Avoid warning when cloning tensor in self.log (#14599)

Co-authored-by: Jirka Borovec <[email protected]>

Author: 2 people

src/pytorch_lightning/CHANGELOG.md

@@ -10,6 +10,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Reset the dataloaders on OOM failure in batch size finder to use the last successful batch size ([#14372](https://github.com/Lightning-AI/lightning/pull/14372))
 - Fixed an issue to keep downscaling the batch size in case there hasn't been even a single successful optimal batch size with `mode="power"` ([#14372](https://github.com/Lightning-AI/lightning/pull/14372))
+- Fixed an issue where `self.log`-ing a tensor would create a user warning from PyTorch about cloning tensors ([#14599](https://github.com/Lightning-AI/lightning/pull/14599))
 - Fixed compatibility when `torch.distributed` is not available ([#14454](https://github.com/Lightning-AI/lightning/pull/14454))
 - Fixed torchscript error with ensembles of LightningModules ([#14657](https://github.com/Lightning-AI/lightning/pull/14657))
 

src/pytorch_lightning/core/module.py

@@ -581,7 +581,11 @@ def __check_allowed(v: Any, name: str, value: Any) -> None:
         raise ValueError(f"`self.log({name}, {value})` was called, but `{type(v).__name__}` values cannot be logged")
 
     def __to_tensor(self, value: Union[torch.Tensor, numbers.Number], name: str) -> Tensor:
-        value = torch.tensor(value, device=self.device)
+        value = (
+            value.clone().detach().to(self.device)
+            if isinstance(value, torch.Tensor)
+            else torch.tensor(value, device=self.device)
+        )
         if not torch.numel(value) == 1:
             raise ValueError(
                 f"`self.log({name}, {value})` was called, but the tensor must have a single element."

tests/tests_pytorch/trainer/logging_/test_train_loop_logging.py

@@ -32,6 +32,7 @@
 from pytorch_lightning.trainer.states import RunningStage
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from tests_pytorch.helpers.runif import RunIf
+from tests_pytorch.helpers.utils import no_warning_call
 
 
 def test__training_step__log(tmpdir):
@@ -626,6 +627,21 @@ def training_step(self, *args):
         trainer.fit(model)
 
 
+def test_log_tensor_and_clone_no_torch_warning(tmpdir):
+    """Regression test for issue https://github.com/Lightning-AI/lightning/issues/14594."""
+
+    class TestModel(BoringModel):
+        def training_step(self, *args):
+            self.log("foo", torch.tensor(1))
+            return super().training_step(*args)
+
+    trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=1)
+    model = TestModel()
+    match = r"recommended.*.clone\(\).detach\(\)"
+    with no_warning_call(UserWarning, match=match):
+        trainer.fit(model)
+
+
 def test_logging_raises(tmpdir):
     class TestModel(BoringModel):
         def training_step(self, batch, batch_idx):