Raise an exception if check_val_every_n_epoch is not an integer (#6411)

* raise an exception if check_val_every_n_epoch is not an integer

* remove unused object

* add type hints

* add return type

* update exception message

* update exception message

pytorch_lightning/trainer/connectors/data_connector.py

@@ -26,10 +26,17 @@ class DataConnector(object):
     def __init__(self, trainer):
         self.trainer = trainer
 
-    def on_trainer_init(self, check_val_every_n_epoch, reload_dataloaders_every_epoch, prepare_data_per_node):
+    def on_trainer_init(
+        self, check_val_every_n_epoch: int, reload_dataloaders_every_epoch: bool, prepare_data_per_node: bool
+    ) -> None:
         self.trainer.datamodule = None
         self.trainer.prepare_data_per_node = prepare_data_per_node
 
+        if not isinstance(check_val_every_n_epoch, int):
+            raise MisconfigurationException(
+                f"check_val_every_n_epoch should be an integer. Found {check_val_every_n_epoch}"
+            )
+
         self.trainer.check_val_every_n_epoch = check_val_every_n_epoch
         self.trainer.reload_dataloaders_every_epoch = reload_dataloaders_every_epoch
         self.trainer._is_data_prepared = False

tests/trainer/test_trainer.py

@@ -1828,3 +1828,13 @@ def compare_optimizers():
     trainer.max_epochs = 2  # simulate multiple fit calls
     trainer.fit(model)
     compare_optimizers()
+
+
+def test_check_val_every_n_epoch_exception(tmpdir):
+
+    with pytest.raises(MisconfigurationException, match="should be an integer."):
+        Trainer(
+            default_root_dir=tmpdir,
+            max_epochs=1,
+            check_val_every_n_epoch=1.2,
+        )