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"),formatandname - 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
from rich_logger import RichTablePrinter
import time
import random
from tqdm import trange
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)"},
".*": True, # Any other field must be logged at the end
}
def optimization():
printer = RichTablePrinter(key="step", fields=logger_fields)
printer.hijack_tqdm()
t = time.time()
for i in trange(10):
time.sleep(random.random() / 3)
printer.log(
{
"step": i,
"task_precision": i / 10.0 if i < 5 else 0.5 - (i - 5) / 10.0,
}
)
time.sleep(random.random() / 3)
printer.log(
{
"step": i,
"task_recall": 0.0 if i < 3 else (i - 3) / 10.0,
"duration": time.time() - t,
}
)
printer.log({"test": i})
t = time.time()
for j in trange(5):
time.sleep(random.random() / 10)
printer.finalize()
optimization()
Use it with PytorchLightning
from rich_logger import RichTableLogger
trainer = pl.Trainer(..., logger=[RichTableLogger(key="epoch", fields=logger_fields)])
