feat(wandb): let wandb cli handle runs

CHANGELOG.md

@@ -37,6 +37,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Tuner algorithms will be skipped if `fast_dev_run=True` ([#3903](https://github.com/PyTorchLightning/pytorch-lightning/pull/3903))
 
+- WandbCallback does not force wandb `reinit` arg to True anymore and creates a run only when needed ([#4648](https://github.com/PyTorchLightning/pytorch-lightning/pull/4648))
+
 
 - Metric states are no longer as default added to `state_dict` ([#4685](https://github.com/PyTorchLightning/pytorch-lightning/pull/))
 

pytorch_lightning/loggers/wandb.py

@@ -58,6 +58,8 @@ class WandbLogger(LightningLoggerBase):
 
     Example::
 
+    .. code::
+
         from pytorch_lightning.loggers import WandbLogger
         from pytorch_lightning import Trainer
         wandb_logger = WandbLogger()
@@ -126,7 +128,7 @@ def experiment(self) -> Run:
                 os.environ['WANDB_MODE'] = 'dryrun'
             self._experiment = wandb.init(
                 name=self._name, dir=self._save_dir, project=self._project, anonymous=self._anonymous,
-                reinit=True, id=self._id, resume='allow', **self._kwargs)
+                id=self._id, resume='allow', **self._kwargs) if wandb.run is None else wandb.run
             # save checkpoints in wandb dir to upload on W&B servers
             if self._log_model:
                 self._save_dir = self._experiment.dir

tests/loggers/test_wandb.py

@@ -23,19 +23,27 @@
 
 
 @mock.patch('pytorch_lightning.loggers.wandb.wandb')
-def test_wandb_logger(wandb):
+def test_wandb_logger_init(wandb):
     """Verify that basic functionality of wandb logger works.
     Wandb doesn't work well with pytest so we have to mock it out here."""
-    logger = WandbLogger(anonymous=True, offline=True)
 
+    # test wandb.init called when there is no W&B run
+    wandb.run = None
+    logger = WandbLogger()
     logger.log_metrics({'acc': 1.0})
+    wandb.init.assert_called_once()
     wandb.init().log.assert_called_once_with({'acc': 1.0}, step=None)
 
+    # test wandb.init not called if there is a W&B run
     wandb.init().log.reset_mock()
+    wandb.init.reset_mock()
+    wandb.run = wandb.init()
+    logger = WandbLogger()
     logger.log_metrics({'acc': 1.0}, step=3)
+    wandb.init.assert_called_once()
     wandb.init().log.assert_called_once_with({'acc': 1.0}, step=3)
 
-    # continue training on same W&B run
+    # continue training on same W&B run and offset step
     wandb.init().step = 3
     logger.finalize('success')
     logger.log_metrics({'acc': 1.0}, step=3)
@@ -67,6 +75,7 @@ class Experiment:
         def project_name(self):
             return 'the_project_name'
 
+    wandb.run = None
     wandb.init.return_value = Experiment()
     logger = WandbLogger(id='the_id', offline=True)