Update app.py

app.py

@@ -126,35 +126,27 @@ def plex(prompt,neg_prompt,modil,stips,scaly,nut,wei,hei,los,loca,gaul,progress=
     try:
         pipe=accelerator.prepare(DiffusionPipeline.from_pretrained(""+modil+"",torch_dtype=torch.bfloat16, variant="fp16", use_safetensors=True, safety_checker=None))
     except:
-        pipe=None
         gc.collect()
-    if pipe==None:
         try:
             pipe=accelerator.prepare(DiffusionPipeline.from_pretrained(""+modil+"",torch_dtype=torch.float32, variant="fp32", use_safetensors=True, safety_checker=None))
         except:
             gc.collect()
-    elif pipe==None:
-        try:
-            pipe=accelerator.prepare(DiffusionPipeline.from_pretrained(""+modil+"",torch_dtype=torch.bfloat16, variant="fp16", use_safetensors=False, safety_checker=None))
-        except:
-            gc.collect()
-    elif pipe==None:
-        try:
-            pipe=accelerator.prepare(DiffusionPipeline.from_pretrained(""+modil+"",torch_dtype=torch.float32, variant="fp32", use_safetensors=False, safety_checker=None))
-        except:
-            gc.collect()
-    elif pipe==None:
-        try:
-            pipe=accelerator.prepare(DiffusionPipeline.from_pretrained(""+modil+"",torch_dtype=torch.float, variant=None, use_safetensors=True, safety_checker=None))
-        except:
-            gc.collect()
-    elif pipe==None:
-        try:
-            pipe=accelerator.prepare(DiffusionPipeline.from_pretrained(""+modil+"",torch_dtype=torch.float, variant=None, use_safetensors=False, safety_checker=None))
-        except:
-            print("no pipe")
-    else:
-        print("no pipes")
+            try:
+                pipe=accelerator.prepare(DiffusionPipeline.from_pretrained(""+modil+"",torch_dtype=torch.bfloat16, variant="fp16", use_safetensors=False, safety_checker=None))
+            except:
+                gc.collect()
+                try:
+                    pipe=accelerator.prepare(DiffusionPipeline.from_pretrained(""+modil+"",torch_dtype=torch.float32, variant="fp32", use_safetensors=False, safety_checker=None))
+                except:
+                    gc.collect()
+                    try:
+                        pipe=accelerator.prepare(DiffusionPipeline.from_pretrained(""+modil+"",torch_dtype=torch.float, variant=None, use_safetensors=True, safety_checker=None))
+                    except:
+                        gc.collect()
+                        try:
+                            pipe=accelerator.prepare(DiffusionPipeline.from_pretrained(""+modil+"",torch_dtype=torch.float, variant=None, use_safetensors=False, safety_checker=None))
+                        except:
+                            print("no pipe")
     if los:
         try:
             lrda=ModelCard.load(""+los+"")