# 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())