MotionGPT / mGPT /utils /logger.py
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from pathlib import Path
import os
import time
import logging
from omegaconf import OmegaConf
from pytorch_lightning.utilities.rank_zero import rank_zero_only
def create_logger(cfg, phase='train'):
# root dir set by cfg
root_output_dir = Path(cfg.FOLDER)
# set up logger
if not root_output_dir.exists():
print('=> creating {}'.format(root_output_dir))
root_output_dir.mkdir()
cfg_name = cfg.NAME
model = cfg.model.target.split('.')[-2]
cfg_name = os.path.basename(cfg_name).split('.')[0]
final_output_dir = root_output_dir / model / cfg_name
cfg.FOLDER_EXP = str(final_output_dir)
time_str = time.strftime('%Y-%m-%d-%H-%M-%S')
new_dir(cfg, phase, time_str, final_output_dir)
head = '%(asctime)-15s %(message)s'
logger = config_logger(final_output_dir, time_str, phase, head)
if logger is None:
logger = logging.getLogger()
logger.setLevel(logging.CRITICAL)
logging.basicConfig(format=head)
return logger
@rank_zero_only
def config_logger(final_output_dir, time_str, phase, head):
log_file = '{}_{}_{}.log'.format('log', time_str, phase)
final_log_file = final_output_dir / log_file
logging.basicConfig(filename=str(final_log_file))
logger = logging.getLogger()
logger.setLevel(logging.INFO)
console = logging.StreamHandler()
formatter = logging.Formatter(head)
console.setFormatter(formatter)
logging.getLogger('').addHandler(console)
file_handler = logging.FileHandler(final_log_file, 'w')
file_handler.setFormatter(logging.Formatter(head))
file_handler.setLevel(logging.INFO)
logging.getLogger('').addHandler(file_handler)
return logger
@rank_zero_only
def new_dir(cfg, phase, time_str, final_output_dir):
# new experiment folder
cfg.TIME = str(time_str)
if os.path.exists(final_output_dir) and not os.path.exists(cfg.TRAIN.RESUME) and not cfg.DEBUG and phase not in ['test', 'demo']:
file_list = sorted(os.listdir(final_output_dir), reverse=True)
for item in file_list:
if item.endswith('.log'):
os.rename(str(final_output_dir), str(final_output_dir) + '_' + cfg.TIME)
break
final_output_dir.mkdir(parents=True, exist_ok=True)
# write config yaml
config_file = '{}_{}_{}.yaml'.format('config', time_str, phase)
final_config_file = final_output_dir / config_file
OmegaConf.save(config=cfg, f=final_config_file)