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#!/usr/bin/env python | |
""" | |
generic helper methods | |
""" | |
import os | |
import string | |
import logging | |
import warnings | |
log_format = '%(asctime)s %(levelname)s: %(message)s' | |
logging.basicConfig(level = logging.INFO, format = log_format) | |
warnings.filterwarnings(action="ignore", category=DeprecationWarning) | |
warnings.filterwarnings(action="ignore", category=FutureWarning) | |
warnings.filterwarnings(action="ignore", category=UserWarning) | |
log = logging.getLogger("sd") | |
def set_logfile(logfile): | |
fh = logging.FileHandler(logfile) | |
formatter = logging.Formatter(log_format) | |
fh.setLevel(log.getEffectiveLevel()) | |
fh.setFormatter(formatter) | |
log.addHandler(fh) | |
log.info({ 'log file': logfile }) | |
def safestring(text: str): | |
lines = [] | |
for line in text.splitlines(): | |
lines.append(line.translate(str.maketrans('', '', string.punctuation)).strip()) | |
res = ', '.join(lines) | |
return res[:1000] | |
def get_memory(): | |
def gb(val: float): | |
return round(val / 1024 / 1024 / 1024, 2) | |
mem = {} | |
try: | |
import psutil | |
process = psutil.Process(os.getpid()) | |
res = process.memory_info() | |
ram_total = 100 * res.rss / process.memory_percent() | |
ram = { 'free': gb(ram_total - res.rss), 'used': gb(res.rss), 'total': gb(ram_total) } | |
mem.update({ 'ram': ram }) | |
except Exception as e: | |
mem.update({ 'ram': e }) | |
try: | |
import torch | |
if torch.cuda.is_available(): | |
s = torch.cuda.mem_get_info() | |
gpu = { 'free': gb(s[0]), 'used': gb(s[1] - s[0]), 'total': gb(s[1]) } | |
s = dict(torch.cuda.memory_stats('cuda')) | |
allocated = { 'current': gb(s['allocated_bytes.all.current']), 'peak': gb(s['allocated_bytes.all.peak']) } | |
reserved = { 'current': gb(s['reserved_bytes.all.current']), 'peak': gb(s['reserved_bytes.all.peak']) } | |
active = { 'current': gb(s['active_bytes.all.current']), 'peak': gb(s['active_bytes.all.peak']) } | |
inactive = { 'current': gb(s['inactive_split_bytes.all.current']), 'peak': gb(s['inactive_split_bytes.all.peak']) } | |
events = { 'retries': s['num_alloc_retries'], 'oom': s['num_ooms'] } | |
mem.update({ | |
'gpu': gpu, | |
'gpu-active': active, | |
'gpu-allocated': allocated, | |
'gpu-reserved': reserved, | |
'gpu-inactive': inactive, | |
'events': events, | |
}) | |
except Exception: | |
pass | |
return Map(mem) | |
class Map(dict): # pylint: disable=C0205 | |
__slots__ = ('__dict__') # pylint: disable=superfluous-parens | |
def __init__(self, *args, **kwargs): | |
super(Map, self).__init__(*args, **kwargs) # pylint: disable=super-with-arguments | |
for arg in args: | |
if isinstance(arg, dict): | |
for k, v in arg.items(): | |
if isinstance(v, dict): | |
v = Map(v) | |
if isinstance(v, list): | |
self.__convert(v) | |
self[k] = v | |
if kwargs: | |
for k, v in kwargs.items(): | |
if isinstance(v, dict): | |
v = Map(v) | |
elif isinstance(v, list): | |
self.__convert(v) | |
self[k] = v | |
def __convert(self, v): | |
for elem in range(0, len(v)): # pylint: disable=consider-using-enumerate | |
if isinstance(v[elem], dict): | |
v[elem] = Map(v[elem]) | |
elif isinstance(v[elem], list): | |
self.__convert(v[elem]) | |
def __getattr__(self, attr): | |
return self.get(attr) | |
def __setattr__(self, key, value): | |
self.__setitem__(key, value) | |
def __setitem__(self, key, value): | |
super(Map, self).__setitem__(key, value) # pylint: disable=super-with-arguments | |
self.__dict__.update({key: value}) | |
def __delattr__(self, item): | |
self.__delitem__(item) | |
def __delitem__(self, key): | |
super(Map, self).__delitem__(key) # pylint: disable=super-with-arguments | |
del self.__dict__[key] | |
if __name__ == "__main__": | |
pass | |