Update app.py

app.py

@@ -72,20 +72,19 @@ with block:
                         choices=metric_names, label="Select Metrics for Leaderboard", value=metric_names, interactive=True
                     )
 
-                with gr.Row():
-                    # Display the filtered leaderboard
-                    baseline_value = get_baseline_df(method_names, metric_names)
-                    baseline_header = ["method_name"] + metric_names
-                    baseline_datatype = ['markdown'] + ['number'] * len(metric_names)
+                # Display the filtered leaderboard
+                baseline_value = get_baseline_df(method_names, metric_names)
+                baseline_header = ["method_name"] + metric_names
+                baseline_datatype = ['markdown'] + ['number'] * len(metric_names)
         
-                    data_component = gr.components.Dataframe(
-                        value=baseline_value,
-                        headers=baseline_header,
-                        type="pandas",
-                        datatype=baseline_datatype,
-                        interactive=False,
-                        visible=True,
-                    )
+                data_component = gr.components.Dataframe(
+                    value=baseline_value,
+                    headers=baseline_header,
+                    type="pandas",
+                    datatype=baseline_datatype,
+                    interactive=False,
+                    visible=True,
+                )
     
                 # Update leaderboard when method/metric selection changes
                 leaderboard_method_selector.change(
@@ -101,9 +100,8 @@ with block:
 
             with gr.Row(variant='panel', show_progress=True):
 
-                with gr.Row():
-                    # Dropdown for benchmark type
-                    benchmark_type_selector = gr.Dropdown(choices=list(benchmark_specific_metrics.keys()), label="Select Benchmark Type")
+                # Dropdown for benchmark type
+                benchmark_type_selector = gr.Dropdown(choices=list(benchmark_specific_metrics.keys()), label="Select Benchmark Type")
 
                 with gr.Row():
                     # Dynamic selectors
@@ -114,16 +112,13 @@ with block:
                     dataset_selector = gr.Dropdown(choices=[], label="Select Dataset", visible=False)
                     single_metric_selector = gr.Dropdown(choices=[], label="Select Metric", visible=False)
 
-                with gr.Row():
-                    # CheckboxGroup for methods
-                    method_selector = gr.CheckboxGroup(choices=method_names, label="Select methods to visualize", interactive=True, value=method_names)
+                method_selector = gr.CheckboxGroup(choices=method_names, label="Select methods to visualize", interactive=True, value=method_names)
                 
                 # Button to draw the plot for the selected benchmark
                 with gr.Row():
                     plot_button = gr.Button("Plot")
                 
-                with gr.Row():
-                    plot_output = gr.Image(label="Plot")
+                plot_output = gr.Image(label="Plot")
                 
                 # Update selectors when benchmark type changes
                 benchmark_type_selector.change(