Update LightningCLI test for new support in latest release of jsonargparse

requirements/pytorch/extra.txt

@@ -3,6 +3,6 @@ matplotlib>3.1, <3.5.3
 torchtext>=0.10.*, <=0.12.0
 omegaconf>=2.0.5, <2.3.0
 hydra-core>=1.0.5, <1.3.0
-jsonargparse[signatures]>=4.10.2, <=4.10.2
+jsonargparse[signatures]>=4.12.0, <=4.12.0
 gcsfs>=2021.5.0, <2022.6.0
 rich>=10.14.0, !=10.15.0.a, <13.0.0

src/pytorch_lightning/cli.py

@@ -27,7 +27,7 @@
 from pytorch_lightning.utilities.model_helpers import is_overridden
 from pytorch_lightning.utilities.rank_zero import _warn, rank_zero_deprecation, rank_zero_warn
 
-_JSONARGPARSE_SIGNATURES_AVAILABLE = _RequirementAvailable("jsonargparse[signatures]>=4.10.2")
+_JSONARGPARSE_SIGNATURES_AVAILABLE = _RequirementAvailable("jsonargparse[signatures]>=4.12.0")
 
 if _JSONARGPARSE_SIGNATURES_AVAILABLE:
     import docstring_parser

tests/tests_pytorch/test_cli.py

@@ -1414,21 +1414,47 @@ def _test_logger_init_args(logger_name, init, unresolved={}):
 
 @pytest.mark.skipif(not _COMET_AVAILABLE, reason="comet-ml is required")
 def test_comet_logger_init_args():
-    _test_logger_init_args("CometLogger", {"save_dir": "comet", "workspace": "comet"})
+    _test_logger_init_args(
+        "CometLogger",
+        {
+            "save_dir": "comet",  # Resolve from CometLogger.__init__
+            "workspace": "comet",  # Resolve from Comet{,Existing,Offline}Experiment.__init__
+        },
+    )
 
 
 @pytest.mark.skipif(not _NEPTUNE_AVAILABLE, reason="neptune-client is required")
 def test_neptune_logger_init_args():
-    _test_logger_init_args("NeptuneLogger", {"name": "neptune"}, {"description": "neptune"})
+    _test_logger_init_args(
+        "NeptuneLogger",
+        {
+            "name": "neptune",  # Resolve from NeptuneLogger.__init__
+        },
+        {
+            "description": "neptune",  # Unsupported resolving from neptune.new.internal.init.run.init_run
+        },
+    )
 
 
 def test_tensorboard_logger_init_args():
-    _test_logger_init_args("TensorBoardLogger", {"save_dir": "tb", "name": "tb"})
+    _test_logger_init_args(
+        "TensorBoardLogger",
+        {
+            "save_dir": "tb",  # Resolve from TensorBoardLogger.__init__
+            "comment": "tb",  # Resolve from tensorboard.writer.SummaryWriter.__init__
+        },
+    )
 
 
 @pytest.mark.skipif(not _WANDB_AVAILABLE, reason="wandb is required")
 def test_wandb_logger_init_args():
-    _test_logger_init_args("WandbLogger", {"save_dir": "wandb", "notes": "wandb"})
+    _test_logger_init_args(
+        "WandbLogger",
+        {
+            "save_dir": "wandb",  # Resolve from WandbLogger.__init__
+            "notes": "wandb",  # Resolve from wandb.sdk.wandb_init.init
+        },
+    )
 
 
 def test_cli_auto_seeding():
@@ -1512,13 +1538,13 @@ def test_pytorch_profiler_init_args():
     from pytorch_lightning.profilers import Profiler, PyTorchProfiler
 
     init = {
-        "dirpath": "profiler",
-        "row_limit": 10,
-        "group_by_input_shapes": True,
+        "dirpath": "profiler",  # Resolve from PyTorchProfiler.__init__
+        "row_limit": 10,  # Resolve from PyTorchProfiler.__init__
+        "group_by_input_shapes": True,  # Resolve from PyTorchProfiler.__init__
     }
     unresolved = {
-        "profile_memory": True,
-        "record_shapes": True,
+        "profile_memory": True,  # Not possible to resolve parameters from dynamically chosen Type[_PROFILER]
+        "record_shapes": True,  # Resolve from PyTorchProfiler.__init__, gets moved to init_args
     }
     cli_args = ["--trainer.profiler=PyTorchProfiler"]
     cli_args += [f"--trainer.profiler.{k}={v}" for k, v in init.items()]
@@ -1528,5 +1554,6 @@ def test_pytorch_profiler_init_args():
         cli = LightningCLI(TestModel, run=False)
 
     assert isinstance(cli.config_init.trainer.profiler, PyTorchProfiler)
+    init["record_shapes"] = unresolved.pop("record_shapes")  # Test move to init_args
     assert {k: cli.config.trainer.profiler.init_args[k] for k in init} == init
     assert cli.config.trainer.profiler.dict_kwargs == unresolved