fix mypy errors for loggers/wandb.py

environment.yml

@@ -50,5 +50,5 @@ dependencies:
         - test-tube>=0.7.5
         - mlflow>=1.0.0
         - comet_ml>=3.1.12
-        - wandb>=0.8.21
+        - wandb>=0.10.22
         - neptune-client>=0.10.0

pyproject.toml

@@ -59,7 +59,6 @@ module = [
     "pytorch_lightning.demos.mnist_datamodule",
     "pytorch_lightning.loggers.comet",
     "pytorch_lightning.loggers.neptune",
-    "pytorch_lightning.loggers.wandb",
     "pytorch_lightning.profilers.advanced",
     "pytorch_lightning.profilers.base",
     "pytorch_lightning.profilers.pytorch",

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]>=4.10.0, <=4.10.0
+jsonargparse[signatures]>=4.10.2, <=4.10.2
 gcsfs>=2021.5.0, <2022.6.0
 rich>=10.14.0, !=10.15.0.a, <13.0.0

requirements/pytorch/loggers.txt

@@ -4,4 +4,4 @@ neptune-client>=0.10.0, <0.16.4
 comet-ml>=3.1.12, <3.31.6
 mlflow>=1.0.0, <1.27.0
 test_tube>=0.7.5, <=0.7.5
-wandb>=0.8.21, <0.12.20
+wandb>=0.10.22, <0.12.20

src/pytorch_lightning/loggers/wandb.py

@@ -32,10 +32,11 @@
 
 try:
     import wandb
+    from wandb.sdk.lib import RunDisabled
     from wandb.wandb_run import Run
 except ModuleNotFoundError:
     # needed for test mocks, these tests shall be updated
-    wandb, Run = None, None
+    wandb, Run, RunDisabled = None, None, None  # type: ignore
 
 
 class WandbLogger(Logger):
@@ -251,18 +252,18 @@ def __init__(
         self,
         name: Optional[str] = None,
         save_dir: Optional[str] = None,
-        offline: Optional[bool] = False,
+        offline: bool = False,
         id: Optional[str] = None,
         anonymous: Optional[bool] = None,
         version: Optional[str] = None,
         project: Optional[str] = None,
         log_model: Union[str, bool] = False,
-        experiment=None,
-        prefix: Optional[str] = "",
+        experiment: Union[Run, RunDisabled, None] = None,
+        prefix: str = "",
         agg_key_funcs: Optional[Mapping[str, Callable[[Sequence[float]], float]]] = None,
         agg_default_func: Optional[Callable[[Sequence[float]], float]] = None,
-        **kwargs,
-    ):
+        **kwargs: Any,
+    ) -> None:
         if wandb is None:
             raise ModuleNotFoundError(
                 "You want to use `wandb` logger which is not installed yet,"
@@ -288,17 +289,16 @@ def __init__(
         self._log_model = log_model
         self._prefix = prefix
         self._experiment = experiment
-        self._logged_model_time = {}
-        self._checkpoint_callback = None
+        self._logged_model_time: Dict[str, float] = {}
+        self._checkpoint_callback: Optional["ReferenceType[Checkpoint]"] = None
         # set wandb init arguments
-        anonymous_lut = {True: "allow", False: None}
-        self._wandb_init = dict(
+        self._wandb_init: Dict[str, Any] = dict(
             name=name or project,
             project=project,
             id=version or id,
             dir=save_dir,
             resume="allow",
-            anonymous=anonymous_lut.get(anonymous, anonymous),
+            anonymous=("allow" if anonymous else None),
         )
         self._wandb_init.update(**kwargs)
         # extract parameters
@@ -310,7 +310,7 @@ def __init__(
             wandb.require("service")
             _ = self.experiment
 
-    def __getstate__(self):
+    def __getstate__(self) -> Dict[str, Any]:
         state = self.__dict__.copy()
         # args needed to reload correct experiment
         if self._experiment is not None:
@@ -322,7 +322,7 @@ def __getstate__(self):
         state["_experiment"] = None
         return state
 
-    @property
+    @property  # type: ignore[misc]
     @rank_zero_experiment
     def experiment(self) -> Run:
         r"""
@@ -357,13 +357,14 @@ def experiment(self) -> Run:
                 self._experiment = wandb.init(**self._wandb_init)
 
                 # define default x-axis
-                if getattr(self._experiment, "define_metric", None):
+                if isinstance(self._experiment, Run) and getattr(self._experiment, "define_metric", None):
                     self._experiment.define_metric("trainer/global_step")
                     self._experiment.define_metric("*", step_metric="trainer/global_step", step_sync=True)
 
+        assert isinstance(self._experiment, Run)
         return self._experiment
 
-    def watch(self, model: nn.Module, log: str = "gradients", log_freq: int = 100, log_graph: bool = True):
+    def watch(self, model: nn.Module, log: str = "gradients", log_freq: int = 100, log_graph: bool = True) -> None:
         self.experiment.watch(model, log=log, log_freq=log_freq, log_graph=log_graph)
 
     @rank_zero_only
@@ -379,7 +380,7 @@ def log_metrics(self, metrics: Dict[str, float], step: Optional[int] = None) ->
 
         metrics = _add_prefix(metrics, self._prefix, self.LOGGER_JOIN_CHAR)
         if step is not None:
-            self.experiment.log({**metrics, "trainer/global_step": step})
+            self.experiment.log(dict(metrics, **{"trainer/global_step": step}))
         else:
             self.experiment.log(metrics)
 
@@ -417,7 +418,7 @@ def log_text(
         self.log_table(key, columns, data, dataframe, step)
 
     @rank_zero_only
-    def log_image(self, key: str, images: List[Any], step: Optional[int] = None, **kwargs: str) -> None:
+    def log_image(self, key: str, images: List[Any], step: Optional[int] = None, **kwargs: Any) -> None:
         """Log images (tensors, numpy arrays, PIL Images or file paths).
 
         Optional kwargs are lists passed to each image (ex: caption, masks, boxes).

src/pytorch_lightning/utilities/cli.py

@@ -31,7 +31,7 @@
 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]>=4.10.0")
+_JSONARGPARSE_SIGNATURES_AVAILABLE = _RequirementAvailable("jsonargparse[signatures]>=4.10.2")
 
 if _JSONARGPARSE_SIGNATURES_AVAILABLE:
     import docstring_parser

tests/tests_pytorch/loggers/test_all.py

@@ -45,6 +45,7 @@
     mock.patch("pytorch_lightning.loggers.mlflow.MlflowClient"),
     mock.patch("pytorch_lightning.loggers.neptune.neptune", new_callable=create_neptune_mock),
     mock.patch("pytorch_lightning.loggers.wandb.wandb"),
+    mock.patch("pytorch_lightning.loggers.wandb.Run", new=mock.Mock),
 )
 ALL_LOGGER_CLASSES = (
     CometLogger,
@@ -363,7 +364,9 @@ def test_logger_with_prefix_all(tmpdir, monkeypatch):
         logger.experiment.add_scalar.assert_called_once_with("tmp-test", 1.0, 0)
 
     # WandB
-    with mock.patch("pytorch_lightning.loggers.wandb.wandb") as wandb:
+    with mock.patch("pytorch_lightning.loggers.wandb.wandb") as wandb, mock.patch(
+        "pytorch_lightning.loggers.wandb.Run", new=mock.Mock
+    ):
         logger = _instantiate_logger(WandbLogger, save_dir=tmpdir, prefix=prefix)
         wandb.run = None
         wandb.init().step = 0

tests/tests_pytorch/loggers/test_wandb.py

@@ -24,6 +24,7 @@
 from tests_pytorch.helpers.utils import no_warning_call
 
 
+@mock.patch("pytorch_lightning.loggers.wandb.Run", new=mock.Mock)
 @mock.patch("pytorch_lightning.loggers.wandb.wandb")
 def test_wandb_logger_init(wandb, monkeypatch):
     """Verify that basic functionality of wandb logger works.
@@ -111,20 +112,21 @@ class Experiment:
         def name(self):
             return "the_run_name"
 
-    wandb.run = None
-    wandb.init.return_value = Experiment()
-    logger = WandbLogger(id="the_id", offline=True)
+    with mock.patch("pytorch_lightning.loggers.wandb.Run", new=Experiment):
+        wandb.run = None
+        wandb.init.return_value = Experiment()
+        logger = WandbLogger(id="the_id", offline=True)
 
-    trainer = Trainer(default_root_dir=tmpdir, max_epochs=1, logger=logger)
-    # Access the experiment to ensure it's created
-    assert trainer.logger.experiment, "missing experiment"
-    assert trainer.log_dir == logger.save_dir
-    pkl_bytes = pickle.dumps(trainer)
-    trainer2 = pickle.loads(pkl_bytes)
+        trainer = Trainer(default_root_dir=tmpdir, max_epochs=1, logger=logger)
+        # Access the experiment to ensure it's created
+        assert trainer.logger.experiment, "missing experiment"
+        assert trainer.log_dir == logger.save_dir
+        pkl_bytes = pickle.dumps(trainer)
+        trainer2 = pickle.loads(pkl_bytes)
 
-    assert os.environ["WANDB_MODE"] == "dryrun"
-    assert trainer2.logger.__class__.__name__ == WandbLogger.__name__
-    assert trainer2.logger.experiment, "missing experiment"
+        assert os.environ["WANDB_MODE"] == "dryrun"
+        assert trainer2.logger.__class__.__name__ == WandbLogger.__name__
+        assert trainer2.logger.experiment, "missing experiment"
 
     wandb.init.assert_called()
     assert "id" in wandb.init.call_args[1]
@@ -133,6 +135,7 @@ def name(self):
     del os.environ["WANDB_MODE"]
 
 
+@mock.patch("pytorch_lightning.loggers.wandb.Run", new=mock.Mock)
 @mock.patch("pytorch_lightning.loggers.wandb.wandb")
 def test_wandb_logger_dirs_creation(wandb, monkeypatch, tmpdir):
     """Test that the logger creates the folders and files in the right place."""
@@ -169,6 +172,7 @@ def test_wandb_logger_dirs_creation(wandb, monkeypatch, tmpdir):
     assert trainer.log_dir == logger.save_dir
 
 
+@mock.patch("pytorch_lightning.loggers.wandb.Run", new=mock.Mock)
 @mock.patch("pytorch_lightning.loggers.wandb.wandb")
 def test_wandb_log_model(wandb, monkeypatch, tmpdir):
     """Test that the logger creates the folders and files in the right place."""
@@ -234,6 +238,7 @@ def test_wandb_log_model(wandb, monkeypatch, tmpdir):
     )
 
 
+@mock.patch("pytorch_lightning.loggers.wandb.Run", new=mock.Mock)
 @mock.patch("pytorch_lightning.loggers.wandb.wandb")
 def test_wandb_log_media(wandb, tmpdir):
     """Test that the logger creates the folders and files in the right place."""