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Duplicate from Anonymous-sub/Rerender
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# Copyright (c) OpenMMLab. All rights reserved.
import logging
import torch.distributed as dist
logger_initialized = {}
def get_logger(name, log_file=None, log_level=logging.INFO, file_mode='w'):
"""Initialize and get a logger by name.
If the logger has not been initialized, this method will initialize the
logger by adding one or two handlers, otherwise the initialized logger will
be directly returned. During initialization, a StreamHandler will always be
added. If `log_file` is specified and the process rank is 0, a FileHandler
will also be added.
Args:
name (str): Logger name.
log_file (str | None): The log filename. If specified, a FileHandler
will be added to the logger.
log_level (int): The logger level. Note that only the process of
rank 0 is affected, and other processes will set the level to
"Error" thus be silent most of the time.
file_mode (str): The file mode used in opening log file.
Defaults to 'w'.
Returns:
logging.Logger: The expected logger.
"""
logger = logging.getLogger(name)
if name in logger_initialized:
return logger
# handle hierarchical names
# e.g., logger "a" is initialized, then logger "a.b" will skip the
# initialization since it is a child of "a".
for logger_name in logger_initialized:
if name.startswith(logger_name):
return logger
# handle duplicate logs to the console
# Starting in 1.8.0, PyTorch DDP attaches a StreamHandler <stderr> (NOTSET)
# to the root logger. As logger.propagate is True by default, this root
# level handler causes logging messages from rank>0 processes to
# unexpectedly show up on the console, creating much unwanted clutter.
# To fix this issue, we set the root logger's StreamHandler, if any, to log
# at the ERROR level.
for handler in logger.root.handlers:
if type(handler) is logging.StreamHandler:
handler.setLevel(logging.ERROR)
stream_handler = logging.StreamHandler()
handlers = [stream_handler]
if dist.is_available() and dist.is_initialized():
rank = dist.get_rank()
else:
rank = 0
# only rank 0 will add a FileHandler
if rank == 0 and log_file is not None:
# Here, the default behaviour of the official logger is 'a'. Thus, we
# provide an interface to change the file mode to the default
# behaviour.
file_handler = logging.FileHandler(log_file, file_mode)
handlers.append(file_handler)
formatter = logging.Formatter(
'%(asctime)s - %(name)s - %(levelname)s - %(message)s')
for handler in handlers:
handler.setFormatter(formatter)
handler.setLevel(log_level)
logger.addHandler(handler)
if rank == 0:
logger.setLevel(log_level)
else:
logger.setLevel(logging.ERROR)
logger_initialized[name] = True
return logger
def print_log(msg, logger=None, level=logging.INFO):
"""Print a log message.
Args:
msg (str): The message to be logged.
logger (logging.Logger | str | None): The logger to be used.
Some special loggers are:
- "silent": no message will be printed.
- other str: the logger obtained with `get_root_logger(logger)`.
- None: The `print()` method will be used to print log messages.
level (int): Logging level. Only available when `logger` is a Logger
object or "root".
"""
if logger is None:
print(msg)
elif isinstance(logger, logging.Logger):
logger.log(level, msg)
elif logger == 'silent':
pass
elif isinstance(logger, str):
_logger = get_logger(logger)
_logger.log(level, msg)
else:
raise TypeError(
'logger should be either a logging.Logger object, str, '
f'"silent" or None, but got {type(logger)}')