From ecaf07f6739f73ba83b09d970e04b5424e1800d6 Mon Sep 17 00:00:00 2001 From: Daniel Gu Date: Tue, 16 May 2023 13:00:58 -0700 Subject: [PATCH] make style --- tests/pipelines/unidiffuser/test_unidiffuser.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/tests/pipelines/unidiffuser/test_unidiffuser.py b/tests/pipelines/unidiffuser/test_unidiffuser.py index 0d6545f112..c15969cb6d 100644 --- a/tests/pipelines/unidiffuser/test_unidiffuser.py +++ b/tests/pipelines/unidiffuser/test_unidiffuser.py @@ -540,7 +540,7 @@ class UniDiffuserPipelineSlowTests(unittest.TestCase): for latent_name, latent_tensor in latents.items(): inputs[latent_name] = latent_tensor return inputs - + def get_fixed_latents(self, device, seed=0): if type(device) == str: device = torch.device(device) @@ -584,7 +584,7 @@ class UniDiffuserPipelineSlowTests(unittest.TestCase): assert np.abs(image_slice.flatten() - expected_img_slice).max() < 1e-3 expected_text_prefix = "A living room" - assert text[0][:len(expected_text_prefix)] == expected_text_prefix + assert text[0][: len(expected_text_prefix)] == expected_text_prefix def test_unidiffuser_default_text2img_v1(self): pipe = UniDiffuserPipeline.from_pretrained("dg845/unidiffuser-diffusers") @@ -614,7 +614,7 @@ class UniDiffuserPipelineSlowTests(unittest.TestCase): text = sample.text expected_text_prefix = "T CL CL CL " - assert text[0][:len(expected_text_prefix)] == expected_text_prefix + assert text[0][: len(expected_text_prefix)] == expected_text_prefix def test_unidiffuser_default_joint_v1_fp16(self): pipe = UniDiffuserPipeline.from_pretrained("dg845/unidiffuser-diffusers", torch_dtype=torch.float16) @@ -639,7 +639,7 @@ class UniDiffuserPipelineSlowTests(unittest.TestCase): assert np.abs(image_slice.flatten() - expected_img_slice).max() < 1e-3 expected_text_prefix = "A living room" - assert text[0][:len(expected_text_prefix)] == expected_text_prefix + assert text[0][: len(expected_text_prefix)] == expected_text_prefix def test_unidiffuser_default_text2img_v1_fp16(self): pipe = UniDiffuserPipeline.from_pretrained("dg845/unidiffuser-diffusers", torch_dtype=torch.float16) @@ -671,4 +671,4 @@ class UniDiffuserPipelineSlowTests(unittest.TestCase): print(f"Text: {text}") expected_text_prefix = "T CL CL CL " - assert text[0][:len(expected_text_prefix)] == expected_text_prefix + assert text[0][: len(expected_text_prefix)] == expected_text_prefix