feat(wandb): log in sync with Trainer step

CHANGELOG.md

@@ -45,6 +45,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Fixed santized parameters for `WandbLogger.log_hyperparams` ([#4320](https://github.com/PyTorchLightning/pytorch-lightning/pull/4320))
 
 
+- W&B log in sync with Trainer step ([#4405](https://github.com/PyTorchLightning/pytorch-lightning/pull/4405))
+
+
 ### Deprecated
 
 

pytorch_lightning/loggers/wandb.py

@@ -94,6 +94,8 @@ def __init__(
         self._offline = offline
         self._log_model = log_model
         self._kwargs = kwargs
+        # logging multiple Trainer on a single W&B run (k-fold, etc)
+        self._step_offset = 0
 
     def __getstate__(self):
         state = self.__dict__.copy()
@@ -141,8 +143,7 @@ def log_hyperparams(self, params: Union[Dict[str, Any], Namespace]) -> None:
     @rank_zero_only
     def log_metrics(self, metrics: Dict[str, float], step: Optional[int] = None) -> None:
         assert rank_zero_only.rank == 0, 'experiment tried to log from global_rank != 0'
-
-        self.experiment.log({'global_step': step, **metrics} if step is not None else metrics)
+        self.experiment.log(metrics, step=(step + self._step_offset) if step is not None else None)
 
     @property
     def save_dir(self) -> Optional[str]:
@@ -159,6 +160,10 @@ def version(self) -> Optional[str]:
         return self._experiment.id if self._experiment else self._id
 
     def finalize(self, status: str) -> None:
+        # offset future training logged on same W&B run
+        if self._experiment is not None:
+            self._step_offset = self._experiment.step
+
         # upload all checkpoints from saving dir
         if self._log_model:
             wandb.save(os.path.join(self.save_dir, "*.ckpt"))

tests/loggers/test_wandb.py

@@ -29,11 +29,17 @@ def test_wandb_logger(wandb):
     logger = WandbLogger(anonymous=True, offline=True)
 
     logger.log_metrics({'acc': 1.0})
-    wandb.init().log.assert_called_once_with({'acc': 1.0})
+    wandb.init().log.assert_called_once_with({'acc': 1.0}, step=None)
 
     wandb.init().log.reset_mock()
     logger.log_metrics({'acc': 1.0}, step=3)
-    wandb.init().log.assert_called_once_with({'global_step': 3, 'acc': 1.0})
+    wandb.init().log.assert_called_once_with({'acc': 1.0}, step=3)
+
+    # continue training on same W&B run
+    wandb.init().step = 3
+    logger.finalize('success')
+    logger.log_metrics({'acc': 1.0}, step=3)
+    wandb.init().log.assert_called_with({'acc': 1.0}, step=6)
 
     logger.log_hyperparams({'test': None, 'nested': {'a': 1}, 'b': [2, 3, 4]})
     wandb.init().config.update.assert_called_once_with(