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test_failures.txt

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+tests/pipelines/altdiffusion/test_alt_diffusion.py;AltDiffusionPipelineFastTests;test_alt_diffusion_ddim;expected_slice = np.array([0.5746, 0.6042, 0.4882, 0.5009, 0.5430, 0.4577, 0.4965, 0.4813, 0.4757])
+tests/pipelines/altdiffusion/test_alt_diffusion.py;AltDiffusionPipelineFastTests;test_alt_diffusion_pndm;expected_slice = np.array([0.5159, 0.5706, 0.4736, 0.5057, 0.5633, 0.4643, 0.5182, 0.4876, 0.4908])
+tests/pipelines/altdiffusion/test_alt_diffusion.py;AltDiffusionPipelineIntegrationTests;test_alt_diffusion;expected_slice = np.array([0.1010, 0.0800, 0.0794, 0.0885, 0.0843, 0.0762, 0.0769, 0.0729, 0.0586])
+tests/pipelines/altdiffusion/test_alt_diffusion.py;AltDiffusionPipelineIntegrationTests;test_alt_diffusion_fast_ddim;expected_slice = np.array([0.4019, 0.4052, 0.3810, 0.4119, 0.3916, 0.3982, 0.4651, 0.4195, 0.5323])
+tests/pipelines/altdiffusion/test_alt_diffusion_img2img.py;AltDiffusionImg2ImgPipelineFastTests;test_stable_diffusion_img2img_default_case;expected_slice = np.array([0.4129, 0.3866, 0.4088, 0.4782, 0.4657, 0.4139, 0.4142, 0.4715, 0.4570])
+tests/pipelines/altdiffusion/test_alt_diffusion_img2img.py;AltDiffusionImg2ImgPipelineFastTests;test_stable_diffusion_img2img_pipeline_multiple_of_8;expected_slice = np.array([0.9358, 0.9397, 0.9599, 0.9901, 1.0000, 1.0000, 0.9882, 1.0000, 1.0000])
+tests/pipelines/ddim/test_ddim.py;DDIMPipelineIntegrationTests;test_inference_cifar10;expected_slice = np.array([0.2060, 0.2042, 0.2022, 0.2193, 0.2147, 0.2111, 0.2472, 0.2447, 0.2388])
+tests/pipelines/ddim/test_ddim.py;DDIMPipelineIntegrationTests;test_inference_ema_bedroom;expected_slice = np.array([0.1547, 0.1562, 0.1596, 0.1565, 0.1570, 0.1586, 0.1555, 0.1550, 0.1575])
+tests/pipelines/ddpm/test_ddpm.py;DDPMPipelineFastTests;test_inference;expected_slice = np.array([5.5886e-01, 7.0888e-01, 2.6321e-01, 6.8414e-01, 8.2970e-05, 9.9992e-01,
+        1.9726e-01, 8.2970e-05, 8.0121e-02])
+tests/pipelines/ddpm/test_ddpm.py;DDPMPipelineIntegrationTests;test_inference_cifar10;expected_slice = np.array([0.4454, 0.2025, 0.0315, 0.3023, 0.2574, 0.1031, 0.0953, 0.1604, 0.2020])
+tests/pipelines/karras_ve/test_karras_ve.py;KarrasVePipelineFastTests;test_inference;expected_slice = np.array([0., 1., 0., 0., 0., 1., 0., 0., 0.])
+tests/pipelines/karras_ve/test_karras_ve.py;KarrasVePipelineIntegrationTests;test_inference;expected_slice = np.array([0.5780, 0.5811, 0.5924, 0.5809, 0.5870, 0.5886, 0.5861, 0.5802, 0.5860])
+tests/pipelines/latent_diffusion/test_latent_diffusion.py;LDMTextToImagePipelineFastTests;test_inference_text2img;expected_slice = np.array([0.5945, 0.6408, 0.5551, 0.5123, 0.6964, 0.3696, 0.5930, 0.6080, 0.4933])
+tests/pipelines/latent_diffusion/test_latent_diffusion_superresolution.py;LDMSuperResolutionPipelineFastTests;test_inference_superresolution;expected_slice = np.array([0.8678, 0.8245, 0.6382, 0.6831, 0.4385, 0.5600, 0.4641, 0.6202, 0.5150])
+tests/pipelines/latent_diffusion/test_latent_diffusion_superresolution.py;LDMSuperResolutionPipelineIntegrationTests;test_inference_superresolution;expected_slice = np.array([0.7644, 0.7679, 0.7642, 0.7633, 0.7666, 0.7560, 0.7425, 0.7257, 0.6907])
+tests/pipelines/latent_diffusion/test_latent_diffusion_uncond.py;LDMPipelineFastTests;test_inference_uncond;expected_slice = np.array([0.8512, 0.8180, 0.6411, 0.6808, 0.4465, 0.5618, 0.4600, 0.6231, 0.5172])
+tests/pipelines/latent_diffusion/test_latent_diffusion_uncond.py;LDMPipelineIntegrationTests;test_inference_uncond;expected_slice = np.array([0.4399, 0.4497, 0.4682, 0.4740, 0.4359, 0.4581, 0.4509, 0.4341, 0.4447])
+tests/pipelines/paint_by_example/test_paint_by_example.py;PaintByExamplePipelineFastTests;test_paint_by_example_inpaint;expected_slice = np.array([0.4701, 0.5555, 0.3994, 0.5107, 0.5691, 0.4517, 0.5125, 0.4769, 0.4539])
+tests/pipelines/paint_by_example/test_paint_by_example.py;PaintByExamplePipelineIntegrationTests;test_paint_by_example;expected_slice = np.array([0.4834, 0.4811, 0.4874, 0.5122, 0.5081, 0.5144, 0.5291, 0.5290, 0.5374])
+tests/pipelines/pndm/test_pndm.py;PNDMPipelineFastTests;test_inference;expected_slice = np.array([1., 1., 0., 1., 0., 1., 0., 0., 0.])
+tests/pipelines/pndm/test_pndm.py;PNDMPipelineIntegrationTests;test_inference_cifar10;expected_slice = np.array([0.1583, 0.1483, 0.1431, 0.1488, 0.1277, 0.1416, 0.1339, 0.1248, 0.1277])
+tests/pipelines/repaint/test_repaint.py;RepaintPipelineFastTests;test_repaint;expected_slice = np.array([1.0000, 0.5426, 0.5497, 0.2200, 1.0000, 1.0000, 0.5623, 1.0000, 0.6274])
+tests/pipelines/score_sde_ve/test_score_sde_ve.py;ScoreSdeVeipelineFastTests;test_inference;expected_slice = np.array([0., 1., 0., 0., 0., 1., 0., 0., 0.])
+tests/pipelines/score_sde_ve/test_score_sde_ve.py;ScoreSdeVePipelineIntegrationTests;test_inference;expected_slice = np.array([0., 1., 1., 1., 1., 1., 1., 0., 0.])
+tests/pipelines/stable_diffusion/test_cycle_diffusion.py;CycleDiffusionPipelineFastTests;test_stable_diffusion_cycle;expected_slice = np.array([0.4448, 0.4946, 0.4544, 0.6640, 0.5489, 0.4333, 0.5701, 0.5969, 0.5182])
+tests/pipelines/stable_diffusion/test_cycle_diffusion.py;CycleDiffusionPipelineFastTests;test_stable_diffusion_cycle_fp16;expected_slice = np.array([0.3501, 0.4541, 0.4458, 0.4590, 0.5195, 0.4155, 0.5278, 0.5171, 0.4116])
+tests/pipelines/stable_diffusion/test_stable_diffusion.py;StableDiffusionPipelineFastTests;test_stable_diffusion_ddim;expected_slice = np.array([0.5644, 0.6018, 0.4799, 0.5267, 0.5585, 0.4641, 0.5160, 0.4964, 0.4792])
+tests/pipelines/stable_diffusion/test_stable_diffusion.py;StableDiffusionPipelineFastTests;test_stable_diffusion_ddim_factor_8;expected_slice = np.array([0.5524, 0.5626, 0.6069, 0.4727, 0.3860, 0.3995, 0.4613, 0.4328, 0.4269])
+tests/pipelines/stable_diffusion/test_stable_diffusion.py;StableDiffusionPipelineFastTests;test_stable_diffusion_k_euler;expected_slice = np.array([0.4708, 0.5372, 0.4562, 0.5221, 0.5734, 0.4795, 0.5466, 0.5074, 0.5042])
+tests/pipelines/stable_diffusion/test_stable_diffusion.py;StableDiffusionPipelineFastTests;test_stable_diffusion_k_euler_ancestral;expected_slice = np.array([0.4707, 0.5372, 0.4563, 0.5220, 0.5734, 0.4795, 0.5464, 0.5074, 0.5044])
+tests/pipelines/stable_diffusion/test_stable_diffusion.py;StableDiffusionPipelineFastTests;test_stable_diffusion_negative_prompt;expected_slice = np.array([0.5108, 0.5688, 0.4685, 0.5098, 0.5658, 0.4631, 0.5226, 0.4913, 0.4899])
+tests/pipelines/stable_diffusion/test_stable_diffusion.py;StableDiffusionPipelineFastTests;test_stable_diffusion_pndm;expected_slice = np.array([0.5096, 0.5677, 0.4669, 0.5122, 0.5696, 0.4674, 0.5274, 0.4964, 0.4947])
+tests/pipelines/stable_diffusion/test_stable_diffusion_image_variation.py;StableDiffusionImageVariationPipelineFastTests;test_stable_diffusion_img_variation_default_case;expected_slice = np.array([0.5167, 0.5746, 0.4835, 0.4914, 0.5605, 0.4691, 0.5201, 0.4898, 0.4958])
+tests/pipelines/stable_diffusion/test_stable_diffusion_image_variation.py;StableDiffusionImageVariationPipelineFastTests;test_stable_diffusion_img_variation_multiple_images;expected_slice = np.array([0.6568, 0.5470, 0.5684, 0.5444, 0.5945, 0.6221, 0.5508, 0.5531, 0.5263])
+tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py;StableDiffusionImg2ImgPipelineFastTests;test_stable_diffusion_img2img_default_case;expected_slice = np.array([0.4492, 0.3865, 0.4222, 0.5854, 0.5139, 0.4379, 0.4193, 0.4800, 0.4218])
+tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py;StableDiffusionImg2ImgPipelineFastTests;test_stable_diffusion_img2img_multiple_init_images;expected_slice = np.array([0.5144, 0.4447, 0.4735, 0.6676, 0.5526, 0.5454, 0.6450, 0.5149, 0.4689])
+tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py;StableDiffusionImg2ImgPipelineFastTests;test_stable_diffusion_img2img_negative_prompt;expected_slice = np.array([0.4065, 0.3784, 0.4050, 0.5267, 0.4781, 0.4253, 0.4204, 0.4693, 0.4365])
+tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py;StableDiffusionImg2ImgPipelineSlowTests;test_stable_diffusion_img2img_pipeline_multiple_of_8;expected_slice = np.array([0.9393, 0.9500, 0.9399, 0.9438, 0.9458, 0.9400, 0.9455, 0.9414, 0.9423])
+tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint.py;StableDiffusionInpaintPipelineFastTests;test_stable_diffusion_inpaint;expected_slice = np.array([0.4723, 0.5731, 0.3939, 0.5440, 0.5922, 0.4392, 0.5059, 0.4651, 0.4474])
+tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint_legacy.py;StableDiffusionInpaintLegacyPipelineFastTests;test_stable_diffusion_inpaint_legacy;expected_slice = np.array([0.4731, 0.5346, 0.4531, 0.6251, 0.5446, 0.4057, 0.5527, 0.5896, 0.5153])
+tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint_legacy.py;StableDiffusionInpaintLegacyPipelineFastTests;test_stable_diffusion_inpaint_legacy_negative_prompt;expected_slice = np.array([0.4765, 0.5339, 0.4541, 0.6241, 0.5439, 0.4056, 0.5504, 0.5892, 0.5150])
+tests/pipelines/stable_diffusion/test_stable_diffusion_instruction_pix2pix.py;StableDiffusionInstructPix2PixPipelineFastTests;test_stable_diffusion_pix2pix_default_case;expected_slice = np.array([0.7319, 0.3724, 0.4663, 0.6234, 0.5771, 0.5015, 0.4282, 0.5551, 0.4813])
+tests/pipelines/stable_diffusion/test_stable_diffusion_instruction_pix2pix.py;StableDiffusionInstructPix2PixPipelineFastTests;test_stable_diffusion_pix2pix_euler;expected_slice = np.array([0.7260, 0.3902, 0.4868, 0.5850, 0.5672, 0.5110, 0.3906, 0.5510, 0.4846])
+tests/pipelines/stable_diffusion/test_stable_diffusion_instruction_pix2pix.py;StableDiffusionInstructPix2PixPipelineFastTests;test_stable_diffusion_pix2pix_multiple_init_images;expected_slice = np.array([0.6061, 0.5713, 0.5099, 0.5979, 0.5805, 0.7204, 0.6792, 0.5540, 0.5607])
+tests/pipelines/stable_diffusion/test_stable_diffusion_instruction_pix2pix.py;StableDiffusionInstructPix2PixPipelineFastTests;test_stable_diffusion_pix2pix_negative_prompt;expected_slice = np.array([0.7323, 0.3688, 0.4611, 0.6255, 0.5746, 0.5017, 0.4330, 0.5553, 0.4827])
+tests/pipelines/stable_diffusion/test_stable_diffusion_instruction_pix2pix.py;StableDiffusionInstructPix2PixPipelineSlowTests;test_stable_diffusion_pix2pix_pipeline_multiple_of_8;expected_slice = np.array([0.2726, 0.2529, 0.2664, 0.2655, 0.2641, 0.2642, 0.2591, 0.2649, 0.2590])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion.py;StableDiffusion2PipelineFastTests;test_stable_diffusion_ddim;expected_slice = np.array([0.5650, 0.6022, 0.4805, 0.5270, 0.5585, 0.4644, 0.5160, 0.4963, 0.4793])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion.py;StableDiffusion2PipelineFastTests;test_stable_diffusion_k_euler;expected_slice = np.array([0.4717, 0.5376, 0.4568, 0.5226, 0.5734, 0.4798, 0.5467, 0.5074, 0.5044])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion.py;StableDiffusion2PipelineFastTests;test_stable_diffusion_k_euler_ancestral;expected_slice = np.array([0.4716, 0.5377, 0.4569, 0.5225, 0.5735, 0.4798, 0.5465, 0.5074, 0.5046])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion.py;StableDiffusion2PipelineFastTests;test_stable_diffusion_pndm;expected_slice = np.array([0.5099, 0.5677, 0.4671, 0.5128, 0.5697, 0.4676, 0.5278, 0.4964, 0.4946])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion_inpaint.py;StableDiffusion2InpaintPipelineFastTests;test_stable_diffusion_inpaint;expected_slice = np.array([0.4727, 0.5735, 0.3941, 0.5446, 0.5926, 0.4394, 0.5062, 0.4654, 0.4476])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion_upscale.py;StableDiffusionUpscalePipelineFastTests;test_stable_diffusion_upscale;expected_slice = np.array([0.2563, 0.3607, 0.4205, 0.4470, 0.4822, 0.4648, 0.5316, 0.5749, 0.5607])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion_v_pred.py;StableDiffusion2VPredictionPipelineFastTests;test_stable_diffusion_v_pred_ddim;expected_slice = np.array([0.6424, 0.6109, 0.4940, 0.5088, 0.4984, 0.4525, 0.5059, 0.5068, 0.4474])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion_v_pred.py;StableDiffusion2VPredictionPipelineFastTests;test_stable_diffusion_v_pred_k_euler;expected_slice = np.array([0.4616, 0.5184, 0.4887, 0.5111, 0.4839, 0.4800, 0.5119, 0.5263, 0.4776])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion_v_pred.py;StableDiffusion2VPredictionPipelineIntegrationTests;test_stable_diffusion_v_pred_default;expected_slice = np.array([0.1868, 0.1922, 0.1527, 0.1921, 0.1908, 0.1624, 0.1779, 0.1652, 0.1734])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion_v_pred.py;StableDiffusion2VPredictionPipelineIntegrationTests;test_stable_diffusion_v_pred_dpm;expected_slice = np.array([0.3303, 0.3184, 0.3291, 0.3300, 0.3256, 0.3113, 0.2965, 0.3134, 0.3192])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion_v_pred.py;StableDiffusion2VPredictionPipelineIntegrationTests;test_stable_diffusion_v_pred_euler;expected_slice = np.array([0.1781, 0.1695, 0.1661, 0.1705, 0.1588, 0.1699, 0.2005, 0.1589, 0.1677])
+tests/pipelines/stable_diffusion_2/test_stable_diffusion_v_pred.py;StableDiffusion2VPredictionPipelineIntegrationTests;test_stable_diffusion_v_pred_upcast_attention;expected_slice = np.array([0.4209, 0.4087, 0.4097, 0.4209, 0.3860, 0.4329, 0.4280, 0.4324, 0.4187])
+tests/pipelines/stable_diffusion_safe/test_safe_diffusion.py;SafeDiffusionPipelineFastTests;test_safe_diffusion_ddim;expected_slice = np.array([0.5644, 0.6018, 0.4799, 0.5267, 0.5585, 0.4641, 0.5160, 0.4964, 0.4792])
+tests/pipelines/stable_diffusion_safe/test_safe_diffusion.py;SafeDiffusionPipelineFastTests;test_stable_diffusion_pndm;expected_slice = np.array([0.5095, 0.5674, 0.4668, 0.5126, 0.5697, 0.4675, 0.5278, 0.4964, 0.4945])
+tests/pipelines/unclip/test_unclip.py;UnCLIPPipelineFastTests;test_unclip;expected_slice = np.array([0.9997, 0.9988, 0.0028, 0.9997, 0.9985, 0.9965, 0.0029, 0.9987, 0.0025])
+tests/pipelines/unclip/test_unclip_image_variation.py;UnCLIPImageVariationPipelineFastTests;test_unclip_image_variation_input_image;expected_slice = np.array([9.9974e-01, 2.6384e-04, 9.9974e-01, 9.9974e-01, 9.9703e-01, 2.4424e-03,
+        9.9974e-01, 9.9706e-01, 9.9707e-01])
+tests/pipelines/unclip/test_unclip_image_variation.py;UnCLIPImageVariationPipelineFastTests;test_unclip_image_variation_input_list_images;expected_slice = np.array([9.9974e-01, 9.9896e-01, 8.8045e-04, 2.1891e-03, 9.9604e-01, 1.8842e-03,
+        1.4433e-03, 2.6384e-04, 9.9330e-01])
+tests/pipelines/unclip/test_unclip_image_variation.py;UnCLIPImageVariationPipelineFastTests;test_unclip_image_variation_input_num_images_per_prompt;expected_slice = np.array([0.9980, 0.9997, 0.0023, 0.0029, 0.9997, 0.9985, 0.9997, 0.0010, 0.9995])
+tests/pipelines/unclip/test_unclip_image_variation.py;UnCLIPImageVariationPipelineFastTests;test_unclip_image_variation_input_tensor;expected_slice = np.array([9.9974e-01, 2.6384e-04, 9.9974e-01, 9.9974e-01, 9.9700e-01, 2.3511e-03,
+        9.9974e-01, 9.9698e-01, 9.9708e-01])
+tests/pipelines/versatile_diffusion/test_versatile_diffusion_dual_guided.py;VersatileDiffusionDualGuidedPipelineIntegrationTests;test_inference_dual_guided;expected_slice = np.array([0.0787, 0.0849, 0.0826, 0.0812, 0.0807, 0.0795, 0.0818, 0.0798, 0.0779])
+tests/pipelines/versatile_diffusion/test_versatile_diffusion_image_variation.py;VersatileDiffusionImageVariationPipelineIntegrationTests;test_inference_image_variations;expected_slice = np.array([0.0441, 0.0469, 0.0507, 0.0575, 0.0632, 0.0650, 0.0865, 0.0909, 0.0945])
+tests/pipelines/versatile_diffusion/test_versatile_diffusion_mega.py;VersatileDiffusionMegaPipelineIntegrationTests;test_inference_dual_guided_then_text_to_image;expected_slice = np.array([0.1448, 0.1619, 0.1741, 0.1086, 0.1147, 0.1128, 0.1199, 0.1165, 0.1001])
+tests/pipelines/versatile_diffusion/test_versatile_diffusion_text_to_image.py;VersatileDiffusionTextToImagePipelineIntegrationTests;test_inference_text2img;expected_slice = np.array([0.3493, 0.3757, 0.4093, 0.4495, 0.4233, 0.4102, 0.4507, 0.4756, 0.4787])
+tests/pipelines/vq_diffusion/test_vq_diffusion.py;VQDiffusionPipelineFastTests;test_vq_diffusion;expected_slice = np.array([0.6615, 0.6401, 0.5293, 0.5622, 0.5567, 0.4252, 0.5983, 0.5517, 0.4877])
+tests/pipelines/vq_diffusion/test_vq_diffusion.py;VQDiffusionPipelineFastTests;test_vq_diffusion_classifier_free_sampling;expected_slice = np.array([0.6648, 0.6531, 0.5303, 0.5891, 0.5727, 0.4439, 0.6305, 0.5565, 0.4913])