diff --git a/CHANGELOG.md b/CHANGELOG.md
index 23ba6c4f26411..9f81e97b3efbb 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -221,6 +221,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated `is_overridden(model=...)` in favor of `is_overridden(instance=...)` ([#7918](https://github.com/PyTorchLightning/pytorch-lightning/pull/7918))
 
 
+- Deprecated automatically detaching returned extras with grads ([#7994](https://github.com/PyTorchLightning/pytorch-lightning/pull/7994))
+
+
 - Deprecated default value of `monitor` argument in EarlyStopping callback to enforce `monitor` as a required argument ([#7907](https://github.com/PyTorchLightning/pytorch-lightning/pull/7907))
 
 
diff --git a/pytorch_lightning/trainer/connectors/logger_connector/result.py b/pytorch_lightning/trainer/connectors/logger_connector/result.py
index f751916804ad1..096741d4a7486 100644
--- a/pytorch_lightning/trainer/connectors/logger_connector/result.py
+++ b/pytorch_lightning/trainer/connectors/logger_connector/result.py
@@ -26,12 +26,15 @@
 from pytorch_lightning.utilities.enums import LightningEnum
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.metrics import metrics_to_scalars
+from pytorch_lightning.utilities.warnings import WarningCache
 
 # re-define the ones from pytorch_lightning.utilities.types without the `Number` type
 # TODO(@tchaton): Typing-pickle issue on python<3.7 (https://github.com/cloudpipe/cloudpickle/pull/318)
 _METRIC = Any  # Union[Metric, torch.Tensor]
 _METRIC_COLLECTION = Union[_METRIC, Mapping[str, _METRIC]]
 
+warning_cache = WarningCache()
+
 
 class MetricSource(LightningEnum):
     CALLBACK = "callback"
@@ -367,9 +370,15 @@ def extra(self, extra: Mapping[str, Any]) -> None:
 
         def check_fn(v):
             if v.grad_fn is not None:
-                raise MisconfigurationException(f'You returned a tensor with `grad_fn`. The extra values are {extra}')
+                warning_cache.warn(
+                    f"One of the returned values {set(extra.keys())} has a `grad_fn`. We will detach it automatically"
+                    " but this behaviour will change in v1.6. Please detach it manually:"
+                    " `return {'loss': ..., 'something': something.detach()}`", DeprecationWarning
+                )
+                return v.detach()
+            return v
 
-        apply_to_collection(extra, torch.Tensor, check_fn)
+        extra = apply_to_collection(extra, torch.Tensor, check_fn)
         self['_extra'] = extra
 
     def log(
diff --git a/tests/deprecated_api/test_remove_1-6.py b/tests/deprecated_api/test_remove_1-6.py
index cb150cb013ec2..2fa54f3b253fb 100644
--- a/tests/deprecated_api/test_remove_1-6.py
+++ b/tests/deprecated_api/test_remove_1-6.py
@@ -212,3 +212,18 @@ def test_v1_6_0_early_stopping_monitor(tmpdir):
         " For backward compatibility, setting this to `early_stop_on`."
     ):
         EarlyStopping()
+
+
+def test_v1_6_0_extras_with_gradients(tmpdir):
+
+    class TestModel(BoringModel):
+
+        def training_step(self, *args):
+            loss = super().training_step(*args)['loss']
+            return {"loss": loss, 'foo': loss}
+
+    trainer = Trainer(default_root_dir=tmpdir, fast_dev_run=1)
+    model = TestModel()
+    match = r"\{'foo'\} has a `grad_fn`.*behaviour will change in v1\.6"
+    with pytest.deprecated_call(match=match):
+        trainer.fit(model)
diff --git a/tests/trainer/logging_/test_train_loop_logging.py b/tests/trainer/logging_/test_train_loop_logging.py
index bff558e81b29e..8ca51b2dee3ef 100644
--- a/tests/trainer/logging_/test_train_loop_logging.py
+++ b/tests/trainer/logging_/test_train_loop_logging.py
@@ -690,17 +690,6 @@ def training_step(self, batch, batch_idx):
     with pytest.raises(MisconfigurationException, match='`self.log` with the key `foo/dataloader_idx_0`'):
         trainer.fit(model)
 
-    class TestModel(BoringModel):
-
-        def training_step(self, *args):
-            loss = super().training_step(*args)['loss']
-            return {"loss": loss, 'foo': loss}
-
-    trainer = Trainer(default_root_dir=tmpdir)
-    model = TestModel()
-    with pytest.raises(MisconfigurationException, match='You returned a tensor with `grad_fn`'):
-        trainer.fit(model)
-
     class TestModel(BoringModel):
 
         def training_step(self, *args):