Add warning when wandb.run already exists

CHANGELOG.md

@@ -24,6 +24,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Added DeepSpeed collate checkpoint utility function ([#8701](https://github.com/PyTorchLightning/pytorch-lightning/pull/8701))
 
 
+- Added a warning to `WandbLogger` when reusing a wandb run ([#8714](https://github.com/PyTorchLightning/pytorch-lightning/pull/8714))
+
+
 - Added `log_graph` argument for `watch` method of `WandbLogger` ([#8662](https://github.com/PyTorchLightning/pytorch-lightning/pull/8662))
 
 

pytorch_lightning/loggers/wandb.py

@@ -183,7 +183,14 @@ def experiment(self) -> Run:
         if self._experiment is None:
             if self._offline:
                 os.environ["WANDB_MODE"] = "dryrun"
-            self._experiment = wandb.init(**self._wandb_init) if wandb.run is None else wandb.run
+            if wandb.run is None:
+                self._experiment = wandb.init(**self._wandb_init)
+            else:
+                warning_cache.warn(
+                    "There is a wandb run already in progress and newly created instances of `WandbLogger` will reuse"
+                    " this run. If this is not desired, call `wandb.finish()` before instantiating `WandbLogger`."
+                )
+                self._experiment = wandb.run
 
         # define default x-axis (for latest wandb versions)
         if getattr(self._experiment, "define_metric", None):

tests/loggers/test_wandb.py

@@ -18,6 +18,7 @@
 
 import pytest
 
+import pytorch_lightning
 from pytorch_lightning import Trainer
 from pytorch_lightning.loggers import WandbLogger
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
@@ -51,8 +52,13 @@ def test_wandb_logger_init(wandb):
     wandb.init.reset_mock()
     wandb.run = wandb.init()
     logger = WandbLogger()
+
     # verify default resume value
     assert logger._wandb_init["resume"] == "allow"
+
+    _ = logger.experiment
+    assert any("There is a wandb run already in progress" in w for w in pytorch_lightning.loggers.wandb.warning_cache)
+
     logger.log_metrics({"acc": 1.0}, step=3)
     wandb.init.assert_called_once()
     wandb.init().log.assert_called_once_with({"acc": 1.0, "trainer/global_step": 3})