Fix the case where logger=None is passed to Trainer

pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py

@@ -88,13 +88,14 @@ def should_update_logs(self) -> bool:
         return should_log_every_n_steps or self.trainer.should_stop
 
     def configure_logger(self, logger: Union[bool, LightningLoggerBase, Iterable[LightningLoggerBase]]) -> None:
-        if isinstance(logger, bool):
+        if not logger:
+            # logger is None or logger is False
+            self.trainer.loggers = []
+        elif logger is True:
             # default logger
-            self.trainer.loggers = (
-                [TensorBoardLogger(save_dir=self.trainer.default_root_dir, version=SLURMEnvironment.job_id())]
-                if logger
-                else []
-            )
+            self.trainer.loggers = [
+                TensorBoardLogger(save_dir=self.trainer.default_root_dir, version=SLURMEnvironment.job_id())
+            ]
         elif isinstance(logger, Iterable):
             self.trainer.loggers = list(logger)
         else:

tests/loggers/test_all.py

@@ -365,6 +365,26 @@ def _test_logger_created_on_rank_zero_only(tmpdir, logger_class):
     assert trainer.state.finished, f"Training failed with {trainer.state}"
 
 
+@pytest.mark.parametrize(
+    "logger_value",
+    [
+        None,
+        False,
+        [],
+    ],
+)
+def test_no_logger(tmpdir, logger_value):
+    """Test the cases where logger=None, logger=False, logger=[] are passed to Trainer."""
+    trainer = Trainer(
+        logger=logger_value,
+        default_root_dir=tmpdir,
+        max_steps=1,
+    )
+    assert trainer.logger is None
+    assert trainer.loggers == []
+    assert trainer.log_dir == tmpdir
+
+
 def test_logger_with_prefix_all(tmpdir, monkeypatch):
     """Test that prefix is added at the beginning of the metric keys."""
     prefix = "tmp"