CLI utility to quickly inspect the latest scalar values from TensorBoard logs.

tensorboard_inspect.py

#!/usr/bin/env python
"""
CLI utility to quickly inspect the latest scalar values from TensorBoard logs.

Dependencies:
  pip install tbparse pandas fire tqdm

Usage:
  python tensorboard_inspect.py --logdir ./path/to/logs
"""

import logging
from pathlib import Path

import pandas as pd
from tbparse import SummaryReader
from tqdm import tqdm
import fire

# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s]: %(message)s')
logger = logging.getLogger(__name__)


def infer_latest_logdir(logdir: Path) -> Path:
    """Automatically finds the latest modified event file directory."""
    logdirs = [d for d in logdir.glob("**/*") if d.is_dir()]
    latest_dir = max(logdirs, key=lambda d: d.stat().st_mtime, default=logdir)
    logger.info(f"Inferred latest log directory: {latest_dir}")
    return latest_dir


def extract_latest_scalars(logdir: Path) -> pd.DataFrame:
    """Extracts the latest scalar values from TensorBoard logs."""
    if not logdir.exists():
        raise FileNotFoundError(f"Log directory '{logdir}' does not exist.")

    reader = SummaryReader(str(logdir))
    scalars_df = reader.scalars

    if scalars_df.empty:
        raise ValueError(f"No scalar data found in '{logdir}'.")

    latest_scalars = scalars_df.sort_values("step").groupby("tag").last().reset_index()
    return latest_scalars


def main(logdir: str, infer_latest: bool = False):
    """
    CLI entrypoint to print latest TensorBoard scalar metrics.

    Args:
        logdir (str): Path to TensorBoard log directory.
        infer_latest (bool): If True, auto-selects the most recent log subdirectory.
    """
    logdir_path = Path(logdir).resolve()

    if infer_latest:
        logdir_path = infer_latest_logdir(logdir_path)

    logger.info(f"Loading TensorBoard logs from: {logdir_path}")

    try:
        latest_scalars = extract_latest_scalars(logdir_path)
    except (FileNotFoundError, ValueError) as e:
        logger.error(e)
        return

    logger.info("Latest scalar values:")
    for _, row in latest_scalars.iterrows():
        tag, step, value = row['tag'], row['step'], row['value']
        print(f"{tag:30}: step {step:<10} value {value:.6f}")


if __name__ == "__main__":
    fire.Fire(main)

what it does: