handle gpu quota

app.py

@@ -961,41 +961,43 @@ def run_fn(
     }
     # print(kwargs)
     
-    try:
+    # try:
     
-        if old_school_ncut:
-            return super_duper_long_run(model, images, **kwargs)
-        
-        if is_lisa:
-            return super_duper_long_run(model, images, **kwargs)
-        
-        num_images = len(images)
-        if num_images >= 100:
-            return super_duper_long_run(model, images, **kwargs)
-        if 'diffusion' in model_name.lower():
-            return super_duper_long_run(model, images, **kwargs)
-        if recursion:
-            return longer_run(model, images, **kwargs)
-        if num_images >= 50:
-            return longer_run(model, images, **kwargs)
-        if old_school_ncut:
+    if old_school_ncut:
+        return super_duper_long_run(model, images, **kwargs)
+    
+    if is_lisa:
+        return super_duper_long_run(model, images, **kwargs)
+    
+    num_images = len(images)
+    if num_images >= 100:
+        return super_duper_long_run(model, images, **kwargs)
+    if 'diffusion' in model_name.lower():
+        return super_duper_long_run(model, images, **kwargs)
+    if recursion:
+        return longer_run(model, images, **kwargs)
+    if num_images >= 50:
+        return longer_run(model, images, **kwargs)
+    if old_school_ncut:
+        return longer_run(model, images, **kwargs)
+    if num_images >= 10:
+        return long_run(model, images, **kwargs)
+    if embedding_method == "UMAP":
+        if perplexity >= 250 or num_sample_tsne >= 500:
             return longer_run(model, images, **kwargs)
-        if num_images >= 10:
-            return long_run(model, images, **kwargs)
-        if embedding_method == "UMAP":
-            if perplexity >= 250 or num_sample_tsne >= 500:
-                return longer_run(model, images, **kwargs)
+        return long_run(model, images, **kwargs)
+    if embedding_method == "t-SNE":
+        if perplexity >= 250 or num_sample_tsne >= 500:
             return long_run(model, images, **kwargs)
-        if embedding_method == "t-SNE":
-            if perplexity >= 250 or num_sample_tsne >= 500:
-                return long_run(model, images, **kwargs)
-            return quick_run(model, images, **kwargs)
-        
         return quick_run(model, images, **kwargs)
     
-    except Exception as e:
-        gr.Error(str(e))
-        gr.Info("Running out of GPU Quota? Try this demo hosted at UPenn.\n https://ncut-pytorch.readthedocs.io/en/latest/demo/")
+    return quick_run(model, images, **kwargs)
+    
+    # except spaces.GPUError as e:
+    #     print(e)
+    #     gr.Error(str(e))
+    #     gr.Info("Running out of GPU Quota? Try this demo hosted at UPenn.\n https://ncut-pytorch.readthedocs.io/en/latest/demo/")
+