consistency decoder

CHANGELOG.md

@@ -21,7 +21,8 @@
   - Updated logic for calculating **steps** when using base/hires/refiner workflows  
   - Safe model offloading for non-standard models  
   - Fix **DPM SDE** scheduler  
-  - Better support for SD 1.5 **inpainting** models
+  - Better support for SD 1.5 **inpainting** models  
+  - Add support for **OpenAI Consistency decoder VAE**
   - Update to `diffusers==0.23.0`  
 - **Extra networks**  
   - Use multi-threading for 5x load speedup  

modules/processing_diffusers.py

@@ -98,7 +98,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
             model.vae.to(devices.device)
         latents.to(model.vae.device)
 
-        upcast = (model.vae.dtype == torch.float16) and model.vae.config.force_upcast and hasattr(model, 'upcast_vae')
+        upcast = (model.vae.dtype == torch.float16) and getattr(model.vae.config, 'force_upcast', False) and hasattr(model, 'upcast_vae')
         if upcast: # this is done by diffusers automatically if output_type != 'latent'
             model.upcast_vae()
             latents = latents.to(next(iter(model.vae.post_quant_conv.parameters())).dtype)

modules/sd_vae.py

@@ -203,10 +203,16 @@ def load_vae_diffusers(model_file, vae_file=None, vae_source="unknown-source"):
         if os.path.isfile(vae_file):
             _pipeline, model_type = sd_models.detect_pipeline(model_file, 'vae')
             diffusers_load_config = { "config_file":  paths.sd_default_config if model_type != 'Stable Diffusion XL' else os.path.join(paths.sd_configs_path, 'sd_xl_base.yaml')}
-            vae = diffusers.AutoencoderKL.from_single_file(vae_file, **diffusers_load_config)
+            if os.path.getsize(vae_file) > 1310944880:
+                vae = diffusers.ConsistencyDecoderVAE.from_pretrained('openai/consistency-decoder', **diffusers_load_config) # consistency decoder does not have from single file, so we'll just download it once more
+            else:
+                vae = diffusers.AutoencoderKL.from_single_file(vae_file, **diffusers_load_config)
             vae = vae.to(devices.dtype_vae)
         else:
-            vae = diffusers.AutoencoderKL.from_pretrained(vae_file, **diffusers_load_config)
+            if 'consistency-decoder' in vae_file:
+                vae = diffusers.ConsistencyDecoderVAE.from_pretrained(vae_file, **diffusers_load_config)
+            else:
+                vae = diffusers.AutoencoderKL.from_pretrained(vae_file, **diffusers_load_config)
         global loaded_vae_file # pylint: disable=global-statement
         loaded_vae_file = os.path.basename(vae_file)
         # shared.log.debug(f'Diffusers VAE config: {vae.config}')