diff --git a/pytorch_lightning/models/trainer.py b/pytorch_lightning/models/trainer.py
index ac67d83dad..5ce253c29c 100644
--- a/pytorch_lightning/models/trainer.py
+++ b/pytorch_lightning/models/trainer.py
@@ -438,8 +438,10 @@ class Trainer(TrainerIO):
                 raise MisconfigurationException('amp + cpu is not supported. Please use a GPU option')
 
             # CHOOSE OPTIMIZER
-            # filter out the weights that were done on gpu so we can load on good old cpus
-            self.optimizers, self.lr_schedulers = model.configure_optimizers()
+            # allow for lr schedulers as well
+            self.optimizers = model.configure_optimizers()
+            if len(self.optimizers) == 2:
+                self.optimizers, self.lr_schedulers = self.optimizers
 
             self.__run_pretrain_routine(model)
 
@@ -450,8 +452,10 @@ class Trainer(TrainerIO):
     def __dp_train(self, model):
 
         # CHOOSE OPTIMIZER
-        # filter out the weights that were done on gpu so we can load on good old cpus
-        self.optimizers, self.lr_schedulers = model.configure_optimizers()
+        # allow for lr schedulers as well
+        self.optimizers = model.configure_optimizers()
+        if len(self.optimizers) == 2:
+            self.optimizers, self.lr_schedulers = self.optimizers
 
         model.cuda(self.data_parallel_device_ids[0])
 
@@ -504,8 +508,10 @@ class Trainer(TrainerIO):
         self.__init_tcp_connection()
 
         # CHOOSE OPTIMIZER
-        # filter out the weights that were done on gpu so we can load on good old cpus
-        self.optimizers, self.lr_schedulers = model.configure_optimizers()
+        # allow for lr schedulers as well
+        self.optimizers = model.configure_optimizers()
+        if len(self.optimizers) == 2:
+            self.optimizers, self.lr_schedulers = self.optimizers
 
         # MODEL
         # copy model to each gpu