style

src/accelerate/accelerator.py

@@ -2583,7 +2583,7 @@ def save_model(
         for param in model.parameters():
             if param.device == torch.device("meta"):
                 raise RuntimeError("You can't save the model since some parameters are on the meta device.")
-        
+
         # get the state_dict of the model
         state_dict = self.get_state_dict(model)
 

tests/test_accelerator.py

@@ -34,6 +34,7 @@ def load_random_weights(model):
     state = torch.nn.Linear(*tuple(model.weight.T.shape)).state_dict()
     model.load_state_dict(state)
 
+
 class ModelForTest(torch.nn.Module):
     def __init__(self):
         super().__init__()
@@ -44,6 +45,7 @@ def __init__(self):
     def forward(self, x):
         return self.linear2(self.batchnorm(self.linear1(x)))
 
+
 class AcceleratorTester(AccelerateTestCase):
     @require_cuda
     def test_accelerator_can_be_reinstantiated(self):