Remove winner

src/validator_states.py

@@ -1,4 +1,3 @@
-import statistics
 from datetime import timedelta
 
 import gradio as gr
@@ -6,7 +5,7 @@ import pandas as pd
 from packaging import version
 
 from chain_data import get_nodes, UPDATED
-from wandb_data import get_current_runs, Run, BenchmarkStatus
+from wandb_data import get_current_runs, Run
 
 AVERAGE_BENCHMARKING_TIME_WARNING_THRESHOLD = 180  # 3 minutes
 ETA_WARNING_THRESHOLD = 43200  # 12 hours
@@ -30,8 +29,6 @@ def colorize(val, color: str) -> str:
 def create_validator_states() -> gr.Dataframe:
     data: list[list] = []
     runs = sorted(get_current_runs(), key=lambda run: run.uid)
-    winners = [run.winner_uid for run in runs if run.winner_uid and run.status == BenchmarkStatus.FINISHED]
-    winner_uid_mode = statistics.mode(winners) if winners else None
     latest_version = get_latest_version(runs)
     for run in runs:
         if not run.hotkey in get_nodes():
@@ -43,7 +40,6 @@ def create_validator_states() -> gr.Dataframe:
             run.name,
             colorize(run.version, "springgreen" if run.version == latest_version else "red"),
             colorize(run.status.name(), run.status.color()),
-            colorize(run.winner_uid, "springgreen" if winner_uid_mode and run.winner_uid == winner_uid_mode else "orange" if run.winner_uid and run.status == BenchmarkStatus.FINISHED else "gray"),
             f"{min(run.total_submissions, len(run.submissions) + len(run.invalid_submissions))}/{run.total_submissions}",
             len(run.invalid_submissions),
             colorize(f"{timedelta(seconds=int(run.average_benchmarking_time))}", "orange" if run.average_benchmarking_time > AVERAGE_BENCHMARKING_TIME_WARNING_THRESHOLD else "springgreen" if run.average_benchmarking_time > 0 else "gray"),
@@ -54,8 +50,8 @@ def create_validator_states() -> gr.Dataframe:
         ])
 
     return gr.Dataframe(
-        pd.DataFrame(data, columns=["UID", "Name", "Version", "Status", "Winner", "Tested", "Invalid", "Avg. Benchmark Time", "ETA", "Step", "VTrust", "Updated"]),
-        datatype=["number", "markdown", "markdown", "markdown", "markdown", "number", "number", "markdown", "markdown", "number", "markdown", "markdown"],
+        pd.DataFrame(data, columns=["UID", "Name", "Version", "Status", "Tested", "Invalid", "Avg. Benchmark Time", "ETA", "Step", "VTrust", "Updated"]),
+        datatype=["number", "markdown", "markdown", "markdown", "number", "number", "markdown", "markdown", "number", "markdown", "markdown"],
         interactive=False,
         max_height=800,
         row_count=1,

src/wandb_data.py

@@ -88,7 +88,6 @@ class Run:
     average_benchmarking_time: float
     step: int
     eta: int
-    winner_uid: int | None
     baseline_metrics: Metrics | None
     total_submissions: int
     submissions: dict[Key, Submission]
@@ -201,13 +200,6 @@ def _add_runs(wandb_runs: list[wapi.Run]):
                 ...
 
         status = _status_from_run(wandb_run)
-        winner_submission = max(
-            submissions.values(),
-            key=lambda submission: submission.score,
-            default=None
-        )
-        winner_uid = winner_submission.info.uid if winner_submission else None
-
         uid = int(wandb_run.config["uid"])
         hotkey = wandb_run.config["hotkey"]
         date = _date_from_run(wandb_run)
@@ -216,11 +208,11 @@ def _add_runs(wandb_runs: list[wapi.Run]):
 
         # Get num_gpus from metrics, default to 1 if not found
         num_gpus = int(metrics.get("num_gpus", 1))
-        
+
         # Update ETA calculation to account for GPUs
         eta_calculation = (
             max(
-                int(average_benchmarking_time * (len(submission_info) - len(submissions) - len(invalid_submissions))) if average_benchmarking_time else 0, 
+                int(average_benchmarking_time * (len(submission_info) - len(submissions) - len(invalid_submissions))) if average_benchmarking_time else 0,
                 0
             ) // num_gpus  # Divide by number of GPUs
             if status != BenchmarkStatus.FINISHED else 0
@@ -236,7 +228,6 @@ def _add_runs(wandb_runs: list[wapi.Run]):
             average_benchmarking_time=average_benchmarking_time,
             step=int(metrics["step"]),
             eta=eta_calculation,
-            winner_uid=winner_uid,
             baseline_metrics=baseline_metrics,
             total_submissions=len(submission_info),
             submissions=submissions,