Update Ruff to latest Version (#10919)

* update

* update

* update

* update

tests/pipelines/pag/test_pag_hunyuan_dit.py

@@ -177,15 +177,15 @@ class HunyuanDiTPAGPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
         image_disabled = pipe(**inputs)[0]
         image_slice_disabled = image_disabled[0, -3:, -3:, -1]
 
-        assert np.allclose(
-            original_image_slice, image_slice_fused, atol=1e-2, rtol=1e-2
-        ), "Fusion of QKV projections shouldn't affect the outputs."
-        assert np.allclose(
-            image_slice_fused, image_slice_disabled, atol=1e-2, rtol=1e-2
-        ), "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
-        assert np.allclose(
-            original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2
-        ), "Original outputs should match when fused QKV projections are disabled."
+        assert np.allclose(original_image_slice, image_slice_fused, atol=1e-2, rtol=1e-2), (
+            "Fusion of QKV projections shouldn't affect the outputs."
+        )
+        assert np.allclose(image_slice_fused, image_slice_disabled, atol=1e-2, rtol=1e-2), (
+            "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
+        )
+        assert np.allclose(original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2), (
+            "Original outputs should match when fused QKV projections are disabled."
+        )
 
     def test_pag_disable_enable(self):
         device = "cpu"  # ensure determinism for the device-dependent torch.Generator
@@ -198,9 +198,9 @@ class HunyuanDiTPAGPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
 
         inputs = self.get_dummy_inputs(device)
         del inputs["pag_scale"]
-        assert (
-            "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters
-        ), f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        assert "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters, (
+            f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        )
         out = pipe_sd(**inputs).images[0, -3:, -3:, -1]
 
         components = self.get_dummy_components()

tests/pipelines/pag/test_pag_kolors.py

@@ -140,9 +140,9 @@ class KolorsPAGPipelineFastTests(
 
         inputs = self.get_dummy_inputs(device)
         del inputs["pag_scale"]
-        assert (
-            "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters
-        ), f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        assert "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters, (
+            f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        )
         out = pipe_sd(**inputs).images[0, -3:, -3:, -1]
 
         # pag disabled with pag_scale=0.0

tests/pipelines/pag/test_pag_pixart_sigma.py

@@ -120,9 +120,9 @@ class PixArtSigmaPAGPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
 
         inputs = self.get_dummy_inputs(device)
         del inputs["pag_scale"]
-        assert (
-            "pag_scale" not in inspect.signature(pipe.__call__).parameters
-        ), f"`pag_scale` should not be a call parameter of the base pipeline {pipe.__class__.__name__}."
+        assert "pag_scale" not in inspect.signature(pipe.__call__).parameters, (
+            f"`pag_scale` should not be a call parameter of the base pipeline {pipe.__class__.__name__}."
+        )
         out = pipe(**inputs).images[0, -3:, -3:, -1]
 
         # pag disabled with pag_scale=0.0

tests/pipelines/pag/test_pag_sana.py

@@ -268,9 +268,9 @@ class SanaPAGPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
 
         inputs = self.get_dummy_inputs(device)
         del inputs["pag_scale"]
-        assert (
-            "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters
-        ), f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        assert "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters, (
+            f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        )
         out = pipe_sd(**inputs).images[0, -3:, -3:, -1]
 
         components = self.get_dummy_components()

tests/pipelines/pag/test_pag_sd.py

@@ -154,9 +154,9 @@ class StableDiffusionPAGPipelineFastTests(
 
         inputs = self.get_dummy_inputs(device)
         del inputs["pag_scale"]
-        assert (
-            "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters
-        ), f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        assert "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters, (
+            f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        )
         out = pipe_sd(**inputs).images[0, -3:, -3:, -1]
 
         # pag disabled with pag_scale=0.0
@@ -328,9 +328,9 @@ class StableDiffusionPAGPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.58251953, 0.5722656, 0.5683594, 0.55029297, 0.52001953, 0.52001953, 0.49951172, 0.45410156, 0.50146484]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )
 
     def test_pag_uncond(self):
         pipeline = AutoPipelineForText2Image.from_pretrained(self.repo_id, enable_pag=True, torch_dtype=torch.float16)
@@ -345,6 +345,6 @@ class StableDiffusionPAGPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.5986328, 0.52441406, 0.3972168, 0.4741211, 0.34985352, 0.22705078, 0.4128418, 0.2866211, 0.31713867]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )

tests/pipelines/pag/test_pag_sd3.py

@@ -170,9 +170,9 @@ class StableDiffusion3PAGPipelineFastTests(unittest.TestCase, PipelineTesterMixi
         # TODO (sayakpaul): will refactor this once `fuse_qkv_projections()` has been added
         # to the pipeline level.
         pipe.transformer.fuse_qkv_projections()
-        assert check_qkv_fusion_processors_exist(
-            pipe.transformer
-        ), "Something wrong with the fused attention processors. Expected all the attention processors to be fused."
+        assert check_qkv_fusion_processors_exist(pipe.transformer), (
+            "Something wrong with the fused attention processors. Expected all the attention processors to be fused."
+        )
         assert check_qkv_fusion_matches_attn_procs_length(
             pipe.transformer, pipe.transformer.original_attn_processors
         ), "Something wrong with the attention processors concerning the fused QKV projections."
@@ -186,15 +186,15 @@ class StableDiffusion3PAGPipelineFastTests(unittest.TestCase, PipelineTesterMixi
         image = pipe(**inputs).images
         image_slice_disabled = image[0, -3:, -3:, -1]
 
-        assert np.allclose(
-            original_image_slice, image_slice_fused, atol=1e-3, rtol=1e-3
-        ), "Fusion of QKV projections shouldn't affect the outputs."
-        assert np.allclose(
-            image_slice_fused, image_slice_disabled, atol=1e-3, rtol=1e-3
-        ), "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
-        assert np.allclose(
-            original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2
-        ), "Original outputs should match when fused QKV projections are disabled."
+        assert np.allclose(original_image_slice, image_slice_fused, atol=1e-3, rtol=1e-3), (
+            "Fusion of QKV projections shouldn't affect the outputs."
+        )
+        assert np.allclose(image_slice_fused, image_slice_disabled, atol=1e-3, rtol=1e-3), (
+            "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
+        )
+        assert np.allclose(original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2), (
+            "Original outputs should match when fused QKV projections are disabled."
+        )
 
     def test_pag_disable_enable(self):
         device = "cpu"  # ensure determinism for the device-dependent torch.Generator
@@ -207,9 +207,9 @@ class StableDiffusion3PAGPipelineFastTests(unittest.TestCase, PipelineTesterMixi
 
         inputs = self.get_dummy_inputs(device)
         del inputs["pag_scale"]
-        assert (
-            "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters
-        ), f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        assert "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters, (
+            f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        )
         out = pipe_sd(**inputs).images[0, -3:, -3:, -1]
 
         components = self.get_dummy_components()

tests/pipelines/pag/test_pag_sd3_img2img.py

@@ -149,9 +149,9 @@ class StableDiffusion3PAGImg2ImgPipelineFastTests(unittest.TestCase, PipelineTes
 
         inputs = self.get_dummy_inputs(device)
         del inputs["pag_scale"]
-        assert (
-            "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters
-        ), f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        assert "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters, (
+            f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        )
         out = pipe_sd(**inputs).images[0, -3:, -3:, -1]
 
         components = self.get_dummy_components()
@@ -254,9 +254,9 @@ class StableDiffusion3PAGImg2ImgPipelineIntegrationTests(unittest.TestCase):
                 0.17822266,
             ]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )
 
     def test_pag_uncond(self):
         pipeline = AutoPipelineForImage2Image.from_pretrained(
@@ -272,6 +272,6 @@ class StableDiffusion3PAGImg2ImgPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.1508789, 0.16210938, 0.17138672, 0.16210938, 0.17089844, 0.16137695, 0.16235352, 0.16430664, 0.16455078]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )

tests/pipelines/pag/test_pag_sd_img2img.py

@@ -161,9 +161,9 @@ class StableDiffusionPAGImg2ImgPipelineFastTests(
 
         inputs = self.get_dummy_inputs(device)
         del inputs["pag_scale"]
-        assert (
-            "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters
-        ), f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        assert "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters, (
+            f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        )
         out = pipe_sd(**inputs).images[0, -3:, -3:, -1]
 
         # pag disabled with pag_scale=0.0
@@ -267,9 +267,9 @@ class StableDiffusionPAGImg2ImgPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.58251953, 0.5722656, 0.5683594, 0.55029297, 0.52001953, 0.52001953, 0.49951172, 0.45410156, 0.50146484]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )
 
     def test_pag_uncond(self):
         pipeline = AutoPipelineForImage2Image.from_pretrained(self.repo_id, enable_pag=True, torch_dtype=torch.float16)
@@ -285,6 +285,6 @@ class StableDiffusionPAGImg2ImgPipelineIntegrationTests(unittest.TestCase):
             [0.5986328, 0.52441406, 0.3972168, 0.4741211, 0.34985352, 0.22705078, 0.4128418, 0.2866211, 0.31713867]
         )
 
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )

tests/pipelines/pag/test_pag_sd_inpaint.py

@@ -302,9 +302,9 @@ class StableDiffusionPAGPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.38793945, 0.4111328, 0.47924805, 0.39208984, 0.4165039, 0.41674805, 0.37060547, 0.36791992, 0.40625]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )
 
     def test_pag_uncond(self):
         pipeline = AutoPipelineForInpainting.from_pretrained(self.repo_id, enable_pag=True, torch_dtype=torch.float16)
@@ -319,6 +319,6 @@ class StableDiffusionPAGPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.3876953, 0.40356445, 0.4934082, 0.39697266, 0.41674805, 0.41015625, 0.375, 0.36914062, 0.40649414]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )

tests/pipelines/pag/test_pag_sdxl.py

@@ -167,9 +167,9 @@ class StableDiffusionXLPAGPipelineFastTests(
 
         inputs = self.get_dummy_inputs(device)
         del inputs["pag_scale"]
-        assert (
-            "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters
-        ), f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        assert "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters, (
+            f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        )
         out = pipe_sd(**inputs).images[0, -3:, -3:, -1]
 
         # pag disabled with pag_scale=0.0
@@ -331,9 +331,9 @@ class StableDiffusionXLPAGPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.3123679, 0.31725878, 0.32026544, 0.327533, 0.3266391, 0.3303998, 0.33544615, 0.34181812, 0.34102726]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )
 
     def test_pag_uncond(self):
         pipeline = AutoPipelineForText2Image.from_pretrained(self.repo_id, enable_pag=True, torch_dtype=torch.float16)
@@ -348,6 +348,6 @@ class StableDiffusionXLPAGPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.47400922, 0.48650584, 0.4839625, 0.4724013, 0.4890427, 0.49544555, 0.51707107, 0.54299414, 0.5224372]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )

tests/pipelines/pag/test_pag_sdxl_img2img.py

@@ -215,9 +215,9 @@ class StableDiffusionXLPAGImg2ImgPipelineFastTests(
 
         inputs = self.get_dummy_inputs(device)
         del inputs["pag_scale"]
-        assert (
-            "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters
-        ), f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        assert "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters, (
+            f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        )
         out = pipe_sd(**inputs).images[0, -3:, -3:, -1]
 
         # pag disabled with pag_scale=0.0
@@ -316,9 +316,9 @@ class StableDiffusionXLPAGImg2ImgPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.20301354, 0.21078318, 0.2021082, 0.20277798, 0.20681083, 0.19562206, 0.20121682, 0.21562952, 0.21277016]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )
 
     def test_pag_uncond(self):
         pipeline = AutoPipelineForImage2Image.from_pretrained(self.repo_id, enable_pag=True, torch_dtype=torch.float16)
@@ -333,6 +333,6 @@ class StableDiffusionXLPAGImg2ImgPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.21303111, 0.22188407, 0.2124992, 0.21365267, 0.18823743, 0.17569828, 0.21113116, 0.19419771, 0.18919235]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )

tests/pipelines/pag/test_pag_sdxl_inpaint.py

@@ -220,9 +220,9 @@ class StableDiffusionXLPAGInpaintPipelineFastTests(
 
         inputs = self.get_dummy_inputs(device)
         del inputs["pag_scale"]
-        assert (
-            "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters
-        ), f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        assert "pag_scale" not in inspect.signature(pipe_sd.__call__).parameters, (
+            f"`pag_scale` should not be a call parameter of the base pipeline {pipe_sd.__class__.__name__}."
+        )
         out = pipe_sd(**inputs).images[0, -3:, -3:, -1]
 
         # pag disabled with pag_scale=0.0
@@ -322,9 +322,9 @@ class StableDiffusionXLPAGInpaintPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.41385046, 0.39608297, 0.4360491, 0.26872507, 0.32187328, 0.4242474, 0.2603805, 0.34167895, 0.46561807]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )
 
     def test_pag_uncond(self):
         pipeline = AutoPipelineForInpainting.from_pretrained(self.repo_id, enable_pag=True, torch_dtype=torch.float16)
@@ -339,6 +339,6 @@ class StableDiffusionXLPAGInpaintPipelineIntegrationTests(unittest.TestCase):
         expected_slice = np.array(
             [0.41597816, 0.39302617, 0.44287828, 0.2687074, 0.28315824, 0.40582314, 0.20877528, 0.2380802, 0.39447647]
         )
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-3
-        ), f"output is different from expected, {image_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-3, (
+            f"output is different from expected, {image_slice.flatten()}"
+        )

tests/pipelines/pixart_sigma/test_pixart.py

@@ -260,9 +260,9 @@ class PixArtSigmaPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
         # TODO (sayakpaul): will refactor this once `fuse_qkv_projections()` has been added
         # to the pipeline level.
         pipe.transformer.fuse_qkv_projections()
-        assert check_qkv_fusion_processors_exist(
-            pipe.transformer
-        ), "Something wrong with the fused attention processors. Expected all the attention processors to be fused."
+        assert check_qkv_fusion_processors_exist(pipe.transformer), (
+            "Something wrong with the fused attention processors. Expected all the attention processors to be fused."
+        )
         assert check_qkv_fusion_matches_attn_procs_length(
             pipe.transformer, pipe.transformer.original_attn_processors
         ), "Something wrong with the attention processors concerning the fused QKV projections."
@@ -276,15 +276,15 @@ class PixArtSigmaPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
         image = pipe(**inputs).images
         image_slice_disabled = image[0, -3:, -3:, -1]
 
-        assert np.allclose(
-            original_image_slice, image_slice_fused, atol=1e-3, rtol=1e-3
-        ), "Fusion of QKV projections shouldn't affect the outputs."
-        assert np.allclose(
-            image_slice_fused, image_slice_disabled, atol=1e-3, rtol=1e-3
-        ), "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
-        assert np.allclose(
-            original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2
-        ), "Original outputs should match when fused QKV projections are disabled."
+        assert np.allclose(original_image_slice, image_slice_fused, atol=1e-3, rtol=1e-3), (
+            "Fusion of QKV projections shouldn't affect the outputs."
+        )
+        assert np.allclose(image_slice_fused, image_slice_disabled, atol=1e-3, rtol=1e-3), (
+            "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
+        )
+        assert np.allclose(original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2), (
+            "Original outputs should match when fused QKV projections are disabled."
+        )
 
 
 @slow

tests/pipelines/shap_e/test_shap_e_img2img.py

@@ -266,7 +266,7 @@ class ShapEImg2ImgPipelineIntegrationTests(unittest.TestCase):
 
     def test_shap_e_img2img(self):
         input_image = load_image(
-            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main" "/shap_e/corgi.png"
+            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/shap_e/corgi.png"
         )
         expected_image = load_numpy(
             "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"

tests/pipelines/stable_cascade/test_stable_cascade_combined.py

@@ -198,12 +198,12 @@ class StableCascadeCombinedPipelineFastTests(PipelineTesterMixin, unittest.TestC
         assert image.shape == (1, 128, 128, 3)
 
         expected_slice = np.array([0.0, 1.0, 0.0, 1.0, 1.0, 0.0, 1.0, 1.0, 0.0])
-        assert (
-            np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
-        ), f" expected_slice {expected_slice}, but got {image_slice.flatten()}"
-        assert (
-            np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2
-        ), f" expected_slice {expected_slice}, but got {image_from_tuple_slice.flatten()}"
+        assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2, (
+            f" expected_slice {expected_slice}, but got {image_slice.flatten()}"
+        )
+        assert np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2, (
+            f" expected_slice {expected_slice}, but got {image_from_tuple_slice.flatten()}"
+        )
 
     @require_torch_accelerator
     def test_offloads(self):

tests/pipelines/stable_diffusion/test_stable_diffusion.py

@@ -293,15 +293,15 @@ class StableDiffusionPipelineFastTests(
         inputs["sigmas"] = sigma_schedule
         output_sigmas = sd_pipe(**inputs).images
 
-        assert (
-            np.abs(output_sigmas.flatten() - output_ts.flatten()).max() < 1e-3
-        ), "ays timesteps and ays sigmas should have the same outputs"
-        assert (
-            np.abs(output.flatten() - output_ts.flatten()).max() > 1e-3
-        ), "use ays timesteps should have different outputs"
-        assert (
-            np.abs(output.flatten() - output_sigmas.flatten()).max() > 1e-3
-        ), "use ays sigmas should have different outputs"
+        assert np.abs(output_sigmas.flatten() - output_ts.flatten()).max() < 1e-3, (
+            "ays timesteps and ays sigmas should have the same outputs"
+        )
+        assert np.abs(output.flatten() - output_ts.flatten()).max() > 1e-3, (
+            "use ays timesteps should have different outputs"
+        )
+        assert np.abs(output.flatten() - output_sigmas.flatten()).max() > 1e-3, (
+            "use ays sigmas should have different outputs"
+        )
 
     def test_stable_diffusion_prompt_embeds(self):
         components = self.get_dummy_components()
@@ -656,9 +656,9 @@ class StableDiffusionPipelineFastTests(
         sd_pipe.enable_freeu(s1=0.9, s2=0.2, b1=1.2, b2=1.4)
         output_freeu = sd_pipe(prompt, num_inference_steps=1, output_type="np", generator=torch.manual_seed(0)).images
 
-        assert not np.allclose(
-            output[0, -3:, -3:, -1], output_freeu[0, -3:, -3:, -1]
-        ), "Enabling of FreeU should lead to different results."
+        assert not np.allclose(output[0, -3:, -3:, -1], output_freeu[0, -3:, -3:, -1]), (
+            "Enabling of FreeU should lead to different results."
+        )
 
     def test_freeu_disabled(self):
         components = self.get_dummy_components()
@@ -681,9 +681,9 @@ class StableDiffusionPipelineFastTests(
             prompt, num_inference_steps=1, output_type="np", generator=torch.manual_seed(0)
         ).images
 
-        assert np.allclose(
-            output[0, -3:, -3:, -1], output_no_freeu[0, -3:, -3:, -1]
-        ), "Disabling of FreeU should lead to results similar to the default pipeline results."
+        assert np.allclose(output[0, -3:, -3:, -1], output_no_freeu[0, -3:, -3:, -1]), (
+            "Disabling of FreeU should lead to results similar to the default pipeline results."
+        )
 
     def test_fused_qkv_projections(self):
         device = "cpu"  # ensure determinism for the device-dependent torch.Generator
@@ -706,15 +706,15 @@ class StableDiffusionPipelineFastTests(
         image = sd_pipe(**inputs).images
         image_slice_disabled = image[0, -3:, -3:, -1]
 
-        assert np.allclose(
-            original_image_slice, image_slice_fused, atol=1e-2, rtol=1e-2
-        ), "Fusion of QKV projections shouldn't affect the outputs."
-        assert np.allclose(
-            image_slice_fused, image_slice_disabled, atol=1e-2, rtol=1e-2
-        ), "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
-        assert np.allclose(
-            original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2
-        ), "Original outputs should match when fused QKV projections are disabled."
+        assert np.allclose(original_image_slice, image_slice_fused, atol=1e-2, rtol=1e-2), (
+            "Fusion of QKV projections shouldn't affect the outputs."
+        )
+        assert np.allclose(image_slice_fused, image_slice_disabled, atol=1e-2, rtol=1e-2), (
+            "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
+        )
+        assert np.allclose(original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2), (
+            "Original outputs should match when fused QKV projections are disabled."
+        )
 
     def test_pipeline_interrupt(self):
         components = self.get_dummy_components()

tests/pipelines/stable_diffusion_3/test_pipeline_stable_diffusion_3.py

@@ -171,9 +171,9 @@ class StableDiffusion3PipelineFastTests(unittest.TestCase, PipelineTesterMixin):
         # TODO (sayakpaul): will refactor this once `fuse_qkv_projections()` has been added
         # to the pipeline level.
         pipe.transformer.fuse_qkv_projections()
-        assert check_qkv_fusion_processors_exist(
-            pipe.transformer
-        ), "Something wrong with the fused attention processors. Expected all the attention processors to be fused."
+        assert check_qkv_fusion_processors_exist(pipe.transformer), (
+            "Something wrong with the fused attention processors. Expected all the attention processors to be fused."
+        )
         assert check_qkv_fusion_matches_attn_procs_length(
             pipe.transformer, pipe.transformer.original_attn_processors
         ), "Something wrong with the attention processors concerning the fused QKV projections."
@@ -187,15 +187,15 @@ class StableDiffusion3PipelineFastTests(unittest.TestCase, PipelineTesterMixin):
         image = pipe(**inputs).images
         image_slice_disabled = image[0, -3:, -3:, -1]
 
-        assert np.allclose(
-            original_image_slice, image_slice_fused, atol=1e-3, rtol=1e-3
-        ), "Fusion of QKV projections shouldn't affect the outputs."
-        assert np.allclose(
-            image_slice_fused, image_slice_disabled, atol=1e-3, rtol=1e-3
-        ), "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
-        assert np.allclose(
-            original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2
-        ), "Original outputs should match when fused QKV projections are disabled."
+        assert np.allclose(original_image_slice, image_slice_fused, atol=1e-3, rtol=1e-3), (
+            "Fusion of QKV projections shouldn't affect the outputs."
+        )
+        assert np.allclose(image_slice_fused, image_slice_disabled, atol=1e-3, rtol=1e-3), (
+            "Outputs, with QKV projection fusion enabled, shouldn't change when fused QKV projections are disabled."
+        )
+        assert np.allclose(original_image_slice, image_slice_disabled, atol=1e-2, rtol=1e-2), (
+            "Original outputs should match when fused QKV projections are disabled."
+        )
 
     def test_skip_guidance_layers(self):
         components = self.get_dummy_components()

tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl.py

@@ -242,15 +242,15 @@ class StableDiffusionXLPipelineFastTests(
         inputs["sigmas"] = sigma_schedule
         output_sigmas = sd_pipe(**inputs).images
 
-        assert (
-            np.abs(output_sigmas.flatten() - output_ts.flatten()).max() < 1e-3
-        ), "ays timesteps and ays sigmas should have the same outputs"
-        assert (
-            np.abs(output.flatten() - output_ts.flatten()).max() > 1e-3
-        ), "use ays timesteps should have different outputs"
-        assert (
-            np.abs(output.flatten() - output_sigmas.flatten()).max() > 1e-3
-        ), "use ays sigmas should have different outputs"
+        assert np.abs(output_sigmas.flatten() - output_ts.flatten()).max() < 1e-3, (
+            "ays timesteps and ays sigmas should have the same outputs"
+        )
+        assert np.abs(output.flatten() - output_ts.flatten()).max() > 1e-3, (
+            "use ays timesteps should have different outputs"
+        )
+        assert np.abs(output.flatten() - output_sigmas.flatten()).max() > 1e-3, (
+            "use ays sigmas should have different outputs"
+        )
 
     def test_ip_adapter(self):
         expected_pipe_slice = None
@@ -742,9 +742,9 @@ class StableDiffusionXLPipelineFastTests(
             inputs_1 = {**inputs, **{"denoising_end": split_1, "output_type": "latent"}}
             latents = pipe_1(**inputs_1).images[0]
 
-            assert (
-                expected_steps_1 == done_steps
-            ), f"Failure with {scheduler_cls.__name__} and {num_steps} and {split_1} and {split_2}"
+            assert expected_steps_1 == done_steps, (
+                f"Failure with {scheduler_cls.__name__} and {num_steps} and {split_1} and {split_2}"
+            )
 
             with self.assertRaises(ValueError) as cm:
                 inputs_2 = {
@@ -771,9 +771,9 @@ class StableDiffusionXLPipelineFastTests(
             pipe_3(**inputs_3).images[0]
 
             assert expected_steps_3 == done_steps[len(expected_steps_1) + len(expected_steps_2) :]
-            assert (
-                expected_steps == done_steps
-            ), f"Failure with {scheduler_cls.__name__} and {num_steps} and {split_1} and {split_2}"
+            assert expected_steps == done_steps, (
+                f"Failure with {scheduler_cls.__name__} and {num_steps} and {split_1} and {split_2}"
+            )
 
         for steps in [7, 11, 20]:
             for split_1, split_2 in zip([0.19, 0.32], [0.81, 0.68]):

tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_inpaint.py

@@ -585,9 +585,9 @@ class StableDiffusionXLInpaintPipelineFastTests(
             inputs_1 = {**inputs, **{"denoising_end": split_1, "output_type": "latent"}}
             latents = pipe_1(**inputs_1).images[0]
 
-            assert (
-                expected_steps_1 == done_steps
-            ), f"Failure with {scheduler_cls.__name__} and {num_steps} and {split_1} and {split_2}"
+            assert expected_steps_1 == done_steps, (
+                f"Failure with {scheduler_cls.__name__} and {num_steps} and {split_1} and {split_2}"
+            )
 
             inputs_2 = {
                 **inputs,
@@ -601,9 +601,9 @@ class StableDiffusionXLInpaintPipelineFastTests(
             pipe_3(**inputs_3).images[0]
 
             assert expected_steps_3 == done_steps[len(expected_steps_1) + len(expected_steps_2) :]
-            assert (
-                expected_steps == done_steps
-            ), f"Failure with {scheduler_cls.__name__} and {num_steps} and {split_1} and {split_2}"
+            assert expected_steps == done_steps, (
+                f"Failure with {scheduler_cls.__name__} and {num_steps} and {split_1} and {split_2}"
+            )
 
         for steps in [7, 11, 20]:
             for split_1, split_2 in zip([0.19, 0.32], [0.81, 0.68]):

tests/pipelines/test_pipelines.py

@@ -167,9 +167,9 @@ class DownloadTests(unittest.TestCase):
             download_requests = [r.method for r in m.request_history]
             assert download_requests.count("HEAD") == 15, "15 calls to files"
             assert download_requests.count("GET") == 17, "15 calls to files + model_info + model_index.json"
-            assert (
-                len(download_requests) == 32
-            ), "2 calls per file (15 files) + send_telemetry, model_info and model_index.json"
+            assert len(download_requests) == 32, (
+                "2 calls per file (15 files) + send_telemetry, model_info and model_index.json"
+            )
 
             with requests_mock.mock(real_http=True) as m:
                 DiffusionPipeline.download(
@@ -179,9 +179,9 @@ class DownloadTests(unittest.TestCase):
             cache_requests = [r.method for r in m.request_history]
             assert cache_requests.count("HEAD") == 1, "model_index.json is only HEAD"
             assert cache_requests.count("GET") == 1, "model info is only GET"
-            assert (
-                len(cache_requests) == 2
-            ), "We should call only `model_info` to check for _commit hash and `send_telemetry`"
+            assert len(cache_requests) == 2, (
+                "We should call only `model_info` to check for _commit hash and `send_telemetry`"
+            )
 
     def test_less_downloads_passed_object(self):
         with tempfile.TemporaryDirectory() as tmpdirname:
@@ -217,9 +217,9 @@ class DownloadTests(unittest.TestCase):
             assert download_requests.count("HEAD") == 13, "13 calls to files"
             # 17 - 2 because no call to config or model file for `safety_checker`
             assert download_requests.count("GET") == 15, "13 calls to files + model_info + model_index.json"
-            assert (
-                len(download_requests) == 28
-            ), "2 calls per file (13 files) + send_telemetry, model_info and model_index.json"
+            assert len(download_requests) == 28, (
+                "2 calls per file (13 files) + send_telemetry, model_info and model_index.json"
+            )
 
             with requests_mock.mock(real_http=True) as m:
                 DiffusionPipeline.download(
@@ -229,9 +229,9 @@ class DownloadTests(unittest.TestCase):
             cache_requests = [r.method for r in m.request_history]
             assert cache_requests.count("HEAD") == 1, "model_index.json is only HEAD"
             assert cache_requests.count("GET") == 1, "model info is only GET"
-            assert (
-                len(cache_requests) == 2
-            ), "We should call only `model_info` to check for _commit hash and `send_telemetry`"
+            assert len(cache_requests) == 2, (
+                "We should call only `model_info` to check for _commit hash and `send_telemetry`"
+            )
 
     def test_download_only_pytorch(self):
         with tempfile.TemporaryDirectory() as tmpdirname: