Use run name for logging with WandbLogger

CHANGELOG.md

@@ -106,6 +106,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Raise an error if there are insufficient training batches when using a float value of `limit_train_batches` ([#12885](https://github.com/PyTorchLightning/pytorch-lightning/pull/12885))
 
 
+- The `WandbLogger` will now use the run name in the logs folder if it is provided, and otherwise the project name  ([#12604](https://github.com/PyTorchLightning/pytorch-lightning/pull/12604))
+
 
 
 ### Deprecated

src/pytorch_lightning/loggers/wandb.py

@@ -293,7 +293,7 @@ def __init__(
         # set wandb init arguments
         anonymous_lut = {True: "allow", False: None}
         self._wandb_init = dict(
-            name=name,
+            name=name or project,
             project=project,
             id=version or id,
             dir=save_dir,
@@ -316,7 +316,7 @@ def __getstate__(self):
         if self._experiment is not None:
             state["_id"] = getattr(self._experiment, "id", None)
             state["_attach_id"] = getattr(self._experiment, "_attach_id", None)
-            state["_name"] = self._experiment.project_name()
+            state["_name"] = self._experiment.name
 
         # cannot be pickled
         state["_experiment"] = None
@@ -449,7 +449,7 @@ def name(self) -> Optional[str]:
             The name of the experiment if the experiment exists else the name given to the constructor.
         """
         # don't create an experiment if we don't have one
-        return self._experiment.project_name() if self._experiment else self._name
+        return self._experiment.name if self._experiment else self._name
 
     @property
     def version(self) -> Optional[str]:

tests/tests_pytorch/loggers/test_all.py

@@ -118,7 +118,7 @@ def log_metrics(self, metrics, step):
     if logger_class == WandbLogger:
         # required mocks for Trainer
         logger.experiment.id = "foo"
-        logger.experiment.project_name.return_value = "bar"
+        logger.experiment.name = "bar"
 
     if logger_class == CometLogger:
         logger.experiment.id = "foo"
@@ -299,7 +299,7 @@ def on_train_batch_start(self, trainer, pl_module, batch, batch_idx):
 
 
 @pytest.mark.parametrize("logger_class", ALL_LOGGER_CLASSES_WO_NEPTUNE_WANDB)
-@RunIf(skip_windows=True)
+@RunIf(skip_windows=True, skip_hanging_spawn=True)
 def test_logger_created_on_rank_zero_only(tmpdir, monkeypatch, logger_class):
     """Test that loggers get replaced by dummy loggers on global rank > 0."""
     _patch_comet_atexit(monkeypatch)

tests/tests_pytorch/loggers/test_wandb.py

@@ -43,6 +43,14 @@ def test_wandb_logger_init(wandb, monkeypatch):
     )
     wandb.init().log.assert_called_once_with({"acc": 1.0})
 
+    # test wandb.init called with project as name if name not provided
+    wandb.run = None
+    wandb.init.reset_mock()
+    WandbLogger(project="test_project").experiment
+    wandb.init.assert_called_once_with(
+        name="test_project", dir=None, id=None, project="test_project", resume="allow", anonymous=None
+    )
+
     # test wandb.init and setting logger experiment externally
     wandb.run = None
     run = wandb.init()
@@ -83,7 +91,7 @@ def test_wandb_logger_init(wandb, monkeypatch):
     logger.watch("model", "log", 10, False)
     wandb.init().watch.assert_called_once_with("model", log="log", log_freq=10, log_graph=False)
 
-    assert logger.name == wandb.init().project_name()
+    assert logger.name == wandb.init().name
     assert logger.version == wandb.init().id
 
 
@@ -99,8 +107,9 @@ class Experiment:
         step = 0
         dir = "wandb"
 
-        def project_name(self):
-            return "the_project_name"
+        @property
+        def name(self):
+            return "the_run_name"
 
     wandb.run = None
     wandb.init.return_value = Experiment()
@@ -134,18 +143,18 @@ def test_wandb_logger_dirs_creation(wandb, monkeypatch, tmpdir):
     logger = WandbLogger(save_dir=str(tmpdir), offline=True)
     # the logger get initialized
     assert logger.version == wandb.init().id
-    assert logger.name == wandb.init().project_name()
+    assert logger.name == wandb.init().name
 
     # mock return values of experiment
     wandb.run = None
     logger.experiment.id = "1"
-    logger.experiment.project_name.return_value = "project"
+    logger.experiment.name = "run_name"
 
     for _ in range(2):
         _ = logger.experiment
 
     assert logger.version == "1"
-    assert logger.name == "project"
+    assert logger.name == "run_name"
     assert str(tmpdir) == logger.save_dir
     assert not os.listdir(tmpdir)
 
@@ -155,7 +164,7 @@ def test_wandb_logger_dirs_creation(wandb, monkeypatch, tmpdir):
     assert trainer.log_dir == logger.save_dir
     trainer.fit(model)
 
-    assert trainer.checkpoint_callback.dirpath == str(tmpdir / "project" / version / "checkpoints")
+    assert trainer.checkpoint_callback.dirpath == str(tmpdir / "run_name" / version / "checkpoints")
     assert set(os.listdir(trainer.checkpoint_callback.dirpath)) == {"epoch=0-step=3.ckpt"}
     assert trainer.log_dir == logger.save_dir
 
@@ -173,7 +182,7 @@ def test_wandb_log_model(wandb, monkeypatch, tmpdir):
     # test log_model=True
     logger = WandbLogger(log_model=True)
     logger.experiment.id = "1"
-    logger.experiment.project_name.return_value = "project"
+    logger.experiment.name = "run_name"
     trainer = Trainer(default_root_dir=tmpdir, logger=logger, max_epochs=2, limit_train_batches=3, limit_val_batches=3)
     trainer.fit(model)
     wandb.init().log_artifact.assert_called_once()
@@ -183,7 +192,7 @@ def test_wandb_log_model(wandb, monkeypatch, tmpdir):
     wandb.init.reset_mock()
     logger = WandbLogger(log_model="all")
     logger.experiment.id = "1"
-    logger.experiment.project_name.return_value = "project"
+    logger.experiment.name = "run_name"
     trainer = Trainer(default_root_dir=tmpdir, logger=logger, max_epochs=2, limit_train_batches=3, limit_val_batches=3)
     trainer.fit(model)
     assert wandb.init().log_artifact.call_count == 2
@@ -193,7 +202,7 @@ def test_wandb_log_model(wandb, monkeypatch, tmpdir):
     wandb.init.reset_mock()
     logger = WandbLogger(log_model=False)
     logger.experiment.id = "1"
-    logger.experiment.project_name.return_value = "project"
+    logger.experiment.name = "run_name"
     trainer = Trainer(default_root_dir=tmpdir, logger=logger, max_epochs=2, limit_train_batches=3, limit_val_batches=3)
     trainer.fit(model)
     assert not wandb.init().log_artifact.called
@@ -204,7 +213,7 @@ def test_wandb_log_model(wandb, monkeypatch, tmpdir):
     wandb.Artifact.reset_mock()
     logger = WandbLogger(log_model=True)
     logger.experiment.id = "1"
-    logger.experiment.project_name.return_value = "project"
+    logger.experiment.name = "run_name"
     trainer = Trainer(default_root_dir=tmpdir, logger=logger, max_epochs=2, limit_train_batches=3, limit_val_batches=3)
     trainer.fit(model)
     wandb.Artifact.assert_called_once_with(