feat(wandb): offset logging step when resuming

pytorch_lightning/loggers/wandb.py

@@ -31,6 +31,7 @@
 
 from pytorch_lightning.loggers.base import LightningLoggerBase, rank_zero_experiment
 from pytorch_lightning.utilities import rank_zero_only
+from pytorch_lightning.utilities.warning_utils import WarningCache
 
 
 class WandbLogger(LightningLoggerBase):
@@ -66,6 +67,9 @@ class WandbLogger(LightningLoggerBase):
         wandb_logger = WandbLogger()
         trainer = Trainer(logger=wandb_logger)
 
+    Note: When logging manually through `wandb.log` or `trainer.logger.experiment.log`,
+    make sure to use `commit=False` so the logging step does not increase.
+
     See Also:
         - `Tutorial <https://app.wandb.ai/cayush/pytorchlightning/reports/
           Use-Pytorch-Lightning-with-Weights-%26-Biases--Vmlldzo2NjQ1Mw>`__
@@ -103,8 +107,9 @@ def __init__(
         self._log_model = log_model
         self._prefix = prefix
         self._kwargs = kwargs
-        # logging multiple Trainer on a single W&B run (k-fold, etc)
+        # logging multiple Trainer on a single W&B run (k-fold, resuming, etc)
         self._step_offset = 0
+        self.warning_cache = WarningCache()
 
     def __getstate__(self):
         state = self.__dict__.copy()
@@ -134,6 +139,8 @@ def experiment(self) -> Run:
             self._experiment = wandb.init(
                 name=self._name, dir=self._save_dir, project=self._project, anonymous=self._anonymous,
                 id=self._id, resume='allow', **self._kwargs) if wandb.run is None else wandb.run
+            # offset logging step when resuming a run
+            self._step_offset = self._experiment.step
             # save checkpoints in wandb dir to upload on W&B servers
             if self._log_model:
                 self._save_dir = self._experiment.dir
@@ -154,6 +161,8 @@ def log_metrics(self, metrics: Dict[str, float], step: Optional[int] = None) ->
         assert rank_zero_only.rank == 0, 'experiment tried to log from global_rank != 0'
 
         metrics = self._add_prefix(metrics)
+        if step is not None and step + self._step_offset < self.experiment.step:
+            self.warning_cache.warn('Trying to log at a previous step. Use `commit=False` when logging metrics manually.')
         self.experiment.log(metrics, step=(step + self._step_offset) if step is not None else None)
 
     @property

tests/loggers/test_all.py

@@ -74,7 +74,9 @@ def test_loggers_fit_test_all(tmpdir, monkeypatch):
     with mock.patch('pytorch_lightning.loggers.test_tube.Experiment'):
         _test_loggers_fit_test(tmpdir, TestTubeLogger)
 
-    with mock.patch('pytorch_lightning.loggers.wandb.wandb'):
+    with mock.patch('pytorch_lightning.loggers.wandb.wandb') as wandb:
+        wandb.run = None
+        wandb.init().step = 0
         _test_loggers_fit_test(tmpdir, WandbLogger)
 
 
@@ -368,5 +370,7 @@ def test_logger_with_prefix_all(tmpdir, monkeypatch):
     # WandB
     with mock.patch('pytorch_lightning.loggers.wandb.wandb') as wandb:
         logger = _instantiate_logger(WandbLogger, save_idr=tmpdir, prefix=prefix)
+        wandb.run = None
+        wandb.init().step = 0
         logger.log_metrics({"test": 1.0}, step=0)
         logger.experiment.log.assert_called_once_with({'tmp-test': 1.0}, step=0)

tests/loggers/test_wandb.py

@@ -22,8 +22,14 @@
 from tests.base import EvalModelTemplate, BoringModel
 
 
+def get_warnings(recwarn):
+    warnings_text = '\n'.join(str(w.message) for w in recwarn.list)
+    recwarn.clear()
+    return warnings_text
+
+
 @mock.patch('pytorch_lightning.loggers.wandb.wandb')
-def test_wandb_logger_init(wandb):
+def test_wandb_logger_init(wandb, recwarn):
     """Verify that basic functionality of wandb logger works.
     Wandb doesn't work well with pytest so we have to mock it out here."""
 
@@ -34,6 +40,9 @@ def test_wandb_logger_init(wandb):
     wandb.init.assert_called_once()
     wandb.init().log.assert_called_once_with({'acc': 1.0}, step=None)
 
+    # mock wandb step
+    wandb.init().step = 0
+
     # test wandb.init not called if there is a W&B run
     wandb.init().log.reset_mock()
     wandb.init.reset_mock()
@@ -49,15 +58,28 @@ def test_wandb_logger_init(wandb):
     logger.log_metrics({'acc': 1.0}, step=3)
     wandb.init().log.assert_called_with({'acc': 1.0}, step=6)
 
+    # log hyper parameters
     logger.log_hyperparams({'test': None, 'nested': {'a': 1}, 'b': [2, 3, 4]})
     wandb.init().config.update.assert_called_once_with(
         {'test': 'None', 'nested/a': 1, 'b': [2, 3, 4]},
         allow_val_change=True,
     )
 
+    # watch a model
     logger.watch('model', 'log', 10)
     wandb.init().watch.assert_called_once_with('model', log='log', log_freq=10)
 
+    # verify warning for logging at a previous step
+    assert 'Trying to log at a previous step' not in get_warnings(recwarn)
+    # current step from wandb should be 6 (last logged step)
+    logger.experiment.step = 6
+    # logging at step 2 should raise a warning (step_offset is still 3)
+    logger.log_metrics({'acc': 1.0}, step=2)
+    assert 'Trying to log at a previous step' in get_warnings(recwarn)
+    # logging again at step 2 should not display again the same warning
+    logger.log_metrics({'acc': 1.0}, step=2)
+    assert 'Trying to log at a previous step' not in get_warnings(recwarn)
+
     assert logger.name == wandb.init().project_name()
     assert logger.version == wandb.init().id
 
@@ -71,6 +93,7 @@ def test_wandb_pickle(wandb, tmpdir):
     class Experiment:
         """ """
         id = 'the_id'
+        step = 0
 
         def project_name(self):
             return 'the_project_name'
@@ -108,8 +131,11 @@ def test_wandb_logger_dirs_creation(wandb, tmpdir):
     assert logger.name is None
 
     # mock return values of experiment
+    wandb.run = None
+    wandb.init().step = 0
     logger.experiment.id = '1'
     logger.experiment.project_name.return_value = 'project'
+    logger.experiment.step = 0
 
     for _ in range(2):
         _ = logger.experiment