make style for MLUs

tests/test_custom_models.py

@@ -956,8 +956,8 @@ def test_disable_adapters_with_merging(self, test_name, model_id, config_cls, co
         # check that there is a difference in results after training
         assert not torch.allclose(outputs_before, outputs_after, atol=atol, rtol=rtol)
 
-        if self.torch_device in ['mlu'] and model_id in ['Conv2d']:
-            atol, rtol = 1e-3, 1e-2  # MLU 
+        if self.torch_device in ["mlu"] and model_id in ["Conv2d"]:
+            atol, rtol = 1e-3, 1e-2  # MLU
 
         # unmerged or merged should make no difference
         assert torch.allclose(outputs_after, outputs_unmerged, atol=atol, rtol=rtol)

tests/test_lora_megatron.py

@@ -26,6 +26,7 @@
 
 from .testing_utils import require_torch_gpu
 
+
 def is_megatron_available() -> bool:
     return importlib.util.find_spec("megatron") is not None
 

tests/testing_common.py

@@ -561,8 +561,8 @@ def _test_merge_layers(self, model_id, config_cls, config_kwargs):
         logits_merged_unloaded = model(**dummy_input)[0]
 
         atol, rtol = 1e-4, 1e-4
-        if self.torch_device in ['mlu']:
-            atol, rtol = 1e-3, 1e-3  # MLU 
+        if self.torch_device in ["mlu"]:
+            atol, rtol = 1e-3, 1e-3  # MLU
         if (config.peft_type == "IA3") and (model_id == "Conv2d"):
             # for some reason, the IA³ Conv2d introduces a larger error
             atol, rtol = 0.3, 0.01
@@ -691,7 +691,7 @@ def _test_safe_merge(self, model_id, config_cls, config_kwargs):
         model = get_peft_model(model, config).eval()
         logits_peft = model(**inputs)[0]
 
-        atol, rtol = 1e-6, 1e-6 # default
+        atol, rtol = 1e-6, 1e-6  # default
         # Initializing with LN tuning cannot be configured to change the outputs (unlike init_lora_weights=False)
         if not issubclass(config_cls, LNTuningConfig):
             # sanity check that the logits are different
@@ -700,8 +700,8 @@ def _test_safe_merge(self, model_id, config_cls, config_kwargs):
         model_unloaded = model.merge_and_unload(safe_merge=True)
         logits_unloaded = model_unloaded(**inputs)[0]
 
-        if self.torch_device in ['mlu']:
-            atol, rtol = 1e-3, 1e-3  # MLU 
+        if self.torch_device in ["mlu"]:
+            atol, rtol = 1e-3, 1e-3  # MLU
         # check that the logits are the same after unloading
         assert torch.allclose(logits_peft, logits_unloaded, atol=atol, rtol=rtol)