Fix trainer.logger deprecation message

pytorch_lightning/core/lightning.py

@@ -36,10 +36,10 @@
 from pytorch_lightning.core.mixins import DeviceDtypeModuleMixin, HyperparametersMixin
 from pytorch_lightning.core.optimizer import LightningOptimizer
 from pytorch_lightning.core.saving import ModelIO
-from pytorch_lightning.loggers import Logger
+from pytorch_lightning.loggers import Logger, LoggerCollection
 from pytorch_lightning.trainer.connectors.data_connector import _DataHookSelector
 from pytorch_lightning.trainer.connectors.logger_connector.fx_validator import _FxValidator
-from pytorch_lightning.utilities import _IS_WINDOWS, _TORCH_GREATER_EQUAL_1_10, GradClipAlgorithmType
+from pytorch_lightning.utilities import _IS_WINDOWS, _TORCH_GREATER_EQUAL_1_10, GradClipAlgorithmType, warnings
 from pytorch_lightning.utilities.apply_func import apply_to_collection, convert_to_tensors
 from pytorch_lightning.utilities.cloud_io import get_filesystem
 from pytorch_lightning.utilities.distributed import distributed_available, sync_ddp
@@ -245,7 +245,26 @@ def truncated_bptt_steps(self, truncated_bptt_steps: int) -> None:
     @property
     def logger(self) -> Optional[Logger]:
         """Reference to the logger object in the Trainer."""
-        return self.trainer.logger if self.trainer else None
+        # this should match the implementation of `trainer.logger`
+        # we don't reuse it so we can properly set the deprecation stacklevel
+        if self.trainer is None:
+            return
+        loggers = self.trainer.loggers
+        if len(loggers) == 0:
+            return None
+        if len(loggers) == 1:
+            return loggers[0]
+        else:
+            if not self._running_torchscript:
+                rank_zero_deprecation(
+                    "Using `lightning_module.logger` when multiple loggers are configured."
+                    " This behavior will change in v1.8 when `LoggerCollection` is removed, and"
+                    " `lightning_module.logger` will return the first logger available.",
+                    stacklevel=5,
+                )
+            with warnings.catch_warnings():
+                warnings.simplefilter("ignore")
+                return LoggerCollection(loggers)
 
     @property
     def loggers(self) -> List[Logger]:

pytorch_lightning/trainer/trainer.py

@@ -2622,19 +2622,21 @@ def _active_loop(self) -> Optional[Union[FitLoop, EvaluationLoop, PredictionLoop
 
     @property
     def logger(self) -> Optional[Logger]:
-        if len(self.loggers) == 0:
+        loggers = self.loggers
+        if len(loggers) == 0:
             return None
-        if len(self.loggers) == 1:
-            return self.loggers[0]
+        if len(loggers) == 1:
+            return loggers[0]
         else:
-            rank_zero_warn(
-                "Using trainer.logger when Trainer is configured to use multiple loggers."
-                " This behavior will change in v1.8 when LoggerCollection is removed, and"
-                " trainer.logger will return the first logger in trainer.loggers"
+            rank_zero_deprecation(
+                "Using `trainer.logger` when multiple loggers are configured."
+                " This behavior will change in v1.8 when `LoggerCollection` is removed, and"
+                " `trainer.logger` will return the first logger available.",
+                stacklevel=5,
             )
             with warnings.catch_warnings():
                 warnings.simplefilter("ignore")
-                return LoggerCollection(self.loggers)
+                return LoggerCollection(loggers)
 
     @logger.setter
     def logger(self, logger: Optional[Logger]) -> None:

tests/core/test_lightning_module.py

@@ -77,7 +77,7 @@ def test_property_logger(tmpdir):
     assert model.logger is None
 
     logger = TensorBoardLogger(tmpdir)
-    trainer = Mock(logger=logger)
+    trainer = Mock(loggers=[logger])
     model.trainer = trainer
     assert model.logger == logger
 

tests/deprecated_api/test_remove_1-8.py

@@ -758,10 +758,11 @@ def test_v1_8_0_logger_collection(tmpdir):
     trainer1.logger
     trainer1.loggers
     trainer2.loggers
-    trainer2.logger
 
+    with pytest.deprecated_call(match="logger` will return the first logger"):
+        _ = trainer2.logger
     with pytest.deprecated_call(match="`LoggerCollection` is deprecated in v1.6"):
-        LoggerCollection([logger1, logger2])
+        _ = LoggerCollection([logger1, logger2])
 
 
 def test_v1_8_0_precision_plugin_checkpoint_hooks(tmpdir):

tests/trainer/properties/test_loggers.py

@@ -61,7 +61,8 @@ def test_trainer_loggers_setters():
     assert trainer.loggers == [logger1]
 
     trainer.logger = logger_collection
-    assert trainer.logger._logger_iterable == logger_collection._logger_iterable
+    with pytest.deprecated_call(match="logger` when multiple loggers are configured"):
+        assert trainer.logger._logger_iterable == logger_collection._logger_iterable
     assert trainer.loggers == [logger1, logger2]
 
     # LoggerCollection of size 1 should result in trainer.logger becoming the contained logger.
@@ -76,7 +77,8 @@ def test_trainer_loggers_setters():
     # Test setters for trainer.loggers
     trainer.loggers = [logger1, logger2]
     assert trainer.loggers == [logger1, logger2]
-    assert trainer.logger._logger_iterable == logger_collection._logger_iterable
+    with pytest.deprecated_call(match="logger` when multiple loggers are configured"):
+        assert trainer.logger._logger_iterable == logger_collection._logger_iterable
 
     trainer.loggers = [logger1]
     assert trainer.loggers == [logger1]