Show top 500 explanations

app.py

@@ -79,7 +79,7 @@ def generate_activations(image):
         result.scatter_(-1, topk.indices, topk.values)
         cached_list.append(result.detach().cpu())
         topk_indices = (
-            latents.squeeze(0).mean(dim=0).topk(k=200).indices.detach().cpu()
+            latents.squeeze(0).mean(dim=0).topk(k=500).indices.detach().cpu()
         )
 
     handles = [hooked_module.register_forward_hook(hook)]
@@ -101,7 +101,7 @@ def generate_activations(image):
     
     
     torch.cuda.empty_cache()
-    return topk_indices, cached_list[0], examples
+    return topk_indices[:200], cached_list[0], examples
     
 def visualize_activations(image, feature_num, cached_tensor):
     base_img_tokens = 576
@@ -216,8 +216,8 @@ with gr.Blocks() as demo:
             with gr.Row():
                 with gr.Column():
                     image = gr.Image(type="pil", interactive=True, label="Sample Image")
-                    topk_features = gr.Textbox(value=topk_indices, placeholder="Top 200 Features", label="Top 100 Features", max_lines=5)
-                    known_explanation = gr.DataFrame(headers=["Feature", "Auto Interp Explanation(first 5k neurons)"], label="Auto Interp Explanations(first 5k neurons)")
+                    topk_features = gr.Textbox(value=topk_indices, placeholder="Top 200 Features", label="Top 200 Features", max_lines=5)
+                    known_explanation = gr.DataFrame(headers=["Feature", "Auto Interp Explanation(first 5k neurons)"], label="Auto Interp Explanations(first 5k neurons) for top 500 features")
                     with gr.Row():
                         clear_btn = gr.ClearButton([image, topk_features], value="Clear")
                         submit_btn = gr.Button("Submit", variant="primary")