update

app.py

@@ -381,7 +381,7 @@ def render_sidebar():
             st.markdown("**Eigen-IG**")
             eigen_components = st.slider("Number of principal components", 1, 12, 5, 1)
 
-        run_btn = st.button("▶ Run Analysis", use_column_width=True)
+        run_btn = st.button("▶ Run Analysis", use_container_width=True)
 
     return {
         "model_name": model_name,
@@ -577,7 +577,7 @@ def run_batch_benchmark(model, config, cfg, labels, device):
 
     st.markdown("#### Results summary (mean ± std)")
     summary = df.groupby("method")[["deletion_auc", "insertion_auc", "infidelity"]].agg(["mean", "std"]).round(4)
-    st.dataframe(summary, use_column_width=True)
+    st.dataframe(summary, use_container_width=True)
 
     csv_bytes = df.to_csv(index=False).encode()
     st.download_button(
@@ -586,9 +586,9 @@ def run_batch_benchmark(model, config, cfg, labels, device):
         file_name="xai_benchmark_results.csv",
         mime="text/csv",
         type="primary",
-        use_column_width=True,
+        use_container_width=True,
     )
-    st.dataframe(df, use_column_width=True)
+    st.dataframe(df, use_container_width=True)
 
 # ─── Main ─────────────────────────────────────────────────────────────────────
 
@@ -731,11 +731,11 @@ def main():
         st.info("Click **▶ Run Analysis** in the sidebar to compute attributions.")
         col1, col2 = st.columns([1, 2])
         with col1:
-            st.image(display_img, caption="Input Image", use_column_width=True).use_column_width
+            st.image(display_img, caption="Input Image", use_column_width=True)
         with col2:
             st.plotly_chart(
                 plot_top_predictions(probs, labels, top_k=5),
-                use_column_width=True,
+                use_container_width=True,
             )
         return
 
@@ -796,12 +796,12 @@ def main():
             colormap=cfg["colormap"],
             alpha=cfg["alpha"],
         )
-        st.image(fig_to_pil(fig), use_column_width=True).use_column_width
+        st.image(fig_to_pil(fig), use_column_width=True)
 
         st.markdown("#### Top-5 Predictions")
         st.plotly_chart(
             plot_top_predictions(probs, labels, top_k=5),
-            use_column_width=True,
+            use_container_width=True,
         )
 
     # ── Tab 2: Individual interactive maps ─────────────────────────────────────
@@ -889,7 +889,7 @@ def main():
             ann.font.color = "white"
         fig.update_xaxes(gridcolor="#2a2f3e")
         fig.update_yaxes(gridcolor="#2a2f3e")
-        st.plotly_chart(fig, use_column_width=True)
+        st.plotly_chart(fig, use_container_width=True)
 
     # ── Tab 4: Method Info ─────────────────────────────────────────────────────
     with tabs[3]: