@@ -14,21 +14,21 @@ class PretrainedModelsUnitTest(unittest.TestCase):
         self.imagenet_pretrained_models = ["resnet50", "repvgg_a0", "regnetY800"]
 
     def test_pretrained_resnet50_imagenet(self):
-        trainer = Trainer('imagenet_pretrained_resnet50_unit_test', model_checkpoints_location='local',
+        trainer = Trainer('imagenet_pretrained_resnet50_unit_test',
                           multi_gpu=MultiGPUMode.OFF)
         model = models.get("resnet50", pretrained_weights="imagenet")
         trainer.test(model=model, test_loader=classification_test_dataloader(), test_metrics_list=[Accuracy()],
                      metrics_progress_verbose=True)
 
     def test_pretrained_regnetY800_imagenet(self):
-        trainer = Trainer('imagenet_pretrained_regnetY800_unit_test', model_checkpoints_location='local',
+        trainer = Trainer('imagenet_pretrained_regnetY800_unit_test',
                           multi_gpu=MultiGPUMode.OFF)
         model = models.get("regnetY800", pretrained_weights="imagenet")
         trainer.test(model=model, test_loader=classification_test_dataloader(), test_metrics_list=[Accuracy()],
                      metrics_progress_verbose=True)
 
     def test_pretrained_repvgg_a0_imagenet(self):
-        trainer = Trainer('imagenet_pretrained_repvgg_a0_unit_test', model_checkpoints_location='local',
+        trainer = Trainer('imagenet_pretrained_repvgg_a0_unit_test',
                           multi_gpu=MultiGPUMode.OFF)
         model = models.get("repvgg_a0", pretrained_weights="imagenet", arch_params={"build_residual_branches": True})
         trainer.test(model=model, test_loader=classification_test_dataloader(), test_metrics_list=[Accuracy()],