rich_logger

Table logger using Rich, aimed at Pytorch Lightning logging

Features

• display your training logs with pretty rich tables
• describe your fields with goal ("higher_is_better" or "lower_is_better"), format and name
• a field descriptor can be matched with any regex
• a field name can be computed as a regex substitution
• works in Jupyter notebooks as well as in a command line
• integrates easily with Pytorch Lightning

Demo

import time
import random
from rich_logger import RichTablePrinter
logger_fields = {
    "step": {},
    "(.*)_precision": {"goal": "higher_is_better", "format": "{:.4f}", "name": r"\1_p"},
    "(.*)_recall": {"goal": "higher_is_better", "format": "{:.4f}", "name": r"\1_r"},
    "duration": {"format": "{:.1f}", "name": "dur(s)"},
}

def optimization():
    printer = RichTablePrinter(key="step", fields=logger_fields)
    t = time.time()
    for i in range(10):
        time.sleep(random.random())
        printer.log({"step": i, "task_precision": i/10. if i < 5 else 0.5-(i-5)/10.})
        time.sleep(random.random())
        printer.log({"step": i, "task_recall": 0. if i < 3 else (i-3)/10., "duration": time.time() - t})
        t = time.time()
    printer.finalize()
        
optimization()

Use it with PytorchLightning

from rich_logger import RichTableLogger
trainer = pl.Trainer(..., logger=[RichTableLogger(key="epoch", fields=logger_fields)])