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# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Logger configuration for Compressed Tensors.
"""
import os
import sys
from dataclasses import dataclass
from typing import Any, Dict, Optional
from loguru import logger
__all__ = ["LoggerConfig", "configure_logger", "logger"]
# used by `support_log_once``
_logged_once = set()
@dataclass
class LoggerConfig:
disabled: bool = False
clear_loggers: bool = True
console_log_level: Optional[str] = "INFO"
log_file: Optional[str] = None
log_file_level: Optional[str] = None
def configure_logger(config: Optional[LoggerConfig] = None):
"""
Configure the logger for Compressed Tensors.
This function sets up the console and file logging
as per the specified or default parameters.
Note: Environment variables take precedence over the function parameters.
:param config: The configuration for the logger to use.
:type config: LoggerConfig
"""
logger_config = config or LoggerConfig()
# env vars get priority
if bool(os.getenv("COMPRESSED_TENSORS_LOG_DISABLED")):
logger_config.disabled = True
if bool(os.getenv("COMPRESSED_TENSORS_CLEAR_LOGGERS")):
logger_config.clear_loggers = True
if (console_log_level := os.getenv("COMPRESSED_TENSORS_LOG_LEVEL")) is not None:
logger_config.console_log_level = console_log_level.upper()
if (log_file := os.getenv("COMPRESSED_TENSORS_LOG_FILE")) is not None:
logger_config.log_file = log_file
if (log_file_level := os.getenv("COMPRESSED_TENSORS_LOG_FILE_LEVEL")) is not None:
logger_config.log_file_level = log_file_level.upper()
if logger_config.disabled:
logger.disable("compressed_tensors")
return
logger.enable("compressed_tensors")
if logger_config.clear_loggers:
logger.remove()
if logger_config.console_log_level:
# log as a human readable string with the time, function, level, and message
logger.add(
sys.stdout,
level=logger_config.console_log_level.upper(),
format="{time} | {function} | {level} - {message}",
filter=support_log_once,
)
if logger_config.log_file or logger_config.log_file_level:
log_file = logger_config.log_file or "compressed_tensors.log"
log_file_level = logger_config.log_file_level or "INFO"
# log as json to the file for easier parsing
logger.add(
log_file,
level=log_file_level.upper(),
serialize=True,
filter=support_log_once,
)
def support_log_once(record: Dict[str, Any]) -> bool:
"""
Support logging only once using `.bind(log_once=True)`
```
logger.bind(log_once=False).info("This will log multiple times")
logger.bind(log_once=False).info("This will log multiple times")
logger.bind(log_once=True).info("This will only log once")
logger.bind(log_once=True).info("This will only log once") # skipped
```
"""
log_once = record["extra"].get("log_once", False)
level = getattr(record["level"], "name", "none")
message = hash(str(level) + record["message"])
if log_once and message in _logged_once:
return False
if log_once:
_logged_once.add(message)
return True
# invoke logger setup on import with default values enabling console logging with INFO
# and disabling file logging
configure_logger(config=LoggerConfig())
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