make style

Author: hlky

src/diffusers/utils/testing_utils.py

@@ -1093,9 +1093,9 @@ def _is_torch_fp64_available(device):
         "default": None,
     }
     BACKEND_MAX_MEMORY_ALLOCATED = {
-       "cuda": torch.cuda.max_memory_allocated,
-       "xpu": torch.xpu.max_memory_allocated,
-       "default": 0,
+        "cuda": torch.cuda.max_memory_allocated,
+        "xpu": torch.xpu.max_memory_allocated,
+        "default": 0,
     }
 
 
@@ -1198,5 +1198,3 @@ def update_mapping_from_spec(device_fn_dict: Dict[str, Callable], attribute_name
         update_mapping_from_spec(BACKEND_RESET_PEAK_MEMORY_STATS, "RESET_PEAK_MEMORY_STATS_FN")
         update_mapping_from_spec(BACKEND_RESET_MAX_MEMORY_ALLOCATED, "RESET_MAX_MEMORY_ALLOCATED_FN")
         update_mapping_from_spec(BACKEND_MAX_MEMORY_ALLOCATED, "MAX_MEMORY_ALLOCATED_FN")
-
-

tests/pipelines/controlnet/test_controlnet.py

@@ -35,6 +35,9 @@
 from diffusers.utils.import_utils import is_xformers_available
 from diffusers.utils.testing_utils import (
     backend_empty_cache,
+    backend_max_memory_allocated,
+    backend_reset_max_memory_allocated,
+    backend_reset_peak_memory_stats,
     enable_full_determinism,
     get_python_version,
     is_torch_compile,

tests/pipelines/deepfloyd_if/test_if_inpainting.py

@@ -124,8 +124,8 @@ def test_if_inpainting(self):
         pipe.unet.set_attn_processor(AttnAddedKVProcessor())
         pipe.enable_model_cpu_offload(device=torch_device)
 
-        backend_reset_max_memory_allocated(torch_device)
         backend_empty_cache(torch_device)
+        backend_reset_max_memory_allocated(torch_device)
         backend_reset_peak_memory_stats(torch_device)
 
         image = floats_tensor((1, 3, 64, 64), rng=random.Random(0)).to(torch_device)

tests/pipelines/deepfloyd_if/test_if_inpainting_superresolution.py

@@ -127,8 +127,8 @@ def test_if_inpainting_superresolution(self):
         pipe.enable_model_cpu_offload(device=torch_device)
 
         # Super resolution test
-        backend_reset_max_memory_allocated(torch_device)
         backend_empty_cache(torch_device)
+        backend_reset_max_memory_allocated(torch_device)
         backend_reset_peak_memory_stats(torch_device)
 
         generator = torch.Generator(device="cpu").manual_seed(0)