File size: 1,666 Bytes
f71ac1d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | """This module contains utilities for progress bar."""
from __future__ import annotations
import datetime
from torch import Tensor
from .time import Timer
from .typing import MetricLogs
def compose_log_str(
prefix: str,
cur_iter: int,
total_iters: int,
timer: Timer,
metrics: None | MetricLogs = None,
) -> str:
"""Compose log str from given information."""
time_sec_tot = timer.time()
time_sec_avg = time_sec_tot / cur_iter
eta_sec = time_sec_avg * (total_iters - cur_iter)
if not eta_sec == float("inf"):
eta_str = str(datetime.timedelta(seconds=int(eta_sec)))
else: # pragma: no cover
eta_str = "---"
metrics_list: list[str] = []
if metrics is not None:
for k, v in metrics.items():
name = k.split("/")[-1] # remove prefix, e.g. train/loss
if isinstance(v, (Tensor, float)):
# display more digits for small values
if abs(v) < 1e-3: # type: ignore[operator]
kv_str = f"{name}: {v:.3e}"
else:
kv_str = f"{name}: {v:.4f}"
else:
kv_str = f"{name}: {v}"
if name == "loss": # put total loss first
metrics_list.insert(0, kv_str)
else:
metrics_list.append(kv_str)
time_str = f"ETA: {eta_str}, " + (
f"{time_sec_avg:.2f}s/it"
if time_sec_avg > 1
else f"{1/time_sec_avg:.2f}it/s"
)
logging_str = f"{prefix}: {cur_iter}/{total_iters}, {time_str}"
if len(metrics_list) > 0:
logging_str += ", " + ", ".join(metrics_list)
return logging_str
|