diff --git a/pytorch_lightning/trainer/model_hooks.py b/pytorch_lightning/trainer/model_hooks.py
index 3cf42136d4..065add2352 100644
--- a/pytorch_lightning/trainer/model_hooks.py
+++ b/pytorch_lightning/trainer/model_hooks.py
@@ -6,8 +6,9 @@ from pytorch_lightning.core.lightning import LightningModule
 
 class TrainerModelHooksMixin(ABC):
 
-    def is_function_implemented(self, f_name):
-        model = self.get_model()
+    def is_function_implemented(self, f_name, model=None):
+        if model is None:
+            model = self.get_model()
         f_op = getattr(model, f_name, None)
         return callable(f_op)
 
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index cd77f1caa8..36664b5549 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -848,7 +848,7 @@ class Trainer(
 
         # callbacks
         self.on_fit_start()
-        if self.is_function_implemented('on_fit_start'):
+        if self.is_function_implemented('on_fit_start', model):
             model.on_fit_start()
 
         # on multi-gpu jobs we only want to manipulate (download, etc) on node_rank=0, local_rank=0
@@ -860,7 +860,7 @@ class Trainer(
         self.barrier('fit_prepare_data')
 
         self.setup('fit')
-        if self.is_function_implemented('setup'):
+        if self.is_function_implemented('setup', model):
             model.setup('fit')
 
         # Run auto batch size scaling
@@ -1149,8 +1149,8 @@ class Trainer(
             trainer.test(model, test_dataloaders=test)
         """
         self.setup('test')
-        if self.is_function_implemented('setup'):
-            model_ref = self.model if model is None else model
+        model_ref = self.model if model is None else model
+        if self.is_function_implemented('setup', model_ref):
             model_ref.setup('test')
 
         self.barrier('test_setup')