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use Schedule instead of Sched

Kohaku-Blueleaf 2 lat temu
rodzic
commit
a69b71a37f

+ 12 - 12
modules/generation_parameters_copypaste.py

@@ -306,17 +306,17 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
     if "RNG" not in res:
         res["RNG"] = "GPU"
 
-    if "KDiff Sched Type" not in res:
-        res["KDiff Sched Type"] = "Automatic"
+    if "KDiff Schedule Type" not in res:
+        res["KDiff Schedule Type"] = "Automatic"
 
-    if "KDiff Sched max sigma" not in res:
-        res["KDiff Sched max sigma"] = 14.6
+    if "KDiff Schedule max sigma" not in res:
+        res["KDiff Schedule max sigma"] = 14.6
 
-    if "KDiff Sched min sigma" not in res:
-        res["KDiff Sched min sigma"] = 0.3
+    if "KDiff Schedule min sigma" not in res:
+        res["KDiff Schedule min sigma"] = 0.3
 
-    if "KDiff Sched rho" not in res:
-        res["KDiff Sched rho"] = 7.0
+    if "KDiff Schedule rho" not in res:
+        res["KDiff Schedule rho"] = 7.0
 
     return res
 
@@ -330,10 +330,10 @@ infotext_to_setting_name_mapping = [
     ('Conditional mask weight', 'inpainting_mask_weight'),
     ('Model hash', 'sd_model_checkpoint'),
     ('ENSD', 'eta_noise_seed_delta'),
-    ('KDiff Sched Type', 'k_sched_type'),
-    ('KDiff Sched max sigma', 'sigma_max'),
-    ('KDiff Sched min sigma', 'sigma_min'),
-    ('KDiff Sched rho', 'rho'),
+    ('KDiff Schedule Type', 'k_sched_type'),
+    ('KDiff Schedule max sigma', 'sigma_max'),
+    ('KDiff Schedule min sigma', 'sigma_min'),
+    ('KDiff Schedule rho', 'rho'),
     ('Noise multiplier', 'initial_noise_multiplier'),
     ('Eta', 'eta_ancestral'),
     ('Eta DDIM', 'eta_ddim'),

+ 4 - 4
modules/sd_samplers_kdiffusion.py

@@ -328,18 +328,18 @@ class KDiffusionSampler:
             }
 
             sigmas_func = k_diffusion_scheduler[opts.k_sched_type]
-            p.extra_generation_params["KDiff Sched Type"] = opts.k_sched_type
+            p.extra_generation_params["KDiff Schedule Type"] = opts.k_sched_type
 
             if opts.sigma_min != 0.3:
                 # take 0.0 as model default
                 sigmas_kwargs['sigma_min'] = opts.sigma_min or m_sigma_min
-                p.extra_generation_params["KDiff Sched min sigma"] = opts.sigma_min
+                p.extra_generation_params["KDiff Schedule min sigma"] = opts.sigma_min
             if opts.sigma_max != 14.6:
                 sigmas_kwargs['sigma_max'] = opts.sigma_max or m_sigma_max
-                p.extra_generation_params["KDiff Sched max sigma"] = opts.sigma_max
+                p.extra_generation_params["KDiff Schedule max sigma"] = opts.sigma_max
             if opts.k_sched_type != 'exponential':
                 sigmas_kwargs['rho'] = opts.rho
-                p.extra_generation_params["KDiff Sched rho"] = opts.rho
+                p.extra_generation_params["KDiff Schedule rho"] = opts.rho
 
             sigmas = sigmas_func(n=steps, **sigmas_kwargs, device=shared.device)
         elif self.config is not None and self.config.options.get('scheduler', None) == 'karras':

+ 4 - 4
scripts/xyz_grid.py

@@ -220,10 +220,10 @@ axis_options = [
     AxisOption("Sigma min", float, apply_field("s_tmin")),
     AxisOption("Sigma max", float, apply_field("s_tmax")),
     AxisOption("Sigma noise", float, apply_field("s_noise")),
-    AxisOption("KDiff Sched Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)),
-    AxisOption("KDiff Sched min sigma", float, apply_override("sigma_min")),
-    AxisOption("KDiff Sched max sigma", float, apply_override("sigma_max")),
-    AxisOption("KDiff Sched rho", float, apply_override("rho")),
+    AxisOption("KDiff Schedule Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)),
+    AxisOption("KDiff Schedule min sigma", float, apply_override("sigma_min")),
+    AxisOption("KDiff Schedule max sigma", float, apply_override("sigma_max")),
+    AxisOption("KDiff Schedule rho", float, apply_override("rho")),
     AxisOption("Eta", float, apply_field("eta")),
     AxisOption("Clip skip", int, apply_clip_skip),
     AxisOption("Denoising", float, apply_field("denoising_strength")),