diff --git a/classy_vision/tasks/classification_task.py b/classy_vision/tasks/classification_task.py
index 443ce61dcb..526ae8d58d 100644
--- a/classy_vision/tasks/classification_task.py
+++ b/classy_vision/tasks/classification_task.py
@@ -719,10 +719,7 @@ def init_distributed_data_parallel_model(self):
             broadcast_buffers=broadcast_buffers,
             find_unused_parameters=self.find_unused_parameters,
         )
-        if (
-            isinstance(self.base_loss, ClassyLoss)
-            and self.base_loss.has_learned_parameters()
-        ):
+        if self._loss_has_learnable_params():
             logging.info("Initializing distributed loss")
             self.distributed_loss = init_distributed_data_parallel_model(
                 self.base_loss,
@@ -1014,6 +1011,13 @@ def _broadcast_buffers(self):
             for buffer in buffers:
                 broadcast(buffer, 0, group=self.distributed_model.process_group)
 
+    def _loss_has_learnable_params(self):
+        """Returns True if the loss has any learnable parameters"""
+        return (
+            isinstance(self.base_loss, ClassyLoss)
+            and self.base_loss.has_learned_parameters()
+        )
+
     # TODO: Functions below should be better abstracted into the dataloader
     # abstraction
     def get_batchsize_per_replica(self):