Fix irreproducible seeds.

Dockerfile

@@ -24,7 +24,7 @@ RUN pip3 install -e git+https://github.com/CompVis/taming-transformers.git@maste
 #RUN unzip stable-diffusion-private-hypernets.zip
 ADD stable-diffusion-private stable-diffusion-private
 RUN pip3 install -e stable-diffusion-private/
-RUN pip3 install https://github.com/crowsonkb/k-diffusion/archive/481677d114f6ea445aa009cf5bd7a9cdee909e47.zip
+RUN pip3 install https://github.com/NovelAI/k-diffusion-multigen/archive/727aaf3b25c28b7ce450c41fa8cbe7f8d0717a36.zip
 RUN pip3 install simplejpeg
 RUN pip3 install min-dalle
 #RUN pip3 install https://github.com/microsoft/DeepSpeed/archive/55b7b9e008943b8b93d4903d90b255313bb9d82c.zip

hydra_node/models.py

@@ -442,7 +442,7 @@ class StableDiffusionModel(nn.Module):
                     start_code = start_code * sigmas[0]
 
                 extra_args = {'cond': prompt_condition, 'uncond': uc, 'cond_scale': request.scale}
-                samples = self.sampler_map[request.sampler](self.k_model, start_code, sigmas, extra_args=extra_args)
+                samples = self.sampler_map[request.sampler](self.k_model, start_code, sigmas, request.seed, extra_args=extra_args)
 
         with torch.autocast("cuda", enabled=False):
             x_samples_ddim = self.model.decode_first_stage(samples.float())