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Unverified Commit edc154da authored by Dhruv Nair's avatar Dhruv Nair Committed by GitHub
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Update Ruff to latest Version (#10919) 

* update

* update

* update

* update
parent 552cd320
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Showing with 184 additions and 184 deletions
tests/pipelines/pag/test_pag_hunyuan_dit.py
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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
View file @ edc154da
......@@ -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:
......
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