emergency fix for #1199

1 files changed, 13 insertions, 12 deletions

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 17faeab1..a1183997 100644
--- a/modules/sd_samplers.py
+++ b/modules/sd_samplers.py
@@ -3,6 +3,7 @@ import numpy as np
 import torch

 import tqdm

 from PIL import Image

+import inspect

 

 import k_diffusion.sampling

 import ldm.models.diffusion.ddim

@@ -38,11 +39,11 @@ samplers = [
 samplers_for_img2img = [x for x in samplers if x.name != 'PLMS']

 

 sampler_extra_params = {

-    'sample_euler':['s_churn','s_tmin','s_tmax','s_noise'],

-    'sample_euler_ancestral':['eta'],

-    'sample_heun' :['s_churn','s_tmin','s_tmax','s_noise'],

-    'sample_dpm_2':['s_churn','s_tmin','s_tmax','s_noise'],

-    'sample_dpm_2_ancestral':['eta'],

+    'sample_euler': ['s_churn', 's_tmin', 's_tmax', 's_noise'],

+    'sample_euler_ancestral': ['eta'],

+    'sample_heun': ['s_churn', 's_tmin', 's_tmax', 's_noise'],

+    'sample_dpm_2': ['s_churn', 's_tmin', 's_tmax', 's_noise'],

+    'sample_dpm_2_ancestral': ['eta'],

 }

 

 def setup_img2img_steps(p, steps=None):

@@ -231,7 +232,7 @@ class KDiffusionSampler:
         self.model_wrap = k_diffusion.external.CompVisDenoiser(sd_model, quantize=shared.opts.enable_quantization)

         self.funcname = funcname

         self.func = getattr(k_diffusion.sampling, self.funcname)

-        self.extra_params = sampler_extra_params.get(funcname,[]) 

+        self.extra_params = sampler_extra_params.get(funcname, [])

         self.model_wrap_cfg = CFGDenoiser(self.model_wrap)

         self.sampler_noises = None

         self.sampler_noise_index = 0

@@ -278,9 +279,9 @@ class KDiffusionSampler:
             k_diffusion.sampling.torch = TorchHijack(self)

 

         extra_params_kwargs = {}

-        for val in self.extra_params:

-          if hasattr(p,val):

-            extra_params_kwargs[val] = getattr(p,val)

+        for param_name in self.extra_params:

+            if hasattr(p, param_name) and param_name in inspect.signature(self.func).parameters:

+                extra_params_kwargs[param_name] = getattr(p, param_name)

 

         return self.func(self.model_wrap_cfg, xi, sigma_sched, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)

 

@@ -300,9 +301,9 @@ class KDiffusionSampler:
             k_diffusion.sampling.torch = TorchHijack(self)

 

         extra_params_kwargs = {}

-        for val in self.extra_params:

-          if hasattr(p,val):

-            extra_params_kwargs[val] = getattr(p,val)

+        for param_name in self.extra_params:

+            if hasattr(p, param_name) and param_name in inspect.signature(self.func).parameters:

+                extra_params_kwargs[param_name] = getattr(p, param_name)

 

         samples = self.func(self.model_wrap_cfg, x, sigmas, extra_args={'cond': conditioning, 'uncond': unconditional_conditioning, 'cond_scale': p.cfg_scale}, disable=False, callback=self.callback_state, **extra_params_kwargs)