Note
Click here to download the full example code
Simple Logging Profiler¶
This is a simple profiler that’s used as part of the trainer app example. This logs the Lightning training stage durations a logger such as Tensorboard. This output is used for HPO optimization with Ax.
import time
from typing import Dict
from pytorch_lightning.loggers.logger import Logger
from pytorch_lightning.profilers.profiler import Profiler
class SimpleLoggingProfiler(Profiler):
"""
This profiler records the duration of actions (in seconds) and reports the
mean duration of each action to the specified logger. Reported metrics are
in the format `duration_<event>`.
"""
def __init__(self, logger: Logger) -> None:
super().__init__()
self.current_actions: Dict[str, float] = {}
self.logger = logger
def start(self, action_name: str) -> None:
if action_name in self.current_actions:
raise ValueError(
f"Attempted to start {action_name} which has already started."
)
self.current_actions[action_name] = time.monotonic()
def stop(self, action_name: str) -> None:
end_time = time.monotonic()
if action_name not in self.current_actions:
raise ValueError(
f"Attempting to stop recording an action ({action_name}) which was never started."
)
start_time = self.current_actions.pop(action_name)
duration = end_time - start_time
self.logger.log_metrics({"duration_" + action_name: duration})
def summary(self) -> str:
return ""
# sphinx_gallery_thumbnail_path = '_static/img/gallery-lib.png'
Total running time of the script: ( 0 minutes 0.000 seconds)