Deprecate LoggerCollection in favor of trainer.loggers

CHANGELOG.md

@@ -445,6 +445,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated `BaseProfiler.profile_iterable` ([#12102](https://github.com/PyTorchLightning/pytorch-lightning/pull/12102))
 
 
+- Deprecated `LoggerCollection` in favor of `trainer.loggers` ([#12147](https://github.com/PyTorchLightning/pytorch-lightning/pull/12147))
+
+
 ### Removed
 
 - Removed deprecated parameter `method` in `pytorch_lightning.utilities.model_helpers.is_overridden` ([#10507](https://github.com/PyTorchLightning/pytorch-lightning/pull/10507))

pytorch_lightning/trainer/trainer.py

@@ -2599,10 +2599,11 @@ def logger(self) -> Optional[LightningLoggerBase]:
         if len(self.loggers) == 1:
             return self.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 Trainer is configured to use multiple loggers."
+                " `LoggerCollection` is deprecated in v1.6 in favor of `trainer.loggers` and will be removed in v1.8."
+                " This behavior will change in v1.8 such that `trainer.logger` will return the first"
+                " logger in `trainer.loggers`."
             )
             return LoggerCollection(self.loggers)
 

tests/deprecated_api/test_remove_1-8.py

@@ -652,3 +652,24 @@ def _get_python_cprofile_total_duration(profile):
     recorded_total_duration = _get_python_cprofile_total_duration(advanced_profiler.profiled_actions[action])
     expected_total_duration = np.sum(expected)
     np.testing.assert_allclose(recorded_total_duration, expected_total_duration, rtol=0.2)
+
+
+def test_v1_8_0_logger_collection(tmpdir):
+    logger1 = CSVLogger(tmpdir)
+    logger2 = CSVLogger(tmpdir)
+
+    trainer1 = Trainer(logger=logger1)
+    trainer2 = Trainer(logger=[logger1, logger2])
+
+    # Should have no deprecation warning
+    trainer1.logger
+    trainer1.loggers
+    trainer2.loggers
+
+    with pytest.deprecated_call(
+        match="Using `trainer.logger` when Trainer is configured to use multiple loggers."
+        " `LoggerCollection` is deprecated in v1.6 in favor of `trainer.loggers` and will be removed in v1.8."
+        " This behavior will change in v1.8 such that `trainer.logger` will return the first"
+        " logger in `trainer.loggers`."
+    ):
+        trainer2.logger

tests/profiler/test_profiler.py

@@ -24,7 +24,7 @@
 
 from pytorch_lightning import Callback, Trainer
 from pytorch_lightning.callbacks import EarlyStopping, StochasticWeightAveraging
-from pytorch_lightning.loggers import CSVLogger, LoggerCollection, TensorBoardLogger
+from pytorch_lightning.loggers import CSVLogger, TensorBoardLogger
 from pytorch_lightning.profiler import AdvancedProfiler, PassThroughProfiler, PyTorchProfiler, SimpleProfiler
 from pytorch_lightning.profiler.pytorch import RegisterRecordFunction, warning_cache
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
@@ -450,9 +450,9 @@ def test_pytorch_profiler_nested(tmpdir):
     assert events_name == expected, (events_name, torch.__version__, platform.system())
 
 
-def test_pytorch_profiler_logger_collection(tmpdir):
-    """Tests whether the PyTorch profiler is able to write its trace locally when the Trainer's logger is an
-    instance of LoggerCollection.
+def test_pytorch_profiler_multiple_loggers(tmpdir):
+    """Tests whether the PyTorch profiler is able to write its trace locally when the Trainer is configured with
+    multiple loggers.
 
     See issue #8157.
     """
@@ -466,9 +466,9 @@ def look_for_trace(trace_dir):
 
     model = BoringModel()
     # Wrap the logger in a list so it becomes a LoggerCollection
-    logger = [TensorBoardLogger(save_dir=tmpdir), CSVLogger(tmpdir)]
-    trainer = Trainer(default_root_dir=tmpdir, profiler="pytorch", logger=logger, limit_train_batches=5, max_epochs=1)
-    assert isinstance(trainer.logger, LoggerCollection)
+    loggers = [TensorBoardLogger(save_dir=tmpdir), CSVLogger(tmpdir)]
+    trainer = Trainer(default_root_dir=tmpdir, profiler="pytorch", logger=loggers, limit_train_batches=5, max_epochs=1)
+    assert len(trainer.loggers) == 2
     trainer.fit(model)
     assert look_for_trace(tmpdir)
 

tests/trainer/properties/test_log_dir.py

@@ -15,7 +15,7 @@
 
 from pytorch_lightning import Trainer
 from pytorch_lightning.callbacks import ModelCheckpoint
-from pytorch_lightning.loggers import CSVLogger, LoggerCollection, TensorBoardLogger
+from pytorch_lightning.loggers import CSVLogger, TensorBoardLogger
 from tests.helpers.boring_model import BoringModel
 
 
@@ -109,8 +109,8 @@ def test_logdir_custom_logger(tmpdir):
     assert trainer.log_dir == expected
 
 
-def test_logdir_logger_collection(tmpdir):
-    """Tests that the logdir equals the default_root_dir when the logger is a LoggerCollection."""
+def test_logdir_multiple_loggers(tmpdir):
+    """Tests that the logdir equals the default_root_dir when trainer has multiple loggers."""
     default_root_dir = tmpdir / "default_root_dir"
     save_dir = tmpdir / "save_dir"
     model = TestModel(default_root_dir)
@@ -119,7 +119,6 @@ def test_logdir_logger_collection(tmpdir):
         max_steps=2,
         logger=[TensorBoardLogger(save_dir=save_dir, name="custom_logs"), CSVLogger(tmpdir)],
     )
-    assert isinstance(trainer.logger, LoggerCollection)
     assert trainer.log_dir == default_root_dir
 
     trainer.fit(model)

tests/trainer/properties/test_loggers.py

@@ -12,6 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import pytest
+
 from pytorch_lightning import Trainer
 from pytorch_lightning.loggers import LoggerCollection, TensorBoardLogger
 from tests.loggers.test_base import CustomLogger
@@ -52,6 +54,10 @@ def test_trainer_loggers_setters():
     logger2 = CustomLogger()
     logger_collection = LoggerCollection([logger1, logger2])
     logger_collection_2 = LoggerCollection([logger2])
+    logger_collection_dep = "Using `trainer.logger` when Trainer is configured to use multiple loggers."
+    " `LoggerCollection` is deprecated in v1.6 in favor of `trainer.loggers` and will be removed in v1.8."
+    " This behavior will change in v1.8 such that `trainer.logger` will return the first"
+    " logger in `trainer.loggers`."
 
     trainer = Trainer()
     assert type(trainer.logger) == TensorBoardLogger
@@ -63,7 +69,8 @@ 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_collection_dep):
+        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.
@@ -78,7 +85,8 @@ 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_collection_dep):
+        assert trainer.logger._logger_iterable == logger_collection._logger_iterable
 
     trainer.loggers = [logger1]
     assert trainer.loggers == [logger1]