Deprecate lr_sch_names from LearningRateMonitor

CHANGELOG.md

@@ -445,10 +445,12 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated `ClusterEnvironment.creates_children()` in favor of `ClusterEnvironment.creates_processes_externally` (property) ([#10106](https://github.com/PyTorchLightning/pytorch-lightning/pull/10106))
 
 
-
 - Deprecated `PrecisionPlugin.master_params()` in favor of `PrecisionPlugin.main_params()` ([#10105](https://github.com/PyTorchLightning/pytorch-lightning/pull/10105))
 
 
+- Deprecated `lr_sch_names` from `LearningRateMonitor` ([#10066](https://github.com/PyTorchLightning/pytorch-lightning/pull/10066))
+
+
 ### Removed
 
 - Removed deprecated `metrics` ([#8586](https://github.com/PyTorchLightning/pytorch-lightning/pull/8586/))

pytorch_lightning/callbacks/lr_monitor.py

@@ -28,6 +28,7 @@
 import pytorch_lightning as pl
 from pytorch_lightning.callbacks.base import Callback
 from pytorch_lightning.utilities import rank_zero_warn
+from pytorch_lightning.utilities.distributed import rank_zero_deprecation
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
 
@@ -93,7 +94,7 @@ def __init__(self, logging_interval: Optional[str] = None, log_momentum: bool =
         self.logging_interval = logging_interval
         self.log_momentum = log_momentum
         self.lrs: Dict[str, List[float]] = {}
-        self.lr_sch_names: List[str] = []
+        self._lr_sch_names: List[str] = []
 
     def on_train_start(self, trainer: "pl.Trainer", *args: Any, **kwargs: Any) -> None:
         """Called before training, determines unique names for all lr schedulers in the case of multiple of the
@@ -334,6 +335,16 @@ def _check_duplicates_and_update_name(
         name_list = [self._add_suffix(name, param_groups, i) for i in range(len(param_groups))]
 
         if add_lr_sch_names:
-            self.lr_sch_names.append(name)
+            self._lr_sch_names.append(name)
 
         return name_list
+
+    @property
+    def lr_sch_names(self) -> List[str]:
+        # TODO remove `lr_sch_names` and `add_lr_sch_names` argument in v1.7.0
+        rank_zero_deprecation(
+            "`LearningRateMonitor.lr_sch_names` has been deprecated in v1.5 and will be removed in 1.7."
+            " Consider accessing them using `LearningRateMonitor.lrs.keys()` which will return"
+            " the names of all the optimizers, even those without a scheduler."
+        )
+        return self._lr_sch_names

tests/callbacks/test_lr_monitor.py

@@ -41,7 +41,7 @@ def test_lr_monitor_single_lr(tmpdir):
     assert lr_monitor.lrs, "No learning rates logged"
     assert all(v is None for v in lr_monitor.last_momentum_values.values()), "Momentum should not be logged by default"
     assert len(lr_monitor.lrs) == len(trainer.lr_schedulers)
-    assert lr_monitor.lr_sch_names == list(lr_monitor.lrs.keys()) == ["lr-SGD"]
+    assert list(lr_monitor.lrs) == ["lr-SGD"]
 
 
 @pytest.mark.parametrize("opt", ["SGD", "Adam"])
@@ -77,7 +77,7 @@ def configure_optimizers(self):
 
     assert all(v is not None for v in lr_monitor.last_momentum_values.values()), "Expected momentum to be logged"
     assert len(lr_monitor.last_momentum_values) == len(trainer.lr_schedulers)
-    assert all(k == f"lr-{opt}-momentum" for k in lr_monitor.last_momentum_values.keys())
+    assert all(k == f"lr-{opt}-momentum" for k in lr_monitor.last_momentum_values)
 
 
 def test_log_momentum_no_momentum_optimizer(tmpdir):
@@ -104,7 +104,7 @@ def configure_optimizers(self):
 
     assert all(v == 0 for v in lr_monitor.last_momentum_values.values()), "Expected momentum to be logged"
     assert len(lr_monitor.last_momentum_values) == len(trainer.lr_schedulers)
-    assert all(k == "lr-ASGD-momentum" for k in lr_monitor.last_momentum_values.keys())
+    assert all(k == "lr-ASGD-momentum" for k in lr_monitor.last_momentum_values)
 
 
 def test_lr_monitor_no_lr_scheduler_single_lr(tmpdir):
@@ -127,7 +127,7 @@ def configure_optimizers(self):
 
     assert lr_monitor.lrs, "No learning rates logged"
     assert len(lr_monitor.lrs) == len(trainer.optimizers)
-    assert lr_monitor.lr_sch_names == ["lr-SGD"]
+    assert list(lr_monitor.lrs) == ["lr-SGD"]
 
 
 @pytest.mark.parametrize("opt", ["SGD", "Adam"])
@@ -162,7 +162,7 @@ def configure_optimizers(self):
 
     assert all(v is not None for v in lr_monitor.last_momentum_values.values()), "Expected momentum to be logged"
     assert len(lr_monitor.last_momentum_values) == len(trainer.optimizers)
-    assert all(k == f"lr-{opt}-momentum" for k in lr_monitor.last_momentum_values.keys())
+    assert all(k == f"lr-{opt}-momentum" for k in lr_monitor.last_momentum_values)
 
 
 def test_log_momentum_no_momentum_optimizer_no_lr_scheduler(tmpdir):
@@ -188,7 +188,7 @@ def configure_optimizers(self):
 
     assert all(v == 0 for v in lr_monitor.last_momentum_values.values()), "Expected momentum to be logged"
     assert len(lr_monitor.last_momentum_values) == len(trainer.optimizers)
-    assert all(k == "lr-ASGD-momentum" for k in lr_monitor.last_momentum_values.keys())
+    assert all(k == "lr-ASGD-momentum" for k in lr_monitor.last_momentum_values)
 
 
 def test_lr_monitor_no_logger(tmpdir):
@@ -238,7 +238,7 @@ def configure_optimizers(self):
 
     assert lr_monitor.lrs, "No learning rates logged"
     assert len(lr_monitor.lrs) == len(trainer.lr_schedulers)
-    assert lr_monitor.lr_sch_names == ["lr-Adam", "lr-Adam-1"], "Names of learning rates not set correctly"
+    assert list(lr_monitor.lrs) == ["lr-Adam", "lr-Adam-1"], "Names of learning rates not set correctly"
 
     if logging_interval == "step":
         expected_number_logged = trainer.global_step // log_every_n_steps
@@ -281,7 +281,7 @@ def configure_optimizers(self):
 
     assert lr_monitor.lrs, "No learning rates logged"
     assert len(lr_monitor.lrs) == len(trainer.optimizers)
-    assert lr_monitor.lr_sch_names == ["lr-Adam", "lr-Adam-1"], "Names of learning rates not set correctly"
+    assert list(lr_monitor.lrs) == ["lr-Adam", "lr-Adam-1"], "Names of learning rates not set correctly"
 
     if logging_interval == "step":
         expected_number_logged = trainer.global_step // log_every_n_steps
@@ -317,8 +317,7 @@ def configure_optimizers(self):
 
     assert lr_monitor.lrs, "No learning rates logged"
     assert len(lr_monitor.lrs) == 2 * len(trainer.lr_schedulers)
-    assert lr_monitor.lr_sch_names == ["lr-Adam"]
-    assert list(lr_monitor.lrs.keys()) == ["lr-Adam/pg1", "lr-Adam/pg2"], "Names of learning rates not set correctly"
+    assert list(lr_monitor.lrs) == ["lr-Adam/pg1", "lr-Adam/pg2"], "Names of learning rates not set correctly"
 
 
 def test_lr_monitor_custom_name(tmpdir):
@@ -339,7 +338,7 @@ def configure_optimizers(self):
         enable_model_summary=False,
     )
     trainer.fit(TestModel())
-    assert lr_monitor.lr_sch_names == list(lr_monitor.lrs.keys()) == ["my_logging_name"]
+    assert list(lr_monitor.lrs) == ["my_logging_name"]
 
 
 def test_lr_monitor_custom_pg_name(tmpdir):
@@ -360,7 +359,6 @@ def configure_optimizers(self):
         enable_model_summary=False,
     )
     trainer.fit(TestModel())
-    assert lr_monitor.lr_sch_names == ["lr-SGD"]
     assert list(lr_monitor.lrs) == ["lr-SGD/linear"]
 
 
@@ -434,7 +432,7 @@ def configure_optimizers(self):
     class Check(Callback):
         def on_train_epoch_start(self, trainer, pl_module) -> None:
             num_param_groups = sum(len(opt.param_groups) for opt in trainer.optimizers)
-            assert lr_monitor.lr_sch_names == ["lr-Adam", "lr-Adam-1", "lr-Adam-2"]
+
             if trainer.current_epoch == 0:
                 assert num_param_groups == 3
             elif trainer.current_epoch == 1:
@@ -512,7 +510,10 @@ def finetune_function(self, pl_module, epoch: int, optimizer, opt_idx: int):
     assert lr_monitor.lrs["lr-Adam-1/pg3"] == expected
 
 
-def test_lr_monitor_multiple_param_groups_no_scheduler(tmpdir):
+def test_lr_monitor_multiple_param_groups_no_lr_scheduler(tmpdir):
+    """Test that the `LearningRateMonitor` is able to log correct keys with multiple param groups and no
+    lr_scheduler."""
+
     class TestModel(BoringModel):
         def __init__(self, lr, momentum):
             super().__init__()
@@ -550,8 +551,7 @@ def configure_optimizers(self):
     trainer.fit(model)
 
     assert len(lr_monitor.lrs) == len(trainer.optimizers[0].param_groups)
-    assert list(lr_monitor.lrs.keys()) == ["lr-Adam/pg1", "lr-Adam/pg2"]
-    assert lr_monitor.lr_sch_names == ["lr-Adam"]
-    assert list(lr_monitor.last_momentum_values.keys()) == ["lr-Adam/pg1-momentum", "lr-Adam/pg2-momentum"]
+    assert list(lr_monitor.lrs) == ["lr-Adam/pg1", "lr-Adam/pg2"]
+    assert list(lr_monitor.last_momentum_values) == ["lr-Adam/pg1-momentum", "lr-Adam/pg2-momentum"]
     assert all(val == momentum for val in lr_monitor.last_momentum_values.values())
     assert all(all(val == lr for val in lr_monitor.lrs[lr_key]) for lr_key in lr_monitor.lrs)

tests/deprecated_api/test_remove_1-7.py

@@ -19,6 +19,7 @@
 
 from pytorch_lightning import Callback, LightningDataModule, Trainer
 from pytorch_lightning.callbacks.gpu_stats_monitor import GPUStatsMonitor
+from pytorch_lightning.callbacks.lr_monitor import LearningRateMonitor
 from pytorch_lightning.callbacks.xla_stats_monitor import XLAStatsMonitor
 from pytorch_lightning.loggers import LoggerCollection, TestTubeLogger
 from tests.callbacks.test_callbacks import OldStatefulCallback
@@ -438,3 +439,13 @@ def test_v1_7_0_resume_from_checkpoint_trainer_constructor(tmpdir):
     trainer = Trainer(resume_from_checkpoint="trainer_arg_path")
     with pytest.raises(FileNotFoundError, match="Checkpoint at fit_arg_ckpt_path not found. Aborting training."):
         trainer.fit(model, ckpt_path="fit_arg_ckpt_path")
+
+
+def test_v1_7_0_deprecate_lr_sch_names(tmpdir):
+    model = BoringModel()
+    lr_monitor = LearningRateMonitor()
+    trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=True, callbacks=[lr_monitor])
+    trainer.fit(model)
+
+    with pytest.deprecated_call(match="`LearningRateMonitor.lr_sch_names` has been deprecated in v1.5"):
+        assert lr_monitor.lr_sch_names == ["lr-SGD"]