ['k_euler'], {}),
@@ -31,6 +28,7 @@ samplers_k_diffusion = [
     ('DPM++ 2S a Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras'}),
     ('DPM++ 2M Karras', 'sample_dpmpp_2m', ['k_dpmpp_2m_ka'], {'scheduler': 'karras'}),
     ('DPM++ SDE Karras', 'sample_dpmpp_sde', ['k_dpmpp_sde_ka'], {'scheduler': 'karras'}),
+    ('DPM++ 2M SDE', 'sample_dpmpp_2m_sde', ['k_dpmpp_2m_sde'], {}),
 ]
 
 samplers_data_k_diffusion = [

requirements.txt

@@ -45,7 +45,7 @@ yapf
 scikit-image
 basicsr
 compel
-requests==2.30.0
+requests==2.31.0
 tqdm==4.65.0
 accelerate==0.18.0
 opencv-python==4.7.0.72