samplers add custom sigma

Signed-off-by: Vladimir Mandic <mandic00@live.com>

CHANGELOG.md

@@ -68,6 +68,7 @@
 - **OpenVINO**: update to 2024.5.0  
 - **Sampler** improvements  
   - Euler FlowMatch: add sigma methods (*karras/exponential/betas*)  
+  - Euler FlowMatch: allow using timestep presets to set sigmas  
   - DPM FlowMatch: update all and add sigma methods  
   - BDIA-DDIM: *experimental*  
 

installer.py

@@ -459,7 +459,7 @@ def check_python(supported_minors=[9, 10, 11, 12], reason=None):
 def check_diffusers():
     if args.skip_all or args.skip_requirements:
         return
-    sha = 'c96bfa5c80eca798d555a79a491043c311d0f608'
+    sha = '63b631f38336f56755fb5cf15d9b0fb70bbf6323' # diffusers commit hash
     pkg = pkg_resources.working_set.by_key.get('diffusers', None)
     minor = int(pkg.version.split('.')[1] if pkg is not None else 0)
     cur = opts.get('diffusers_version', '') if minor > 0 else ''

modules/processing_args.py

@@ -186,6 +186,21 @@ def set_pipeline_args(p, model, prompts: list, negative_prompts: list, prompts_2
                     shared.log.error(f'Sampler timesteps: {e}')
             else:
                 shared.log.warning(f'Sampler: sampler={model.scheduler.__class__.__name__} timesteps not supported')
+    if 'sigmas' in possible:
+        sigmas = re.split(',| ', shared.opts.schedulers_timesteps)
+        sigmas = [float(x)/1000.0 for x in sigmas if x.isdigit()]
+        if len(sigmas) > 0:
+            if hasattr(model.scheduler, 'set_timesteps') and "sigmas" in set(inspect.signature(model.scheduler.set_timesteps).parameters.keys()):
+                try:
+                    args['sigmas'] = sigmas
+                    p.steps = len(sigmas)
+                    p.timesteps = sigmas
+                    steps = p.steps
+                    shared.log.debug(f'Sampler: steps={len(sigmas)} sigmas={sigmas}')
+                except Exception as e:
+                    shared.log.error(f'Sampler sigmas: {e}')
+            else:
+                shared.log.warning(f'Sampler: sampler={model.scheduler.__class__.__name__} sigmas not supported')
 
     if hasattr(model, 'scheduler') and hasattr(model.scheduler, 'noise_sampler_seed') and hasattr(model.scheduler, 'noise_sampler'):
         model.scheduler.noise_sampler = None # noise needs to be reset instead of using cached values