o oi@sdZddlZddlmZddlmZmZmZmZddl m Z ddl m Z ddl mZddlmZdd lmZdd lmZdd lmZdd lmZdd lmZGdddeZGdddee Z dS)ze CSV logger ---------- CSV logger for basic experiment logging that does not require opening ports N) Namespace)AnyDictOptionalUnion)override) CSVLogger)_ExperimentWriter)rank_zero_experiment)_convert_params)_PATH)save_hparams_to_yaml)Logger)rank_zero_onlycsZeZdZdZdZdeddffdd Zdeeefddfd d Z e d fd d Z Z S)ExperimentWritera3Experiment writer for CSVLogger. Currently, supports to log hyperparameters and metrics in YAML and CSV format, respectively. This logger supports logging to remote filesystems via ``fsspec``. Make sure you have it installed. Args: log_dir: Directory for the experiment logs z hparams.yamllog_dirreturnNcstj|di|_dS)Nr)super__init__hparams)selfr __class__V/home/ubuntu/.local/lib/python3.10/site-packages/lightning/pytorch/loggers/csv_logs.pyr5s zExperimentWriter.__init__paramscCs|j|dS)zRecord hparams.N)rupdaterrrrr log_hparams9szExperimentWriter.log_hparamscs(tj|j|j}t||jtS)z-Save recorded hparams and metrics into files.) ospathjoinrNAME_HPARAMS_FILEr rrsave)r hparams_filerrrr$=s  zExperimentWriter.save)rN) __name__ __module__ __qualname____doc__r#strrrrrrr$ __classcell__rrrrr&s rc seZdZdZdZ    ddedeed eee efd ed e f fd d Z e e defddZ e e defddZe e defddZe edeeeefefddfddZe e edefddZZS)raLog to local file system in yaml and CSV format. Logs are saved to ``os.path.join(save_dir, name, version)``. Example: >>> from lightning.pytorch import Trainer >>> from lightning.pytorch.loggers import CSVLogger >>> logger = CSVLogger("logs", name="my_exp_name") >>> trainer = Trainer(logger=logger) Args: save_dir: Save directory name: Experiment name, optional. Defaults to ``'lightning_logs'``. If name is ``None``, logs (versions) will be stored to the save dir directly. version: Experiment version. If version is not specified the logger inspects the save directory for existing versions, then automatically assigns the next available version. prefix: A string to put at the beginning of metric keys. flush_logs_every_n_steps: How often to flush logs to disk (defaults to every 100 steps). -lightning_logsNdsave_dirnameversionprefixflush_logs_every_n_stepscs&tj|||||dt||_dS)N)root_dirr1r2r3r4)rrr fspath _save_dir)rr0r1r2r3r4rrrr]szCSVLogger.__init__rcCstj|j|jS)zParent directory for all checkpoint subdirectories. If the experiment name parameter is an empty string, no experiment subdirectory is used and the checkpoint will be saved in "save_dir/version" )r r!r"r0r1rrrrr5ns zCSVLogger.root_dircCs.t|jtr |jnd|j}tj|j|S)zThe log directory for this run. By default, it is named ``'version_${self.version}'`` but it can be overridden by passing a string value for the constructor's version parameter instead of ``None`` or an int. version_) isinstancer2r*r r!r"r5)rr2rrrrys zCSVLogger.log_dircCs|jS)zThe current directory where logs are saved. Returns: The path to current directory where logs are saved. )r7r8rrrr0s zCSVLogger.save_dirrcCst|}|j|dS)N)r experimentrrrrrlog_hyperparamsszCSVLogger.log_hyperparamscCs6|jdur|jS|jj|jddt|jd|_|jS)zActual _ExperimentWriter object. To use _ExperimentWriter features in your :class:`~lightning.pytorch.core.LightningModule` do the following. Example:: self.logger.experiment.some_experiment_writer_function() NT)exist_okr) _experiment_fsmakedirsr5rrr8rrrr;s zCSVLogger.experiment)r-Nr.r/)r&r'r(r)LOGGER_JOIN_CHARr rr*rintrpropertyrr5rr0rrrrr<r _FabricExperimentWriterr;r+rrrrrEsD   &r)r)r argparsertypingrrrrtyping_extensionsr!lightning.fabric.loggers.csv_logsrFabricCSVLoggerr rDlightning.fabric.loggers.loggerr !lightning.fabric.utilities.loggerr lightning.fabric.utilities.typesr lightning.pytorch.core.savingr lightning.pytorch.loggers.loggerr%lightning.pytorch.utilities.rank_zerorrrrrrs