Upload app.py

app.py

@@ -38,8 +38,6 @@ good_vae = AutoencoderKL.from_pretrained(base_model, subfolder="vae", torch_dtyp
 pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=dtype, vae=taef1).to(device)
 controlnet_union = None
 controlnet = None
-controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union_repo, torch_dtype=dtype).to(device)
-controlnet = FluxMultiControlNetModel([controlnet_union]).to(device)
 last_model = models[0]
 last_cn_on = False
 
@@ -62,8 +60,8 @@ def change_base_model(repo_id: str, cn_on: bool): # , progress=gr.Progress(track
             #progress(0, desc=f"Loading model: {repo_id} / Loading ControlNet: {controlnet_model_union_repo}")
             print(f"Loading model: {repo_id} / Loading ControlNet: {controlnet_model_union_repo}")
             #clear_cache()
-            #controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union_repo, torch_dtype=dtype).to(device)
-            #controlnet = FluxMultiControlNetModel([controlnet_union]).to(device)
+            controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union_repo, torch_dtype=dtype)#.to(device)
+            controlnet = FluxMultiControlNetModel([controlnet_union])#.to(device)
             pipe = FluxControlNetPipeline.from_pretrained(repo_id, controlnet=controlnet, torch_dtype=dtype)#.to(device)
             #pipe.flux_pipe_call_that_returns_an_iterable_of_images = flux_pipe_call_that_returns_an_iterable_of_images.__get__(pipe)
             last_model = repo_id