o ei'@sdZddlZddlZddlZddlZddlZddlZddlZddlZddl Z ddl m Z ddl m Z ddlmZidddd d d d d dddddddddddddddddddd d!d"d#d$d%d&Zidd'dd(d d)d d*dd+dd,dd-dd.dddd/dd0dd1dd2dd3d!d4d#d5d%d6ZGd7d8d8ejZd9ed:efd;d<Zd=id>fd?d@ZGdAdBdBejZdHdDdEZdFdGZdS)IzManaging the logger, utilities Author * Fang-Pen Lin 2012 https://fangpenlin.com/posts/2012/08/26/good-logging-practice-in-python/ * Peter Plantinga 2020 * Aku Rouhe 2020 N)recursive_updateif_main_process) run_shelliyiziaifipiniµmkM G TPEZY septillionths sextillionthsquintillionthsquadrillionths trillionths billionths millionths thousandthsThousandMillionBillionTrillion Quadrillion Quintillion Sextillion Septillionc@s\eZdZdZededefddZdedede d e fd d Z e d de d e fd dZd S)MultiProcessLoggerAdaptera  Logger adapter that handles multi-process logging, ensuring logs are written only on the main process if specified. This class extends `logging.LoggerAdapter` and provides additional functionality for controlling logging in multi-process environments, with the option to limit logs to the main process only. This class is heavily inspired by HuggingFace Accelerate toolkit: https://github.com/huggingface/accelerate/blob/85b1a03552cf8d58e036634e004220c189bfb247/src/accelerate/logging.py#L22 main_process_onlyreturncCs| p|otS)a Determines if logging should occur based on whether the code is running on the main process or not. Arguments --------- main_process_only : bool A flag indicating if logging should be restricted to the main process. Returns ------- bool True if logging should be performed (based on the process and the flag), False otherwise. r)r1r3V/home/ubuntu/transcripts/venv/lib/python3.10/site-packages/speechbrain/utils/logger.py _should_logNsz%MultiProcessLoggerAdapter._should_loglevelmsgargskwargscOsd|dd}|dd||r.||r0|||\}}|jj||g|Ri|dSdSdS)az Logs a message with the specified log level, respecting the `main_process_only` flag to decide whether to log based on the current process. Arguments --------- level : int Logging level (e.g., logging.INFO, logging.WARNING). msg : str The message to log. *args : tuple Additional positional arguments passed to the logger. **kwargs : dict Additional keyword arguments passed to the logger, including: - main_process_only (bool): If True, log only from the main process (default: True). - stacklevel (int): The stack level to use when logging (default: 2). Notes ----- If `main_process_only` is True, the log will only be written if the current process is the main process, as determined by `if_main_process()`. r1T stacklevelN)pop setdefault isEnabledForr5processloggerlog)selfr6r7r8r9r1r3r3r4rAcs     zMultiProcessLoggerAdapter.logNcOs|j|i|dS)a Logs a warning message only once by using caching to prevent duplicate warnings. Arguments --------- *args : tuple Positional arguments passed to the warning log. **kwargs : dict Keyword arguments passed to the warning log. Notes ----- This method is decorated with `functools.lru_cache(None)`, ensuring that the warning message is logged only once regardless of how many times the method is called. N)warning)rBr8r9r3r3r4 warning_oncesz&MultiProcessLoggerAdapter.warning_once)__name__ __module__ __qualname____doc__ staticmethodboolr5intstrtupledictrA functools lru_cacherDr3r3r3r4r0Cs r0namer2cCsFt|}tjdd}|durd}|tjd<||t|iS)a Retrieves a logger with the specified name, applying a log level from the environment variable `SB_LOG_LEVEL` if set, or defaults to `INFO` level. If the environment variable `SB_LOG_LEVEL` is not defined, it defaults to `INFO` level and sets this level in the environment for future use. The environment variable can be set manually or automatically in `Brain` class following `setup_logging`. Arguments --------- name : str The name of the logger to retrieve. Returns ------- MultiProcessLoggerAdapter An instance of `MultiProcessLoggerAdapter` wrapping the logger with the specified name. SB_LOG_LEVELNDEBUG)logging getLoggerosenvirongetsetLevelupperr0)rQr@ log_levelr3r3r4 get_loggers   r\zlog-config.yamlrScCsvtj|r.t|ddd }t|}Wdn1swYt||tj |ntj |d|tj d<dS)aSetup logging configuration. Arguments --------- config_path : str The path to a logging config file. overrides : dict A dictionary of the same structure as the config dict with any updated values that need to be applied. default_level : str The log level to use if the config file is not found. Python logging allows ints or strings: https://docs.python.org/3/library/logging.html#logging.Logger.setLevel but strings are used here as environment variables have to be strings. The available levels are listed here: https://docs.python.org/3/library/logging.html#levels rtzutf-8)encodingN)r6rR) rVpathexistsopenyaml safe_loadrrTconfig dictConfig basicConfigrW) config_path overrides default_levelr rdr3r3r4 setup_loggings    rjc@seZdZdZddZdS)TqdmCompatibleStreamHandlerzTQDM compatible StreamHandler. Writes and prints should be passed through tqdm.tqdm.write so that the tqdm progressbar doesn't get messed up. cCs`z||}|j}tjj||j|d|WdSty!ty/||YdSw)zTQDM compatible StreamHandler.)endfileN) formatstreamtqdmwrite terminatorflushRecursionError Exception handleError)rBrecordr7ror3r3r4emits   z TqdmCompatibleStreamHandler.emitN)rErFrGrHrxr3r3r3r4rks rkTcCs|rtnt}d}dttt|d}||vr.|dkr.|td|}||vr.|dks||}|dkrA|j|d|d}nt|t rKt |}n|j|d}|sU|sY||S|d|S)aFormats number to the appropriate order of magnitude for printing. Arguments --------- number : int, float The number to format. abbreviate : bool Whether to use abbreviations (k,M,G) or words (Thousand, Million, Billion). Numbers will be either like: "123.5k" or "123.5 Thousand". Returns ------- str The formatted number. Note that the order of magnitude token is part of the string. Example ------- >>> print(format_order_of_magnitude(123456)) 123.5k >>> print(format_order_of_magnitude(0.00000123, abbreviate=False)) 1.2 millionths >>> print(format_order_of_magnitude(5, abbreviate=False)) 5 z {num:3.1f}rir )num ) ORDERS_ABBREV ORDERS_WORDSmathfloorrAfabscopysignrn isinstancerKrL)number abbreviatestyle precisionorder order_tokenformatted_numberr3r3r4format_order_of_magnitudes     rcCsdtjd}ztd\}}}d}||jdd7}Wn ty%d}Ynwztd\}}}d |jdd}Wn tyBd }Ynwtjr\tjjd urUd tjj}n d tjj}nd}d}|d7}||7}|d7}||7}|d7}||7}|d7}||7}|S)a`Returns a string describing the current Python / SpeechBrain environment. Useful for making experiments as replicable as possible. Returns ------- str The string is formatted ready to be written to a file. Example ------- >>> get_environment_description().splitlines()[0] 'SpeechBrain system description' zPython version:  z pip freezezInstalled Python packages: replace)errorsz.Could not list python packages with pip freezezgit rev-parse --short HEADzGit revision: zCould not get git revisionNzROCm version: zCUDA version: zCUDA not availablezSpeechBrain system description z============================== ) sysversionrdecodeOSErrortorchcuda is_availablehip)python_version_strfreezed_python_packages_strgit_hashgit_strcuda_strresultr3r3r4get_environment_descriptions:    r)T)rHrOrTlogging.configr~rVrrrprbspeechbrain.utils.data_utilsrspeechbrain.utils.distributedrspeechbrain.utils.superpowersrr|r} LoggerAdapterr0rLr\rj StreamHandlerrkrrr3r3r3r4s             S   .