Add baseline to leaderboard

src/app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 
 from chain_data import sync_metagraph
-from leaderboard import create_leaderboard, create_dropdown
+from leaderboard import create_leaderboard, create_dropdown, create_baseline
 from model_demo import create_demo
 from submissions import create_submissions
 from validator_states import create_validator_states
@@ -17,10 +17,14 @@ def main():
             dropdown = gr.Dropdown()
             dropdown.attach_load_event(lambda: create_dropdown(), None)
 
+            baseline_dataframe = gr.Dataframe()
+            baseline_dataframe.attach_load_event(lambda uid: create_baseline(uid), None, inputs=[dropdown])
+            leaderboard_tab.select(lambda uid: create_baseline(uid), inputs=[dropdown], outputs=[baseline_dataframe])
+            dropdown.change(lambda uid: create_baseline(uid), inputs=[dropdown], outputs=[baseline_dataframe])
+
             leaderboard_dataframe = gr.Dataframe()
             leaderboard_dataframe.attach_load_event(lambda uid: create_leaderboard(uid), None, inputs=[dropdown])
             leaderboard_tab.select(lambda uid: create_leaderboard(uid), inputs=[dropdown], outputs=[leaderboard_dataframe])
-
             dropdown.change(lambda uid: create_leaderboard(uid), inputs=[dropdown], outputs=[leaderboard_dataframe])
         with gr.Tab("Validator States") as validator_states_tab:
             validator_states_dataframe = gr.Dataframe()

src/leaderboard.py

@@ -3,6 +3,7 @@ import os
 import gradio as gr
 import pandas as pd
 
+from src import Uid
 from wandb_data import get_current_runs
 
 DEFAULT_VALIDATOR_UID = int(os.environ["DEFAULT_VALIDATOR_UID"])
@@ -28,7 +29,7 @@ def create_dropdown() -> gr.Dropdown:
     )
 
 
-def create_leaderboard(validator_uid) -> gr.Dataframe:
+def create_leaderboard(validator_uid: Uid) -> gr.Dataframe:
     data: list[list] = []
     runs = get_current_runs()
     for run in runs:
@@ -60,3 +61,26 @@ def create_leaderboard(validator_uid) -> gr.Dataframe:
         interactive=False,
         max_height=800,
     )
+
+
+def create_baseline(validator_uid: Uid) -> gr.Dataframe:
+    data: list[list] = []
+    runs = get_current_runs()
+    for run in runs:
+        if run.uid != validator_uid:
+            continue
+        data.append([
+            f"{run.baseline_metrics.generation_time:.4f}s",
+            f"{run.baseline_metrics.size / 1024 ** 3:.4f}GB",
+            f"{run.baseline_metrics.vram_used / 1024 ** 3:.4f}GB",
+            f"{run.baseline_metrics.ram_used / 1024 ** 3:.4f}GB",
+            f"{run.baseline_metrics.watts_used:.3f}W",
+            f"{run.baseline_metrics.load_time:.3f}s",
+        ])
+
+    return gr.Dataframe(
+        pd.DataFrame(data, columns=["Gen Time", "Size", "VRAM Used", "RAM Used", "Power Used", "Load Time"]),
+        datatype=["number", "markdown", "markdown", "markdown", "markdown", "markdown"],
+        interactive=False,
+        label="Baseline",
+    )