removed encoder layer selection feature (for now)

app.py

@@ -81,11 +81,11 @@ def predict_tensor(img_tensor):
 
 random_image = PIL.Image.open('examples/TomatoYellowCurlVirus6.JPG').convert('RGB')
 
-def plot_attention(image, layer_num):
+def plot_attention(image):
     """Given an input image, plot the average attention weight given to each image patch by each attention head."""
     attention_map_outputs = []
     input_data = data_transforms(image)
-    with nopdb.capture_call(vision_transformer.blocks[int(layer_num)-1].attn.forward) as attn_call:
+    with nopdb.capture_call(vision_transformer.blocks[int(6)-1].attn.forward) as attn_call:
         predict_tensor(img_transformed)
     attn = attn_call.locals['attn'][0]
     with torch.inference_mode():
@@ -138,8 +138,7 @@ classify_interface = gr.Interface(
 
 attention_interface = gr.Interface(
     fn=plot_attention,
-    inputs=[gr.Image(type="pil", label="Image"),
-            gr.Slider(1, 12, step=1, label="Transformer Encoder Layer")],
+    inputs=gr.Image(type="pil", label="Image"),
     outputs=gr.Gallery(value=attention_maps, label="Attention Maps").style(grid=(3, 4)),
     examples=example_list,
     title=title_attention,