LinghtningCLI now will not allow setting a class instance as a default (

#18822)

(cherry picked from commit c5a731c)

requirements/pytorch/extra.txt

@@ -5,7 +5,7 @@
 matplotlib>3.1, <3.9.0
 omegaconf >=2.0.5, <2.4.0
 hydra-core >=1.0.5, <1.4.0
-jsonargparse[signatures] >=4.18.0, <4.28.0
+jsonargparse[signatures] >=4.26.1, <4.28.0
 rich >=12.3.0, <13.6.0
 tensorboardX >=2.2, <2.7.0  # min version is set by torch.onnx missing attribute
 bitsandbytes <=0.41.1

src/lightning/pytorch/CHANGELOG.md

@@ -7,6 +7,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ## [2.1.3] - 2023-12-21
 
+### Changed
+
+- `LightningCLI` no longer allows setting a normal class instance as default. A `lazy_instance` can be used instead ([#18822](https://github.com/Lightning-AI/lightning/pull/18822))
+
 ### Fixed
 
 - Fixed checks for local file protocol due to fsspec changes in 2023.10.0 ([#19023](https://github.com/Lightning-AI/lightning/pull/19023))

src/lightning/pytorch/cli.py

@@ -30,7 +30,7 @@
 from lightning.pytorch.utilities.model_helpers import is_overridden
 from lightning.pytorch.utilities.rank_zero import rank_zero_warn
 
-_JSONARGPARSE_SIGNATURES_AVAILABLE = RequirementCache("jsonargparse[signatures]>=4.18.0")
+_JSONARGPARSE_SIGNATURES_AVAILABLE = RequirementCache("jsonargparse[signatures]>=4.26.1")
 
 if _JSONARGPARSE_SIGNATURES_AVAILABLE:
     import docstring_parser

tests/tests_pytorch/test_cli.py

@@ -60,6 +60,9 @@
 else:
     from argparse import Namespace
 
+    def lazy_instance(*args, **kwargs):
+        return None
+
 
 @contextmanager
 def mock_subclasses(baseclass, *subclasses):
@@ -173,7 +176,9 @@ def on_fit_start(self):
             self.trainer.ran_asserts = True
 
     with mock.patch("sys.argv", ["any.py", "fit", f"--trainer.callbacks={json.dumps(callbacks)}"]):
-        cli = LightningCLI(TestModel, trainer_defaults={"fast_dev_run": True, "logger": CSVLogger(".")})
+        cli = LightningCLI(
+            TestModel, trainer_defaults={"fast_dev_run": True, "logger": lazy_instance(CSVLogger, save_dir=".")}
+        )
 
     assert cli.trainer.ran_asserts
 
@@ -589,7 +594,7 @@ def on_fit_start(self):
 
 # mps not yet supported by distributed
 @RunIf(skip_windows=True, mps=False)
-@pytest.mark.parametrize("logger", [False, TensorBoardLogger(".")])
+@pytest.mark.parametrize("logger", [False, lazy_instance(TensorBoardLogger, save_dir=".")])
 @pytest.mark.parametrize("strategy", ["ddp_spawn", "ddp"])
 def test_cli_distributed_save_config_callback(cleandir, logger, strategy):
     from torch.multiprocessing import ProcessRaisedException