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nerfstudio/mattport/utils/profiler.py
2022-05-11 00:09:33 +00:00

76 lines
2.5 KiB
Python

"""
Profiler base class and functionality
"""
import logging
import sys
import time
from typing import Callable
from omegaconf import DictConfig
from mattport.utils import comms
from mattport.utils.decorators import check_main_thread, check_profiler_enabled, decorate_all
PROFILER = []
def time_function(func: Callable) -> Callable:
"""Decorator: time a function call"""
def wrapper(*args, **kwargs):
start = time.time()
ret = func(*args, **kwargs)
if PROFILER:
vals = vars(sys.modules[func.__module__])
class_str = ""
for attr in func.__qualname__.split(".")[:-1]:
class_str += f"{vals[attr].__qualname__}_"
class_str += func.__name__
PROFILER[0].update_time(class_str, start, time.time())
return ret
return wrapper
def flush_profiler(config: DictConfig):
"""Method that checks if profiler is enabled before flushing"""
if config.enable_profiler and PROFILER:
PROFILER[0].print_profile()
def setup_profiler(config: DictConfig):
"""Initialization of profilers"""
if comms.is_main_process():
PROFILER.append(Profiler(config))
@decorate_all([check_profiler_enabled, check_main_thread])
class Profiler:
"""Profiler class"""
def __init__(self, config: DictConfig):
self.config = config
self.profiler_dict = {}
def update_time(self, func_name: str, start_time: float, end_time: float):
"""update the profiler dictionary with running averages of durations
Args:
func_name (str): the function name that is being profiled
start_time (float): the start time when function is called
end_time (float): the end time when function terminated
"""
val = end_time - start_time
func_dict = self.profiler_dict.get(func_name, {"val": 0, "step": 0})
prev_val = func_dict["val"]
prev_step = func_dict["step"]
self.profiler_dict[func_name] = {"val": (prev_val * prev_step + val) / (prev_step + 1), "step": prev_step + 1}
def print_profile(self):
"""helper to print out the profiler stats"""
logging.info("Printing profiling stats, from longest to shortest duration in seconds")
sorted_keys = [k for k, _ in sorted(self.profiler_dict.items(), key=lambda item: item[1]["val"], reverse=True)]
for k in sorted_keys:
val = f"{self.profiler_dict[k]['val']:0.4f}"
print(f"{k:<20}: {val:<20}")