r""" .. _wandb: WandbLogger ------------- """ import argparse import os from typing import Optional, List, Dict try: import wandb from wandb.wandb_run import Run except ImportError: raise ImportError('You want to use `wandb` logger which is not installed yet,' ' please install it e.g. `pip install wandb`.') from .base import LightningLoggerBase, rank_zero_only class WandbLogger(LightningLoggerBase): """ Logger for `W&B `_. Args: name (str): display name for the run. save_dir (str): path where data is saved. offline (bool): run offline (data can be streamed later to wandb servers). id or version (str): sets the version, mainly used to resume a previous run. anonymous (bool): enables or explicitly disables anonymous logging. project (str): the name of the project to which this run will belong. tags (list of str): tags associated with this run. Example -------- .. code-block:: python from pytorch_lightning.loggers import WandbLogger from pytorch_lightning import Trainer wandb_logger = WandbLogger() trainer = Trainer(logger=wandb_logger) """ def __init__(self, name: Optional[str] = None, save_dir: Optional[str] = None, offline: bool = False, id: Optional[str] = None, anonymous: bool = False, version: Optional[str] = None, project: Optional[str] = None, tags: Optional[List[str]] = None, experiment=None, entity=None): super().__init__() self._name = name self._save_dir = save_dir self._anonymous = "allow" if anonymous else None self._id = version or id self._tags = tags self._project = project self._experiment = experiment self._offline = offline self._entity = entity def __getstate__(self): state = self.__dict__.copy() # cannot be pickled state['_experiment'] = None # args needed to reload correct experiment state['_id'] = self.experiment.id return state @property def experiment(self) -> Run: r""" Actual wandb object. To use wandb features do the following. Example:: self.logger.experiment.some_wandb_function() """ if self._experiment is None: if self._offline: os.environ["WANDB_MODE"] = "dryrun" self._experiment = wandb.init( name=self._name, dir=self._save_dir, project=self._project, anonymous=self._anonymous, id=self._id, resume="allow", tags=self._tags, entity=self._entity) return self._experiment def watch(self, model, log="gradients", log_freq=100): wandb.watch(model, log, log_freq) @rank_zero_only def log_hyperparams(self, params: argparse.Namespace): self.experiment.config.update(params) @rank_zero_only def log_metrics(self, metrics: Dict[str, float], step: Optional[int] = None): metrics["global_step"] = step self.experiment.log(metrics) def save(self): pass @rank_zero_only def finalize(self, status: str = 'success'): try: exit_code = 0 if status == 'success' else 1 wandb.join(exit_code) except TypeError: wandb.join() @property def name(self) -> str: return self.experiment.project_name() @property def version(self) -> str: return self.experiment.id