Fix error when batch count > 1

modules/sd_samplers_kdiffusion.py

@@ -269,14 +269,15 @@ class KDiffusionSampler:
 
         return sigmas
 
-    def create_noise_sampler(self, x, sigmas, seeds):
+    def create_noise_sampler(self, x, sigmas, p):
         """For DPM++ SDE: manually create noise sampler to enable deterministic results across different batch sizes"""
         if shared.opts.no_dpmpp_sde_batch_determinism:
             return None
 
         from k_diffusion.sampling import BrownianTreeNoiseSampler
         sigma_min, sigma_max = sigmas[sigmas > 0].min(), sigmas.max()
-        return BrownianTreeNoiseSampler(x, sigma_min, sigma_max, seed=seeds)
+        current_iter_seeds = p.all_seeds[p.iteration * p.batch_size:(p.iteration + 1) * p.batch_size]
+        return BrownianTreeNoiseSampler(x, sigma_min, sigma_max, seed=current_iter_seeds)
 
     def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning, steps=None, image_conditioning=None):
         steps, t_enc = sd_samplers_common.setup_img2img_steps(p, steps)
@@ -302,7 +303,7 @@ class KDiffusionSampler:
             extra_params_kwargs['sigmas'] = sigma_sched
 
         if self.funcname == 'sample_dpmpp_sde':
-            noise_sampler = self.create_noise_sampler(x, sigmas, p.all_seeds)
+            noise_sampler = self.create_noise_sampler(x, sigmas, p)
             extra_params_kwargs['noise_sampler'] = noise_sampler
 
         self.model_wrap_cfg.init_latent = x
@@ -337,7 +338,7 @@ class KDiffusionSampler:
             extra_params_kwargs['sigmas'] = sigmas
 
         if self.funcname == 'sample_dpmpp_sde':
-            noise_sampler = self.create_noise_sampler(x, sigmas, p.all_seeds)
+            noise_sampler = self.create_noise_sampler(x, sigmas, p)
             extra_params_kwargs['noise_sampler'] = noise_sampler
 
         self.last_latent = x