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Running
Running
from datetime import timedelta | |
import gradio as gr | |
import pandas as pd | |
from packaging import version | |
from chain_data import get_neurons | |
from wandb_data import get_current_runs, Run | |
AVERAGE_BENCHMARKING_TIME_WARNING_THRESHOLD = 180 # 3 minutes | |
ETA_WARNING_THRESHOLD = 43200 # 12 hours | |
UPDATED_WARNING_THRESHOLD = 1000 | |
VTRUST_WARNING_THRESHOLD = 0.75 | |
def get_latest_version(runs: list[Run]) -> str: | |
latest_version = version.parse("0.0.0") | |
for run in runs: | |
current_version = version.parse(run.version) | |
if current_version > latest_version: | |
latest_version = current_version | |
return str(latest_version) | |
def colorize(val, color: str) -> str: | |
return f"<span style='color: {color}'>{val}</span>" | |
def create_validator_states() -> gr.Dataframe: | |
data: list[list] = [] | |
runs = sorted(get_current_runs(), key=lambda run: run.uid) | |
latest_version = get_latest_version(runs) | |
for run in runs: | |
if not run.hotkey in get_neurons(): | |
continue | |
vtrust = get_neurons()[run.hotkey].validator_trust | |
updated = get_neurons()[run.hotkey].updated | |
data.append([ | |
run.uid, | |
run.name, | |
colorize(run.version, "springgreen" if run.version == latest_version else "red"), | |
colorize(run.status.name(), run.status.color()), | |
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"), | |
colorize(f"{timedelta(seconds=run.eta)}", "orange" if run.eta > ETA_WARNING_THRESHOLD else "springgreen" if run.eta > 0 else "gray"), | |
run.step, | |
colorize(f"{vtrust:.4f}", "springgreen" if vtrust > VTRUST_WARNING_THRESHOLD else "red"), | |
colorize(updated, "springgreen" if updated < UPDATED_WARNING_THRESHOLD else "red"), | |
]) | |
return gr.Dataframe( | |
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, | |
) | |