update on comments

pytorch_lightning/utilities/cli.py

@@ -379,11 +379,13 @@ def link_optimizers_and_lr_schedulers(self) -> None:
         if any(
             True for v in sys.argv for optim_name in OPTIMIZER_REGISTRIES.keys() if f"--optimizer={optim_name}" in v
         ):
-            self.parser.add_optimizer_args(self.optimizer_registered)
+            if "optimizer" not in self.parser.groups:
+                self.parser.add_optimizer_args(self.optimizer_registered)
 
-        if any(True for v in sys.argv for sch_name in SCHEDULER_REGISTRIES.keys() if f"-lr_scheduler={sch_name}" in v):
+        if any(True for v in sys.argv for sch_name in SCHEDULER_REGISTRIES.keys() if f"--lr_scheduler={sch_name}" in v):
             lr_schdulers = tuple(v for v in SCHEDULER_REGISTRIES.values())
-            self.parser.add_lr_scheduler_args(lr_schdulers)
+            if "lr_scheduler" not in self.parser.groups:
+                self.parser.add_lr_scheduler_args(lr_schdulers)
 
         for key, (class_type, link_to) in self.parser.optimizers_and_lr_schedulers.items():
             if link_to == "AUTOMATIC":
@@ -471,10 +473,12 @@ def prepare_class_list_from_registry(self, pattern: str, registry: Registry):
 
     def parse_arguments(self, parser: LightningArgumentParser) -> None:
         """Parses command line arguments and stores it in ``self.config``."""
-        with self.prepare_from_registry(OPTIMIZER_REGISTRIES), self.prepare_from_registry(
-            SCHEDULER_REGISTRIES
-        ), self.prepare_class_list_from_registry("--trainer.callbacks", CALLBACK_REGISTRIES):
+        # fmt: off
+        with self.prepare_from_registry(OPTIMIZER_REGISTRIES), \
+             self.prepare_from_registry(SCHEDULER_REGISTRIES), \
+             self.prepare_class_list_from_registry("--trainer.callbacks", CALLBACK_REGISTRIES):
             self.config = parser.parse_args()
+        # fmt: on
 
     def before_instantiate_classes(self) -> None:
         """Implement to run some code before instantiating the classes."""

tests/utilities/test_cli.py

@@ -663,9 +663,9 @@ def add_arguments_to_parser(self, parser):
 def test_lightning_cli_optimizers_and_lr_scheduler_with_link_to(tmpdir):
     class MyLightningCLI(LightningCLI):
         def add_arguments_to_parser(self, parser):
-            parser.add_optimizer_args(torch.optim.Adam, nested_key="optim1", link_to="model.optim1")
-            parser.add_optimizer_args((torch.optim.ASGD, torch.optim.SGD), nested_key="optim2", link_to="model.optim2")
-            parser.add_lr_scheduler_args(torch.optim.lr_scheduler.ExponentialLR, link_to="model.scheduler")
+            parser.add_optimizer_args(self.optimizer_registered, nested_key="optim1", link_to="model.optim1")
+            parser.add_optimizer_args(torch.optim.SGD, nested_key="optim2", link_to="model.optim2")
+            parser.add_lr_scheduler_args(self.lr_scheduler_registered, link_to="model.scheduler")
 
     class TestModel(BoringModel):
         def __init__(self, optim1: dict, optim2: dict, scheduler: dict):
@@ -677,9 +677,11 @@ def __init__(self, optim1: dict, optim2: dict, scheduler: dict):
     cli_args = [
         f"--trainer.default_root_dir={tmpdir}",
         "--trainer.max_epochs=1",
-        "--optim2.class_path=torch.optim.SGD",
-        "--optim2.init_args.lr=0.01",
-        "--lr_scheduler.gamma=0.2",
+        "--optim1=Adam",
+        "--optim1.weight_decay=0.001",
+        "--optim2.lr=0.005",
+        "--lr_scheduler=ExponentialLR",
+        "--lr_scheduler.gamma=0.1",
     ]
 
     with mock.patch("sys.argv", ["any.py"] + cli_args):