diff --git a/pytorch_lightning/trainer/distrib_parts.py b/pytorch_lightning/trainer/distrib_parts.py
index 78bc22d21589d..8d19655175f8e 100644
--- a/pytorch_lightning/trainer/distrib_parts.py
+++ b/pytorch_lightning/trainer/distrib_parts.py
@@ -222,7 +222,7 @@ def tpu_train(self, tpu_core_idx, model):
         self.run_pretrain_routine(model)
 
         # when training ends on these platforms dump weights to get out of the main process
-        if self.on_colab_kaggle:
+        if self.on_colab_kaggle and not self.testing:
             rank_zero_warn('cleaning up... please do not interrupt')
             self.save_spawn_weights(model)
 
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index c104ab8b2f78d..c91b6a63a04d5 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -1014,7 +1014,7 @@ def fit(
                 xmp.spawn(self.tpu_train, args=(model,), nprocs=self.tpu_cores, start_method=start_method)
 
             # load weights if not interrupted
-            if self.on_colab_kaggle:
+            if self.on_colab_kaggle and not self.testing:
                 self.load_spawn_weights(model)
 
             self.model = model
diff --git a/tests/callbacks/test_model_checkpoint.py b/tests/callbacks/test_model_checkpoint.py
index b5cb7ca0c756e..1091a4cf3a8dd 100644
--- a/tests/callbacks/test_model_checkpoint.py
+++ b/tests/callbacks/test_model_checkpoint.py
@@ -15,7 +15,9 @@
 
 @pytest.mark.parametrize('save_top_k', [-1, 0, 1, 2])
 def test_model_checkpoint_with_non_string_input(tmpdir, save_top_k):
-    """ Test that None in checkpoint callback is valid and that chkp_path is set correctly """
+    """
+    Test that None in checkpoint callback is valid and that chkp_path is set correctly
+    """
     tutils.reset_seed()
     model = EvalModelTemplate()