Use radio

app.py

@@ -140,12 +140,13 @@ BENCHMARK_DATA = {
 }
 
 
-def get_plot(model_name, generate_type):
+def get_plot(model_name, plot_eager, generate_type):
     df = pd.DataFrame(BENCHMARK_DATA[generate_type][model_name])
     df["framework"] = ["PyTorch", "TF (Eager Execition)", "TF (XLA)"]
     df = pd.melt(df, id_vars=["framework"], value_vars=["T4", "3090", "A100"])
+    if plot_eager == "No":
+        df = df[df["framework"] != "TF (Eager Execition)"]
 
-    # fig = plt.figure(figsize=(100, 6), dpi=200)
     g = sns.catplot(
         data=df, kind="bar",
         x="variable", y="value", hue="framework",
@@ -171,9 +172,9 @@ with demo:
         with gr.TabItem("Greedy Search"):
             gr.Markdown(
                 """
-                ### Greedy Search parameters
+                ### Greedy Search benchmark parameters
                 - `max_new_tokens = 64`;
-                - `pad_multiple = 64` for Tensorflow XLA models. Others do not pad (input prompts between 2 and 33 tokens).
+                - `pad_to_multiple_of = 64` for Tensorflow XLA models. Others do not pad (input prompts between 2 and 33 tokens).
                 """
             )
             with gr.Row():
@@ -183,10 +184,15 @@ with demo:
                     label="Model",
                     interactive=True,
                 )
-                eager_enabler = gr.Radio(["Yes", "No"], value="Yes", label="Plot TF Eager Execution?")
+                eager_enabler = gr.Radio(
+                    ["Yes", "No"],
+                    value="Yes",
+                    label="Plot TF Eager Execution?",
+                    interactive=True
+                )
             plot_fn = functools.partial(get_plot, generate_type="Greedy Search")
             plot = gr.Plot(value=plot_fn("T5 Small"))  # Show plot when the gradio app is initialized
-            model_selector.change(fn=plot_fn, inputs=model_selector, outputs=plot)
+            model_selector.change(fn=plot_fn, inputs=[model_selector, eager_enabler], outputs=plot)
         with gr.TabItem("Sample"):
             gr.Button("New Tiger")
         with gr.TabItem("Beam Search"):