:j2,ddlZddlmZddlmZddlmZmZmZm Z ddl m Z ddl m Z ddlmZddlmZdd lmZmZdd lmZmZdd lmZmZmZdd lmZdd lmZm Z ddl!m"Z"ddl#m$Z$e dZ%e dZ&ere%rddl'm(Z(nddl)m(Z(GddeZ*y)N) Namespace)Mapping) TYPE_CHECKINGAnyOptionalUnion)RequirementCache)Tensor)Module)override)Loggerrank_zero_experiment)_is_dirget_filesystem) _add_prefix_convert_params _flatten_dict)_sanitize_params)rank_zero_onlyrank_zero_warn)_PATH)_unwrap_objects tensorboard tensorboardX SummaryWriterceZdZdZdZ d!dedeedeee efde ded eed e ffd Z e ed efd Ze ed ee effdZe ed efdZe ed efdZe d eefdZe ed"dZeed#deeefdee d dfdZee d$deeee fefdeeee fdee d dfdZeed#dedeed dfdZeed%dZ eeded dfdZ!d e fdZ"e#deee fd eee ffdZ$d eee ffd Z%xZ&S)&TensorBoardLoggeraLog to local file system in `TensorBoard `_ format. Implemented using :class:`~tensorboardX.SummaryWriter`. Logs are saved to ``os.path.join(root_dir, name, version)``. This is the recommended logger in Lightning Fabric. Args: root_dir: The root directory in which all your experiments with different names and versions will be stored. name: Experiment name. Defaults to ``'lightning_logs'``. If it is the empty string then no per-experiment subdirectory is used. version: Experiment version. If version is not specified the logger inspects the save directory for existing versions, then automatically assigns the next available version. If it is a string then it is used as the run-specific subdirectory name, otherwise ``'version_${version}'`` is used. default_hp_metric: Enables a placeholder metric with key `hp_metric` when `log_hyperparams` is called without a metric (otherwise calls to ``log_hyperparams`` without a metric are ignored). prefix: A string to put at the beginning of all metric keys. sub_dir: Sub-directory to group TensorBoard logs. If a ``sub_dir`` argument is passed then logs are saved in ``/root_dir/name/version/sub_dir/``. Defaults to ``None`` in which case logs are saved in ``/root_dir/name/version/``. \**kwargs: Additional arguments used by :class:`tensorboardX.SummaryWriter` can be passed as keyword arguments in this logger. To automatically flush to disk, `max_queue` sets the size of the queue for pending logs before flushing. `flush_secs` determines how many seconds elapses before flushing. Example:: from lightning.fabric.loggers import TensorBoardLogger logger = TensorBoardLogger("path/to/logs/root", name="my_model") logger.log_hyperparams({"epochs": 5, "optimizer": "Adam"}) logger.log_metrics({"acc": 0.75}) logger.finalize("success") -Nroot_dirnameversiondefault_hp_metricprefixsub_dirkwargsc ts1ts+tdttdttt|t j|}||_|xsd|_ ||_ |dnt j||_ ||_ ||_ t||_d|_||_y)NzTNeither `tensorboard` nor `tensorboardX` is available. Try `pip install`ing either.  )_TENSORBOARD_AVAILABLE_TENSORBOARDX_AVAILABLEModuleNotFoundErrorstrsuper__init__osfspath _root_dir_name_version_sub_dir_default_hp_metric_prefixr_fs _experiment_kwargs) selfr r!r"r#r$r%r& __class__s y/home/mcse/projects/srt_converter/srt-converter-venv/lib/python3.12/site-packages/lightning/fabric/loggers/tensorboard.pyr/zTensorBoardLogger.__init__Rs&.E%g./037M3N2OQ  99X&!ZR  'RYYw5G "3 !(+48 returnc|jS)zcGet the name of the experiment. Returns: The name of the experiment. )r3r;s r=r!zTensorBoardLogger.nameoszzr>c\|j|j|_|jS)z~Get the experiment version. Returns: The experiment version if specified else the next version. )r4_get_next_versionrAs r=r"zTensorBoardLogger.versionzs( ==  224DM}}r>c|jS)zGets the save directory where the TensorBoard experiments are saved. 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