diff --git a/pytorch_lightning/trainer/training_loop.py b/pytorch_lightning/trainer/training_loop.py
index 48a10e19..06d3ebd5 100644
--- a/pytorch_lightning/trainer/training_loop.py
+++ b/pytorch_lightning/trainer/training_loop.py
@@ -460,11 +460,12 @@ class TrainerTrainLoopMixin(ABC):
             for opt_idx, optimizer in enumerate(self.optimizers):
                 # make sure only the gradients of the current optimizer's paramaters are calculated
                 # in the training step to prevent dangling gradients in multiple-optimizer setup.
-                for param in self.get_model().parameters():
-                    param.requires_grad = False
-                for group in optimizer.param_groups:
-                    for param in group['params']:
-                        param.requires_grad = True
+                if len(self.optimizers) > 1:
+                    for param in self.get_model().parameters():
+                        param.requires_grad = False
+                    for group in optimizer.param_groups:
+                        for param in group['params']:
+                            param.requires_grad = True
 
                 # wrap the forward step in a closure so second order methods work
                 def optimizer_closure():