diff --git a/src/lightning/pytorch/trainer/connectors/logger_connector/result.py b/src/lightning/pytorch/trainer/connectors/logger_connector/result.py
index 7e0ef433031bdf..c887ef1befc71f 100644
--- a/src/lightning/pytorch/trainer/connectors/logger_connector/result.py
+++ b/src/lightning/pytorch/trainer/connectors/logger_connector/result.py
@@ -403,26 +403,19 @@ def log(
 
         # register logged value if it doesn't exist
         if key not in self:
-            self.register_key(key, meta, value)
+            metric = _ResultMetric(meta, isinstance(value, Tensor))
+            self[key] = metric
 
         # check the stored metadata and the current one match
         elif meta != self[key].meta:
             raise MisconfigurationException(
                 f"You called `self.log({name}, ...)` twice in `{fx}` with different arguments. This is not allowed"
             )
+        self[key].to(value.device)
 
         batch_size = self._extract_batch_size(self[key], batch_size, meta)
         self.update_metrics(key, value, batch_size)
 
-    def register_key(self, key: str, meta: _Metadata, value: _VALUE) -> None:
-        """Create one _ResultMetric object per value.
-
-        Value can be provided as a nested collection
-
-        """
-        metric = _ResultMetric(meta, isinstance(value, Tensor)).to(value.device)
-        self[key] = metric
-
     def update_metrics(self, key: str, value: _VALUE, batch_size: int) -> None:
         result_metric = self[key]
         # performance: avoid calling `__call__` to avoid the checks in `torch.nn.Module._call_impl`