remove control panel

app.py

@@ -33,19 +33,22 @@ with demo:
                     gr.Markdown(config.detail, elem_classes="descriptive-text")
 
                 ######################## CONTROL PANEL #######################
-                (
-                    filter_button,
-                    machine_value,
-                    backends_value,
-                    hardware_type_value,
-                    memory_slider,
-                    quantization_checkboxes,
-                ) = create_control_panel(
-                    machine=config.machine,
-                    backends=config.backends,
-                    hardware_provider=config.hardware_provider,
-                    hardware_type=config.hardware_type,
-                )
+                # (
+                #     filter_button,
+                #     machine_value,
+                #     backends_value,
+                #     hardware_type_value,
+                #     memory_slider,
+                #     quantization_checkboxes,
+                # ) = create_control_panel(
+                #     machine=config.machine,
+                #     backends=config.backends,
+                #     hardware_provider=config.hardware_provider,
+                #     hardware_type=config.hardware_type,
+                # )
+                machine_value = gr.State(value=config.machine)
+                backends_value = gr.State(value=config.backends)
+                hardware_type_value = gr.State(value=config.hardware_type)
                 ####################### HARDWARE SUBTABS #######################
                 with gr.Tabs(elem_classes="subtabs"):
                     open_llm_perf_df = get_llm_perf_df(
@@ -69,24 +72,24 @@ with demo:
                     #         create_quant_krnl_plots(llm_perf_df)
                     #     )
                 ####################### CONTROL CALLBACK #######################
-                create_control_callback(
-                    filter_button,
-                    # inputs
-                    machine_value,
-                    backends_value,
-                    hardware_type_value,
-                    memory_slider,
-                    quantization_checkboxes,
-                    # interactive
-                    columns_checkboxes,
-                    search_bar,
-                    # outputs
-                    leaderboard_table,
-                    # attn_prefill_plot,
-                    # attn_decode_plot,
-                    # quant_krnl_prefill_plot,
-                    # quant_krnl_decode_plot,
-                )
+                # create_control_callback(
+                #     filter_button,
+                #     # inputs
+                #     machine_value,
+                #     backends_value,
+                #     hardware_type_value,
+                #     memory_slider,
+                #     quantization_checkboxes,
+                #     # interactive
+                #     columns_checkboxes,
+                #     search_bar,
+                #     # outputs
+                #     leaderboard_table,
+                #     # attn_prefill_plot,
+                #     # attn_decode_plot,
+                #     # quant_krnl_prefill_plot,
+                #     # quant_krnl_decode_plot,
+                # )
 
                 create_select_callback(
                     # inputs

src/leaderboard.py

@@ -4,7 +4,7 @@ from src.utils import model_hyperlink
 
 LEADERBOARD_COLUMN_TO_DATATYPE = {
     # open llm
-    "Model": "markdown",
+    "Model": "str",
     "Quantization": "str",
     # primary measurements
     "Prefill (tokens/s)": "number",
@@ -35,7 +35,7 @@ def process_model(model_name):
 def get_leaderboard_df(llm_perf_df):
     df = llm_perf_df.copy()
     # transform for leaderboard
-    df["Model"] = df["Model"].apply(process_model)
+    # df["Model"] = df["Model"].apply(process_model)
     return df
 
 

src/panel.py

@@ -1,10 +1,10 @@
 from typing import List
 
 import gradio as gr
+import pandas as pd
 
 from src.leaderboard import get_leaderboard_df
 from src.llm_perf import get_llm_perf_df
-
 # from attention_implementations import get_attn_decode_fig, get_attn_prefill_fig
 # from custom_kernels import get_kernel_decode_fig, get_kernel_prefill_fig
 
@@ -21,7 +21,7 @@ def create_control_panel(
     hardware_type_value = gr.State(value=hardware_type)
 
     if hardware_provider == "ARM":
-        backends = ["llama.cpp"]
+        backends = ["llama_cpp"]
         quantizations = ["Q8_0", "Q4_K_M", "Q4_0_4_4"]
     else:
         raise ValueError(f"Unknown hardware provider: {hardware_provider}")
@@ -30,7 +30,7 @@ def create_control_panel(
         with gr.Row():
             with gr.Column(scale=2, variant="panel"):
                 memory_slider = gr.Slider(
-                    label="Model Size (GB) 📈",
+                    label="Model Size (GB)",
                     info="🎚️ Slide to maximum Model Size",
                     minimum=0,
                     maximum=16,
@@ -81,7 +81,7 @@ def filter_rows_fn(
     filtered_llm_perf_df = llm_perf_df[
         llm_perf_df["Model"].str.contains(search, case=False)
         & llm_perf_df["Quantization"].isin(quantizations)
-        & (llm_perf_df["Model Size (GB)"] <= memory)
+        & llm_perf_df["Model Size (GB)"] <= memory
     ]
     selected_filtered_llm_perf_df = select_columns_fn(
         machine, backends, hardware_type, columns, search, filtered_llm_perf_df