lightning/pytorch_lightning/loggers/wandb.py

113 lines
3.1 KiB
Python

r"""
.. _wandb:
WandbLogger
-------------
"""
import os
try:
import wandb
except ImportError:
raise ImportError('Missing wandb package.')
from .base import LightningLoggerBase, rank_zero_only
class WandbLogger(LightningLoggerBase):
"""
Logger for `W&B <https://www.wandb.com/>`_.
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=None, save_dir=None, offline=False, id=None, anonymous=False,
version=None, project=None, tags=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):
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):
self.experiment.config.update(params)
@rank_zero_only
def log_metrics(self, metrics, step=None):
metrics["global_step"] = step
self.experiment.log(metrics)
def save(self):
pass
@rank_zero_only
def finalize(self, status='success'):
try:
exit_code = 0 if status == 'success' else 1
wandb.join(exit_code)
except TypeError:
wandb.join()
@property
def name(self):
return self.experiment.project_name()
@property
def version(self):
return self.experiment.id